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AACPDM 2013 Clinical Use of FAQ 1
Clinical Use of the Gillette Functional Assessment
Questionnaire: Translating Research into Clinical Practice
Jean Stout, PT, MSRocio Riveros-Charry, PT
AcknowledgementsFunding Sources & Collaborators
Medical Education & Research Association
2008 Clinical Research Planning Grant (Tucker)
Carole TuckerGeorge GortonAnita Bagley
Raymond TervoTom Novacheck
Outline•Motivation•Review of the Gillette Functional Assessment Questionnaire• Rasch Analysis•Assessing Development•Clinical Scenarios
Functional Assessment Questionnaire Novacheck et al. 2000
Gorton et al. 2011
Stout et al. 2012
Tervo et al. 2002
The reliability and validity of the Gillette Functional Outcome Questionnaire. JPO 20:75-81, 2000
Correlation between physical findings and gait measures in children with cerebral palsy. DMCN 44:185-190, 2002
The Gillette Functional Assessment Questionnaire 22-item skill set: Factor & Rasch Analysis. DMCN 53:250-255, 2011
Rasch Analysis of items from two self-report measures of motor function: Determination of item difficulty and relationships with children’s ability levels. DMCN 54:443-450, 2012
Practice of Evidence BasedTreatment
Influence Reimbursement Patterns
Critically Evaluate Effectiveness of Treatments
Motivation Motivation
ICF
AACPDM 2013 Clinical Use of FAQ 2
Motivation
ICF
what a child is able to do in an ideal environment
Capacity
Capability A child’s capacity influenced by environmental factors and choice
Performancewhat a child actually does in the environment in which they live
So What Is the Challenge?
Dx: Autism; In-toeing
Difficulty keeping up
Unable to ride a two-wheel bike
The Challenge? Unable to ride a two-wheel bike
The Challenge? Walk up/down stairs using a railingStand washing hands at sink
The Challenge?The family rates his walking at a level 9He is able to do 16 of 22 advanced functional skills
age 7 (16 of 22)
age 4 (10 of 22) age 5 (13 of 22)
AACPDM 2013 Clinical Use of FAQ 3
age 4age 7 age 5
Are these the right skills for each age?
Age 3
So What Is the Challenge?
GMFCSFMS
4.75x typical
III
3,3,1
Integration !
Skill Mastery of Typically Developing Children Using the Gillette Functional Assessment
Questionnaire
1) To acquire normative data on both the 22 queried skills and the walking scale on the FAQ
2) To establish the range and type of skills a child would be expected to perform based on a given FAQ walking level
Purpose:
Validation of FAQ-22 Skill Set
Rank Order with Classification Systems
Functional Assessment Questionnaire Novacheck et al. 2000
Gorton et al. 2011
Stout et al. 2012
Tervo et al. 2002
The reliability and validity of the Gillette Functional Outcome Questionnaire. JPO 20:75-81, 2000
Correlation between physical findings and gait measures in children with cerebral palsy. DMCN 44:185-190, 2002
The Gillette Functional Assessment Questionnaire 22-item skill set: Factor & Rasch Analysis. DMCN 53:250-255, 2011
Rasch Analysis of items from two self-report measures of motor function: Determination of item difficulty and relationships with children’s ability levels. DMCN 54:443-450, 2012
AACPDM 2013 Clinical Use of FAQ 4
Functional Assessment Questionnaire 10 Level Walking Scale
10
62
Functional Assessment Questionnaire 10 Level Walking Scale
Functional Assessment Questionnaire 22 Advanced Functional Skills
FAQ validationNovacheck, Stout, Tervo. J Pediatr Orthop 2000
Wee
Fim
Gai
t Ind
ex
O2
Cos
t
PO
DC
I T/B
M
PO
DC
I Glo
bal
FAQ
Questions/Discussion?Methods:
Cross-sectional survey design of parents of children between 9 months and 9 years of age
Challenge:Because of the broad range of typical development for each skill, statistical power analysis of needed numbers depended on the proportion of children who were able to perform any given skill at any given age levelA preliminary power analysis estimated the probability to detect a +10% difference if the proportion of the population able to perform any skill within the age category is 50%
Target: N=75 every 6 month interval (9 months – 9 years)
AACPDM 2013 Clinical Use of FAQ 5
Results:977 total surveys through 2010
response rate (.005 - 40%) average 20%
810 no co-morbidities (83%)
523 M ; 454 F
73% white; 11% black; 10% multi-racial
19% qualify for medicaid/medical assistance
796 surveys <6 years of age (81%)
Results:
0
25
50
75
100
125
150
175
200
225
1 2 3 4 5 6 7 8 9 10
0
2550
75100
125150
175200
225
<1 1 2 3 4 5 6 7 8 9 >10
Age in Years
FAQ Level
Skill by Age How Are The Ranks Determined?Rank Description Total Able Percent1 Walk carrying an Object 746 92%
2 Maneuver in Tight Areas 716 88%
3 Runs 716 88%
4 Step Over Object Right Foot First 704 87%
5 Step Over Object Left Foot First 700 86%
6 Runs with Control 700 86%
7 Walks Carrying a Fragile Object 694 85%
8 Walk Up/Down Stairs with Railing 693 85%
9 Walk Carrying a Fragile Object 692 85%
10 Kick Ball with Left Foot 681 83%
11 Step Backward 677 83%
12 Step Up/Down Curb Independently 661 82%
13 Walk Up/Down Stairs Without Railing 598 72%
14 Jump Off Single Step 584 70%
15 Ride a Three Wheel Bike 569 68%
16 On/Off Escalator Without Help 501 62%
17 On/Off Bus Independently 465 57%
18 Hop on Right Foot 430 46%
19 Hop on Left Foot 417 44%
20 Ice Skate/Roller Skate Independently 263 32%
21 Ride a Two Wheel Bike Wout Training Wheels 188 23%
22 Jump Rope 169 21%
Easist
Most Difficult
Walking Level by Age (up to age 2 1/2)
<1 12-18 mos.
24-30 mos.18-24 mos.
Walking Level by Age (up to age 3)
<1 <1-1.5 <1.5-2<2-2.5
<2.5-3
AACPDM 2013 Clinical Use of FAQ 6
Skill by FAQ LevelAge 3
Questions/Discussion? Problem
•Classical Test Theory Depends on a Normal Distribution Across Levels of Measurement
•Issue for Validation of FAQ-22 in Children with Gait Impairment
•Item-Response Theory & Rasch Analysis
0
2550
75100
125150
175200
225
<1 1 2 3 4 5 6 7 8 9 >10
Rasch & Item Response Theory Analysis
Rasch Analysis: A mathematical logistic model that determinesa person’s ability (relative to the ability of each other person) and the difficulty of an item (relative to the difficulty of all other items) and places them on the same interval measurement scale
person abilityitem difficulty
How Does It Actually Work?
