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ORAL HEALTH RELATED QUALITY OF LIFE OUTCOMES OF ORTHODONTICS IN CHILDREN
by
Shoroog Agou
A dissertation submitted in conformity with the requirements for the degree of Doctor of Philosophy
Graduate Department of Dentistry
University of Toronto © 2009 Shoroog Agou
ABSTRACT
Children Oral Health Related Quality of Life Outcomes in Orthodontics
Shoroog Agou Doctor of Philosophy
Graduate Department of Dentistry University of Toronto
2009
Contemporary conceptual models of health emphasize the importance of patient-
based outcomes and recognize the complexity involved in their assessment. Various
health conditions, personal, social, and environmental factors, are all thought to
contribute to individual’s quality of life. However, the impact of orthodontic treatment on
Oral Health-related Quality of Life (OH-QOL) outcomes in children has not yet been
systematically studied. Hence, this research was planned to assess the effect orthodontic
treatment has on pediatric OH-QOL outcomes. Further, the important moderational role
of children’s psychological assets on OH-QOL reports is explored.
Following completion of a preliminary study to confirm the psychometric
properties of the Child Perception Questionnaire (CPQl1-14), the current two-phase study
was undertaken. This consisted of a cross-sectional study examining the relationship
among Self-Esteem (SE), malocclusion, and OH-QOL, and a longitudinal study
examining the influence of orthodontics and children’s Psychological Wellbeing (PWB)
on OH-QOL reports.
This PhD dissertation is presented in the “Publishable Style”. The journals which
hold the copyrights for the papers published from this thesis have given permission for
the reproduction of the text and figures for this dissertation.
ii
The preliminary data confirmed that the CPQ11-14 is sensitive to change when
used with children receiving orthodontic treatment. Our cross-sectional findings indicated
that the impact of malocclusion on OH-QOL is substantial in children with low SE and
identified SE as a salient determinant of OH-QOL in children seeking orthodontic
treatment. Longitudinal data, on the other hand, detected significant improvement of OH-
QOL outcomes after orthodontic treatment. As postulated, these improvements were most
evident for the social and emotional domains of OH-QOL. However, covariate analysis
emphasized the important role psychological factors play in moderating OH-QOL
reports, as children with better PWB were more likely to report better OH-QOL
regardless of their orthodontic treatment status.
These results substantiate the validity of contemporary models of patient-based
outcomes linking biological, personal, social, and environmental factors. Researchers and
clinicians are encouraged to adopt this forward thinking approach when dealing with
children with oro-facial conditions. Further studies with larger samples and longer
follow-ups would be of value to expand on these findings.
iii
TABLE OF CONTENTS
Abstract.............................................................................................................................. ii Table of Contents ............................................................................................................. iv List of Tables .................................................................................................................... vi List of Figures.................................................................................................................. vii List of Appendices.......................................................................................................... viii Acknowledgments ............................................................................................................ ix List of Abbreviations ........................................................................................................ x Thesis Introduction ........................................................................................................... 1 Chapter 1: Epidemiology of Malocclusion ..................................................................... 7
Overview......................................................................................................................... 7 Prevalence of Malocclusion............................................................................................ 8 Orthodontic Treatment Needs......................................................................................... 9
Chapter 2: Conceptual Background ............................................................................. 11 Terminology: OH, QOL, H-QOL, and OH-QOL......................................................... 11 The Bio-Psychosocial Model of Outcome Assessment as Applied to Orthodontics.... 14 Determinants of OH-QOL in Children ......................................................................... 17
Clinical Determinants of OH-QOL in Children........................................................ 17 Dental caries...................................................................................................... 17 Gingival and periodontal disease. ..................................................................... 17 Malocclusion..................................................................................................... 18 Hypodontia........................................................................................................ 20 Cleft lip and/or palate........................................................................................ 20 Non-clinical Determinants of OH-QOL in Children ................................................ 21 Personal factors................................................................................................. 21 Social and environmental factors...................................................................... 24
Chapter 3: Quality of Life in Orthodontics .................................................................. 27 Overview....................................................................................................................... 27 Challenges in Psychosocial Assessment in Orthodontics............................................. 28
Who Should be the Informant? ................................................................................. 28 Are 11- to 14-year-old Children Capable of Providing Valid OH-QOL Reports?... 29 Is it Possible to Measure Change in OH-QOL in Children?..................................... 31
Assessment of Change in Children’s OH-QOL............................................................ 32 Direct Measures of Change....................................................................................... 32 Multiple Item Measures ............................................................................................ 34
How Has OH-QOL Been Assessed in Children Thus Far? .......................................... 36 Adult OH-QOL Measures......................................................................................... 36 Child OH-QOL Measures ......................................................................................... 37
The Child-OIDP................................................................................................ 39 The CPQ11–14.................................................................................................. 40
Does Orthodontic Treatment Improve OH-QOL?........................................................ 45 Does Orthodontic Treatment Improve Oral Symptoms? ...................................... 50 Does Orthodontic Treatment Improve Oral Function?......................................... 51 Does Orthodontic Treatment Improve Social Wellbeing?.................................... 51
iv
Does Orthodontic Treatment Improve Emotional and Psychological Wellbeing?52 Chapter 4: Self-Esteem and Psychological Wellbeing in Children ............................ 56
Self-Esteem................................................................................................................... 56 Conceptual Background........................................................................................ 56 Stability of SE....................................................................................................... 58
Psychological Wellbeing .............................................................................................. 61 Conceptual Background........................................................................................ 61 Stability of PWB................................................................................................... 62
Chapter 5: Statement of the Problem ........................................................................... 64 Chapter 6: Materials and Methods ............................................................................... 67
Ethical Considerations .................................................................................................. 67 Study Approval ..................................................................................................... 67 Confidentiality ...................................................................................................... 67 Informed Consent Process .................................................................................... 67
Methodology................................................................................................................. 68 Study Design......................................................................................................... 68 Sampling Design................................................................................................... 69 Selection Criteria .................................................................................................. 69 Sample Size........................................................................................................... 69 Recruitment........................................................................................................... 70 Data Collection Procedure .................................................................................... 70 Quality Control and Data Management ................................................................ 72 Budget ................................................................................................................... 72 Analytic Approach ................................................................................................ 73
Measures ....................................................................................................................... 73 The Child Perceptions Questionnaire (CPQ11-14)............................................... 73 The Child Health Questionnaire (CHQ-CF87) ..................................................... 74 The Dental Aesthetic Index (DAI)........................................................................ 75 Richmond Peer Assessment Rating (PAR)........................................................... 78
Chapter 7: Results........................................................................................................... 80 Manuscript I: Is the Child Oral Health Quality of Life Questionnaire Sensitive to Change in the Context of Orthodontic Treatment? A Brief Communication........... 81 Manuscript II: Impact of Self-Esteem on the Oral Health-related Quality of Life of Children with Malocclusion...................................................................................... 85 Manuscript III: Does Orthodontic Treatment Improve Children’s Oral Health Related Quality of Life?............................................................................................ 92 Manuscript IV: Does Psychological Well-being Influence Oral Health Related Quality of Life in Children Receiving Orthodontic Treatment?............................. 118
Chapter 8: Discussion and Conclusions ...................................................................... 148 References ...................................................................................................................... 158
v
LIST OF TABLES
Table 1: Orthodontic Studies evaluating personal OH-QOL determinants ..................... 26 Table 2: Development and age adaptations of the Child-OIDP and the CPQ11-14........ 39 Table 3: Summary of studies validating the CPQ11-14 .................................................. 44 Table 4: Studies examining OH-QOL, malocclusion, and/or orthodontics..................... 47 Table 5: Studies evaluating the effect of orthodontics on children’s SE/self concept..... 55 Tables in manuscript I Table 1: The Child OH-QOL Questionnaire scores and clinical measures before and after orthodontics………………………………………………………………………………83 Table 2: Children responses to global questions about appearance, occlusion, oral health, and life overall…………………………………………………………………………... 84 Tables in manuscript II Table 1: Summary statistics for the study variables……………………………………. 88 Table 2: Correlation between CPQ11-14 scores and SE per malocclusion category…... 88 Table 3: Correlation CPQ11-14 scores and DAI per SE category…………………….... 88 Table 4: Amount of variance explained for overall and subscale CPQ11-14 scores…… 89 Tables in manuscript III Table 1: Main study variables at T1 and T2 for treatment and control groups………... 113 Table 2: GTR responses for treatment and control groups……………………………. 114 Table 3: Mean CPQ11-14 change scores per GTR category for the overall sample….. 115 Tables in manuscript IV Table 1: The main study variables and their interpretation…...…...…...…...…...…......143 Table 2: Main study variables at T1 and T2 for treatment and control groups………... 144 Table 3: ANCOVA models showing covariates contributing to OH-QOL ...………… 145 Table 4: Observed and adjusted mean follow-up CPQ11-14, EWB, and SWB scores.. 146 Table 5: Mean baseline and follow-up CPQ11-14 based on PWB status……………... 147
vi
LIST OF FIGURES
Figure 1: The main components of OH-QOL.................................................................. 13 Figure 2: The Wilson-Cleary model of patient-centered outcomes................................. 16 Figure 3: Diagrammatic representation of the CPQ11-14 developmental process ......... 41 Figure 4: Distribution of Standard DAI Scores and their Cumulative Percentages ........ 77
Figures in manuscript II Figure 1: CPQ11-14 scores of high and low SE children per malocclusion group……..89 Figures in manuscript III Figure 1: Percentage of subjects reporting satisfaction with dental occlusion for treatment and control groups at T1 and T2………………………………………..……116 Figure 2: Percentage of subjects reporting satisfaction with dental aesthetics for treatment and control groups at T1 and T2……………………………………………..117
vii
LIST OF APPENDICES
Appendix A Study flowchart
Appendix B Patient information letter, consent form, assent form, and cover letter
Appendix C The child perception questionnaire for 11- to 14-year-old
Appendix D Global ratings (treatment group)
Appendix E Global ratings (control group)
Appendix F The self-esteem subscale of the child health questionnaire
Appendix G The psychological wellbeing subscale of the child health questionnaire
Appendix H The dental aesthetic index form
Appendix I The peer assessment rating form
viii
ACKNOWLEDGMENTS
I would like to acknowledge my supervisor, Prof. David Locker, for providing me
with the great opportunity to publish and present the findings from this study at local,
national, and international levels. I express my sincere appreciation to Prof. David
Streiner for his guidance and advice. His insights were invaluable in designing and
interpreting the findings from this study. I am sure they will remain so for a lifetime. I am
also very thankful to Dr. Bryan Tompson for his kind assistance in implementing the
project.
My gratitude is extended to Ms. Lori Mockler for her continuous assistance and
resourcefulness. I would also like to give a special thanks to Dr. Preeti Parkash, Dr.
Vanessa Muirhead, Dr. Bruce Tasios, Dr. Sunjay Suri, Ms. Didem Sarikaya, Ms. Arwa
Aulaqi, Ms. Karen Propper, Ms. Lucy Ferraro, the late Elise Sunga, as well as the
orthodontic residents for all their help, encouragement, and friendship. I am also very
grateful to Dr. Dena Taylor for her editorial help and constructive advice.
I can not forget to thank the Ministry of Higher Education, Kingdom of Saudi
Arabia, for funding my education. This research was supported by the Community Dental
Health Services Research Unit, Faculty of Dentistry, University of Toronto and the
Harron Scholarship, Faculty of Dentistry, University of Toronto.
Above all, I thank God, the most gracious, the most merciful, for blessing me with
such wonderful parents. I could not have done this without their constant support and
countless prayers.
ix
x
LIST OF ABBREVIATIONS
Child-OIDP Child-Oral Impact on Daily Performance CHQ-CF87 The Child Health Questionnaire CPQ11-4 The Child Perception Questionnaire CS-OIDP Condition Specific-Child Oral Impact on Daily Performance DAI The Dental Aesthetic Index EWB Emotional Wellbeing FL Functional Limitation GTR Global Transition Rating H-QOL Health-related Quality of Life ICC Intra-Class Correlation Coefficient ICSII-OHRQOL The Second International Collaborative Study -Oral Health-Related
Quality of Life Questionnaire IOTN The Index of Orthodontic Treatment Need IOTN.AC Aesthetic Component of the Index of Orthodontic Treatment Need OASIS The Oral Aesthetic Subjective Impact Scale OH Oral Health OHIP Oral Health Impact Profile OH-QOL Oral Health-related Quality of Life OIDP Oral Impact on Daily Performance OQOL Orthognathic Quality of Life Questionnaire OS Oral Symptoms PAR Peer Assessment Rating PIDAQ The Psychosocial Impact of Dental Aesthetics Questionnaire PPQ Parent/caregiver Perception Questionnaire PWB Psychological Wellbeing QOL Quality of Life SE Self-Esteem SWB Social Wellbeing WHO The World Health Organization
THESIS INTRODUCTION
The increased emphasis on inclusion of patient-centered outcome measures in
clinical research studies by agencies such as the World Health Organization (WHO) is
one of the many factors that has led to an increase in Quality of Life (QOL) research over
the last 40 years. These advances were paralleled by developments of holistic conceptual
models of patient outcomes, which integrate both biological and psychological aspects of
health (1,2).
The field of orthodontics has, however, lagged behind. Whilst clinical outcomes
of orthodontic treatment are well documented, relatively little is known about the
psychological aspects. This is surprising considering that improvement in smile aesthetics
and subsequent enhancement of psychosocial wellbeing is the most frequently cited
reason for undergoing orthodontic treatment (3,4). For years, orthodontic clinicians have
assumed that orthodontic anomalies can negatively impact the lives of people and that
orthodontic treatment can enhance the lives and overall wellbeing of those people.
However, research has not yet provided evidence to support these anecdotal claims,
which lead some to speculate the existence of an element of “supplier-induced demand”
(5).
The relatively few empirical attempts to consider the patient’s view in evaluating
treatment results found no difference in children’s Self-Esteem (SE) or Psychological
Wellbeing (PWB). This could be partly attributed to two main reasons. First, earlier
empirical work was not paralleled by conceptual work clarifying the relationships
between relevant psychosocial constructs. Conceptual frameworks are essential to
determine what to measure and how it should be measured. Consequently, earlier studies
failed to measure what orthodontists perceived as an obvious benefit of orthodontic
therapy (6-8).
Second, a critical analysis of the methodology employed in these studies reveals
that, for the most part, orthodontic outcome studies designed and conducted prior to the
new millennium, used SE as a primary outcome. However, results from child psychology
studies question the validity of this measurement approach. For instance, in an extensive
report on SE, Emler noted that appearance, in general, contributes only modestly to SE
(9). Therefore, SE is not an appropriate end-point assessment tool when it comes to
orthodontics in children. In fact, Cunningham identified the method of assessment of
psychological health as an important reason for the conflicting evidence regarding the
psychosocial benefits of orthodontics (10).
Currently, new measures have been developed to allow us to focus on outcomes
that are more relevant to the child population; notably, Oral Health-related Quality of
Life outcomes (OH-QOL) measures. OH-QOL is defined as an individual's assessment of
how functional factors, psychological factors, social factors, and the experience of
pain/discomfort in relation to oro-facial concerns affect his or her wellbeing (11). Thus
defined, OH-QOL instruments are potentially promising research tools in orthodontics
since improvement of QOL is a frequently stated reason for undertaking orthodontic
treatment.
Results of OH-QOL studies could have significant implications for the
orthodontic community. With the increased demands to justify the needs for and
outcomes of treatment, an appropriately designed study could provide useful evidence for
2
parents, clinicians, public health agencies, and insurance companies to support the
claimed benefits of orthodontic treatment.
Several cross-sectional studies have, indeed, supported the widely shared belief
that an association exists between OH-QOL and orthodontics. However, most studies
pointed out that the association between OH-QOL and normative measures of
malocclusion are rather weak. Moreover, the longitudinal effects of orthodontic treatment
on OH-QOL have not been determined. Hence, the intense debate about the relationships
among malocclusions, orthodontic treatment, and OH-QOL remain unresolved. Further,
the role of psychological factors which are deemed to be an important predictor of quality
of life was often overlooked. Thus, longitudinal controlled evaluations are needed to
assess causality and to account for relevant psychological constructs moderating OH-
QOL reports in the population of children seeking orthodontic treatment.
As mentioned earlier, in addition to being either inadequately controlled or
underpowered, earlier studies also lacked the theoretical grounding needed to accurately
interpret their findings. Since this dissertation aims to tackle the above research
weaknesses, a theoretical framework of patient-based outcomes, linking both clinical
variables and characteristics of the individual to OH-QOL and general wellbeing (1), was
adopted to help in answering the following questions: 1) Does orthodontics improve OH-
QOL in children receiving treatment compared to those waiting for treatment? and 2) Do
psychological factors influence OH-QOL outcomes in those children?.
This PhD dissertation is presented in the “Publishable Style”. The journals which
hold the copyrights for the papers published from this thesis have given permission for
the reproduction of the text and figures for this dissertation.
3
In Chapter 1, the epidemiology of malocclusion in children is reviewed. The large
discrepancy between subjective and objective assessments of orthodontic treatment needs
discussed in this chapter emphasizes the importance of supplementing clinical indicator
with subjective measures whenever possible.
Chapter 2 provides operational definitions related to oral health and quality of life
and introduces a bio-psychosocial model of patient-based health outcome measures.
Since this model of disease and its consequences links the physical and the psychosocial
wellbeing of the individual, it is used as a framework to discuss relevant clinical and non-
clinical determinants of OH-QOL outcomes in children.
Chapter 3 provides an overview of the current status of patient-centered outcome
research in orthodontics. Challenges and current developments are discussed in depth.
Special attention is given to the assessment of change in children. This chapter also
includes a summary of OH-QOL measures published prior to 2004. Their advantages and
disadvantages are emphasized as they were considered in planning the study. In addition,
a review of the evidence concerning the impact of orthodontic treatment on children's
health status and wellbeing is provided. This review indicates that OH-QOL has not been
studied in a systematic manner in relation to orthodontics. Further, earlier psychosocial
studies in orthodontics are conceptually and methodologically examined.
Since the thesis reports on the effect of SE and PWB on pediatric OH-QOL
outcome research, Chapter 4 provides a brief review of these constructs. The stability of
SE and PWB is also discussed as portrayed in social and developmental psychology
literature.
4
The knowledge gaps identified in the literature review are summarized in Chapter
5. Consequently, this chapter provides a rationale for undertaking this study and the
objectives of the dissertation. Chapter 6 provides a description of the specific methods
used. The relative merits of the measures employed are outlined as a basis for their
selection.
Chapter 7 presents the results of this research. These consist of four manuscripts
that address the main objectives of this dissertation. Manuscript I, “Is the child oral health
quality of life questionnaire sensitive to change in the context of orthodontic treatment?”,
describes the longitudinal psychometric properties of the Child Perception Questionnaire
(CPQ11-14). This manuscript has been published in the Journal of Public Health
Dentistry 2008 Fall; 68(4):246-8. Manuscript II, “Impact of self-esteem on the oral
health-related quality of life of children with malocclusion” covers the main baseline
findings. It has been published in the American Journal of Orthodontics and Dentofacial
Orthopedics 2008; 134:484-9. Manuscripts III and IV present the longitudinal findings of
this project. Manuscript III, “Does orthodontic treatment improve children’s oral health-
related quality of life?”, reports on OH-QOL gains following orthodontic treatment. It has
been submitted to Community Dentistry and Oral Epidemiology, and is currently under
revision. Manuscript IV, “Does psychological wellbeing influence oral health-related
quality of life in children receiving orthodontic treatment?”, focuses on the role of PWB
in moderating children’s response to OH-QOL questionnaires. It also examines the
analytic implications of such results. This manuscript has been accepted for publication
in the American Journal of Orthodontics and Dentofacial Orthopedics.
5
The research findings and their implications are summarized and discussed in
Chapter 8. Here are also presented the limitations of the study and suggestions for future
research.
6
CHAPTER 1: EPIDEMIOLOGY OF MALOCCLUSION
Overview
Malocclusion exists on a continuum with no clear or simple division as to when
treatment becomes desirable. Therefore, orthodontic treatment is different from most
other medical interventions in that it does not cure or treat a condition; rather it aims to
correct variations from an arbitrary norm (12).
Malocclusions can occur due to congenital and/or acquired aberrations in the size
or the position of teeth and/or the supporting dentoalveolar structures. Classifications and
indices of malocclusion are either qualitative (e.g., Angle's classification and British
Standards Institute classification) or quantitative (e.g., Dental Aesthetic Index – DAI (13)
and Index of Orthodontic Treatment Need – IOTN (14) ).
Qualitative assessments are not usually suitable for use in epidemiological
research. Therefore, prevalence figures for malocclusion are usually based on the
normative need for orthodontic treatment. Quantitative assessments measure the clinical
severity or complexity of the orthodontic condition. For instance, the IOTN establishes
the prevalence of selected malocclusion traits such as dental crowding, maxillary median
diastema (space between the upper central incisors), crossbite (facial or lingual
displacement of posterior teeth), overjet (excessive protrusion of the upper incisors), and
overbite (vertical overlap of the incisors).
7
Prevalence of Malocclusion
Approximately one-third of US and UK children have a clear normative need for
orthodontic therapy (15-17). For instance, the U.K. Child Dental Health Survey in 1993
estimated that approximately 66% of 12-year-olds required some form of orthodontic
treatment, and 33% required complex orthodontic treatment (14). Further, the 1994-1995
U.K. National Health Services Dental Survey found a definitive treatment need, in 25.6%
of l4-year-olds sampled (18).
Similarly, the 1963-1965 and the 1969-1970 U.S. National Health and Nutrition
Examination Survey indicated that approximately 14% of children aged 6-11 years and
30% of children aged 12-17 years had severe malocclusion (17). A later survey in 1988-
1991 confirmed these findings (19).
The statistics are not that different for French Canadian children (20). Using the
Grainger's Orthodontic Treatment Priority Index, 32% of the Quebec children surveyed
were Angle's class II; 18% had an overjet of 5 mm and over; and 50% had one or more
teeth in minor or major displacement.
8
Orthodontic Treatment Needs
Traditionally, orthodontic treatment needs and outcomes were assessed using
normative measures of malocclusion. For instance, the IOTN is heavily used in the UK to
prioritize treatment needs and guide the allocation of resources to support government
programs. The DAI is another example of an index used world wide to screen and
identify persons eligible for subsidized or free care on the basis of their objective
aesthetic needs. The proposed argument is that these instruments can serve as neutral,
unbiased instruments to discuss treatment need with patients and as guides to allocate
financial resources for orthodontic care. Although these clinical indicators are still of
importance, they require supplementation with OH-QOL measures for two main reasons:
first, the OH-QOL outcome does not necessarily correlate with objective findings, and
patients’ ratings of outcome may not correlate with those of clinicians (21).
The studies conducted in Thailand to estimate orthodontic treatment need using
both OH-QOL measures and normative indices demonstrate these concepts clearly. The
results detected a marked difference between the standard normative and the sociodental
orthodontic needs assessment approach, with the latter approach showing a 60% lower
assessment of dental health care needs in 11- to 12-year-old Thai children (22,23). In
contrast, the subjective demands for orthodontic treatment in Europe and North America
exceed professionally assessed needs (24,25). The impact of idealized media images,
especially where mass media is omnipresent, can significantly influence adolescents’
perception of their malocclusion, and hence, demands for orthodontic treatment (26). In
fact, it has been suggested that social and cultural expectations regarding dental
appearance have increased in the United States over the years (27). Clearly, professional
9
assessment of treatment needs does not necessarily reflect the impact of malocclusion on
the daily life of children. Therefore, OH-QOL measures should be used in combination
with normative indices in order to cover different dimensions of oral health.
10
CHAPTER 2: CONCEPTUAL BACKGROUND
Terminology: OH, QOL, H-QOL, and OH-QOL
In 1946, the World Health Organization broadened its definition of health to
include physical, emotional, and social wellbeing (28). Subsequently, the Department of
Health in England defined Oral Health (OH) as “the standard of oral and related tissue
health that enables individuals to eat, speak, and socialize without active disease,
discomfort, or embarrassment, and that contributes to general wellbeing” (29).
This broadened concept of health meant that biological measures of disease
needed to be supplemented with subjective health measures evaluating the individual's
perspective. Consequently, a plethora of terms and measures have appeared over the past
40 years. The term QOL was first used by Pigou in his book The Economics of Welfare
(30) as a general description of a person’s sense of wellbeing. However, current
definitions of QOL involve a combination of objectively and subjectively indicated
wellbeing in multiple domains of life considered salient in one’s culture and time, while
adhering to universal standards of human rights (31,32).
Quality of life first appeared in the medical literature in a 1966 study of
hemodialysis patients (33). Currently, Health-related quality of life (H-QOL) refers to the
physical, psychological, and social domains of health, seen as distinct areas that are
influenced by a person's experiences, beliefs, expectations, and perceptions (34). H-QOL
measures were designed to complement clinical indicators in population health needs
assessment, individual health care, evaluation of health interventions, and policy
programs. In essence, the H-QOL notion was developed to humanize health care (35).
11
Factors like chronic illness, new technology, cost containment, and interest in medical
outcomes were major derivers of this H-QOL paradigm (35).
Not surprisingly, being a relatively young endeavor, there are many variations in
the operational approach to OH-QOL. OH-QOL was initially defined by Kressin as “the
impact of oral conditions on daily functioning” (36). A few years later, in a paper
evaluating OH-QOL outcomes in elderly people, Locker et al. redefined OH-QOL as “the
symptoms and functional and psychosocial impacts that emanate from oral diseases and
disorders” (37). Then, Inglehart defined OH-QOL more specifically as “the absence of
negative impacts of oral conditions on social life and a positive sense of dentofacial self-
confidence” (11). In this definition, Inglehart embraced the central dimensions of OH-
QOL proposed by Gift and Atchison (38). These suggest that OH-QOL be defined as a
person's assessment of how the following factors affect his or her wellbeing: (a)
functional factors; (b) psychological factors; (c) social factors; and (d) the experience of
pain/discomfort. When these considerations center on oro-facial concerns, OH-QOL is
assessed (Figure 1).
In theory, H-QOL measures combine information about health status and the
value attached to that status by the individual (39,39-41). Since health conditions may
affect the physical, psychological, and social functioning of the individual, these impacts
may compromise the individual's QOL. However, the extent to which these experiences
compromise the individual's QOL as assessed by H-QOL measures is still not clear.
Similarly, there seems to be an implicit assumption that since OH-QOL measures
address aspects of daily life that are compromised by oral disorders, they must reflect
how these disorders affect the QOL (42). Nonetheless, there remains a conceptual
12
ambiguity on how OH-QOL measures address the broader concept of QOL. QOL and
disease impact are theoretically distinct concepts, the former clearly being more general.
As such, they need to be labeled and measured separately from one another (31).
Therefore, while I chose to use Inglehart’s as a working definition of OH-QOL for the
purposes of this dissertation, it is important to note that available OH-QOL measures
document the frequency of the functional and psychosocial impacts resulting from oral
disorders, but they do not necessarily relate the meaning and significance of these
impacts to QOL (43).
Figure 1: The main components of OH-QOL
Reproduced from Oral health-related quality of life (2002), Page 3 (11)
13
The Bio-Psychosocial Model of Outcome Assessment as Applied to Orthodontics
Since the post-World War II definition of health was introduced, the assessment
of therapeutic interventions continued to move away from the traditional bio-medical
model of health, which views disease strictly as pathological processes affecting the
body, towards a more holistic bio-psychosocial model of health, which views disease in
terms of its impact on an individual's physical functioning and psychosocial wellbeing
(44). The central concept in this salutogenic movement has to do with establishing and
maintaining a harmonious balance among the body, mind, and spirit, as well as with the
individuals’ social context and their environment. According to salutogenesis,
maintaining this balance results in a good quality of life, despite unfavorable health
conditions. Similarly, disturbance of such a balance can lead to poor quality of life (35).
