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Internet Interventions

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Guided internet-based cognitive behavioral therapy for adolescent anxiety: Predictors of treatment response

Silke Stjerneklar⁎, Esben Hougaard, Mikael Thastum Department of Psychology and Behavioral Sciences, Aarhus BSS, Aarhus University, Bartholins Allé 9, 8000 Aarhus C, Denmark

A R T I C L E I N F O

Keywords: Anxiety disorders Internet-based Cognitive behavioral therapy Adolescents Predictors Treatment response

A B S T R A C T

Background: Guided internet-based cognitive behavioral therapy (ICBT) has been found efficacious in reducing symptoms of anxiety in adolescents with anxiety disorders, but not all respond equally well. Objective: In this study, we explored candidate predictors of ICBT treatment response within the frame of a randomized controlled trial. Methods: Sixty-five adolescents (13–17 years) with anxiety disorders according to DSM-IV received 14 weeks of therapist-guided ICBT. Outcome was evaluated as improvement (continuous change score) from pre-treatment to 12-month follow-up according to self-reported anxiety symptoms and clinician-rated diagnostic severity. Clinical predictors included baseline self- and parent-reported anxiety symptom levels, baseline clinician-rated severity of primary diagnosis, summed baseline clinician-rated severity of all anxiety diagnoses, baseline self-rated de- pressive symptoms, age of onset, and primary diagnosis of social phobia. Demographic predictors included age, gender and computer comfortability. Therapy process-related predictors included number of completed modules and therapist phone calls, summed duration of therapist phone calls, degree of parent support, and therapeutic alliance. Multi-level models were used to test the prediction effects over time. Results: Higher levels of self- and clinician-rated baseline anxiety and self-rated depressive symptoms, female gender, and higher levels of computer comfortability were associated with increased treatment response. None of the proposed therapy process-related predictors significantly predicted treatment response. Conclusion: The present findings indicate that ICBT may be an acceptable choice of treatment for youths, even those with relative high levels of anxiety and depressive symptoms.

1. Introduction

Anxiety is one of the most common mental health disorders af- fecting 5–12% of youths from western cultures (Beesdo et al., 2009; Costello et al., 2011). When left untreated, anxiety disorders are asso- ciated with persistent difficulties and long-term consequences inter- fering with general development (Langley et al., 2004), social func- tioning (La Greca and Harrison, 2005; Wood and McLeod, 2008) and academic achievements (Essau et al., 2000). Treatment studies of adolescents with anxiety disorders have proven face-to-face cognitive behavioral therapy (CBT) to be highly effective in reducing anxiety symptoms (Cartwright-Hatton et al., 2004; James et al., 2013; Reynolds et al., 2012). However, it has been estimated that only around 25% of clinically anxious youths receive treatment (Essau et al., 2000; Wang et al., 2007) as their access to health care services is often limited (Gulliver et al., 2010; Stallard et al., 2007). Adolescents may be

especially reluctant to seek professional help for mental health issues due to a variety of health care barriers such as concerns about con- fidentiality, fear of social stigma, and worries concerning costs and transportation (Booth et al., 2004; Elliott and Larson, 2004; Gulliver et al., 2010; Rickwood et al., 2007).

As means to increase access to and reduce costs of psychological interventions, internet-based CBT (ICBT) has been proposed, and re- search shows promising results for the ICBT treatment of adolescents with anxiety disorders (Ebert et al., 2015; Pennant et al., 2015; Podina et al., 2016; Stjerneklar et al., submitted for publication).

However, a considerable proportion of anxious adolescents re- ceiving ICBT do not, or only partially, respond to treatment; and non- response at follow-up (FU) from recent randomized controlled trials (RCTs) range from 38 to 68% (Lenhard et al., 2017; Spence et al., 2011; Stjerneklar et al., submitted for publication; Tillfors et al., 2011), mir- roring results reported from regular CBT of 40–50% non-responders

https://doi.org/10.1016/j.invent.2019.01.003 Received 2 July 2018; Received in revised form 15 January 2019; Accepted 17 January 2019

⁎ Corresponding author at: Dep. of Psychology and Behavioral Sciences, Aarhus BSS, Aarhus University, Bartholins Allé 13, building 1343, room 393, 8000 Aarhus C, Denmark.

E-mail address: [email protected] (S. Stjerneklar).

Internet Interventions 15 (2019) 116–125

Available online 31 January 2019 2214-7829/ © 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/).

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(James et al., 2015; Silverman et al., 2008). Knowledge of predictors of treatment response may help clinicians identify adolescents at risk of low response before they commend therapy and guide the development and refinement of more effective interventions (Hudson et al., 2015a; Rapee, 2000; Steketee and Chambless, 1992).

Few pre-treatment patient predictors in face-to-face CBT with chil- dren and adolescents with anxiety disorders have been consistently demonstrated (Knight et al., 2014; Lundkvist-Houndoumadi et al., 2014). Pre-treatment predictors most consistently associated with poorer response are higher baseline symptom severity, social phobia (SoP) as primary anxiety disorder, comorbid externalizing and/or de- pressive symptoms, and parental psychopathology (Hudson et al., 2015a; Knight et al., 2014; Lundkvist-Houndoumadi et al., 2014; Rapee et al., 2009). Although an association between higher age and outcome has been documented (Reynolds et al., 2012), a large meta-analysis with individual patient data found no age effects (Bennett et al., 2013).

Despite the assumption that the therapeutic mechanisms underlying regular CBT and ICBT are the same, there are important differences between the two therapy formats possibly influencing both the kind, strength and direction of factors predicting treatment response. For example, adolescents receiving ICBT typically have less therapist gui- dance than those receiving regular CBT and the modality in which this guidance is offered differs (i.e., physical presence versus telephone calls or emails). Given the physical absence of a therapist, ICBT most likely demands more self-discipline from the adolescents as well as greater responsibility for the implementation of learned techniques than CBT. It is therefore relevant to investigate factors that may predict treatment response specifically in ICBT.

Research within ICBT for adults with anxiety disorders has con- sistently demonstrated higher baseline symptom severity (El Alaoui et al., 2013; Hadjistavropoulos et al., 2016; Hedman et al., 2012; Hedman et al., 2013) and higher adherence (i.e. number of completed modules) (Berger et al., 2014; El Alaoui et al., 2015; Hadjistavropoulos et al., 2016; Hedman et al., 2012; Hedman et al., 2013), to predict better treatment response. Mixed results have been found when in- vestigating the predictive effect of baseline depressive symptoms. Two trials (Hedman et al., 2012; Hedman et al., 2013) have reported sig- nificant negative associations with outcome, whereas one trial (El Alaoui et al., 2015) reported no association. Similarly, mixed results have been demonstrated for computer comfortability with two studies (Hedman et al., 2012; Hedman et al., 2013) demonstrating level of computer skills not to be associated with outcome, and one study (Hadjistavropoulos et al., 2016) demonstrating ‘comfortability with written communication’ to be positively associated with treatment re- sponse.

Within adult face-to-face psychotherapy research, the therapeutic alliance is the most studied process variable with a mean correlation with outcome of 0.28 in a large meta-analysis (Horvath et al., 2011). Alliance-outcome associations among youths have generally lead to somewhat smaller correlations as shown by two meta-analyses that also both found lower correlations for adolescents (0.10 and 0.19) than for children (McLeod, 2011; Shirk et al., 2011). The therapeutic alliance has been investigated within ICBT for adults suggesting that even minimal therapist contact is sufficient to establish an adequate alliance (Andersson et al., 2012; Cuijpers et al., 2010). Although a recent nar- rative review of the alliance in internet-based psychotherapy reported client-rated alliance scores roughly equivalent to those found in face-to- face therapy, mixed results have been found for alliance-outcome as- sociations (Berger, 2017).

Gender (Berger et al., 2014; El Alaoui et al., 2013; El Alaoui et al., 2015; Hadjistavropoulos et al., 2016; Hedman et al., 2012; Hedman et al., 2013) and age of onset (El Alaoui et al., 2013; El Alaoui et al., 2015; Hedman et al., 2012) have previously failed to predict outcome in ICBT for adults. Despite that therapist involvement has generally been shown to substantially increase program usage and improve the efficacy of ICBT with adults when compared with self-help

interventions with no therapist support (Christensen et al., 2009; Spek et al., 2007), previous studies of various degrees of therapist support (i.e., number of telephone calls, number of messages sent by therapist and patient, and therapist time) as predictors has failed so far to de- monstrate significant associations (Berger et al., 2014; El Alaoui et al., 2015; Hadjistavropoulos et al., 2016).

Only few studies have investigated pre-treatment patient predictors of treatment response within ICBT for adolescents with anxiety dis- orders. Three meta-analyses of ICBT for children, adolescents and younger adults (age range 5–25) with anxiety disorders (Ebert et al., 2015; Pennant et al., 2015; Podina et al., 2016) concurrently found superior results for older youths compared to younger indicating age to predict treatment response. Furthermore, (Ebert et al., 2015) in- vestigated parental involvement (‘yes/no’) and did not find support for a predictive relationship. Anderson et al. (2012) studied the role of working alliance in predicting treatment outcome for children and adolescents (age 7–18) with anxiety disorders and found adolescents, but not children, to improve significantly more in overall functioning when alliance was higher (beta = 0.22, t79 = 2.21, P = 0.03). Of two more recent studies, Lenhard et al. (2017) examined the effect of an ICBT program for adolescents (age 12–17) with OCD and found no association between number of completed modules and outcome while Spence et al. (2017) in their study on generic versus disorder specific ICBT for youths (age 8–17) with social anxiety disorder found a sig- nificant positive association between number of completed sessions and reductions in anxiety symptoms and improvements in functioning. However, this association was only significant for children – not for adolescents.

To the best of our knowledge, no previous studies of ICBT has looked at the predictive value of primary diagnosis within anxiety disorders, e.g. whether having been diagnosed with SoP as primary diagnosis significantly predicts treatment outcome compared to other anxiety diagnoses.

1.1. Aim and hypotheses

The aim of the present study was to explore a range of candidate predictors of treatment response within ICBT for adolescents. More specifically, we investigated clinical (baseline anxiety symptom se- verity, baseline depressive symptoms, a primary diagnosis of SoP, and age of onset), demographic (age, gender and computer comfortability), and therapy process-related predictors (number of completed modules, number of therapist calls, total call duration, degree of parental sup- port, and therapeutic alliance). Based on previous results, we hy- pothesized that higher baseline symptom severity, higher age (within the range 13 to 17), more completed modules, as well as higher ther- apeutic alliance scores would predict larger improvements, while more baseline depressive symptoms, a primary diagnosis of SoP, and low computer comfortability would predict less improvement. Due to the limited research on age of onset, gender, and degree of parent- and therapist support as candidate predictors, these analyses were con- sidered exploratory.

2. Methods

2.1. Participants and recruitment

The study took place at the Centre for Psychological Treatment of Children and Adolescents (CEBU), a research and teaching facility at the Department of Psychology and Behavioral Sciences, Aarhus University, Denmark. Participants in the study were 65 adolescents who received ICBT treatment within the context of a previous randomized controlled trial (Stjerneklar et al., submitted for publication; ClinicalTrials.gov: NCT02535403). Inclusion criteria were as follows: (a) age between 13 and 17 years; (b) a primary anxiety diagnosis ac- cording to the Diagnostic and Statistical Manual of Mental Disorders, 4th

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ed. (DSM–IV; American Psychiatric Association, 1994); (c) access to a home computer with internet; and (d) ability to write and read in Danish. Criteria of exclusion were: (a) severe comorbid depression (CSR > 5); (b) substance abuse; (c) severe self-harm or suicidal idea- tion; (d) pervasive developmental disorder; (e) intellectual disability; (f) learning disorder; and (f) psychotic symptoms. A detailed descrip- tion of RCT study procedures are found elsewhere (Stjerneklar, Hougaard, McLellan, & Thastum, submitted for publication). Upon the return of a signed consent form, 70 families were included in the pre- vious RCT and randomly allocated to 14 weeks of ICBT treatment (n = 35) or a WL group (n = 35). Having waited for 14 weeks, families in the WL group recompleted questionnaires, took part in a second diagnostic interview, and were offered ICBT treatment identical to the one participants in the ICBT group had completed. Four participants from WL declined treatment and dropped out before their second as- sessment (the baseline assessment of the present study); additionally, one had improved during the WL period and did not meet criteria for any diagnoses at baseline. This participant decided to complete treat- ment, but was excluded from the present study. The study was ap- proved by the local Ethics Committee of Central Denmark Region (1-10- 72-98-15) and by the Danish Data Protection Agency.