Start out Comparing Each to the Other
object to be measured
person ability
reference for comparison
item difficulty
AACPDM 2013 Clinical Use of FAQ 7
How Does It Actually Work?
Score=0 Score=1
How Does It Actually Work?
Items
Person 1
How Does It Actually Work?
Items
Item 1 score=0
Person 1
How Does It Actually Work?
Items
Item 2 score=1
Person 1
How Does It Actually Work?
Items
Item 3 score=1
Person 1
How Does It Actually Work?
Items
Item 4 score=0
Person 1
AACPDM 2013 Clinical Use of FAQ 8
How Does It Actually Work?
Items
P1 0 1 1 0
How Does It Actually Work?
Items
P1 0 1 1 0
P2 1 1 1 1
P3 0 1 0 0
P4 0 1 1 1
How Does It Actually Work?
Reorder People
P3 0 1 0 0
P1 0 1 1 0
P4 0 1 1 1
P2 1 1 1 1
How Does It Actually Work?
Re-Order Items
P3 0 0 0 1
P1 0 0 1 1
P4 0 1 1 1
P2 1 1 1 1
1 2 3 4
How Does It Actually Work?
Hardest
P3 0 0 0 1
P1 0 0 1 1
P4 0 1 1 1
P2 1 1 1 1
1 2 3 4
Easiest
Least Able
Most Able
How Does It Actually Work?
Items
P3 0 0 0 1
P1 0 0 1 1
P4 0 1 1 1
P2 1 1 1 1
1 2 3 4
Categories: [Easy, A Little Hard, Very Hard, Can’t Do]
FAQ – Polytomous Scoring
AACPDM 2013 Clinical Use of FAQ 9
Results:Gait Impaired
Frequency Distribution of Subjects by Level of Ability
Difficulty of Skills
Results:Typ Develop
Frequency Distribution of Subjects by Level of Ability
Difficulty of Skills
Gait ImpairedTyp Dev
ResultsRank Order of Skills
Results
What Was Next?
Challenge:
Establish an appropriate, clinically meaningful way to integrate multiple measures into a single perspective of how each relates to the other.
What Was Next?
Retrospective study N=485 First time gait analysisAcross GMFCS levels I – IVAll diagnoses (not just CP)Ages: <19 years oldFAQ+PODCI
AACPDM 2013 Clinical Use of FAQ 10
Measures
Objective Self ReportClassification Systems
Gait Deviation Index
PODCIFAQ - Skills
GMFCS LevelFAQ Walking
Results:
Person Ability or Item Difficulty
Rasch-derived Person Ability Map of Function and Walking Ability
Results:Item # Description Measure
(logits)FAQ Walking Level 9 Mean
Ability; 95% CI:1.12,1.451.18
F04 Walk up and down stairs without using the railing
Runs well including around a corner with good control
0.92
F22 Ride an escalator, can step on/off without help
0.72
F12 Jumps off a single step independently
0.43
FAQ Walking Level 8 Mean Ability; 95% CI:0.18,0.55
0.32
GMFCS Level II 0.24F06 runs 0.19F18 Kick a ball with left foot -0.19
F07 0.84
Can get on/off bus by self 0.25
Person Ability or Item Difficulty
Rasch-derived Person Ability Map of Function and Walking Ability
Clinical Scenarios Remember Blake?The family rates his walking at a level 9He is able to do 16 of 22 advanced functional skills
AACPDM 2013 Clinical Use of FAQ 11
Remember Blake?Skills by Age
Remember Blake?Skills by Walking Level
Scenario I: BlakeScenario II
Child who walks at FAQ-WL8 & is able to run, but can’t play hopscotch or skip with friends.
Clinician: Ability to hop is beyond her capability at WL 8, but should be able to “jump off a single step”.
Scenario IIIUnable to ride a two-wheel bike
Scenario III
AACPDM 2013 Clinical Use of FAQ 12
Scenario III
Clinician: Mismatch of skills & walking level
Plan: Determine whether mismatch is skills or walking level. Add:Skills that may be present in the gaps
Scenario IVUnable to jump off a single step
GMFCS Level II
Scenario IV Scenario IV
Clinician: Not a clear mismatch of skills, but many abilities are reported as “very hard” to perform
Plan: Determine whether mismatch is skills or walking level. Add:Skills that may be present in the gaps
Scenario V
3 yr. old who walks at FAQ-WL 10 & is able to do 11 of 22 advanced skills. Crawls at home for primary mobility
Clinician: Mismatch of skills & walking level
Person Ability or Item Difficulty
AACPDM 2013 Clinical Use of FAQ 13
Scenario V
Clinician: Mismatch of skills & walking level
Plan: Determine whether mismatch is skills or walking level. Add:Skills that may be present in the gaps
Scenario VI Walk up/down stairs using a railing
Stand washing hands at sink
Scenario VIScenario VI
Clinician: Mismatch of skills & walking level,GMFCS
Plan: Add skills that may be present in the gaps
Scenario VII Walk one block
Scenario VII
AACPDM 2013 Clinical Use of FAQ 14
Use Before & After Intervention?
Scenario IV-GMFCS II
Pre-Ortho Post-Ortho
GMFCS IVPre-SDR
AACPDM 2013 Clinical Use of FAQ 15
Post-SDRConclusion
Framework to Link Outcome Tools & Classification Systems
Guides Counseling of Families Regarding Functional Expectations
Treatment Planning to Choose Skills within Child’s Capability
Questions?Discussion?
Thank [email protected]@gillettechildrens.com
From
: Stout JL, et al. D
MC
N 2012, 54:443-450.
From
: Stout JL, et al. D
MC
N 2012, 54:443-450.
Skills By Age
Based on Stout J et al. Unpublished data. N=977 parent-report FAQ data of typically developing children. Each cell represents the percentage of children at each age able to perform a particular skill.
