Forest school INterventions for Children’s Health: a feasibility cluster randomised controlled trial to compare Forest School versus usual indoor classroom-based curriculum activity with KS2 children: the FINCH protocol
Notice bibliographique
Résumé
Background: Child and adolescent mental health is a public health priority, and prevention, early intervention, and treatment are identified as national strategic priorities. Children and young people (CYP) in the United Kingdom are experiencing poorer mental health outcomes than ever, and the demand for services is the highest on record. Understanding the effectiveness of school-based interventions for promoting and developing emotional well-being is a core research priority. A school-based intervention that is inclusive and has the potential for widespread delivery is 'Forest School'. Forest schools provide children with immersive experiences in nature that are non-classroom-based and have a core focus on child-led activities and exploration. Despite widespread implementation, evidence about optimal delivery methods for Forest Schools and their impact on mental health and emotional well-being is scarce. This study will generate new knowledge about the feasibility of running a definitive Forest School trial with Key Stage 2 (KS2) children aged between 7-11 inclusive of children with special educational needs and disabilities. Research Questions: Is Forest School an acceptable and feasible intervention to improve the mental health of KS2 children?Is it feasible to run a cluster Randomised Controlled Trial (RCT) of Forest School for children in key stage 2 (aged 7-11)? Objectives: 1. Test feasibility of trial procedures for recruitment, randomisation, and data collection2. Conduct a mixed methods process evaluation to evaluate implementation and fidelity3. Collect feasibility data to support an economic evaluation in a full trial4. Refine the current logic model and optimise the intervention. Methods: In Work Package (WP) 1, we will conduct a feasibility cluster RCT of a Forest School intervention with 200 children in five schools across Hull, East Yorkshire, and North Yorkshire. We will test the acceptability and feasibility of intervention delivery, assess the feasibility of the trial processes, and establish key parameters for effectiveness. In WP2, we will evaluate the quality and fidelity of intervention delivery through process evaluation, including observations and qualitative interviews. WP3 focused on the preliminary collection of health economic data. WP4 uses focus groups to refine the logic model and optimize the content of the intervention. We seek to produce a manualised toolkit informed by interconnected work packages to inform further research and implementation. The trial was registered in ISRCTN (The United Kingdom's Trial Registry). Clinical Trials Registration Number ISRCTN87263624. Patient and Public Involvement: This proposal was developed with the active involvement of parents/guardians, children, and schools alongside key stakeholders from the local authority, education, and the community sector. Dissemination: We will develop accessible presentations, online workshops with interactive elements, and newsletters. Producing a set of easily read infographics and creative outputs (video/social media) alongside our children's Patient and Public Involvement (PPI) groups will be a key output. We anticipate that two publications in open-access peer-reviewed journals will share the quantitative and qualitative findings of the study.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,012 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,004 | 0,002 |
| Méta-épidémiologie (sens large) | 0,006 | 0,004 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,003 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,005 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,035 | 0,003 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».