An explanatory mixed methods study assessing Canadian chiropractors’ attitudes and orientation toward patient-centred care
Bibliographic record
Abstract
Abstract Background Patient-centred care (PCC) is considered an essential concept in twentyfirst-century healthcare; however, health care providers’ attitudes can be an important barrier or facilitator to its actual implementation. Chiropractic is frequently referred to as providing PCC. However, the attitudes of practising chiropractors towards patient-centred care have not previously been evaluated. Objectives To explore attitudes and orientation of chiropractors towards patient-centered care. Methods We used a sequential explanatory mixed methods with quantitative priority study design. Data were collected from May 2018 to April 2019 from a convenience sample of Canadian chiropractors located across Canada. Quantitative data were collected by a survey consisting of demographic and clinical practice questions, and the Patient-Practitioner Orientation Scale (PPOS) to measure practitioner attitudes towards care delivered (range 1–6, scores < 4.57 = doctor-centred attitudes). Qualitative data were collected using semi-structured interviews. Quantitative data were analyzed with descriptive statistics and bivariate analysis; whilst qualitative data were analyzed using thematic analysis. Results We included 31 chiropractors in the study, with seven completing interviews. The mean for PPOS Overall score was 4.35 (95% CI [4.18, 4.52]) and was found to be significantly associated with years in practice and number of patients seen per week. The average PPOS Sharing and PPOS Caring scores were 4.20 (95% CI 3.95–4.45) and 4.50 (95% CI 4.35–4.66), respectively. Number of patients seen per week and per hour were significant predictors of the PPOS Sharing score; whilst years in practice was a significant predictor of PPOS Caring and Overall scores. Interview data supported the association between greater exposure to patients and more patient-centred attitudes among chiropractors. Conclusions In our sample of Canadian chiropractors, doctor-centred attitudes towards care prevailed, comparable to that reported for other health professions. The significant association between patient-centred attitudes and patient load and clinical experience suggests that chiropractors may learn such attitudes through experience. Future research to further explore chiropractors’ attitudes and orientation towards care using the PPOS or a similar instrument are required.
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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 | 0.019 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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".