Skill <1 1-1.5 1.5-2 2-2.5 2.5-3 3-3.5 3.5-4 4-4.5 4.5-5 walks carrying an object 19 92 98 100 100 100 100 100 100 runs 6 67 98 100 100 100 100 100 100 manuever in tight areas 1 72 96 100 100 100 100 100 100 step over object R foot 3 66 89 89 99 100 100 100 100 step over object L foot 3 65 89 89 96 100 100 100 100 runs well w/control 3 53 95 98 100 100 100 100 100 kick ball R foot 0 55 92 97 97 100 100 100 100 walks up/down stairs with railing 0 50 89 100 100 100 100 100 100 step backward 0 41 89 93 93 100 100 100 100 kick ball L foot 0 51 86 95 96 99 100 100 100 step up/down curb 0 34 69 98 99 100 100 100 100 jump off single step 0 3 36 73 91 99 100 100 100 walks carrying a fragile object 0 5 50 100 100 100 100 100 100 walk up/down stairs w/o railing 0 7 37 86 93 100 100 100 100 ride 3 wheel bike 0 2 30 76 84 96 96 100 100 on/off escalator w/o help 0 0 10 44 64 82 88 96 96 on/off bus 0 0 0 25 48 69 90 90 96 hop right foot 0 0 0 14 28 56 81 98 98 hop left foot 0 0 0 10 22 46 80 98 98 ice skate/roller skate 0 0 0 17 15 23 30 45 57 ride 2 wheel bike 0 0 0 0 0 6 0 20 26 jump rope 0 0 0 0 0 0 0 2 6
Rasch analysis of items from two self-report measures of motorfunction: determination of item difficulty and relationships withchildren's ability levels
JEAN L STOUT1 | GEORGE E GORTON III2 | TOM F NOVACHECK1 | ANITA M BAGLEY3 | RAYMOND C TERVO1 |KATHERINE BEVANS4 | CAROLE A TUCKER5
1 Gillette Children's Specialty Healthcare, St Paul, MN; 2 Shriners Hospitals for Children, Springfield, MA; 3 Shriners Hospitals for Children- Northern California Unit,Sacramento, CA; 4 Children's Hospital of Philadelphia, Philadelphia, PA; 5 Temple University, Philadelphia, PA, USA.
Correspondence to Jean L Stout at James R Gage Center for Gait and Motion Analysis, Gillette Children's Specialty Healthcare, 205 East University Avenue, St Paul, MN 55101, USA. E-mail:[email protected]
This article is commented on by Gates on pages 391–392 of this issue.
PUBLICATION DATA
Accepted for publication 18th November 2011.Published online 14th March 2012.
ABBREVIATIONSFAQ Gillette Functional Assessment
QuestionnaireFAQ-WL Gillette Functional Assessment
Questionnaire walking scale levelGDI Gait Deviation IndexPODCI Pediatric Outcome Data Collection
InstrumentSPF Sports and physical functionTBM Transfers and basic mobility
AIM The aim of this article was to determine item measurement properties of a set of items
selected from the Gillette Functional Assessment Questionnaire (FAQ) and the Pediatric Outcome
Data Collection Instrument (PODCI) using Rasch analysis, and to explore relationships between
the FAQ ⁄ PODCI combined set of items, FAQ walking scale level, Gross Motor Function Classifica-
tion System (GMFCS) levels, and the Gait Deviation Index on a common measurement scale.
METHOD Rasch analysis was performed on data from a retrospective chart review of parent-
reported FAQ and PODCI data from 485 individuals (273 males; 212 females; mean age 9y 10mo,
SD 3y 10mo) who underwent first-time three-dimensional gait analysis. Of the 485 individuals, 289
had a diagnosis of cerebral palsy (104 GMFCS level I, 97 GMFCS level II, 69 GMFCS level III, and 19
GMFCS level IV). Rasch-based person abilities and item difficulties based on subgroups defined
by the FAQ walking scale level, Gait Deviation Index, and the GMFCS level were compared.
RESULTS The FAQ ⁄ PODCI item set demonstrated necessary Rasch characteristics to support its
use as a combined measurement scale. Item groupings at similar difficulty levels were consistent
with the mean person abilities of subgroups based on FAQ walking scale level, Gait Deviation
Index, and GMFCS level.
INTERPRETATION Rasch-derived person ability scores from the FAQ ⁄ PODCI combined item
set are consistent with clinical measures. Rasch analysis provides insights that may improve
interpretation of the difficulty of motor functions for children with disabilities.
Improvements in mobility, ambulation, and enhanced partici-pation in activities with family and peers are often identified asprimary goals of clinical and surgical interventions for childrenand adolescents with physical impairments. Clinical measure-ment of ambulation and functional mobility can be accom-plished using a variety of measures including instrumentedgait analysis, standardized clinical assessments of gross motorskills, and ⁄ or self-reported outcomes. Despite concern aboutthe accuracy of self- ⁄ proxy report,1–3 the perspective providedby the affected individual and ⁄ or family adds important insightinto both goal setting and the assessment of outcome.
The reporting of multiple assessments, however, is complex.The International Classification of Functioning, Disability;and Health (ICF) framework4 has become an important orga-nizing framework for health and disability in rehabilitationresearch. Within the ICF framework, an activity is defined asthe execution of a task or action by an individual. Participationis defined as involvement in a life situation. The ICF providestwo qualifiers for activity and participation: (1) ‘capacity’ – what
a child is able to do in an ideal environment, the highest func-tioning level; and (2) ‘performance’ – what a child actually doesin the environment in which they live. Since the ICF’s emer-gence in 2001, the use of these ICF qualifiers, along with ‘capa-bility’ – a child’s capacity influenced by environmental factorsand choice – have become increasingly important in clinicalresearch, particularly in assessing treatment efficacy anddescribing the range of function for the child with a disabil-ity.5–7 Existing validated instruments often predate the emer-gence of the ICF, and may include within a single instrumentitems that measure capability, capacity, or performance, andgenerically use words (capable, skill, ability, etc.) in their instru-ment description that now have additional, specific ICF-relatedmeanings. The fact that existing instruments often blend mea-surement of different ICF components and qualifiers of func-tioning and disability complicates the issues faced by cliniciansand researchers in their choice of appropriate instruments.
Ideally, a comprehensive battery of instruments chosen tocharacterize function would be structured to ‘fit’ together to
ª The Authors. Developmental Medicine & Child Neurology ª 2012 Mac Keith Press DOI: 10.1111/j.1469-8749.2012.04231.x 443
DEVELOPMENTAL MEDICINE & CHILD NEUROLOGY ORIGINAL ARTICLE
provide the greatest breadth of assessment, with each measureadding complementary information about the person’s statuswithout adding redundancy. Often, however, each instrumentin a given battery is reported in isolation from the others –lacking a common context of how each relates to the others.Approaches that provide common measurement across instru-ments can help to reduce the complexity introduced by theuse of multiple instruments.
