More value and less waste in research on primary cam morphology and its natural history: a qualitative interview study of stakeholders' perspectives
Bibliographic record
Abstract
Background Primary cam morphology, an acquired bony prominence at the head-neck junction of the femur, is highly prevalent in athlete populations, and causally associated with femoroacetabular impingement syndrome and early hip osteoarthritis. Experts agreed on key elements for primary cam morphology and a prioritised research agenda for the field. This research agenda will require higher-quality research to achieve meaningful progress on the aetiology, prognosis and treatment of primary cam morphology in athletes. Aim To explore stakeholders’ perspectives of high-quality research in the research field of primary cam morphology and its natural history. Methods Grounded in interpretive description, we used semi-structured interviews to explore stakeholders’ perspectives of high-quality research in the primary cam morphology research field. The framework for INcreasing QUality In patient-orientated academic clinical REsearch (INQUIRE) informed the interview guide. Audio-recorded interviews were transcribed and analysed using thematic analysis. We recruited a heterogenous and purposive maximum variation sample, drawing from a network of research contacts. Results Fifteen individuals, several with multiple perspectives on research quality in the field, participated. Exploring stakeholders’ perspectives on research quality through an established research quality framework (INQUIRE) illuminated areas for immediate action for research communities in the field of primary cam morphology and its natural history. We crafted five action inviting themes: research communities should: partner with athletes/patients; champion equity, diversity and inclusion; collaborate with one another; pursue open science; and nurture young scholars. Conclusion The findings of this study could inform concrete actions by research communities to pursue higher quality research—more research value and less waste—in the field of primary cam morphology and its natural history. Although the five action-inviting themes reflect contemporary trends in research, and could therefore be transferable to other areas of research, their practical application remains context- and field-specific.
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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 | 0.072 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.020 | 0.027 |
| Scholarly communication | 0.011 | 0.014 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".