A meta-analysis of nonrandomized effectiveness studies on outpatient cognitive behavioral therapy for adult anxiety disorders

    A Meta-Analysis of Nonrandomized Effectiveness Studies on Outpatient Cognitive Behavioral Therapy for Adult Anxiety Disorders Eva Hans, Wolfgang Hiller PII: DOI: Reference:

S0272-7358(13)00091-3 doi: 10.1016/j.cpr.2013.07.003 CPR 1327

To appear in:

Clinical Psychology Review

Received date: Revised date: Accepted date:

18 November 2012 7 July 2013 9 July 2013

Please cite this article as: Hans, E. & Hiller, W., A Meta-Analysis of Nonrandomized Effectiveness Studies on Outpatient Cognitive Behavioral Therapy for Adult Anxiety Disorders, Clinical Psychology Review (2013), doi: 10.1016/j.cpr.2013.07.003

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A Meta-Analysis of Nonrandomized Effectiveness Studies on Outpatient Cognitive

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Behavioral Therapy for Adult Anxiety Disorders

Eva Hans and Wolfgang Hiller

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Department of Clinical Psychology, Johannes Gutenberg University Mainz, Germany

Eva Hans

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Correspondence should be addressed to:

Department of Clinical Psychology Johannes Gutenberg University Mainz Wallstrasse 3, 55122 Mainz, Germany Email:

ACCEPTED MANUSCRIPT CBT FOR ADULT ANXIETY Abstract Objective: The primary aim of this study was to assess the overall effectiveness of individual

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and group outpatient cognitive behavioral therapy (CBT) for adults with a primary anxiety

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disorder in routine clinical practice.

Method: We conducted a random effects meta-analysis of 71 nonrandomized effectiveness

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studies on outpatient individual and group CBT for adult anxiety disorders. Standardized mean gain effect sizes pre- to posttreatment, and posttreatment to follow-up are reported for

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disorder-specific symptoms, depression, and general anxiety. The mean dropout from CBT is

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reported.

Results: Outpatient CBT was effective in reducing disorder-specific symptoms in completer (d = 0.90–1.91) and intention-to-treat samples (d = 0.67–1.45). Moderate to large (d = 0.54–

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1.09) and small to large effect sizes (d = 0.42–0.97) were found for depressive and general

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anxiety symptoms posttreatment. Across all anxiety disorders, the weighted mean dropout rate was 15.06%. Posttreatment gains for disorder-specific anxiety were maintained 3 and 12

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months after completion of therapy. Conclusions: CBT for adult anxiety disorders is very effective and widely accepted in routine practice settings. However, the methodological and reporting quality of nonrandomized effectiveness studies must be improved. Keywords: meta-analysis, effectiveness, cognitive behavioral therapy, anxiety disorders, treatment outcome

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A Meta-Analysis of Nonrandomized Effectiveness Studies on Outpatient Cognitive

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Behavioral Therapy for Adult Anxiety Disorders

(d = 1.58;

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Norton & Price, 2007) and a superiority of CBT over psychological or pill placebo conditions

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at reducing disorder-specific anxiety (Hedges’ gcompleter = 0.73; Hedges’ gITT = 0.33) and associated depression (Hedges’ g completer = 0.45; Hofmann & Smits, 2008). While the efficacy of CBT is well established, meta-analytic evidence on the relative efficacy of

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individual versus group CBT for anxiety disorders is scarce and is based on indirect comparisons (except for the 2011 study of Jónsson, Hougaard, & Bennedsen . There is no

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clear indication of a superiority of either treatment format. Individual CBT was more effective than group CBT for GAD (Covin, Ouimet, Seeds, & Dozois, 2008) and equally effective as panic disorder (Sánchez-Meca, Rosa-Alcázar,

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group CBT for

Marín-Martínez, & Gómez-Conesa, 2010), and social phobia (Fedoroff & Taylor, 2001; Gould, Buckminster, Pollack, Otto, & Yap, 1997; Powers, Sigmarsson, & Emmelkamp, 2008; Taylor, 1996)

CBT for PTSD

comparing the efficacy of both treatment formats Furthermore

(Hofmann & Smits, 2008: M = 10.1, SD = 4.2; Norton & Price, 2007: M = 11.8, SD = 4.2; Powers et al., 2008: M = 10.5, SD = 3.7; Sánchez-Meca et al., 2010: M = 10.2, SD = 3.6). Besides improvement in symptom severity, it is important to evaluate treatment success in terms of dropout from treatment. Given that most meta-analyses use completer effect sizes

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which are generally larger than those according to intention-to-treat (ITT; cf., Hofmann & Smits, 2008), increased rates of attrition can limit the interpretation of meta-analytic findings.

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However, a recent meta-analysis of 669 treatment outcome studies showed a modest mean

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dropout rate (16.2%) among adult psychotherapy patients with an anxiety disorder, with equal

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dropout rates between individual and group CBT (Swift & Greenberg, 2012).

