Priority setting of healthcare provider barriers and facilitators to supporting patient physical activity in rheumatology: a nominal group technique study
Bibliographic record
Abstract
Objective: To determine the most important barriers, facilitators and resources identified by rheumatology healthcare providers (HCPs) to supporting physical activity (PA) among individuals with rheumatoid arthritis (RA). Methods: Nominal group technique (NGT) sessions were conducted with rheumatology HCPs following a structured process of idea generation, discussion and independent rating. Determinants and resources were grouped into themes and mapped to the Behaviour Change Wheel. Results: A total of 14 rheumatology HCPs participated in four NGT sessions. RA HCPs identified 14 facilitators and 14 barriers to PA promotion, along with 12 helpful resources and 13 additional resource needs. The most important facilitators were patient-centred PA discussions, reassurance around movement safety and delegating PA counselling to exercise professionals. Key barriers included limited time, patient information overload and ineffective handouts. Six overarching themes were emphasised after grouping and theoretical mapping: patient-provider conversations, interdisciplinary teamwork, counselling skills, monitoring and feedback, time and capacity and resource quality. The six categories of key resources were tailored programmes, educational handouts, referral tools, exercise professionals, online tools and professional development. Conclusion: This study identified key barriers and facilitators influencing how rheumatology HCPs support PA among RA patients, highlighting the importance of tailored discussions, interdisciplinary teamwork, counselling skills and supportive resources. HCPs emphasised the need for high-quality, RA-specific resources such as allied health networks and RA-specific programmes. Theoretical mapping pinpointed targets within capability, opportunity and motivation to enhance PA promotion. Ongoing work is underway to codevelop evidence-based tools addressing these determinants to improve PA support for individuals with RA.
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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 | 0.016 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".