One conceptual model that reflects this new paradigm of health has been
described by Wilson and Cleary (1). This model, depicted in Figure 2, encompasses both
biological and physiological variables at one end, and overall quality of life at the other
end. In this model, symptoms of disease/disorder, functional, psychological, and social
experiences related to that disease/disorder serve as a link between the two ends. More
importantly, this model identifies the moderating role that personal and environmental
characteristics have on this causal sequence. Thus specified, the Wilson-Cleary model
makes explicit causal relationships between disease, health status, and H-QOL, while still
acknowledging the holistic nature of QOL.
There is considerable evidence of the usefulness of this model in outcome
assessment in dentistry (45,46). However, despite this evidence, the field of orthodontics
has lagged behind in utilizing contemporary models of patient-based outcomes. A quick
14
15
survey of the literature reveals that outcome research in orthodontics focused primarily
on normative assessment. Dental indices like the Peer Assessment Rating (PAR) and
cephalometric radiographic analyses have been extensively used to evaluate the quality of
orthodontic care and guide decisions on important issues like treatment alternatives and
treatment timing.
Overall, little emphasis was given to OH-QOL outcomes in orthodontics. Only
recently have a number of leading scientists in the field of orthodontic outcome research
emphasized that the measurement of patient-based outcomes is central to the
development of orthodontic oral health services (12,47-49). This research direction was,
however, limited by the lack of instruments specifically designed to measure oral health
impacts. As OH-QOL instruments became available, increasingly more studies were
designed to include patient-reported outcomes of treatment.
Using the Wilson-Cleary model as a framework, the next section examines
contemporary orthodontic literature to determine how both clinical and non-clinical
factors influence OH-QOL in children. The literature is critically examined to highlight
relevant conceptual gaps. However, as an overarching conclusion, studies have been, so
far, focused on the linear pathway of the model (highlighted in gray in Figure 2). Very
little consideration has been given to the moderating pathways created by individual and
environmental factors (highlighted in white in Figure 2).
Figure 2: The Wilson-Cleary model of patient-centered outcomes
Reproduced from Wilson and Cleary (1995) (1)
Determinants of OH-QOL in Children
Clinical Determinants of OH-QOL in Children
Poor OH-QOL has been linked to several oro-facial conditions. In order of
prevalence, dental caries, gingival and periodontal problems, malocclusion, hypodontia,
and developmental malformations such as cleft lip and/or palate have all been studied in
relation to OH-QOL in children. Other factors that contribute to the incidence of impacts
in pre-adolescent children include sensitive teeth and oral ulcers. However, these impacts
are usually associated with low levels of severity.
Dental caries. Dental caries is the most common chronic disease of childhood.
The WHO has estimated that 60–90% of all school-age children are affected (50).
However, despite the high prevalence of dental caries, it does not seem to affect Arabian
children’s OH-QOL in its early stages (51). In contrast, others have shown the exact
opposite; despite low levels of dental caries in Uganda, children experienced appreciable
negative impacts on OH-QOL (52). These contradictory findings speak to the presence of
other factors that influence the relationship between dental caries and OH-QOL reports,
perhaps culture in this case.
Gingival and periodontal disease. Gingival problems are among the most
important oral conditions affecting children's OH-QOL (22). More than 20% of Thai
children surveyed reported that bleeding and swollen gums had impacts on their daily
life. This could be related to natural processes like shedding primary teeth or space due to
a non-erupted permanent tooth.
Malocclusion. While some researchers may not deem the effects as handicapping
(53), the literature appears to support the notion that malocclusion does affect a person’s
OH-QOL. Several studies reported on the impacts of malocclusion in children (54-58).
For instance, the prevalence of oral impacts for children with definite need for
orthodontic treatment was twice that for children with no or slight need for orthodontic
treatment (54). Similarly, Australian children who had less acceptable occlusal traits
reported poorer OH-QOL (59).
A study of 414 college students supports these findings; individuals with incisor
crowding and anterior maxillary irregularity greater than two mm were at least twice as
likely to experience an impact on “smiling, laughing, and showing teeth without
embarrassment.” Further, individuals with overjet greater than five mm were almost four
times more likely to experience impacts on their emotional state (60). In general, the
impacts of self-perceived malocclusion primarily affected psychological and social
everyday activities such as smiling, emotion, and social contact (54,56).
Altogether, there is definitely a trend for children with clinically identifiable
malocclusions to report poorer OH-QOL compared to children with ideal occlusion. Of
seven articles identified in a recent systematic review of malocclusion and children OH-
QOL, six (22,52,56,58,61,62) found statistical associations and one did not (63).
However, the associations between normative measures and OH-QOL scores are rather
weak.
In fact, a study of British children with a need for treatment based on the
examiner-assessed Aesthetic Component of the Index of Orthodontic Treatment Need
(IOTN.AC) found that children with IOTN.AC of 6 or greater (indicating worse
18
malocclusion) did not have significantly higher CPQ11-14 scores (61). The authors noted
that the association between OH-QOL and IOTN.AC was low and that they are two
different attributes. Another British study of the same population used a different OH-
QOL measure, the Child-Oral Impact on Daily Performance (Child-OIDP), and yet,
found similar results (54). Although the prevalence of oral impacts increased from 16.8%
for adolescents with no or slight need for orthodontic treatment to 31.7% for those with
definite need for orthodontic treatment, there were inconsistencies between self-reports of
OH-QOL and normative assessment of treatment needs. Interestingly, the same research
group found that the OH-QOL scores were poorer when increased normative needs were
associated with perceived treatment needs (the child felt their teeth needed straightening).
Similarly, Mandall et al. found that the aesthetic impacts of malocclusion were not
different between treated and untreated children; however, the untreated children who
wished for orthodontic treatment perceived worse aesthetic impacts (64). Clearly,
awareness of occlusal traits and satisfaction with one’s own occlusal condition varies
among different individuals (65,66). It is also plausible that the desire for orthodontic
treatment may differ according to the patient’s psychological status.
These weak associations can be explained by the fact that clinical indices, such as
the IOTN (15), can emphasize malocclusions that may not be important to OH-QOL,
such as posterior crossbites (63,67). These inconsistencies also highlight the
shortcomings of using only clinical indices to estimate orthodontic treatment
needs/outcomes and support the contemporary thinking on the consequences of disease,
in that health and OH-QOL are not merely determined by the nature of the disease but
also by other contextual factors.
19
Hypodontia. Until recently, only one study has evaluated the impacts of
hypodontia (the congenital absence of teeth) on OH-QOL (68). All subjects studied
reported considerable impact on OH-QOL. The majority experienced oral symptoms,
functional limitations, as well as impacts on social and emotional wellbeing. The results
confirm that chronic oral conditions can influence an individual's wellbeing by impacting
on everyday physical, psychological, and social functioning (45). In this study, the
number of missing permanent teeth was moderately correlated with OH-QOL. However,
when retained primary teeth were taken into account, the number of missing teeth was
highly correlated with OH-QOL, suggesting the importance of retaining primary teeth in
children and adolescents with severe hypodontia. This study, however, did not examine
the effect of other, potentially more important, variables such as the location of missing
teeth. For instance, one could hypothesize that missing visible teeth would have more of
an impact than missing teeth that could not be seen. Therefore, further studies are
warranted to examine these findings.
Cleft lip and/or palate. Cleft lip and/or palate cases are more clinically severe and
can affect facial appearance throughout life. Therefore, it has been assumed that they will
have greater impacts on OH-QOL. However, Locker et al. found that the overall OH-
QOL in those children was not different from children with dental decay (69). Actually,
children with oro-facial conditions rated their OH better than the ones with dental decay.
Although they may encounter more challenges in daily life such as mouth breathing,
speech problems, missing school, being teased, and being asked questions about their
condition, it seems that the majority of these children are well adjusted and able to cope
with the adversities engendered by their condition. In fact, research indicates that many
20
persons with disabilities do experience good quality of life against all odds. This
discordance between patients’ perception of health and well-being on one hand, and their
objective health status on the other hand, is known as the “Disability Paradox” (35).
As Locker and Slade state, health and disease belong to different dimensions of
human experience; so, paradoxes occur when disease is assumed by researchers to cause
an impact (70). Such paradoxes highlight the importance of personal experience in
defining the self, one’s view of the world, social context, and social relationships (35).
Indeed, all contemporary models of disease and its consequences, such as that of Wilson
and Cleary, indicate that the relationships between biological variables and H-QOL
outcomes are not direct, but moderated by a variety of personal, social, and
environmental variables (1).
Non-clinical Determinants of OH-QOL in Children
Personal factors. According to the Wilson-Cleary model, personal, social, and
environmental factors may account for the weak relationships observed between OH-
QOL scores and clinical data. For instance, factors like age and gender can influence
QOL. It has been reported that females tend to be more concerned with dental aesthetics
than males (71-73). Nonetheless, this gender effect is usually most apparent during young
adulthood (18- to 29-year-old) (74), and therefore may not be relevant to the current
investigation. The effect of age on OH-QOL, on the other hand, has not been adequately
investigated. One study concluded that adolescents, despite having the most severe
malocclusions, were less affected by their occlusal status, compared to young adults (74).
21
As alluded to earlier, the moderational role of personality characteristics can be
inferred from such studies highlighting the inconsistencies between normative and
subjective outcomes. To recap, several studies indicated that the demand for orthodontic
treatment does not seem to be directly related to measurable malocclusions (64,75,76).
There are considerable variations in an individual’s ability to adapt to oro-facial
abnormalities, while some remain quite unaffected, others have significant difficulties
that can affect their QOL (77).
A recent systematic review of the relationship between clinical OH status and
OH-QOL in children supports this moderational role of personal characteristics (67). The
review further suggests that the weak relationships between children's oral conditions and
OH-QOL, can be explained by inter- and intra- personal variations (78,79).
Although personality characteristics, such as negative affectivity, were found to
influence OH-QOL assessment in older men (80), orthognathic patients (81), and college
students (82), the direct role of personal characteristics in moderating orthodontic
treatment outcomes in children has not been well investigated. In fact, only a few studies
make reference to personality attributes in relation to the outcomes of conventional
orthodontics. For instance, a study of stereotypes of children with malocclusion
concluded that the impact of social stereotypes on psychological wellbeing is likely to be
modified by social interactions (83).
It was not until recently that the effect of personal traits on the perception of facial
attractiveness was directly examined (Table 1). In a study of teenage Germans, a
significant interaction effect was identified, which showed that the impact of dental
aesthetics on social appearance concern was stronger in respondents with high private
22
and public self-consciousness than in low scoring subjects. This study suggests that
minor differences in dental aesthetics have a significant effect on perceived OH-QOL in
subjects with high self-consciousness (71). However, it must be acknowledged that these
findings relate to young adults and therefore cannot be extrapolated to adolescents; yet, it
certainly drives further research of adolescent orthodontic patients. Nonetheless, it is
interesting to note that three out of the four studies listed in Table 1 point to SE as a
potential moderator of the aesthetic impact of malocclusion.
Similarly, a comprehensive long-term study of British children identified baseline
SE as an important moderator of QOL (8). When SE at baseline was controlled for,
orthodontic treatment had little positive impact on psychological health and QOL in
adulthood. In fact, this same research group drew similar psychosocial conclusions from
a study investigating the effects of malocclusion in the early 1980s: “the individual’s
adjustment to his own imperfections in dental alignment is variable and there is no
evidence that children with visible irregularities will in general be emotionally
handicapped” (53) p.36. Some individuals are concerned about very minor malocclusions
and demand orthodontic intervention, whereas others accept major deviations from the
norm quite happily.
Since the desire for orthodontic treatment may differ according to the patient’s
psychological status, the influence of individual traits, such as SE and PWB, on OH-QOL
cannot be ignored. Longitudinal studies assessing this moderational role of psychological
traits on reported OH-QOL are necessary to better understand and interpret OH-QOL
measures in children.
23
Social and environmental factors. It has been also suggested that culture,
education, ethnicity, and material deprivation can influence the extent of the impact of
disease (63,68,79,84). Variables such as general health status, household income, and life
stress have been shown to explain as much variance in the impact of oral disorders on
adults as clinical indicators (70). Similar effects were reported for Canadian
schoolchildren (62); children from low-income households had higher impacts on QOL
than children from high-income households. Household income remained a predictor of
OH-QOL scores after controlling for the potential confounding effects of oral diseases
and disorders such as dental caries, dental injury, and malocclusion. Notably, the authors
concluded that these disparities can be explained by differences in psychological assets
and psychosocial resources, which reemphasize the importance of personal factors in
moderating OH-QOL.
Further, evidence demonstrates that culture can influence a person’s definition of
health, appraisals, and behavioral expressions (11). The effect of culture on OH-QOL
reports can be extrapolated from a recent investigation of OH-QOL impacts experienced
by Tanzanian schoolchildren. Despite the high prevalence of malocclusion in this sample,
psychosocial impacts and dissatisfaction with appearance or function were not frequent,
compared to similar studies conducted in Canada and New Zealand (85). It is plausible
that individuals may evaluate aesthetics and/or function differently, depending on their
cultural and/ or social background (86). That being said, a recent master’s thesis
concluded that having different value systems does not necessarily imply a difference in
perceived OH-QOL (74).
24
25
These conflicting results highlight the complexity of studying social factors. In
fact, when examining the causal pathways between social determinants and health,
Newton and Bower advocate the use of a theoretical framework that reflects the complex
relationship among material, psychosocial, and behavioral pathways (84). The evaluation
of social and cultural factors, however, requires the use of heterogeneous samples with
adequate variations in factors like cultural norms, cultural assimilation, education, and
household income. Such an evaluation is not usually possible in clinical studies of
orthodontics, where children typically belong to the same socio-economic class.
Therefore, orthodontic researchers need to collaborate with social theorists in large-scale
projects (84).
Table 1: Orthodontic studies evaluating personal determinants of OH-QOL
Author (Year)
Location Measure SD N Main findings
Mandall (2001)
UK OASIS &
Piers Harris SE CS 439
High child SE appears to be related to self-perceived malocclusion and its psycho-social impact (87).
Onyeaso (2003)
Nigeria Questionnaire on orthodontic
concern & the Global Negative Self-Evaluation Scale
CS 520 Significant positive correlation existed between SE
and orthodontic concern in a group of Nigerian adolescents (88).
Klages (2004)
Germany
“Dental self-confidence scale”, “social appearance concern” &
“appearance disapproval”
CS 148
Private self-consciousness was related to social appearance concern, while public self-consciousness was associated with both social appearance concern
and appearance disapproval (71).
Marques (2006)
Brazil OIDP & the Global Negative
Self-Evaluation Scale CS 333
Low SE was an independent risk factor for an aesthetic impact (89).
SD: Study design, CS: Cross-sectional study
CHAPTER 3: QUALITY OF LIFE IN ORTHODONTICS
Overview
The notion that malocclusion is linked to QOL and wellbeing is largely derived
from studies linking physical, social, and psychological distress to malocclusion (53,90).
Since the physical, social, and psychological aspects of malocclusion are key
reasons why orthodontic care is sought, it can be argued that the best measure of the
outcome from orthodontic treatment is improvement of physical, social, and
psychological health (91-93). These aspects of health are encompassed by OH-QOL
measures, which provide an insight into how individual’s OH status affects life quality
and how oral health care brings about improvements to QOL (47,94).
However, in an extensive review of the literature, Zhang et al. note that much
controversy exists about the impact of malocclusion and its treatment on QOL, and
concluded that there is a need for a more comprehensive and rigorous assessment,
employing standardized, valid, and reliable data collection instruments (93).
Challenges in Psychosocial Assessment in Orthodontics
Although OH-QOL assessment has recently penetrated into the orthodontic
literature, longitudinal assessment of children’s OH-QOL has been hindered by several
methodological issues. These challenges are here discussed by posing the following
questions: “Who should be the informant?”; “Are 11- to 14-year-old children capable of
providing valid QOL reports?”; and “Is it possible to measure change in OH-QOL as a
result of orthodontic treatment in children?”.
Who Should be the Informant?
Until recently, children’s H-QOL was measured using parents as informants. This
was mostly related to concerns about children’s cognitive capacities and communication
skills that might compromise the validity and reliability of their QOL reports (41). On the
other hand, concerns about the accuracy of parental assessments stimulated researchers to
reconsider children reports (95,96). Studies that have used parallel reporting, using
questionnaires designed to collect data from both the parent and the child, found parent-
child agreement to be, at best, moderate (41,95,97). In fact, children with malocclusion
consistently rated their OH-QOL worse than their caregivers’ ratings (98-101).
Further, the accuracy of proxy ratings is dependent on the specific domains of
QOL considered (102). In general, there is greater agreement for observable functioning
(e.g., physical QOL) than for non-observable functioning (e.g., emotional or social QOL).
Pediatric OH-QOL measures, therefore, need to include child reports whenever possible.
This is particularly important when the socio-emotional dimension of OH-QOL is of
primary interest, as is the case in children undergoing orthodontic treatment.
28
Are 11- to 14-year-old Children Capable of Providing Valid OH-QOL Reports?
As mentioned earlier, there are concerns that children’s cognitive capacities and
communication skills may compromise the validity and reliability of their QOL reports
(41). However, the literature suggests that self-report of QOL and health status is feasible
in 11- to 14-year-old children as age effects should no longer be significant. At this age,
children have a good capacity to remember, retrieve, and apply information related to
specific events and experiences (103,104). Their matured language skills and ease in
independent reading allow for the comprehension of items and meet the demands of self-
reported questionnaires (105).
Further, children at this stage, reflective of Piaget's stage of formal operations
(106,107), have matured intellectual functioning and are capable of making the
comparative judgments required for representations of health status and QOL. Their
judgments regarding their general and specific abilities are, in fact, realistic (108,109).
11- to 14-year-old children view health as a multidimensional concept organized around
constructs such as being functional, adhering to good lifestyle behaviors, and having a
general sense of wellbeing and relationships with others. However, how these concepts
are settled varies by age and by the kind of experiences to which children are exposed in
their lives (110). In addition, they have a greater appreciation of illness, disease, and
disability in that each can be understood based on causality and multi-system
understanding (111-113). Despite the enormous psychosocial changes associated with
childhood, French and Christie have shown that children begin to understand the effects
of ill-health on social activities around 8 years of age (114). Therefore, most patients
29
undergoing orthodontic treatment are old enough to answer appropriately phrased
questions regarding oral health and OH-QOL (115).
There are several developmental considerations, however, that need to be
addressed when using child-reports of QOL. These include mental competence and
verbal comprehension, understanding and use of time, and identifying QOL domains and
markers that are appropriate to the child’s developmental stage and are relevant to
children themselves (31,116). Thus, instrument developers need to recognize explicitly
that children are developing beings; and use different item sets and response formats
depending on the developmental level of the child (117).
In summary, the majority of research in medicine and dentistry supports the use of
child self-reports. In fact, a systematic review of recently developed instruments like the
Child Health Questionnaire (CHQ-CF87) (96) and the CPQ11-14 (118) has demonstrated
that, with appropriate questionnaire techniques, it is possible to obtain valid and reliable
OH-QOL information from children (119).
30
Is it Possible to Measure Change in OH-QOL in Children?
The meaning of OH can change over time. This change demonstrates the
existence of response shift in relation to QOL (78). Response shift is defined as changing
internal standards, values, and the conceptualization of QOL (120). This response shift, in
general, complicates the assessment of change in QOL research. Response shift in
children is compounded further by changes in cognitive understanding and psychosocial
awareness (121). In fact, these developmental changes can make children “moving
targets” (94).
These changes in a child's values, goals, and priorities concerning the relative
importance of specific domains of health status are, therefore, more likely to be a critical
cause of response shift in children than they are in adults. For example, some diabetic
adolescents who have previously adapted well to the challenges of diabetes when they
were younger, may now regard them as much more onerous, owing to age-related
concerns about the impact of the treatment on peer activities. Children may change their
appraisals of their condition as they adapt to that condition (122).
These changes in the basis that children use to evaluate oral health status and/or
OH-QOL can cause particular problems in evaluating treatments in studies that involve
repeated measurements (121,123). The causal direction of potential influences on
children's health-related outcomes is very difficult to disentangle and is often
misinterpreted. Thus, it can be difficult to isolate changes in OH-QOL that are solely
brought about by interventions such as orthodontic treatment. Hence, having a control
group of comparable age followed-up for an equivalent duration of time can help to take
31
these developmental changes into account and improve the interpretability of the results
(124).
Assessment of Change in Children’s OH-QOL
Direct Measures of Change
Andrews and Withey believed that questions like “How do you feel about your
life as a whole?” can represent a person’s quality of life (125). The most obvious
advantage of such global questions is their brevity. It has been suggested that global
questions pull together various components of health. As such they make the least
demands on respondents' time. Hence, the use of global questions that directly assess
change is advocated by some OH-QOL researchers, because they are simple, represent
patients’ overall assessment of how their condition has changed over a specified
timeframe, integrate patients’ values, and avoid the statistical issues associated with
change scores (126,127).
These summary answers, however, do not provide information about aspects of
health compromised by the disease/disorder. As a result, they cannot be used for clinical
decision-making purposes such as treatment planning. Similarly, Global Transition
Ratings (GTR) do not reveal the opposing trends in different dimensions of health, if they
ever occur. This is something that is of obvious interest in the context of intervention
studies.
More importantly, these retrospective judgments of change are subject to
significant response shift and recall bias. As discussed earlier, response shift may reduce
the confidence in the initial assessment (128) and, therefore, can undermine the validity
32
of direct change measures. According to Streiner and Norman, children may simply not
remember their baseline state. When children are asked how they felt two or three years
ago, they first reflect on their current state (how do I feel today?). This in turn triggers an
“implicit theory of change” where children contemplate how they think the treatment
influenced their lives. They then try to estimate what their initial state must have been.
This theory of implicit change questions the robustness of GTR as direct measures of
change (129).
Further, evidence indicates that participants may use different frames of reference
in responding to global questions (79,130,131). While some place a value on physical
health, others respond in terms of emotional functioning or health behavior. Also, there
are respondents who make comparisons with others or refer to their own condition before
becoming sick. Consequently, some questionnaires position the global questions at the
beginning to prevent the respondents from being influenced by later items, while others
place them at the end so that the earlier items serve as a frame for the areas of functioning
that are of interest in the study. However, the true effect of positioning global questions
remains unknown. Unlike adults, the criteria used by children to answer global questions
have not been studied. It is not clear to what extent the terms health and wellbeing are
distinguished by child respondents. It appears that health relates principally to physical
problems, while wellbeing focuses primarily on mental problems (115). Therefore,
considering the limitations above, global questions should be used to supplement, not to
replace, QOL scales (127).
33
Multiple Item Measures
Classical measurement theory views the variability in the respondents' scores on a
measure of a given concept as due to a combination of true variation in the concept across
or within respondents, and error variation in the respondents' scores (129,132). According
to Streiner and Norman, random errors tend to cancel each other out if enough
observations are made (129). Multiple item measures have the same effect of allowing
random errors to average out (133,134), since the scores on the individual items represent
related observations. Therefore, the reliability of a measure for a given study population
and study context can be improved by increasing the number of items and/or by
increasing their inter-correlations.
For measures to identify within-individual changes that occur either naturally or
as a result of clinical interventions, however, they should be sensitive to change. A wide
range of statistical approaches are now available to assess the ability of OH-QOL
measures to detect clinically significant changes and enhance the clinical application of
these measures (135). In general, these statistical methods are based on two potential
approaches, relating measurement sensitivity to meaningful clinical change, and
evaluating the meaningfulness of change based on the perspectives of respondents (136).
For instance, calculation of effect sizes can be used to determine the significance and
magnitude of change. The scores on a questionnaire prior to and after an intervention are
compared (132). Effect sizes can be calculated by dividing the mean of change scores by
the standard deviation. Effect sizes of 0.2 are generally taken to be small, 0.5 to be
moderate, and 0.8 or above to be large (137).
34
The CPQ1l-14, the instrument chosen for this study, was constructed according to
a process derived from the theory of measurement and scale development that represents
the most systematic and sophisticated approach to the design of multi-item questionnaires
(129,138). However, the ability of the CPQ11-14 to detect clinically relevant changes in
children's outcomes is not yet fully explored (139).
35
How Has OH-QOL Been Assessed in Children Thus Far?
Adult OH-QOL Measures
Initially, OH-QOL was evaluated in orthodontics using measures that were
originally developed in the field of dentistry. Adult instruments like the Oral Health
Impact Profile (OHIP) (140) and the Oral Impacts of Daily Performance (OIDP) (36)
have been used to assess the impacts of malocclusion in children. The Psychosocial
Impact of Dental Aesthetics Questionnaire (PIDAQ) (141) and the Orthognathic Quality
of Life Questionnaire (OQOL) (32) were developed more recently for assessment of
orthodontic and orthognathic aspects of quality of life. The PIDAQ and OQOL are
potentially promising tools for research and clinical application in orthodontics.
However, both instruments were designed for use in adults above 18 years old. As
discussed earlier, in order for an OH-QOL measure to be appropriate for children, they
should:
Operationalize an accepted, clear, generic QOL definition.
Include broadly encompassing QOL domains applicable to all children.
Include both objective and subjective approaches.
Have parallel forms for children and other informants.
Weigh satisfaction on domains of perceived importance to the child.
Demonstrate satisfactory psychometric characteristics.
Provide norms for the general population in addition to any specific group of
children it targets.
36
Recognize explicitly that children are developing beings (e.g., through the use
of different item sets, response formats, or entirely different forms dependent
upon the developmental level of the child) (31).
Therefore, the validity of these measures for children has been questioned given
their conceptual basis, item content and wording, recall periods, and response formats
(94,142,143). In fact, some of these measures require advanced reading and language
skills, and high levels of abstract thinking that render them unsuitable for children. For
example, the OHIP ask questions like:" Because of problems with your teeth, mouth or
dentures ... have you been less tolerant of your spouse or family? ... have you suffered
financial loss?". Clearly, such questions are irrelevant to children. Moreover, adult
measures ignore aspects of daily life that are important for children such as school
activities and peer relationships. Therefore, the majority of these measures are not
applicable to the child orthodontic patient (12). This is really important considering that
54% of patients currently receiving orthodontic care in the United States are between the
ages of 12 and 17 (144).
Child OH-QOL Measures
In an attempt to address the shortcomings above, several OH-QOL measures were
developed specifically for use in children to fill this urgent need. These are:
The Second International Collaborative Study-Oral Health-Related Quality of
Life Questionnaire for Children (ICSII-OHRQOL)
Michigan Oral Health-Related Quality of Life Scale-Child Version
Oral Aesthetic Subjective Impact Scale (OASIS)
37
Child Oral Health Quality Of Life Questionnaire (Child OH-QOL
Questionnaire)
Child-Oral Impacts of Daily Performance (Child-OIDP)
Preliminary evaluation of the ICSII-OHRQOL showed its potential validity in
children (143). However, to the best of our knowledge, this validation was not pursued
any further. The Michigan Oral Health-Related Quality of Life Scale-Child Version was
designed for use in a younger age group to assess the impacts of early childhood caries
and it is therefore irrelevant to orthodontic patients. The OASIS was one of the early
attempts to assess the aesthetic impacts of malocclusion on subjective quality of life (64).
It consists of five questions to measure the amount of concern that children feel because
of the arrangement of their teeth. Respondents are asked to indicate, on a seven-point
Likert scale, their concern about tooth appearance, nice comments about teeth, unpleasant
comments about teeth, teasing about teeth, avoidance of smiling, and covering the mouth.
However, OASIS was originally designed to reflect orthodontic treatment need, and it has
not been so far applied as an outcome measure. OASIS is composed of only five items; it
seems that the developers have given little consideration to the multidimensional aspect
of OH-QOL. Further, its technical properties are not known as it was not tested in
different groups apart from the original 14- to 15-year-old children it was developed in.
Thus, it is fair to conclude that at present, there are two adequately validated OH-
QOL measures that could be potentially useful in the context of orthodontic treatment of
children, the Child-OIDP (145) and the CPQ11–14 component of the child OH-QOL
Questionnaire (146). The properties of both measures are contrasted in Table 2 and a
detailed description is provided.