Rasch analysis can be used to create a common, continuousinterval-level measurement scale for estimates of both ‘personability’ (how much of the underlying construct the persondemonstrates) and ‘item difficulty’.8 The Rasch terms‘person ability’ and ‘item difficulty’ have a specific meaning inthis context. This person item mapping indicates the probabil-ity that an individual of a certain ‘person ability’ can performspecific items based on each ‘item’s difficulty’. Recent outcomeassessments of physical function have used Rasch or itemresponse theory analyses to more fully evaluate the measure-ment properties of the instruments on an item-level basis9–14
and in designing functional staging systems which have beenfound to be useful in enhancing clinical decision making.15,16
The Gillette Functional Assessment Questionnaire(FAQ)10,17 and the Pediatric Outcome Data Collection Instru-ment (PODCI)9,18–21 are self- ⁄ parent-report measures ofphysical abilities commonly used in pediatric clinical practice.Both are often used in conjunction with the Gross MotorFunction Classification System (GMFCS)22,23 to describefunction and walking ability in children with cerebral palsy(CP).24–26 The FAQ consists of a 10-level classification ofwalking ability (FAQ walking scale level or FAQ-WL) and 22functional activities rated on a five-point Likert difficulty scale(FAQ-22). The FAQ-WL portion of the FAQ has been vali-dated as a measure of functional walking status.17 The PODCIconsists of 86 items divided into eight subscales. The PODCIis ‘designed to assess overall health, pain, and participation innormal daily activities as well as in more vigorous activitiesassociated with young people.’18 The transfers and basicmobility (TBM) subscale consists of 11 items, and the sportsand physical function (SPF) subscale consists of 21 items (12tasks and nine conditional responses). PODCI test scores andsubscales have been shown to be reliable and valid.19 Factor-and item-level properties of both the FAQ and PODCI instru-ments have been previously reported.9,10 Items contained inboth measures (FAQ and PODCI) reflect a blend of ICFactivity and participation concepts because the ICF emergedafter the development of these instruments. Therefore, theunderlying construct being assessed by these instruments isreflective of more general physical functioning.
Rasch analysis can be used to establish the relationshipbetween items from the FAQ-22 and PODCI TBM ⁄ SPF itemson a common difficulty scale. Subsequent stratification of indi-viduals based on classification systems such as the FAQ-WLand GMFCS and measures of gait impairment such as the GaitDeviation Index (GDI)27 may reveal additional relationships,which will allow clinicians to have a higher level of confidencethat certain physical skills tend to be associated with a specificclassification of functional mobility or gait impairment.
The purposes of this study were to assess the factor- anditem-level properties of a combined FAQ-22 and PODCITBM ⁄ SPF item set, and to explore the associations betweenthe Rasch-ordered combined FAQ-22 ⁄ PODCI TBM ⁄ SPFitem set, with participant groupings based on the FAQ-WL,GMFCS, and GDI.
METHODA retrospective medical record review of FAQ (FAQ-WL andthe FAQ-22), PODCI (TBM ⁄ SPF scale), and GDI data wasconducted on a group of children and young adults (<19y)who underwent first-time gait analysis in a tertiary hospitalsetting between January 2006 and June 2008. GMFCS levelwas included for children with a diagnosis of CP. FAQ andPODCI data were obtained by proxy report of the parents orlegal guardian as part of the routine clinical gait analysis. AllFAQ-22 items, nine of 11 PODCI-TBM subscale items, andfive of 12 PODCI-SPF subscale items scored on a similar five-point Likert difficulty scale were included for analysis. Thetwo excluded TBM items measure frequency of assistanceneeded, a different construct, rather than a specific physicalskill. The excluded SPF items either measure frequency ofassistance needed or are structured as multiple responses to asingle item with conditional responses that are not on a five-point Likert difficulty scale which did not allow these items tobe included in the analysis. Waiver of informed consent andHealth Insurance Portability and Accountability Act authori-zation were obtained for this study from the local institutionalreview board. Individuals whose families had opted out of useof medical records for research were excluded.
Statistical analysisExploratory and confirmatory factor analysis was conductedusing MPlus 5.1 software28 to validate the structure of thecombined FAQ-22 ⁄ PODCI TBM ⁄ SPF item set. Model fitwas examined via multiple indices including the ConfirmatoryFit Index, the Tucker–Lewis Index, and standardized rootmean square residual. Confirmatory Fit Index and Tucker–Lewis Index values greater than 0.95 and a standardized rootmean square residual less than 0.08 indicate good fit of themodel to the data. Data were tested to ensure that the statisti-cal assumptions for Rasch analyses were met. The Rasch rat-ing scale model was implemented using Winsteps software29
to simultaneously determine item difficulty or location (i.e.the difficulty level of each item relative to other items in thescale), person ability (i.e. the ability level of each person rela-tive to other persons in the sample), and item-level fit statistics(degree of variation in the responses relative to the predicted
What this paper adds• This article provides a Rasch analysis of item-level measurement characteris-
tics of a combined FAQ ⁄ PODCI item set which exhibits better content cover-age and greater precision than either item set alone.
• Item groupings at similar difficulty levels were consistent with the mean per-son abilities of subgroups based on FAQ-WL, GDI, and GMFCS level.
• Clinically meaningful integration of self-report measures (FAQ ⁄ PODCI), clinicalscales (GMFCS), and objective (GDI) assessments are described.
444 Developmental Medicine & Child Neurology 2012, 54: 443–450
responses) for the combined FAQ-22 ⁄ PODCI TBM ⁄ SPFitem set. The Rasch model uses a log odds units (logit) scale,which is linear and additive. Logit distances describe the rela-tive performance on adjacent categories of the response scale.For our Likert scale, there is a point on the latent trait of phys-ical functioning at which ‘some difficulty’ and ‘much difficulty’are equally likely to be observed. So, on a logit scale at a point1.4 logits higher, ‘much difficulty’ is likely to be observed eighttimes for every two times that ‘some difficulty’ is observed.Precision (standard error) of the estimated person ability usingthe PODCI TBM ⁄ SPF items alone, the FAQ-22 items alone,and the combined set of FAQ-22 ⁄ PODCI TBM ⁄ SPF item setwas calculated based on the assumption that all items werecompleted.
All children were subsequently grouped by their FAQ-WL.Children with CP were also separately grouped by theirGMFCS level. In each of the subgroups for the FAQ-WL andGMFCS level, the mean Rasch-based person ability scorefrom the combined FAQ-22 ⁄ PODCI TBM ⁄ SPF item set wasdetermined. The differences between mean person abilityscores of the FAQ-WL and GMFCS subgroups were testedusing analysis of variance (ANOVA; p < 0.05) with least signifi-cant difference post hoc testing, correcting for multiple com-parisons if the main effect of the factor (FAQ-WL or GMFCSlevel) was significant. These resultant mean and related 95%confidence intervals were then compared with the item diffi-culty statistics from Rasch analysis to determine the corre-sponding sets of items that individuals at each GMFCS leveland FAQ-WL could be expected to perform with a 50%probability.
Pearson’s correlations were calculated between the GDIand person ability measures. The GDI was also used to groupchildren. The continuous GDI scores, ranging from 42 to116, were transformed to a discrete measure by creating five1-SD bins for GDI scores from 50 to 100 (50.1–60, 60.1–70,etc.). Those with GDI scores below 50 were grouped togetherand those with GDI scores above 100 were grouped together.The differences in mean person ability scores among GDIbins was tested using ANOVA (p < 0.05) with least significantdifference post hoc testing if the main effect of the factor(GDI bin) was significant.
