Building a community-based participatory approach to child, youth, and family health: Learnings from organizational engagement in the Peel Region of Ontario.
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: As hospital-based pediatric clinicians and researchers, we conducted engagement with representatives from public, private, and nonprofit organizations in the Peel Region of Ontario. Objectives were to build relationships and inform research, education, innovation, and programming to improve the health of local children, youth, and families (CYF). METHOD: Relevant public, private, and nonprofit organizations were identified through an extensive environmental scan. Semistructured interviews and focus groups were conducted with front-line, managerial, and executive representatives. Analysis consisted of thematic analysis and quantitative content analysis. All participants were invited to a 1-day community networking event to discuss the engagement findings and brainstorm next steps. RESULTS: = 41 organizations. Participants identified the top three health issues facing families as: (a) mental health and wellbeing (63%); (b) socioeconomic insecurity (52%); (c) lack of physical activity (43%). Major themes included: holistic health and wellness; equity and sociocultural dimensions of health; cross-sector/organizational collaboration and integration; need for inclusive, action-oriented, and participatory approaches. CONCLUSIONS: Insights from these engagement activities led to the development of a community-based participatory research (CBPR) approach to CYF health in Peel. In this article we posit CBPR and a population health approach can come together in research and care to prioritize equity, collaboration, and active participation in a community-wide approach to CYF health. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".