38
Table 2: Development and age adaptations of the Child-OIDP and the CPQ11-14
Age adaptation feature Child-OIDP CPQ11-14
Age versions available (Years) 11-12 11-14
Direct application or modification of an adult measure
Child specific development
Children involved in item generation and reduction
Items from children
Domains from children
Wording addressed
Response Burden 8 37
Response options addressed
Recall time addressed
Attribution addressed
Negative wording addressed
The Child-OIDP. The original Oral Impact on Daily Performance (OIDP) index
was developed from a theoretical model of oral health proposed by Locker (147) as
adapted from the WHO Classification of Impairments, Disabilities, and Handicaps (148).
The Child-OIDP was developed from the original OIDP index using input from children
and pediatric dentists, and pays attention particularly to the language used, performances
included, number of questions, and the response format. The Child-OIDP is administered
39
as an interview. The recall period of 6 months for the OIDP was shortened to 3 months
for the child version (145).
The Child-OIDP assesses the oral impacts on 11- to 12-year-old children’s daily
life in relation to eight daily performances, namely, eating, speaking, cleaning mouth,
sleeping, smiling, studying, emotion, and social contact. It records the frequency of the
impact (on a scale from 1–3) and its severity (on a scale from 1–3). If no impact is
reported, then a zero score is assigned. The impact per daily performance is then
estimated by multiplying the corresponding frequency and severity scores. The overall
Child-OIDP score is the sum of the eight performance scores (ranging from 0–72)
multiplied by 100 and divided by 72 (145).
The CPQ11–14. This is one of the recent child OH-QOL instruments. This
questionnaire, developed by Jokovic and colleagues (118), forms one part of the generic
self-completed child OH-QOL questionnaire, incorporating a Parental/Caregiver
Perceptions Questionnaire (PPQ), the Family Impact Scale, and three age-specific
questionnaires for children. The CPQ11-14 was developed for use with 11 to 14-year-
olds with a wide range of dental, oral, and oro-facial disorders. It is composed of 37
questions encompassing four domains: six questions assessing Oral Symptoms (OS), nine
questions assessing Functional Limitations (FL), nine questions related to Emotional
Wellbeing (EWB), and 13 questions evaluating Social Wellbeing (SWB). CPQ11-14
Score ranges from zero to 80. A high score indicates worse OH-QOL.
All questions ask about the frequency of events in the preceding three months in
relation to the condition of the child’s lips, teeth, and jaws. The CPQ11-14 was
developed using the item-impact method proposed by Guyatt and Juniper (149). The
40
development process involved several critical stages (Figure 3). After developing a
preliminary list of items by interviewing parents and experts dealing with children
affected by oro/craniofacial conditions; the initial item list was reduced using the item-
impact method. This method is based on the frequency and the perceived importance of
the items selected by that population. Since the ultimate goal was to develop an
evaluative measure, the high prevalence items were selected to promote responsiveness.
Finally, the reduced questionnaire was tested for validity and reliability.
Figure 3: Diagrammatic representation of the CPQ11-14 developmental process Reproduced from Jokovic (2003). Page 97 (118)
Initial testing of the questionnaire has shown that the CPQ11-14 possesses good
discriminative ability, with the highest scores being noted for the oro-facial group and the
lowest for the pedodontic group, the orthodontic group lying in between (146,150). The
instrument has been, so far, tested in Canada, New Zealand, Uganda, Saudi Arabia,
Brazil, and the United Kingdom and found to be a valid and reliable in children with
malocclusion (51,52,63,151,152). It consistently demonstrated good test-retest reliability
41
and internal consistency in each of these countries. Altogether, these results show that 11-
to 14-year-old children are able to give acceptable accounts of OH-QOL (115). Non-
English versions of the CPQ11-14 are now available (51,153) and attempts to develop a
short form for use in clinical trials and public health survey are also underway (152,154).
Further, Foster Page et al., investigated the ability of the CPQ11-14 to
discriminate between the various levels of malocclusion severity (152). They
hypothesized that children with more severe malocclusions should have higher overall
CPQ11-14 scores. The study evaluated 430 children in New Zealand, and revealed that
there was a statistically significant distinct gradient in mean CPQ11-14 score by
malocclusion severity. These differences were, however, clearer for the emotional and
social wellbeing sub-scales. A similar gradient in CPQ11-14 scores was observed across
categories of the PAR index in a study of Canadian children (151).
Increasingly, studies are being undertaken to evaluate the CPQ11-14 in different
orthodontic contexts (Table 3). These results support the use of CPQ11-14 for future
orthodontic studies and demonstrate its excellent cross-sectional psychometric properties.
Nonetheless, the longitudinal psychometric properties of the CPQ11-14 have not been
assessed thus far. Therefore, a preliminary study was undertaken, by this author and a
colleague, to confirm its longitudinal psychometric properties. (155).
In summary, while the CPQ11-14 was primarily intended for use as an outcome
measure in clinical trials and evaluation studies, the Child-OIDP was designed
specifically to be used in population based surveys to assist dental service planning.
Further, the psychometric properties of the CPQ11-14 are currently well-established for
11- to 14-year-old children; an age group that comprises a good percentage of the patients
42
43
currently seeking orthodontic treatment. Therefore, the use of the CPQ11-14 has become
popular in orthodontics. In fact, leading OH-QOL researchers consider it as the
questionnaire of choice in future orthodontic QOL research (10).
Table 3: Summary of studies validating the CPQ11-14
Author (Year)
Location SD N Main findings
Jokovic (2002)
Canada CS 123 CPQ11-14 has good discriminative ability and test-retest reliability (146).
Jokovic (2005)
Canada CS 123 Children are able to give acceptable accounts of oro/craniofacial impact (115).
Marshman (2005)
UK CS 89 CPQ11-14 exhibits acceptable reliability and validity (63).
Foster Page (2005)
New Zealand
CS 430 There was a distinct gradient in mean CPQ11-14 scores by malocclusion severity (58).
O’Brien K. (2006)
UK CS 325 CPQ11-14 is likely to be a useful measure for orthodontic trials in the UK (57)
O’Brien C (2007)
UK CS 116
CPQ11-14 did not differentiate between the crowding, hypodontia, or an increased overjet, but there was a statistically significant difference between the malocclusion and control total CPQ11-14 scores. These differences were significant for the EWB and SWB domains, and non-significant for the OS and FL domains (56).
Locker (2007)
Canada CS 141
There was a clear gradient in CPQ11-14 scores categories of the PAR index. The gradient across the DAI categories was less clear. The results provide evidence of the validity of the CPQ11-14 when used to evaluate orthodontic treatment (151).
Do (2008)
Australia CS 1401The CPQ11-14 showed acceptable construct validity against global ratings of oral health and overall wellbeing. Children who had more caries or less acceptable occlusal traits reported worse OH-QOL (59).
Agou (2008)
Canada LG 45 The results provide preliminary evidence of the sensitivity to change of the CPQ11-14 when used with children receiving orthodontic treatment (156).
SD: Study design, CS: Cross-sectional study, LG: Longitudinal study
Does Orthodontic Treatment Improve OH-QOL?
Although many studies have examined the relationship between malocclusion and
OH-QOL in children (Table 4), very few studies have directly compared OH-QOL
outcomes between children who received orthodontic treatment to those who did not.
Only recently have de Oliveira and Sheiham studied the impact of orthodontic treatment
on OH-QOL in Brazilian adolescents (72). The findings showed that those who had
completed treatment were 1.85 times less likely to have OH-QOL impacts than those
currently undergoing treatment, and 1.43 times less likely than those who had not had
treatment. These findings were corroborated by a recent case-control study of the same
population (157).
The majority of these studies highlight the importance of the emotional and social
dimensions of OH-QOL in children when assessing orthodontic treatment outcomes.
Nonetheless, given the cross-sectional study designs, an association rather than evidence
of causation was observed. Therefore, further studies are warranted to confirm or refute
these findings.
As mentioned earlier, according to the operational definition of OH-QOL
employed in this dissertation, OH-QOL consists of four major domains (Figure 1). These
are: oral symptoms, functional limitations, social wellbeing, and emotional wellbeing.
Therefore, in order to examine the relationship between orthodontics and the various OH-
QOL domains, the literature is surveyed by posing the following questions: Does
orthodontic treatment improve oral symptoms?; Does orthodontic treatment improve oral
46
function?; Does orthodontic treatment improve social wellbeing?; and Does orthodontic
treatment improve emotional and psychological wellbeing?
Table 4: Studies examining OH-QOL, malocclusion, and/or orthodontics
Author (Y) Location Measure SD N Main findings
Mandall (2000)
UK OASIS CS 334 OASIS scores were similar between treated and untreated children, but untreated children who wished for orthodontic treatment had worse scores (64).
de Oliveira (2003, 2004)
Brazil OIDP & OHIP-14
CS 1675
Adolescents who had completed orthodontic treatment had fewer oral health-related impacts compared to those currently under treatment or those who never had any treatment. Current methods of assessing orthodontic need should be complemented by OH-QOL measures (72,158)
Gherunpong (2004)
Thailand Child-OIDP
CS 1126 The severity of oral impacts was mainly related to difficulty eating and smiling. Toothache, oral ulcers, and natural processes contributed largely to the incidence of oral impacts (145).
Kok (2004)
UK CPQ11-14 CS 174 Children with a normative need for treatment did not have significantly higher CPQ11-14 scores. (61).
Jokovic (2005)
Canada CPQ11-14 CS 123 The impact of child oral and oro-facial conditions on functional and psychosocial wellbeing is substantial (115).
Gherunpong (2006) Tsakos (2006)
Thailand Child-OIDP
CS 1034
There was a marked difference between the standard normative and the sociodental orthodontic needs assessment approach, with the latter approach showing a 60% lower assessment of dental health care needs in Thai 11- to 12-year-old children (23,159,160).
O’Brien K (2006)
UK CPQ11-14 CS 325 CPQ11-14 scores were increased for girls, increased treatment needs (IOTN), and when the child felt their teeth needed straightening (57).
O’Brien C. (2007)
UK CPQ11-14 CS 116 Malocclusion has a negative impact on the OH-QOL of adolescents. The OS and FL subscales of the current questionnaire are not relevant to orthodontic patients (56).
Johal (2007)
UK CPQ11-14 CS 90 Increased overjet or spacing does have a significant negative impact on the child’s quality of life compared to controls, but no differences between the overjet and spaced group (55).
Zhang (2007)
China CPQ11-14 CS 217 The impact on QOL after insertion of fixed orthodontic appliances was considerately less than what child patients expected (161).
Bernabe (2007)
Peru Child-OIDP
CS 805 Impacts of self-perceived malocclusion primarily affected psychological and social everyday activities such as smiling, emotion and, social contact (162).
Traebert (2007)
Brazil OIDP CS 414 Some types of malocclusions have an impact on quality of life, especially in terms of satisfaction with appearance (60).
de Oliveira (2008)
UK CPQ11-14 CS 187 OH-QOL measures explained the prediction of perceived need for braces. Importantly, children with an impact were denied orthodontic treatment (163).
Mtaya (2008)
Tanzania OIDP CS 1601 Compared to the high prevalence of malocclusion, psychosocial impacts and dissatisfaction with appearance or function was not frequent among Tanzanian schoolchildren (85).
Bernabe (2008)
UK Child-OIDP
CS 200
The prevalence of OIDP attributed to any oral condition was 26.5% whereas the prevalence of OIDP attributed to malocclusion was 21.5%. The prevalence of such impacts increased from 16.8% for adolescents with no/slight need for orthodontic treatment, to 31.7% for those with definite need for orthodontic treatment (54).
Bernabe (2008)
Brazil Child-OIDP
CS 157 One in four Brazilian adolescents undergoing orthodontic treatment reported side effects, specific impacts on daily living, related to wearing orthodontic appliances (164).
48
49
Bernabe (2008)
Brazil Child-OIDP
CC 279
Brazilian adolescents with a history of orthodontic treatment were less likely to have physical, psychological, and social impacts on their daily performances associated with malocclusion than those with no history of orthodontics (157).
SD: Study design, CS: Cross-sectional study, CC: Case-control study
Does Orthodontic Treatment Improve Oral Symptoms?
Pain is a common symptom that can impact on QOL (165). Malocclusion by itself
does not cause oro-facial pain; however, it can give rise to pain indirectly by leading to
either temporomandibular disorder, dental, or gingival trauma (166-170). Nevertheless,
the relationship between malocclusion and temporomandibular disorder is not confirmed
(171-173), and there is no convincing evidence that orthodontic treatment could cause or
treat temporomandibular disorder (168,171,172,174).
Similarly, the literature is conflicting regarding the association between
malocclusion and dental trauma. A meta-analysis of the relationship between overjet size
and dental trauma suggests that children with an overjet greater than 3 mm are twice as
much at risk of injury to the incisors compared to children with an overjet of less than
3 mm (175). In contrast, several studies have reported no significant relationship between
dental trauma and overjet (176,177).
The relationship between gingival trauma and malocclusion is also controversial
(178). The current consensus is that malocclusion is a cofactor that may accelerate the
rate of development of an existing periodontal disease, but it does not initiate it on its
own (179,180). However, large overjets, deep overbites, and severe Class II, division 2
malocclusions have been associated with increased periodontal disease prevalence (166).
In fact, one randomized controlled study suggested that early correction of protruding
upper incisors may have some effect on the incidence of both dental and gingival trauma
(169).
Does Orthodontic Treatment Improve Oral Function?
Improvement of speech and masticatory efficiency are perhaps the most
commonly claimed functional benefits of orthodontic treatment. However, the evidence
for these claims remains largely anecdotal.
Some studies reported on differences between subjects with malocclusion and
those with normal occlusion in masticatory ability and chewing efficiency (181,182). One
study even suggested that more severe malocclusions may affect dietary habits such as
choice of food and nutritional status (183). However, most studies found either no, or
very weak, associations between malocclusion and masticatory function (184,185).
Similarly, orthodontic treatment did not improve chewing efficiency in growing patients
(186), but it did improve the masticatory ability of orthognathic patients (187,188).
Speech disorders are another potential consequence of malocclusion. A significant
but weak association between speech disorder and malocclusion has been demonstrated
in a number of studies (189-191). For example, pronunciation problems for sibilants like
/s/, /z/, /j/, and /ch/ have been associated with occlusal traits like large overjet and deep
bite (192-195). However, the complexity of speech production makes it difficult to draw
a conclusive cause-and-effect relationship (196). Studies have shown that patients with
malocclusion can compensate for their malocclusion, regardless of its severity, and
produce normal speech (189,197-199).
Does Orthodontic Treatment Improve Social Wellbeing?
Dental aesthetics is an important aspect of facial appearance (191,200,201), which
is in turn an important element of social attractiveness (200-202). In fact, several reviews
have identified facial appearance as an important determinant of interpersonal popularity,
51
evaluation of one's personality, social behavior, and intellectual expression (203,204).
Some even argue that the dentofacial appearance of children can impact teachers’
judgment of students’ intelligence and academic potentials (203). For instance, some
studies have suggested that children with incisor crowding and median diastemas were
judged to be less attractive, less intelligent, and from a lower social class (200). These
assumptions are, however, undermined by studies that reported no differences in the
rating of attractive or unattractive schoolchildren based on facial appearance (205). In
addition, the judgment an individual makes concerning the personality of others under
experimental settings, are usually made in the absence of other real life information
regarding these individuals (206).
Bullying is another social impact commonly attributed to malocclusion (207).
Psychological theorists believe that bullying victims are often socially isolated, and suffer
from psychological problems including anxiety and depression (208). In fact, name
calling and teasing in childhood can leave lasting impressions extending into adulthood
(188,209). However, due to improper study designs or inappropriate assessment
techniques, there is little evidence of improvement in the social wellbeing of children
following orthodontic treatment (207).
Nonetheless, current research shows that OH-QOL measures are potentially
promising tools to demonstrate the importance of psychological and social components of
oral health on children's lives (56,72,157).
Does Orthodontic Treatment Improve Emotional and Psychological Wellbeing?
Many claim that certain malocclusions, especially conspicuous occlusal and space
anomalies, may adversely affect SE and/or PWB, and that treating it would likely result
52
in enhancement of SE and/or PWB (82,88,210-214). While some studies support this
assumption in adults (24,215,216) and orthognathic surgical patients (21,217-222), the
research is less clear-cut for children and adolescents.
Some studies did, indeed, establish connections between orthodontic treatment
and enhanced SE (75,88,223,224). People who are satisfied with their facial appearance,
and presumably their dental appearance, seem to be more self-confident and have higher
SE than those who are dissatisfied with their facial appearance (200,215). In fact, severe
malocclusions were associated with feelings of uselessness, shamefulness, and inferiority
(188,209,225). Most of these studies, however, were cross-sectional in nature
(75,88,223,224), underpowered (75), or inadequately controlled (75,88,215,223,224).
Controlled evaluations, on the other hand, have often failed to document a cause-
and-effect relationship between SE and orthodontics (Table 5). For instance, a
prospective longitudinal evaluation of 224 eleven to 15-year-old Norwegian children
revealed that improvement in SE was not correlated with orthodontic treatment changes
(6). Similar results were reported for British and American children who participated in
randomized controlled trials examining the psychosocial effects of early orthodontic
treatment (226,227). It seems that while dental-specific evaluations appear to be
influenced by treatment, the more general psychosocial responses such as subjects' SE are
not (7).
Perhaps the most striking results were those reported by Cardiff researchers. In
this 20-year follow-up study, the authors noted that the lack of orthodontic treatment
when there was need did not lead to psychological difficulties in later life (8,228). The
study’s overall conclusion was that while participants' SE increased over the 20-year
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period, in general, it was not as a result of receiving braces, and it did not relate to
whether an orthodontic treatment need existed in 1981.
In summary, although the psychosocial component is a dominant factor in
determining the demands for orthodontic treatment (229), experimental data have
repeatedly shown that treatment does not increase children’s global SE or PWB. These
results do not necessarily negate the widespread belief among clinicians that orthodontic
treatment has considerable psychosocial benefits; rather, they question the way we have
been measuring these benefits thus far. They also shed light on the way we view SE and
PWB as endpoint outcomes in orthodontic psychosocial research, and warrant a review of
how these concepts are defined and measured in the child psychology literature.
Table 5 : Studies evaluating the effect of orthodontics on children’s SE/self-concept
Author* (Year)
Study design N Psychosocial Instrument Indication of SE
improvement
Rutzen (1973)
Cross-sectional study 252 Rosenberg SE Scale (230) No
Klima (1979)
Cross-sectional study 173 Secord Self-concept (231) No
O’Regan (1991)
Cross-sectional study 218 Piers-Harris Self-concept Scale
(232) No
Korabik (1994)
Prospective longitudinal study 58 Piers-Harris Self-concept Scale
(233) No
Albino (1994)
Randomized Controlled Trial 76 Coopersmith SE Inventory Rosenberg Self Image (7)
No
Dann (1995)
Randomized Controlled Trial 101 Piers-Harris Self-concept Scale
(226) No
Birkeland (2000)
Prospective longitudinal study 208 Global Negative Self-Evaluation
Scale (6) No
O’Brien (2003-2005)
Randomized Controlled Trial 176 Piers-Harris Self-Concept Scale
(210,227) Short-term: Yes Long-term: No
Shaw (1986-2007)
Prospective longitudinal study 337
Rosenberg SE Scale Centre for epidemiological studies
depression scale Perceived stress scale (8,228,234)
No
*Studies examining orthognathic patients are not included
CHAPTER 4: SELF-ESTEEM AND PSYCHOLOGICAL WELLBEING IN CHILDREN
Self-Esteem
Conceptual Background
SE continues to be one of the most widely researched concepts in social and
developmental psychology (235-238). Generally conceptualized as a part of the self-
concept, to some, SE is one of the most important parts of the self-concept. For a period
of time, so much attention was given to SE that it seemed to be synonymous with self-
concept in the literature on the self (239,240). This focus on SE has largely been due to
the association of high SE with a number of positive outcomes (235,241). For instance,
the belief is widespread that raising a child or an adolescent’s SE would be beneficial for
both the individual and society as a whole.
Self-concept is a broad-ranging concept relating to personal self-concept (facts or
one's own opinions about oneself), social self-concept (one's perceptions about how one
is regarded by others), and self-ideals (what or how one would like to be) (242). On the
other hand, SE refers most generally to an individual's overall positive evaluation of the
self (239,243-245).
SE is composed of two distinct dimensions, competence and worth (243,244). The
competence dimension (efficacy-based SE) refers to the degree to which people see
themselves as capable and efficacious. The worth dimension (worth-based SE) refers to
the degree to which individuals feel they are persons of value. Blascovich and Tomaka
described SE as an encompassing self evaluation influenced by many variables including
abilities, traits, behaviors, clinical conditions, and coping abilities (246). However, using
factor analysis, Fleming and Watts observed three essential components of SE in
adolescents: social confidence, school abilities, and self regard (247).
Further, Emler’s extensive report on SE states that appearance, in contrast to
parental influence for instance, does not contribute significantly to variations in SE (9).
Although Festinger’s social comparison theory implies that individuals have a tendency
to compare themselves with others, which can cause feelings of inadequacy or failure
(26), research suggests that adolescents simply tend to delete roles in which their
performances are less satisfactory. For example, Harter found in studies of adolescents
that poor self-evaluations in domains such as attractiveness or athletic skills are
associated with low self-esteem only in children who rate those domains as important;
high self-esteem children tend to devalue the importance of domains in which they
believe they are not doing well (108). Hence, it is unlikely that impaired perception of
oro-facial appearance as a result of malocclusion would translate into diminished SE.
Research on SE has generally proceeded on the presumption of one of three
conceptualizations. First, SE has been investigated as an outcome. Scholars taking that
approach have focused on processes that produce or inhibit SE (108,248-250). Second,
SE has been investigated as a self-motive, noting the tendency for people to behave in
ways that maintain or increase positive evaluations of the self (251,252). Finally, SE has
been investigated as a buffer for the self, moderating various life encounters and
providing protection from experiences that are harmful (253-256).
There is considerable evidence that supports this role of SE as a personal resource
that may moderate the effects of conditions or events (257,258). Numerous psychological
studies, including Harter’s popular thesis of SE, suggest that SE facilitates coping with
57
less favorable conditions (109,259-262). One dimension of the self may compensate for
the loss or chaos in another, so that a relatively balanced self is maintained where good
quality of life may result (35).
It is therefore fair to conclude that SE is not an ideal outcome measure to assess
the psychosocial benefits of orthodontic treatment. In fact, speculations about the
moderational role of SE in orthodontics find roots in studies as early as the 1970s. In a
five-year follow-up study of the social importance of orthodontic rehabitulation, Rutzen
states that there were no differences in SE between persons with treated and untreated
malocclusion because the untreated persons compensate in their role performance (230).
Stability of SE
SE, like other dimensions of personality, is a function of interacting biological,
developmental, and social processes across the life course. However, most definitions of
SE suggest that it is a stable and enduring characteristic (246). Rosenberg (1995), for
example, described SE as "the evaluation which an individual makes and customarily
maintains with regard to himself/herself; it expresses an attitude of approval or
disapproval (239)."
Whether or not SE is truly stable is an important question that has received
considerable attention in experimental psychology (263). Although the occurrence of
short-term fluctuations in SE has been convincingly demonstrated (264), there is
overwhelming empirical evidence indicating an appreciable stability in global SE
(238,265). Individuals who are higher (or lower) relative to their peers in global SE at
one time point also tend to be higher (or lower) in SE relative to their peers at a future
time point (266).
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That being said, adolescence is generally regarded as a period of considerable
biological, social, psychological, and developmental change. Therefore, there is some
debate concerning the proportion of adolescents who are troubled by these changes and
the proportion who go through this stage without tumult (267,268). In theory, the
significant changes associated with adolescence are likely to be reflected by shifts in a
person’s SE. During this developmental period, SE is dominated by inner thoughts,
feelings, attitudes, desires, beliefs, fears, and expectations (245,269-271). As early
adolescents gradually move into late adolescence, they liberate from parents, parent-
adolescent conflict heightens, peer association intensifies, and concerns turn to dating and
sexual activity (272). In fact, Rosenberg and several others noted that these processes
may generate more disturbances to SE at ages 12 and 13 than at any other point in the life
cycle (245).
It is important to note, however, that SE solidifies during adolescence and
becomes less susceptible to evaluations by others. Ellis et al. found that roughly midway
through adolescence, individuals shifted from evaluating themselves primarily on
external standards of achievement to rating themselves primarily on internal standards of
personal happiness (273). Hence, as adolescents continue to mature and adjust to new
social roles, physical characteristics, and cognitive abilities, they redefine their self-
theories. Self-cognitions are reorganized and reintegrated, self-consciousness diminishes,
stability of self is restored, and levels of SE rise steadily as individuals move through this
period of development (267,268,274-278).
In fact, empirical research on changes in SE during adolescence has yielded fairly
consistent results. Engel (279), Monge (280), and Piers and Harris (281) have reported
59
that SE is stable from approximately 13 through 18 years of age. The few studies (282)
which found changes in SE across the adolescent years were dismissed by many theorists
(280,283), as these studies did not account for the multidimensional structure of SE.
To sum, despite short-term fluctuations that may occur during adolescence, SE is,
for the most part, a relatively steady trait. As individuals grow, SE becomes more stable,
resistant to change, and uninfluenced by the short-term evaluations of peers (284). These
conclusions coupled with the empirical evidence undermining the importance of
appearance to maintain high levels of SE in children, explain why earlier orthodontic
studies did not demonstrate increases in SE following treatment.
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Psychological Wellbeing
Conceptual Background
Over the past 30 years or so, there have been various attempts by psychologists to
define PWB and explain its causes and consequences. In social psychology, wellbeing
refers to general happiness and overall satisfaction with life (285). In the health industry,
however, the term is used as kind of a catch-all phrase meaning contentment, satisfaction
with all elements of life, self-actualization, peace, and happiness. According to Campbell,
PWB resides within the experience of the individual (286). It is a person’s evaluative
reaction to his/her life, either in terms of life satisfaction (cognitive evaluations) or affect
(ongoing emotional reaction).
SE has been reported to be one of the strongest predictors of wellbeing (287-289).
For instance, Diener’s review of wellbeing cites 11 studies demonstrating positive
associations between SE and PWB (290). Similarly, Rosenberg found that those low in
SE tend to be more self-conscious, depressed, and isolated than those with high self-
esteem (291). Further, Campbell et al. compared satisfaction in different domains with
overall life satisfaction, and found that among all the variables studied, the highest
correlation with life satisfaction was satisfaction with the self (r=0.55, p<0.001) (292).
The conceptualization of PWB revolves around two distinct, but complementary,
philosophies: hedonism and eudemonism. In hedonism (293), wellbeing consists of
pleasure or happiness, while in eudemonism, wellbeing lies in the actualization of human
potentials (294); a feeling of having achieved something with one's life.
The hedonic position has dominated psychological research for many years. Many
researchers accept the use of subjective wellbeing as an operational definition of
61
hedonism and wellbeing while still endorsing a eudaimonic view of what fosters
subjective wellbeing. Although subjective wellbeing is perhaps a noisy and imperfect
metric for happiness, it is a useful, effective, and a scientific measure provided that its
limitations are acknowledged. According to Diener, the assessment of subjective
wellbeing, consists of life satisfaction, the presence of positive mood, and the absence of
negative mood (295,296).
Stability of PWB
Twin studies have demonstrated that PWB is considerably stable over time (297).
Albeit relationships with parents, peers, and school performance have been found in
various studies to be important to children’s PWB (298), PWB is largely determined by
genetics and inherent personality characteristics (297). Objective physical attractiveness
(299) and physical health (300), on the other hand, correlated with wellbeing at very low
levels.
Because of this trait-like feature of subjective wellbeing, many researchers were
able to demonstrate that characteristically happy people tend to interpret the same life
events and encounters more favorably than unhappy people (301). Lyubomirsky and
Tucker, for example, showed that individuals with high subjective wellbeing tended to
cast events and situations in a more positive light, to be less responsive to negative
feedback, and to ignore opportunities that are not available to them (302). Thus, people
high in subjective wellbeing may have attributional styles that are more self-enhancing
and enabling, which in turn could contribute to the relative stability of their happiness.