RESULTSNine hundred thirty-five children and adolescents had gaitanalysis during the specified time frame. Of those 935, 485who had first-time gait analysis met the criteria for inclusion.Two hundred and eighty-nine children had a diagnosis of CP(104 GMFCS level I, 97 level II, 69 level III, 19 level IV) and196 children had other neurological or musculoskeletal diag-noses (73 orthopedic, 39 neuromuscular, 30 joint disorder, 17acquired brain injury, 11 genetic, 26 miscellaneous). Mean agewas 9 years 10 months (SD 3y 10mo). Demographic data aresummarized in Table I.
Exploratory and confirmatory factor analysis of the com-bined FAQ-22 ⁄ PODCI TBM ⁄ SPF item set indicated a suffi-ciently unidimensional underlying construct as only twofactors explained more than 5% of the variance. The ratio of
these two factors was greater than 12:1, indicating dominanceof the single factor. Consistently high communalities (range0.666–0.904) indicated that approximately 80% of the com-mon variance is represented by a single latent factor. Themodel goodness of fit statistics demonstrated adequate one-factor model fit (standardized root mean square resid-ual=0.071; Tucker–Lewis Index=0.976; Confirmatory FitIndex=0.979). Data met the statistical assumption of monoto-nicity necessary for subsequent Rasch analysis. Local depen-dence in 26 of 535 item pairings was noted, but the itemsretained. The item fit statistics for the combined item set areshown in Table SI (supporting information published online).
The resultant item person map showing the relationship ofthe combined set of item difficulties to the distribution of per-son abilities in the sample is provided in Figure 1. Item diffi-culties ranged from easiest (‘sit in a regular chair withoutholding on’ at )3.1 logits) to hardest (‘ice skating or rollerskating’ at 2.8 logits; Fig. 1 and Table II). Rasch analyses dem-onstrated adequate fit of all items except one (‘ride a three-wheel bike [or a two-wheel bike with training wheels]’) whichwas retained in the analyses. No floor or ceiling effects werenoted. The range of item difficulties closely matched the rangeof person abilities, with 35 of 36 skills (97%) falling within2 SDs of the mean person ability (Fig. 1).
The Rasch-derived person item map shown in parallel withmean (standard error) participant groupings based on FAQ-WL and GDI for all children and GMFCS level for those withCP is found in Figure 2. This figure illustrates the relationshipbetween the ability level of the person and the relevant tasksthat this person is likely and unlikely to be able to accomplish.It also depicts the relationship between the FAQ-WL,GMFCS, and GDI with item difficulties.
Estimated person abilities based on the FAQ-22 ⁄ PODCITBM ⁄ SPF item set exhibited strong correlation with classifi-cation by FAQ-WL (Spearman’s rho = 0.739; p < 0.001) andGMFCS level (Spearman’s rho = )0.777; p < 0.001). There wasa significant difference in mean estimated person ability whengrouped by FAQ-WL classifications 6 to 10. Post hoc testing
Table I: Demographics and breakdown of available data by diagnosiscategory
Overall(n=485)
Cerebral palsy(n=289)
Other(n=196)
Sex, M ⁄ F 273 ⁄ 212 172 ⁄ 117 101 ⁄ 95Mean age (SD), y 9.9 (3.8) 9.1 (3.8) 11.1 (3.7)GMFCS (CP only) level
I – 104 –II – 97 –III – 69 –IV – 19 –
FAQ, n 479 285 194PODCI, n 465 277 188GDI, n 480 284 196
Age range for all children is 3 to 19 years. Differences in total numbersrepresent missing data values for some variables. n, number totals;GMFCS, Gross Motor Function Classification System; FAQ, GilletteFunctional Assessment Questionnaire; PODCI, Pediatric Outcome DataCollection Instrument; GDI, Gait Deviation Index.
Rasch Analysis of the FAQ ⁄ PODCI Jean L Stout et al. 445
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#######.###
###.#.#
#.
.
.
.
.
.###########
######
##########
.#####
.# T
T
S
S
M
M
S
S
T
T
#
.#
.
#
5
4
3
2
1
0
–1
–2
–3
–4
–5(less able) (less difficult)
PODCI29
PODCI31
PODCI28
PODCI7
FAQ1
FAQ16
FAQ10FAQ12
FAQ22
FAQ13
FAQ19FAQ11
FAQ21
FAQ14
FAQ7FAQ4
FAQ17 FAQ18 FAQ20FAQ8 FAQ9FAQ15 FAQ5
FAQ3
PODCI30
PODCI24PODCI21
PODCI19PODCI20
PODCI33
PODCI22
PODCI25
PODCI23PODCI18FAQ6FAQ2
Persons(more able) (more difficult)
– –MAP Items
Figure 1: Rasch Item Person Map. The frequency distribution of the sample by person ability (left) and item difficulty (right) is demonstrated on a single diffi-culty continuum. The vertical scale (logits) is an interval scale which represents the relative difficulty of lower extremity function, with lower numbers repre-senting easier skills (less person ability) and higher numbers representing more difficult skills (more person ability). Each `#' represents three children andeach `.' represents one child. Items in the right hand column include the Gillette Functional Assessment Questionnaire (FAQ) items (FAQ1:22) and PediatricOutcome Data Collection Instrument (PODCI) transfers and basic mobility ⁄ sports and physical function (TBM ⁄ SPF) items (PODCI*). Please refer to Table IIfor item descriptions. Ideally, these two columns (item responses and person ability) should appear similar, with the distribution of possible item responsesand person skill ability spread similarly across the difficulty scale. Distribution shows that most items and abilities surround the mean and 1 SD. M, mean; S,one SD; T, 2 SD of person ability (left) or item difficulty (right).
446 Developmental Medicine & Child Neurology 2012, 54: 443–450
indicated that each estimated mean person ability for eachFAQ-WL 6 to 10 was statistically different from all otherFAQ-WLs (ANOVA; p < 0.05). There was a significant differ-ence in estimated person ability when grouped by GMFCSlevel (ANOVA; p < 0.05). The mean person ability for eachGMFCS level was statistically different from all otherGMFCS levels.
Similarly, the GDI exhibited a good correlation with esti-mated person abilities based on the FAQ-22 ⁄ PODCITBM ⁄ SPF item set (Pearson’s rank correlation coeffi-cient = 0.643; p < 0.001). As a continuous variable, each GDIscore has a broad range of abilities possible, and for each esti-mated person ability score there is a broad range of GDIscores possible (r2=0.42). When the person ability scores weregrouped into GDI SD bins, there were significant differencesin average ability score between the bins (ANOVA; p < 0.05).Post hoc testing revealed that Rasch-derived person scores foreach group by GDI 10-point bin was statistically different(p < 0.05) from all others except for GDI 50 to 60 with GDI60 to 70.
Precision of the combined FAQ-22 ⁄ PODCI TBM ⁄ SPFitem set was assessed by calculating the standard error for eachability score. The standard error of the model for each scorealong the ability spectrum is shown in Figure S1 (supportinginformation published online). At the high and low end ofscoring where there are few items that measure or provideinformation at these ability levels and few people with thoselevels of ability, the standard errors are, as expected, higher.Precision is best (standard errors are lowest) in the middle ofthe ability scale, where many tasks target that ability level andmany respondents have their ability. The combined item setmeasures a greater range of person abilities (content coverage)with better precision than either item set alone.
