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Delineation of a proof-of-concept process for NBT uptake in each country

2025· report· en· W7055831229 sur OpenAlexaff

Notice bibliographique

RevueVU Research Portal · 2025
Typereport
Langueen
DomaineMaterials Science
ThématiqueThermal properties of materials
Établissements canadiensAthena Sustainable Materials Institute
Organismes subventionnairesResearch Executive AgencyEuropean Commission
Mots-clésData collectionProcess (computing)Nonprobability samplingStakeholderQualitative researchScale (ratio)Semi-structured interviewThe Conceptual FrameworkQuality (philosophy)Deliverable
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

This report serves as Deliverable 4.1, titled "Delineation of a Proof-of-Concept Process for NBT Uptake in Each Country", and presents findings from a qualitative multiple-case study that explored the needs and perspectives of key stakeholders to engage with and scale up nature-based therapies (NBT). This study was led by the Vrije Universiteit (VU) Amsterdam, conducted as part of the NATURELAB project and in collaboration with academic and non-academic project partners, and used a transdisciplinary approach. Data collection and analysis were guided by a conceptual framework, which combined “interactive-learning-action” and “system innovation perspective”. Scaling up was understood as a cyclical process of embedding novel structures and cultures into existing ones, requiring active stakeholder involvement. Key informant interviews were the main method for data collection. Purposive and convenience sampling was used to select interview participants from eight different categories: i) the medical and health care community; ii) scientific community and innovation structures; iii) environmental organisations; iv) policymakers and governance; v) small and medium- sized enterprises; vi) civil society; vii) the media; and viii) people working in the field of NBT. In total, 100 KIIs were conducted in the five project countries (i.e. Germany, Greece, the Netherlands, Peru, and Portugal). Project partners (from within and outside of R&I organisations) led data collection and initial analyses in their respective countries, with training and support provided by the VU. Interview data was thematically analysed using the framework method and synthesised in five country chapters. Comparative analysis was conducted to explore differences between the five project countries and eight interviewee groups. Various quality and validation checks were performed throughout the process. The five country chapters provide detailed narratives of the perceived needs, benefits, and concerns of study participants in each country, including their views of landscape and other factors influencing the potential integration of NBT into existing systems, and of possible strategies for NBT integration and stakeholder engagement. The comparative analysis showed that the health benefits of nature exposure were widely acknowledged across country data sets. From the total interview data, seven broad categories of stakeholders were identified for future engagement in the scaling up of NBT, with i) the health and social care system being mostly mentioned, followed by: ii) the education sector; iii) citizens, patients, and civil society; iv) government; v) environmental organisations; vi) research community; and vii) business. Potential influencing factors could be grouped within ten broad categories, with i) financial resources most often cited by study participants, and next ii) geography, iii) acceptance, iv) communication and dissemination, v) awareness, vi) culture, vii) research evidence, viii) human resources, ix) regulations, and x) demand. These influencing factors were considered to have the ability to be both constraining and enabling the uptake and integration of NBT in existing systems in different countries. As anticipated, there will be some systemic barriers that require addressing in all countries, like securing sustainable funding sources for making NBT financially and equitably accessible to potential clients. Also, regulations and human resources will be systemic factors that require careful navigation by niche actors. There were some variations in the dominance of specific categories of influencing factors when comparing the five countries or the eight interviewee groups. For example, while financial resources were overall the most commonly cited influencing factor, this was neither the case for all countries nor for all interviewee groups. Additionally, the comparative analysis revealed some notable differences in stakeholder perceptions and needs, both at country level and between interviewee groups. These differences suggest that tailored and context-specific scale-up approaches will be required. While no definitive conclusions can be drawn from this first cycle of stakeholder consultation and engagement, it does provide insights into ways forward, including processes that can be put in motion to facilitate the uptake and integration of NBT in NATURELAB’s five project countries. For example, participants in this study perceived there to be multiple potential benefits of NBT for human health and well-being, health systems, and the human-nature relationship. A key next step will be to start communicating and disseminating this positive message to more stakeholders. Additionally, this study showed that for some stakeholders, like health providers and funders, such messages need to be supported with research evidence; therefore, where available, such evidence needs to be highlighted, and where not available, such evidence needs to be generated as part of the NATURELAB project or through other research initiatives. Another practical next step will be to start a second cycle of consultations with stakeholders, such as through the organisation of focus group discussions. Such consultations are necessary for further developing and refining the preliminary strategies for NBT integration and stakeholder engagement outlined in this report. More general and country-specific recommendations are described at the end of this deliverable.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,254
score de la tête « metaresearch » (Gemma)0,253
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Autre · Signal consensuel: aucune
Score de désaccord entre enseignants0,254
Score d'incertitude au seuil0,920

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,2540,253
Méta-épidémiologie (sens strict)0,0020,002
Méta-épidémiologie (sens large)0,0010,003
Bibliométrie0,0050,002
Études des sciences et des technologies0,0070,009
Communication savante0,0140,011
Science ouverte0,0050,018
Intégrité de la recherche0,0060,008
Charge utile insuffisante (le modèle a refusé de juger)0,0170,005

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,157
Tête enseignante GPT0,440
Écart entre enseignants0,282 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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