Evaluating the unique contribution of irrational beliefs and negative bias interpretations in predicting child anxiety: implications for cognitive bias modification interventions

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Child Anxiety: Roles of Irrational Beliefs and Negative Bias Interpretation 465

Journal of Cognitive and Behavioral Psychotherapies,

Vol. 13, No. 2a, November 2013, 465-475.

EVALUATING THE UNIQUE CONTRIBUTION OF

IRRATIONAL BELIEFS AND NEGATIVE BIAS

INTERPRETATIONS IN PREDICTING CHILD

ANXIETY. IMPLICATIONS FOR COGNITIVE BIAS

MODIFICATION INTERVENTIONS Cristina MOGOAŞE, Ioana R. PODINĂ*, Mădălina SUCALĂ ,

Anca DOBREAN Babeş–Bolyai University, Cluj-Napoca, Romania

Abstract

The purpose of this study was to investigate the unique contribution of

irrational beliefs and negative bias interpretations in predicting child

anxiety, based on cognitive models of anxiety. We used a cross-sectional

design. Five hundred seventy one volunteers (M age = 13.008, SD = 1.192;

53.73% girls) completed measures of irrationality, negative bias

interpretations, and anxiety. In line with theoretical assumptions, our results

showed that negative interpretation bias acted as a partial mediator between

irrational beliefs and child anxiety, indirect effect = .025, SE = .008, 95%

CI = [.012; .045]. Noteworthy, irrationality remained a significant

predictor of child anxiety level when controlling for negative bias

interpretation, B = .211, SE = .024, p < .001. These results point to the

importance of irrational beliefs in relation to child anxiety, beyond negative

bias interpretation. Therefore, we suggest that cognitive bias modification

procedures, designed to modify negative interpretation biases, could benefit

from targeting irrational beliefs.

Keywords: irrational beliefs, negative bias interpretation, child anxiety,

cognitive bias modification

Introduction

Anxiety disorders are among the most common and functionally

impairing mental health problems in children and adolescents, affecting up to

20% of youth (Costello, Egger, & Angold, 2005). They are associated with

significant and lasting impairment in social, academic, occupational, and familial

*Correspondence concerning this article should be addressed to:

E-mail: [email protected]

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Cristina Mogoaşe, Ioana R. Podină, Mădălina Sucală, Anca Dobrean 466

day-by-day functioning (James, Soler, & Weatherall, 2005), as anxiety hinders

the young individual from benefiting of the learning experiences offered by the

environment (Van Ameringen, Mancini, & Farvolden, 2003; Wood, 2006). In

addition, anxiety disorders are thought to increase the risk for the onset of other

emotional problems (e.g., depression) and/or dysfunctional behaviors (behavior

disorders, substance abuse) (James et al., 2005). The functional impairments

persist from childhood to late adulthood in the majority of cases, especially if the

disorder goes undetected and (consequently) untreated (Andlin-Sobocki, Jönsson,

Wittchen, & Olesen, 2005; James et al., 2005). Therefore, it is essential to treat

child anxiety as early as possible.

Cognitive behavioral approach of anxiety

Cognitive-behavioral therapy (CBT) has been shown to be an efficacious

treatment for anxiety disorders in youth (In-Albon & Schneider, 2007; James et

al., 2005; Reynolds, Wilson, Austin, & Hooper, 2012; Seligman & Ollendick,

2011), being recommended as first line of intervention in child anxiety problems

(see National Institute for Health and Clinical Excellence guidelines –

www.guidance.nice.org.uk; see also Marshall & Ramchandani, 2008). The central

tenet of CBT interventions is that anxiety results from dysfunctional feelings,

thoughts, and behaviors learned throughout life experiences. Cognitive-behavioral

models of anxiety (e.g., Clark & Wells, 1995; Rapee & Heimberg, 1997) place a

special emphasis on the cognitive factors involved in the onset and maintenance

of anxiety. Originally elaborated for explaining anxiety in adults, these models

have been found to be applicable in youth as well (e.g., Clark & Wells' model; see

Hodson, McManus, Clark, & Doll, 2008). According to cognitive-behavioral

models of anxiety, anxious people hold dysfunctional cognitions which bias their

perception of reality in a way that maintains their anxiety.

