A Comparison of Rational Versus Empirical Methods in the Prediction of Psychotherapy Outcome

Several systems have been designed to monitor psychotherapy outcome, in which feedback is generated based on how a client\u27s rate of progress compares to an expected level of progress. Clients who progress at a much lesser rate than the average client are referred to as signal-alarm cases. Recent studies have shown that providing feedback to therapists based on comparing their clients\u27 progress to a set of rational, clinically derived algorithms has enhanced outcomes for clients predicted to show poor treatment outcomes. Should another method of predicting psychotherapy outcome emerge as more accurate than the rational method, this method would likely be more useful than the rational method in enhancing psychotherapy outcomes. The present study compared the rational algorithms to those generated by an empirical prediction method generated through hierarchical linear modeling. The sample consisted of299 clients seen at a university counseling center and a psychology training clinic. The empirical method was significantly more accurate in predicting outcome than was the rational method. Clients predicted to show poor treatment outcome by the empirical method showed, on average, very little positive change. There was no difference between the methods in the ability to accurately forecast reliable worsening during treatment. The rational method resulted in a high percentage of false alarms, that is, clients who were predicted to show poor treatment response but in fact showed a positive treatment outcome. The empirical method generated significantly fewer false alarms than did the rational method. The empirical method was generally accurate in its predictions of treatment success, whereas the rational method was somewhat less accurate in predicting positive outcomes. Suggestions for future research in psychotherapy quality management are discussed

Inappropriate data and measures lead to questionable conclusions

Letter to the EditorGlen I. Spielmans, Jon Jureidini, David Healy, Robert Pursse

Adjunctive Atypical Antipsychotic Treatment for Major Depressive Disorder: A Meta-Analysis of Depression, Quality of Life, and Safety Outcomes

Background: Atypical antipsychotic medications are widely prescribed for the adjunctive treatment of depression, yet their total risk–benefit profile is not well understood. We thus conducted a systematic review of the efficacy and safety profiles of atypical antipsychotic medications used for the adjunctive treatment of depression. Methods and Findings: We included randomized trials comparing adjunctive antipsychotic medication to placebo for treatment-resistant depression in adults. Our literature search (conducted in December 2011 and updated on December 14, 2012) identified 14 short-term trials of aripiprazole, olanzapine/fluoxetine combination (OFC), quetiapine, and risperidone. When possible, we supplemented published literature with data from manufacturers' clinical trial registries and US Food and Drug Administration New Drug Applications. Study duration ranged from 4 to 12 wk. All four drugs had statistically significant effects on remission, as follows: aripiprazole (odds ratio [OR], 2.01; 95% CI, 1.48–2.73), OFC (OR, 1.42; 95% CI, 1.01–2.0), quetiapine (OR, 1.79; 95% CI, 1.33–2.42), and risperidone (OR, 2.37; 95% CI, 1.31–4.30). The number needed to treat (NNT) was 19 for OFC and nine for each other drug. All drugs with the exception of OFC also had statistically significant effects on response rates, as follows: aripiprazole (OR, 2.07; 95% CI, 1.58–2.72; NNT, 7), OFC (OR, 1.30, 95% CI, 0.87–1.93), quetiapine (OR, 1.53, 95% CI, 1.17–2.0; NNT, 10), and risperidone (OR, 1.83, 95% CI, 1.16–2.88; NNT, 8). All four drugs showed statistically significant effects on clinician-rated depression severity measures (Hedges' g ranged from 0.26 to 0.48; mean difference of 2.69 points on the Montgomery–Asberg Depression Rating Scale across drugs). On measures of functioning and quality of life, these medications produced either no benefit or a very small benefit, except for risperidone, which had a small-to-moderate effect on quality of life (g = 0.49). Treatment was linked to several adverse events, including akathisia (aripiprazole), sedation (quetiapine, OFC, and aripiprazole), abnormal metabolic laboratory results (quetiapine and OFC), and weight gain (all four drugs, especially OFC). Shortcomings in study design and data reporting, as well as use of post hoc analyses, may have inflated the apparent benefits of treatment and reduced the apparent incidence of adverse events. Conclusions: Atypical antipsychotic medications for the adjunctive treatment of depression are efficacious in reducing observer-rated depressive symptoms, but clinicians should interpret these findings cautiously in light of (1) the small-to-moderate-sized benefits, (2) the lack of benefit with regards to quality of life or functional impairment, and (3) the abundant evidence of potential treatment-related harm

BRIDGE study warrants critique

David M. Allen, Peter I. Parry, Robert Purssey, Glen I. Spielmans, Jon Jureidini, Nicholas Z. Rosenlicht, David Healy, Irwin Feinber

Aripiprazole in the Maintenance Treatment of Bipolar Disorder: A Critical Review of the Evidence and Its Dissemination into the Scientific Literature

A systematic search of the literature reveals limited evidence to support use of aripiprazole, a second-generation antipsychotic medication, in maintenance therapy of bipolar disorder, despite widespread use

Moderators in psychotherapy meta-analysis

Psychotherapy meta-analyses sometimes generate heterogeneous results, partially due to key methodological characteristics which vary between studies (e.g., psychotherapy conditions are contrasted with structurally different control conditions). Examining these potential moderator variables can help explain heterogeneous results within and between psychotherapy meta-analyses. The present manuscript provides an overview of moderators that are highly relevant to test the generalizability of effects across psychotherapy trials. These moderators mainly fall into one of the following groups: (a) structural equivalence of interventions, (b) preferences/allegiances, (c) therapist effects, and (d) sample representativeness. Individual moderators include: Bona fide psychotherapy, proximity to psychological interventions, psychotherapy orientation, pre-training of therapists, supervision, caseload of therapists, dosage, homework, patient preferences, researcher and therapist allegiance, therapist effects in nested designs, aspects of sample representativeness, multiple outcomes, and time of assessment. Our analysis of 15 psychotherapy meta-analyses published in 2016 suggests that the structural equivalence of psychotherapeutic conditions, patient and therapist preferences/allegiances, therapist effects and nested data structures as well as sample representativeness were often neglected and little-discussed as potential moderators. The manuscript describes further conceptual and methodological challenges when conducting moderator analyses such as the categorization of psychological treatments and the importance of interrater coding. We encourage meta-analysts to consider moderators which have previously shown utility in explaining heterogeneous results in the psychotherapy literature. Clinical or methodological significance of this article: Relevant moderator variables help explain heterogeneous results in psychotherapy meta-analyses. Though these variables are often overlooked, they should be regularly incorporated in meta-analyses