¹Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT TIROL - University for Health Sciences and Technology, Hall in Tirol, Austria
²Department of Public Health, Health Services Research and Health Technology Assessment, UMIT TIROL – University for Health Sciences and Technology, Hall in Tirol, Austria
³University of Helsinki, Department of General Practice and Helsinki University Hospital, Unit of Primary Care, University of Helsinki, Helsinki, Finland
⁴Research 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
⁵Institute for Global Health (ISGlobal), Barcelona, Spain
⁶Centre of Expertise in Longevity and Long-Term Care, Faculty of Humanities, Charles University, Prague, Czech Republic
⁷Institute 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
⁸Center for Health Decision Science, Departments of Epidemiology and Health Policy & Management, Harvard Chan School of Public Health, Boston, United States
⁹Institute for Technology Assessment and Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, United States

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Introduction: Social prescribing has emerged as a promising approach to address non-clinical drivers of health, including loneliness and poor quality of life (QoL). Nature-based social prescribing (NBSP), which connects individuals with structured group activities in natural environments, has shown potential in promoting mental and social well-being. However, rigorous evaluation of its effectiveness – particularly regarding adherence or compliance – remains limited. We present a pre-defined concept for a target trial emulation (TTE) designed to estimate the causal effect of compliance with NBSP interventions on loneliness and QoL, using the setting and results from three randomized controlled trials in the EU H2020 project RECETAS [1], [2].

Methods: The causal research question of the study is visualized using directed acyclic graphs (DAGs), accounting for potential selection bias and confounding. DAGs allow to identify baseline confounders (e.g., demographic characteristics, or mental and physical health status), and time-varying confounders (physical and mental well-being, self-confidence, weather).

Intervention strategies are defined based on participants’ engagement in scheduled nature-based activities and operationalized by the frequency of participation (e.g., weekly or biweekly).

The primary outcomes of the trials are loneliness, measured using the De Jong Gierveld Loneliness Scale, and health-related QoL assessed using the 15D instrument and the EQ-5D-5L. Participants are followed for twelve months with data collected at four points in time: at baseline (pre-randomization), at post-intervention (at the end of the intervention, i.e., after 10 weeks), and at 6- and 12-month follow-ups.

For the TTE and estimating the per-protocol effect, we define non-compliance based on deviations from the expected participation frequencies, such as participating weekly in nature-based group activities. Artificial censoring will be applied at the first occurrence of protocol deviation to identify non-compliance and to preserve the causal per-protocol interpretation. A marginal structural model with inverse probability of censoring weights (IPCW) will be employed to account for confounding and selection bias, enabling robust and unbiased estimation of the causal effects of compliance.

Results: This methodological framework applies TTE to estimate the causal per-protocol effects of compliance with NBSP interventions on loneliness and QoL. By employing IPCW, we construct a balanced pseudo-population that mimics a randomized per-protocol scenario, thereby facilitating robust and unbiased estimation of the effects of the intervention as actually received.

Conclusion: Our study protocol introduces a robust framework for evaluating how compliance with NBSP interventions affects loneliness and QoL. By using DAGs, applying TTE and modern causal inference methods, common challenges of a real-world program in assessing effectiveness, particularly around compliance, can be addressed. The results are expected to support evidence-informed policy by identifying the conditions under which NBSP interventions are most effective and highlighting strategies to promote sustained participation. Our work aims to guide the efficient implementation of NBSP as a tool to improve population wellbeing and reduce the burden of loneliness.

Funding: RECETAS received funding from the European Union’s Horizon 2020 Research and Innovation program (grant agreement No 945095).

The authors declare that they have no competing interests.

The authors declare that a positive ethics committee vote has been obtained.

Literatur

[1] Litt JS, Coll-Planas L, Sachs AL, Rochau U, Jansson A, Dostalova V, et al. Nature-based social interventions for people experiencing loneliness: the rationale and overview of the RECETAS project. Cities & Health. 2024;8(3):418. DOI: 10.1080/23748834.2023.2300207
[2] Coll-Planas L, Carbó-Cardeña A, Jansson A, et al. Nature-based social interventions to address loneliness among vulnerable populations: a common study protocol for three related randomized controlled trials in Barcelona, Helsinki, and Prague within the RECETAS European project. BMC Public Health. 2024;24(1):172. DOI: 10.1186/s12889-023-17547-x