A mixed methods exploration of the characteristics, dynamics, processes and perceived effects of research partnerships in child health
Bibliographic record
Abstract
Background: Research partnerships between health researchers and knowledge users (e.g., children and youth, parents and families, healthcare providers) are gaining momentum to promote the uptake and application of research. Yet, comprehensive data on partnerships within child health research that include partnership traditions and knowledge user groups remains limited. This dissertation addresses this gap by exploring child health as a unique context for research partnerships, focusing on their characteristics, dynamics, processes, and effects. Methods: This dissertation adopts an exploratory mixed-methods approach across three concurrent studies, employing multiple data collection and analysis methods while maintaining conceptual coherence and a pragmatic philosophical orientation, integrating findings in the discussion. Objective 1 characterized knowledge user engagement in published child health research through a scoping review, examining characteristics, practices, barriers, facilitators and effects. Objective 2 used interpretive description to provide an in-depth understanding of the experiences, motivations, and relational dynamics of engaging in research partnerships among Canadian child health researchers and knowledge users. Objective 3 employed a concurrent mixed-methods design to explore considerations influencing the individual determinants and perceived effects of partnered child health research compared to other health research contexts, through secondary analysis of a cross-sectional survey of Canadian partnered health research projects funded from 2011-2019 and interviews with child health researchers and knowledge users informed by qualitative description. Results: Objective 1 revealed a growing trend in publications on child health research partnerships, particularly since 2019. Most studies used community-based participatory research approaches and engaged multiple knowledge user groups, though reporting on barriers, facilitators, and effects varied. Objective 2 highlighted role-specific motivations for partnering and underscored the central role of relationships in shaping partnership dynamics, sustainability, and the ability to navigate challenges. Researchers often balanced evolving partnership practices within academic systems and structures not always conducive to collaboration, resulting in tensions. Objective 3 found no significant differences between child and general health cohorts in survey responses. Child health respondents reported positive perceptions of their capability, opportunity, and motivation to work in partnership, but mixed views on project effects. Interview participants embraced common principles across research contexts while navigating additional logistical (e.g., institutional processes) and practical (e.g., engaging proxies) challenges unique to partnered child health research. Participants noted distinct considerations (e.g., safeguarding vulnerable populations), processes (e.g., tailoring engagement strategies) and effects when engaging children and youth, with the ethos of the child health community facilitating partnerships. Conclusion: Overall, research partnerships in child health share common principles and challenges with those in other health research contexts, but also have unique characteristics, dynamics, and processes that add nuance to the conceptualization and practice of partnering. These findings provide a foundational understanding of child health research partnerships, guiding efforts to optimize partnership research and practice. By deepening our understanding of these elements, partners can work toward meaningful collaborations that enhance child health research uptake and effects.
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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 | 0.121 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".