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(Buchkremer & Klingberg, 2001; Fydrich & Schneider,

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2007; Seligman, 1995; Westen & Morrison, 2001)

exclusion of patients with comorbid psychosis or bipolar disorder,

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substance misuse, depression, or another Axis I disorder, avoidant personality disorder, low symptom severity, prior social phobia treatment, and the restriction of the sample to students or a qualitatively homogenous subgroup.

Similarly, when sample selection criteria commonly used in RCTs were applied to routine practice samples of adult outpatients, no significant effect on CBT outcome emerged (Lincoln et al., 2003; McEvoy, 2007). In view of these external validity concerns, effectiveness studies have been widely demanded to complement results from RCTs (Chambless & Hollon, 1998; Chambless & Ollendick, 2001; Seligman, 1995). While there is widespread agreement that the transportability of research findings to clinical practice should be examined, a standard

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definition of what constitutes an effectiveness study is lacking (e.g., Gartlehner, Hansen, Nissman, Lohr, & Carey, 2006). Two studies have used criteria to determine the degree of

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clinical representativeness of a clinical trial of which several had to be met in order to be

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considered as an effectiveness study; the following six common criteria were applied: (a)

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nonuniversity setting, (b) patient referral, (c) professional therapists, (d) flexible structure, (e) no monitoring of treatment implementation, and (g) no therapist training for study purposes (Shadish, Matt, Navarro, & Phillips, 2000; Stewart & Chambless, 2009). In accordance with

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Stewart and Chambless (2009), we considered Shadish and colleagues’ (2000) additional

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criteria of heterogeneous presenting problems, unlimited use of treatment procedures, and a flexible number of sessions to be not clinically relevant. Most clinical effectiveness trials investigate a specific treatment for a particular disorder. Furthermore, treatment in everyday

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practice can be restricted in duration by insurance coverage or financial constraints. However, we regard three additional criteria also provided by Stewart and Chambless (2009) as very

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useful to distinguish effectiveness from efficacy studies: clinically representative inclusion criteria, allowance of medication, and no randomization.

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due to strict

selection criteria including adjunct psychiatric medication, and

Randomly assigning patients to treatment groups is also not feasible in clinical settings due to ethical and practical considerations. Routine practice therapists are committed to providing the best types of treatment depending on the needs of the individual patient rather than providing a standardized treatment protocol. Hence, the randomized allocation of patients is particularly unrepresentative of usual clinical practice. As randomization was the most distinctive feature between effectiveness and efficacy studies, Seligman (1995) defined efficacy studies, as opposed to effectiveness studies, as

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RCTs with strict adherence to a treatment manual and a fixed number of sessions, along with highly selected patient samples to ensure high internal validity. Considering this definition,

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we decided to define effectiveness studies as nonrandomized clinical trials representative of

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clinical representativeness of individual effectiveness studies.

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routine practice. In addition, the abovementioned criteria were used to assess the degree of

Recently, two meta-analyses of effectiveness studies have indicated the transportability of CBT for anxiety disorders to routine clinical settings. Stewart and Chambless (2009)

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included 56 studies and found that CBT was highly effective in reducing disorder-specific

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symptoms (Hedges’ g = 0.92–2.59) as well as symptoms of both general anxiety (Hedges’ g = 1.02) and depression (Hedges’ g = 0.73–1.62). However, they also included RCTs which we deemed to be unrepresentative of routine clinical practice (see above). Van Ingen and

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colleagues (2009) included only 11 effectiveness studies in their meta-analysis and report mean pre-post effect sizes of d = 1.35 for anxiety and d = 0.96 for depression; these treatment

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gains were maintained and even further improved over the 12-month follow-up. The authors report an end-of-treatment mean dropout rate of 26.8% (range = 9.0–36.0) across all anxiety

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disorders. The evaluation of dropout has high clinical relevance since high attrition rates would compromise the application of CBT in clinical practice; nevertheless, dropout from CBT for adult anxiety disorders has not been examined in any further meta-analysis of effectiveness studies to date. A limitation of both the abovementioned meta-analyses is that they did not differentiate between in- and outpatients and considered completer data only. Moreover, van Ingen et al. (2009) averaged the effect sizes across measures of disorderspecific symptoms and general anxiety as well as across various anxiety disorders. This precludes the results from serving as a benchmark for the effectiveness of CBT for single anxiety disorders in outpatient routine practice settings. Accordingly, the primary aim of this study was to evaluate the overall effectiveness of individual and group outpatient CBT for adults with a primary anxiety disorder in routine

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clinical practice.

extend beyond the work of van Ingen et al. and Stewart and

Chambless by providing a more comprehensive meta-analysis, including an additional 66 and

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46 nonrandomized effectiveness studies compared to van Ingen et al.’s and Stewart and

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Chambless’s meta-analyses, respectively. Moreover, we also report effect sizes according to

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ITT. Consideration is also given to dropout rates and variables potentially moderating the effectiveness of CBT: treatment format and treatment dose.