2.2. Measures

2.2.1. Outcome measures 2.2.1.1. The Anxiety Disorders Interview Schedule. Type and severity of anxiety disorders was assessed using the Anxiety Disorders Interview Schedule for DSM-IV: Child and Parent Version (ADIS-IV C/P; Silverman and Albano, 1996). ADIS-IV is a semi-structured diagnostic interview, which in this study was conducted by graduate psychology students with the adolescent and one parent (usually the mother) separately to evaluate the diagnostic criteria of anxiety disorders in accordance with DSM-IV (American Psychiatric Association, 1994). Assembling information from both informants, the severity of diagnoses - the Clinical Severity Rating (CSR) – was assessed by a clinical psychologist on a nine-point Likert scale (0 = not at all disturbing; 8 = severely disturbing). A CSR of ≥ four represent clinical level of impairment, whereas scores below four are considered subclinical. Where symptom criteria for several diagnoses were met, the one with the highest CSR or judged most disturbing by the assessor was considered the primary diagnosis. The ADIS-IV has well-established psychometric properties (Silverman et al., 2001; Wood et al., 2002). High inter-rater reliability and validity of the ADIS-IV administered over the telephone has been demonstrated, comparable to those administered face-to-face (Lyneham and Rapee, 2005). Interrater- reliability (Cohen's Kappa), as calculated in the RCT (Stjerneklar et al., submitted for publication), for primary anxiety diagnoses was excellent, K = 0.80. The intra-class correlation coefficient (ICC; two- way random for individual raters, consistency) was fair, ICC = 0.419 (95% CI: -0.121–0.768; p = 0.060), for the CSR of primary anxiety diagnosis (CSRprim), and good, ICC = 0.73 (95% CI: 0.348–0.905; p = 0.001) for the summed CSR of all anxiety diagnoses (CSRall) when calculated in the RCT (Stjerneklar et al., submitted for publication). Please note that only the summed CSR of all anxiety diagnoses was used as outcome measure in the present study.

2.2.1.2. The Spence Children's Anxiety Scale. Adolescent- and parent- reported anxiety symptoms were assessed using the Spence Children's Anxiety Scale: Child and Parent Version (SCAS-C/P; Spence, 1998). The SCAS contains 38 items rated on a four-point Likert scale from zero to three, with higher scores indicating higher anxiety symptom levels. The questionnaire is administered separately to the adolescent (SCAS-C) and to parents (SCAS-P). The Danish version of SCAS has demonstrated good to excellent internal consistency and good test-retest reliability (Arendt et al., 2014). Internal consistency (Cronbach's alpha) in the current study was excellent for both the adolescent (α = 0.90) and

parent version (α = 0.90). Please note that only the SCAS-C and not the SCAS-P was used as outcome measure.

2.2.2. Measures of predictors The CSRprim and CSRall were assessed with the ADIS-IV. Self-rated

depressive symptoms were measured with The Short version of the Moods and Feelings Questionnaire (S-MFQ; Angold et al., 1995). The S-MFQ measures depressive symptoms within the last two weeks through 13 items rated on a three-point Likert scale (0 = not true; 2 = true). The S- MFQ has demonstrated good psychometric properties (Angold et al., 1995). In the present study, internal consistency was excellent (α = 0.92). Age of onset of anxiety symptoms was derived from the mother pre-treatment questionnaire with the question: At what age did you first notice your child being more anxious than other children?

Demographic data were collected through the online pre-treatment questionnaires. Participants' computer comfortability was measured with the question: How comfortable do you feel using the computer and the internet? rated on a four-point Likert scale (1 = not comfortable at all; 4 = very comfortable).

A module was defined as complete when 80% or above of the core module components (i.e., instructions, example-videos and practice tasks excluding worksheets) had been activated according to website server logs. Number and duration of therapist phone calls was calcu- lated from participant records. Only actual conversations (i.e., no missing calls) were included in the analyses. Degree of parent support was derived from the mother post-treatment questionnaire with the question: On average, how much time have you spent weekly helping your teen complete the program?

Therapeutic alliance was assessed with The Working Alliance Inventory-Short Form (WAI-S; Tracey and Kokotovic, 1989). The WAI-S is a 12-item version of the original 36-item WAI (Horvath and Greenberg, 1989) measuring the therapeutic alliance between therapist and adolescent as reported by the adolescent. Items are rated on a seven-point Likert scale (1 = never; 7 = all the time). The ques- tionnaire contains three subscales in agreement with Bordin's (1979) alliance concept: therapeutic bond, agreement on therapeutic goals, and agreement on therapeutic tasks. In the present study, only the total scale was used. The scale has demonstrated good psychometric prop- erties, with a Cronbach's alpha of α = 0.93 for the total scale (Tracey and Kokotovic, 1989). Internal consistency in the present study was α (week four) = 0.92; α (week eight) = 0.94; α (post) = 0.94.

Diagnostic status was assessed at baseline (pre), after the interven- tion (post), and at three-month FU. All diagnostic interviews were re- corded using Crystal Gears® Ver. 2.00 RTM. Fourteen (20%) of the 35 ICBT pre-interviews were re-assessed for inter-rater reliability purposes. The 14 interviews were selected from the top of a random list of all pre- interviews, created with an online list randomizer using atmospheric noise. Adolescents and their parents received the online self-report questionnaires at pre, post, three- and twelve-month FU. For the pur- pose of the present study, only the adolescents' and mothers' responses were used. The therapeutic alliance questionnaire (WAI-S) was ad- ministered at week four and eight of treatment as well as at post- treatment. All questionnaires were administered through an electronic data collection platform, SurveyXact.

2.3. Treatment

ChilledOut Online is based on the Cool Kids and Chilled treatment programs developed at Macquarie University, Sydney, Australia (Lyneham et al., 2014). The program teaches CBT inspired anxiety management strategies for adolescents through eight online modules of approximately 30 min each, with a focus on psychoeducation, cognitive restructuring, goal setting, and graded exposure. Program content is provided through a combination of multimedia formats such as text, audio, illustrations, and video vignettes. Within each module, adoles- cents are presented with different worksheets and homework practice

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tasks that they are encouraged to keep working on when they are not in front of the computer. Adolescents were advised to complete all mod- ules within the intervention period of 14 weeks, after which they would have another three months of web site access.

Adolescents received a weekly phone call from a trained graduate student therapist focusing on problem solving, technical assistance, feedback about homework tasks, and encouragement. At three-month FU, adolescents received a booster phone call from the therapist mainly addressing motivation and consolidation of previously learned skills. Parents received the ChilledOut Parent Companion handout before treatment start describing the program's core treatment strategies and advising them on how to best support their teenager throughout the intervention. Additionally, parents received an introductory phone call from the therapist within the first two weeks of treatment. Further treatment details are provided elsewhere (Stjerneklar et al., submitted for publication; Stjerneklar et al., 2018).

2.4. Statistical analyses

The present study employed a repeated measurements design ex- amining the following predictors of treatment response: Clinical char- acteristics including baseline self- and parent-reported anxiety symptom levels (SCAS-C/P), baseline CSRprim, summed baseline CSRall, baseline self-rated depressive symptoms, age of onset, and primary di- agnosis of SoP. Demographic characteristics including age, gender and computer comfortability. Therapy process-related variables including number of completed modules, number of therapist phone calls, summed duration of therapist phone calls, degree of parent support, and therapeutic alliance. Predicted outcome was evaluated as (a) change score in summed severity of all anxiety diagnoses (CSRall) from pre to 3-month FU, and (b) change in self-reported anxiety symptoms (SCAS-C) from pre to 12-month FU. Analyses that included the same variable as both predictor and outcome/criterion (i.e., CSRall/CSRall, CSRprim/CSRall, and SCAS-C/SCAS-C) were omitted from the study to prevent overlap.

Mixed linear models (MLMs) were used to test candidate predictors over time, i.e. time × predictor with all measuring points included in the analyses. As MLMs tolerate missing values without compromising power, all analyses were based on the intention-to-treat sample (N = 65) without imputations of missing values; a method re- commended over other procedures in longitudinal clinical trials (Chakraborty and Gu, 2009). Data were hierarchically arranged in two levels, with time at Level 1 nested within individuals at Level 2. MLMs were estimated with the full maximum likelihood method, and depen- dent variables were treated as continuous. Models included a random intercept, and the slope was specified as random if it significantly im- proved model fit as evaluated by a change in the –2LL fit statistics (Heck et al., 2014). A candidate variable was considered a predictor if the two-way interaction term was statistically significant. As suggested when assessing single predictors using multiple measurement tools (Knight et al., 2014), Bonferroni adjustments were used to correct for family-wise analysis error. Candidate predictors were analyzed with two different outcome measures, thus statistical significance was de- fined as p ≤ 0.025 (0.05/2) with a two-tailed significance level. Effect sizes were expressed as Cohen's d derived from the F-test, calculated as d = 2 × √(F / df). All analyses were carried out using IBM® SPSS® sta- tistics, v.24.0 (Armonk, NY: IBM Corp.).

All candidate predictors were included in the analyses as continuous variables. For illustration purposes, variables found to significantly predict treatment response were dichotomized according to the median when graphically depicted.

Although in the original RCT, modest symptom improvements were observed among WL participants while on waitlist (as reported in Stjerneklar et al., submitted for publication), no significant differences in treatment effect over time were found between the two conditions on any of the included outcome measures (p = 0.326–0.954). Thus, all

predictor analyses were conducted using data from the pooled sample of 65 participants. Post hoc power calculations based on ANOVA (re- peated measures) indicated that a sample size of 65 and an error probability of α = 0.05 (two-tailed) would have sufficient power (0.80) to detect an effect size of d = 0.70.

3. Results

3.1. Study flow and sample characteristics

The degree of missing data (intention-to-treat sample, N = 65) was as follows: ADIS (pre = 0; post = 2; 3-month FU = 9); SCAS-C (pre = 1; post = 9; 3-month FU = 16; 12-month FU = 18), and SCAS-P (pre = 0; post = 4; 3-month FU = 6; 12-month FU = 14). Reasons for non-completion are largely unknown, as most non-completers could not be reached.

Baseline sample characteristics are presented in Table 1. The 65 participants (78% females) had a mean age of 15.2 (SD = 1.33; range 13–17). The most common primary diagnosis was SoP (42%), followed by GAD (14%), separation anxiety disorder (11%), specific phobia (9%), and obsessive-compulsive disorder (OCD) (9%). The remaining participants met criteria for panic disorder, with (5%) or without (5%) agoraphobia, or agoraphobia without a history of panic disorder (6%). Mean number of anxiety diagnoses per adolescent was 2.1 (SD = 1.01). Regarding participants' computer comfortability, thirty-four (52%) re- ported feeling ‘very comfortable’ using computer and internet, 28 (43%) reported feeling ‘fairly comfortable’, two (5%) reported feeling only ‘a little comfortable’, and none reported ‘not at all comfortable’,

Table 1 Sample characteristics.

Continuous variables N Mean SD

Age (years) 65 15.2 1.33 Age of onset 65 8.6 4.32 SCAS-C total 64 43.8 17.01 SCAS-P total 65 44.7 16.94 CSR primary diagnosis 65 6.4 0.86 CSR all anxiety diagnoses 65 12.0 5.62 S-MFQ 64 9.3 6.86 Number of anxiety diagnoses 65 2.1 1.01 Number of completed modules 65 6.4 2.02 Number of therapist calls 65 10.4 2.80 Summed call duration (hours) 65 3.1 1.33 Computer comfortability 65 3.5 0.59

Dichotomous variables N Frequency Percentage

Gender (female) 65 51 78 Primary diagnosis Social phobia 65 27 42 Generalized anxiety disorder 65 9 14 Separation anxiety disorder 65 7 11 Specific phobia 65 6 9 Obsessive compulsive disorder 65 6 9 Agoraphobia without a history of panic disorder 65 4 6 Panic disorder without agoraphobia 65 3 5 Panic disorder with agoraphobia 65 3 5

Comorbid mood disorder 65 4 6 Degree of parental assistancea

No time 61 7 11 0–10 min 61 17 28 10–30 min 61 13 21 30–60 min 61 16 26 1–2 h 61 4 7 2–5 h 61 3 5 > 10 h 61 1 2

Note: SCAS-C: Spence Children's Anxiety Scala, Child version; SCAS-P: Spence Children's Anxiety Scale, Parent version; CSR: Clinical Severity Rating; S-MFQ: Short version of the Mood and Feelings Questionnaire.

a Weekly average.

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resulting in a mean rating of M = 3.5 (SD = 0.59). Participants (in- tention-to-treat, N = 65) completed a mean of 4.6 modules (SD = 2.67) and received a mean of 10.4 therapist calls (SD = 2.80) with an average summed call duration of 3.1 h (SD = 1.33).

3.2. Clinical predictors

Results are presented in Table 2. Higher self-reported baseline an- xiety symptoms (SCAS-C) predicted larger improvement (d = 0.42; p = 0.020) on clinician-rated summed severity of all anxiety diagnoses (CSRall). In addition, higher clinician-rated baseline severity of all an- xiety diagnoses (CSRall) predicted larger treatment response (d = 0.44; p = 0.007) in self-reported anxiety symptoms (SCAS-C). Change in variables for significant predictors is depicted in Fig. 1a–b.

