Amidst strong efforts to promote the therapeutic benefits of physical activity for reducing depression and anxiety in clinical populations, little focus has been directed towards the mental health benefits of activity for non-clinical populations. The objective of this meta-meta-analysis was to systematically aggregate and quantify high-quality meta-analytic findings of the effects of physical activity on depression and anxiety for non-clinical populations. A systematic search identified eight meta-analytic outcomes of randomised trials that investigated the effects of physical activity on depression or anxiety. The subsequent meta-meta-analyses were based on a total of 92 studies with 4310 participants for the effect of physical activity on depression and 306 study effects with 10,755 participants for the effect of physical activity on anxiety. Physical activity reduced depression by a medium effect [standardised mean difference (SMD) = −0.50; 95% CI: −0.93 to −0.06] and anxiety by a small effect (SMD = −0.38; 95% CI: −0.66 to −0.11). Neither effect showed significant heterogeneity across meta-analyses. These findings represent a comprehensive body of high-quality evidence that physical activity reduces depression and anxiety in non-clinical populations.

This individual patient data meta-analysis aimed to evaluate the effects of exercise on quality of life (QoL) and physical function (PF) in patients with cancer, and to identify moderator effects of demographic (age, sex, marital status, education), clinical (body mass index, cancer type, presence of metastasis), intervention-related (intervention timing, delivery mode and duration, and type of control group), and exercise-related (exercise frequency, intensity, type, time) characteristics. Relevant published and unpublished studies were identified in September 2012 via PubMed, EMBASE, PsycINFO, and CINAHL, reference checking and personal communications. Principle investigators of all 69 eligible trials were requested to share IPD from their study. IPD from 34 randomised controlled trials (n=4519 patients) that evaluated the effects of exercise compared to a usual care, wait-list or attention control group on QoL and PF in adult patients with cancer were retrieved and pooled. Linear mixed-effect models were used to evaluate the effects of the exercise on post-intervention outcome values (z-score) adjusting for baseline values. Moderator effects were studies by testing interactions. Exercise significantly improved QoL (β=0.15, 95%CI=0.10;0.20) and PF (β=0.18, 95%CI=0.13;0.23). The effects were not moderated by demographic, clinical or exercise characteristics. Effects on QoL (βdifference_in_effect=0.13, 95%CI=0.03;0.22) and PF (βdifference_in_effect=0.10, 95%CI=0.01;0.20) were significantly larger for supervised than unsupervised interventions. In conclusion, exercise, and particularly supervised exercise, effectively improves QoL and PF in patients with cancer with different demographic and clinical characteristics during and following treatment. Although effect sizes are small, there is consistent empirical evidence to support implementation of exercise as part of cancer care.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet

Acceptability is a core concept in digital health. Available frameworks have not clearly articulated why and how researchers, practitioners and policy makers may wish to study the concept of acceptability. Here, we aim to discuss (i) the ways in which acceptability might differ from closely related concepts, including user engagement; (ii) the utility of the concept of acceptability in digital health research and practice; (iii) social and cultural norms that influence acceptability; and (iv) pragmatic means of measuring acceptability, within and beyond the research process. Our intention is not to offer solutions to these open questions but to initiate a debate within the digital health community. We conducted a narrative review of theoretical and empirical examples from the literature. First, we argue that acceptability may usefully be considered an emergent property of a complex, adaptive system of interacting components (e.g., affective attitude, beliefs), which in turn influences (and is influenced by) user engagement. Second, acceptability is important due to its ability to predict and explain key outcomes of interest, including user engagement and intervention effectiveness. Third, precisely what people find acceptable is deeply contextualized and interlinked with prevailing social and cultural norms. Understanding and designing for such norms (e.g., through drawing on principles of user centered design) is therefore key. Finally, there is a lack of standard acceptability measures and thresholds. Star ratings coupled with free-text responses may provide a pragmatic means of capturing acceptability. Acceptability is a multifaceted concept, which may usefully be studied with a complexity science lens.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet