Bayesian re-analysis suggests participation rather than referral underlies the benefits of social prescribing for chronic diseases

Abstract

Social prescribing (SP) is increasingly implemented to address the social determinants of health in people with chronic diseases, yet uncertainty remains regarding its effectiveness and the mechanisms through which benefit is achieved. We performed a Bayesian re-analysis of randomized trials to distinguish overall treatment effects from implementation-related mechanisms. We systematically identified randomized controlled trials of SP following PRISMA 2020 guidelines. Bayesian hierarchical models were used to estimate intention-to-treat (ITT) effects on physical activity, evaluate dose–response relationships, quantify the additional benefit associated with program participation, examine patient-reported outcomes of link-worker SP, and summarize published economic evaluations. 10 reports involving 4,840 participants were included. SP increased the likelihood of achieving recommended physical activity levels [OR 1.31, 95% credible interval (CrI) 1.07–1.67; posterior probability of benefit = 0.991]. No consistent dose–response relationship was identified (slope −1.29 benefit units, 95% CrI − 6.17 to 3.48). In contrast, high program participation was associated with an additional 0.26 clinically meaningful benefit units (95% CrI − 0.07 to 0.63; posterior probability of benefit = 0.940). Positive effects were observed across physical activity, body weight, blood pressure, mental health, health-related quality of life, patient activation, and functional activity. Exercise-oriented SP remained cost-effective under conventional willingness-to-pay thresholds, whereas the economic value of link-worker SP depended on implementation capacity. SP has a high probability of improving physical activity among adults with chronic diseases. Successful participation, rather than referral alone, appears to be the principal mechanism underlying these benefits.