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
Bibliographic record
Abstract
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.013 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.035 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".