Challenging Research: Completing Participatory Social Research with Children and Adolescents in a Hospital Setting
Bibliographic record
Abstract
OBJECTIVE: A discussion of the challenges to completing participatory social research with children and adolescents in a hospital setting. BACKGROUND: Beginning with the dominant medical culture of hospitals, coupled with a persistent skepticism of social and in particular, qualitative research and its contribution to knowledge in medical circles, restrictive contextual challenges also include attitudinal, methodological, and logistical considerations. Together, these challenges hamper good participatory research practice and the capacity to maintain quality data, as well as impede children's participation in research, which has the capacity to contribute to healthcare design, policy, and planning processes. METHODS: Two studies in pediatric settings in Australia, one of which was completed in 2008 and the other which was discontinued in 2011, provide the basis for this research discussion. The discussion addresses the issues that persist in inhibiting the completion of participatory social research and the resulting impacts on research, children's right to participate, and the volume of evidence that is ultimately available from children's perspectives to support and inform healthcare design, planning, and policy in pediatric settings. CONCLUSIONS: Recommendations for changes that could strengthen and improve this research experience include building awareness of the potential value of this research; increasing its influence; building the capacity and knowledge of gatekeepers, ethics committees, and researchers working in this context; and recognizing and valuing children's competence and participation. KEYWORDS: Evidence-based design, hospital, methodology, patients, pediatric.
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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 | 0.326 | 0.177 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.028 | 0.043 |
| Scholarly communication | 0.020 | 0.016 |
| Open science | 0.006 | 0.029 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 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".