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Record W4386484155 · doi:10.1016/j.msksp.2023.102856

Barriers and facilitators to reducing paracetamol use in low back pain: A qualitative study

2023· article· en· W4386484155 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMusculoskeletal Science and Practice · 2023
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicDrug-Induced Hepatotoxicity and Protection
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsDeprescribingMedicineQualitative researchThematic analysisHealth carePsychological interventionHealth professionalsPolypharmacyNursingIntensive care medicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.024
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0240.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.156
GPT teacher head0.496
Teacher spread0.341 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it