Researcher allegiance in psychotherapy outcome research: an overview of reviews

Researcher allegiance (RA) is widely discussed as a risk of bias in psychotherapy outcome research. The relevance attached to RA bias is related to meta-analyses demonstrating an association of RA with treatment effects. However, recent meta-analyses have yielded mixed results. To provide more clarity on the magnitude and robustness of the RA-outcome association this article reports on a meta-meta-analysis summarizing all available meta-analytic estimates of the RA-outcome association. Random-effects methods were used. Primary study overlap was controlled. Thirty meta-analyses were included. The mean RA-outcome association was r=.262 (p=.002, I(2)=28.98%), corresponding to a moderate effect size. The RA-outcome association was robust across several moderating variables including characteristics of treatment, population, and the type of RA assessment. Allegiance towards the RA bias hypothesis moderated the RA-outcome association. The findings of this meta-meta-analysis suggest that the RA-outcome association is substantial and robust. Implications for psychotherapy outcome research are discussed.

Crossing borders: Ethnic minorities matter? A meta analytic examionation of the alliance-outcome relationship

Objectives: The purpose of this meta analysis was to examine the moderating impact of substance use disorder as inclusion/exclusion criterion as well as the percentage of racial/ethnic minorities on the strength of the alliance-outcome relationship in psychotherapy. It was hypothesized that the presence of a dsm axis i substance use disorders as a criterion and the presence of racial/ethnic minority as a psychosocial indicator are confounded client factors reducing the relationship between alliance and outcome. Methods: A random effects restricted maximum-likelihood estimator was used for omnibus and moderator models (k = 94). results: the presence of (a) substance use disorder and, (b) racial/ethnic minorities (overall and specific to african americans) partially moderated the alliance-outcome correlation. The percentage of substance use disorders and racial/ethnic minority status was highly correlated. Conclusions: Socio-cultural contextual variables should be considered along with dsm axis i diagnosis of substance use disorders in analyzing and interpreting mechanisms of change.

Chow–Liu trees are sufficient predictive models for reproducing key features of functional networks of periictal EEG time-series

Seizure freedom in patients suffering from pharmacoresistant epilepsies is still not achieved in 20–30% of all cases. Hence, current therapies need to be improved, based on a more complete understanding of ictogenesis. In this respect, the analysis of functional networks derived from intracranial electroencephalographic (iEEG) data has recently become a standard tool. Functional networks however are purely descriptive models and thus are conceptually unable to predict fundamental features of iEEG time-series, e.g., in the context of therapeutical brain stimulation. In this paper we present some first steps towards overcoming the limitations of functional network analysis, by showing that its results are implied by a simple predictive model of time-sliced iEEG time-series. More specifically, we learn distinct graphical models (so called Chow–Liu (CL) trees) as models for the spatial dependencies between iEEG signals. Bayesian inference is then applied to the CL trees, allowing for an analytic derivation/prediction of functional networks, based on thresholding of the absolute value Pearson correlation coefficient (CC) matrix. Using various measures, the thus obtained networks are then compared to those which were derived in the classical way from the empirical CC-matrix. In the high threshold limit we find (a) an excellent agreement between the two networks and (b) key features of periictal networks as they have previously been reported in the literature. Apart from functional networks, both matrices are also compared element-wise, showing that the CL approach leads to a sparse representation, by setting small correlations to values close to zero while preserving the larger ones. Overall, this paper shows the validity of CL-trees as simple, spatially predictive models for periictal iEEG data. Moreover, we suggest straightforward generalizations of the CL-approach for modeling also the temporal features of iEEG signals.

Amygdala response to self-critical stimuli and symptom improvement in psychotherapy for depression

Background: Cognitive–behavioural therapy is efficacious in the treatment of major depressive disorder but response rates are still far from satisfactory. Aims: To better understand brain responses to individualised emotional stimuli and their association with outcome, to enhance treatment. Method: Functional magnetic resonance imaging data were collected prior to individual psychotherapy. Differences in brain activity during passive viewing of individualised self-critical material in 23 unmedicated out-patients with depression and 28 healthy controls were assessed. The associations between brain activity, cognitive and emotional change, and outcome were analysed in 21 patients. Results: Patients showed enhanced activity in the amygdala and ventral striatum compared with the control group. Non-response to therapy was associated with enhanced activity in the right amygdala compared with those who responded, and activity in this region was negatively associated with outcome. Emotional but not cognitive changes mediated this association. Conclusions: Amygdala hyperactivity may lessen symptom improvement in psychotherapy for depression through attenuating emotional skill acquisition.

Prefrontal Thinning Affects Functional Connectivity and Regional Homogeneity of the Anterior Cingulate Cortex in Depression

Major depressive disorder (MDD) is associated with structural and functional alterations in the prefrontal cortex (PFC) and anterior cingulate cortex (ACC). Enhanced ACC activity at rest (measured using various imaging methodologies) is found in treatment-responsive patients and is hypothesized to bolster treatment response by fostering adaptive rumination. However, whether structural changes influence functional coupling between fronto-cingulate regions and ACC regional homogeneity (ReHo) and whether these functional changes are related to levels of adaptive rumination and treatment response is still unclear. Cortical thickness and ReHo maps were calculated in 21 unmedicated depressed patients and 35 healthy controls. Regions with reduced cortical thickness defined the seeds for the subsequent functional connectivity (FC) analyses. Patients completed the Response Style Questionnaire, which provided a measure of adaptive rumination associated with better response to psychotherapy. Compared with controls, depressed patients showed thinning of the right anterior PFC, increased prefrontal connectivity with the supragenual ACC (suACC), and higher ReHo in the suACC. The suACC clusters of increased ReHo and FC spatially overlapped. In depressed patients, suACC ReHo scores positively correlated with PFC thickness and with FC strength. Moreover, stronger fronto-cingulate connectivity was related to higher levels of adaptive rumination. Greater suACC ReHo and connectivity with the right anterior PFC seem to foster adaptive forms of self-referential processing associated with better response to psychotherapy, whereas prefrontal thinning impairs the ability of depressed patients to engage the suACC during a major depressive episode. Bolstering the function of the suACC may represent a potential target for treatment.