The hedonic treadmill theory is a widely accepted model of PWB, according to
this theory, good and bad events temporarily affect well-being, but people quickly adapt
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63
back to hedonic neutrality. The term “hedonic treadmill”, therefore, stand for the
hypothesis that trying to improve one’s wellbeing is futile, and that wellbeing is instead
determined by a combination of genes and random factors (303).
This theory, however, was recently revisited using data from recent empirical
work. In a 2006 article, Diener et al. indicate that individuals may have different set
points and that a single person may have multiple happiness set points where different
components of wellbeing, such as pleasant emotions, unpleasant emotions, and life
satisfaction, can operate in different directions. These revisions to the hedonic treadmill
theory imply that wellbeing can change under some condition for some people in reaction
to some external event (303).
Nevertheless, Diener et al. stress that while these revisions provide psychologists
and policy makers with a possibility for changing individuals’ wellbeing, the processes of
adaptation must still be carefully considered when evaluating interventions aiming at
enhancing PWB (303). This is particularly important considering that experimental
intervention studies are in the initial stages and that no experiments have directly tested
whether an average person can be made reliably happier in the long-term by some
intervention. The effect of the intervention could be transitory; although people might
initially react positively to interventions, they may adapt over time and return to their
baseline wellbeing.
CHAPTER 5: STATEMENT OF THE PROBLEM
Several key themes were identified in this overview of the psychosocial literature
in orthodontics. In summary, although children represent more than half the patient
population currently receiving orthodontic treatment in North America, the evidence
supporting the strongly held beliefs among the orthodontic community regarding the
psychosocial benefits of orthodontic care in children is, at best, conflicting. These
benefits were commonly assessed using SE as a “yard stick”. However, results from
long-term psychological studies question the conceptual appropriateness of this
measurement approach in children. Furthermore, the diverse interpretations as to what
social and psychological oral health mean, as well as the lack of rigorous standardized
approaches to assess these constructs, make it difficult to compare the impact of
orthodontic treatment across studies.
Fortunately, with the emergence of OH-QOL measures, significant advances have
been made in the assessment of the social and psychological consequences of oral health
(304). OH-QOL measures have the potential to provide a greater understanding of the
consequences of untreated malocclusion and the benefits of orthodontic care.
Research on the use of these measures among children is promising (146). There
is a boom in studies examining the association between orthodontics and OH-QOL. The
number of studies listing “OH-QOL” as a key word in the orthodontic literature in the
MEDLINE database has increased from only eight studies in the early nineties (1991-
1996), to just less than 30 papers during the subsequent five years (1997-2002), to over
100 articles published in the last five years (2003-2008). These numbers clearly indicate
that orthodontic researchers are moving away from the traditional clinician-centered
model towards the modern patient-centered model of assessment. These new research
movements are, in fact, both important and timely considering the significant debates
regarding the psychosocial benefits of orthodontic treatment.
Nonetheless, the associations between OH-QOL and orthodontic treatment have
not been examined longitudinally. Hence, there is an urgent need for a longitudinal
evaluation of the effects of malocclusion and its treatment on OH-QOL. However, since
longitudinal assessments of children are complicated by a variety of factors, the inclusion
of a control group is essential considering the rapid, multi-faceted, and rather
unpredictable developmental changes children undergo during this period.
Moreover, most studies indicated that the association between OH-QOL and
normative measures of malocclusion are rather weak. According to contemporary models
of the consequences of disease, H-QOL and, by extension, OH-QOL are not merely
determined by the clinical condition but also by the characteristics of the individual.
We decided, therefore, to examine the effect of individual characteristics, namely;
SE and PWB, in moderating OH-QOL reports of participating children. This involves a
two-phase study, a cross-sectional phase examining the relationship among SE,
malocclusion, and CPQ11-14 reports, and a longitudinal study examining the influence of
children’s PWB and orthodontic treatment on CPQ11-14 reports. Only one psychological
factor was reported on each phase of the study (SE at baseline and PWB at follow-up)
because of the expected high correlation between SE and PWB. If both constructs were
concurrently assessed as independent variables using regression models, this may lead to
imprecise estimates of regression coefficients, slight fluctuations in correlation or number
65
of cases may lead to large differences in regression coefficients. In addition, this may
increases the standard error of coefficients, thus reducing tests of significance (305,306).
In summary, the main objectives of this dissertation are twofold; first, to
determine changes in OH-QOL in children receiving orthodontic treatment compared to
those waiting for treatment; and second, to examine the moderational role of SE and
PWB on OH-QOL outcomes in these children. More specifically, this research project
was planned to address the following questions:
Is the CPQ11-14 sensitive to change in the context of orthodontic treatment?
Does SE impact OH-QOL reports in children with malocclusion?
Does orthodontic treatment improve children’s OH-QOL?
Does PWB influence OH-QOL in children receiving orthodontic treatment?
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CHAPTER 6: MATERIALS AND METHODS
Ethical Considerations
Study Approval
All aspects of the research project were approved by the Research Committee,
Faculty of Dentistry, University of Toronto; the Scientific Review Committee, University
of Toronto; and the Research Ethics Board, University of Toronto.
Confidentiality
Confidentiality was assured to patients in the consent letter. All data collected
would remain strictly confidential. No names or addresses would be released to the
Community Dental Health Services Research Unit, or to any family member or treating
staff member. Subjects’ dental records were accessed only to obtain clinical and
demographic information needed for interpretation of the results. Questionnaire responses
would be coded and stored in a locked filing cabinet in a secure location at the Faculty of
Dentistry. Only researchers involved in this project have access to this material. As per
the Tri-council Policy on Ethics guidelines, research data will be retained for at least five
years following completion of the study.
Informed Consent Process
A member of the research team verbally explained the details of the study to
prospective participants and their parents. The parents were also given a written
information sheet to clarify the aim, characteristics, and importance of the study, and to
ask for their participation. Parent’s consent and child’s assent were obtained to allow for
child’s participation. Negative consent was accepted without any prejudice being
67
attached to the children who chose not to participate. The same process of obtaining
consents from control subjects was undertaken. However, minor changes to the wording
of information sheets, consent, and assent forms were made to reflect that children were
waiting for treatment.
Methodology
Study Design
Treatment outcomes are ideally assessed using randomized controlled trials.
However, randomized controlled trials are not feasible in orthodontics for a number of
important reasons. These were discussed in detail in the Journal of Evidence Based
Dentistry in a paper titled “Are random controlled trials appropriate for orthodontics?”
(307). Perhaps the most relevant of these reasons are the ethical constraints of
randomization in orthodontics. Mew suggests that a prospective consecutive trial might
be the best and most feasible alternative in orthodontics (307).
Therefore, this three-year prospective consecutive cohort study was planned to
evaluate OH-QOL among children seeking orthodontic treatment. All subjects were
assessed twice: at baseline after consenting for participation in the study and two months
after finishing orthodontic therapy for the treatment group or after an equivalent duration
of time for controls awaiting treatment. A checklist developed by Wallander et al. to
guide the implementation of H-QOL measures in intervention studies was adapted to aid
in designing the present study (31).
68
Sampling Design
A convenience consecutive sampling design was employed. This design
minimizes volunteerism and other selection biases by consecutively selecting every
accessible person who meets the entry criteria. Overly specified inclusion criteria were
avoided to enhance generalizability of the results.
Selection Criteria
Treatment subjects were recruited from the graduate orthodontic clinic at the
University of Toronto during their initial assessment visit. Control subjects, on the other
hand, were recruited from the graduate orthodontic wait-list after their initial screening
visit. All children aged 11 to 14 years (birth years from 1990-1994), who were in good
general health and capable of reading at first-grade level English were included. Children
with cleft lip and/or palate or other gross cranio-facial disproportions requiring combined
orthodontic and surgical treatment were excluded.
Sample Size
We estimated that a 5% difference between groups would be clinically important.
This is a rough estimation of the minimal clinically important difference since evidence is
lacking in this area. Thus, the mean difference at follow-up would be four (corresponding
to a mean score of 24.3 in the treatment group vs. 20.3 in the comparison group) and the
common within-group standard deviation is 14.5. The sample size needed for this study
to achieve an 80% power to yield a statistically significant result at level of 0.05 is
approximately 60 per group. Justification of the proposed sample size was based on
CPQ11-14 scores in children awaiting orthodontic treatment (118). Assuming a response
rate of approximately 60%, more subjects were recruited. The number of subjects
69
recruited at baseline was 199. The total number of subjects at follow-up was 118
(Appendix A). Hence, the overall response rate was 59.29%.
Recruitment
The goals of the recruitment procedure were to obtain a sample that represents the
target population and meet the sample size requirement of the study. The sample
recruited for this dissertation was independent from that used in the validity study.
Children were recruited from the Orthodontic Clinic, Faculty of Dentistry, University of
Toronto. Data were collected as part of the usual screening procedure implemented to
assign patients for treatment. Eligible subjects were asked to participate in the study at
the assessment visit, after being triaged to the graduate orthodontic clinic. Subjects were
assured that their participation would not influence the outcome of their
treatment/assessment. Recruitment was terminated when the target sample size was
reached. Two dentally-trained research assistants, who were not involved in the
treatment, approached all subjects using a standardized approach. All measurements were
standardized.
Data Collection Procedure
All subjects completed the questionnaire unassisted by parents or researchers,
following explanation of the study purposes and questionnaire format, and obtainment of
parental consents and children assents (Appendix B). Tracking information including
mailing address and telephone numbers were recorded. Study casts were prepared using
alginate impressions and wax bite registrations. These casts were used to assess clinical
changes using the DAI and PAR indices at T1 and T2 time-points. The need for T2 PAR
and DAI assessment of control subjects was re-assessed after obtaining data from the first
70
15 cases. Since the scores in the wait-list group did not change, there was no need for
further occlusal assessment of control subjects.
Comprehensive orthodontic treatment of all treatment subjects was undertaken by
instructor-supervised graduate students. T2 Time point represents the assessment of
subjects two months after the completion of treatment for the treatment subjects, or after
an equivalent duration for control subjects. A yoked control design was employed to
ensure the comparability of follow-up duration. This design was first described by
Church in the early 60’s (308). It simply indicates that each time follow-up data are
collected from a treatment subject, a follow-up questionnaire is sent to a control subject.
This should approximate the overall T1-T2 time interval for treatment and control
groups.
Since implementing repeat mailing strategies and/or telephone reminders may
improve response to postal questionnaires in health care research (309), a systematic
series of repeated contact attempts was implemented to minimize loss of control subjects
and incomplete follow-ups (310). First follow-up questionnaires were sent with a pre-
paid envelope and a hand-signed personalized letter (Appendix B-4). A reminder letter
and a second questionnaire were sent to non-respondents after 2 weeks. Non-responders
were then telephoned two weeks later. Data collection was terminated and a complete
database was compiled for data analysis in December of 2008.
T2 data included the same measures administered at T1. In addition to the two
global questions assessing satisfaction with dental aesthetics and function administered at
T1, four global transition ratings were included in the CPQ11-14 follow-up
questionnaires. These rated changes in the child's perception of oral health status, related
71
overall wellbeing, the way their teeth look, and the way their teeth come together, on a
seven-point scale ("Worsened a lot"; "Worsened somewhat"; "Worsened a little"; "Stayed
the same"; "Improved a little"; "Improved somewhat"; "Improved a lot compared to the
first time they filled the questionnaire") (Appendices D and E). The repeated
administration of the questionnaires to both groups allowed direct comparison between
scores at baseline and follow-up.
Quality Control and Data Management
An electronic operational folder was developed to document recruitment,
measurement procedures, variables definition, database creation, data management,
analysis, and missing data. Data-entry control checks to identify and correct errors were
scheduled. A list of eligible, approached, accepted, rejected, and completed subjects was
created. Reasons for rejections to participate or loss at follow-up were recorded
(Appendix A). Any changes in original data were documented. Finally, regular back up
and creation of separate data sets for analysis, archiving, and storing original data were
implemented.
Budget
The Community Dental Health Services Research Unit funded this study. An
estimated sample size of 100 in each group was used to calculate costs. Each study model
cost CDN$25 per control subject. Printing and mailing follow-up questionnaires cost
approximately CDN$500. PAR ratings cost approximately CDN$2000. Therefore, the
total budget needed was approximately CDN$5000.
72
Analytic Approach
Data analysis was carried out using SPSS (Statistical Package for Social Sciences)
version 12. Statistical analysis is detailed in each of the papers presented in Chapter 7 of
this dissertation.
Measures
Subjects’ OH-QOL was assessed using the CPQ11-14 while their SE and PWB
was assessed using the CHQ-CF87. The DAI was used to determine the severity of
malocclusion and the PAR was used to evaluate normative outcomes of orthodontic
treatment. The following measures represent the major variables of the study. Each will
be discussed with respect to scale description, validity and reliability, and strengths and
weaknesses.
o Self-reported measures
The Child Perception Questionnaire (CPQ11-14)
The Child Health Questionnaire (CHQ-CF87)
o Normative measures
The Dental Aesthetic Index (DAI)
The Richmond Peer Assessment Rating (PAR)
The Child Perceptions Questionnaire (CPQ11-14)
Description of the scale. This study uses the CPQ11-14 as a measure of OH-QOL
(Appendix C) (118). The measure was described in depth in Chapter 3 of this
dissertation.
73
Validity and Reliability. The instrument has been tested and validated in clinical
populations similar to that of the current investigation (Table 3). Thus, the psychometric
properties of the CPQ11-14 have been well established.
Strengths and Weaknesses. The CPQ11-14 is the first standardized self-report
child OH-QOL measure that accounts for developmental differences (118). Its
longitudinal psychometric properties have been recently evaluated and found to be
acceptable in the context of orthodontic treatment (151,156).
The Child Health Questionnaire (CHQ-CF87)
Description of the scale. The CHQ-CF87 is a generic pediatric H-QOL
instrument (96) that was developed according to the 1946 WHO multidimensional
definition of health (28). This self-report child-format questionnaire consists of 87 items
designed to tap into the physical and psychosocial experiences of children aged 11- to 17-
years. As noted earlier, only two of the CHQ-CF87 subscales were used in this study: the
SE (14 items) and the PWB (16 items) subscales. This helped reduce the child response-
burden while still measuring psychological attributes relevant to the scope of this study.
The SE subscale of the CHQ-CF87 (Appendix F) recognizes that SE is an
important multidimensional concept that emerges during pre-adolescent development and
continues to be shaped and redefined through adulthood (311). Child and parents
interviews were used to develop the SE scale of the CHQ-CF87. The CHQ-CF87
includes items assessing satisfaction with school and athletic ability, looks or appearance,
ability to get along with others and family, and life overall. Thus, the following
components of SE are assessed: social confidence, school abilities, and self regard (247).
Responses were measured along a five-level response continuum that ranges from "very
74
satisfied" to "very unsatisfied". Low SE score indicates significant dissatisfaction with
abilities, looks, family/peer relationships and life overall.
The PWB scale (Appendix G) originated from a scale developed by Dupuy (312).
It measures the frequency of both negative and positive experiences. There are items to
capture anxiety, depression and happiness. Frequency was captured using a five-level
continuum that ranges from "all of the time" to "none of the time".
Validity and Reliability. The CHQ-CF87 has undergone extensive psychometric
evaluation and been shown to be a reliable and valid measure in healthy schoolchildren.
The CHQ-CF87 has demonstrated good test-retest reliability and internal consistency.
(96,313-320).
Strengths and Weaknesses. The majority of child and adolescent SE and PWB
measures that were available prior to the CHQ-CF87 lacked sufficient evidence
concerning their validity and interpretation of scores relative to a normative sample, or
required the use of a trained interviewer (321,322). The CHQ-CF87 addresses these
caveats. It is appropriate for use as a self-completion measure for children aged 11 years
upwards. Several reviews recommend the use of the CHQ-CF87 to assess children’s H-
QOL (323-326). The length of the instrument, however, limits its application. Therefore,
we decided to administer only the two sub-scales that are relevant to the context of the
present study; SE and PWB.
The Dental Aesthetic Index (DAI)
Description of the index. The DAI indicates the severity of malocclusion by
fitting a score on a continuum of dental aesthetics on the social acceptability scale of
occlusal conditions. Hence, the DAI can serve as an orthodontic treatment need index,
75
because it can indicate, for any set of occlusal measurements, the amount of deviation
from social norms for aesthetic dental appearance (13).
A DAI score is produced using a number of objective physical measurements of
occlusal traits associated with dental aesthetics as perceived by the public. Ten simple
intraoral measurements of occlusal traits are recorded and multiplied by a pre-determined
weight. The products are summed and a constant is added. This calculation procedure
identifies deviant occlusal traits and links clinical and aesthetic components
mathematically to produce a single score (Appendix H). The sum obtained is the DAI
score for the person being assessed. An example of the equation for a DAI score is as
follows:
The score can be placed on the social acceptability scale of occlusal conditions to
determine the percentile score for that person on a dental aesthetic continuum from 0
(most socially acceptable) to 100 (least socially acceptable), thus establishing societal
norms for dental aesthetics (Figure 4) (327). The social acceptability scale of occlusal
conditions is based on lay populations’ aggregate judgments of the social acceptability of
two different sample sets of 100 occlusal configurations. The DAI is the standard double
cross-validated regression equation that links objective measurements of occlusal
morphology with societal norms for socially acceptable dental appearance. The
76
theoretical concept underlying the DAI predicts that the more a person’s dental
appearance deviates from excellent, the more likely it is that the person will experience
social handicaps, and therefore he/she needs orthodontic treatment (328).
Figure 4: Distribution of standard DAI scores and their cumulative percentages (Reproduced from the DAI manual-1986: Page 11)
Validity and Reliability. Studies in the United States, as well as internationally,
show the validity and reliability of the DAI for prospective orthodontic patients. DAI
scores were significantly associated with student and parents’ perceptions of orthodontic
77
treatment need (13,328) and were a good predictor of future fixed orthodontic treatment
(185,329,330). Further, agreement between orthodontists' decisions and the DAI scores in
a sample of 1337 dental models was approximately 90% (327).
Strengths and Weaknesses. The DAI was chosen for this study because it
mathematically links the perceptions of aesthetics with anatomic trait measurements. Not
only this obviates the need for two separate instruments that cannot be combined as in the
Index of Complexity, Outcome, and Need (4) or the IOTN (329), but it also makes DAI
scores the closest to correspond to consumers’ assessment of perceived orthodontic
treatment need. Further, this index is relatively easy to use by trained dental auxiliaries
(331). A DAI score can be obtained clinically or from a study model, without using
radiographs. Therefore, it is not surprising that the DAI has been adopted by the WHO as
a cross-cultural index. Nonetheless, like other occlusal indices, the DAI does not account
for facial aesthetics.
Richmond Peer Assessment Rating (PAR)
Description of the index. The PAR was introduced by Richmond to objectively
assess the professional outcomes of orthodontic treatment (332,333). It is a commonly
used, reliable, and reproducible index that is well known on national and international
levels. The index assigns a score to a particular malocclusion trait and multiplies this
score by a weighting. The weighting factors were established by a British panel of 74
dentists (332,333). The sum of scores represents the extent of departure from ideal
occlusion. The index takes into account maxillary and mandibular anterior crowding or
spacing, buccal segment relationships (anterio-posterior, transverse, and vertical
direction), overjet, anterior crossbites, overbite, and midline deviations (Appendix I). The
78
ways with which the PAR index could be used to determine treatment effectiveness are
twofold: a reduction in the overall PAR score and percentage reduction in the PAR score.
Comparing treatment results, the PAR index would categorize the change as either
"Worse- No different", "Improved," or "Greatly improved". Richmond suggested that a
"high standard orthodontic treatment" should indicate an overall reduction of at least 70%
in the PAR score (332-334).
Validity and Reliability. The PAR has been extensively used to assess effects of
treatment (335-337). It has consistently demonstrated excellent reliability and superb
agreements with orthodontists’ opinions of treatment outcomes (338-341).
Strengths and Weaknesses. Although the PAR offers uniformity and
standardization in assessing the objective outcomes of orthodontic treatment, it does not
consider the aesthetic value directly. Dental aesthetics is assessed only by considering
anterior alignment (340). Therefore, the PAR has several shortcomings. For example, no
account is taken of features such as facial profile, occlusal function, or iatrogenic damage
resulting from treatment. Its assessment is relatively crude and does not consider tooth
inclination, angulations, posterior arch alignment, or arch width (339). Moreover, it can
be very difficult to use in mixed dentition cases (342). Most importantly, PAR scores
represent only one aspect of orthodontic treatment outcome as it does not include the
patient’s perspective (343).
79
CHAPTER 7: RESULTS
The results from this study are presented in four manuscripts that comprise this
chapter. Each of these manuscripts addresses one objective of the dissertation.
Manuscript I, “Is the child OH-QOL questionnaire sensitive to change in the
context of orthodontic treatment?”, describes the longitudinal psychometric properties of
the CPQ11-14. This manuscript has been published in the Journal of Public Health
Dentistry 2008 Fall; 68(4):246-8.
Manuscript II, “Impact of self-esteem on the oral health-related quality of life of
children with malocclusion,” covers the main baseline findings. It has been published in
the American Journal of Orthodontics and Dentofacial Orthopedics 2008; 134:484-9.
Manuscript III, “Does orthodontic treatment improve children’s oral health-
related quality of life?”, presents the longitudinal comparison of OH-QOL reports in
children who received orthodontic treatment and children who did not. It has been
submitted to Community Dentistry and Oral Epidemiology, and is currently under
revision.
Manuscript IV, “Does psychological wellbeing influence oral health-related
quality of life in children receiving orthodontic treatment?”, addresses the role of
psychological factors in moderating children’s response to OH-QOL questionnaires. It
also examines the analytic implications of such results. It has been accepted for
publication in the American Journal of Orthodontics and Dentofacial Orthopedics. As
indicated earlier, only one psychological factor was reported on each phase of the study
(SE at baseline and PWB at follow-up) because of the high correlation between the two
constructs (r=0.63; p<0.001).
80
Manuscript I: Is the Child Oral Health Quality of Life Questionnaire Sensitive to Change in the Context of Orthodontic Treatment? A Brief
Communication
81
Is the Child Oral Health Quality of Life QuestionnaireSensitive to Change in the Context of OrthodonticTreatment? A Brief CommunicationShoroog Agou, BDS; Monika Malhotra, D.DS, MSc, FRCD; Bryan Tompson, D.DS, D. ORTHO,D. PAEDO, FRCD(C), FACD; Preeti Prakash, D.DS; David Locker, DDS, PhD, DSc, FCAHS
Abstract
Objective: This study aimed to assess the ability of the Child Oral Health Qualityof Life Questionnaire (COHQoL) to detect change following provision of orthodontictreatment. Methods: Children were recruited from an orthodontic clinic just prior tostarting orthodontic treatment. They completed a copy of the Child PerceptionQuestionnaire, while their parents completed a copy of the Parents PerceptionQuestionnaire and the Family Impact Scale. Normative outcomes were assessedusing the Dental Aesthetic Index (DAI) and the Peer Assessment Rating (PAR)index. Change scores and effect sizes were calculated for all scales. Results:Complete data were collected for 45 children and 26 parents. The mean age was12.6 years (standard deviation = 1.4). There were significant pre-/posttreatmentchanges in DAI and PAR scores and significant changes in scores on all threequestionnaires (P < 0.05). Effect sizes for the latter were moderate. Global transitionjudgments also confirmed pre-/posttreatment improvements in oral health and well-being. Conclusion: The results provide preliminary evidence of the sensitivity tochange of the COHQoL questionnaires when used with children receiving orthodon-tic treatment. However, the study needs to be repeated in different treatment settingsand with a larger sample size in order to confirm the utility of the measure.
Key Words: children, malocclusion, oral-related quality of life, validity,responsiveness
IntroductionThe process of developing and
evaluating oral health-related qualityof life measures involves an ongoingassessment of the performance of themeasure in different populations andvarious contexts. This is particularlyimportant with respect to genericmeasures which were developed tobe used as outcome indicators insurveys and clinical trials. The ChildOral Health Quality of Life Question-naire (COHQoL) is a generic instru-ment designed to assess the adverseimpacts of oral conditions on childrenaged 11-14 years (1-3). It consists ofquestionnaires for children [ChildPerception Questionnaire (CPQ11-14)] and parents [Parents PerceptionQuestionnaire (PPQ)], and a Family
Impact Scale (FIS) also completed byparents. The cross-sectional constructvalidity and test–retest reliability ofthe questionnaires have been estab-lished (4). The sensitivity of theCPQ11-14 to variations in orthodonticstatus has also been demonstrated(5). However, a key property of anymeasure used to evaluate a therapeu-tic intervention is sensitivity tochange. To date, no studies haveassessed the utility of the COHQoL asan evaluative measure.
Consequently, we undertook astudy of 11- to 14-year-old childrenwith malocclusions who receivedorthodontic therapy to determine ifthe CPQ11-14, PPQ, and FIS wereable to detect pre-/posttreatmentchanges in the oral health quality of
life of these children. In assessingsensitivity to change, there are threeissues that need to be considered,namely responsiveness, longitudinalconstruct validity, and the minimalimportant difference (4,5).
MethodsStudy Design. This study uti-
lized a single group before-and-afterdesign to assess changes in oralhealth-related quality of life follow-ing orthodontic treatment.
Study Subjects. Participantswere 11- to 14-year-old children withclinically identified malocclusions asdefined by the Dental Aesthetic Index(DAI) (6) and the Peer AssessmentRating (PAR) (7). The children wereconsecutively recruited during theirfirst orthodontic screening visit at theFaculty of Dentistry, University ofToronto. To be eligible, a child had tobe fluent in English and be in goodgeneral health. Children with severedento-facial deformities were ex-cluded. Parents’ consent and chil-dren’s assent were obtained, and theUniversity Research Ethics Boardapproved all study procedures. Com-prehensive orthodontic treatment ofan average duration of 28 months wasprovided to all subjects. Follow-updata were collected at the first recallappointment after treatment wascompleted. If the parent/caregiverfailed to attend the recall appoint-ment, the questionnaire was mailedto their home address with a self-addressed envelope. A second copywas mailed if the follow-up question-naire had not been returned within 1month.
Send correspondence and reprint requests to Shoroog Agou, Faculty of Dentistry, University of Toronto, 124 Edward Street, Toronto, ON, CanadaM5G 1G6. Tel.: 416-979-4912 extension 2; Fax: 416-979-4936; e-mail: [email protected]. Shoroog Agou, Monika Malhotra, Bryan Tompson,Preeti Prakash, and David Locker are with the Faculty of Dentistry, University of Toronto, Toronto, ON, Canada. Manuscript received: 1/3/08;accepted for publication: 2/2/08.
Vol. ••, No. ••, •• 1
© 2008 American Association of Public Health DentistryDOI: 10.1111/j.1752-7325.2008.00093.x
Data Collection. Data wereobtained using the CPQ11-14 (1),PPQ (2), and FIS (2). The followingsubscale scores were created for theCPQ11-14 and PPQ by summing theresponses to items organized intoconceptually distinct subscales: oralsymptoms (OSs), functional limita-tions (FLs), emotional well-being(EWB), and social well-being (SWB).Included in the follow-up CPQ11-14and PPQ questionnaires were single-item global transition ratings pertain-ing to change in subjects’ perceptionof dental appearance and occlusion,oral health, and overall well-being asa result of orthodontic treatment.These were scored on a 7-point scaleranging from “improved a lot” to“worsened a lot.”
Pre- and posttreatment studymodels were taken to assess thechild’s occlusion using the DAI andPAR. The ratings were undertaken bythree calibrated examiners. Intra-examiner reliability for the DAI raterswas high with intraclass correlationcoefficients (ICCs) of 0.98, 0.91, and0.98, respectively. The ICC for inter-examiner reliability was 0.80. For thePAR raters, ICCs for intra-examinerreliability were all 0.99 and forinter-examiner reliability the ICC was0.95.
