Article
Decision-Analytic Modeling Studies on Nature-Based Social Prescribing or Loneliness Reducing Interventions: A Systematic Overview
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Authors
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Igor Stojkov
- Institute of Public Health, Medical Decision Making and HTA, Department of Public Health, Health Services Research and HTA, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria
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Felicitas Kühne
- Institute of Public Health, Medical Decision Making and HTA, Department of Public Health, Health Services Research and HTA, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria
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Marjan Arvandi
- Institute of Public Health, Medical Decision Making and HTA, Department of Public Health, Health Services Research and HTA, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria
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Annette Conrads-Frank
- Institute of Public Health, Medical Decision Making and HTA, Department of Public Health, Health Services Research and HTA, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria
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Daniela Schmid
- Division for Quantitative Methods in Public Health and Health Services Research, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria
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Beate Jahn
- Institute of Public Health, Medical Decision Making and HTA, Department of Public Health, Health Services Research and HTA, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria
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Jùlia Santamaria Navarro
- Institute of Public Health, Medical Decision Making and HTA, Department of Public Health, Health Services Research and HTA, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria
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Erica Aranha Suzumura
- Department of Preventive Medicine, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil
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Richard Kimberlee
- Faculty of Health and Life Sciences, University of the West of England, Bristol, United Kingdom
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Kaisu Pitkälä
- Department of General Practice and Helsinki University Hospital, Unit of Primary Care, University of Helsinki, Helsinki, Finland
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Laura Coll-Planas
- Research group on Methodology, Methods, Models and Outcomes of Health and Social Sciences (M3O). Faculty of Health Sciences and Welfare. Centre for Health and Social Care Research (CESS), University of Vic-Central University of Catalonia (UVic-UCC), Vic, Spain
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Jill S. Litt
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
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Uwe Siebert
- Institute of Public Health, Medical Decision Making and HTA, Department of Public Health, Health Services Research and HTA, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria; Division of Health Technology Assessment, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria; Center for Health Decision Science, Departments of Epidemiology and Health Policy & Management, Harvard Chan School of Public Health, Boston, United States; Institute for Technology Assessment and Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, United States
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Ursula Rochau
- Institute of Public Health, Medical Decision Making and HTA, Department of Public Health, Health Services Research and HTA, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria
| Published: | August 19, 2022 |
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Outline
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Introduction: Social prescribing (SP) refers people with a wide range of social, emotional, or practical needs to community-based, non-clinical services (e.g., volunteering, arts activities, gardening, peer support) in coordination with local agencies and care professionals [1]. Nature-based social prescribing (NBSP) is a subset of SP, promoting nature activities to activate and strengthen social structures and to improve mental and physical health [2], [3]. Although NBSP is gaining popularity as a therapeutic option for people experiencing various psychosocial burdens including loneliness and social isolation, limited high-quality research on potential long-term benefits and costs of NBSP exists [4], [5]. Research on NBSP is vital to assess health-economic effects, to secure institutional support from policymakers, and to further adoption by the public. To compare different NBSP strategies with standard care or against each other, decision makers and health technology assessment agencies often rely on estimates from decision-analytic models. The aim of our systematic literature review was to give an overview of decision models within the domain of NBSP or loneliness reducing interventions.
Methods: We performed a systematic literature search in PubMed/MEDLINE, Embase, INAHTA Database, GH CEA Registry, and NHS EED. Two independent reviewers performed the title/abstract and full-text screening. We included all available primary, peer reviewed original studies containing any decision-analytic model type (e.g., decision trees, Markov state-transition cohort models, microsimulation models) related to NBSP or loneliness reducing interventions in adults, irrespectively of outcomes. Studies published in English, German, or Spanish were included. We did not apply restrictions regarding publication date. Evidence was extracted with a priori defined extraction forms and summarized in systematic evidence tables. This work is part of the “Re-imagining Environments for Connection and Engagement: Testing Actions for Social Prescribing in Natural Spaces” (RECETAS) project.
Results: Of 2,574 identified studies, 14 studies were selected for the full-text screening phase after duplicates were removed and titles and abstracts were screened. Only two studies fulfilled the inclusion criteria, one from Australia [6] and one from England [7]. Both studies compared interventions intended to reduce loneliness to usual care in people (55+ or 65+ years), who experienced loneliness. The evaluated strategies included friendship enrichment programs, computer and internet-based classes, and varying community services [6], [7].
Both studies applied a Markov state-transition cohort model with a one year cycle length, a five-year time horizon, and extensive sensitivity analyses including deterministic, probabilistic, and structural sensitivity analyses [6], [7]. The study performed in England adopted the health system (government) perspective [7] and the Australian study a partial societal perspective [6].
Engel et al. [6] performed a cost-utility analysis concluding cost-saving results and a positive net return based on the return on investment analysis. McDaid et al. [7] performed a cost-effectiveness analysis resulting in 768£ per loneliness-free year gained.
Conclusion: The evidence on decision models for reducing loneliness is very limited. Both identified studies suggested favorable cost-effectiveness or even cost-savings for the evaluated interventions. Main limitations include lack of appropriate input data such as transition probabilities and effect estimates, as well as lack of uniform definition of loneliness and its unknown impact on overall health.
Funding: The work received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 945095 for the project "Re-imagining Environments for Connection and Engagement: Testing Actions for Social Prescribing in Natural Spaces (RECETAS)".
The authors declare that they have no competing interests.
The authors declare that a positive ethics committee vote has been obtained.
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