DISCUSSIONThe item difficulties derived from the Rasch analysis in thisstudy resulted in an interval-level measurement scale whichenables direct comparison of item difficulties between items
Table II: The 22 FAQ skill items and 14 PODCI TBM ⁄ SPF Items are shownin order of difficulty on an interval scale
Item no. DescriptionMeasure(logits)
GDI ‡ 100.1; CI: 2.46, 3.86 3.16FAQ Walking Level 10 Mean Ability;95% CI: 2.45, 3.06
2.76
F21 Ice skate or roller skate 2.71F11 Jump rope 2.30
GDI 90.1–100.0; CI: 1.83, 2.67 2.25F19 Ride 2 wheel bike (without
training wheels)2.02
GDI 80.1–90.0; CI:1.54,2.08 1.81F13 Hop on right foot 1.66F14 Hop on left foot 1.65
GMFCS Level I Mean Ability;95% CI:1.36,1.82
1.59
P22 Walk more than a mile 1.55FAQ Walking Level 9 Mean Ability;95% CI:1.01, 1.36
1.18
F04 Walk up and down stairs withoutusing the railing
0.92
F07 Runs well including around a cornerwith good control
0.84
GDI 70.1–80.0; CI:0.52,0.99 0.76F22 Ride an escalator, can step
on ⁄ off without help0.72
P20 Climb three flights of stairs 0.61F12 Jumps off a single step independently 0.43P19 Bicycle or tricycle 0.42
FAQ Walking Level 8 Mean Ability;95% CI:0.13, 0.52
0.32
F10 Can get on and off a bus byhim ⁄ herself
0.25
F02 Walk carrying a fragile object orglass of liquid
0.24
P18 Run short distances 0.24GMFCS Level II Mean Ability;95% CI:0.04, 0.44
0.24
P23 Walk three blocks 0.21F06 Runs 0.19P25 Get on and off the bus )0.13F18 Kick a ball with left foot )0.19F20 Ride 3 wheel bike (or 2 wheel bike
with training wheels))0.19
F17 Kick a ball with right foot )0.25F16 Step over an object, left foot first )0.29F15 Step over an object, right foot first )0.30
FAQ Walking Level 7 Mean Ability;95% CI: )0.73, 0.00
)0.37
F08 Can take steps backwards )0.39GDI 60.1–70.0; CI: )0.63, )0.18 )0.40GDI 50.1–60.0; CI: )0.64, )0.03 )0.41
F05 Steps up and down curb independently )0.41F09 Can maneuver in tight areas )0.42P33 Bend over from standing; pick
something off floor)0.72
P21 Climb one flight of stairs )0.77F01 Walk carrying an object )0.82F03 Walk up and down stairs
using the railing)0.90
GMFCS Level III Mean Ability;95% CI: )1.16, )0.72
)0.94
FAQ Walking Level 6 Mean Ability;95% CI: )1.30, )0.63
)0.97
P24 Walk one block )0.98P7 Put on coat )1.18
GDI <=50; 95% CI: )2.06, )0.81 )1.43FAQ Walking Level £5 Mean Ability;95% CI: )1.93, )1.01
)1.47
P30 Get on and off a toilet or chair )1.73
Table II: Continued
Item no. DescriptionMeasure(logits)
P28 Stand while washing handsand face at a sink
)1.88
GMFCS Level IV Mean Ability;95% CI: )2.77, )1.09
)1.93
P31 Get in and out of bed )2.23P29 Sit in a regular chair without holding on )3.13
F, FAQ-22 item; P, PODCI item. Measure ‘logits’ represents a non-dimensional level of difficulty. Higher ‘measure’ scores represent moredifficult tasks. Mean and 95% confidence interval of the average abilitylevels by GMFCS (bold), GDI bin (italic), and FAQ Walking Level(shadow pink) are shown. Average ability represents a 50% probabilityof successfully achieving a skill of the same level. Probability ofsuccess for a given level of person ability or classification grouping ishigher for items of lesser difficulty and lower for items of higherdifficulty. FAQ Walking Level £5 N=30 (14 FAQ-WL 5; 12 FAQ-WL 4; 2FAQ-WL 3; 2 FAQ-WL 2).
Rasch Analysis of the FAQ ⁄ PODCI Jean L Stout et al. 447
from two different instruments of physical functioning. Bothmeasure a blend of ICF activity and participation qualifiers, sothe resultant represents not a single ICF aspect but a more gen-eral construct of physical functioning. The resultant calibrationof items from both instruments collected on the same sample(common people) provides a means to relate scores from theindividual measures (FAQ-22 and PODCI TBM ⁄ SPF) to eachother as well as to scores derived from the combined set. Inaddition, interpretation is now enhanced as the magnitude ofdifficulty between skills and person abilities is established onone common continuous interval scale. Individuals with Raschperson ability scores at a given level have a 50% probability ofsuccessfully completing skills at that same level of itemdifficulty. The improved precision and content coverage of thecombined FAQ-22 ⁄ PODCI TBM ⁄ SPF item set suggests thatthe use of both tools together may be an improved measure ofphysical functioning compared with using either instrument
alone. This reflects both the increased number of items in thecombined set and the distribution of items along the scale.Additional work to refine the set of items would be useful. Itemswith local dependence should be divided between different, butstill directly comparable, instrument versions.
