What factors do health professionals view as influencing the success of otitis media detection programs for First Nations children? A scoping review and synthesis of qualitative research
Bibliographic record
Abstract
Targeted early detection programs for otitis media exist for First Nations populations across several countries, with variable success reported. Health professionals are in a unique position to evaluate factors that may impact on programme success. This research therefore aims to understand: “What factors do health professionals view as influencing the success of otitis media detection programs for First Nations children?” A scoping review, including a systematic search and synthesis of qualitative research on this topic, was conducted using adapted PRISMA and JBI guidelines. Articles were critically appraised using tools to assess their methodological quality and cultural safety. Seven sources published between 2003 and 2022 met the review inclusion criteria. Two major themes of Health Resource Access and Person and Family Centred Care were identified. Health Resource Access was further explored through three sub-themes examining Client, Practitioner and Service access. Subthemes related to Person and Family Centred Care included Cultural Safety, Health Service Collaboration, Health Education and Consumer Partnerships. The voices of health professionals are largely missing from conversations on otitis media detection for First Nations children. Health professionals can provide unique insights into service delivery that compliment those of parents and care-givers.
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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 | 0.118 | 0.277 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".