Essentially, cognitive-behavioral models of anxiety are based on the

Albert Ellis’ ABC model of distress (Ellis, 1958, 1994), which states the

following: when confronted with undesirable activating events (A) people filter

the reality through their distorted (dysfunctional/irrational) or undistorted

(functional/rational) set of beliefs/cognitions (B), which in turn generate

functional or dysfunctional emotional, cognitive, and/or behavioral consequences

(C). Therefore, cognitive factors are thought to be causally involved in the onset

and maintenance of anxiety. As cognition (C, in the form of automatic or more

controlled processes and contents) is assumed to play an important meditational

role between the trigger (A, feared situation) and anxiety (C), an effective

intervention would necessarily imply a change in subsequent cognitions that

maintain symptomatology.

However, it is not fully clear what types of cognitions are modified via

CBT interventions. Clinical theories of CBT state that there are different levels of

cognition and different CBT schools emphasize different types of cognitions, not

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necessarily mutually exclusive (for a detailed discussion, see David &

Szentagotai, 2006). For example, rational-emotive behavior therapy (REBT)

emphasizes the clinical importance of rational and irrational beliefs (Ellis, 1958,

1994), while cognitive therapy (CT) is structured around the concepts of

intermediary/core beliefs (e.g., cognitive schemas) and automatic thoughts (Beck,

1976). In addition, more recent developments, coming from experimental

cognitive science, talk about cognitive biases (i.e., “systematic selectivity in

information processing that operates to favor one type of information over

another” (MacLeod & Mathews, 2012). Although the existence and clinical

importance of cognitive biases has been recognized and incorporated by cognitive

theories of anxiety (Beck & Clark, 1997; Beck, Emery, & Greenberg, 1985), few

attempts have been made to integrate various types of cognitions, as suggested by

different clinical CBT approaches (e.g., REBT, CT) and/or findings from

experimental cognitive science. This is unfortunate, as it may hinder a better

understanding of the cognitive underpinnings of anxiety by generating theoretical

confusions and terminology overlap.

However, we clearly need improved intervention techniques for treating

youth anxiety, as despite the existence of effective treatment options, the early

onset and the considerable life-time persistence of anxiety continue to result in

high rate of anxiety disorders in adults. For example, in Europe, anxiety disorders

rank as the most frequent mental disorders, with a 1-year prevalence of 12% in

the adult population and with high associated costs (Andlin-Sobocki et al., 2005).

Arguably, this situation is probably due to the fact that a lot of young people with

anxiety problems do not get access to CBT treatment for a number of reasons,

including lack of adequately trained professionals (and their willingness to work

with children), perceived stigma associated to accessing mental health services,

and time or financial constraints (Spence et al., 2011; Stallard, Udwin, Goddard,

& Hibbert, 2007).

Cognitive bias modification

In an attempt to overcome these barriers, recent research efforts resulted

in new ways of intervention, capitalizing on cognitive theories of anxiety and on

findings coming from experimental cognitive science. These so-called “cognitive

bias modification” (CBM) interventions aim to modify cognitive biases in order

to reduce psychopathology. They are simple and easy-to-deliver interventions that

do not require extensive assistance from a psychotherapist. One promising CBM

procedure used with anxious children and adolescents is the Cognitive Bias

Modification of Interpretations (CBM-I). As biased interpretations (i.e., the

tendency to preferentially resolve ambiguity in a negative/threatening way) have

been reported in anxious youth (Cannon & Weems, 2010; Lau et al., 2012) and

considering numerous experimental data showing that negative interpretation bias

is a hallmark of adult anxiety and may be even causally related to anxiety in

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adults (e.g., Mathews & MacLeod, 2005), it seems reasonable to assume that the

modification of negative interpretation bias can have clinical utility in youth.

