Perceptions and use of self-management support strategies to improve the management of spine pain patients in a French-Canadian chiropractic teaching program: a mixed method study
Bibliographic record
Abstract
BACKGROUND: Clinical guidelines for managing non-specific spine pain recommend providing patient education and self-management support strategies (SMSS) as first-line treatment. However, SMSS implementation in daily chiropractic care remains challenging. This study aimed to assess the level of patient activation in their care, explore chiropractic senior interns and clinician supervisors' beliefs about evidence-based practice (EBP) and self-management support, and identify theoretical barriers and facilitators to implementing SMSS. METHODS: We used a three-phase mixed-methods convergent design. In phase 1, during the spring and summer of 2022, 250 consecutive adults with spine pain at the outpatient chiropractic clinic at the Université du Québec à Trois-Rivières, Quebec, Canada, were invited to complete the patients' activation measure (PAM). In phase 2, all senior interns (n = 39) and clinician supervisors (n = 29) were invited to complete three self-administered online questionnaires: 1) EBP Beliefs and Implementation Scales, 2) Pain Attitudes and Beliefs Scale (PABS), and 3) the Practice Style questionnaire. In phase 3, patients, interns and clinicians having completed the questionnaires were convened to semi-structured individual interviews based on the Theoretical Domains Framework (TDF). RESULTS: In phase 1, three quarters of patients (76.3%) reported a moderate-to-high level of activation. In phase 2, interns and clinician supervisors had similar EBP Beliefs mean scores (62.8% and 62.5%, respectively) and EBP Implementation scores (28.6% and 38.2%, respectively). For the PABS, no predominant biomedical or behavioural treatment orientations were observed among interns (mean (SD) = 34.8 (6.3) /60 vs 36.7 (3.5) /48) or clinicians (34.7 (9.1) /60 vs 34.6 (4.9) /48). Interns primarily had a pragmatic practice style, whereas clinicians were equally pragmatic and receptive. In phase 3, four key TDF domains emerged for patients (Social influences, Behavioural regulation, Emotions, and Goals); five for interns (Knowledge, Environmental Context and Resources, Skills, Memory, Attention and Decision Process, and Goals), and four for clinicians (Knowledge, Environmental Context and Resources, Social Influences and Beliefs on Consequences). CONCLUSION: Although patients demonstrated moderate-to-high activation, EBP and SMSS implementation among interns and supervisor was limited. Treatment orientation, practice style, and contextual factors highlight the need for targeted educational and organizational strategies to bridge the knowledge-practice gap.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".