Engaging children and families in pediatric Health Research: a scoping review
Bibliographic record
Abstract
AIM: Patient engagement (PE) in pediatric health services research is challenging due to contextual factors such as busyness of parenting, work schedules, and diverse family structures. This scoping review seeks to comprehensively map current PE strategies with parents and families across existing published pediatric health research literature. METHODS: We followed Arksey and O'Malley (2005) and Levac et al., (2010) six-stage scoping review process. We conducted the search strategy in Medline, Embase, CINAHL, and Psychinfo databases. Data were extracted from included articles; evidence tables were developed and narrative synthesis was completed. RESULTS: Of 3925 retrieved records, seventeen articles were included in the review. Patient engagement primarily occurred through strategies such as advisory groups, meetings, focus groups and interviews. Strategies were used to engage patients at various levels, for different purposes (e.g., to inform, participate, consult, involve collaborate and/or lead). These strategies were also used at various stages of the research process. Navigating power differences, time and money were commonly reported challenges. Inconsistent terminology plagued (e.g., stakeholder engagement, consumer participation, patient and public involvement, participatory research) this body of literature and clarity is urgently needed. CONCLUSIONS: This review offers insights into current PE strategies used in pediatric health services research and offers insight for researchers considering employing PE in the future.
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 | 0.026 | 0.076 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.019 | 0.021 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.004 |
| 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".