When the individuals in the sample are grouped by FAQ-WL, GMFCS level, or GDI SD bin, their classification levelcan be related to groups of items that fall within the confidenceband of the group. For example, the relationship between FAQ-WL 8 and FAQ-22 skills ‘runs’ and ‘jump off a single step’ isnow established. Individuals’ estimated abilities can be associ-ated with the likelihood of their successful performance of agiven skill or set of skills. It broadens the scope of understandingof function beyond the interpretation of each tool or systemindividually, and establishes the relationship between item diffi-culties and person abilities. The information is specific enoughto be of practical use to clinicians, children, and families. For
–4.00
Easiest items
least able people
Hardest itemsmost able people
FAQ skill set
FAQ walking level
GMFCS level
PODCI items
GDI
Sit in
a re
gular
chair
Get in
and
out
of b
ed
Get o
n an
d of
f a to
ilet o
r cha
ir
Walk
1 b
lock
Put o
n co
at
Climb
1 flig
ht fo
stair
s
Bend
over
; pick
from
floor
Get o
n an
d of
f the
bus
Walk
3 b
locks
Run sh
ort d
istan
ces
Bicycle
or t
ricyc
le
Climb
3 flig
hts o
f sta
irs
Walk
a m
ile
Walk
up/
down
stairs
usin
g ra
iling
FAQ ≤≤5
GMFCS 4
GMFCS 3
GMFCS 2
GMFCS 1
GDI ≤50
GDI 50–
60
GDI 60–
70
GDI 70–
80
GDI 80–
90
GDI 90–
100
GDI >10
0
FAQ 6
FAQ 7
FAQ 8
FAQ 9
FAQ 10
Walk
carry
ing o
bject
Man
euve
r in
tight
are
as
Step
up/d
own
curb
Step
back
wards
Step
over
obje
ct
Ride 3
whe
el bik
e
Kick a
ball
Runs
Get o
n/of
f a b
us
Walk
carry
ing a
frag
ile o
bject
Jum
p of
f a si
ngle
step
Ride a
n es
calat
or
Runs w
ell in
cludin
g ar
ound
a co
rner
Walk
up/
down
stairs
with
out r
ailing
Hop o
n R/L
foot
Ride 2
whe
el bik
e
Jum
p ro
pe
Ice sk
ate
or ro
ller s
kate
Stand
was
hing
hand
s at s
ink
–3.00 –2.00 –1.00 0.00
Person ability or item difficulty (logits)
1.00 2.00 3.00 4.00
Figure 2: Rasch-derived person item map and functional classification subgroups. Item level difficulty scores for the combined Gillette Functional Assess-ment Questionnaire (FAQ) FAQ-22 ⁄ Pediatric Outcome Data Collection Instrument (PODCI) transfers and basic mobility ⁄ sports and physical function(TBM ⁄ SPF) item set are shown in parallel with mean (standard error) person ability participant groupings based on FAQ-WL 5 to 10 and 1 SD Gait DeviationIndex (GDI) bins for all individuals, and Gross Motor Function Classification System (GMFCS) levels I to IV for children with cerebral palsy. The likelihood ofan individual being able to successfully perform specific skills is demonstrated. An individual at a given ability level will have a 50% chance of successfullyperforming a skill of that same difficulty level. For example, a child with a GMFCS level II classification has a 50% probability of being able to run shortdistances and a 50% probability of being able to walk carrying a fragile object. The same child has approximately a 12.5% probability of being able to walkup ⁄ down stairs without a railing because the skill is almost four times as difficult based on the logit scale. The FAQ-22 and PODCI TBM ⁄ SPF items areseparated only to more clearly identify each. The vertical dashed lines from the PODCI TBM ⁄ SPF items to the FAQ-22 items depict where they are locatedif presented as a single item set. The person ability or item difficulty is an interval scale.
448 Developmental Medicine & Child Neurology 2012, 54: 443–450
example, when a child who walks at a FAQ-WL 8 and is able torun describes the difficulty encountered when attempting toplay hop-scotch or to skip with friends, the clinician now has atool to demonstrate that the ability to hop is more difficult thanthe ability to run. The same child, however, should be expectedto have the ability to ‘jump off a single step’ as it is within therange of item difficulty of the person ability estimate.
This study produced a model that matches clinical impres-sion of differences in skill level based on a GMFCS level. Forexample, the level of difficulty assigned to the ability to ‘walkup ⁄ down stairs without a railing’, a common skill used to dif-ferentiate between GMFCS levels I and II, clearly fallsbetween the two GMFCS levels on the difficulty scale.Another example, the ability to ‘hop on the right or left foot’,is associated with GMFCS I. The FAQ-22 skill set (designedto be a set of skills more advanced than walking) is associatedwith GMFCS levels I to III. Specifically, all FAQ-22 itemshad an estimated difficulty higher than the PODCI item ‘walkone block’, which has an estimated difficulty of )0.98. PODCIskills ‘get in ⁄ out of bed’ and ‘get on ⁄ off a toilet or chair’ arewithin a level of difficulty assigned to GMFCS IV. Across alllevels, the level of difficulty assigned to skills appears to beconsistent with clinical impression.
Understanding each perspective of function (proxy-reportinstruments, classification systems, and GDI) in the context ofthe others provides the clinician with a more complete inte-grated context for interpretation. Although previous reportshave demonstrated that measures of gait pathology such as theGDI or the Gait Profile Score distinguish between each pairof community walking levels on the FAQ,27,30 how they relatein difficulty has not been previously established. This can pro-vide direction for therapies, as well as counseling for familiesregarding expectations of their child’s abilities. It also canidentify mismatches in reported function.
A limitation of this study is that item misfit and responsedependency were found within our item set, but were notaccounted for within the study. The sample size impact on in-fit and outfit statistics may also be a potential limitation. A rec-ommendation for further work would be to investigate theimpact of this misfit and response dependency upon the scal-ing characteristics of the grouped item set.
The retrospective nature of our study limited the items andinstruments to those that were available on a large commonparticipant sample. Therefore, we focused our analyses on aversion of the FAQ-22 and a subset of the PODCI(TBM ⁄ SPF). The subset of PODCI items selected for analysesrelied on the same five-point Likert difficulty scale as the FAQ-22 in order to maintain consistency of item structure for theRasch analysis. The excluded items were frequency of personal
assistance or use of assistive device questions (sitting ⁄ standing[TBM] and walking ⁄ climbing [SPF]) not associated with anyparticular skill. In addition, the PODCI SPF items concerningparticipation in recreational outdoor activities, pick-up gamesor sports, competitive level sports, and gym ⁄ recess also wereexcluded as the structure of the questions included a condi-tional response that is not consistent with other questions. Wewould expect that if these items were included, the upper rangeof the PODCI item coverage would be extended toward themore difficult end, as found for the FAQ-22 items.
Another potential limitation is the inclusion of only childrenwho were ambulatory and referred for gait analysis. Hence,our results should be interpreted very cautiously in non-ambu-lant children with lower skill levels than our study sample andare not an exhaustive query of functional skills, which areimportant supplements to locomotion. Given that the scope ofour work was on application of Rasch analyses to improve ourknowledge of the measurement properties of the combinedinstruments, we did not attempt to directly map the includeditems to specific ICF components and qualifiers. Future workusing a prospective longitudinal design will help to define reli-ability and responsiveness, including the minimum clinicallyimportant difference. Studies of changes in skill ability as aresult of intervention are also needed.
CONCLUSIONSThe combined FAQ-22 ⁄PODCI TBM ⁄ SPF item sets orderedusing Rasch analysis lays the foundation for a framework to linkoutcome tools. This study represents an initial attempt to relateperson ability and skill difficulty to functional classification andgait impairment. The association between the classificationscales and GDI and a specific cluster of items from the ordereditem set may help clinicians to better understand the relation-ship between each type of measure and potentially to guidetreatment with a level of confidence that specific skills are withinthe child’s capability. With continued efforts, the potential for aparadigm shift to an integrated view of how lower extremityfunction is conceptualized, measured, and reported is possible.
ACKNOWLEDGMENTSThis study was funded in part by an American Academy for Cerebral
Palsy and Developmental Medicine Planning Grant 2008. The
funding agency did not participate in any way in the conceptualiza-
tion, design, data collection, data analysis, manuscript preparation,
and ⁄ or publication decisions.