Indeed, studies conducted on anxious children and adolescents yielded promising

results (for a review, see Lau, 2013), in that CBM-I seems capable of modifying

negative interpretation biases. However, the reduction in anxious symptoms is

less consistently found (Lau, 2013), highlighting the need for further refinement

of CBM-I procedures in order to boost their clinical utility. One way of doing this

may be to carefully consider cognitive models of anxiety in order to gain a deep

understanding of what biased interpretations are and how they function.

In this context, the present study aims to evaluate the unique contribution

of irrational beliefs and negative interpretation biases in predicting child anxiety.

Our approach is based on the cognitive models of anxiety, stating that negative

interpretation biases are driven by underlying dysfunctional cognitions.

Therefore, from a theoretical point of view, we expected negative interpretation

biases to mediate the relationship between dysfunctional/irrational cognitions and

child anxiety. In addition, we were interested to investigate if this expected

mediation is a total or a partial one, as this can have important implications for

further development of CBM-I procedures (e.g., if it is a partial mediation, CBM-

I procedures could benefit from targeting not only negative interpretations bias,

but also dysfunctional/irrational beliefs).

Method

We used a cross-sectional design. Volunteers filled in questionnaires

which assessed the level of irrationality, anxiety symptoms, and negative

interpretation biases.

Participants

Five hundred seventy one participants were enrolled in the study (M age

= 13.008, SD = 1.192; 53.73% girls). Participants were recruited from several

schools in Romania. They were enrolled in the study based on an informed

consent signed by both parents and children and received tokens (i.e., candy) for

their participation. The study received the approval of the Babeș-Bolyai

University’s Review Board and was in agreement with internal school

regulations. All our participants volunteered to participate in the study and no

specific inclusion and exclusion criteria were applied.

Measures

Child and Adolescent Scale of Irrationality-Revised (CASI-R). CASI

(Bernard & Cronan, 1999) is an instrument that measures general core

dysfunctional/irrational cognitions (e.g., “I think that the others are better than

me”). CASI helps therapists in determining which irrational beliefs a child or

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adolescent may have. It was adapted and validated on the Romanian population

(Trip & Popa, 2005). Every item is rated on a 5-point Likert scale (varying from 1

= strongly disagree to 5 = strongly agree) where the higher the score, the higher

the irrationality level. Although the instrument can be split into four subscales

(i.e., self-downing, intolerance of frustrating rules, intolerance of work frustration,

and demands of fairness), for the purposes of this study we were interested in the

overall irrationality score, derived from summing up all the items. CASI has been

shown to have good psychometric properties (e.g., overall irrationality, α

Cronbach = 0.84; Trip & Popa, 2005). In our sample, the overall irrationality

scale (α Cronbach = 0.870) showed a good internal reliability.

Screen for Child Anxiety-Related Disorder (SCARED). The child version

of SCARED (Birmaher, et al., 1997; Birmaher, Brent, Chiappetta, Monga, &

Baugher, 1999) was used to measure anxiety symptoms in children, namely

symptoms of generalized anxiety, separation anxiety, panic disorder, social

anxiety, and school phobia. We used the 41-item version of the SCARED

(Birmaher et al., 1999) where children had to describe, on a three-point Likert

scale, the degree to which the SCARED statements were true for them (0 = not

true or hardly ever true, 1= somewhat true or sometimes true, 2= very true or

often true). Higher scores signal higher anxiety levels. Although the instrument

allows the computation of separate scores for different anxiety symptoms, for the

purposes of this study we used the overall score. SCARED has demonstrated

good psychometric properties (e.g., Crocetti, Hale WW 3rd, Fermani,

Raaijmakers, Meeus, 2009). In our sample, the overall anxiety score (α Cronbach

= 0.901) showed a good internal reliability.

