Healthcare provider back pain beliefs unaffected by a media campaign
Bibliographic record
Abstract
OBJECTIVE: Healthcare providers play a key role in transmitting knowledge and beliefs about LBP to their patients. There are differences in back pain beliefs between the various professionals groups treating LBP patients. This study examined whether LBP beliefs changed among the healthcare providers exposed to a media campaign. DESIGN: A quasi-experimental postal before-and-after survey of health professional beliefs following a campaign aimed at improving beliefs about LBP in the general public, and which included specific interventions also towards the healthcare providers. SETTING: Two Norwegian counties, with a neighbouring county serving as control. SUBJECTS: A total of 243 doctors, physiotherapists, and chiropractors in primary care. MAIN OUTCOME MEASURES: Beliefs about LBP before and after exposure to the campaign. RESULTS: A total of 243 doctors, physiotherapists, and chiropractors answered the questionnaire in 2002 and 2005. A general tendency was observed for all providers to have beliefs more in line with guidelines in 2005 compared with 2002, irrespective of exposure status. Some baseline differences in beliefs between the professional groups were not only sustained but in fact seemed to increase from 2002 to 2005. This was particularly as regards LBP as a self-limiting condition. CONCLUSION: An LBP mass media campaign with educational initiatives aimed at healthcare providers did not result in important improvement in LBP beliefs of providers exposed to the campaign. Important differences were observed between beliefs of the different healthcare provider groups in their view of LBP.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".