Identification and Selection of Studies

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Method

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As the terms efficacy and effectiveness are not only inconsistently used in the literature but are also unreliably indexed by electronic databases (Reeves, Deeks, Higgins, & Wells, 2011), we used a variety of (truncated) keywords identified from effectiveness studies and

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meta-analyses thereof (Stewart & Chambless, 2009; van Ingen et al., 2009) to locate nonrandomized clinical trials in routine clinical practice: clinic setting, community mental

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health center, dissemination, effectiveness, generalizability, generalization, mental health field, naturalistic, nonrandomized, outpatient clinic, private practice, routine practice, service

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setting, transportability, and uncontrolled. We developed a search strategy combining these keywords with subject headings relevant to various

and CBT (cf. Web

Appendix A in the supplemental materials for exact search strings). The following electronic databases were searched from their inception: MEDLINE via Ovid ( ), PsycINFO (

), and PSYNDEXplus (

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supplemented electronic searches with hand searches of reviews including nonrandomized clinical trials (Foa & Meadows, 1997; Harvey, Bryant, & Tarrier, 2003; Heimberg, 2002; Himle, van Etten, & Fischer, 2003; Jónsson & Hougaard, 2009; Margraf, Barlow, Clark, & Telch, 1993; Mitte, 2005; Rodebaugh, Holaway, & Heimberg, 2004; Ruhmland & Margraf, 2001; Sherman, 1998; Stewart & Chambless, 2009; van Ingen et al., 2009; Zaider & Heimberg, 2003) and hand searches of the reference lists of all effectiveness studies located.

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To identify other published or unpublished trials, enquiries requesting potentially relevant effectiveness studies were sent to experts in the field.

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Selection Criteria

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Effectiveness studies were considered eligible if they examined the outcome of face-to-

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face CBT for adult outpatients with a primary GAD, OCD, panic disorder and/or agoraphobia (referred to in the following as panic disorder), PTSD, social phobia, or specific phobia. CBT refers to cognitive, behavioral, or a combination of cognitive and behavioral therapy. As we

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were interested in the effects of CBT delivered in routine clinical practice and as we deemed

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randomization of patients to be unrepresentative of routine care, we excluded RCTs. We also excluded studies in which less than half of the typical number of 12 CBT sessions was offered. Finally, if authors provided insufficient quantitative data for effect size estimation,

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studies had to be excluded. We included both peer-reviewed and non-peer-reviewed studies (e.g., dissertations). No studies were excluded due to start date or language restrictions.

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Data Extraction

For each study included in the meta-analysis, we coded patient and intervention

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characteristics. To obtain some indication of the extent to which the effect sizes can be generalized and trusted, we coded and reported the clinical representativeness and methodological quality of the studies. We used a standardized coding protocol (available from the authors). Clinical representativeness was coded according to criteria adapted from Stewart and Chambless (2009) as well as Shadish et al. (2000): (a) referrals, (b) therapists, (c) structure, (d) monitoring, (e) therapist pretherapy training, (f) patients, and (g) allowance of medication. Their criteria for clinical representativeness were adapted in that the clinical representativeness items “referrals” (referred through usual clinical routes vs. some active recruiting), “structure” (flexible structure vs. strict adherence to a treatment manual), “monitoring” (no adherence monitoring other than routine supervision vs. extensive

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supervision and/or monitoring), and “training” (pretherapy training vs. no training) were dummy coded. Due to the fact that authors often do not provide sufficient information to rate

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whether a mental health care setting was university affiliated or not, we excluded Stewart and Chambless’ s criterion of a clinically representative setting (

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Web Appendix B in ). The

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the supplemental materials criterion of randomization was not used (cf. inclusion criteria).

The methodological quality of included studies was assessed according to the guidelines

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for assessing methodological quality of nonrandomized controlled studies of the Cochrane

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Consumers and Communication Review Group (CCCRG) which were modified for the present study. The original criteria of allocation concealment, blinding, and baseline comparability were not applicable to the design of pre-post studies (Ryan, Hill, Prictor, &

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McKenzie, 2011). Additional criteria were developed based on a checklist of the German Academic Advisory Council for the quality assessment of clinical trials (Wissenschaftlicher

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Beirat Psychotherapie, 2010). Following the recommendations of the CCCRG, information on individual items is provided rather than an overall numerical quality score. If information was

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not available or unclear, quality items were coded as “not available” (Ryan et al., 2011). The following resulting criteria were used: (a) low dropout rate (<30%), (b) use of ITT analysis, (c) formal diagnostic investigation, (d) minimum within-study sample size of 30, and (e) minimum follow-up length of 6 months (cf. Web Appendix C in the supplemental materials). The first author coded all the studies. The second author was trained in the use of the coding protocol and independently coded 20% of the studies. Interrater reliability for the coding of clinical representativeness and methodological quality of the studies was assessed using Cohen’s kappa score. The strength of interrater agreement on methodological quality was moderate (diagnostic procedures: κ = .63) to perfect (all other items: κ = 1.00). Interrater agreement on the criteria for clinical representativeness can be considered moderate for the item “patients” (κ = .42), substantial for the items “adherence monitoring” (κ = .76),

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“structure” (κ = .84), and “therapist training” (κ = .85), and perfect for all other items (κ = 1.00). Discrepancies in ratings were resolved by discussion until consensus was reached.