Data Analysis. Change scores forthe overall CPQ11-14, PPQ, and FISwere computed by subtracting post-treatment scores from pretreatmentscores. Paired t-tests were used to testthe statistical significance of thechanges. Change scores were alsocalculated for the DAI and PAR andevaluated using paired t-tests. The Pvalue for all tests was set at P < 0.05.The responsiveness of the question-naire and clinical measures was deter-mined by the calculation of effectsizes. Effect size (d) statistics werecalculated by dividing the mean of thechange scores by the standard devia-tion (SD) of the pretreatment scores,in order to give a dimensionlessmeasure of the effect. Effect sizestatistics of <0.2 indicate a smallclinically meaningful magnitude ofchange, 0.2-0.7 a moderate change,and >0.7 a large change (8). Assess-ment of longitudinal construct validity
and calculation of the minimal impor-tant differences were limited by a lackof variation in responses to the globaltransition ratings.
ResultsSample Characteristics. Com-
plete baseline and follow-up datawere available for 45 children and 26parents. The mean age of those chil-dren was 12.6 years (SD = 1.4) andalmost 60 percent were girls.
The mean DAI and PAR scores atbaseline and follow-up are presentedin Table 1. As expected, significantdeclines were observed with effectsizes exceeding 2.0 (P < 0.001). Dataon the pre-orthodontic interventionand post-orthodontic interventionCOHQoL scores with effect sizes arealso presented in Table 1. With theexception of the FL and SWB sub-scales of the PPQ, all scales andsubscales demonstrated significantreductions following orthodontictreatment (P < 0.05). This reductionwas associated with effect sizesreflecting moderate changes. By sub-scale, the largest change score wasobserved for the EWB subscale of
the CPQ11-14, and the OS subscaleof the P-CPQ.
Table 2 shows the distribution ofresponses to the global transitionitems for children and parents. For allitems, the majority reported that theyimproved a lot or improved some-what. Longitudinal construct validityis indicated if those reportingimprovement on the global transitionratings have positive change scores,those reporting deterioration havenegative change scores, and thosewho report no change have scoresclose to zero. The skewed distribu-tion and small cell sizes precludedsuch assessment. Similarly, themethod recommended by Juniperet al. (9) for calculating minimalimportant differences could not beemployed. However, those childrenwho reported that their overall well-being had improved somewhat hadmean CPQ change scores of 6.6, andthose who reported improving a littlehad mean change scores of 5.0.Although based on small numbers ofsubjects, these provide a preliminaryestimate of the minimal importantdifference for the CPQ11-14.
Table 1Comparison of the Child Oral Health Quality of Life Questionnaire
(COHQoL) Overall, Domain Scores, and Clinical Measures Before andAfter Orthodontic Treatment
COHQoL scores: pre-/posttreatment
Pretreatment Posttreatment P value* Effect size
CPQ11-14 60.7 50.8 <0.001 0.55Oral symptoms 12.0 10.3 <0.01 0.50Functional limitation 14.8 13.1 <0.05 0.45Emotional well-being 15.0 11.4 <0.001 0.60Social well-being 18.9 16.0 <0.01 0.44
PPQ 53.8 46.3 <0.05 0.39Oral symptoms 12.2 9.9 <0.01 0.56Functional limitation 11.5 11.7 NS –Emotional well-being 14.2 10.3 <0.01 0.51Social well-being 15.9 14.5 NS 0.20
Family Impact Scale 20.7 17.6 <0.01 0.42
Clinical measures: pre-/posttreatmentDAI 36.6 18.2 <0.001 2.1PAR 30.4 4.2 <0.001 2.2
* Paired t-test.Sample sizes: child n = 45; parents n = 26.Effect sizes: pretreatment score–posttreatment score/standard deviation of baseline score.CPQ11-14, Child Perception Questionnaire; PPQ, Parents Perception Questionnaire; DAI, DentalAesthetic Index; PAR, Peer Assessment Rating; NS, not significant.
Journal of Public Health Dentistry2
DiscussionThis study aimed to document
changes in the oral health-relatedquality of life of children having orth-odontic treatment, and, in doing so,to examine the evaluative propertiesof the COHQoL questionnaires. Theprovision of orthodontic treatmentwas associated with substantial andstatistically significant improvementsin scores on the CPQ11-14, PPQ, andFIS (Table 1). Hence, the COHQoLwas found to be sensitive to changein the context of orthodontic treat-ment for children with malocclusion.
Responsiveness and longitudinalconstruct validity are importantcharacteristics of oral health-relatedquality of life instruments which areto be used as evaluative measures.Effect sizes were used in this study tocompare the relative responsivenessto change resulting from orthodonticinterventions using both subjectiveand clinical measures. The data inTable 1 provide evidence that respon-siveness was acceptable for all threescales of the COHQoL with moderateeffect sizes observed. These effectsizes were comparable to thosereported for other widely used instru-ments such as the OHIP-14 (10). Thechanges in COHQoL scores were par-alleled by substantial decreases in thescores on the two normative indicesemployed. Some minor concernsremain because of the clustered dis-tribution of responses to the globaltransition ratings, shown in Table 2.This precluded assessment of longitu-dinal construct validity and the propercalculation of the minimal important
difference. However, the fact that themajority of children reported consid-erable improvement as a result oftreatment supports the validity of themeasure as an indicator of change.
Ideally, this study should haveincluded a comparison group whichdid not receive treatment. This wouldhave allowed comparison of changesin scores over time between a treatedgroup and one who had not receivedtreatment. However, our objectivewas not to evaluate the benefit to bederived from orthodontic treatment;rather, it was to assess the sensitivityto change of a measure. A study isunderway to compare change scoresof a treated and an untreated group ofchildren with malocclusions whichcan address the issue of treatmentefficacy. Its larger sample size willalso allow the sensitivity to change ofthe COHQoL to be explored morefully. Nevertheless, the resultsreported here suggest that theCOHQoL is a suitable measure to usewhen the aim is to assess changes inchild oral health-related quality of life.The effect sizes we report and thepreliminary estimate of the minimalimportant difference can also providethe basis for sample size calculationsfor treatment efficacy studies.
The children in this study areamong those with the worst maloc-clusions in their age group. Thismeans that the sensitivity of theinstruments to more subtle differ-ences and changes in child oralhealth requires further investigation.Future work with the COHQoL mea-sures should determine whether
there are differences in quality of lifeoutcomes associated with differentorthodontic intervention strategiessuch as multiple extractions versusfunctional appliance therapy.
References1. Jokovic A, Locker D, Stephens M, Kenny
D, Tompson B. Validity and reliability ofa measure of child oral health-relatedquality of life. J Dent Res. 2002;81:459-63.
2. Jokovic A, Locker D, Stephens M, KennyD, Tompson B, Guyatt G. Measuringparental perceptions of child oral health-related quality of life. J Public HealthDent. 2003;63:67-72.
3. Locker D, Jokovic A, Stephens M, KennyD, Tompson B, Guyatt G. Family impactof child oral and oro-facial disorders.Community Dent Oral Epidemiol.2002;30:438-48.
4. Foster Page LA, Thomson WM, JokovicA, Locker D. Validation of the Child Per-ceptions Questionnaire (CPQ 11-14). JDent Res. 2005;84:649-52.
5. Locker D, Jokovic A, Tompson B,Prakash P. Is the Child Perceptions Ques-tionnaire for 11 to 14 year olds sensitiveto variations in orthodontic status?Community Dent Oral Epidemiol. 2007;35:179-85.
6. Cons NC, Jenny J, Kohout FJ. DAI: theDental Aesthetic Index. Iowa City:College of Dentistry, University of Iowa;1986.
7. Richmond S, Shaw WC, O’Brien KD,Buchanan IB, Jones R, Stephens CD,Roberts CT, Andrews M. The develop-ment of the PAR index: reliability andvalidity. Eur J Orthodont. 1992;14:180-7.
8. Cohen J. Statistical power analysis for thebehavioural sciences. 2nd ed. Hillsdale:Lawrence Erlbaum Associates; 1988.
9. Juniper E, Guyatt G, Willan A, Griffith L.Determining a minimal important changein a disease-specific quality of life ques-tionnaire. J Clin Epidemiol. 1994;47:81-7.
10. Locker D, Jokovic A, Clarke M. Assessingthe responsiveness of measures of oralhealth-related quality of life. CommunityDent Oral Epidemiol. 2004;32:10-8.
Table 2Distribution of Children and Parents’ Responses (%) to Global Questions About the Extent to Which
Appearance, Occlusion, Oral Health, and Life Overall Were Affected by Orthodontic Treatment
Appearance Occlusion Oral health Life effect
Global transition ratings Child Parent Child Parent Child Parent Child Parent
Improved a lot 86.7 97.2 86.7 88.9 48.9 72.2 44.4 61.1Improved somewhat 5.6 0 11.1 11.1 33.3 16.7 35.6 19.4Improved a little 2.8 2.8 0 0 6.7 2.8 11.1 11.1Stayed the same 0 0 2.2 0 11.1 5.6 8.9 8.3Worsened a little 0 0 0 0 0 2.8 0 0Worsened somewhat 0 0 0 0 0 0 0 0Worsened a lot 0 0 0 0 0 0 0 0
CPQ11-14 and Orthodontic Treatment 3
Manuscript II: Impact of Self-Esteem on the Oral Health-related Quality of Life of Children with Malocclusion
85
ORIGINAL ARTICLE
Impact of self-esteem on the oral-health-relatedquality of life of children with malocclusionShoroog Agou,a David Locker,b David L. Streiner,c and Bryan Tompsond
Toronto, Ontario, Canada
Introduction: The purpose of this study was to examine the relationship between self-esteem andoral-health-related quality of life (OHRQoL) in a sample of children seeking orthodontic treatment in Toronto,Ontario, Canada. Methods: This was a cross-sectional study of children aged 11 to 14 years, evaluating theassociations among the child perception questionnaire (CPQ11-14), the self-esteem subscale of the childhealth questionnaire, and the dental aesthetic index (DAI). Results: The CPQ11-14 scores were significantlyrelated to the self-esteem scores and the DAI ratings. Regression analysis showed that self-esteemcontributed significantly to the variance in CPQ11-14 scores. However, the amount of variance explained bynormative measures of malocclusion was relatively small. Conclusions: The impact of malocclusion onquality of life is substantial in children with low self-esteem. Compared with normative measures ofmalocclusion, self-esteem is a more salient determinant of OHRQoL in children seeking orthodontictreatment. Longitudinal data will be of value to confirm this finding. (Am J Orthod Dentofacial Orthop 2008;
134:484-9)The child perception questionnaire (CPQ11-14)is a generic oral-health-related quality of life(OHRQoL) instrument designed to assess the
adverse impacts of oral conditions in children aged 11to 14 years.1 The CPQ11-14 is becoming an increas-ingly popular tool in orthodontic outcome research,2
because of its demonstrable psychometric properties.3,4
However, when its performance was assessed againstclinical indicators, modest associations were often ob-served.3,5,6
The inconsistencies between clinical indicators andreported OHRQoL agree with anecdotal clinical expe-rience. Some children have remarkable levels of con-cern for the most minor anomalies, and, paradoxically,others are tolerant of severe occlusal problems. Moreadolescents with good occlusion who feel dissatisfiedwith their teeth have been reported.7-9 Moreover, pa-tients’ concerns regarding orthodontic treatment do notalways agree with professional evaluations.10,11 Ac-cordingly, it is reasonable to assume that the relation-ship between reported OHRQoL and malocclusion ismost likely mediated by other factors.6,12 Studies in the
From the University of Toronto, Toronto, Ontario, Canada.aPhD candidate, Faculty of Dentistry.bProfessor, Faculty of Dentistry.cProfessor, Baycrest Center for Geriatric Care and Department of Psychiatry.dAssociate professor, Faculty of Dentistry.Reprint requests to: Shoroog Agou, Faculty of Dentistry, University ofToronto, 124 Edward St, Toronto, Ontario, Canada M5G 1G6; e-mail,[email protected], September 2006; revised and accepted, November 2006.0889-5406/$34.00Copyright © 2008 by the American Association of Orthodontists.
doi:10.1016/j.ajodo.2006.11.021484
medical literature have stressed the importance ofinnate psychological attributes, such as self-esteem(SE), in predicting the effect of health conditions on thequality of life.13,14 Spilker15 advocated controlling forpsychological parameters whenever quality of life isused as a primary outcome. Few studies have examinedparallel associations in children seeking orthodontictreatment.16,17 In a study of Brazilian schoolchildren,those with low SE were found to be more sensitive tothe esthetic effects of malocclusion.17 Similarly, astudy of potential orthodontic patients in Nigeria foundthat children with high SE most frequently did notexpress orthodontic concerns.18
Although many cross-sectional studies reported sig-nificant associations between malocclusion and SE inadolescents,18-20 longitudinal evaluations often failed todocument a clear-cut cause-and-effect relationship.21-28
The findings of these studies should shed light on theway we view SE as an end point outcome in orthodon-tic psychosocial research. It also supports the argumentof the role of SE as an effect modifier. This hypothesisagrees with empirical psychological evidence that de-notes the stability of the SE construct as a personalresource that might moderate the effects of conditionsor events.29,30 Self-concept is broad ranging and relates topersonal self-concept (facts or one’s own opinions aboutoneself), social self-concept (one’s perceptions about howone is regarded by others), and self-ideals (what or howone would like to be).31 With this definition, it isunlikely that impaired perception of orofacial appear-
ance as a result of malocclusion would translate to
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Agou et al 485
diminished SE. The relationship between normative mea-sures of malocclusion, SE, and OHRQoL should beclarified if we are to meaningfully interpret the results ofclinical investigations using OHRQoL outcomes.
Therefore, we examined the role of SE as a medi-ator influencing OHRQoL outcomes in children seek-ing orthodontic treatment. We hypothesized that chil-dren with high SE would have better OHRQoL thanthose with low SE.
MATERIAL AND METHODS
Participants in the study were children aged 11 to14 years, attending orthodontic clinics at the Faculty ofDentistry, University of Toronto, in Canada. Mostchildren were motivated by their parents to seek orth-odontic consultation. A convenient consecutive sam-pling approach was used. The children were recruited attheir first visit for orthodontic screening. The parentssigned a consent form, and all children agreed toparticipate. To be eligible, the child had to be fluent inEnglish and in good general health. Children withsevere dentofacial deformities were excluded. TheUniversity Research Ethics Board approved all studyprocedures.
All children completed the CPQ11-14 and the SEsubscale of the child health questionnaire (CHQ-CF87)before treatment. The questionnaires were completedby the children unassisted by parents or investigators.The dental aesthetic index (DAI) was used to determinethe clinical need for orthodontic treatment. Age, sex,and ethnic background were recorded because of theirpotential associations with both outcome and explana-tory variables.24,32 Socioeconomic status, however, wasnot assessed because it was previously shown to haveno bearing on CPQ11-14 scores when examined insimilar groups.2,6
The CPQ 11-14 is a child OHRQoL instrument.The age-specific questionnaire (11-14 years) consists of37 items, grouped into 4 domains: oral symptoms (OS),functional limitations (FL), emotional well-being(EW), and social well-being (SW). Each item askedabout the frequency of events, as applied to the teeth,lips, and jaws, in the last 3 months. The responseoptions were “never, once or twice, sometimes, often,”and “every day or almost every day.” Although theinstrument is designed to yield an overall score, aseparate score can be generated for each of the 4subscales. Higher scores signify worse OHRQoL. Thevalidity and reliability of this questionnaire have beenestablished in clinical and general population sam-
ples.1,3,4The children’s SE was measured by using the SEsubdomain of the CHQ-CF87, a widely used andvalidated self-report instrument. The following dimen-sions of SE are captured in the 14-item measuredeveloped by Landgraf and Abetz33: satisfaction withschool and athletic ability, looks or appearance, abilityto get along with others and family, and perception oflife overall. Responses are given on a 5-point Likertscale (very satisfied to very unsatisfied). Low SE scoresindicate significant dissatisfaction with abilities, looks,family and peer relationships, and life overall. Specificinstructions confirming the generic nature of the mea-sure were added at the beginning of the questionnaire.
The severity of each child’s orthodontic conditionwas assessed by using study models taken at the initialvisit with a widely used orthodontic index, the DAI,34
which measures the social acceptability of a child’sdental appearance. The rating is based on the measure-ment of 10 occlusal traits; each trait is multiplied by aweight. The products are summed, and a constant isadded to give the DAI score; scores range from 13(most acceptable) to 100 (least acceptable) and can becollapsed into 4 malocclusion severity levels: 13 to 25,minor or none; 26 to 31, definite; 32 to 35, severe; and36 and over, handicapping.35
The DAI ratings were recorded by 3 trained andcalibrated examiners. To assess intra- and interexam-iner reliability, the raters independently assessed arandom 10% sample of the models and then reassessedthe models 1 week later. Intraexaminer reliability forthe DAI raters was almost perfect with intraclasscorrelation coefficients of 0.96, 0.91, and 0.97, respec-tively, and the interexaminer reliability was high at0.81.
Statistical analysis
The data were analyzed by using SPSS software(version 12, SPSS, Chicago, Ill). Additive scale andsubscale scores for the CPQ11-14 and the CHQ-CF87were calculated by summing the item response codes.Data analyses included descriptive statistics, bivariateanalyses, and multiple regression models.
RESULTS
One hundred ninety-nine children (102 girls, 97boys) entered the study. Their mean age was 12.7 years(SD, 1.1). Seventy-six percent of the subjects were white.The sample distribution of DAI categories was minormalocclusion (8.4%), definite malocclusion (27.2%), se-vere malocclusion (20.4%), and handicapping malocclu-sion (44%). The truncated distribution can be expectedin such a sample of children seeking orthodontic
treatment at a teaching institution. SE scores ranged
5
American Journal of Orthodontics and Dentofacial OrthopedicsOctober 2008
486 Agou et al
from 50 to 100 with a mean score of 84 (SD � 13.4).The sample mean SE score was not significantlydifferent from that of reported norms for normalschoolchildren (mean, 81.8; SD, 15.8).33 DAI scores,total, and individual subscale CPQ11-14 scores for highand low SE children are summarized in Table I. LowSE children had significantly higher total CPQ11-14,OS, FL, EW, and SW domain scores than high SEchildren even though they had similar malocclusions(DAI scores).
The Pearson correlation between the overall CPQ11-14and SE scores was significant (r � –0.43, P �0.01),indicating moderate negative association between the 2scales. Similar associations were observed between SEand all 4 CPQ11-14 subscales for the overall sampleand for the sample divided according to malocclusion
Table I. Summary statistics for the study variables
OS domain FL domain EWMean (SD) range Mean (SD) range Mean
Low SE children‡
(N � 71)6.6 (2.9) 6.9 (5.3) 7
0-14 0-23High SE children‡
(N � 128)5.2 (3.2)* 4.8 (4.1)* 4
0-17 0-19
*Difference statistically significant at P �0.01.†Difference statistically significant at P �0.001.‡SE classification, using norms reported by Landgraf and Abetz.33
Table II. Pearson correlation coefficient between reporaccording to malocclusion category‡
DAI category OS domain FL domai
Minor N � 16 �0.13 �0.49Definite N � 52 �0.15 �0.36†
Severe N � 39 �0.19 �0.24Handicapping N � 84 �0.25* �0.25*Overall sample N � 191 �0.27† �0.32†
*Correlation significant at 0.05 level (2-tailed).†Correlation significant at 0.01 level (2-tailed).‡Malocclusion classification, using cutoff points from Estioko et al.3
Table III. Pearson correlation coefficients between reporaccording to SE category‡
SE category OS domain FL dom
Low SE children‡ N � 71 0.05 0.04High SE children‡ N � 128 �0.08 0.14Overall sample N � 191 �0.02 0.09
*Correlation significant at 0.05 level (2-tailed).†Correlation significant at 0.01 level (2-tailed).‡SE classification, using norms reported by Landgraf and Abetz.33
severity (Table II): OS (r � –0.27, P �0.01); FL (r �
–0.32, P �0.01); EW (r � –0.42, P �0.01), and SW(r � �0.38, P �0.01). A significant, but weak, corre-lation was noted between the overall CPQ11-14 scoresand DAI scores (r � 0.16, P �0.05). When theassociation was examined according to the SE catego-ries, children with low SE had no correlation for DAIscores and CPQ11-14 scores (Table III).
Hierarchical multiple regression models were usedto explore the relationship between SE and CPQ11-14and its subscale scores. Two key issues were addressed:the total amount of variance explained, and the inde-pendent and separate variance contributions of theclinical condition (DAI scores) and psychological fac-tors (SE).
After controlling for age, sex, and ethnicity, the 2main effects (SE and DAI) were entered into the
in SW domain Total CPQ11-14 DAIange Mean (SD) range Mean (SD) range Mean (SD) range
7.1 (6.4) 28.4 (16.3) 33.7 (6.9)0-29 4-73 20-59
† 4.3 (4.8)† 19.4 (13.2)† 35.8 (9.0)0-24 3-68 17-74
al and subscale OHRQoL (CPQ11-14) scores and SE
EW domain SW domain Total CPQ11-14
�0.42 �0.33 �0.54*�0.55† �0.37† �0.45†
�0.41† �0.39* �0.39*�0.23* �0.24* �0.31†
�0.42† �0.38† �0.43†
tal and subscale OHRQoL (CPQ11-14) scores and DAI
EW domain SW domain Total CPQ11-14
0.04 �0.03 0.010.26† 0.28† 0.23*0.17* 0.19† 0.16*
doma(SD) r
.7 (5.8)0-24
.7 (4.9)0-24
ted tot
n
ted to
ain
regression equation and tested for overall significance.
American Journal of Orthodontics and Dentofacial OrthopedicsVolume 134, Number 4
Agou et al 487
Table IV summarizes the results of the regressionmodel and the total amount of variance, in overall andsubscale CPQ11-14 scores, explained by introducingeach variable.
Eighteen percent of the total variance in CPQ11-14scores was explained by the combined model. The ex-planatory power was highest for the EW scale (adjustedR2 � 0.17) and lowest for the OS subscale (adjusted R2 �0.04). As illustrated in the Figure, children with low SEconsistently reported worse OHRQoL across the differ-ent DAI categories than children with high SE.
Less than 2% of the variance in CPQ11-14 scoreswas explained by age, sex, or malocclusion as mea-sured by DAI scores. Of the total variance in CPQ11-14scores, approximately 17% was attributed to SE alone.Of the CPQ11-14 subscales individually, the contribu-tion of the main effect of SE was significant for allsubscales. As expected, the most pronounced effect wasfor the EW and SW subscales. The independent effectof DAI was small overall, but significant for both theEW and SW subscales. DAI ratings did not contribute
Table IV. Amount of variance explained for overall CP
Dependent variable Independent variable Total adjust
Total CPQ11-14 Step 1: DAI 0.183Step 2: SE
OS domain Step 1: DAI 0.036Step 2: SE
FL domain Step 1: DAI 0.106Step 2: SE
EW domain Step 1: DAI 0.166Step 2: SE
SW domain Step 1: DAI 0.144Step 2: SE
Fig 1. Error bars comparing CPQ11-14 scores betweenhigh and low SE children across the malocclusioncategories.
to the FL or OS subscales.
DISCUSSION
These results support the postulated mediator roleof SE when evaluating OHRQoL in children comingfor orthodontic treatment. This indicates that the child’spsychological profile can influence the social and emo-tional impacts of malocclusion, because those with highSE are more likely to report better OHRQoL.
This sample of Canadian children seeking orth-odontic treatment reported significantly more negativeoral impacts (mean CPQ11-14, 22.8; SD, 15.2) thanschoolchildren of comparable age in the United King-dom36 and New Zealand.3 The reported psychosocialimpacts are similar to those reported for Nigerianorthodontic patients, emphasizing the negative conse-quences of malocclusion.37
The tenuous but significant association betweenDAI scores and patient-based measures concurs withearlier studies.2,3,5,6,18 Since the correlation coefficientwas small, we cannot conclusively state that increasedmalocclusion severity produced a direct increase inCPQ11-14 scores. This was further confirmed by theminor independent contribution of DAI scores to thevariance in CPQ11-14 scores. Interestingly, CPQ11-14scores reported by children with low SE were notcorrelated with the normative severity of malocclusion(Table III). This seems to suggest that children withlow SE report negative OHRQoL impacts that do notnecessarily correspond to their orthodontic treatmentneeds. Obviously, there are many reasons that childrenseek orthodontic treatment, and these are not alwaysrelated to the severity of malocclusion.38
As hypothesized, high SE was associated withbetter OHRQoL. The moderately low correlation coef-ficient indicates that other factors might contribute toboth constructs. The variance in CPQ11-14 scores inchildren coming for orthodontic treatment was ex-plained by the child’s SE to a reasonable extent.39
Not surprisingly, analysis of the CPQ11-14 domain
4 and subscale scores
R2 change Standard beta t P value
0.017 0.18 2.70 �0.010.166 �0.41 �6.26 �0.001
�0.013 0.00 0.01 0.990.049 �0.23 �3.27 �0.010.010 0.10 1.45 0.150.096 �0.32 �4.57 �0.0010.015 0.21 3.11 �0.010.141 �0.39 �5.90 �0.0010.036 0.19 2.81 �0.010.108 �0.34 �4.96 �0.001
Q11-1
ed R2
correlations showed that SE and DAI mostly contrib-
American Journal of Orthodontics and Dentofacial OrthopedicsOctober 2008
488 Agou et al
uted to the child’s emotional and social well-being.This is logical when we consider that the most commonreason for seeking orthodontic treatment is to correctdental esthetics.11,40,41 As previously demonstrated bymany investigators, it is unlikely that oral symptoms(bleeding gums, pain in the teeth)42-44 and functionallimitations (speech problems, difficulty in mouth open-ing, and eating) are greatly influenced by psychologicalfactors or the normative severity of malocclusion.45,46
The SE results support the findings of Marques et al,17
who identified low SE as a risk factor for worseningmalocclusion esthetic effects, and Onyeaso,18 whofound significant positive associations between SE andorthodontic concern. Our findings are also consistent withassociations reported for different age groups.16,47 Theeffect of personality traits on perceived impacts ofdental esthetics is similar to that reported by Klageset al.48
This study had some limitations. The lack of tem-porality limited the confidence in establishing thedirection of association in this study. Although SE wassignificantly associated with OHRQoL, the questionremains whether SE improves OHRQoL, or vice versa.There are arguments for the association in eitherdirection or both directions.49 The reported resultsrepresent only the baseline of an inception-controlledcohort study. All patients will be followed and assessedafter orthodontic treatment to evaluate changes inOHRQoL and to ascertain the proposed hypothesis.Meanwhile, our belief that SE is a personal resourcethat facilitates coping with less favorable conditionssuch as poor dental esthetics is corroborated by manypsychological studies including Harter’s popular articleabout SE.50
This study also has implications for topical orth-odontic decision-making research. The current consensusis that decisions should be based on individual psychos-ocial indications.51,52 The self-report CPQ11-14 is poten-tially a proxy measure to replace subjective clinicalopinions for determining treatment timing especially forpsychosocially compromised children. This is becausethe CPQ11-14 reflects the contribution of the child’s SEin ameliorating the clinical severity of malocclusion;this allows for prioritization of treatment needs accord-ing to child’s level of daily disruption. With thisapproach, dental services should correspond moreclosely to consumer-based health needs and focus moreon improving the quality of life.
CONCLUSIONS
SE significantly impacted the relationship betweenmalocclusion and well-being in children seeking orth-
odontic treatment. Longitudinal data will be of value toconfirm this finding. Investigators should consider theneed to control for baseline psychological attributeswhen assessing OHRQoL outcomes in orthodontics.
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35. Estioko LJ, Wright FA, Morgan MV. Orthodontic treatment needof secondary schoolchildren in Heidelberg, Victoria: an epide-miologic study using the dental aesthetic index. Community
Dent Health 1994;11:147-51.36. Nuttall NM, Steele JG, Evans D, Chadwick B, Morris AJ, Hill K.The reported impact of oral condition on children in the UnitedKingdom, 2003. Br Dent J 2006;200:551-5.
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38. O’Brien K, Kay L, Fox D, Mandall N. Assessing oral healthoutcomes for orthodontics—measuring health status and qualityof life. Community Dent Health 1998;15:22-6.
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40. Gosney MB. An investigation into some of the factors influenc-ing the desire for orthodontic treatment. Br J Orthod 1986;13:87-94.
