Fine-tuning the practical relevance of a quality framework for integrated nature-based interventions in healthcare facilities. A qualitative interview study.

Introduction: Integrated nature-based interventions in healthcare facilities are gaining importance as promising health and biodiversity promotion strategies. This type of interventions combines the restoration of biodiversity in the vicinity of the healthcare facility with guiding patients in that natural environment for health outcomes. However, quality appraisal of these interventions is still poorly developed. Based on a recent scoping review, the authors developed a preliminary quality framework in support of healthcare facilities designing, implementing and evaluating integrated nature-based interventions. This present study aims to fine-tune the practical relevance of the quality framework within the emerging practice. Methods: A qualitative interview study was conducted in seven healthcare facilities in Belgium. Using a combination of snowball and purposive sampling, 22 professionals, involved in the integrated nature-based intervention in their facility, participated in the study. The semi-structured interviews were transcribed and imported into NVivo. A deductive and inductive thematic analysis was used to explore the practical relevance of the quality framework. A stakeholders' assembly review and a member checking of the findings were also part of the study. Findings: Twenty-two interviews with nature management coordinators, healthcare professionals, and healthcare managers were conducted by three principal investigators in seven healthcare facilities implementing integrated nature-based interventions. The contextualization and complexity of integrated nature-based interventions in the participating healthcare facilities demonstrated the need for an evidence-based quality framework describing nature-based interventions. The study led to nine quality criteria, confirming the eight quality criteria derived from a previous scoping review, and the identification of a new quality criterion 'Capacity building, leverage and continuity'. These quality criteria have been refined. Finally, a proposal for a quality framework was developed and operationalized in a checklist. Deployment of the quality framework should be embedded in a continuous cyclical, adaptive process of monitoring and adjusting based on evaluations at each phase of an integrated nature-based intervention. Discussion: Bridging the domains of healthcare and nature management in the context of an integrated nature-based intervention in a healthcare facility requires a transdisciplinary approach. Scientific frameworks such as "complex interventions," Planetary Health and One Health can support the co-design, implementation and evaluation of integrated nature-based interventions within a cyclical, adaptive process. In addition, the importance of the quality of the interactions with nature could gain from more sophisticated attention. Finally, the implications for healthcare facilities, policymakers and education are discussed, as well as the strengths and limitations of the study.

Quality criteria of nature-based interventions in healthcare facilities: a scoping review.

Introduction: Implementing integrated nature-based interventions that simultaneously serve human health and the restoration of biodiversity in healthcare facilities is considered a promising strategy. As an emerging field of research and practice in healthcare, identification of quality criteria is necessary to support desired outcomes related to biodiversity, human health and intervention processes. This study is part of a larger research project in collaboration with the Flemish Agency of Nature and Forest in Belgium. Methods: A scoping review was conducted in accordance with the Joanna Briggs Institute methodology for scoping reviews, in PubMed, Medline, Web of Science and Scopus. A step-by-step tabular screening process was conducted to identify relevant studies and reviews of nature-based interventions, published in English between January 2005 and April 2023. A qualitative content analysis was conducted and the results were then presented to the project steering group and a panel of stakeholders for refinement. Results: After filtering on the eligibility criteria, and with focus on healthcare facilities, 14 articles were included in this study. A preliminary nature-based interventions quality framework with a set of quality indicators has been developed. Discussion: When designing integrated nature-based interventions, a needs analysis of users and the outdoor environment should be conducted. Next, the integration of a One Health and biodiversity perspective and the application of a complex intervention framework, could support the quality of the design and implementation of nature-based interventions in healthcare facilities and facilitate their assessment. In future work, more rigorous research into the design and implementation of integrated nature-based interventions is needed to test and refine the quality criteria in practice.

Prediction uncertainty of environmental change effects on temperate European biodiversity.

Observed patterns of species richness at landscape scale (gamma diversity) cannot always be attributed to a specific set of explanatory variables, but rather different alternative explanatory statistical models of similar quality may exist. Therefore predictions of the effects of environmental change (such as in climate or land cover) on biodiversity may differ considerably, depending on the chosen set of explanatory variables. Here we use multimodel prediction to evaluate effects of climate, land-use intensity and landscape structure on species richness in each of seven groups of organisms (plants, birds, spiders, wild bees, ground beetles, true bugs and hoverflies) in temperate Europe. We contrast this approach with traditional best-model predictions, which we show, using cross-validation, to have inferior prediction accuracy. Multimodel inference changed the importance of some environmental variables in comparison with the best model, and accordingly gave deviating predictions for environmental change effects. Overall, prediction uncertainty for the multimodel approach was only slightly higher than that of the best model, and absolute changes in predicted species richness were also comparable. Richness predictions varied generally more for the impact of climate change than for land-use change at the coarse scale of our study. Overall, our study indicates that the uncertainty introduced to environmental change predictions through uncertainty in model selection both qualitatively and quantitatively affects species richness projections.