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Effect Size Calculation and Statistical Procedures

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The primary outcome was the end-of-treatment effect for disorder-specific symptom

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severity, as variously assessed by self-report and clinician-rated disorder-specific outcome measures (e.g., the Yale-Brown Obsessive Compulsive Scale [Y-BOCS; Goodman et al., 1989] for OCD) Secondary outcomes were depression (e.g., the Beck Depression Inventory

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[BDI; Beck, Ward, Mendelson, Mock, & Erbaugh, 1961]) and general anxiety (e.g., BAI;

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Beck, Epstein, Brown, & Steer, 1988). Pre- to posttreatment effects were investigated separately for both completer and ITT samples as available. Effect sizes for disorder-specific symptom severity from posttreatment to 12-month

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follow-up were based on completer samples due to a paucity of ITT data. A nonsignificant

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result would suggest that end-of-treatment gains were retained over the follow-up period.

Only one study was included on each social phobia (Aderka, Hermesh, Marom,

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Weizman, & Gilboa-Schechtman, 2011), OCD (Tolin, Maltby, Diefenbach, Hannan, & Worhunsky, 2004), PTSD (Resick & Schnicke, 1992), and panic disorder (Evans, Holt, & Oei, 1991) that used a formal nonrandomized wait-list condition of 1 to 8 months. Therefore, this meta-analysis reports on within-group effect sizes according to the procedures for calculation outlined by Lipsey and Wilson (2001). Becker’s (1988) standardized mean gain effect size statistic, using the pooled standard deviation, was calculated from means and standard deviations following the recommendations for within-group analyses (Dunlap, Cortina, Vaslow, & Burke, 1996; Maier-Riehle & Zwingmann, 2000). If insufficient information was reported, data were requested from corresponding study authors. Given the small sample sizes of some studies, introducing potential upward bias, a small sample bias correction was applied to each effect size (Hedges & Olkin, 1985).

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In considering that between-studies heterogeneity was to be expected, a random effects analysis was deemed most appropriate for pooling effect sizes. The inverse variance weighted

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overall effect size and the respective 95% confidence interval were calculated for each

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outcome across studies (Lipsey & Wilson, 2001) if sufficient data were available (five or

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more within-study samples). As the correlation between pre- and posttest scores (required for the calculation of the standard errors and inverse variance weights) is not commonly reported, we assumed a value of zero for this correlation, which leads to the most conservative (large)

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estimate of the standard error of each effect size. A z test was used to evaluate whether the overall effect sizes were significantly different from zero. Effect sizes were pooled using

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Lipsey and Wilson’s (2001) SPSS mean effect size macro. According to Cohen’s (1988, p. 40) hypothetical rule of thumb, effect sizes of 0.2, 0.5, and 0.8 were considered small,

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moderate, and large, respectively. Lipsey’s (1990, p. 56) empirically based rule of thumb compares with Cohen’s guideline, with effect sizes of less or equal to 0.32 being considered

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small, 0.33 to 0.55 moderate, and 0.56 to 1.2 large. Subsample effect sizes were calculated if results were reported separately for different

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primary diagnoses (Joormann, Kosfelder, & Schulte, 2005) and treatment formats (Norberg, Calamari, Cohen, & Riemann, 2008) as these can be considered statistically independent (Lipsey & Wilson, 2001) and also because we were interested in differences between diagnoses and treatment formats. In order to reduce the risk of artificial reduction of heterogeneity, we included one weighted mean effect size per study if results were reported separately for nonoverlapping (e.g., diagnostic) subsamples (Aigner et al., 2004; Friedman, Braunstein, & Halpern, 2006; Friedman et al., 2003; García-Palacios et al., 2002; Hunt & Andrews, 1998; Joormann et al., 2005; Marom, Gilboa-Schechtman, Aderka, Weizman, & Hermesh, 2009; Martín et al., 2009; Niedermeier, Pfeiffer-Gerschel, Manzinger, Mangold, & Althaus, 2007; Ruipérez, García-Palacios, & Botella, 2002; Storch et al., 2008; van Minnen & Foa, 2006; van Velzen, Emmelkamp, & Scholing, 1997). Similarly, in case of multiple

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outcome measures, effect sizes were averaged to yield one effect size per outcome for each within-study sample. One outlier study (Nakano et al., 2008) reporting an effect size that was

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more than three SDs above the mean effect size for disorder-specific symptom severity was

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removed from the meta-analysis (Lipsey & Wilson, 2001).

