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

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.

Authors

Institutions

Publication Details

Journal
Health & Social Care in the Community
Published
2025-01-01
DOI
https://doi.org/10.1155/hsc/6115206
Citations
1
Primary Topic
Art Therapy and Mental Health
Type
article
Field-Weighted Citation Impact
6.15

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Uwe Siebert, Sibylle Puntscher, Ursula Rochau, Érica Aranha Suzumura et al.
1 citations
Health & Social Care in the Community
Art Therapy and Mental Health
6.15
article

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

Uwe Siebert, Sibylle Puntscher, Ursula Rochau, Érica Aranha Suzumura, Kaisu Pitkälä, Laura Coll‐Planas, Jill Litt, Igor Stojkov, Júlia Santamaria, Annette Conrads‐Frank, Beate Jahn, Marjan Arvandi, Felicitas Kühne, Veronika Papon, Daniela Schmid, Richard Kimberlee
article en
1 citations

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.

Health & Social Care in the CommunityVol. 2025(1)
Universitat de Vic - Universitat Central de Catalunya (ES), University of Helsinki (FI), Harvard University (US), Universitat Pompeu Fabra (ES), University of the West of England (GB), Helsinki Institute of Physics (FI), Helsinki University Hospital (FI), Massachusetts General Hospital (US), UMIT - Private Universität für Gesundheitswissenschaften, Medizinische Informatik und Technik (AT), Albstadt-Sigmaringen University (DE), Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo (BR), Fundação Faculdade de Medicina (BR), Barcelona Institute for Global Health (ES), Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (ES), Center for Systems Biology (US), Hospital District of Helsinki and Uusimaa (FI)
European Commission, Horizon 2020 Framework Programme
Openalex Percentile: Top 5%
Art Therapy and Mental Health
6.15
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.