Mixed methods study exploring parent engagement in child health research in British Columbia
Bibliographic record
Abstract
Objectives The objective of this study was to explore parent perspectives of and interest in an interactive knowledge translation platform called Child-Sized KT that proposes to catalyse the collaboration of patients, families, practitioners and researchers in patient-oriented research at British Columbia Children’s Hospital (BCCH). Methods An explanatory sequential mixed methods design was used over 1 year. Over 500 parents across BC completed an online survey, including a subsample of 102 parents who had accessed care at BCCH within the past 2 years. The survey explored parent perspectives about the value of their engagement at all stages of the research process and their interest in and concerns with using an online platform. Following the online survey, two focus groups were held with parents in the Vancouver area to explore themes emerging from the survey. Results Parents expressed keen interest in engaging in research at BCCH. Parents perceived benefit from their input at all stages of the research process; however, they were most interested in helping to identify the problem, develop the research question and share the results. Although parents preferred online participation, they had concerns about protecting the privacy of their child’s information. Conclusions Parents see value in their involvement in all stages of child health research at BCCH. Their input suggests that Child-Sized KT, a hypothetical online platform, would facilitate meaningful stakeholder engagement in child health research, but should offer a customised experience and ensure the highest standard of data privacy and protection.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".