Baseline depressive symptoms (S-MFQ) significantly predicted treatment response (d = 0.44; p = 0.005) when using self-reported anxiety symptoms (SCAS-C) as outcome variable. As seen in Fig. 2, higher levels of baseline depressive symptoms were associated with larger improvements over time compared with lower levels of baseline depressive symptoms.

Age of onset did not significantly predict treatment response after Bonferroni-correction. However, a numerical trend (p < 0.05) was found associating later age of onset with larger improvements in self- reported anxiety symptoms (SCAS-C).

3.3. Demographic predictors

A significant effect of gender was found both on change in self-re- ported anxiety symptoms (SCAS-C; d = 0.38; p = 0.017) and on change in summed severity of all anxiety diagnoses (CSRall; d = 0.52; p = 0.004), indicating larger improvement for girls than for boys (de- picted Fig. 3a–b).

Participants' computer comfortability significantly predicted treat- ment response (d = −0.49; p = 0.002) when measured as self-reported anxiety symptoms (SCAS-C). As depicted in Fig. 4, higher levels of

computer comfortability were associated with less improvement over time compared to lower levels of computer comfortability.

3.4. Therapy process-related predictors

None of the proposed therapy process-related variables significantly predicted treatment outcome after Bonferroni-correction (see Table 2). Trends (p < 0.05) were, however, found for four of the investigated six associations between alliance and outcome with small to moderate ef- fect sizes (d = 0.33–0.41), i.e. better alliance scores associated with increased treatment response. WAI-S scores in week 4 ranged from 3.3 to 7.0 (M = 5.9; SD = 0.81), in week 8 from 2.4 to 7.0 (M = 5.9; SD = 0.89), and post-treatment from 2.0 to 7.0 (M = 5.7; SD = 1.22).

4. Discussion

As hypothesized, higher levels of self-reported baseline anxiety symptoms (SCAS-C) predicted larger improvements in clinician-rated summed severity of all anxiety diagnoses (CSRall) over time. Also, higher clinician-rated summed baseline severity of all anxiety diagnoses (CSRall) predicted larger improvements in self-reported anxiety symp- toms (SCAS-C) over time. These results are in line with previous ICBT research in adults with anxiety disorders (Hadjistavropoulos et al., 2016; Hedman et al., 2013), suggesting that adolescents who suffer from relatively severe anxiety symptoms may obtain greater reductions in symptom severity from ICBT interventions compared to adolescents with less severe anxiety. Results should be interpreted in light of the symptom severity of the present sample. The average baseline scores on clinician-rated diagnostic severity (CSRprim: M = 6.4, SD = 0.86), and on self- and parent-reported anxiety symptoms (SCAS-C: M = 43.8, SD = 17.01; SCAS-P: M = 44.7, SD = 16.94) of the present sample were generally similar to or higher than those of other adolescent stu- dies using similar outcome measures, e.g. Spence et al. (2011) (CRSprim: M = 5.7–6.3, SD = 0.13–0.16; SCAS-C: M = 36.3–41.9, SD = 2.62–3.34; SCAS-P: M = 27.2–33.9, SD = 1.95–2.49) and Wuthrich et al. (2012) (CRSprim: M = 6.9–7.0, SD = 0.25–0.29; SCAS-C: M = 34.0–39.0, SD = 3.63–3.99; SCAS-P: M = 34.2–39.3, SD = 3.79–4.14). Self- and parent rated baseline anxiety symptom le- vels of the present sample were also generally similar to or moderately higher than those of adolescents from a gender differentiated clinical Danish norm population (SCAS-Cfemales: M = 46.0, SD = 14.42; SCAS- Cmales: M = 34.1, SD = 18.34; SCAS-Pfemales: M = 44.7, SD = 16.65; SCAS-Pmales: M = 34.6, SD = 17.54). Since not all measures of anxiety symptom severity predicted greater improvement (CSRprim and SCAS-P were not significantly correlated with treatment response) it is hard to draw any firm conclusions about baseline symptom severity in general and interpretations should be done with caution. Furthermore, it should be notes.

Also in line with previous ICBT research in adults with anxiety disorders (El Alaoui et al., 2013; El Alaoui et al., 2015; Hedman et al., 2012), age of onset did not predict improvement. Contrary to our hy- potheses, higher levels of baseline depressive symptoms predicted larger improvements in self-reported anxiety symptoms over time. This is in contrast to previous ICBT research with adults and to research within regular CBT for youth with anxiety disorders, both typically demonstrating higher levels of depressive symptoms to predict smaller improvements in anxiety. Similar to the average baseline anxiety symptom levels of the present sample, the baseline levels of depressive symptoms were relatively high in this study (S-MFQ: M = 9.3, SD = 6.86), compared to those of a Danish sample of clinically anxious youths (aged 7–16) assed with the same measure (M = 6.5–6.7, SD = 5.00–6.02) (Arendt et al., 2015). It is possible, that the demon- strated associations between baseline severity and degree of change are influenced by simple regression towards the mean, since participants with higher scores have more room for improvement. However, al- though participants with higher anxiety and depressive symptom scores

Table 2 Results from predictor analyses.

SCAS-C CSRall

F p d F p d

Clinical predictors Baseline SCAS-C – – – 5.53 0.020⁎ 0.42 Baseline SCAS-P 1.75 0.187 0.21 2.16 0.144 0.26 Baseline CSRprim 2.07 0.152 0.23 – – – Baseline CSRall 7.57 0.007⁎ 0.44 – – – Baseline S-MFQ 8.02 0.005⁎ 0.44 1.08 0.300 0.19 Anxiety symptoms onset 4.21 0.042 0.32 2.30 0.132 0.27 Primary diagnosis of SoP 0.68 0.410 0.13 0.54 0.466 0.13

Demographic predictors Age 0.62 0.433 0.12 1.31 0.255 0.21 Gender 5.79 0.017⁎ 0.38 8.62 0.004⁎ 0.52 Computer comfortability 9.57 0.002⁎ −0.49 0.98 0.323 −0.18

Therapy process-related predictors Number of completed modules 0.00 0.972 0.00 0.06 0.806 0.04 Number of therapist calls 2.55 0.112 0.24 0.98 0.325 0.17 Summed duration of therapist

calls 0.03 0.870 0.03 0.26 0.608 0.09

Parent support 0.81 0.369 0.14 2.67 0.105 0.30 WAI-S week 4 0.82 0.368 0.15 4.11 0.045 0.39 WAI-S week 8 4.45 0.037 0.36 4.42 0.038 0.41 WAI-S post-treatment 4.17 0.043 0.33 1.42 0.236 0.23

Note. SCAS-C/P: Spence Children's Anxiety Scale: Child and Parent Version; CSRprim: Clinical Severity Rating of primary diagnosis; CSRall: summed Clinical Severity Ratings of all anxiety diagnoses; S-MFQ: Short version of the Moods and Feelings Questionnaire; SoP: social phobia; WAI-S: Working Alliance Inventory-Short Form. Positive effect sizes indicate improvement.

⁎ Indicates statistically significant at the Bonferroni-corrected 0.025 level.

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obtained greater reductions in symptom severity over time, this does not mean that those with lower scores did not also improve. Finally, contrary to our expectations, a primary diagnosis of SoP did not predict less anxiety symptoms improvement compared to other anxiety diag- noses, thus contrasting previous results within CBT with children and adolescents (Compton et al., 2014; Hudson et al., 2015a, 2015b; Knight

et al., 2014; Lundkvist-Houndoumadi et al., 2014). Although it is a small-scale study, almost half of participants fulfilled criteria for a primary diagnosis of SoP. Future studies may provide more insight into the possibilities of treating SoP in adolescents with generic ICBT pro- grams like ChilledOut Online.

Surprisingly, higher levels of computer comfortability predicted less

Fig. 1. a. Baseline self-reported anxiety symptoms on summed severity of all anxiety diagnoses b. Baseline summed severity of all anxiety diagnoses on self-reported anxiety symptoms.

Fig. 2. Baseline depressive symptoms on self-reported anxiety symptoms.

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improvement in self-reported anxiety symptoms over time. To our knowledge, this has not previously been tested within an adolescent population, and only few adult studies have investigated this variable with inconsistent results (Hadjistavropoulos et al., 2016; Hedman et al., 2012; Hedman et al., 2013). Although the adolescents' comfortability ratings were generally high with little variability (i.e., 95% reported feeling either ‘fairly’ or ‘very’ comfortable using computer and in- ternet), it appears as if the adolescents' perception of their idiosyncratic

technological capabilities may be important to their overall treatment gains. Gender predicted both self-reported and clinician-rated reduction in symptom severity, suggesting that females show larger improve- ments over time compared to males. To our knowledge, this is the first study to include gender as a candidate predictor of ICBT for adolescents with anxiety disorders. The vast majority of studies of face-to-face CBT for children and adolescents, however, finds no gender differences in outcome (see reviews by Knight et al., 2014; Lundkvist-Houndoumadi

Fig. 3. a. Gender on self-rated anxiety symptoms b. Gender on summed severity of all anxiety diagnoses.

Fig. 4. Computer comfortability on self-reported anxiety symptoms.

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et al., 2014; Rapee et al., 2009). Results of this study should be con- sidered within the limits of a relatively small sample with few males represented (n = 14) and with females scoring markedly higher base- line anxiety on both outcome measures compared to males; baseline severity also predicted higher degree of change (SCAS-C: Mfemales = 47.6 (SD = 16.57), Mmales = 30.1 (SD = 10.44); CSRall: Mfemales = 12.7 (SD = 5.89), Mmales = 9.1 (SD = 3.39)). Age did not predict outcome, in contrast to previous research within ICBT for children and adolescents typically associating higher age with better outcome (Ebert et al., 2015; Pennant et al., 2015; Podina et al., 2016). Our results may be explained by the small age range of the present study sample (i.e., 13–17 years) which is considerably narrower than those of previous studies demonstrating significant findings (6–25, 5–25, and 7–18, respectively).

Concerning process-related predictors, module completion did not predict treatment response contrasting previous research within ICBT for adults (Berger et al., 2014; El Alaoui et al., 2015; Hadjistavropoulos et al., 2016; Hedman et al., 2012; Hedman et al., 2013). It is, however, in line with the study by Lenhard et al. (2017) showing no predictive effect of module completion among anxious adolescents and with the study by Spence et al. (2017) who demonstrated a positive association between module completion and improvement accounting only for children – not for adolescents. Degree of parent support also did not predict treatment response, which may be explained by the need for autonomy and an ability to receive appropriate amounts of support from the adolescents' surroundings. However, as parent support has not previously been investigated as a continuous variable within ICBT for adolescents, these results must be interpreted with caution.

The therapeutic alliance was not a significant predictor of treatment response after Bonferroni-correction, although there was a positive trend (p < 0.05) in four of the six examined associations. Disregarding the post-therapy alliance ratings (which cannot influence later therapy outcome) the mean effect size of the association between alliance and outcome was d = 0.33, corresponding to r = 0.16 (Rosenthal, 1991), roughly equivalent to those found in the two meta-analyses of face-to- face psychotherapy with adolescents (McLeod, 2011; Shirk et al., 2011). The level of alliance ratings on WAI-S in the present study (M = 5.7–5.9 out of max 7.0) are high, corresponding to those reported in a previous study by Anderson et al. (2012) on ICBT for adolescents with anxiety disorders (M = 5.6). Thus, current research seems to support a prior conclusion from the adult literature (Berger, 2017) that level of alliance ratings in ICBT are roughly equivalent to those re- ported for face-to-face psychotherapy.

The most important clinical implication of the present study is that adolescents suffering from more severe baseline anxiety symptoms show greater reductions in clinician-rated summed severity of all di- agnoses and in anxiety symptom severity, possibly suggesting that adolescents with more severe anxiety symptoms may benefit as much (if not more) from ICBT as those with less severe anxiety; hence, clin- icians and researchers should be mindful not to exclude these in- dividuals from ICBT interventions due to the assumption that ICBT as a low intensity treatment is suitable only for adolescents with mild an- xiety. Also, levels of depressive symptoms may not per se impair the beneficial effects of ICBT on anxiety. However, it should be kept in mind that comorbid severe depression was excluded from the study. The finding of gender should be taken with caution due to the low number (14) of males in the sample and marked gender differences in pre-treatment anxiety severity that also predicted outcome.

4.1. Limitations

The study has several limitations. The primary study was an RCT, and the predictor analyses were secondary. As in most RCTs, exclusion criteria (e.g. not allowing comorbid severe depression) might have limited the variability in relevant clinical pre-treatment variables. The study had only acceptable power to detect moderate to large effects

(d ≥ 0.7). The lack of control group makes it impossible to determine if pre-treatment predictors interacted with treatment (i.e. were mod- erators) or just might indicate positive prognoses even without treat- ment. Alliance-outcome associations were correlational in nature without taking account of timelines of change in alliance and outcome. As effect sizes of predictors identified in the present study ranged from small to moderate, the clinical impact is probably limited and results should be viewed in this perspective.