41. Mohlin B, al-Saadi E, Andrup L, Ekblom K. Orthodontics in12-year old children. Demand, treatment motivating factors andtreatment decisions. Swed Dent J 2002;26:89-98.
42. Davies SJ, Gray RJ, Linden GJ, James JA. Occlusal consider-ations in periodontics. Br Dent J 2001;191:597-604.
43. Henrikson T, Nilner M. Temporomandibular disorders, occlu-sion and orthodontic treatment. J Orthod 2003;30:129-37.
44. Koroluk LD, Tulloch JF, Phillips C. Incisor trauma and earlytreatment for Class II Division 1 malocclusion. Am J OrthodDentofacial Orthop 2003;123:117-26.
45. English JD, Buschang PH, Throckmorton GS. Does malocclu-sion affect masticatory performance? Angle Orthod 2002;72:21-7.
46. Onyeaso CO, Aderinokun GA. The relationship between dentalaesthetic index (DAI) and perceptions of aesthetics, function andspeech amongst secondary school children in Ibadan, Nigeria. IntJ Paediatr Dent 2003;13:336-41.
47. Mandall NA, McCord JF, Blinkhorn AS, Worthington HV,O’Brien KD. Perceived aesthetic impact of malocclusion andoral self-perceptions in 14-15-year-old Asian and Caucasianchildren in greater Manchester. Eur J Orthod 2000;22:175-83.
48. Klages U, Bruckner A, Zentner A. Dental aesthetics, self-awareness, and oral health-related quality of life in young adults.Eur J Orthod 2004;26:507-14.
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Dentofacial Orthop 2004;125:657-67.
Manuscript III: Does Orthodontic Treatment Improve Children’s Oral Health Related Quality of Life?
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Title page
Does Orthodontic Treatment Improve Children’s Oral Health Related Quality of Life? Shoroog Agou1, David Locker1, Bryan Tompson1 and David L. Streiner2 1 Faculty of Dentistry, University of Toronto, Toronto, Ontario, Canada
2 Baycrest Center, and Department of Psychiatry, University of Toronto
Running head: CPQ11-14, orthodontics, and oral health related quality of life Key words: CPQ11-14, orthodontics, oral-health related quality of life Address for correspondence: Shoroog Agou Faculty of Dentistry University of Toronto 124 Edward Street Toronto Ontario Canada M5G 1G6 Tel: (416) 979-4907 ext 4664 Fax: (416) 979-4936 e-mail: [email protected] Agou S, Locker D, Streiner DL, Tompson B. Does Orthodontic Treatment Improve Children’s Oral Health Related Quality of Life? Community Dentsitry and Oral Epidemiology
Number of words in Abstract: Number of words in the abstract and the text: Number of tables: 3 Number of figures: 2 Number of cited references: Based on a thesis submitted to the school of graduate studies, University of Toronto, in partial fulfillment of the requirements for the PhD degree. A preliminary report was presented at the International Association of Dental Research meeting in Toronto (2008).
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ABSTRACT
OBJECTIVES: The main objective of this longitudinal clinical study is to establish Oral
Health Related Quality Of Life (OH-QOL) gains following orthodontic treatment
compared to a sample of untreated controls. The secondary objective is to confirm the
longitudinal psychometric properties of the Child Perception Questionnaire (CPQ11-14).
METHODS: In this prospective clinical study, children receiving treatment were
compared to wait-list controls awaiting treatment. The CPQ11-14 was administered at
baseline and at follow-up. Global Transition Ratings (GTR) were used to assess
satisfaction with dental appearance and function. Occlusal changes were measured using
the Dental Aesthetic Index (DAI).
RESULTS: 118 eleven to 14-year-old children attending the orthodontic clinics at the
University of Toronto participated in this study. Treatment subjects reported significantly
better CPQ11-14 scores at follow-up (p<0.05) compared to untreated controls. At the
sub-domain level, no changes were observed for the oral symptoms and functional
limitations sub-domains. However, emotional and social wellbeing sub-domains changed
significantly after providing orthodontic treatment. Analysis of responses to GTR showed
that orthodontic treatment contributed significantly to increased satisfaction with dental
appearance and function. CPQ11-14 change scores closely corresponded to children’s
responses to GTR (p<0.001).
CONCLUSIONS: The results support the hypothesis that orthodontic treatment improves
OH-QOL outcomes in children. Improvements were most evident for the social and
emotional wellbeing sub-domains of CPQ11-14. Association between CPQ11-14 change
scores and GTR helps in confirming the longitudinal psychometric properties of the
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CPQ11-14 instrument. The findings are yet to be examined in view of important
contextual factors moderating the relationship between orthodontics and OH-QOL.
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Introduction
In 1946, the World Health Organization defined health as being not only the absence of
disease but also the presence of physical, mental, and social well-being (1). Since then,
the concept of oral health related quality-of-life (OH-QOL) has become increasingly
more important in oral health practice and research. The field of orthodontics, however,
has lagged behind. Only recently, a number of leading scientists in the field of
orthodontic outcome research have emphasized that the measurement of OH-QOL
outcomes is central to the development of oral health services (2-5)
With this new research direction, the use of OH-QOL measures as an outcome
assessment tool in orthodontic research has increased exponentially. The number of
studies listing “OH-QOL” as a key word in the orthodontic literature in the MEDLINE
database has increased from only eight studies in the early nineties (1991-1996), to just
less than 30 papers during the subsequent five years (1997-2002), to over 100 articles
published in the last five years (2003-2008). These numbers clearly indicate that
orthodontic researchers are moving away from the traditional clinician-centered model
towards the modern patient-centered model of assessment. These new research
movements are, in fact, both important and timely considering the significant debates
regarding the long term psychosocial benefits of orthodontic treatment (6,7).
As would be expected, early studies examining the effect of conventional orthodontic
treatment on OH-QOL reports were, for the most part, cross-sectional in nature. Most
studies found associations between orthodontics and better OH-QOL or between
increased treatment needs and worse OH-QOL (8-17). For instance, in a survey of
Brazilian schoolchildren, adolescents who had completed orthodontic treatment had a
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better OH-QOL than those currently under treatment or those who never had treatment
(11). These findings were confirmed in a more recent case-control study of a similar
population (17).
Although these findings highlight the positive impacts of orthodontic treatment, these
studies are obviously limited by their design. According to the widely accepted
guidelines of evidence-based dentistry, these studies merely indicate the presence of
significant associations between better OH-QOL and orthodontic treatment. Hence, there
is a clear need for a prospective longitudinal clinical study in order to establish a cause-
and-effect relationship between OH-QOL and orthodontic treatment. This need for a
rigorous assessment of treatment effects was certainly urged by many reviewers of the
orthodontic literature (5,18-20)
Therefore, we decided to undertake this prospective longitudinal design study in order to
assess the hypothesis that orthodontic treatment improves OH-QOL in children.
Since changes in children’s’ psychosocial awareness over time can make repeated
measurements difficult to compare (21,22), we decided to compare children receiving
treatment to those awaiting treatment. The inclusion of a control group in the present
study was essential in order to interpret the findings and exclude any age-related effects
in this dynamic group of growing children.
OH-QOL was assessed using the Child Perception Questionnaire (CPQ11-14). The
CPQ11-14 is one of the most widely used OH-QOL measures in orthodontics. It is a valid
and reliable OH-QOL instrument that was developed and tested for use in children aged
11 to 14 years, a common age for undergoing orthodontic treatment. Cunningham
describes it as the questionnaire of choice in future orthodontic QOL research (2007)(23),
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because of its established discriminative properties (24-28) and responsiveness to change
in orthodontic status (29-31). Since evaluation of the psychometric properties of any
instrument is an ongoing iterative process (32), we also used this opportunity to confirm
the longitudinal psychometric properties of the CPQ11-14 in orthodontic settings.
There is no preferred method to assess change in children’s quality of life studies. This
study used Global Transition Ratings (GTR) alongside changes in CPQ11-14 scores to
assess changes in OH-QOL. GTR represent patients’ overall assessment of how their
condition has changed over a specified timeframe. Although opposed by some (33), the
use of GTR was advocated by OH-QOL researchers, because they are simple, integrate
patients’ values and avoid the statistical issues associated with change scores (34).
To summarize, the objectives of this longitudinal clinical study are twofold, first, to
establish OH-QOL gains following orthodontic treatment compared to a sample of
untreated controls, and, second, to confirm the psychometric properties of the CPQ11-14
in an orthodontic sample.
MATERIALS AND METHODS
Study Design
This is a longitudinal two-group cohort study designed to assess changes in OH-QOL
following orthodontic treatment. Participants receiving treatment were compared to
patients awaiting treatment.
Study Subjects
Subjects were 11- to 14-year-old children with a definite clinical need for orthodontic
treatment as assessed by the Dental Aesthetic Index (DAI) (35). Treatment subjects were
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recruited from the graduate orthodontic clinic during their first diagnostic visit (T1).
Control subjects were consecutively recruited during their first orthodontic screening visit
prior to being placed on a wait-list (T1). All data were collected by the first author. To be
eligible, the child had to be fluent in English and be in good general health. Children with
severe dento-facial deformities, warranting surgical intervention, were not included in
this study. Parents’ consents and children’s assents were obtained and the University
Research Ethics Board approved all study procedures. Treatment was completed at the
graduate orthodontic clinic as routinely prescribed using fixed appliance therapy. The
treatment duration typically ranged from 24 to 28 months. Follow-up data were collected
at the first retention check appointment after braces were removed (T2) for subjects
receiving treatment. T2 data for control subjects were collected after a comparable time
interval between T1 and T2 for treatment subjects. Questionnaires were mailed to their
home address with a prepaid self-addressed envelope. A second copy was mailed if the
follow-up questionnaire had not been returned within one month.
Procedure
All children independently completed a copy of the Child Perception Questionnaire
(CPQ11-14) before starting orthodontic treatment. The DAI was used to determine the
severity of malocclusion. Age and gender were recorded because of their potential
association with outcome and explanatory variables.
Measures
The Child Perception Questionnaire (CPQ 11-14)
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The CPQ 11-14 is an age-specific child OH-QOL instrument designed for use in 11- to
14-year-old children. It consists of 37 items, grouped into four domains: Oral Symptoms
(OS), Functional Limitations (FL), Emotional Well-being (EWB), and Social Well-being
(SWB). Responses can be summed to generate an overall score or a separate score for
each of the four sub-domains.
The questionnaire included the two GTR of orthodontic treatment effects on oral health
and on life overall (24). In addition, children also completed a short questionnaire
designed to assess their satisfaction with their teeth compared to the first time they
answered the questionnaire. The first two questions asked were: “How happy are you
with the way your teeth look?” and “How happy are you with the way your teeth come
together?”. Response options were “Very happy”, “Happy”, “Unhappy”, and “Very
Unhappy”. The other two questions assessed improvement in dental aesthetics and
occlusion on a seven point Likert scale. They asked: ‘Do you think the way your teeth
look has:’ and ‘Do you think the way your teeth come together has:’ Response options
for these two questions were ‘improved a lot’, ‘improved somewhat’, ‘improved a little’,
‘stayed the same’, ‘worsened a little’, ‘worsened somewhat’, ‘worsened a lot’.
The Dental Aesthetic Index (DAI)
The severity of each child’s orthodontic condition was assessed using study models taken
at the initial visit and following orthodontic treatment and recorded objectively with the
DAI (35). DAI scores range from 13 (the most acceptable) to 100 (the least acceptable).
The DAI ratings were recorded by three trained and calibrated examiners. DAI raters
independently assessed a random 10% sample of the models and then reassessed the
models after a one-week interval. The inter-examiner reliability was high with Intra-class
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Correlation Coefficients (ICC) based on a two-way repeated measures ANOVA of 0.81.
Intra-examiner reliability for the three raters was also high with ICC of 0.96, 0.91, and
0.97.
Data analysis
The data were analyzed using SPSS, Version 16 (SPSS, Chicago, IL, USA). Additive
scale and sub-domain scores for the CPQ11-14 were calculated by summing the item
response codes. Distributions of responses to GTR were individually summarized for
each question.
Paired t-tests were used to test the statistical significance of within group changes over
time. To assess the effect of providing orthodontic treatment on OH-QOL while
controlling for baseline variations, we used an ANCOVA model, where treatment status
(treatment vs. controls) was entered as a fixed factor and baseline scores were controlled
for as covariates. The ANCOVA model was used to estimate the adjusted mean overall
and sub-domain CPQ11-14 scores (Table 1).
In order to assess the longitudinal psychometric properties of CPQ11-14 to change,
change scores were computed by subtracting post-treatment scores from pretreatment
scores. Change scores were then compared against responses to GTR assessing
improvement in oral health and life overall.
Results
Of the 199 children, (98 treatment subjects and 101 control subjects), who entered the
study, 118 subjects were successfully followed-up. Follow-up data were obtained from
74 treatment subjects and 44 control subjects. Despite the persistent recall efforts, 35.6%
of wait-list subjects sought orthodontic treatment elsewhere and 20.8% were lost to
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follow-up. In addition, 24.5% of the treatment subjects were lost to follow-up.
Nevertheless, the relatively high attrition rates did not influence the distribution of
baseline characteristics between retained and original subjects, at least for the variables
measured (Agou et al, in press).
At the outset of the study, 50.0% were girls with a mean age of 14.9 years. Initially, 92%
of the subjects had significant malocclusion as measured by the DAI. DAI scores ranged
from 17.0 to 74.8 with a mean of 35.46 (SD=8.63).
DAI scores of the treatment group were significantly reduced following orthodontic
treatment to 22.49 (SD=2.86). On the other hand, DAI scores for the wait-list group
remained unchanged indicating a persistent need for orthodontic treatment (33.56;
SD=7.14).
The ANCOVA models indicated that there was a significant reduction in overall CPQ11-
14, SWB, and EWB scores for treatment subjects, but not for wait-list controls (p<0.05).
Conversely, the OS and FL scores remained unchanged for both groups over the course
of this study. The estimated adjusted mean overall and sub-domain CPQ11-14 scores are
summarized in Table 1.
Responses to GTR assessing satisfaction with dental aesthetics and occlusion at T1 and
T2 for both study groups are graphically represented in Figures 1 and 2. Table 2
summarizes treatment and control children’s responses to global questions assessing
improvement in oral health, life overall, dental aesthetics and occlusion. The figures
clearly favor the treated group for both dental aesthetics and occlusion.
When CPQ11-14 change scores of the overall sample were compared against responses
to GTR assessing change in life overall and in oral health, a clear gradient existed across
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children who reported improvement, those who remained the same, and those who
worsened over time (Table 3). GTR were significantly correlated with CPQ11-14 change
scores (p<0.01).
Discussion:
This longitudinal study is a step forward towards providing the empirical evidence
needed to validate the common assumption that orthodontic treatment improves OH-
QOL. The results extend the findings of earlier cross-sectional studies examining
malocclusion and OH-QOL from consistent associations to a causal relationship (20).
According to the findings of this study, orthodontic treatment produces a measurable
improvement in OH-QOL of treated children compared to untreated wait-list controls. In
addition, responses to the GTR clearly demonstrate the positive changes in aesthetics and
occlusion brought about by orthodontic treatment. These findings are timely and answer
many of the recently raised questions concerning the psychosocial benefits of orthodontic
treatment in children.
Improvement in OH-QOL following treatment was most evident for the social and
emotional domains of the CPQ11-14. This is not surprising in view of earlier studies
using the CPQ11-14. A study of New Zealand schoolchildren revealed a distinct gradient
in the mean EWB and SWB domain scores across increasing severities of malocclusion
(25). Similar results were described for British and Canadian children with malocclusion
(29,31). OH-QOL data from cross-sectional studies have repeatedly linked orthodontic
treatment to better socio-emotional wellbeing and malocclusion to teasing, bullying, and
lower OH-QOL. For example, difficulty with smiling due to the misalignment of teeth
has been found to be one of the most important impacts of children's OH-QOL (36).
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Thus, it is reasonable to assume that the benefits of orthodontic treatment are more likely
to impact children’s day-to-day social and emotional activities than any other domains of
OH-QOL.
The lack of significant improvement in the OS and FL domains following treatment was
also expected. In fact, O’Brien deemed these two domains to be irrelevant to orthodontic
patients (29). This is also consistent with a comprehensive review of the orthodontic
literature, which concluded that conventional orthodontics does not improve patients’
speech or mastication (19).
Wearing a fixed orthodontic appliance typically compromises the functional aspects of
daily life like eating and speaking. In a study that focused on OH-QOL assessment during
the initial stages of orthodontic treatment, Zhang et al (2007) reported that children
experienced a deterioration of OS and FL within the first six months of treatment(37).
Another study indicated that more than 90% of subjects wearing fixed orthodontic
appliances experienced at least one negative impact as assessed by the Oral Impact on
Daily Performance (38). Our data indicate that children recover from the negative
functional impacts associated with treatment soon after the removal of fixed appliances.
When the effect of age was examined, there was an overall tendency for CPQ11-14
scores to decrease over time. At first glance, this may seem to contradict the general
hypothesis that children give increasing attention to peers and become preoccupied with
others' views of self as they enter early adolescence (39). Nevertheless, this decline in
CPQ11-14 scores may represent a process of adaptation to the oral health condition. This
explanation is supported by Kok et al, who suggest that children may respond with better
OH-QOL when a questionnaire is re-administered at a later time(8). Decline in CPQ11-
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14 scores for children in the treatment group was significantly larger than that of the
control group and thus, can not be solely attributed to age-related effects. Having a
control group was essential to isolate treatment effects and exclude effects stemming
from cognitive or developmental changes.
Differences between treatment and control subjects also emerged when analyzing
responses to GTR. At baseline, the groups responded to global questions, asking about
happiness with the way teeth look and come together, in a strikingly comparable fashion.
Yet, at follow-up, responses to these two questions differentiated noticeably between
those who had been treated and those who had not (Figures 1 and 2). Over 70% of
treatment subjects were either happy or very happy with their aesthetics and occlusion
compared to only 10% of those awaiting treatment. When children were asked if their
occlusion or aesthetics had changed over time, 100% of treatment subjects reported some
degree of improvement. On the other hand, over half of the control subjects discerned
that their aesthetics and occlusion had either remained the same or deteriorated compared
to the first time they had answered the questionnaire.
Similarly, when asked to rate their oral health, only 6.7% of treatment subjects reported
no improvement following orthodontics compared to approximately 50% of controls.
10% of those who were treated said that their life overall had worsened, while
approximately two thirds of those who were not treated, 55.9%, reported that their life
had remained the same, or worsened to some degree. To summarize, for all questions, the
majority of children with malocclusion who were treated reported that they had
improved, whereas children who did not receive treatment had an equal chance of getting
better or worse.
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Although these results demonstrate the presence of significant treatment effects, one must
be cautions in interpreting results from GTR. These retrospective judgments of change
are subjected to significant recall bias. According to Streiner and Norman (2008),
children may simply not remember their baseline state. When children are asked how
they felt two or three years ago, they first reflect on their current state (how do I feel
today?), this in turn triggers an “implicit theory of change” where children contemplate
how they think the treatment influenced their lives, they then try to estimate what their
initial state must have been (33). This theory of implicit change questions the robustness
of GTR as direct measures of change. Therefore, responses to GTR must be interpreted in
light of analysis of CPQ11-14 scores.
Longitudinal analyses of overall CPQ11-14 scores for both groups and data extracted
from responses to global questions were also used to confirm the psychometric properties
of the CPQ11-14. Change scores were examined against the different responses to GTR.
There were significant associations, in the expected direction, between children’s global
judgment regarding improvement of oral health and life overall CPQ11-14 scores (p<0.01
for all analyses). Moreover, We found that those reporting improvement on the GTR had
positive changes scores, those reporting deterioration had negative change scores and
those who report no change had scores close to zero (Table 3). Since children’s global
judgment closely corresponded to changes in CPQ11-14 scores, it is reasonable to
conclude that the CPQ11-14 possesses good longitudinal psychometric properties.
Nevertheless, the clinical relevance of these findings is yet to be determined. Clinical
relevance is usually assessed in quality of life research by calculating the Minimal
Important Differences (MID) (40). However, determining the MID in growing children
106
using anchor measures like the GTR used in this study, might be problematic (22). In
addition to potential recall bias, children may change their conceptualization of health as
they grow. Therefore, alternative strategies are needed to establish the MID for OH-QOL
data in the context of orthodontic treatment.
The fact that this study concluded that orthodontics does contribute to improvement in
children’s social and emotional wellbeing emphasizes the importance of selecting the
appropriate measure when examining psychosocial constructs. Outcomes of any
longitudinal psychosocial study are highly dependent on the operational definition of the
instruments used (6). For the most part, earlier studies assessing psychosocial gain after
orthodontics focused on measuring self esteem and general wellbeing, which are
relatively stable constructs that are unlikely to change by minor changes in teeth position
(6,41). On the other hand, whenever oral specific measurements are employed, research
clearly identifies the positive impacts of orthodontics on the daily aspects of children’s
lives (11,42). In fact, de Oliveira states that outcome research on the treatment of
malocclusion requires the use of OH-QOL measures (13).
The CPQ11-14 is a generic OH-QOL measure. Although some argue that OH-QOL
measures should be condition-specific in order to be appropriately used in orthodontic
patients (15,29), generic instruments are useful for making comparisons with the general
populations, which is particularly helpful in interpreting the results, making it possible to
evaluate the relative impacts of therapies and healthcare programs (43).
The results from this study have important implications at many levels (44,45). Data from
the present study help establishing a baseline for comparing treatment outcomes similar
to the manner by which normative measures are used (46). The clear benefits of
107
orthodontic treatment demonstrated in this sample could be also used to inform policy
makers about the importance of treatment. However, long term follow-ups are needed to
confirm these benefits. It is also necessary to examine how contextual factors like,
personality, social, and environmental factors moderate the relationship between OH-
QOL and orthodontic treatment.
Conclusion:
In conclusion, the results of this study support the hypothesis that orthodontic treatment
improves OH-QOL outcomes in children. Improvements were most evident for the social
and emotional wellbeing domains of CPQ11-14. Analysis of CPQ11-14 individual
domain scores corroborates the majority of literature indicating that the most significant
impacts of orthodontics on OH-QOL are psychosocial in nature. Association between
CPQ11-14 change scores and GTR confirms the longitudinal psychometric properties of
the CPQ11-14 instrument. The findings are yet to be examined in view of important
contextual factors moderating the relationship between orthodontics and OH-QOL.
108
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TABLES
Table 1: Main study variables at baseline (T1) and follow-up (T2) for treatment and control groups.
Group Treatment Control
Time T1 (N=98)
T2 (N=74)
Adjusted T2
T1 (N=101)
T2 (N=44)
Adjusted T2
Variable Mean (SD) Range
Mean (SD) Range
Mean (SE) 95% CI
Mean (SD) Range
Mean (SD) Range
Mean (SE) 95% CI
CPQ11-14 21.05 (15.09) 1.00-68.00
16.16 (10.99)*
0.00-44.00
16.44 (1.58) 13.32-19.57
24.07 (16.15) 3.00-80.00
23.14 (17.97) 2.00-73.00
22.67 (2.05) 18.61-26.72
OS 5.58 (3.40) 0-17.00
5.26 (3.15) 0-13.00
5.36 (0.39) 4.59- 6.12
6.07 (3.59) 0-16.00
6.34 (3.69) 0-15.00
6.32 (0.52) 5.29- 7.35
FL 5.09 (4.15) 0-21.00
5.41 (4.26) 0-18.00
5.55 (0.49) 4.57- 6.54
5.36 (4.69) 0-23.00
4.82 (4.57) 0-17.00
4.62 (0.67) 3.29- 5.94
EWB 5.19 (5.09) 0-24.00
2.51 (2.96)* 0-12.00
2.61(0.61) 1.39- 3.83
6.75 (5.45) 0-22.00
6.82 (7.56) 0-29.00
6.76 (0.82) 5.13- 8.39
SWB 5.18 (5.39) 0-27.00
2.99 (3.59)* 0-17.00
3.16 (0.54) 2.09- 4.23
5.89 (6.13) 0-29.00
5.16 (6.34) 0-27.00
4.98 (0.76) 3.54- 6.42
SD: Standard Deviation; SE: Standard Error Lower CPQ11-14 scores represent better oral quality of life. * Paired t statistics were significant (p<0.05), indicating within group changes over time ANCOVA statistics were significant (p<0.05), indicating between group differences over time
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Table 2: Percentage of subjects responding to GTR for treatment and control groups.
Aesthetic Occlusion Oral Health Life Overall Response to GTR
T(%) C(%) T(%) C(%) T(%) C(%) T(%) C(%)Improved a lot 94.7 25.6 93.3 25.6 46.7 9.1 42.7 15.9 Improved somewhat 4.0 25.6 5.3 20.9 32.0 25.0 32.0 18.2 Improved a little 1.3 2.3 1.3 4.7 9.3 11.4 18.7 18.2 Remained the same 0 0 0 34.9 9.3 40.9 6.7 31.8 Worsened a little 0 37.2 0 4.7 2.7 6.8 0 9.1 Worsened somewhat 0 7.0 0 7.0 0 2.3 0 0 Worsened a lot 0 2.3 0 2.3 0 4.5 0 6.8 T: Treatment group C: Control group
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Table 3: Mean CPQ11-14 change scores per GTR category for the overall sample
Mean CPQ11-14 change scores
OH* r Life over all r
Improved 6.56 (15.74) 5.11 (15.20) Stayed the same -1.04 (18.65) 3.79 (21.07)
Worsened -16.38 (23.08)
0.34** -20.43 (23.63)
0.28**
*ANOVA results were significant at p<0.001 and F ratio of 7.95 ANOVA results were significant at p<0.001 and F ratio of 7.51 ** r (Pearson Correlation Coefficient) is significant at the 0.01 level (2-tailed).
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Figure 1: Percentage of subjects reporting satisfaction with dental occlusion for treatment and control groups at baseline (T1) and follow-up (T2).
0
10
20
30
40
50
60
70
Treatment (T1) Control (T1) Treatment (T2) Control (T2)
Very happy
Happy
Unhappy
Very unhappy
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Figure 2: Percentage of subjects reporting satisfaction with dental aesthetics for treatment and control groups at baseline (T1) and follow-up (T2).
0
10
20
30
40
50
60
70
80
Treatment (T1) Control (T1) Treatment (T2) Control (T2)
Very happy
Happy
Unhappy
Very unhappy
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Manuscript IV: Does Psychological Well-being Influence Oral Health Related Quality of Life in Children Receiving Orthodontic Treatment?
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Title page
Does Psychological Well-being Influence Oral Health Related Quality of Life Reports in Children Receiving Orthodontic Treatment? Shoroog Agou1, David Locker1, Bryan Tomnpson1, and David L. Streiner2 1 Faculty of Dentistry, University of Toronto, Toronto, Ontario, Canada
2 Baycrest Center, and Department of Psychiatry, University of Toronto
Running head: CPQ11-14, OH-QOL, and adolescent’s psychological well-being Key words: CPQ11-14, psychological well-being, orthodontics, oral-health related quality of life Address for correspondence: Shoroog Agou Faculty of Dentistry University of Toronto 124 Edward Street Toronto Ontario Canada M5G 1G6 Tel: (416) 979-4907 ext 4664 Fax: (416) 979-4936 e-mail: [email protected]
Agou S, Locker D, Tompson B, Streiner DL. Does Psychological Well-being Influence Oral Health Related Quality of Life Reports in Children Receiving Orthodontic Treatment? American Journal of Orthodontics and Dentofacial Orthopedics Based on a thesis submitted to the school of graduate studies, University of Toronto, in partial fulfillment of the requirements for the PhD degree. A preliminary report was presented at the International Association of Dental Research meeting in Toronto (2008)
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ABSTRACT
INTRODUCTION: Although the associations between oral biological variables such as
malocclusion and Oral Health-related Quality of Life (OH-QOL) have been explored,
little research has been done to address the influence of psychological characteristics on
perceived OH-QOL. Hence, the aim of this study was to assess OH-QOL outcomes in
orthodontics while controlling for individual psychological characteristics. We postulated
that children with better Psychological Well-being (PWB) would experience fewer
negative OH-QOL impacts, regardless of their orthodontic treatment status.