Ambiguous situations questionnaire: Child self-report (ASQ-C).

Following Barrett et al. (1996) assessment methodology, each child was

presented with 12 ambiguous situations that could be interpreted as either

threatening or non-threatening (6 physical and 6 social). For instance, for the

following ambiguous situation “You are on your way to your friend’s house when

a big dog comes up to you” children were presented with two alternatives. One

alternative was threatening (“The dog is going to bite you”), while the other was

non-threatening (“The dog wants to smell you and to be petted”). Of the two

provided alternatives, children could choose which one they think was most likely

to have happened. The negative interpretation for each situation was coded with

1, and the neutral interpretation was coded with 0. A total threat score was

calculated by summing up the responses. Higher scores signal a higher threat

interpretation bias.

Procedure

This study was part of a larger cross-sectional project. Given the

correlational nature of the design, volunteering parents and children gave their

informed consent and filled in the following instruments: the CASI-R

questionnaire to measure the level of irrational beliefs, the SCARED scale for

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screening of anxiety symptoms, and the ASQ-C for an assessment of negative

interpretation biases. This set of self-report instruments was filled in by

participants in the context of their classroom and in the presence of a research

assistant who described the instructions and provided assistance with further

questions regarding the instruments.

Data analysis and results

To analyze the data we used correlation and mediational analysis. For

mediational purposes, we used the bootstrapping method for calculating indirect

effects (Preacher & Hayes, 2008). Mediational analysis was performed via the

Preacher and Hayes (2008) mediation script for SPSS. We used bootstrapping

tests with 5000 re-samples and the bias corrected confidence interval (Preacher &

Hayes, 2008). In terms of effect size, we used the kappa-square (i.e., κ2; Preacher

& Kelley, 2011) as an effect size index. The values proposed for this index are to

be interpreted in the same manner as the Cohen’s r2, which are small (0.01),

medium (0.09), and large effect sizes (0.25 or higher) (Cohen, 1988, pp. 79–81).

Correlations between the investigated variables are displayed in Table 1A.

Descriptive data for the investigated variables are presented in Table 1B.

Table 1. Correlations between variables and means with standard deviations (in brackets).

A 1 2 3 B Means and Standard Deviations

1. CASI 1 .243** .429 ** 89.513 (19.002)

2. ASQ-C 1 .305 ** 3.739 (2.154)

3. SCARED 1 17.357 (10.862)

Note: ASQ-C = Ambiguous Situations Questionnaire, child version; CASI = Child and

Adolescent Scale of Irrationality; SCARED = Screen for Child Anxiety-Related and

Emotional Disorders.

**p < 0.01.

The results (see Figure 1) showed that children’s negative interpretation

biases significantly mediated the relationship between irrationality and anxiety,

indirect effect = .025, SE = .008, 95% CI = [.012; .045]. The effect size was high,

k2

= .049, 95% CI = [.025; .083]. However, irrationality still was a significant

predictor of child anxiety level when controlling for negative bias interpretation,

B = .211, SE = .024, p < .001.

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Figure 1. Simple mediation diagram; a, b, c and c’ are path coefficients representing

unstandardized regression weights and standard errors (in parentheses). The c path

coefficient represents the total effect of the irrationality on the self-reported anxiety. The

c-prime path coefficient refers to the direct effect of the irrationality on the self-reported

anxiety. All analyzed paths were significant, **p < 0.01.

Discussion and conclusions

This study aimed to investigate in a cross-sectional design the relationship

between dysfunctional/irrational cognitions and negative interpretation bias in

predicting child anxiety. In line with theoretical assumptions, negative

interpretation bias mediated the relationship between irrational cognitions and

anxiety in children.

