Social Prescribing for Children and Youth: A Scoping Review
Bibliographic record
Abstract
Social prescribing is gaining traction globally, with over 30 countries involved in the social prescribing movement. This holistic approach to health and well‐being is relevant to all ages, but it is especially important for children and youth. While this population has largely been neglected in social prescribing efforts, several evaluations of social prescribing programs specifically targeting this population have emerged in recent years, which calls for a review of the evidence on this topic. Thus, the objective of this scoping review was to map the evidence on the use of social prescribing for children and youth. This review was conducted in accordance with the JBI methodology for scoping reviews and reported in accordance with the Preferred Reporting Items for Systematic reviews and Meta‐Analyses extension for Scoping Reviews (PRISMA‐ScR). The search strategy aimed to locate both published and unpublished literature via 12 databases, Google, Google Scholar, Social Care Online, SIREN Evidence and Resource Library, websites of social prescribing organizations and networks, and a request for evidence sources to members of the International Social Prescribing Collaborative. No language or date restrictions were placed on the search. Two independent reviewers performed title and abstract screening, retrieval and assessment of full‐text evidence sources, and data extraction. Data analysis consisted of basic descriptive analysis. Nine studies met the inclusion criteria, including three mixed methods studies, two rapid evidence reviews, two qualitative studies, one uncontrolled before‐and‐after study, and one randomized clinical trial. All studies were published between 2020 and 2024. Evidently, social prescribing for children and youth is still in its infancy, with an evidence base that is limited in both quantity and quality. However, the existing evidence is promising, offering a starting point to build a robust evidence base, which calls for research and practice advancements in social prescribing for children and youth.
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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 | 0.028 | 0.085 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.023 | 0.024 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".