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Homogeneity Analysis

Heterogeneity was assessed using the Q test (Hedges & Olkin, 1985) for evidence of statistically significant heterogeneity. This statistical test has low power given small numbers

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of studies with small samples (Hardy & Thompson, 1998). Therefore, we additionally

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computed the test statistic I2 (Higgins, Thompson, Deeks, & Altman, 2003) to quantify the amount of heterogeneity. It gives values ranging between 0% and 100%, with larger values indicating greater heterogeneity. According to Higgins and Thompson’s (2003) rule of thumb,

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an I2 of 25%, 50%, and 75% is considered small, moderate, and large, respectively. Dropout

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Most studies defined completion as the termination of treatment in accordance with therapist advice or as attendance at a predefined minimum number of sessions. Hence, we

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defined dropout as the proportion of patients who have attended at least one but fewer than the number of sessions necessary to complete treatment. For the purpose of meta-analysis of dropout from CBT, we followed the procedures described by Lipsey and Wilson (2001) to compute logit transformed effect sizes for proportions. Lipsey and Wilson’s SPSS mean effect size macro was used for pooling effect sizes, using random effects analysis. The inverse variance weighted mean logit effect size for proportions and its corresponding confidence interval were back-transformed into proportions to ease interpretation. Moderator Analyses To investigate statistical heterogeneity, a priori specified subgroup and meta-regression analyses were performed. We used mixed effects analogs to the analysis of variance (ANOVA) followed by pairwise multiple comparisons at the .05 level, if needed, to compare

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the CBT outcome and dropout posttreatment between anxiety disorders and treatment formats across studies. Mixed effects weighted meta-regression was used to investigate whether

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treatment dose was related to CBT outcome with regard to disorder-specific symptom severity

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(Higgins & Thompson, 2004; Thompson & Higgins, 2002). In order to have a sufficient

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amount of data, completer data were used. Analogs to the ANOVA and meta-regression analyses were performed using Lipsey and Wilson’s (2001) analog to the ANOVA and maximum likelihood meta-regression SPSS macro, respectively.

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Power Calculations

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Analogs to the ANOVA tend to have low statistical power under the mixed effects model. To determine whether we had sufficient power to detect small (0.32), medium (0.55), and large (1.2) moderator effect sizes (Lipsey, 1990, p. 56), we conducted retrospective power

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analyses according to Hedges and Pigott (2004) using the effect size estimates specified above and the observed (mixed model) within-group variances for each group.

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Assessment of Reporting Biases

To identify potential small-study effects, funnel plots were visually inspected for

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evidence of asymmetry. In the absence of bias, the scatterplot of effect size against precision (inverse of standard error) should look like a symmetrical inverted funnel. Egger’s linear regression method (Egger, Davey Smith, Schneider, & Minder, 1997; Sterne & Egger, 2006) was used to statistically test for funnel plot asymmetry. A significant deviation of the intercept of the (unweighted) regression of standard normal deviates on their precision from zero indicates the presence of bias. Additionally, Orwin’s (1983) Fail-safe N, the number of studies with null effect that would need to exist in order to reduce the significant overall effect size to 0.40, was determined. We chose this criterion effect size based on a wait-list effect size reported in a previous meta-analysis on CBT for adult anxiety disorders (Stewart & Chambless, 2009). This moderate criterion effect size yields a conservative estimate of the Fail-safe N.

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Results Characteristics of Included Studies

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Forty-five effectiveness studies were retrieved from the electronic databases MEDLINE,

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PsycINFO, and PSYNDEXplus. Twenty-six additional studies were located through hand

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searching of reference lists of the included articles and review articles or were identified by experts. A flow diagram is provided to describe the inclusion process (see Web Figure 1 in the supplemental materials). A total of 71 studies (excluding one outlier study) on OCD (n = 28),

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social phobia (n = 15), panic disorder (n = 20), and PTSD (n = 9) were included in the meta-

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analysis. One effectiveness study (Joormann et al., 2005) provided separate data for social phobia and panic disorder patients and was therefore counted twice. No studies on specific phobia and on GAD met our inclusion criteria. Included studies are indicated by an asterisk in

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Sample Description

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the reference section.

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Effect sizes of CBT for reducing disorder-specific anxiety were derived from all 71 studies and included a total of 3,625 patients who completed (k = 65) and 1,793 patients (k =

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28) who were intended to be treated with CBT (Web Tables 1 & 2 in the supplemental materials). The majority of the completer (weighted M = 60.6%, SD = 15.8) and the ITT samples (weighted M = 55.3%, SD = 14.1) were women, with a weighted mean age of 34.8 years (SD = 3.1 and SD = 3.6, respectively). If reported, comorbidity of Axis I (weighted M = 43.7%, SD = 26.7 and weighted M = 52.4%, SD = 20.0) and Axis II disorders (weighted M = 18.3%, SD = 18.5 and weighted M = 6.3%, SD = 9.2) was common among completer and ITT samples. The majority of completers used psychiatric medication (weighted M = 52.1%, SD = 24.2) and more than one out of three patients who was intended to be treated was medicated (weighted M = 43.4%, SD = 22.5). Treatment

