Systematic Literature Review of Decision-Analytic Modeling Studies on Nature-Based Social Prescribing and Loneliness

Abstract

Nature-based social prescribing (NBSP) is an evolving subject aiming to reduce loneliness and to foster social connections, health, and well-being. To evaluate the short-term and long-term consequences of different health technologies, decision-analytic modeling can be applied. Decision-analytic modeling studies systematically integrate current short- and long-term evidence to weigh benefits, harms, and costs of different strategies. Our systematic literature review identified and assessed decision-analytic modeling studies addressing specifically NBSP or other interventions aiming to reduce loneliness. Predefined inclusion/exclusion criteria guided our systematic literature search in five databases. Title/abstract screening and full-text screening were conducted by two independent reviewers. An a priori defined extraction table included country, intervention, and model type. The Philips framework was used to evaluate the quality of the studies. Overall, 3273 studies were identified, and 16 studies were eligible for full-text screening. None of these studies applied a decision-analytic model specifically to NBSP. However, two studies compared interventions for reducing loneliness. One study was conducted in Australia and performed a cost-utility analysis, resulting in cost-saving results and a positive return on investment. The second study was conducted in England and applied a cost-effectiveness analysis resulting in 768 British pounds per loneliness-free year gained. Overall, the evaluated interventions can be regarded as cost-effective, and in some instances, they have the potential to save costs. Further research on the connection of loneliness, overall health, social well-being, and quality of life and their integration into decision-analytic studies is needed.