Network meta-analysis is an extension of standard meta-analysis. It allows researchers to build a network of evidence to compare multiple interventions that may have not been compared directly in existing publications. With a Bayesian approach, network meta-analysis can be used to obtain a posterior probability distribution of all the relative treatment effects, which allows for the estimation of relative treatment effects to quantify the uncertainty of parameter estimates, and to rank all the treatments in the network. Ranking treatments using both direct and indirect evidence can provide guidance to policy makers and clinicians for making decisions. The purpose of this paper is to introduce fundamental concepts of Bayesian network meta-analysis (BNMA) to researchers in psychology and social sciences. We discuss several essential concepts of BNMA, including the assumptions of homogeneity and consistency, the fixed and random effects models, prior specification, and model fit evaluation strategies, while pointing out some issues and areas where researchers should use caution in the application of BNMA. Additionally, using an automated R package, we provide a step-by-step demonstration on how to conduct and report the findings of BNMA with a real dataset of psychological interventions extracted from PubMed.

Background: In response to the COVID-19 pandemic, experts in mental health science emphasized the importance of developing and evaluating approaches to support and maintain the mental health of older adults. Objective: The aim of this study was to assess whether a group-based exercise program relative to a personal exercise program (both delivered online) and waitlist control (WLC) can improve the psychological health of previously low active older adults during the early stages of the COVID-19 pandemic. Methods: The Seniors COVID-19 Pandemic and Exercise (SCOPE) trial was a 3-arm, parallel randomized controlled trial conducted between May and September 2020 in which low active older adults (aged ≥65 years) were recruited via media outlets and social media. After baseline assessments, consented participants were randomized to one of two 12-week exercise programs (delivered online by older adult instructors) or a WLC condition. A total of 241 older adults (n=187 women) provided baseline measures (via online questionnaires), were randomized (ngroup=80, npersonal=82, ncontrol=79), and completed measures every 2 weeks for the duration of the trial. The trial’s primary outcome was psychological flourishing. Secondary outcomes included global measures of mental and physical health, life satisfaction, and depression symptoms. Results: The results of latent growth modeling revealed no intervention effects for flourishing, life satisfaction, or depression symptoms (P>.05 for all). Participants in the group condition displayed improved mental health relative to WLC participants over the first 10 weeks (effect size [ES]=0.288-0.601), and although the week 12 effect (ES=0.375) was in the same direction the difference was not statistically significant (P=.089). Participants in the personal condition displayed improved mental health, when compared with WLC participants, in the same medium ES range (ES=0.293-0.565) over the first 8 weeks, and while the effects were of a similar magnitude at weeks 10 (ES=0.455, P=.069) and 12 (ES=0.258, P=.353), they were not statistically significant. In addition, participants in the group condition displayed improvements in physical health when compared with the WLC (ES=0.079-0.496) across all 12 weeks of the study following baseline. No differences were observed between the personal exercise condition and WLC for physical health (slope P=.271). Conclusions: There were no intervention effects for the trial’s primary outcome (ie, psychological flourishing). It is possible that the high levels of psychological flourishing at baseline may have limited the extent to which those indicators could continue to improve further through intervention (ie, potential ceiling effects). However, the intervention effects for mental and physical health point to the potential capacity of low-cost and scalable at-home programs to support the mental and physical health of previously inactive adults in the COVID-19 pandemic. Trial Registration: ClinicalTrials.gov NCT04412343; https://clinicaltrials.gov/ct2/show/NCT04412343

Recent years have witnessed some rapid and tremendous progress in natural language processing (NLP) techniques that are used to analyse text data. This study endeavours to offer an up‐to‐date review of NLP applications by examining their use in counselling and psychotherapy from 1990 to 2021. The purpose of this scoping review is to identify trends, advancements, challenges and limitations of these applications. Among the 41 papers included in this review, 4 primary study purposes were identified: (1) developing automated coding; (2) predicting outcomes; (3) monitoring counselling sessions; and (4) investigating language patterns. Our findings showed a growing trend in the number of papers utilizing advanced machine learning methods, particularly neural networks. Unfortunately, only a third of the articles addressed the issues of bias and generalizability. Our findings provided a timely systematic update, shedding light on concerns related to bias, generalizability and validity in the context of NLP applications in counselling and psychotherapy.

To examine the psychological mediators of exercise adherence among older adults in a group-based physical activity randomized controlled trial. Older adults (≥65 years) were randomized to one of three conditions as part of the "GrOup-based physical Activity for oLder adults" (GOAL) randomized controlled trial. These included similar age same gender (SASG) and similar age mixed gender (SAMG) exercise programs that were informed by the tenets of self-categorization theory, and a "standard" mixed age mixed gender (MAMG) exercise program. Participants represented a subgroup (n = 483, Mage = 71.41 years) from the larger trial (n = 627) who completed measures of the trial's putative psychological mediators (i.e., group cohesion and affective attitudes) over the course of the 24-week exercise programs. Piecewise latent growth modeling revealed different trajectories between participants in the two intervention conditions (SASG, SAMG) when compared with the comparison MAMG condition with regard to perceptions of group cohesion and affective attitudes. Results of subsequent cross-lagged panel modeling revealed that better program adherence in the two intervention conditions, when compared with the referent MAMG condition, was mediated by perceptions of group cohesion. The findings provide insight into how the two intervention programs differentially strengthened perceptions of group cohesion and affective attitudes over time. Consistent with self-categorization theory, the results also shed light on the role of group cohesion, in particular, as a psychological mechanism of action to promote older adults' exercise adherence behaviors. (PsycInfo Database Record (c) 2021 APA, all rights reserved).