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Completers were provided an average number of 23.9 individual (Min = 12.0, Max = 48.0, SD = 10.1) or 17.4 group therapy sessions (Min = 8.0, Max = 45.0, SD = 8.2). In three

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studies, patients received individual CBT, group CBT, or a combination of both (Leveni,

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Piacentini, & Campana, 2002; Starcevic, Linden, Uhlenhuth, Kolar, & Latas, 2004; Wade,

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Treat, & Stuart, 1998). In studies reporting ITT analyses, patients received an average of 23.2 (Min = 8.0, Max = 48.0, SD = 12.0) individual or 18.1 (Min = 10.0, Max = 45.0, SD = 10.0) group therapy sessions. Two studies offered individual sessions, group sessions, or a

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combination of both (Leveni et al., 2002; Starcevic et al., 2004). Individual and group

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sessions typically lasted 45 to 60 and 90 to 120 min, respectively. To ensure comparability, we converted treatment dose into standard 45- and 90-min individual and group CBT sessions, respectively, in case total hours of CBT or an extended length of sessions was

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reported.

Clinical Representativeness of Included Studies

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Most studies indicated that their patients had been referred through usual clinical routes (84.8%) rather than being additionally or exclusively solicited for participation. In almost all

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studies (82.6%), common exclusion criteria for admission to routine outpatient treatment were applied. Treatment was exclusively provided by practicing therapists and/or therapists in training (100.0%) of whom the majority (71.0%) were not specifically trained for study purposes. In almost all studies evaluating the effectiveness of individual therapy (87.9%), treatment manuals were flexibly used, whereas in the majority of group therapy studies treatments were strictly manualized (72.2%). Most studies did not formally assess therapist adherence (75.0%). In some studies, however, treatment was monitored through extensive supervision and/or formal adherence checks (25.0%). In almost all studies (98.6%), patients were allowed to use psychiatric medication. Methodological Quality of Included Studies

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Structured or semistructured validated diagnostic interviews or a diagnostic checklist were administered in 49 out of 65 studies with available data on this item. In the remaining

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studies, no diagnostic interview was specified or diagnoses were based on clinical judgment.

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Effect sizes of 43 studies (60.6%) were derived from sample sizes greater than or equal to 30.

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Dropout data could only be extracted from 51 studies (69.9%), almost all of which (92.2%) reported low dropout rates (<30%). More than a third of studies (36.6%) provided results based on ITT analyses. In 24 out of 71 studies (33.8%), patients were followed up for 6

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months or more posttreatment; however, in two of the studies (Aderka et al., 2011;

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Niedermeier et al., 2007), data were too incomplete for the estimation of post-follow-up effect sizes (Web Tables 1 & 2 in the supplemental materials). End-of-Treatment Improvement in Primary and Secondary Outcomes

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Single pre-post effect sizes are presented rather than a mean effect size if there were a small number of studies. Completer effect sizes for symptoms of OCD, panic disorder, PTSD,

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and social phobia were large (d = 0.90–1.91; Table 1 & Web Figures 2 to 5 in the supplemental materials) and ITT effect sizes for symptom severity in OCD, panic disorder,

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and social phobia were moderate to large (d = 0.67–1.45; Table 2 & Web Figures 6 to 8 in the supplemental materials). The completer sample showed moderate to large effect sizes for depression (d = 0.66–1.09) and small to large effect sizes for general anxiety (d = 0.42–0.97). While there is a paucity of ITT data for general anxiety symptoms (panic disorder: d = 0.94), moderate to large pre-post effect sizes were found for depressive symptoms (d = 0.54–0.96). All effect sizes reached statistical significance (Tables 1 & 2). Please insert Tables 1 & 2 about here Overall, seven studies on CBT for panic disorder (n = 4), social phobia (n = 1), OCD (n = 1), and PTSD (n = 1) reported a zero dropout rate. If dropout from treatment was present, the weighted mean dropout rate across all anxiety disorders was 15.06%, including 17.52% (95% CI [13.52, 22.38], k = 10) with panic disorder, 15.31% (95% CI [10.58, 21.64], k = 10)

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with social phobia, 11.73% (95% CI [9.22, 14.82], k = 20) with OCD, and 27.68% (95% CI [16.57, 42.45], k = 5) with PTSD.

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Maintenance of Treatment Gains

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Effect sizes for disorder-specific symptom severity from posttreatment to follow-up are d = 0.10, 95% CI

d = 0.20, 95% CI [-0.01, 0.40], k = 5

d = 0.09,

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reported [-0.03, 0.23], k = 9 95% CI [-0.11, 0.28], k = 6

after the completion of CBT, as indicated by the

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nonsignificant post-follow-up effect sizes, with a trend towards further improvement in

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disorder-specific anxiety. Results of the one PTSD study with available follow-up data indicated that PTSD symptom severity was reduced over 12 months after the completion of CBT (d = 1.22, 95% CI [0.81, 1.63]; Echeburúa, de Corral, Sarasua, & Zubizarreta, 1996).

