Children, young people and parent engagement in health intervention design and implementation: A scoping review
Bibliographic record
Abstract
INTRODUCTION: Engaging children and young people (CYP) with and without their parents in health research has the potential to improve the development and implementation of health interventions. However, to our knowledge, the scope of engagement activities used with this population and barriers to their engagement is unknown. The objective of this review was to identify and describe CYP engagement with and without their parents in the development and/or implementation of health interventions. METHODS: This scoping review included any primary research studies reporting on engaging CYP, with or without parents, in the design and/or implementation of health interventions. Healthcare professionals had to be involved over the course of the study and the study had to take place in either community, primary or tertiary care settings. The following databases were searched in May 2017, May 2020 and June 2021: Medline (OVID), CINAHL (EBSCO) and Embase (Elsevier). Two independent reviewers screened titles, abstracts and full-text articles and used a previously piloted extraction form to extract and summarize information from the included articles. RESULTS: Twenty-eight articles discussing twenty-four studies were included. CYP engagement throughout the research cycle was limited. There were no observed differences in the reported presence of engagement, types of interventions or outcomes of engagement between studies engaging CYP or CYP and parents. Studies engaging CYP and parents contained limited information on how these relationships affected outcomes of engagement. Engagement was enabled primarily by the maintenance of resources and relationships among stakeholders. CONCLUSIONS: Although CYP engagement often influenced health intervention and implementation design, they are inconsistently engaged across the research cycle. It is unclear whether parental involvement enhances CYP engagement. Future research should consider reporting guidelines to clarify the level of CYP and/or parent engagement, and enhance CYP engagement by fostering synergistic and sustainable partnerships with key stakeholders. PATIENT OR PUBLIC CONTRIBUTION: A parent partner with codesign experience contributed to the creation of the research questions, screened titles, abstracts and full texts, helped with data extraction and provided feedback on the manuscript.
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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 | 0.043 | 0.128 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".