Enhancing patient-centred chiropractic care in Canada: identifying barriers, enablers, and strategies through a qualitative needs assessment
Bibliographic record
Abstract
BACKGROUND: The Canadian Chiropractic Association (CCA) initiated a quality improvement project to develop best practices aimed at enhancing the patient experience. OBJECTIVES: (1) Identify and prioritise the key moments in the new patient experience that could be improved by providing chiropractors with focused support and resources; (2) explore views, barriers, and enablers to implementing these best practices; and (3) develop recommendations to facilitate the adoption of these practices. METHODS: We conducted a qualitative needs assessment using a human-centred design approach, focused on understanding the needs and experiences of end-users to create tailored solutions. The Theoretical Domains Framework (TDF) was employed to explore chiropractors' knowledge use and behaviour change, and TDF domains were mapped to Behaviour Change Techniques (BCTs) to develop targeted strategies for addressing identified barriers and enablers. Thirteen chiropractors from across Canada participated in semi-structured interviews and related activities. RESULTS: The key moments where participants felt they needed the most support were "treatment", "report of findings", "informed consent", "physical examination", and "before the appointment". All participants agreed with the best practices seed statements. Key barriers included gaps in knowledge, communication skills, and resource availability, particularly in rural areas. Enablers included collaboration with other health professionals, mentorship, and access to practice tools. Recommendations include enhanced training in communication and treatment planning, increased access to resources in rural areas, and fostering collaborative relationships among health professionals. CONCLUSION: Understanding the barriers and enablers to implementing best practices can inform targeted strategies to improve patient-centred care in chiropractic practice across Canada.
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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 | 0.031 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.017 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".