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Completer effect sizes for disorder-specific symptom severity significantly differed

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between disorders (QB[3] = 32.85, p < .001). Pairwise multiple comparisons indicated that reductions in symptom severity of PTSD and OCD were larger than those of both panic

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disorder and social phobia and that there was no large effect (1−β = 0.82) for the difference between reductions in panic disorder and social phobia symptom severity. All other differences between treatment outcomes across anxiety disorders fell short of significance; however, the power to detect any large effects was inadequate (1−β = 0.22−0.33). At completion of CBT, individual CBT was more effective than group CBT for OCD symptoms (d = 1.87, 95% CI [1.49, 2.25], k = 12 vs. d = 1.09, 95% CI [0.73, 1.44] k = 11; QB[1] = 8.59, p < .01) and PTSD symptoms (d = 2.34, 95% CI [1.92, 2.77], k = 5 vs. d = 1.38, 95% CI [0.95, 1.81], k = 3; QB[1] = 9.76, p < .01). However, differences between individual CBT (panic disorder: d = 1.02, 95% CI [0.72, 1.31], k = 8; social phobia: d = 0.93, 95% CI [0.73, 1.14], k = 3) and group CBT (panic disorder: d = 0.83, 95% CI [0.58, 1.09], k = 9; social phobia: d = 0.91, 95% CI [0.78, 1.04], k = 11) in reducing disorder-specific anxiety fell

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short of significance for panic disorder (QB[1] = 0.81, p = .37) and social phobia (QB[1] = 0.04, p = .84). The statistically nonsignificant results should be regarded as inconclusive as

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post hoc power calculations indicated that the statistical power was insufficient to detect large

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CBT effects on panic disorder (1−β = 0.53) and to detect moderate effects on social phobia

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symptoms (1−β = 0.49).

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Treatment dose significantly predicted CBT effects on disorder-specific anxiety, 

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The number of sessions did not differ between panic disorder (M = 17.52, SD = 6.53), social phobia (M = 21.21, SD = 9.86), OCD (M =

(QB[3] = 10.57, p < .05)

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22.25, SD = 11.44), and PTSD (M = 20.02, SD = 9.23), F(3, 55) = 0.80, p = .50

1−β =

–

Individual CBT was associated with a larger dropout than

group CBT for panic disorder (p < .05), but differences between dropout rates in individual and in group CBT for OCD (p = .46), social phobia (p = .56), and PTSD (p = .17) fell short of significance. Again, the power to detect a large effect size for the three latter comparisons was only .27, .21, and .19, respectively. Assessment of Reporting Bias Based on visual inspection, there was no evidence of

for

completer effect sizes except for OCD symptom severity. This corresponds with a nonsignificant Egger’s test for panic disorder (intercept -0.94, 95% CI [-2.79, 0.90], t = -1.08, two-tailed p = .30), social phobia (intercept 0.93, 95% CI [-0.09, 1.95], t = 1.98, two-tailed p

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= .07), and PTSD symptom severity (intercept 1.78, 95% CI [-2.76, 6.32], t = 0.96, two-tailed p = .37) and a significant Egger’s test for OCD symptom severity (intercept 2.48, 95% CI

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[0.03, 4.93], t = 2.10, two-tailed p < .05) suggesting there may be a small-study bias. For ITT

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effect sizes, the Egger’s test was not significant for panic disorder (intercept 1.36, 95% CI [-

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1.79, 4.51], t = 1.20, two-tailed p = .30), social phobia (intercept 0.99, 95% CI [-0.62, 2.59], t = 1.46, two-tailed p = .19), and OCD (intercept -4.03, 95% CI [-8.25, 0.19], t = -2.26, twotailed p = .06). Thus, while results

f a positively biased completer

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effect size with regard to OCD symptoms, results suggest that the remaining mean effect sizes are not overestimated.

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According to Orwin’s (1983) Fail-safe N, 50, 29, 28, and 17 unpublished studies with nonsignificant findings would be necessary in order to reduce the mean completer effect sizes

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for OCD, panic disorder, PTSD, and social phobia symptoms, respectively, to the criterion effect size of 0.40. For the mean ITT effect sizes for OCD, panic disorder, and social phobia

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symptoms, the Fail-safe Ns were 27, 5, and 5, respectively. Hence, given the small number of effectiveness studies identified, the relatively large Fail-safe Ns suggest effect sizes were

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robust against the file drawer problem. Discussion

general depression and anxiety symptoms.

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Given that 64% of studies only used completer data, it is important to note that attrition

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from CBT across all anxiety disorders (15.1%) was moderate in routine clinical practice. This

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dropout rate compares favorably with those previously found in effectiveness studies of adult psychotherapy as a whole (16.2%; Swift & Greenberg, 2012) and, more specifically, CBT for anxiety disorders (26.8%; van Ingen et al., 2009). One reason for the higher dropout rate

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found in the latter meta-analysis may arise from the limited number of studies included. The moderate dropout rate found in the present meta-analysis supports the validity of our results.