However, irrational cognitions remained a significant predictor of child

anxiety even when controlling for negative interpretation bias. This indicates that

the modification of the negative interpretation bias via CBM-I might not be

enough to reliably reduce anxiety in children, especially on the long-term. As

irrational beliefs are thought to act as vulnerability factors for psychopathology

(David, Lynn, & Ellis, 2009), and as CBM-I long term effects and mechanisms of

change are currently under investigated (Lau, 2013; Mobini, Reynolds, &

Mackintosh, 2012), these results can provide valuable inputs for future research.

For example, it could be interesting to see if CBM-I, in its current form, has any

impact on irrational beliefs, beyond modifying negative interpretation biases. No

study has investigated this until now.

From a clinical point of view, the results suggest that, when targeting

child anxiety, clinicians should not only focus on modifying the negative

interpretation bias, but also on changing the irrational beliefs and replacing them

with rational ones.

Child

Irrationality

Child

Anxiety

a = .028** (.005) b = .904** (.208)

c = .237** (.023)

c’ = .211** (.024)

Child Negative Interpretation Bias

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To our knowledge, this is the first study considering the competitive roles

of irrational beliefs and negative interpretation bias in predicting child anxiety, in

an effort to bring together different but complementary perspectives on cognitive

underpinnings of psychopathology. Similar endeavors previously reported in the

literature showed that negative automatic thoughts partially mediate the

relationship between irrational beliefs and distress (Szentagotai & Freeman,

2007). Interestingly, we found the same pattern of results this time using the

negative interpretation bias instead of the negative automatic thoughts. This

indicates certain equivalence between negative automatic thoughts and cognitive

biases. However the extent to which these two constructs are superimposable

remains to be established. Notably, although the original CT theory speaks about

the so-called “cognitive distortions” (e.g., selective abstracting,

overgeneralization, etc.) (Beck, 1976) and cognitive theories of anxiety

incorporate the idea of cognitive biases (Beck & Clark, 1997; Beck et al., 1985),

what cognitive biases are is not fully clear.

As noted elsewhere (David & Szentagotai, 2006), we believe that the

future development of CBT-based approach in psychopathology lies in integrating

different perspectives on cognitive functioning into a coherent model providing a

comprehensive description of different cognition levels and relationships between

them. To that end, we need to eliminate theoretical redundancy by clearly

delimitating similar, but conceptually different constructs. For example, it may be

that cognitive biases are rather cognitive processes, while negative automatic

thoughts would be better described as cognitive contents. This suggests that

although naturally associated, they are yet different. Future studies should

investigate this possibility and identify methods of measurement that can capture

the conceptual differences between these two constructs.

This study is not without limitations. First, we used a cross-sectional

design, thus precluding any causal relationship. Second, participants in our study

were unselected volunteers. To strengthen our results, future studies should aim to

replicate our findings in clinical samples. Third, we used a general screening

measure of anxiety in youth. Future studies should investigate the stability of the

reported results on samples diagnosed with a certain form of anxiety (i.e., social,

generalized, etc.).

Despite its inherent limitations, this study adds to the small quantity of

research aimed to empirically investigate the relationship between different

cognitive factors involved in psychopathology and provide potential directions for

further research in CBM-I, when applied to anxious youth.

ACKNOWLEDGEMENTS The authors would like to thank Dr. Kathryn J. Lester for providing access to the

Ambiguous Scenarios Questionnaires, the schools which took part in our study, the

children and their parents for all their help and involvement. The authors would also like

to thank the following research assistants involved in collecting data: Ioana Bel, Tatiana

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Buglea, Maria Fetti, Gabriela Fătușanu, Camelia Lăpuşneanu, Lia Meşenschi, Costina

Păsărelu, and Florina Popescu.

This research was funded by the Executive Unit for Financing Education Higher

Research, Development and Innovation (UEFISCDI) via the “Effectiveness of an

empirically based web platform for anxiety in youths” grant, number PN-II-PT-PCCA-

2011-3.1-1500, 81/2012, coordinated by Dr. Anca Dobrean.

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Evaluating the unique contribution of irrational beliefs and negative bias interpretations in predicting child anxiety: implications for cognitive bias modification interventions