The study also has several strengths, for instance the use of psy- chometrically strong and validated assessment instruments, low attri- tion rates, and one-year FU. To the best of our knowledge, it is the first trial specifically aimed at identifying predictors of ICBT treatment re- sponse for adolescents with anxiety disorders.

5. Conclusion

Most importantly, results from this study suggest that baseline se- verity of anxiety and depressive symptoms were positive predictors of treatment response. This finding lends support to the use of ICBT for youths with anxiety disorders, even those with relatively severe symptom levels. As a first study within the area, results may contribute to enlarge the knowledge base within predictors of treatment response in ICBT for youth anxiety disorders.

Acknowledgements

The study was funded by Trygfonden, Denmark (grant id: 100886) and by Edith and Godtfred Kirk Christiansens Fund, Denmark (grant id: 21-5675). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The authors wish to thank our colleagues at Macquarie University for the permission to use the ChilledOut Online program. We also give our warmest thanks to clinic secretary Marianne Bjerregaard Madsen for administrative assistance throughout the study.

Declaration of interests

The authors declare no conflicting interests.

References

American Psychiatric Association, 1994. Diagnostic and Statistical Manual of Mental Disorders, 4th ed. American Psychiatric Association, Washington, DC.

Anderson, R.E.E., Spence, S.H., Donovan, C.L., March, S., Prosser, S., Kenardy, J., 2012. Working alliance in online cognitive behavior therapy for anxiety disorders in youth: comparison with clinic delivery and its role in predicting outcome. J. Med. Internet Res. 14 (3), 86–101. https://doi.org/10.2196/jmir.1848.

Andersson, G., Paxling, B., Wiwe, M., Vernmark, K., Felix, C.B., Lundborg, L., ... Carlbring, P., 2012. Therapeutic alliance in guided internet-delivered cognitive be- havioural treatment of depression, generalized anxiety disorder and social anxiety disorder. Behav. Res. Ther. 50 (9), 544–550. https://doi.org/10.1016/j.brat.2012.05. 003.

Angold, A., Costello, E.J., Messer, S.C., Pickles, A., 1995. Development of a short ques- tionnaire for use in epidemiological studies of depression in children and adolescents. Int. J. Methods Psychiatr. Res. 5 (4), 237–249.

Arendt, K., Hougaard, E., Thastum, M., 2014. Psychometric properties of the child and parent versions of Spence Children's Anxiety Scale in a Danish community and clinical sample. J. Anxiety Disord. 28 (8), 947–956. https://doi.org/10.1016/j. janxdis.2014.09.021.

Arendt, K., Thastum, M., Hougaard, E., 2015. Efficacy of a Danish version of the cool kids program: a randomized wait-list controlled trial. Acta Psychiatr. Scand. https://doi. org/10.1111/acps.12448.

Beesdo, K., Knappe, S., Pine, D.S., 2009. Anxiety and anxiety disorders in children and adolescents: developmental issues and implications for DSM-V. Psychiatr. Clin. N. Am. 32 (3), 483–524. https://doi.org/10.1016/j.psc.2009.06.002.

Bennett, K., Manassis, K., Walter, S.D., Cheung, A., Wilansky-Traynor, P., Diaz-Granados, N., ... Wood, J.J., 2013. Cognitive behavioral therapy age effects in child and ado- lescent anxiety: an individual patient data metaanalysis. Depress. Anxiety 30 (9), 829–841. https://doi.org/10.1002/da.22099.

Berger, T., 2017. The therapeutic alliance in internet interventions: a narrative review and suggestions for future research. Psychother. Res. 27 (5), 511–524. https://doi. org/10.1080/10503307.2015.1119908.

Berger, T., Boettcher, J., Caspar, F., 2014. Internet-based guided self-help for several

S. Stjerneklar et al. Internet Interventions 15 (2019) 116–125

123

anxiety disorders: a randomized controlled trial comparing a tailored with a stan- dardized disorder-specific approach. Psychotherapy 51 (2), 207–219. https://doi. org/10.1037/a0032527.

Booth, M.L., Bernard, D., Quine, S., Kang, M.S., Usherwood, T., Alperstein, G., Bennett, D.L., 2004. Access to health care among Australian adolescents young people's per- spectives and their sociodemographic distribution. J. Adolesc. Health 34 (1), 97–103.

Bordin, E.S., 1979. The generalizability of the psychoanalytic concept of the working alliance. Psychotherapy 16 (3), 252–260. https://doi.org/10.1037/h0085885.

Cartwright-Hatton, S., Roberts, C., Chitsabesan, P., Fothergill, C., Harrington, R., 2004. Systematic review of the efficacy of cognitive behaviour therapies for childhood and adolescent anxiety disorders. Br. J. Clin. Psychol. 43 (Pt 4), 421–436. https://doi.org/ 10.1348/0144665042388928.

Chakraborty, H., Gu, H., 2009. A Mixed Model Approach for Intent-to-Treat Analysis in Longitudinal Clinical Trials with Missing Values. RTI Press publication No. MR-0009- 0903. Retrieved from. https://doi.org/10.3768/rtipress.2009.mr.0009.0903.

Christensen, H., Griffiths, M.K., Farrer, L., 2009. Adherence in internet interventions for anxiety and depression: systematic review. J. Med. Internet Res. 11 (2), e13. https:// doi.org/10.2196/jmir.1194.

Compton, S.N., Peris, T.S., Almirall, D., Birmaher, B., Sherrill, J., Kendall, P.C., ... Albano, A.M., 2014. Predictors and moderators of treatment response in childhood anxiety disorders: results from the CAMS trial. J. Consult. Clin. Psychol. 82 (2), 212–224. https://doi.org/10.1037/a0035458.

Costello, E.J., Egger, H.L., Copeland, W., Erkanli, A., Angold, A., Silverman WK, F.A., 2011. The developmental epidemiology of anxiety disorders: Phenomenology, pre- valence, and comorbidity. In: Anxiety Disorders in Children and Adolescents, 2 ed. Cambridge University Press, Cambridge, pp. 56–75.

Cuijpers, P., Donker, T., van Straten, A., Li, J., Andersson, G., 2010. Is guided self-help as effective as face-to-face psychotherapy for depression and anxiety disorders? A sys- tematic review and meta-analysis of comparative outcome studies. Psychol. Med. 40 (12), 1943–1957. https://doi.org/10.1017/s0033291710000772.

Ebert, D.D., Zarski, A.C., Christensen, H., Stikkelbroek, Y., Cuijpers, P., Berking, M., Riper, H., 2015. Internet and computer-based cognitive behavioral therapy for an- xiety and depression in youth: a meta-analysis of randomized controlled outcome trials. PLoS One 10 (3), e0119895. https://doi.org/10.1371/journal.pone.0119895.

El Alaoui, S., Hedman, E., Ljótsson, B., Bergström, J., Andersson, E., Rück, C., ... Lindefors, N., 2013. Predictors and moderators of internet- and group-based cognitive behaviour therapy for panic disorder. PLoS One 8 (11), e79024. https://doi.org/10. 1371/journal.pone.0079024.

El Alaoui, S., Ljotsson, B., Hedman, E., Kaldo, V., Andersson, E., Ruck, C., ... Lindefors, N., 2015. Predictors of symptomatic change and adherence in internet-based cognitive behaviour therapy for social anxiety disorder in routine psychiatric care. PLoS One 10 (4), e0124258. https://doi.org/10.1371/journal.pone.0124258.

Elliott, B.A., Larson, J.T., 2004. Adolescents in mid-sized and rural communities: foregone care, perceived barriers, and risk factors. J. Adolesc. Health 35 (4), 303–309. https:// doi.org/10.1016/j.jadohealth.2003.09.015.

Essau, C.A., Conradt, J., Petermann, F., 2000. Frequency, comorbidity, and psychosocial impairment of anxiety disorders in German adolescents. J. Anxiety Disord. 14 (3), 263–279. https://doi.org/10.1016/S0887-6185(99)00039-0.

Gulliver, A., Griffiths, K.M., Christensen, H., 2010. Perceived barriers and facilitators to mental health help-seeking in young people: a systematic review. BMC Psychiatry 10. https://doi.org/10.1186/1471-244X-10-113.

Hadjistavropoulos, H.D., Pugh, N.E., Hesser, H., Andersson, G., 2016. Predicting response to therapist-assisted internet-delivered cognitive behavior therapy for depression or anxiety within an open dissemination trial. Behav. Ther. 47 (2), 155–165. https:// doi.org/10.1016/j.beth.2015.10.006.

Heck, R.H., Thomas, S.L., Tabata, L.N., 2014. Multilevel and Longitudinal Modeling with IBM SPSS, 2 ed. Quantitative Methodology Series Routledge/Taylor & Francis, New York and London.

Hedman, E., Andersson, E., Ljótsson, B., Andersson, G., Andersson, E., Schalling, M., ... Rück, C., 2012. Clinical and genetic outcome determinants of internet- and group- based cognitive behavior therapy for social anxiety disorder. Acta Psychiatr. Scand. 126 (2), 126–136. https://doi.org/10.1111/j.1600-0447.2012.01834.x.

Hedman, E., Lindefors, N., Andersson, G., Andersson, E., Lekander, M., Ruck, C., Ljotsson, B., 2013. Predictors of outcome in internet-based cognitive behavior therapy for severe health anxiety. Behav. Res. Ther. 51 (10), 711–717. https://doi.org/10.1016/ j.brat.2013.07.009.

Horvath, A.O., Greenberg, L.S., 1989. Development and validation of the working Alliance inventory. J. Couns. Psychol. 36 (2), 223–233. https://doi.org/10.1037/ 0022-0167.36.2.223.

Horvath, A.O., Del Re, A.C., Fluckiger, C., Symonds, D., 2011. Alliance in individual psychotherapy. Psychotherapy (Chic.) 48 (1), 9–16. https://doi.org/10.1037/ a0022186.

Hudson, J.L., Keers, R., Roberts, S., Coleman, J.R., Breen, G., Arendt, K., ... Eley, T.C., 2015a. Clinical predictors of response to cognitive-behavioral therapy in pediatric anxiety disorders: the genes for treatment (GxT) study. J. Am. Acad. Child Adolesc. Psychiatry 54 (6), 454–463. https://doi.org/10.1016/j.jaac.2015.03.018.

Hudson, J.L., Rapee, R.M., Lyneham, H.J., McLellan, L.F., Wuthrich, V.M., Schniering, C.A., 2015b. Comparing outcomes for children with different anxiety disorders fol- lowing cognitive behavioural therapy. Behav. Res. Ther. 72, 30–37. https://doi.org/ 10.1016/j.brat.2015.06.007.

James, A.C., James, G., Cowdrey, F.A., Soler, A., Choke, A., 2013. Cognitive behavioural therapy for anxiety disorders in children and adolescents. Cochrane Database Syst. Rev.(6). https://doi.org/10.1002/14651858.CD004690.pub3.

James, A.C., James, G., Cowdrey, F.A., Soler, A., Choke, A., 2015. Cognitive behavioural therapy for anxiety disorders in children and adolescents. Cochrane Database Syst. Rev. 2. https://doi.org/10.1002/14651858.CD004690.pub4.

Knight, A., McLellan, L., Jones, M., Hudson, J., 2014. Pre-Treatment Predictors of Outcome in Childhood Anxiety Disorders: A Systematic Review. Textrum.

La Greca, A.M., Harrison, H.M., 2005. Adolescent peer relations, friendships, and ro- mantic relationships: do they predict social anxiety and depression? J. Clin. Child Adolesc. Psychol. 34 (1), 49–61. https://doi.org/10.1207/s15374424jccp3401_5.

Langley, A.K., Bergman, R.L., McCracken, J., Piacentini, J.C., 2004. Impairment in childhood anxiety disorders: preliminary examination of the child anxiety impact scale-parent version. J. Child Adolesc. Psychopharmacol. 14 (1), 105–114. https:// doi.org/10.1089/104454604773840544.

Lenhard, F., Andersson, E., Mataix-Cols, D., Ruck, C., Vigerland, S., Hogstrom, J., ... Serlachius, E., 2017. Therapist-guided, internet-delivered cognitive-behavioral therapy for adolescents with obsessive-compulsive disorder: a randomized controlled trial. J. Am. Acad. Child Adolesc. Psychiatry 56 (1), 10–19.e12. https://doi.org/10. 1016/j.jaac.2016.09.515.

Lundkvist-Houndoumadi, I., Hougaard, E., Thastum, M., 2014. Pre-treatment child and family characteristics as predictors of outcome in cognitive behavioural therapy for youth anxiety disorders. Nord. J. Psychiatry 0 (0), 1–12. https://doi.org/10.3109/ 08039488.2014.903295.

Lyneham, H.J., Rapee, R.M., 2005. Agreement between telephone and in-person delivery of a structured interview for anxiety disorders in children. J. Am. Acad. Child Adolesc. Psychiatry 44 (3), 274–282. https://doi.org/10.1097/00004583- 200503000-00012.