SUPPORTING INFORMATIONSupporting information may be found in the online version of this
article.
REFERENCES
1. Sheffler LC, Hanley C, Bagley A, Molitor F, James MA.
Comparison of self-reports and parent proxy-reports of func-
tion and quality of life of children with below-the-elbow
deficiency. J Bone Joint Surg Am 2009; 91: 2852–9.
2. Burns R, Olson I, Kazmucha J, Balise R, Chin R, Chin C.
Correlation of subjective questionnaires with cardiac func-
tion as determined by exercise testing in a pediatric popula-
tion. Pediatric Cardiol 2010; 31: 1043–8.
3. Ravelli A, Viola S, Migliavaa D, Pistorio A, Ruperto N, Mar-
tini A. Discordance between proxy-reported and observed
assessment of functional ability of children with juvenile idio-
pathic arthritis. Rheumatology 2001; 40: 914–9.
4. World Health Organization. International Classification of
Functioning, Disability and Health. Geneva: World Health
Organization, 2001.
5. Young NL, Williams IJ, Yoshida KK, Bombardier C, Wright
JG. The context of measuring disability: does it matter
Rasch Analysis of the FAQ ⁄ PODCI Jean L Stout et al. 449
whether capability or performance is measured? J Clin Epi-
demiol 1996; 49: 1097–101.
6. Morris C. Measuring participation in childhood disability:
how does the capability approach improve our understand-
ing? Dev Med Child Neurol 2009; 51: 92–4.
7. Holsbeeke L, Ketelaar M, Schoemaker MM, Gorter JW.
Capacity, capability, and performance: different constructs
or three of a kind? Arch Phys Med Rehabil 2009; 90:
849–55.
8. Linacre M. A User’s Guide to WinSteps Rasch-model Com-
puter Program. Chicago: MESA Press, 2004.
9. Allen DD, Gorton GE, Oeffinger DJ, Tylkowski C,
Tucker CA, Haley SM. Analysis of the pediatric out-
comes data collection instrument in ambulatory children
with cerebral palsy using confirmatory factor analysis and
item response theory methods. J Pediatr Orthop 2008;
28: 192–8.
10. Gorton GE, Stout JL, Bagley AM, Bevans K, Novacheck
TF, Tucker CA. Gillette functional assessment questionnaire
22 item skill set: factor and Rasch analysis. Dev Med Child
Neurol 2011; 53: 250–5.
11. Bagley AM, Gorton GE, Bjornson K, et al. Factor- and
item–level analysis of the 38-item activities scale for kids-per-
formance. Dev Med Child Neurol 2011; 53: 161–6.
12. Avery LM, Russell DJ, Raina PS, Walter SD, Rosenbaum
PL. Rasch analysis of the gross motor function measure:
validating the assumptions of the Rasch model to create
an interval level measure. Arch Phys Med Rehabil 2003;
84: 697–705.
13. Haley SM, Pengsheng N, Ludlow LH, Fragala-Pinkham
MA. Measurement precision and efficiency of multidimen-
sional computer adaptive testing of physical functioning
using the pediatric evaluation of disability inventory. Arch
Phys Med Rehabil 2006; 87: 1223–9.
14. Vollmer B, Holmstrom L, Forsman L, et al. Evidence of
validity in a new method for measurement of dexterity in
children and adolescents. Dev Med Child Neurol 2010; 52:
948–54.
15. Tao W, Haley SM, Coster WJ, Pengsheng N, Jette A. An
exploratory analysis of functional staging using an item
response theory approach. Arch Phys Med Rehabil 2008; 89:
1046–53.
16. Wang YC, Hart DL, Stratford PW, Mioduski JE. Clinical
interpretation of a lower-extremity functional scale-derived
computerized adaptive test. Phys Ther 2009; 89: 957–68.
17. Novacheck T, Stout JL, Tervo R. Reliability and validity of
the gillette functional assessment questionnaire as an out-
come measure in children with walking disabilities. J Pediatr
Orthop 2000; 20: 75–81.
18. American Academy of Orthopedic Surgeons. PODCI ⁄ PO-
SNA Outcomes Data Collection Instruments. http://
www.aaos.org/research/outcomes/outcomes_peds.asp
(accessed 4 October 2010).
19. Daltroy LH, Liang MH, Fossel AH, Goldberg MJ. The PO-
SNA pediatric musculoskeletal functional health question-
naire: report on reliability, validity, and sensitivity to change.
J Pediatr Orthop 1998; 18: 561–71.
20. Barnes D, Linton JL, Sullivan E, et al. Pediatric outcome
data collection instrument scores in ambulatory children with
cerebral palsy. J Pediatr Orthop 2008; 28: 97–102.
21. Haynes RJ, Sullivan E. The pediatric orthopaedic society of
North America pediatric orthopaedic functional health ques-
tionnaire: an analysis of normals. J Pediatr Orthop 2001; 21:
619–21.
22. Palisano R, Rosenbaum P, Walter S, Russell D, Wood E,
Galuppi B. Development and reliability of a system to classify
gross motor function in children with cerebral palsy. Dev
Med Child Neurol 1997; 39: 214–23.
23. Palisano R, Rosenbaum P, Bartlett D, Livingston M. Gross
Motor Function Classification System – Expanded & Revised
(GMFCS-E&R). CanChild Centre for Childhood Disability
Research, McMaster University, 2007. http://motor-
growth.canchild.ca/en/GMFCS/resources/GMFCS-ER.pdf
(accessed 4 October 2010).
24. Oeffinger D, Gorton G, Bagley A, et al. Outcome assess-
ments in children with cerebral palsy, Part I: descriptive char-
acteristics of GMFCS Levels I-III. Dev Med Child Neurol
2007; 49: 172–80.
25. Bagley AM, Gorton G, Oeffinger D, et al. Outcome assess-
ments in children with cerebral palsy, Part II: discriminatory
ability of outcome tools. Dev Med Child Neurol 2007; 49:
181–6.
26. Tervo RC, Azuma S, Stout J, Novacheck T. Correlation
between physical functioning and gait measures in children
with cerebral palsy. Dev Med Child Neurol 2002; 44: 185–90.
27. Schwartz MH, Rozumalski A. The gait deviation index: a
new comprehensive index of gait pathology. Gait Posture
2008; 28: 351–7.
28. Muthen BO, Muthen L. Mplus User’s Guide. Los Angeles,
CA: Muthen & Muthen, 1998.
29. Linacre J. WINSTEPS Rasch Measurement Computer Pro-
gram. Chicago: Winsteps.com, 2008.
30. Baker R, McGinley JL, Schwartz MH, et al. The gait profile
score and movement analysis profile. Gait Posture 2009; 30:
261–9.
450 Developmental Medicine & Child Neurology 2012, 54: 443–450