ObjectiveWalking groups are increasingly being set up but little is known about their efficacy in promoting physical activity. The present study aims to assess the efficacy of interventions to promote walking in groups to promoting physical activity within adults, and to explore potential moderators of this efficacy.MethodSystematic literature review searches were conducted using multiple databases. A random effect model was used for the meta-analysis, with sensitivity analysis.ResultsThe effect of the interventions (19 studies, 4 572 participants) on physical activity was of medium size (d = 0.52), statistically significant (95%CI 0.32 to 0.71, p < 0.0001), and with large fail-safe of N = 753. Moderator analyses showed that lower quality studies had larger effect sizes than higher quality studies, studies reporting outcomes over six months had larger effect sizes than studies reporting outcomes up to six months, studies that targeted both genders had higher effect sizes than studies that targeted only women, studies that targeted older adults had larger effect sizes than studies that targeted younger adults. No significant differences were found between studies delivered by professionals and those delivered by lay people.ConclusionInterventions to promote walking in groups are efficacious at increasing physical activity. Despite low homogeneity of results, and limitations (e.g. small number of studies using objective measures of physical activity, publication bias), which might have influence the findings, the large fail-safe N suggests these findings are robust. Possible explanations for heterogeneity between studies are discussed, and the need for more investigation of this is highlighted.

Automated telecommunication interventions, including short message service and interactive voice response, are increasingly being used to promote adherence to medications prescribed for cardio-metabolic conditions. This systematic review aimed to comprehensively assess the effectiveness of such interventions to support medication adherence, and to identify the behaviour change techniques (BCTs) and other intervention characteristics that are positively associated with greater intervention effectiveness. Meta-analysis of 17 randomised controlled trials showed a small but statistically significant effect on medication adherence, OR = 1.89, 95% CI [1.51, 2.36], I = 89%, N = 25,101. Multivariable meta-regression analysis including eight BCTs explained 88% of the observed variance in effect size (ES). The BCTs 'tailored' and 'information about health consequences' were positively and significantly associated with ES. Future studies could explore whether the inclusion of these and/or additional techniques (e.g., 'implementation intentions') would increase the effect of automated telecommunication interventions, using rigorous designs and objective outcome measures.

ObjectivesTo estimate the efficacy of app-based interventions designed to support medication adherence and investigate which behaviour change techniques (BCTs) used by the apps are associated with efficacy.DesignSystematic review of randomised controlled trials (RCTs), with meta-analysis.SettingMedline/PubMed, PsycINFO, Cumulative Index to Nursing and Allied Health Literature, Embase and Web of Science were searched from 1990 to November 2018 for RCTs conducted in any healthcare setting.ParticipantsStudies of participants of any age taking prescribed medication for any health condition and for any duration.InterventionAn app-based intervention delivered through a smartphone, tablet computer or personal digital assistant to help, support or advise about medication adherence.ComparatorOne of (1) usual care, (2) a control app which did not use any BCTs to improve medication adherence or (3) a non-app-based comparator.Primary and secondary outcome measuresThe primary outcome was the pooled effect size of changes in medication adherence. The secondary outcome was the association between BCTs used by the apps and the effect size.ResultsThe initial search identified 13 259 citations. After title and abstract screening, full-text articles of 83 studies were screened for eligibility. Nine RCTs with 1159 recruited participants were included. The mean age of participants was >50 years in all but one study. Health conditions of target populations included cardiovascular disease, depression, Parkinson’s disease, psoriasis and multimorbidity. The meta-analysis indicated that patients who use mobile apps to support them in taking medications are more likely to self-report adherence to medications (OR 2.120, 95% CI 1.635 to 2.747, n=988) than those in the comparator groups. Meta-regression of the BCTs did not reveal any significant associations with effect size.ConclusionsApp-based medication adherence interventions may have a positive effect on patient adherence. Larger scale studies are required to further evaluate this effect, including long-term sustainability, and intervention and participant characteristics that are associated with efficacy and app usage.Prospero registration numberPROSPERO Protocol Registration Number: CRD42017080150.

ObjectiveA number of promising automated behaviour change interventions have been developed using advanced phone technology. This paper reviewed the effectiveness of interactive voice response (IVR)-based interventions designed to promote changes in specific health behaviours.MethodsA systematic literature review of papers published between January 1990 and September 2017 in MEDLINE, CINAHL, Embase, PsycINFO, SCOPUS and the Cochrane Central Register of Controlled Trials (CENTRAL) was conducted. From the total of 2546 papers identified, 15 randomised control trials (RCTs) met the eligibility criteria and were included in a random effects meta-analysis. Meta-regression analysis was used to explore whether behaviour change techniques (BCTs) that were used in the interventions were associated with intervention effectiveness.ResultsMeta-analysis of 15 RCTs showed that IVR-based interventions had small but significant effects on promoting medication adherence (OR=1.527, 95% CI 1.207 to 1.932, k=9, p=0.000) and physical activity (Hedges’ g=0.254, 95% CI 0.068 to 0.439, k=3, p=0.007). No effects were found for alcohol (Hedges’ g=−0.077, 95% CI −0.162 to 0.007, k=4, p=0.073) or diet (Hedges’ g=0.130, 95% CI −0.088 to 0.347, k=2, p=0.242). In the medication adherence studies, multivariable meta-regression including six BCTs explained 100% of the observed variance in effect size, but only the BCT ‘information about health consequences’ was significantly associated with effect size (β=0.690, SE=0.199, 95% CI 0.29 to 1.08, p=0.000).ConclusionIVR-based interventions appear promising in changing specific health behaviours, such as medication adherence and physical activity. However, more studies are needed to elucidate further the combination of active components of IVR interventions that make them effective and test their feasibility and effectiveness using robust designs and objective outcome measures.

Summary Establish whether digital self‐monitoring of diet and physical activity is effective at supporting weight loss, increasing physical activity and improving eating behavior in adults with obesity or overweight, and determine the intervention components that might explain variations in its effectiveness. A systematic search of MEDLINE, Embase, PsycINFO, Web of Science, Scopus, Cinahl, and CENTRAL identified 4068 studies, of which 12 randomized controlled trials were eligible and included in the review. A random‐effect meta‐analysis evaluated intervention effectiveness and subgroup analyses tested for effective intervention content. Twelve studies were included in the review and meta‐analysis. Digital self‐monitoring of both diet and physical activity had a statistically significant effect at supporting weight loss (mean difference [MD] = ‐2.87 [95% CI −3.78, −1.96], P < 0.001, I2 = 69%), improving moderate physical activity (standardized mean difference [SMD] = 0.44 [95% CI 0.26, 0.62], P < 0.001, I2 = 0%), and reducing calorie intake (MD = −181.71 [95% CI −304.72, −58.70], P < 0.01, I2 = 0%). Tailored interventions were significantly more effective than nontailored interventions (x2 = 12.92, P < 0.001). Digital self‐monitoring of physical activity and diet is an effective intervention to support weight loss in adults with obesity or overweight. This effect is significantly associated with tailored advice. Future studies should use rigorous designs to explore intervention effectiveness to support weight loss as an adjunct to weight management services.