Lyneham, H.J., McLellan, L.F., Cunningham, M., Wuthrich, V., Schniering, C., Hudson, J.L., Rapee, R.M., 2014. ChilledOut Online Program. Centre for Emotional Health, Macquarie University, Sydney.

McLeod, B.D., 2011. Relation of the alliance with outcomes in youth psychotherapy: a meta-analysis. Clin. Psychol. Rev. 31 (4), 603–616. https://doi.org/10.1016/j.cpr. 2011.02.001.

Pennant, M.E., Loucas, C.E., Whittington, C., Creswell, C., Fonagy, P., Fuggle, P., ... Kendall, T., 2015. Computerised therapies for anxiety and depression in children and young people: a systematic review and meta-analysis. Behav. Res. Ther. 67, 1–18. https://doi.org/10.1016/j.brat.2015.01.009.

Podina, I.R., Mogoase, C., David, D., Szentagotai, A., Dobrean, A., 2016. A meta-analysis on the efficacy of technology mediated CBT for anxious children and adolescents. J. Ration. Emot. Cogn. Behav. Ther. 34 (1), 31–50. https://doi.org/10.1007/s10942- 015-0228-5.

Rapee, R.M., 2000. Group treatment of children with anxiety disorders: outcome and predictors of treatment response. Aust. J. Psychol. 52 (3), 125–130. https://doi.org/ 10.1080/00049530008255379.

Rapee, R.M., Schniering, C.A., Hudson, J.L., 2009. Anxiety disorders during childhood and adolescence: origins and treatment. Annu. Rev. Clin. Psychol. 5 (1), 311–341. https://doi.org/10.1146/annurev.clinpsy.032408.153628.

Reynolds, S., Wilson, C., Austin, J., Hooper, L., 2012. Effects of psychotherapy for anxiety in children and adolescents: a meta-analytic review. Clin. Psychol. Rev. 32 (4), 251–262. https://doi.org/10.1016/j.cpr.2012.01.005.

Rickwood, D.J., Deane, F.P., Wilson, C.J., 2007. When and how do young people seek professional help for mental health problems? Med. J. Aust. 187 (7 Suppl), S35–S39.

Rosenthal, R., 1991. Meta-Analytic Procedures for Social Research. Sage Publications, Thousand Oaks, California.

Shirk, S.R., Karver, M.S., Brown, R., 2011. The alliance in child and adolescent psy- chotherapy. Psychotherapy 48 (1), 17–24. https://doi.org/10.1037/a0022181.

Silverman, W.K., Albano, A.M., 1996. Anxiety Disorders Interview Schedule for Children for DSM–IV: Child and Parent Versions. TX: Psychological Corporation, San Antonio.

Silverman, W.K., Saavedra, L.M., Pina, A.A., 2001. Test-retest reliability of anxiety symptoms and diagnoses with Anxiety Disorders Interview Schedule for DSM-IV: child and parent versions. J. Am. Acad. Child Adolesc. Psychiatry 40 (8), 937–944. https://doi.org/10.1097/00004583-200108000-00016.

Silverman, W.K., Pina, A.A., Viswesvaran, C., 2008. Evidence-based psychosocial treat- ments for phobic and anxiety disorders in children and adolescents. J. Clin. Child Adolesc. Psychol. 37 (1), 105–130. https://doi.org/10.1080/15374410701817907.

Spek, V., Cuijpers, P., Nyklíček, I., Riper, H., Keyzer, J., Pop, V., 2007. Internet-based cognitive behaviour therapy for symptoms of depression and anxiety: a meta-ana- lysis. Psychol. Med. 37 (3), 319–328. https://doi.org/10.1017/S0033291706008944.

Spence, S.H., 1998. A measure of anxiety symptoms among children. Behav. Res. Ther. 36 (5), 545–566. https://doi.org/10.1016/S0005-7967(98)00034-5.

Spence, S.H., Donovan, C.L., March, S., Gamble, A., Anderson, R.E., Prosser, S., Kenardy, J., 2011. A randomized controlled trial of online versus clinic-based CBT for ado- lescent anxiety. J. Consult. Clin. Psychol. 79 (5), 629–642. https://doi.org/10.1037/ a0024512.

Spence, S.H., Donovan, C.L., March, S., Kenardy, J.A., Hearn, C.S., 2017. Generic versus disorder specific cognitive behavior therapy for social anxiety disorder in youth: a randomized controlled trial using internet delivery. Behav. Res. Ther. 90, 41–57. https://doi.org/10.1016/j.brat.2016.12.003.

Stallard, P., Udwin, O., Goddard, M., Hibbert, S., 2007. The availability of cognitive behaviour therapy within specialist child and adolescent mental health services (CAMHS): a National Survey. Behav. Cogn. Psychother. 35 (4), 501–505. https://doi. org/10.1017/S1352465807003724.

Steketee, G., Chambless, D.L., 1992. Methodological issues in prediction of treatment outcome. Clin. Psychol. Rev. 12 (4), 387–400. https://doi.org/10.1016/0272- 7358(92)90123-P.

Stjerneklar, S., Hougaard, E., Nielsen, A.D., Gaardsvig, M.M., Thastum, M., 2018. Internet-based cognitive behavioral therapy for adolescents with anxiety disorders: a feasibility study. Internet Interv. 11, 30–40. https://doi.org/10.1016/j.invent.2018. 01.001.

Stjerneklar, S., Hougaard, E., McLellan, L.F., Thastum, M., 2019. A randomized controlled trial examining the efficacy of an internet-based cognitive behavioral therapy

S. Stjerneklar et al. Internet Interventions 15 (2019) 116–125

124

program for adolescents with anxiety disorders. (submitted for publication). Tillfors, M., Andersson, G., Ekselius, L., Furmark, T., Lewenhaupt, S., Karlsson, A.,

Carlbring, P., 2011. A randomized trial of internet-delivered treatment for social anxiety disorder in high school students. Cogn. Behav. Ther. 40 (2), 147–157. https://doi.org/10.1080/16506073.2011.555486.

Tracey, T.J., Kokotovic, A.M., 1989. Factor structure of the working Alliance inventory. Psychol. Assess. 1 (3), 207–210. https://doi.org/10.1037/1040-3590.1.3.207.

Wang, P.S., Aguilar-Gaxiola, S., Alonso, J., Angermeyer, M.C., Borges, G., Bromet, E.J., ... Wells, J.E., 2007. Use of mental health services for anxiety, mood, and substance disorders in 17 countries in the WHO world mental health surveys. Lancet 370 (9590), 841–850. https://doi.org/10.1016/S0140-6736(07)61414-7.

Wood, J.J., McLeod, B.D., 2008. Child Anxiety Disorders: A Family-Based Treatment Manual for Practitioners. W W Norton & Co., New York, NY, US.

Wood, J.J., Piacentini, J.C., Bergman, R.L., McCracken, J., Barrios, V., 2002. Concurrent validity of the anxiety disorders section of the Anxiety Disorders Interview Schedule for DSM-IV: child and parent versions. J. Clin. Child Adolesc. Psychol. 31 (3), 335–342. https://doi.org/10.1207/s15374424jccp3103_05.

Wuthrich, V.M., Rapee, R.M., Cunningham, M.J., Lyneham, H.J., Hudson, J.L., Schniering, C.A., 2012. A randomized controlled trial of the cool teens CD-ROM computerized program for adolescent anxiety. J. Am. Acad. Child Adolesc. Psychiatry 51 (3), 261–270. https://doi.org/10.1016/j.jaac.2011.12.002.

S. Stjerneklar et al. Internet Interventions 15 (2019) 116–125

125

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DOI: 10.1177/1049731513503713

published online 19 September 2013Research on Social Work Practice Kristen Esposito Brendel and Brandy R. Maynard

Parent Interventions for Childhood Anxiety Disorders: A Systematic Review and Meta-Analysis−Child

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Research Article

Child–Parent Interventions for Childhood Anxiety Disorders: A Systematic Review and Meta-Analysis

Kristen Esposito Brendel 1

and Brandy R. Maynard 2

Abstract Objective: This study compared the effects of direct child–parent interventions to the effects of child-focused interventions on anxiety outcomes for children with anxiety disorders. Method: Systematic review methods and meta-analytic techniques were employed. Eight randomized controlled trials examining effects of family cognitive behavior therapy compared to individual or group child-only therapy met criteria. Results: The overall mean effect of parent–child interventions was 0.26, 95% confidence interval [0.05, 0.47], p < .05, a small but positive and significant effect, favoring child–parent interventions. Results of the heterogeneity analysis were not significant (Q ¼ 8.08, df ¼ 7, p > .05, I2 ¼ 13.41). Discussion: Parent–child interventions appear to be more effective than child-focused individual and group cognitive behavioral therapy in treating childhood anxiety disorders. Implications for practice and research are discussed.

Keywords anxiety disorder, systematic review, meta-analysis, family cognitive behavioral therapy

Childhood anxiety disorders are the most prevalent of all

childhood psychiatric disorders, with lifetime prevalence esti-

mates ranging from 2.6% to 32% (American Psychological Association, 2000; Cartwright,-Hatton, McNicol, & Doubleday,

2006; Costello, Mustillo, Erkanli, Keeler, & Angold, 2003;

Merikangas, He, Burstein, Swanson, Avenevoli, Cui, et al.,

2010). Childhood anxiety disorders have been linked to signifi-

cant negative implications for children across social, academic

and family domains and serious mental disorders, such as

depression, substance use disorders, and other anxiety disorders

in later adolescence and adulthood (Albano, Chorpita, & Bar-

low, 2003; Bittner et al., 2007; Langley, Bergman, McCracken,

& Piacentini, 2004). In light of the high prevalence and rates of

comorbidity with other behavioral and emotional problems,

longitudinal and population-based research examining corre-

lates, causes, and the developmental course of childhood anxiety

disorders has increased, including a focus on family and parental

factors that contribute to childhood anxiety disorders.

During the past two decades, a growing body of research

examining parental factors in relation to childhood anxiety dis-

orders suggests that parental anxiety and modeling behaviors

contribute to the development and maintenance of childhood

anxiety disorders (Choate, Pincus, Eyberg, & Barlow, 2005;

Ginsburg & Schlossberg, 2002; Rapee, 1997; Siqueland, Ken-

dall, & Steinberg, 1996). Research suggests an intergenerational

transmission of anxiety, with both genetic and environmental

factors implicated. Children are estimated to be 3 or 5 times

more likely to develop an anxiety disorder if one parent has an

anxiety disorder and 6 times more likely if both parents have

an anxiety disorder (Beidel & Turner, 1997; Last, Hersen,

Kazdin, Francis, & Grubb, 1991; Merikangas, Avenevoli, Dier-

ker, & Grillon, 1999). Additional parent-related risk factors have

been implicated in the cause and maintenance of childhood

anxiety disorders including high parental control, insecure attach-

ment, and parental modeling of poor coping strategies (Ginsburg

& Schlossberg, 2002; Maid, Smokowski, & Bacallao, 2008;

Silverman & Dick-Niederhauser, 2004; Wood, McLeod, Sigman,

Hwang, & Chu, 2003).

Child–Parent Interventions for Childhood Anxiety Disorders

In light of the growing research suggesting an influence of

parental factors in the development and maintenance of child-

hood anxiety disorders, a growing number of child–parent

interventions have been developed and purported as efficacious

in the treatment of childhood anxiety disorders. Research also

supports the integration of parents in child therapy as a means

1 School of Social Work, Aurora University, IL, USA

2 School of Social Work, Saint Louis University, MO, USA

Corresponding Author:

Kristen Esposito Brendel, School of Social Work, Aurora University, 347

Gladstone, Aurora, IL 60506, USA.

Email: [email protected]

Research on Social Work Practice 00(0) 1-9 ª The Author(s) 2013 Reprints and permission: sagepub.com/journalsPermissions.nav DOI: 10.1177/1049731513503713 rsw.sagepub.com

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to better generalize skills from the clinician’s office to the

home environment and for both the children and the parents

to learn and practice better methods to cope with issues of

anxiety that may be pervasive within the household (Bodden

et al., 2008; Bogels & Siqueland, 2006; Mendlowitz et al.,

1999; Wood, Piacentini, Southam-Gerow, Chu, & Sigman,

2006). Although all child–parent interventions have a common

factor, that the child and parent participate in the intervention

together, there are variations in the theories and methods used

across the array of child–parent interventions currently in prac-

tice. Some of the most common child–parent interventions

include family cognitive behavioral therapy (FCBT), parent-

child interaction therapy (PCIT), child–parent psychotherapy

(CPP), and Theraplay.

Family Cognitive Behavioral Therapy. FCBT integrates cognitive behavioral therapy in a family setting that includes parents and

children; the family is seen as the most favorable setting for

effecting change in children’s irrational thoughts. FCBT typi-

cally involves a treatment manual that guides the therapeutic

process and helps family members recognize essential thoughts

that are irrational and reframe them as more rational and pro-

ductive types of beliefs (Bogels & Siqueland, 2006; Kendall,

Hudson, Gosch, Flannery-Schroeder, & Suveg, 2008). FCBT

directly focuses on the most common parental factors that

have been associated with the development and maintenance

of childhood anxiety disorders, including parental control,

acceptance, and modeling, as well as other issues identified

during the assessment process and throughout treatment. More-

over, FCBT encourages parents to facilitate new opportunities

with their children to test distorted beliefs when at home and

while jointly engaging in community activities (Barrett &

Shortt, 2003). Parents also can model their own functional

cognition and behaviors to their children during the treatment

process and at home.

Parent-Child Interaction Therapy. PCIT integrates play therapy with developmental, social learning, and behavioral theories.

Although originally developed for preschool-age children

experiencing externalizing behavioral problems (Brinkmeyer

& Eyberg, 2003; Herschell & McNeil, 2005), researchers have

begun to investigate PCIT for other issues, including victims

of physical abuse, children in foster care, children with develop-

mental delays (Chaffin, Taylor, Wilson, & Igelman, 2007;

Herschell & McNeil, 2005), and children with separation anxiety

disorder (SAD; Choate et al., 2005; Herschell & McNeil, 2005).

Similar to FCBT, the premise of PCIT for children with anxiety

disorders is to effect change within the parent–child system.

PCIT is typically conducted in two phases, a child-directed

phase and then a parent-directed phase. During each phase, par-

ents learn how to modify their own actions, hence modifying the

reactions of their children. PCIT enhances parent–child relation-

ships by fostering healthy attachments, modifying reinforcement

contingencies, and reducing anxiety-provoking responses (Cho-

ate et al., 2005).

Child-Parent Psychotherapy. CPP is a model of family play therapy that involves treatment of the parent–child unit, using play as the

primary medium of intervention (Lieberman & Van Horn,

2005). Lieberman and colleagues posit that by using play in con-

joined sessions with child and parent, parental understanding of

the child’s inner experience increases, as well as trust, recipro-

city, and pleasure within the parent–child relationship (Lieber-

man & Inman, 2009). CPP involves the parent actively

playing with the child in the therapeutic milieu. It is a

relationship-based intervention that helps to change mutual

reinforcement of negative behaviors and instead enhances

emotional attunement (Lieberman & Van Horn, 2005).

Because CPP is designed to facilitate positive and healthy

associations between parent and child, it is conjectured that

it can also be helpful for children with anxiety disorders.

Research needs to be conducted on the efficacy of CPP as

an intervention specifically for children with anxiety disorders.

Theraplay. Theraplay is a systematic procedure invented by Ann M. Jernberg in the 1960s to increase positive interactions

between parent and child (Jernberg, 1979). Jernberg modeled

Theraplay after Winnicott’s (1958) notion of being a ‘‘good

enough mother.’’ Five dimensions present in mother–child

interactions are postulated in this model: structuring, challen-

ging, engagement, nurturing, and play. Jernberg formulated

Theraplay after these dimensions, with the premise that

parent–child interactions can be therapeutic for a number of

childhood disorders by fostering bonding, attunement, and play-

fulness (Jernberg, 1999; Wettig, Franke, & Fjordbark, 2006).

As research during the past decade has begun to elucidate

the relationship of parental influences and behavior and the

causes and maintenance of anxiety disorders in children, prac-

titioners have begun to treat childhood anxiety disorder in the

context of child–parent interventions. Although child–parent

interventions are widely used and supported by practitioners,

little is known about the effectiveness of child–parent interven-

tions compared to child-focused interventions in the treatment

of childhood anxiety disorders. Although prior reviews have

examined the effects of interventions for childhood anxiety dis-

orders, these reviews primarily focused on individual and/or

cognitive behavioral interventions, did not use a systematic

methodology or meta-analytic techniques, included diagnostic

classifications beyond anxiety disorders, or were conducted

before recent advancements in the field (see Cartwright-

Hatton, Roberts, Chitsabesan, Fothergill, & Harrington, 2004;

Creswell & Cartwright-Hatton, 2007; In-Albon & Schneider,

2007; Ishikawa, Okajima, Matsuoka, & Sakano, 2007; James,

Soler, & Weatherall, 2009; King et al.,1998; Reynolds, Wilson,

Austin, & Hooper, 2012; Silverman, Pina, & Viswesvaran,

2008). In light of the advancements made in understanding and

treating childhood anxiety disorder in the past decade and the

plethora of child–parent interventions being developed and

used, this review examines the current state of child–parent

intervention research for treating childhood anxiety disorders

and improves upon prior reviews by using systematic review

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methods and meta-analytic techniques to provide a comprehen-

sive picture of effects.

Purpose of the Present Study

The purpose of this systematic review and meta-analysis is to

specifically examine the differential effect on anxiety out-

comes of child–parent interventions compared to child-

focused interventions for children with anxiety disorders. The

specific research questions guiding this study were as follows:

(1) Are child–parent interventions more effective than inter-

ventions involving solely the child in decreasing anxiety for

children with anxiety disorders? and (2) Are there differences

in magnitude of effects by type of child–parent intervention?

Method

Systematic review procedures, following the Campbell Colla-

boration guidelines (see www.campbellcollaboration.org), were

used for all aspects of the search, retrieval, selection, and coding

of published and unpublished studies meeting study inclusion

criteria. Meta-analytic techniques were employed to quantita-

tively synthesize the results from included studies. The protocol

and screening and coding instruments guiding the conduct of this

study are available from the first author upon request.

Study Eligibility Criteria

Studies were eligible for inclusion if they examined the effects

of a child–parent intervention (i.e., an intervention in which a

parent or guardian and child were directly involved in the treat-

ment) against the effects of interventions targeting only the

child (an individual or group intervention in which the parent

did not directly participate) for children under the age of 18

with at least one anxiety disorder. Interventions were consid-

ered a child–parent intervention if they included at least one

intergenerational family unit, that is, parent and child or pri-

mary caretaker and child. Studies must have employed a rando-

mized or quasi-experimental design, measured at least one

anxiety outcome, and reported sufficient information to calcu-

late an effect size. Published and unpublished studies were eli-

gible and no geographical restrictions were imposed; however,

this review was limited to English language reports of studies

conducted between 1980 and 2013.

Search Strategy

A comprehensive and systematic search strategy was conducted in

an attempt to identify and retrieve all relevant published and

unpublished studies meeting inclusion criteria. The search, com-

pleted in April 2013, involved several sources and used the follow-

ing key words: ‘‘anxiety disorders,’’ ‘‘family therapy,’’ ‘‘childhood

anxiety,’’ ‘‘family treatment,’’ ‘‘randomized,’’ ‘‘experimental,’’

‘‘quasi-experimental,’’ ‘‘clinical,’’ and ‘‘intervention.’’ Informa-

tion sources included seven electronic databases (PsychINFO, Pro-

Quest, Dissertations and Abstracts, Academic Search Premier,

Social Work Abstracts, PubMed, and Medline); personal contacts

with the first authors of all relevant studies, relevant researchers,

research institutes, and professional associations; hand searches

of journals relevant to the topic of the review (i.e., Journal of Mar-

riage and Family Therapy, Journal of the American Association of

Child and Adolescent Psychiatry, The American Journal of

Orthopsychiatry, and Psychiatric Services); online searches

through Google, Google Scholar, Yahoo!, and relevant websites of professional organizations; and reference lists of prior reviews

and included studies.

Study Selection and Coding Procedures

The first author screened titles and abstracts for relevance.

Those that were obviously ineligible (i.e., did not involve the

target population, did not involve a child–parent intervention,

or were theoretical in nature) were screened out. The full text

of all studies that were not obviously ineligible or were ques-

tionable at this stage was obtained and screened for eligibility,

using a screening instrument developed by the first author.

The first author and a trained graduate student then coded stud-

ies deemed eligible by using a coding instrument developed by

the authors to guide systematic examination and extraction of

data. The coding instrument included categories concerning all

relevant bibliographic information, study context, intervention

and sample descriptors, research methods and quality descrip-

tors, and effect size data (Lipsey & Wilson, 2001).

To ensure reliability of coding procedures, the first author

and a trained graduated student independently coded 100% of the studies. Interrater reliability was obtained by dividing the

number of agreements by the number of possible agreements

for each study. There was 98% agreement between the two coders. All discrepancies were discussed and resolved.

Statistical Methods

Statistical analysis was designed to produce descriptive

information on the characteristics of the included studies, the

effect size of each intervention on anxiety outcomes, the grand

mean effect size, and the heterogeneity of effect sizes around

the mean. The standard mean difference effect size statistic,

corrected for small sample size bias (Hedges’ g), was

calculated for each study using a statistical software package,

Comprehensive Meta-Analysis, Version 2.0 (Borenstein,

Hedges, Higgins, & Rothstein, 2005) by inputting the means,

standard deviations, and sample sizes for the treatment and

control groups reported by the primary study authors. To main-

tain statistical independence of data, only one effect size was

computed for each subject sample. Four of the eight studies

used multiple measures to assess anxiety. In cases where mul-

tiple measures were used, the most valid measure was selected.

In two cases, the measure used in the meta-analysis included

both a parent and child report, which were reported by the pri-

mary study authors together as one score. In cases where more

than one comparison group was used (i.e., a waitlist control and

an alternative treatment), the group that received the alternative

child-focused treatment was used in the analysis.

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The effects of included studies were quantitatively synthe-

sized in Comprehensive Meta-Analysis. Effect sizes were

inverse variance weighted and random effects statistical mod-

els were assumed. Cochrane’s Q was used to assess heteroge-

neity in the effect sizes. A significant Q rejects the null

hypotheses, indicating that the variability in effect sizes

between studies is greater than what would be expected from

sampling error alone (Hedges & Olkin, 1985). Moderator anal-

ysis was not indicated, as the statistical test assessing heteroge-

neity was not significant (Lipsey & Wilson, 2001). We had

planned to assess and report publication bias by constructing

a scatter plot of study effect size by sample size; however, due

to the small number of studies, and thus low power, the use of

funnel plots or other techniques such as regression to assess

publication bias was not indicated (Card, 2012).

Results

The search procedures yielded close to 300 titles. After review of

titles and abstracts, 33 potential studies were retrieved in full text

for screening. Of those, 15 reports were excluded due to not

meeting basic eligibility criteria and the remaining 18 reports

were fully coded. Of those 18 studies, 10 were deemed ineligi-

ble. These studies were excluded due to using a single-group

pretest–posttest design (n ¼ 6), reporting secondary results of

included studies (n ¼ 2), or not providing sufficient statistics to compute an effect size (n ¼ 2). The final sample for this review includes eight randomized controlled trials. See Figure

1 for a flowchart detailing the search and selection process.

Descriptive Analysis

The characteristics of the eight included studies are summar-

ized in Table 1. Of the eight studies, one was an unpublished

dissertation and seven were peer-reviewed journal articles. The

studies were conducted in four countries: the United States

(n ¼ 4), Australia (n ¼ 2), Canada (n ¼ 1), and the Netherlands (n ¼ 1). The majority of the studies were conducted in a clinic setting (n ¼ 7), and one was conducted in a hospital setting.

Across the eight studies, participants included a total of 710

children and at least one parent. The age range of child partici-

pants was wide across studies (n ¼ 1, 6–13 years; n ¼ 1, 6–16 years; n ¼ 1, 7–12 years; n ¼ 3, 7–14; n ¼ 1, 12–17 years; n ¼ 1, 8–17 years). No studies included a subgroup analysis by age

range. Studies included a balanced proportion of male and

female child participants. Most of the participants across the

eight studies were Caucasian (68%), and 91% of the partici- pants had a primary diagnosis of social phobia, SAD, or gener-

alized anxiety disorder. Approximately 98% of the participants

Figure 1. Study search and selection process flow chart. RCT ¼ randomized controlled trial.

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had a secondary diagnosis, with the vast majority of secondary

diagnoses (83%) being another anxiety disorder. All child–parent interventions in this review used a treat-

ment manual and were based on FCBT; the comparison group

interventions were either individual CBT with the child (n ¼ 7) or group CBT with children only (n ¼ 1). All interventions were delivered in 12 to 16 sessions of 60 to 90 minutes each.

Four included studies tested Coping Cat (Kendall & Hedtke,

2006) or adaptations of Coping Cat, including a modified Coping

Cat for adolescents (Siqueland, Rynn, & Diamond, 2005), Coping

Koala (Barrett, Dadds, & Rapee, 1991), and Coping Bear (Men-

dlowitz & Scapillato, 1996). Coping Cat is a manualized cogni-

tive behavioral treatment program that assists school-age

children in recognizing and coping with anxious feelings and

physical reactions to anxiety. Wood, Piacentini, Southam-

Gerow, Chu, and Sigman (2006) examined the Building Confi-

dence Program, developed specifically for their study. This inter-

vention involved combining child-focused cognitive behavioral

therapies with in vivo exposure and parent involvement. Spence,

Donovan, and Brechman-Toussaint (2000) used the Social Skills

Training: Enhancing Social Competence in Children and Adoles-

cents program. The program integrated CBT, social skills train-

ing, relaxation techniques, problem-solving, and exposure

interventions. The parent–child interventions in the remaining

three studies were not named, but all used manualized cognitive

behavioral interventions developed for their studies.

