Self-reported attitudes, skills and use of evidence-based practice among Canadian doctors of chiropractic: a national survey.
Bibliographic record
Abstract
OBJECTIVES: To identify Canadian chiropractors' attitudes, skills and use of evidence based practice (EBP), as well as their level of awareness of previously published chiropractic clinical practice guidelines (CPGs). METHODS: 7,200 members of the Canadian Chiropractic Association were invited by e-mail to complete an online version of the Evidence Based practice Attitude & utilisation SurvEy (EBASE); a valid and reliable measure of participant attitudes, skills and use of EBP. RESULTS: Questionnaires were completed by 554 respondents. Most respondents (>75%) held positive attitudes toward EBP. Over half indicated a high level of self-reported skills in EBP, and over 90% expressed an interest in improving these skills. A majority of respondents (65%) reported over half of their practice was based on evidence from clinical research, and only half (52%) agreed that chiropractic CPGs significantly impacted on their practice. CONCLUSIONS: While most Canadian chiropractors held positive attitudes towards EBP, believed EBP was useful, and were interested in improving their skills in EBP, many did not use research evidence or CPGs to guide clinical decision making. Our findings should be interpreted cautiously due to the low response rate.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".