METHODS: 118 (74 treatment and 44 wait-list) eleven to 14-year-old children seeking
treatment at the orthodontic clinics at the University of Toronto, participated in this
study. The Child Perception Questionnaire (CPQ11-14) and the PWB subscale of the
Child Health Questionnaire were administered at baseline and follow-up. Occlusal
changes were assessed using the Dental Aesthetic Index (DAI). A wait-list comparison
group was used to account for age related effects.
RESULTS: Although treatment subjects reported significantly better OH-QOL scores at
follow-up, the results were significantly modified by the individual’s PWB status
(p<0.01). Further, multivariate analysis showed that PWB contributed significantly to the
variance in CPQ11-14 scores (26%). In contrast, the amount of variance explained by the
treatment status alone was relatively small (9%).
CONCLUSIONS: The results of this study support the postulated moderator role of PWB
when evaluating OH-QOL outcomes in children undergoing orthodontic treatment.
Children with better PWB are, in general, more likely to report better OH-QOL
regardless of their orthodontic treatment status. On the other hand, children with low
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PWB, who did not receive orthodontic treatment, experienced worse OH-QOL, compared
to those who received treatment. This suggests that children with low PWB can benefit
from orthodontic treatment, nonetheless, further work, with larger sample sizes and
longer follow-ups, is needed to confirm this finding and to improve our understanding of
how other psychological factors relate to patients’ oral quality of life.
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INTRODUCTION
As orthodontic outcome research continues to move away from the traditional biomedical
model (1)towards a biopsychosocial perspective (2), an increasing amount of attention is
being given to the concept of Oral Health-related Quality of Life (OH-QOL) (3). OH-
QOL is defined as the absence of negative impacts of oral conditions on social life and a
positive sense of dentofacial self-confidence (4). Emerging studies using reliable OH-
QOL measures have identified differences between treated and untreated orthodontic
patients (5-9). For example, a Brazilian study of 1,675 adolescents indicated that children
who had completed orthodontic treatment reported fewer OH-QOL impacts than those
who were never treated (5). These differences are mostly related to socioemotional
aspects of well-being such as; smiling, laughing, and showing teeth without
embarrassment (8, 9).
Such differences between treated and untreated subjects are, indeed, expected in light of
studies emphasizing the importance of dentofacial aesthetics in daily social interactions.
For instance, unattractive dentition has been associated with teasing, bullying (10, 11),
and negative OH-QOL impacts (5, 11-13). In fact, improving dental aesthetics and
subsequently, Psychological Well-being (PWB), are frequently stated reasons for seeking
orthodontic treatment during childhood and adolescence (14, 15). However, the bulk of
evidence denoting the relative stability of PWB undermines this assumption (16-19).
Further, no studies have been published that describe how OH-QOL and PWB change
over the period of orthodontic treatment.
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Attempts to correlate OH-QOL reports with clinical orthodontic indicators, on the other
hand, have often reached equivocal conclusions (20-23). In many of these studies,
children reporting worse OH-QOL were not consistently those with worse malocclusions.
It is possible that some children with severe malocclusion may be more emotionally
resilient to the challenges engendered by their condition. Hence, accurate interpretation
of OH-QOL measures requires an understanding of not only their psychometric
properties, but also the contextual factors which might influence children’s assessments
of their health and well-being (24). In fact, a recent long-term study evaluating
psychosocial outcomes in orthodontics suggested that analyzing the effects of orthodontic
treatment on psychological health without considering intervening factors may lead to
invalid conclusions about the efficacy of treatment (19). This is corroborated by cross-
sectional reports recognizing the effect of innate personality traits on children’s
perception of dentofacial aesthetics ((25-27), and patients’ evaluations of the impact of
their health on daily functioning (28-30).
Contemporary models of disease/disorder and its consequences, which integrate both
biological and psychological aspects of health, support this holistic thinking paradigm
(31). For example, according to the Wilson-Cleary model, health-related quality of life
outcomes experienced by an individual are determined not only by the nature and
severity of the disease/disorder, but also by the characteristics of the individual and their
environment (32). That being said, a thorough examination of the orthodontic OH-QOL
literature using the Wilson-Cleary model as conceptual framework reveals that, for the
most part, studies have focused on the associations between biological variables and OH-
QOL (23, 33, 34), with very little emphasis on the psychological characteristics of
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children receiving orthodontic treatment (35). This is surprising considering that research
has shown that determinants of health-related quality of life are mainly psychological in
nature (36). Hence, psychological factors such as PWB are certainly important
moderators of OH-QOL (37).
Since the relationship between psychological factors and OH-QOL remains largely
unexamined in orthodontic patients, the present study was undertaken to answer the
question: do individual psychological characteristics affect children’s OH-QOL reports?
The specific objectives of this longitudinal investigation were to explore the effect of
PWB on reported OH-QOL in children receiving orthodontic treatment and to compare
this effect to a sample of untreated wait-list controls. We hypothesized that children with
better PWB would experience fewer negative impacts, regardless of their orthodontic
treatment status. According to this hypothesis, children’s assessment of OH-QOL will be
influenced by their PWB. To demonstrate this moderating role of PWB, we compared
OH-QOL in children with high and low PWB. We expected that OH-QOL outcomes
wouldn't change for those in the high PWB group, but may change for those in the low
group.
Since medical research has shown that psychological variables are likely to affect the
more subjective domains of quality of life reports (38), we expected that the influence of
PWB would be more pronounced for the more subjective social and emotional
dimensions of the OH-QOL measure used in this study, than for the more objective
dimensions addressing functional limitations and oral symptoms.
MATERIALS AND METHODS
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Study Design
This study used a two group before-and-after design to assess changes in OH-QOL
following orthodontic treatment. Patients receiving treatment were the focal group of
interest, whereas patients awaiting treatment represented the comparison group.
Study Subjects
To be eligible, the child had to be fluent in English and be in good general health.
Children with severe dento-facial deformities were excluded. Parents’ consents and
children’s assents were obtained and the University Research Ethics Board approved all
study procedures. Subjects were not offered incentives or compensation for participating
in the study. Treatment subjects were consecutively recruited from the graduate
orthodontic clinic at the University of Toronto during their first assessment visit. Control
subjects, on the other hand, were consecutively recruited from the Faculty of Dentistry
clinics during their first orthodontic screening visit. All 11- to 14-year-old subjects who
met the eligibility criteria were recruited by the first author.
Procedure
All children completed a copy of the Child Perception Questionnaire (CPQ11-14) and the
PWB subscale of the Child Health Questionnaire at baseline (T1) and follow-up (T2).
Questionnaires were completed by the children unassisted by parents or investigators.
The Dental Aesthetic Index (DAI) (39) was used to determine the clinical severity of
malocclusion. Age and gender were recorded because of their potential association with
outcome and explanatory variables. Treatment was completed at the graduate orthodontic
clinic as routinely prescribed using fixed appliance therapy. On average, treatment lasted
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for 26 months. T2 data were collected at the first retention check appointment for
treatment subjects and after an equivalent duration of T1-T2 time interval for control
subjects.
Measures
The Child Perception Questionnaire (CPQ 11-14)
The CPQ 11-14 is a child OH-QOL instrument. The age-specific questionnaire (11 to 14
years) consists of 37 items, grouped into four domains: Oral Symptoms (OS), Functional
Limitations (FL), Emotional Well-being (EWB), and Social Well-being (SWB). Each
item asks about the frequency of events, as applied to the teeth, lips, and jaws, in the last
three months. The response options were “never”, “once or twice”, “sometimes”, “often”,
and “every day or almost every day”. Additive scale and subscale scores for the CPQ11-
14 were calculated by summing the item response codes. Although the instrument is
designed to yield an overall score, a separate score can be generated for each of the four
subscales. Higher scores signify worse OH-QOL. The validity, reliability, and
responsiveness of this measure have been established in different settings (6, 21, 23, 33,
40-43). This measure examines the impacts of oral conditions on children’s EWB and
SWB; nonetheless, it is important not to confuse these two domains with the more
generic PWB. EWB and SWB focus specifically on the impacts of oral health condition
on children’s daily functioning, whereas PWB takes into account the effect of all aspects
of health and daily life on well-being.
The Child Health Questionnaire
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Children’s PWB was measured using the PWB sub-domain of the Child Health
Questionnaire. This questionnaire is a widely used and validated self-report instrument
(44). The 16-item PWB scale measures the frequency of both negative and positive
feelings. The items capture anxiety, depression, and happiness. Frequency is measured
using a five-level continuum that ranges from "all of the time" to "none of the time". The
scores were calculated using Landgraf’s user’s manual (45). Higher scores indicate better
PWB; a score of a 100, for example, indicates that the child feels peaceful, happy, and
calm all of the time. In contrast, lower scores indicate that the child has feelings of
anxiety and depression. Specific instructions confirming the generic nature of the
measure were added at the beginning of the questionnaire.
The Dental Aesthetic Index (DAI)
The severity of each treatment and control subject’s orthodontic condition was assessed
using study models taken at T1 and T2 using the DAI (39). Although other treatment
need indices like the Index of Orthodontic Treatment Need and the Index of Complexity,
Outcome, and Need are available, the DAI was chosen because it incorporates the social
acceptability of a child’s dental appearance. The rating is based on the measurement of
ten occlusal traits; each trait is multiplied by a weight derived from the judgment of lay
persons. The products are summed and a constant is added to give a DAI score. DAI
scores range from 13 (the most acceptable) to 100 (the least acceptable).
The DAI ratings were recorded by three trained and calibrated examiners. Intra and inter-
examiner reliability was evaluated by raters independently assessing a random 10%
sample of the models and then reassessing the models after a one-week interval. Intra-
examiner reliability for the DAI raters was high with Intra-class Correlation Coefficients
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of 0.96, 0.91, and 0.97 respectively. The inter-examiner reliability was also high (Intra-
class Correlation Coefficients = 0.81).
Data analysis
The data were analyzed using SPSS, version 16 (SPSS, Chicago, IL, USA). Data analyses
included descriptive statistics, bivariate and multivariate analyses. Paired t-tests were
used to assess within group changes over time for each of the treatment and control
groups. The p value for all tests was set at p<0.05.
Analyses of covariance (ANCOVA) models were then used to explore between group
differences. The first goal was to evaluate the relationship between the provision of
orthodontic treatment and changes in OH-QOL, represented by overall and individual
CPQ11-14 scores, while controlling for baseline CPQ11-14 scores, age, and
malocclusion severity. This analysis plan, represented in model 1 (Table 2) aims to
address the question: “Is there a difference in reported OH-QOL between treatment and
control subjects?”.
The second goal was to evaluate the role of PWB on moderating OH-QOL outcomes by
using a second ANCOVA model (model 2 in Table 2). This model addresses the
following question: “If there is a difference in OH-QOL scores between treatment and
control subjects, does it remain significant after controlling for PWB?”.
RESULTS
50% of the 118 study subjects followed-up over the course of this study were girls and
76% were Caucasians, with a mean age of 12.9 (SD=0.98) years at baseline. According to
published DAI categories (39), 44.2% of the overall sample had handicapping
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malocclusion, 25.7% had severe malocclusion, 23.9% had definite malocclusion, and
6.2% had minor malocclusion.
Although follow-up data were successfully obtained from 118 subjects (74 treatment and
44 control subjects), 199 children were recruited at the onset of the study. To ensure that
the relatively large percentage of drop-out (40.71%) did not compromise the
comparability of baseline characteristics between the treatment and control groups, T1
data of original and retained subjects for both treatment and control groups were
contrasted in Table 2. t statistics indicated that all variables studied were comparable for
both groups at the onset of the study. Hence, the subjects lost to follow-up did not
influence the distribution of these variables.
Table 2 also summarizes T2 data for treatment and control subjects. In addition, a guide
to interpreting these scores is provided in Table 1. It is noteworthy that CPQ11-14, EWB,
SWB, and DAI scores for the treatment subjects were the only variables that changed
significantly over the study period. In contrast, these scores did not change significantly
for the control group. As expected, PWB scores remained relatively constant over time
for both treatment and control subjects. Further, these PWB scores were slightly higher,
but not significantly different from those reported for normal school children (44).
As mentioned earlier, ANCOVA models were used to test the difference in reported OH-
QOL between treatment and control subjects. Treatment status was entered into the
ANCOVA model as a fixed factor and tested for overall effect on CPQ11-14 overall and
subscales scores at follow-up. For each scale, the first model controlled for age, baseline
scores, and initial severity of malocclusion (DAI), while the second model controlled for
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PWB in addition. Table 3 provides a summary of the ANCOVA models, and the total
amount of variance explained by each model.
The results indicated a significant difference in overall CPQ11-14, SWB and EWB scores
between treatment and control subjects (p<0.05). However, after considering PWB as a
covariate, the effect of providing orthodontic treatment was no longer significant, as
measured by the overall CPQ11-14 and SWB scores (p=0.23). Emotional well-being was
the only scale where the difference between treatment and control subjects remained
significant after controlling for clinical and psychological confounders. To illustrate the
results, the adjusted mean CPQ11-14, SWB and, EWB scores for both treatment and
control groups are presented in Table 4.
The contribution of DAI scores was non-significant, with exception to the SWB subscale.
DAI scores significantly contributed to the variance in SWB scores in both ANCOVA
models. In addition, age effects were evident for the overall CPQ11-14, oral symptoms,
and functional limitations subscales. Nonetheless, these effects were apparent only after
controlling for PWB. The moderating role of PWB was further examined by adding the
“Group by PWB status” as an interaction term in a separate ANCOVA model (not
included in Table 3). The results were statistically significant with an F ratio of 7.01
(p<0.01) and an adjusted R2 of 26.8%. Since using normative reference groups is
recommended to meaningfully interpret the results from quality of life surveys (46), we
dichotomized PWB around the mode (76.6%), which approximates the population norms
published by Landgraf and others (44, 47-49). We then examined CPQ11-14 scores in the
high and low PWB groups at T1 and T2. The direction of change was evaluated for both
treatment and control subjects (Table 5).
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DISCUSSION
Although medical studies have stressed the importance of accounting for psychological
parameters whenever quality of life is used as a primary outcome (50, 51), a critical
analysis of orthodontic psychosocial outcome research reveals that most studies have
failed to do so. Hence, the results of the present study are timely, filling a research gap
identified by many researchers (3, 52). To the best of our knowledge, this is the first
controlled longitudinal study evaluating OH-QOL outcomes of orthodontic treatment in
light of pre-treatment psychological attributes. The results of this study support the
postulated moderator role of PWB when evaluating OH-QOL outcomes in children
receiving orthodontic treatment.
The oral health impacts reported by participating subjects were not entirely dependent on
the associated clinical conditions. Rather, PWB influenced participants’ perception of
oral health problems to a significant degree. Children reporting better PWB are more
likely to report better OH-QOL regardless of their treatment status. As hypothesized, the
contribution of PWB to the variance in OH-QOL was considerably greater for the SWB
and EWB subscales, compared to the oral symptoms and functional limitations subscales
(Table 3).
The lack of significant changes in the PWB construct over the study period conforms to
the hedonic treadmill theory, holding that well-being, for most people, is a relatively
constant state (18). The data presented add to the bulk of evidence supporting this theory.
The data also agree with other studies that invalidate the assumption that improving
dental aesthetics can have a significant effect on a child’s PWB (17, 53).
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This sample of Canadian children reported significant reduction in negative oral impacts
following orthodontic treatment (mean CPQ11-14 reduction= 4.88, SD= 14.57)
compared to control subjects of similar age, gender, and dental condition (mean CPQ11-
14 reduction= 0.93, SD= 21.72). These results concur with other studies highlighting the
positive effect of orthodontic treatment on OH-QOL (5, 8, 9). For instance, CPQ11-14
scores improved significantly following orthodontic treatment of children in Hong Kong.
Similarly, de Oliveira’s cross-sectional study of 1,675 schoolchildren found comparable
treatment effects using other OH-QOL measures (5).
In-depth analysis of the present data, however, revealed that the effect of orthodontic
treatment is less dramatic when viewed in the context of the children’s psychological
profiles. The differences between treatment and control subjects clearly diminish after
accounting for PWB (Table 4). Results from the multivariate analyses showed that, for all
scales, PWB explained additional variance in the dependent variables (overall and
subscale CPQ11-14 scores). For example, the ANCOVA models accounting for PWB
explained about one-third of the variance in overall CPQ11-14, EWB, and SWB scores,
with PWB contributing the most to the explanatory power. This was observed for both
treatment and control subjects. As expected, the PWB of children participating in this
study influenced reports of oral symptoms and function to lesser extent.
The PWB results of this study help to clarify the findings of earlier work with the
CPQ11-14 in orthodontic patients, which found that the correlations between CPQ11-14
and clinical indices are rather weak (6, 23, 40). A recent meta-analysis, which concluded
that determinants of quality of life are mainly psychological in nature also supports this
explanation (38). Altogether, these results confirm the validity of contemporary
132
conceptual models of disease and its consequences, which emphasize the importance of
personal, social, and environmental factors in moderating patient-centered quality of life
outcome (32).
Considering that some studies have affirmed the relationship between malocclusion,
orthodontic treatment, and reported OH-QOL, it seemed important to control for the
initial severity of malocclusion and treatment status. Less than 10% of the variance in
overall CPQ11-14 scores was explained by the treatment status alone, indicating a
definite, but relatively small effect. The results support the findings of a long-term British
study (53), which concluded that orthodontic treatment had little positive impact on
psychological health and quality of life in adulthood, when self-esteem at baseline was
controlled for. Nevertheless, analyses of individual CPQ11-14 subscales demonstrated
that treatment effects varied across the four subscales. The EWB subscale was the only
scale for which treatment effects remained significant after adjusting for other clinical
and psychological factors. Conversely, the SWB subscale was the only scale to which
DAI scores made a significant contribution, making this subscale the closest to
correspond to objective treatment needs.
The associations between psychological factors and perceived social and emotional
impacts of oral health concur with what has been previously reported for children,
adolescents, and young adults (13, 22, 24-26, 54-56). Overall, this study emphasizes the
extent to which psychological factors can modify children’s perception of their actual
oral health status.
A closer examination of the items comprising each scale helps to explain these findings.
The EWB subscale focuses on internal feelings such as; being worried, embarrassed, or
133
concerned about looks. In contrast, the SWB subscale consists of items assessing the
impacts of malocclusion on various social interactions, including speaking in class, social
activities, smiling, talking to other children, or being teased by other children. It is also
important to consider that data were collected shortly after termination of treatment. It is
not surprising then that orthodontic treatment did not have an immediate effect on
children’s SWB. Children may simply need time to translate the emotional gains
following treatment to their external environment. In general, the SWB and EWB
findings concur with past studies documenting the negative effects of malocclusion on
children’s lives (10, 57-59).
In addition, treatment effects varied depending on the child’s PWB. In the present study,
children with high PWB scores were more likely to report significant improvement in
OH-QOL after treatment, compared to those with low PWB scores (Table 5). Evaluation
of the overall sample suggests that there is a trend for CPQ11-14 scores to improve over
time regardless of the treatment status. Nevertheless, a closer evaluation of CPQ11-14
scores per PWB group (Table 5) reveals that children with low PWB who did not receive
orthodontic treatment reported worse CPQ11-14 scores over time, compared to those who
received treatment.
This change in behavior of the CPQ11-14 after accounting for the PWB status highlights
the importance of considering the child’s psychological profile when evaluating OH-
QOL outcomes in orthodontics. It is important to note, however, that these results should
be interpreted with caution because of the small sample size in each cell. Nevertheless,
the effect of PWB on reported OH-QOL is worthy of further investigation with larges
samples and longer follow-ups.
134
Information generated from this study will be of great value to both clinical and policy
relevant research. Researchers interested in capturing the multidimensional aspects of
oral health should consider the PWB of participating subjects while designing their
studies. While some investigators may consider the PWB variable as “noise”, it may be
also an important determinant of OH-QOL (37). Further, the minor contribution of DAI
scores to the variance in CPQ11-14 scores demonstrates the limitations of clinical
indicators in interpreting OH-QOL data.
Clinically, the results support the argument that orthodontists should include the
psychological dimension in their assessment when prioritizing treatment needs and
evaluating outcomes. Since children with low PWB scores appeared to suffer more
impacts as a result of their malocclusion, it seems logical to grant them priority accessing
orthodontic care. This could be achieved by using proxy measures that reflect children’s
experience, such as the self-report CPQ11-14. Nevertheless, worse OH-QOL scores alone
may not be sufficient to indicate clinically worse oral health. Further work is needed to
refine existing OH-QOL measures in order to correspond more closely to objective health
needs. For example, results from the CPQ11-14 subscales analyses can guide research to
develop short forms of this measure intended for specific purposes.
There are some inherent limitations relevant to most studies of orthodontic treatment.
Since randomization is difficult to achieve in orthodontics (19, 60), a longitudinal
observational design offered the best, and most feasible alternative approach. Follow-up
data confirmed our preliminary findings (61), and established directionality between OH-
QOL and PWB. The presence of a control group helped to draw conclusions related to
treatment effects rather than changes stemming from the dynamic nature of psychological
135
constructs in growing children (62). Despite the persistence of our recall efforts, this
study was also limited by the relatively high attrition rate. This was mostly because of
wait-list patients seeking alternative care or relocating outside the city. Although it is
possible to assume that those who sought alternative treatment were the ones with worse
malocclusion or worse PWB, the distribution of the main baseline characteristics between
original and retained subjects were comparable, at least for the variables measured (Table
2). Nevertheless, the ANCOVA results should be interpreted with caution, especially
considering the lack of randomization and the observational nature of this study (63).
It is important to reconsider the current biomedical and restricted paradigm on OH-QOL
and to begin to think about the series of processes by which social and psychological
factors influence OH-QOL reports (64). This study lays the grounds for developing a
conceptual understanding of the interaction between reported OH-QOL and individual’s
PWB. Although PWB explained the variance in CPQ11-14 to a reasonable extent, the
lack of comparable studies in the literature makes it difficult to generalize the findings.
Further, the relatively low R2 values associated with the models indicate that there may
be other determinants of OH-QOL. For instance, the direct contribution of factors such
as; other oral health problems, social support, or personality traits was not assessed in this
investigation. Hence, further work should be attempted, to study these factors with larger
sample sizes, different age groups, and longer follow-ups in order to improve the quantity
and quality of orthodontic OH-QOL data. The use of complex structural equation
modeling or path analysis can also add to our understanding of how the various aspects of
psychological health relate to patients’ oral quality of life. Thus, an impetus for further
meaningful OH-QOL research in orthodontics will be provided.
136
CONCLUSION
In conclusion, the findings of this study highlight the importance of considering inherent
psychological parameters in orthodontic psychosocial research. More specifically, the
results support the moderator role of PWB when evaluating OH-QOL outcomes in
children with malocclusion. Children with better PWB are, in general, more likely to
report better OH-QOL regardless of their orthodontic treatment status. On the other hand,
children with low PWB, who did not receive orthodontic treatment, experienced worse
OH-QOL, compared to those who received treatment. This suggests that children with
low PWB may benefit from orthodontic treatment, nonetheless, further work, with larger
sample sizes and longer follow-ups, is needed to confirm this finding and to improve our
understanding of how other psychological factors relate to patients’ oral quality of life.
137
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TABLES
Table 1: The main study variables and their interpretation
CPQ11-4 The Child Perception Questionnaire Lower CPQ11-14 scores represent better oral quality of life
OS Oral Symptoms Lower CPQ11-14 scores represent better oral quality of life
FL Functional Limitation Lower CPQ11-14 scores represent better oral quality of life
EWB Emotional Wellbeing Lower CPQ11-14 scores represent better oral quality of life
SWB Social Wellbeing Lower CPQ11-14 scores represent better oral quality of life
PWB Psychological Wellbeing Lower PWB scores represent worse psychological well-being
DAI The Dental Aesthetic Index Lower DAI scores represent better occlusion
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Table 2: Main study variables at T1 and T2 for treatment and control groups.
Group Treatment Control
Time T1 T2 T1 T2
N Original Baseline (N=98)
Retained Baseline (N=74)
Follow-up (N=74)
Original Baseline (N=101)
Retained Baseline (N=44)
Follow-up (N=44)
Variable Mean (SD)
Range Mean (SD)
Range Mean (SD)
Range Mean (SD)
Range Mean (SD)
Range Mean (SD)
Range
CPQ11-14 21.05 (15.09)
1.00-68.00 21.63 (14.19)
3.00-68.00 16.16 (10.99)*
0.00-44.00 24.07 (16.15)
3.00-80.00 24.07 (16.15)
3.00-80.00 23.14 (17.97)
2.00-73.00
OS 5.58 (3.40) 0.00-17.00
5.75 (3.37) 1.00-17.00
5.26 (3.15) 0.00-13.00
5.93 (3.24) 0.00-16.00
6.07 (3.59) 0.00-16.00
6.34 (3.69) 0.00-15.00
FL 5.09 (4.15) 0.00-21.00
5.27 (4.15) 0.00-21.00
5.41 (4.26) 0.00-18.00
5.92 (4.95) 0.00-23.00
5.36 (4.69) 0.00-22.00
4.82 (4.57) 0.00-17.00
EWB 5.19 (5.09) 0.00-24.00
5.29 (5.14) 0.00- 24.00
2.51 (2.96)* 0.00-12.00
6.83 (5.59) 0.00-22.00
6.75 (5.45) 0.00-22.00
6.82 (7.56) 0.00-29.00
SWB 5.18 (5.39) 0.00-27.00
5.32 (5.46) 0.00-27.00
2.99 (3.59)* 0.00-17.00
6.01 (6.12) 0.00-29.00
5.89 (6.13) 0.00-29.00
5.16 (6.34) 0.00-27.00
PWB 80.66 (10.09)
51.56-100 79.78 (9.29) 54.69-98.44
81.68 (10.52) 46.88-98.44
78.33 (12.98) 28.13-98.44
78.05 (11.7) 48.44-98.44
78.84 (13.39) 43.75-100
DAI 34.21 (8.18) 17.00-58.40
33.72 (7.78) 17.00-58.40
22.49 (2.86)* 17.30-30.10
36.53 (8.89) 20.00-74.80
36.25 (7.25) 25.80-53.80
33.56 (7.14) 23.60-44.40
*paired t statistics significant at p<0.01
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Table 3: ANCOVA models showing contribution of covariates to overall and subscale (T2) CPQ11-14 scores
(T2) CPQ11-14 (T2) EWB (T2) SWB (T2) FL (T2) OS
Model
1 Model
2 Model
1 Model
2 Model
1 Model
2 Model
1 Model
2 Model
1 Model
2
F Statistics F F F F F F F F F F
Age 0.57 5.79** .023 1.59 0.00 1.60 3.17 6.80** 1.41 5.79*
Baseline scores
6.51** 7.81** 1.89 2.09 6.52* 7.10** 5.27* 5.23* 3.45 3.77
DAI 0.58 0.39 0.21 0.11 4.85* 4.88* 0.00 0.03 0.27 0.58
PWB --- 27.09** --- 22.15** --- 18.07** --- 7.14** --- 13.97**
Treatment status
4.17* 1.31 14.97** 10.17** 3.62* 1.29 1.47 3.29 1.77 0.31
Corrected Model
3.79** 8.9** 5.02** 9.08** 4.78** 7.88** 2.73* 3.71** 2.01 4.46**
Adjusted R2 0.09 0.26 0.13 0.27 0.12 0.24 0.06 0.11 0.04 0.14
Model 1: controls for age, DAI, Baseline scores, and treatment status. Model 2: controls for all the variables in model 1 in addition to PWB status. * p<0.05 ** p<0.01
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Table 4: Observed and adjusted mean (T2) CPQ11-14, EWB and SWB scores
Observed scores Adjusted scores Scale Group
Mean (SD) Mean (SE) Treatment 16.16 (10.99) 17.93 (1.44)a
CPQ11-14 Control 23.14 (17.97) 20.89 (1.90)a
Treatment 2.51 (2.96) 2.99 (0.57)b EWB
Control 6.82 (7.56) 6.16 (0.76)b Treatment 3.03 (3.59) 3.48 (0.51)c
SWB Control 5.29 (6.44) 4.50(0.68)c
SE Standard Error SD Standard Deviation aCovariates appearing in the model are evaluated at the following values: CPQ11-14 = 22.47, DAI = 34.56, PWB= 80.52 bCovariates appearing in the model are evaluated at the following values: EWB = 5.70, DAI = 34.61, PWB= 80.43 cCovariates appearing in the model are evaluated at the following values: SWB = 5.38, DAI = 34.61, PWB= 80.43
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Table 5: Mean T1 and T2 CPQ11-14 scores for treatment and control groups based on PWB status.