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Moreover, based on the available evidence, ITT effect sizes were only marginally smaller than completer effect sizes, suggesting that bias caused by attrition was small.

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Our results are also consistent with previous meta-analyses of RCTs which suggested that the largest effect sizes can be achieved for the treatment of OCD and PTSD whereas effect sizes for panic disorder and social phobia tend to be smaller (Hofmann & Smits, 2008; Norton & Price, 2007). Thus, it might be that CBT is more effective for OCD and PTSD compared to other anxiety disorders. This result was surprising, as OCD and PTSD patients are often viewed as a significant challenge to treat, especially in comparison to other anxiety disorders such as panic disorder. However, it is known from a previous study on depression that greater pretreatment severity of symptoms might predict greater effects of psychological treatments (Driessen, Cuijpers, Hollon, & Dekker, 2010). That is, posttreatment effects of CBT may be more pronounced in patients showing more severe disorder-specific symptoms at pretreatment as it might have been the case for OCD and PTSD. Moreover, centers and

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therapists providing treatment for OCD and PTSD are often

and therefore

maybe more effective than others. However, there are other possible explanations that we

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need to take into account.

relative sensitivity to change of various disorder-

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specific outcome measures because outcome measures that are more sensitive to treatment

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changes are able to detect smaller treatment effects.

Both individual and group CBT resulted in a reduction of disorder-specific symptoms. Comparisons across studies showed that individual CBT was more effective than group CBT

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in improving OCD and PTSD while there was only a trend in favor of individual CBT for

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panic disorder and no difference between treatment formats for social phobia.

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is that

dose-response relationship between the number of sessions

delivered and the CBT effect on disorder-specific symptoms. Despite low statistical power, it seems that individual and group CBT were equally effective in improving social phobia although, again, more sessions were delivered in individual than group treatment settings. Group CBT may work particularly well for social phobia compared to other anxiety disorder patients because group therapy may help social phobic patients to build social skills and reduce avoidance of social situations. Unfortunately, direct comparisons between individual and group therapy were not possible due to a lack of such studies. There are some limitations of the present meta-analysis with regard to confounding and bias that need to be addressed. First, results are based on within-group effect sizes. We

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therefore cannot rule out

variables such as the passage of time, social

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demand effects, or regression to the mean

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The present meta-analysis was

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d = 0.14, 95% CI [0.01, 0.27], k = 6

.

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methodological shortcomings inherent in the included effectiveness studies should be mentioned. Almost 30% of studies failed to report dropout rates even though this would have been especially important because findings were most commonly restricted to CBT completers (64%). Similarly, little evidence of the long-term effectiveness of CBT for anxiety disorders is provided for PTSD. These methodological weaknesses highlight the need for applying to effectiveness studies the modified CCCRG quality criteria (Ryan et al., 2011) and the TREND reporting standards (Des Jarlais, Lyles, & Crepaz, 2004) we have previously outlined. First,

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it is essential that authors exactly describe the extent of dropout to help because

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interpret effect sizes

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Fourth, findings need to be complemented with ITT analyses.

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, as has now become standard practice in efficacy studies. Finally, for ease of identification of nonrandomized effectiveness studies, we recommend that

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investigators clearly describe their reports as such, e.g., by using the term “effectiveness” in their title or abstract.

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We propose that future effectiveness studies are conducted as nonrandomized trials representative of routine practice. In real-world clinical settings, it is current practice that less stringent eligibility criteria are applied and that therapists are neither trained nor supervised in delivering treatment. For the results to be applicable to routine practice, patients should be self-referred or referred through usual clinical routes (e.g., by general practioners). If patients meet the criteria for the disorder under study, no exclusion criteria besides acute suicidaliy, acute psychosis, organic brain disease, substance dependence, or disorders potentially interfering with treatment engagement should be applied. Treatment should be conducted by licensed therapists or therapists in training not receiving specific training or extensive supervision for the purposes of the study. If any, treatment manuals should be flexibly used and no formal adherence checks should be done.

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To our knowledge, this is the most comprehensive meta-analysis of nonrandomized effectiveness studies on outpatient CBT for adult anxiety disorders. Despite methodological

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limitations inherent in the design of effectiveness studies, we have demonstrated that both

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outpatient individual and group CBT for anxiety disorders are effective in routine practice

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settings. Both the methodological and reporting quality of effectiveness studies must be

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improved.

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References marked with an asterisk indicate studies included in the meta-analysis.

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 Outpatient CBT is effective for adult anxiety disorders in clinical practice settings.

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 Posttreatment gains were maintained 3 and 12 months after completion of therapy.  Dropout from treatment is moderate.

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 There is a need for high-quality effectiveness studies.