At least one doctoral level therapist or psychiatrist delivered

all interventions. Other treatment personnel included doctoral

students in five studies, one social worker, eight research

assistants (in a single study), one family therapist, one youth

care worker, and other unspecified master’s and doctoral level

clinicians. Six studies used a combination of trained clinicians.

Meta-Analytic Results

The grand mean effect size for anxiety outcomes from the eight

independent samples reported in the included studies, assuming

a random effects model, was 0.26 (95% confidence interval [0.05, 0.47], p < .05), demonstrating a small but positive and

statistically significant effect, favoring child–parent interven-

tions on anxiety outcomes. Table 2 provides a summary of the

characteristics and mean effect sizes for each of the included

studies. The mean effect size and confidence intervals for each

study are also shown in the forest plot in Figure 2. As seen in

the table and forest plot, the effect sizes range from a very small

and negative 0.01 to .88. Moreover, the confidence intervals

around the mean effect size in seven of the eight studies cross

zero, indicating that the child–parent intervention group did not

differ significantly on anxiety outcomes from the child-focused

intervention group. However, when the studies are pooled, the

mean effect is positive, small, and statistically significant.

Analysis of Homogeneity. To examine whether between-study var- iance is greater than what would be expected from sampling

error alone, an analysis of heterogeneity was conducted using the

Q-test. The result of the test of homogeneity was not significant

(Q ¼ 8.08, df ¼ 7, p ¼ .325, I2 ¼ 13.41), indicating that any var- iance in effect sizes across included studies can be attributed to

sampling error alone, rather than systematic or random differ-

ences between studies (Lipsey & Wilson, 2001). Although the

Q-test was not significant, we assumed a random effects model

because the Q-test does not have much statistical power with

small sample sizes and may fail to reject homogeneity when

there is significant variability of effect sizes across studies (Lip-

sey & Wilson, 2001). Moreover, the random effects model was

selected a priori because it was anticipated that the included

studies would vary in terms of study, participant, and interven-

tion characteristics. Because we found no significant variability

beyond sampling error, and due to the small number of included

studies, moderation analysis was not indicated.

Analysis of Publication Bias. To mitigate publication bias, special efforts were made to search for and retrieve unpublished

reports; however, only one unpublished report was included

in this review. Conducting a formal assessment of publication

bias, such as constructing and visually inspecting a funnel plot

or using the trim and fill method, was not indicated due to the

study’s small sample size and low power (Littell, 2008).

Discussion and Applications to Social Work

The purpose of the present study was to compare child–parent

interventions to other treatment modalities to determine whether

child–parent interventions are more effective and to inform

social work practice with children with anxiety. A systematic

Table 1. Characteristics of Included Studies.

Study Characteristics

a N (%)

Participant Characteristics

b N (%)

Publication year Sex 1990–1999 2 (25) Male 347 (52) 2000–2005 2 (25) Female 323 (48) 2006–2009 4 (50)

Publication type Participating parentc

Journal 7 (88) Mother 460 (91) Dissertation 1 (13) Father 249 (38)

Country Anxiety disorder United States 4 (50) Social phobia 229 (34) Australia 2 (25) SAD 199 (30) Canada 1 (13) GAD 182 (27) The Netherlands 1 (13) Other 60 (9)

Sample size Racec

1–50 3 (38) Caucasian 323 (68) 51–100 2 (25) Hispanic 114 (24) 101–150 2 (25) African American 21 (4) 151–200 1 (13) Other 20 (4)

Setting Clinic 7 (88) Hospital 1 (13)

Note. SAD ¼ separation anxiety disorder; GAD ¼ generalized anxiety disorder. a N ¼ 8 studies.

b N ¼ 670 total child participants.

c Three studies did not report data.

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review methodology was used to search, select, and extract

data from studies examining effects of child–parent inter-

ventions against child-focused interventions. Eight studies

met inclusion criteria for this review. Meta-analytic results

revealed a small but overall positive and significant effect

of parent–child interventions compared to child-focused

individual or group interventions. On average, FCBT outper-

formed child-focused CBT individual and group interventions

on anxiety outcomes. While an effect size of .26 is considered

small using Cohen’s rules of thumb (Cohen, 1988), given that

this review directly compares FCBT to already established

interventions, a statistically significant effect size of .26 is

impressive and reveals a non-negligible advantage of FCBT over

already established child-focused CBT interventions. Although

there was some variation in the delivery of the FCBT interven-

tions, there was no statistically significant difference in the mag-

nitude of effects of the FCBT interventions across studies,

indicating that any variations in the FCBT models used did not

affect the magnitude of effect of the intervention.

It is interesting to note that the effect sizes in seven of the

eight studies, when examined individually, were not signifi-

cantly different from zero, meaning that there was no evidence

Figure 2. Forest plot of mean effects (Hedges’ g) of included studies. CI ¼ confidence interval.

Table 2. Summary of Included Studies.

Author (Year) Type of Intervention N Age Range Comparison Intervention Anxiety Measure ES 95% CI

Barrett et al. (1996) FCBT 79 7–14 ICBT RCMAS 0.41 [�0.13, 0.95] Bodden et al. (2008) FCBT 128 8–17 ICBT ADIS C/P 0.53 [�0.05, 1.12] Kendall et al. (2008) FCBT 161 7–14 ICBT MASC �0.01 [�0.38, 0.36] Mendlowitz et al. (1999) FCBT 68 7–12 ICBT RCMAS 0.16 [�0.54, 0.86] Moreno (2007) FCBT 143 6–16 GCBT RCMAS 0.05 [�0.33, 0.43] Siqueland et al. (2005) FCBT 11 12–17 ICBT HAM-A 0.48 [�0.62, 1.59] Spence et al. (2000) FCBT 50 7–14 ICBT ADIS-P 0.34 [�0.35, 1.04] Wood et al. (2006) FCBT 40 6–13 ICBT ADIS-C/P 0.88* [0.22, 1.53]

Note. CI ¼ confidence interval; FCBT ¼ family cognitive behavioral therapy; ICBT ¼ individual cognitive behavioral therapy; RCMAS ¼ Revised Children’s Manifest Anxiety Scale; ADIS ¼ Anxiety Disorder Interview Schedule (C ¼ Child Version, P ¼ Parent Version); MASC ¼ Multidimensional Anxiety Scale for Children; GCBT ¼ group cognitive behavioral therapy; HAM-A ¼ Hamilton Anxiety Rating Scale. *p < .05.

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that FCBT was more effective than child-focused CBT found in

the majority of the individual studies. When combined, how-

ever, the pooled effect size was significantly different from

zero, indicating that FCBT was more effective than child-focused

CBT on average. Given the small sample sizes in several of the

included studies, it is possible that the primary studies failed to

demonstrate a significant effect because they were underpowered.

One of the strengths of meta-analysis over narrative or vote-

counting methods is the capability to find effects that are not readily

apparent or are obscured when using less sophisticated approaches

(Lipsey & Wilson, 2001). By pooling effect size estimates across

studies, meta-analysis can combine the results of underpowered

studies, producing a synthesized effect estimate with considerably

more statistical power to discover meaningful effects that can be

missed in low-powered individual studies (Card, 2012).

Given the advances in the development of non-CBT parent–

child interventions for anxiety disorders, we had anticipated

finding at least some studies examining effects of non-CBT

parent–child interventions. However, despite our best efforts,

we did not locate any studies testing effects of other models

of child–parent interventions against child-focused interven-

tions that met inclusion criteria. Moreover, all of the compari-

son groups received a variant of individual or group CBT

interventions. On the one hand, the lack of diversity in the

interventions examined in this review and the homogeneity

of effects across studies provide greater confidence in the pres-

ent study’s findings. On the other hand, finding only FCBT

studies that met inclusion criteria was disappointing, as we did

not intend for this review to focus on CBT interventions.

The failure to find child–parent intervention studies that met

inclusion criteria and that were not based on FCBT could be

attributed to a number of potential reasons. It is possible that

non-CBT interventions do not receive sufficient empirical

attention (or funding), that research with other types of inter-

ventions is not as well developed or rigorous, that rigorous

research exists but is not compared to child-focused interventions,

or that research is not published or otherwise made available (pos-

sibly due to issues related to reporting bias). Nevertheless, the lack

of rigorous research on non-CBT child–parent interventions for

treating childhood anxiety disorder is concerning and perplexing.

Although the meta-analytic findings indicate support for

FCBT interventions over child-focused CBT interventions,

gaps remain in the evidence base in terms of identifying for

whom and under what circumstances FCBT is more effective.

Primary studies in this review included children across a wide

range of ages and developmental periods. Despite hypotheses

that family interventions may be more effective and develop-

mentally appropriate for younger children, the included studies

did not examine differential effectiveness between ages or

developmental stages of the study participants. Thus, despite

prior recommendations by several researchers to examine dif-

ferential effects of FCBT across age groups (Creswell &

Cartwright-Hatton, 2007; Reynolds et al., 2012), we still know

little about the relative effectiveness of FCBT for children in

different age groups. Similarly, some included studies were

missing relevant information regarding the demographics of

the participants, and some studies did not report effects by

race/ethnicity or other relevant demographic characteristics.

Child-focused CBT may be more appropriate and more effec-

tive than FCBT for some groups of children or parents, based

on race/ethnicity, socioeconomic status, or other demographic

variables. Future research could begin to parse out differential

effectiveness, based on participant characteristics.

Based on the results of the present study, one cannot draw con-

clusions about the relative efficacy of FCBT for different types of

anxiety disorders. While there is some extant evidence of differen-

tial effects of interventions for different anxiety or comorbid disor-

ders (Kendall et al., 2008; Rapee et al., 2013), we were unable to

examine effects by type of disorder in the present study. The

included studies tested FCBT interventions with a range of anxiety

disorders; however, no studies differentiated effects by type, sever-

ity, or duration of anxiety disorders, and no study limited the sam-

ple to a specific disorder. Most studies also included participants

with comorbid conditions; thus, it is unclear whether there are dif-

ferential effects between diagnostic categories. Future research can

begin to elucidate whether and which anxiety disorders are more or

less responsive to FCBT compared to child-focused CBT and other

modalities, either by focusing specifically on one disorder or pro-

viding subsets of outcome data by diagnostic category.

While this study expands and improves upon prior reviews

and contributes to the growing evidence base of intervention

effectiveness for childhood anxiety disorders, the present study

is not without limitations and the findings must be interpreted

in light of the study’s limitations. This review is limited to a rel-

atively small number of studies that compared the effects of

child–parent interventions to those of alternative interventions

for children with anxiety disorders and that met the other inclu-

sion criteria specified for this review. Also, we may not have

captured every eligible intervention study, despite our compre-

hensive and systematic search process. Despite our intent to

include a variety of parent–child interventions outside of CBT,

all of the studies included in this review compared a variant of

FCBT to individual or group CBT. Findings from this review

may not generalize to studies examining effects of different

types of parent–child interventions or studies that were

excluded from this review due to not meeting inclusion criteria

or not being identified in the search. Also, despite our attempts

to include unpublished studies through our gray literature

search, we discovered only one unpublished study and thus

publication bias is a potential threat to the validity of this

review. Moreover, because we calculated effects by using the

most reliable and valid anxiety measure reported in each of the

included studies, the outcome measures used in this analysis

may not represent the outcome measures that the primary study

authors or another reviewer would have selected and in some

cases may overestimate or underestimate the treatment effect

compared to other measures reported in the primary studies.

Conclusion

Due to the significant immediate and long-term implications of

childhood anxiety disorders, it is important that children and

Brendel and Maynard 7

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adolescents who experience anxiety receive effective treatment.

Social workers and other treatment professionals are mandated,

through their respective professional code of ethics, to engage

in evidence-informed practice. The present study contributes to

the evidence base of interventions for childhood anxiety disorders

by synthesizing the effects of child–parent interventions to assist

practitioners in making evidence-informed decisions with their

clients. While the study results provide evidence of effectiveness

of FCBT compared to individual or group child-focused CBT

interventions in reducing anxiety, gaps and areas ripe for further

study were also identified. Future directions for research include

replicating current primary studies, particularly with larger sam-

ple sizes, and assessing effects of other child–parent interventions

that are in the early stages of development, such as PCIT,

attachment-based family therapy, and child–parent psychother-

apy. Additionally, follow-up studies to published research are

vital to establishing the long-term effectiveness of parent–child

interventions. Future research also needs to systematically exam-

ine potential moderating and mediating variables, such age, sex,

race, socioeconomic status, severity and type of anxiety disorder,

parental anxiety, and other comorbid conditions that may have a

differential impact on the effects of interventions. In addition to

research on effects of interventions, future research could assess

and report on implementation issues, intervention fidelity, and the

cost and benefit of interventions to help clinicians, organizations,

and clients make well-informed decisions about treatment.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to

the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the

research, authorship, and/or publication of this article: This research

was supported in part by the Meadows Center for Preventing

Educational Risk and the Institute of Education Sciences (grant #

R324B080008).