PWB status* Treatment status Mean CPQ11-14 at T1 (SD)
Range Mean CPQ11-14 at T2 (SD)
Range
Treatment group (N=23)
24.00 (12.77) 6.00-54.00
22.22 (11.16) 6.00-44.00 Low PWB
Control group (N=19)
21.68 (14.67) 5.00-63.00
30.00 (20.97) 5.00-73.00
Treatment group (N=51)
20.88 (14.79) 3.00-68.00
14.69 (9.57) 3.00-39.00 High PWB
Control group (N=25)
25.88 (17.26) 3.00-80.00
17.92 (13.54) 2.00-51.00
*High PWB ≥ 76.6, low PWB <76.6 (PWB was dichotomized around the mode based on published population norms (44, 47-49).)
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CHAPTER 8: DISCUSSION AND CONCLUSIONS
The US Department of Health and Human Services’ initiative “Healthy People
2010” has as its first goal “to help individuals of all ages increase life expectancy and
improve their quality of life”; consequently, QOL issues are coming to the forefront of
public health policy agendas (47). Additionally, the movement toward evidence-based
dentistry has created a demand for patient data that can document the patient’s perception
of treatment need and treatment benefits (344). Hence, clinicians are increasingly being
asked to justify decisions on clinical diagnosis and treatment outcomes with respect to
patients’ QOL.
It is not surprising, therefore, that the concept of QOL and its relationship to
treatment needs and outcomes is currently a “hot topic” in dentistry. OH-QOL
instruments provide a valid method to evaluate needs and outcomes important to both the
clinician and the patient. In fact, some even argue that OH-QOL should be integral in
overall patient assessment as well as in gauging the efficacy of the treatment from the
patient’s perspective (344,345). This is particularly applicable to orthodontics, where
clinicians treat malocclusions that often carry a large psychosocial component.
Nonetheless, QOL outcomes of orthodontics in children have not been well investigated.
Therefore, this research was designed to study OH-QOL outcomes in children seeking
orthodontic treatment.
The issues related to and arising from the studies presented in this dissertation are
discussed in Manuscripts I-IV. The following is a summary of the research objectives,
findings, and limitations of the study. It also discusses the relevance of these findings and
148
the need for future research to enhance our understanding of children’s OH-QOL
measures.
This study asked four main questions: 1) Is the child OH-QOL questionnaire
sensitive to change in the context of orthodontic treatment?; 2) Does SE impact OH-QOL
reports in children with malocclusion?; 3) Does orthodontic treatment improve children’s
OH-QOL?; and 4) Does PWB influence OH-QOL in children receiving orthodontic
treatment?
A longitudinal two-phase study was designed and implemented to help answer
these questions. The data provide new evidence of adolescents’ OH-QOL where
information has previously been lacking. For instance, this project has established that 1)
The CPQ11-14 is sensitive to change when used with children receiving orthodontic
treatment; 2) The impact of malocclusion on OH-QOL is substantial in children with low
SE, and SE is a salient determinant of OH-QOL in children seeking orthodontic
treatment; 3) Orthodontic treatment improves OH-QOL outcomes in children, and these
improvements were most evident for the social and emotional domains of OH-QOL; and
4) Children with better PWB are more likely to report better OH-QOL, regardless of their
orthodontic treatment status.
There is compelling evidence in the literature to support these findings. These are
discussed in depth in the manuscripts presented in chapter 7. Altogether, this dissertation
has demonstrated that SE and PWB should not be viewed as outcome measures in
orthodontics, but as moderators or effect-modifiers. Although OH-QOL outcomes were
enhanced following orthodontic treatment, the degree of this enhancement was dependant
on the individual’s psychological status. Notably, social and emotional OH-QOL
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domains were more likely to be affected by such psychological factors. These results
support the notion that a person’s quality of life is more of a state of mind, not only a
state of health (127). Further, the results from this study confirm the central idea that the
desire for orthodontic treatment is not necessarily related to the structural or functional
need for treatment (346) and that the effects of malocclusion are not necessarily related to
the severity of malocclusion (16,61,347).
Several methodological challenges were confronted during the conception and
implementation of this study. The assessment of change, in general, is a complex process.
This was complicated further by the circumstances of the current study. Issues like the
multi-faceted dynamic nature of children, the long duration of orthodontic treatment, and
the quasi-experimental study design demanded the inclusion of a control group to enable
a meaningful interpretation of the results.
Nonetheless, despite our persistent recall efforts, the overall response rate was
59.29%. Although this approximates the response rates reported for Canadian studies
using postal surveys (348,349), the relatively high attrition rate of the control group could
have resulted in a biased assessment of treatment effects. As Streiner and Norman
explain, uncontrolled pre-existing differences between groups in quasi-experimental
designs could lead to statistical complications related to the effect of regression to the
mean that can not be accounted for by ANCOVA (129).
This phenomenon is known as the “Lord’s Paradox” (350); it refers to the
relationship between a continuous outcome (e.g., OH-QOL at follow-up) and a
categorical exposure (e.g., the treatment/control groups) being reversed when an
additional continuous covariate (e.g., baseline OH-QOL) is introduced to the analysis
150
(351). The accuracy of the results is conditional on the absence of baseline differences
between groups. To rule out the possibility of this non-response bias, the pre-treatment
characteristics of original and retained subjects were contrasted (manuscript IV).
Fortunately, at least for the variables measured, the groups were comparable, which
allowed for proper interpretation of the ANCOVA results. Thus, it is fair to conclude that
the results are valid for the population of Canadian children seeking orthodontic
treatment. However, the results remain limited by the convenient clinical sample used,
especially considering that children are, in general, not a homogenous group. Future
studies of other populations that include mid-treatment and post-retention assessments, in
addition to pre- and post-treatment observations, can ascertain these results by the use of
advanced statistical tests such as growth curves.
During the course of the present study, a new questionnaire titled the “condition-
specific Child-OIDP (CS-OIDP)” was developed (352). The CS-OIDP allows for
analysis of condition-specific impacts on daily performance by attributing impacts to
specific oral conditions or diseases according to the respondent’s perceptions. The
developers claim that this feature facilitates its use in needs assessment and for planning
oral health care services to provide targeted interventions, increases acceptability to
subjects by including only relevant dimensions (47), and may render the measure more
sensitive and responsive to small changes in oral health (353).
Although it was recently found that the CS-OIDP, attributed to malocclusion, was
better able than OHIP to discriminate between adolescents with and without normative
needs for orthodontic treatment (352), its longitudinal psychometric properties remain
unknown. Hence, there is no evidence on whether generic or condition-specific OH-QOL
151
measures are more appropriate for assessing longitudinal outcomes in the context of
orthodontic intervention. Thus, besides being the best available measure at the time of
study conception, the decision to use the generic CPQ11-14 was based on its established
psychometric properties. Further, because the CPQ11-14 is a generic measure, it has the
clear advantage of allowing for comparisons between conditions and across studies,
which can aid in the allocation of resources among multiple service systems (31).
Although generic measures may include a range of questions, some of which may not be
relevant to orthodontics (56,57), they do have a great potential to pick-up unforeseen
side-effects which may go undetected by a specific instrument (32,161).
Childhood oral diseases and disorders are numerous. It would be impractical for
both patients and clinicians to evaluate individual change on several condition-specific
OH-QOL measures at each clinical/research encounter. However, since comorbidity is
not uncommon, a minor adaptation of the current CPQ11-14 to help in attributing the
reported impacts to a particular oral condition might enhance the interpretability of the
results. After all, continuous refinement of the instrument as it is being used was one of
the objectives of the developers of the CPQ11-14, who viewed its development and
testing as an iterative process (118).
In this study, patients’ PWB and SE were more important than normative
evaluation when considering OH-QOL measures. While this speaks to the holistic nature
of the quality of life construct, it leads to several important questions: should
orthodontists be more concerned with patients who have treatment needs and
psychosocial implications? Should more government funding be available for those
152
patients where there is strong associated psychosocial component? If so, how could
clinicians incorporate it into overall patients’ assessment?
Further, identifying and classifying OH outcomes for various oro-facial
conditions along a continuum of impairment, function, and disability can ultimately be
used to establish benchmarks for the allocation of resources. In fact, patient-based health
outcome measures are now generally accepted as necessary complements to clinical
indicators for the assessment of population health needs and the evaluation of health
interventions and programs (354). Therefore, the results of this study can usefully
contribute to the development of policy recommendations for promoting quality of life.
For example, while orthodontic treatment was mandatory or highly desirable for 13.7%
of Canadian children surveyed in 1989, only 2.9% were actually under treatment (20).
Hence, OH-QOL data can be valuable in efficient allocation of the limited financial
resources to patients who are likely to benefit the most from treatment. However, given
the shortcomings with either the objective or subjective approach to outcome assessment,
a combination of both approaches is preferable for assessing outcomes in children and
adolescents.
In addition, this study has important implications for topical orthodontic decision-
making research. The current consensus is that treatment timing decisions should be
based on individual psychosocial indications (355,356). The self-report CPQ11-14 is
potentially a useful proxy measure to supplement subjective clinical opinions for
determining treatment timing especially for psychosocially compromised children. This is
because the CPQ11-14 reflects the contribution of the child’s SE and PWB in
ameliorating the clinical severity of malocclusion; this allows for timing of treatment
153
according to child’s level of daily disruption. With this approach, dental services should
correspond more closely to consumer-based health needs and focus more on improving
the quality of life.
Further, providers need to pay more attention to patient-driven information,
including evaluation of comfort, functioning, aesthetics, and psychological implications
of the condition (357). Certainly, all who work with or are otherwise concerned with
children would hold as one of their most important goals to ensure that children
experience a life of quality (31). Hence, OH-QOL information could help the orthodontist
to better diagnose and evaluate treatment and to better understand the concerns and
personality of each patient, which would ultimately lead to improvement of the quality of
care (12,21). That being said, current instruments pertain to a research setting more so
than a clinical one, so there is a need to make the CPQ11-14 more user-friendly for
various clinical contexts.
Information generated from this study would not only support the value of
orthodontic intervention but would also enhance our understanding of children’s
psychosocial perspective. QOL is, by nature, a holistic concept; therefore, the influence
of diseases/conditions is very difficult to separate from the influence of all other
experiences, both at the theoretical level and the individual patient level (31). The
importance of controlling for psychological states when assessing OH-QOL is well
reflected in Drotar’s comment regarding pediatric H-QOL measures assessing asthma:
“A child who experiences limitations of daily activities because of the
exacerbation of symptoms of a chronic condition may experience increased
depressed mood, which is a plausible consequence of his/her increased activity
154
limitations. However, if this child happens to have a comorbid depressive
disorder, her H-QOL would also be limited, but for very different reasons.
Consequently, very different clinical interventions would be indicated depending
on the specific cause of the child's diminished H-QOL. Yet, despite the
importance of this issue for clinical assessment, the precise causal influence of
children's psychological status on H-QOL (and vice versa) has not been
adequately specified or tested in models of pediatric measurement”. (358) p.360
Further, as diminished H-QOL has also been linked to increased likelihood of
risky health behaviors such as drinking or smoking (359), efforts to better understand
adolescents’ social and emotional health as possible determinants of adverse behaviors
are now the focus of many public health agencies. It has been suggested that psycho-
educational interventions like social skills training, cognitive behavioral therapy,
empowerment or motivational programs, and health education programs may be useful
for adolescents (5,360,361). Nonetheless, the value of such interventions has not been
scientifically determined. Therefore, these implications can not be extended to OH-QOL.
While the main research questions highlighted above were addressed, several
others arise as the experimental work is put in context with our current knowledge. For
instance, it remains unanswered if we are truly assessing QOL or merely measuring day-
to-day impacts on daily life. As Locker indicates, the qualitative component of the
development process of the CPQ11-14 does not meet the full requirements for a QOL
measure. Nonetheless, the relatively strong correlation (r=0.4; p<0.05) between CPQ11-
14 scores and ratings of life overall implies that the questionnaire goes beyond the
155
assessment of daily activities to address aspects that have some effect on life as whole
(43).
In addition, the role other contextual factors play in moderating health reports
needs to be further examined. A person’s QOL, even when exclusively “health-related”,
has different components, significance, and meaning that are unique for each person
(127). This issue will no doubt continue to receive empirical attention to uncover the
relatively independent sources of variance in OH-QOL owing to cultural, social,
environmental contexts, as well as personal influences. Of particular interest here are the
interactions amongst personality types, parents’ behavior, body image, and cultural
norms. The use of qualitative analysis, structural equation modeling, or path analysis can
also add to our understanding of how the various aspects of psychological health relate to
patients’ oral quality of life and to evaluate their causal relationships (84). Thus, an
impetus for further meaningful OH-QOL research in orthodontics will be provided.
Another important question to address is whether the OH-QOL differences
observed in this study are clinically important. In general, responsiveness studies in
children have been limited by the absence of empirical standards to define clinically
meaningful changes in pediatric oral health status (31,358). Although some advocated the
use of GTR to determine such a change, the clustered distribution of the sample
precluded such assessment. Hence, alternate methods to determine the minimally
important difference need to be further explored.
Nonetheless, the tendency for researchers to utilize diverse definitions, criteria,
and measures of OH-QOL limits comparisons of results across studies and populations
and, therefore, may retard the progress of research in the field of pediatric OH-QOL.
156
Having a common definition and assessment method of OH-QOL, standardizing scoring
methods, and establishing population norms can significantly enhance the progress of
further research (31).
Current conceptual and statistical advances have provided investigators with
powerful tools to research OH-QOL in children. OH-QOL notion has the potential to
represent the ultimate standard against which to judge the impact of malocclusion and
orthodontics on children. However, despite recent progress, research has only begun to
scratch the surface of the needs in the field.
This research suggests that the answer to the focal question of this project, “Does
orthodontics improve OH-QOL reports in children?”, is far from being simple. OH-QOL
is a complex and a multidimensional construct that is influenced by many factors
deserving further investigation. Oro-facial conditions, including malocclusion, and their
treatment represent only one aspect of these factors. Therefore, while the overall results
support the existence of OH-QOL improvement following orthodontic treatment, higher
OH-QOL was experienced when the child had positive PWB. Hence, the long-term
retention of these benefits under the influence of contextual factors is yet to be affirmed
(362). The empirical knowledge base for children’s OH-QOL is in an early stage of
development, and we strongly believe that it will be worthwhile to further this
development.
157
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Appendix A: Flowchart detailing the data collection progress
Data Collection
Treatment Group Graduate Orthodontic clinic
100
Control Group Graduate Orthodon
120 tic wait-list
T1=98 M=42 F=56
T1=101 M=55 F=46
T2=44 M=25 F=19
T2=74 M=34 F=40
19 subjects were excluded 2 subjects were excluded
13 subjects were still in treatment 11 subjects changed address
36 subjects sought treatment elsewhere 21 subjects changed address
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Appendix B-1: Participant Information Sheet
“ASSESSING THE EVALUATIVE PROPERTIES OF THE CHILD ORAL HEALTH QUALITY OF LIFE QUESTIONNAIRE (COHQoL)
IN THE CONTEXT OF ORTHODONTIC TREATMENT ”
Participant Information Sheet Investigators: Dr. David Locker Professor, Faculty of Dentistry, University of Toronto Tel: 416-979-4907, ext 4490 Dr. Bryan Tompson Professor, Faculty of Dentistry, University of Toronto Tel: 416-979-4900, ext 4605 Dr. Shoroog Agou Ph.D candidate, Faculty of Dentistry, University of Toronto Tel: 416-979-4907, ext 4664 Why are we doing this study? We are doing this study to find out about problems children may have in their daily lives because of their teeth and mouth. We also want to find out how much the treatment they receive in this Clinic helps them not to have these problems. What will happen during this study? You and your child will fill out a questionnaire now and when your child’s treatment in this Clinic is finished. This will take no more than 10 minutes. Some questions will ask if your child has pain in his/her teeth and mouth, and if your child can chew some foods. Other questions will ask whether your child’s schoolwork or other things he/she does is affected by his/her teeth and mouth. We will also get information about your child’s teeth and mouth from the dentist and the dental records in this Clinic. Are there good things and bad things about this study? No. There is nothing in this study that can hurt either you or your child. There are no right or wrong answers. The things you tell us will help dentists to be better at treating children like your child. However, you will not benefit directly from taking part in the study. Who will know about what I did in the study? Only people who are helping with the study will see your responses to the questions. Neither your name nor your child’s name will be used on any documents reporting the results from the study. However, the researchers have an obligation to report suspicions of child abuse and neglect. Do my child and I have to take part in the study? No. Only you can decide about your and your child’s participation in the study. Even if you and your child decide to take part and later change your mind about that, nobody can make you stay in the study. No matter whether you and your child choose to be in the study or not, the dentists in this Clinic will keep providing care to your child and the members of your family. Who do I contact if I have any questions about the study? Please contact: Shoroog Agou, Research Associate, Faculty of Dentistry, University of Toronto, Tel: 416-979-4907, ext. 4664. In addition, if you have any questions about your rights as a research participant you may contact: Dr. Rachel Zand, Manager Ethics Review Unit, University of Toronto, Tel: 416-946-3389.
191
Appendix B-2: Consent Form
“ASSESSING THE EVALUATIVE PROPERTIES OF THE CHILD ORAL HEALTH QUALITY OF LIFE QUESTIONNAIRE (COHQoL)
IN THE CONTEXT OF ORTHODONTIC TREATMENT ”
Consent form
By signing this form I agree that the study described in the Participant Information Sheet has been explained to me and that I have been given a copy of the information sheet and the consent form. I have been also informed that information about my child’s dental health will be obtained from the dentist and the records at the Faculty of Dentistry, University of Toronto. All my questions about the study have been answered and I have been given the name of the person who I may contact if I want any further information. I understand that my child has the right not to take part in the study and the right to stop any time. I have been told that no matter what my child decides to do, he/she will continue to receive care at the Faculty of Dentistry, University of Toronto. I have been assured that my name, my child’s name and information collected will be known only to people who are helping with the study and will be not used on any documents reporting the results from the study. I also understand that the researchers have an obligation to report suspicions of child abuse or neglect. I have been informed that if I have any questions about my and my child’s rights as a research participant I may contact: Dr. Rachel Zand, Manager Ethics Review Unit, University of Toronto, Tel. 416-946-3389. I hereby consent for my child ____________________________________to participate. (name of child) _________________________________ Parent’s or Guardian’s name Name of person who obtained consent Signature of person who obtained consent Date _________________________
192
Appendix B-3: Assent form
“ASSESSING THE EVALUATIVE PROPERTIES OF THE CHILD ORAL HEALTH QUALITY OF LIFE QUESTIONNAIRE (COHQoL)
IN THE CONTEXT OF ORTHODONTIC TREATMENT ”
Assent form Investigators: Dr. David Locker Professor, Faculty of Dentistry, University of Toronto Tel: 416-979-4907, ext 4490 Dr.Bryan Tompson Professor, Faculty of Dentistry, University of Toronto Tel: 416-979-4900, ext 4605 Dr. Shoroog Agou Ph.D candidate, Faculty of Dentistry, University of Toronto Tel: 416-979-4907, ext 4664 Why are we doing this study? We are doing this study to find out about problems that children may have because of their teeth and mouth. We also want to find out how much treatment they receive in this Clinic that helps them not to have these problems. What will happen during this study? You will fill out a questionnaire now and when your treatment in this Clinic is finished. This will take no more than 10 minutes. Some questions will ask if your teeth and mouth hurt, and if you can chew some foods. Other questions will ask whether your teeth and mouth affect your schoolwork or other things you do. We will also ask your dentist in this Clinic to tell us about your teeth and mouth. Are there good things and bad things about this study? No. There is nothing in this study that can hurt you. There are no right or wrong answers. The things you tell us will help dentists to be better at treating children like you. Who will know about what I did in the study? Only people who are helping with the study will see your responses to the questions. Your name will not be used anywhere. Do I have to take part in the study? No. Only you can decide if you want to be in the study. Even if you decide to take part and later change your mind about that, nobody can make you stay in the study. No matter whether you choose to be in the study or not, your dentist in this Clinic will keep helping you with your teeth and mouth. ASSENT: “I was present when _________________________________ was given the above information about the study and he/she gave his/her verbal assent” ________________________________ Name of the person who obtained assent ________________________________ ________________ Signature of the person who obtained assent Date
193
Appendix B-4: Cover Letter «Patient_Name» «Address» «City» «Province» «PostalCode» Dear Parent, We appreciate your and child’s participation in our study while he/she was attending the Orthodontic Clinic at the Faculty of Dentistry in 2004. As you recall, we asked you to answer questions asking about experiences related to his/her teeth and mouth. At this time, we would like to ask you and your child to complete the same questionnaire. This is part of the research that is being conducted by the Faculty of Dentistry, University of Toronto to find out how children feel about their teeth and mouth after their treatment in the Orthodontic Clinic has been completed. Your participation is entirely voluntary. All responses will be kept confidential and will not be released in a manner that would identify you or your child. We hope that you will find time to complete the questionnaire. The return envelope is provided in this package. If you have any questions regarding this research or the questionnaire, please phone Dr. Shoroog Agou at 416-979-4901, ext 4664. Thanks again for your and your child’s valuable assistance in this research. Yours sincerely, Shoroog Agou
194
Appendix C: The Child Perception Questionnaire
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199 199
200 200
201 201
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Appendix D: Global Transition Ratings (Treatment Group)
Please answer the following questions:
1. Compared to the time before orthodontic treatment (braces), how happy are you with the way your teeth look now? Very happy Happy Unhappy Very unhappy
2. Compared to the time before orthodontic treatment (braces), how happy are
you with the way your teeth come together now? Very happy Happy Unhappy Very unhappy
3. Compared to the time before orthodontic treatment (braces), do you think
the way your teeth look has: Improved a lot Improved somewhat Improved a little Stayed the same Worsened a little Worsened somewhat Worsened a lot
4. Compared to the time before orthodontic treatment (braces), do you think the way your teeth come together has: Improved a lot Improved somewhat Improved a little Stayed the same Worsened a little Worsened somewhat Worsened a lot
5. Think about the health of your teeth, lips, jaws, and mouth. Compared to the
time before you started orthodontic treatment (braces), has it: Improved a lot Improved somewhat Improved a little Stayed the same
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Worsened a little Worsened somewhat Worsened a lot
6. Think about how your life overall is affected by your teeth, lips, jaws, and mouth. Compared to the time before you started orthodontic treatment (braces), has it: Improved a lot Improved somewhat Improved a little Stayed the same Worsened a little Worsened somewhat Worsened a lot
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Appendix E: Global Transition Ratings (Control Group)
Please answer the following questions:
1. Compared to the first time you answered this questionnaire, how happy are you with the way your teeth look now? Very happy Happy Unhappy Very unhappy
2. Compared to the first time you answered this questionnaire, how happy are
you with the way your teeth come together now? Very happy Happy Unhappy Very unhappy
3. Compared to the first time you answered this questionnaire, do you think the
way your teeth look has: Improved a lot Improved somewhat Improved a little Stayed the same Worsened a little Worsened somewhat Worsened a lot
4. Compared to the first time you answered this questionnaire, do you think the way your teeth come together has: Improved a lot Improved somewhat Improved a little Stayed the same Worsened a little Worsened somewhat Worsened a lot
5. Think about the health of your teeth, lips, jaws, and mouth. Compared to the
first time you answered this questionnaire, has it: Improved a lot Improved somewhat Improved a little Stayed the same
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Worsened a little Worsened somewhat Worsened a lot
6. Think about how your life overall is affected by your teeth, lips, jaws, and mouth. Compared to the first time you answered this questionnaire, has it: Improved a lot Improved somewhat Improved a little Stayed the same Worsened a little Worsened somewhat Worsened a lot
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Appendix F: Self-Esteem scale
CHILD HEALTH QUESTIONNAIRE
How do you generally feel about your self?
Hello,
Thanks for agreeing to help us with our study. By answering the questions, you will help us learn more about experiences children may have. This questionnaire asks about your moods and feeling and how you feel about yourself and life overall.
Answer by checking the appropriate box for each question. Certain questions may look alike but each one is different. Some questions ask about problems you may not have. That is great, but it’s
important for us to know. Please answer each question. There are no right or wrong answers. If you are unsure how to answer a question,
please give the best answer you can and make a comment in the margin. All comments will be read, so please feel free to make as many as you wish.
Community Dental Health Research Unit Faculty of Dentistry, University of Toronto 124 Edward Street, Toronto ON, M5G 1G6
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SELF ESTEEM
How do you feel about yourself, school, and others? It may be helpful if you keep in mind how other children your age might feel about these areas.
During the past 4 weeks, how good or bad have you felt about:
Very good Somewhat
good
Neither good nor
bad
Some what badly
Very Badly
a. Yourself? b. Your schoolwork? c. Your ability to play sports? d. Your friendships? e. The things you CAN do? f. The way you get along with others? g. Your body and your looks? h. The way you seem to feel most of the
time?
i. The way you get along with your family?
j. The way life seems to be for you? k. Your ability to be a friend for others? l. The way others seem to feel about you? m. Your ability to talk with others? n. Your health in general?
Child Health Questionnaire- Child self report form 87 (CHQ-CF87) 1991, 1996 © Landgraf and Ware
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Appendix G: Psychological Wellbeing scale
PSYCHOLOGICAL WELLBEING
The following phrases are about children’s moods and feelings they may have.
During the past 4 weeks, how much of the time did you:
All of the
time Most of the
time Some of the
time A little of the time
None of the time
a. Feel sad b. Feel like crying c. Feel afraid or scared d. Worry about things e. Feel lonely f. Feel unhappy g. Feel nervous h. Feel bothered or upset i. Feel happy j. Feel cheerful k. Enjoy the things you do l. Have fun m. Feel jittery or restless n. Have trouble sleeping o. Have headaches p. Like yourself
Child Health Questionnaire- Child self report form 87 (CHQ-CF87) 1991, 1996 © Landgraf and Ware
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What is the date today? / /
Month/ day/ year
Thank you for helping us
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Appendix H: The Dental Aesthetic Index Recording Form
ID # _____________________ Date _______________ Name ____________________ Male ____ Female ____ Date of Birth __________ Geographic Location ________________________ Ethnic Group ____________Examiner ___________ Cases Needing Referral for Further Evaluation Gross Anomaly Cleft Lip or Palate
Traumatic or Surgical Defect Deep Overbite Impinging on gingival Tissue Have you ever had orthodontic treatment? Yes No Have any of your teeth been extracted to improve appearance? Yes No If Yes, which teeth?
A B C No. or
Score Wt.
0 CONSTANT 13 1 Missing incisor, canine and premolar teeth— Maxillary and Mandibular Enter total #
6
2 Crowding in the incisal segments 0 = no segment crowded 1 = segment crowded 2 = 2 segments crowded
1
3 Spacing in the incisal segments 0 = no spacing 1 = 1 segment spaced 2 = 2 segments spaced
1
4 Diastema in mm 3 5 Largest anterior irregularity—Maxilla (upper) in mm 1 6 Largest anterior irregularity—Mandible (lower) in mm 1 7 Anterior Maxillary Overjet (upper) in mm 2 8 Anterior MAndibular Overjet (lower) in mm 4 9 Vertical anterior openbite in mm 4 10 Antero-posterior molar relation Normal=0 ½ cusp=1 Full cusp=2
3
11 TOTAL (add lines 0 through 11)
DIRECTIONS FOR CALCULATING A DAI SCORE For lines 1-10, multiply Column A by Column B and enter the result in Column C. Then: add Column C including Line 0 to obtain DAI score.
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Appendix I: The Peer Assessment Rating Form
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