Barriers and facilitators to reducing paracetamol use in low back pain: A qualitative study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Paracetamol is widely used for low back pain (LBP), but research questions its efficacy and safety. Patient education booklets have been explored for promoting deprescribing, but barriers and facilitators specific to LBP deprescribing remain unexamined. OBJECTIVE: To identify contextual factors facilitating and obstructing successful deprescribing of paracetamol for LBP after receiving an educational booklet. STUDY DESIGN: This study is part of an uncontrolled cohort feasibility study (CEASE NOW) in the community, recruiting from Musculoskeletal Australia and painaustralia. PATIENT SAMPLE: Twenty-four participants with acute, sub-acute, or chronic LBP, self-reporting paracetamol consumption, were included. METHODS: Thematic content analysis was used to analyze qualitative data on barriers and facilitators. Data were categorized by deprescribing outcomes: i) successful deprescribing, ii) attempted but failed, or iii) no attempt. Semi-structured telephone interviews were conducted within one week after each participant completed the one-month follow-up. RESULTS: Successful deprescribing was facilitated by supportive healthcare professionals, willingness, high self-efficacy, fear of future illness, and diverse strategies for deprescribing plans. Barriers included unsupportive healthcare professionals and fear of flare-ups. Participants not attempting deprescribing believed it unnecessary, perceived it as effortful, unquestioningly trusted healthcare professionals, and lacked risk awareness. CONCLUSIONS: Support from healthcare professionals, patient willingness, perceived necessity, risk awareness, effort, and varied strategies influence deprescribing outcomes for LBP patients using paracetamol. Addressing these factors is crucial when designing interventions to promote safe and effective deprescribing in LBP management.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it