References

References marked with an asterisk indicate studies included in the

meta-analysis.

Albano, A. M., Chorpita, B. F., & Barlow, D. H. (2003). Childhood anxi-

ety disorders. In E. J. Mash & R. A. Barkley (Eds.), Child psycho-

pathology (2nd ed., pp. 279–319). New York, NY: Guilford Press.

American Psychological Association. (2000). Diagnostic and statisti-

cal manual of mental disorders (4th ed.). Washington, DC: Author.

Barrett, P. M., Dadds, M. R., & Rapee, R. M. (1991). Coping Koala

workbook (Unpublished manuscript). School of Applied Psychol-

ogy, Griffith University, Nathan, Australia.

*Barrett, P. M., Dadds, M. R., & Rapee, R. M. (1996). Family treatment

of childhood anxiety: A controlled trial. Journal of Consulting and

Clinical Psychology, 64, 333–342.

Barrett, P. M., & Shortt, A. L. (2003). Parental involvement in the

treatment of anxious children. In A. E. Kazdin & J. R. Weisz

(Eds.), Evidence-based psychotherapies for children and adoles-

cents (pp. 101–119). New York, NY: Guilford Press.

Beidel, D. C., & Turner, M. W. (1997). At risk for anxiety:

Psychopathology in the offspring of anxious parents. Journal of the

American Academy of Child and Adolescent Psychiatry, 36, 918–924.

Bittner, A., Egger, H. L., Erkanli, A., Costello, J., Foley, D. L., &

Angold, A. (2007). What do childhood anxiety disorders predict?

Journal of Child Psychology and Psychiatry, 48, 1174–1183.

*Bodden, D. H. M., Bogels, S. M., Nauta, M. H., De Hann, E.,

Ringrose, J., Appelboom, C., & Appelboom-Geerts, K. C. M.

M. J. (2008). Child versus family cognitive behavioral therapy

in clinically anxious youth: An efficacy and partial effectiveness

study. Journal of the American Academy of Child and Adolescent

Psychiatry, 47, 1384–1394.

Bogels, S. M., & Siqueland, L. (2006). Family cognitive behavioral

therapy for children and adolescents with clinical anxiety disor-

ders. Journal of the American Academy of Child and Adolescent

Psychiatry, 45, 134–141.

Borenstein, M., Hedges, L., Higgins, J., & Rothstein, H. (2005). Com-

prehensive meta-analysis (Version 2) [Computer software]. Engle-

wood, NJ: Biostat.

Brinkmeyer, M. Y., & Eyberg, S. M. (2003). Parent-child interaction

therapy for oppositional children. In A. E. Kazdin (Ed.), Evidence-

based psychotherapies for children and adolescents (pp. 144–184).

New York, NY: Guilford Press.

Card, N. A. (2012). Applied meta-analysis for social science research.

New York, NY: Guilford Press.

Cartwright-Hatton, S., McNicol, K., & Doubleday, E. (2006). Anxiety

in a neglected population: Prevalence of anxiety disorders in pre-

adolescent children. Clinical Psychology Review, 26, 817–833.

Cartwright-Hatton, S., Roberts, C., Chitsabesan, P., Fothergill, C., &

Harrington, R. (2004). Systemic review of the efficacy of cognitive

behavior therapies for childhood and adolescent anxiety disorders.

British Journal of Clinical Psychology, 43, 421–436.

Chaffin, M., Taylor, N., Wilson, C., & Igelman, R. (2007). Parent-

child interaction therapy with at-risk families. Retrieved from

http://www.childwelfare.gov/pubs/f_interactbulletin/

Choate, M. L., Pincus, D. B., Eyberg, S. M., & Barlow, D. H. (2005).

Parent-child interaction therapy for treatment of separation anxiety

disorder in young children: A pilot study. Cognitive and Beha-

vioral Practice, 12, 126–135.

Cohen, J. (1988). Statistical power analysis for the behavioral

sciences (2nd ed.). New York: Academic Press.

Costello, E. J., Mustillo, S., Erkanli, A., Keeler, G., & Angold, A.

(2003). Prevalence and development of psychiatric disorders in

childhood and adolescence. Archives of General Psychiatry, 60,

837–844.

Creswell, C., & Cartwright-Hatton, S. (2007). Family treatment of

child anxiety: Outcomes, limitations and future directions. Clinical

Child and Family Psychology, 10, 232–252.

Ginsburg, G. S., & Schlossberg, M. C. (2002). Family-based treatment

of childhood anxiety disorders. International Review of Psychiatry,

14, 143–154.

Hedges, L. V., & Olkin, I. (1985). Statistical methods for meta-anal-

ysis. New York, NY: Academic Press.

Herschell, A., & McNeil, C. (2005). Parent-child interaction therapy

for children experiencing externalizing behavior problems. In

L. A. Reddy, T. M. Files-Hall & C. E. Schaefer (Eds.), Empirically

8 Research on Social Work Practice 00(0)

at SAINT LOUIS UNIV on September 20, 2013rsw.sagepub.comDownloaded from

based play interventions for children (pp. 210–239). Washington,

DC: American Psychological Association.

In-Albon, T., & Schneider, S. (2007). Psychotherapy of childhood

anxiety disorders: A meta-analysis. Psychotherapy and Psychoso-

matics, 76, 15–24.

Ishikawa, S., Okajima, I., Matsuoka, H., & Sakano, Y. (2007).

Cognitive behavioural therapy for anxiety disorders in children and

adolescents: A meta-analysis. Child and Adolescent Mental

Health, 12, 164–172.

James, A. A. C. J., Soler, A., & Weatherall, R. R. W. (2009). Cognitive

behavioural therapy for anxiety disorders in children and adoles-

cents (Review). Cochrane Database of Systemic Reviews, 4, 1–34.

Jernberg, A. M. (1979). Theraplay: A new treatment using structured

play for children and their families. San Francisco, CA: Jossey-Bass.

Jernberg, A. M. (1999). Theraplay: Helping parents and children

build better relationships through attachment-based play. San

Francisco, CA: Jossey-Bass.

Kendall, P. C., & Hedtke, K. A. (2006). Coping cat workbook (2nd

ed.). Ardmore, PA: Workbook.

*Kendall, P. C., Hudson, J. L., Gosch, E., Flannery-Schroeder, E., & Suveg,

C. (2008). Cognitive-behavioral therapy for anxiety disordered youth:

A randomized clinical trial evaluating child and family modalities.

Journal of Consulting and Clinical Psychology, 76, 282–297.

King, N. J., Tonge, B. J., Heyne, D., Pritchard, M., Rollings, S., Young, D.,

& Ollendick, T. H. (1998). Cognitive-behavioral treatment of school

refusing children: A controlled evaluation. Journal of the American

Academy of Child and Adolescent Psychiatry, 37, 395–403.

Langley, A. K., Bergman, L., McCracken, J., & Piacentini, J. C.

(2004). Impairment in childhood anxiety disorders: Preliminary

examination of the child anxiety impact scale-parent version. Jour-

nal of Child and Adolescent Psychopharmacology, 14, 105–114.

Last, C. G., Hersen, M., Kazdin, A. E., Francis, G., & Grubb, H. J.

(1991). Anxiety disorders in children and their families. Archives

of General Psychiatry, 48, 928–934.

Lieberman, A. F., & Inman, L. R. (2009). Child-parent psychotherapy.

In A. A. Drewes (Ed.), Blending play therapy with cognitive beha-

vioral therapy: Evidence-based and other effective treatments and

techniques (pp. 241–256). Hoboken, NJ: John Wiley.

Lieberman, A. F., & Van Horn, P. (2005). Don’t hit my mommy! A

manual for child-parent psychotherapy with young witnesses of

family violence. Washington, DC: Zero to Three.

Lipsey, M. W., & Wilson, D. B. (2001). Practical meta-analysis.

Thousand Oaks, CA: Sage.

Littell, J. H., Corcoran, J., & Pillai, V. (2008). Systematic reviews and

meta-analysis: Pocket guides to social work research methods.

New York: Oxford University Press.

Maid, R., Smokowski, P., & Bacallao, M. (2008). Family treatment of

childhood anxiety. Child and Family Social Work, 13, 433–442.

*Mendlowitz, S. L., Manassis, K., Bradley, S., Scapillato, D.,

Miezitis, S., & Shaw, B. F. (1999). Cognitive-behavioral group

treatments in childhood anxiety disorders: The role of parental

involvement. Journal of the American Academy of Child and

Adolescent Psychiatry, 38, 1223–1229.

Mendlowitz, S., & Scapillato, D. (1996). Coping bear workbook and

notebook (Unpublished manuscript). Hospital for Sick Children,

Toronto, Canada.

Merikangas, K. R., Avenevoli, S., Dierker, L., & Grillon, C. (1999).

Vulnerability factors among children at risk for anxiety disorders.

Biological Psychiatry, 46, 1523–1535.

Merikangas, K. R., He, J., Burstein, M., Swanson, S. A., Avenevoli, S.,

Cui, L., et al. (2010). Lifetime Prevalence of Mental Disorders in

U.S. Adolescents: Results from the National Comorbidity Survey

Replication-Adolescent Supplement (NCS-A). Journal of the Amer-

ican Academy of Child and Adolescent Psychiatry, 49, 980–989.

*Moreno, J. (2007). Family and group cognitive behavioral therapy:

Evaluation of treatment outcome and treatment specificity

(Doctoral dissertation, Florida International University). Retrieved

from http://digitalcommons.fiu.edu/dissertations/AAI3268658

Rapee, R. M. (1997). Potential role of childrearing practices in the

development of anxiety and depression. Clinical Psychology

Review, 17, 47–67.

Rapee, R. M., Lyneham, H. J., Hudson, J. L., Kangas, M., Wuthrich, V. M.,

& Schniering, C. A. (2013). Effect of comorbidity on treatment of anx-

ious children and adolescents: Results from a large, combined sample.

Journal of the American Academy of Child and Adolescent Psychiatry,

52, 47–56.

Reynolds, S., Wilson, C., Austin, J., & Hooper, L. (2012). Effects of

psychotherapy for anxiety in children and adolescents: A meta-

analytic review. Clinical Psychology Review, 32, 251–262.

Silverman, W. K., & Dick-Niederhauser, A. (2004). Separation anxi-

ety disorder. In T. Morris & J. March (Eds.), Anxiety disorders in

children and adolescents (pp. 69–101). New York, NY: Guilford

Press.

Silverman, W. K., Pina, A. A., & Viswesvaran, C. (2008). Evidence-

based psychosocial treatments for phobic and anxiety disorders in

children and adolescents. Journal of Clinical Child & Adolescent

Psychology, 37, 105–130.

Siqueland, L., Kendall, P. C., & Steinberg, L. (1996). Anxiety in

children: Perceived family environments and observed family

interaction. Journal of Clinical Child Psychology, 25, 225–237.

*Siqueland, L., Rynn, M., & Diamond, G. S. (2005). Cognitive beha-

vioral and attachment based family therapy for anxious adoles-

cents: Phase I and II studies. Anxiety Disorders, 19, 361–381.

*Spence, S. H., Donovan, C., & Brechman-Toussaint, M. (2000). The

treatment of childhood social phobia: The effectiveness of a social

skills training-based, cognitive-behavioural intervention, with and

without parental involvement. Journal of Child Psychology and

Psychiatry, 41, 713–726.

Wettig, H. H. G., Franke, U., & Fjordbark, B. S. (2006). Evaluating the

effectiveness of Theraplay. In C. S. Schaefer & H. G. Kaduson

(Eds.), Contemporary play therapy: Theory, research, and practice

(pp. 103–135). New York, NY: Guilford Press.

Winnicott, D. W. (1958). Collected papers: Through pediatrics to

psychoanalysis. London, UK: Tavistock.

Wood, J. J., McLeod, B. D., Sigman, M., Hwang, W., & Chu, B. C.

(2003). Parenting and childhood anxiety: Theory, empirical find-

ings, and future directions. Journal of Child Psychology and Psy-

chiatry, 44, 134–151.

*Wood, J. J., Piacentini, J. C., Southam-Gerow, M., Chu, B., & Sig-

man, M. (2006). Family cognitive behavioral therapy for child

anxiety disorders. Journal of the American Academy of Child and

Adolescent Psychiatry, 45, 314–321.

Brendel and Maynard 9

at SAINT LOUIS UNIV on September 20, 2013rsw.sagepub.comDownloaded from View publication statsView publication stats