Professional barriers and facilitators to using stratified care approaches for managing non-specific low back pain: a qualitative study with Canadian physiotherapists and chiropractors
Bibliographic record
Abstract
Abstract Background Recent clinical practice guidelines for the management of non-specific low back pain (LBP) recommend using stratified care approaches. To date, no study has assessed barriers and facilitators for health professionals in using stratified care approaches for managing non-specific LBP in the Canadian primary care setting. This study aimed to identify and contrast barriers and facilitators to using the stratified care approaches for non-specific LBP among Canadian physiotherapists and chiropractors. Methods Individual telephone interviews, underpinned by the Theoretical Domains Framework (TDF), explored beliefs and attitudes about, and identified barriers and facilitators to the use of stratified care approaches for managing non-specific LBP in a purposive sample of 13 chiropractors and 14 physiotherapists between September 2015 and June 2016. Interviews were digitally recorded, transcribed verbatim and analysed by two independent assessors using directed content analysis. Results Three and seven TDF domains were identified as likely relevant for physiotherapists and chiropractors, respectively. Shared key beliefs (and relevant domains of the TDF) for both physiotherapists and chiropractors included: lack of time, cost, and expertise (Environmental Context and Resources);and consulting more experienced colleagues and chronic patients with important psychological overlay (Social Influences).Unique key domains were identified among physiotherapists: incompatibility with achieving other objectives (Goals), and chiropractors: confidence in using stratified care approaches (Beliefs about Capabilities);intention to use stratified care approaches (Intentions);awareness and agreement with stratified care approaches (Knowledge);assessment of readiness for change and intentional planning behaviour (Behavioural Regulation);and improving the management of non-specific LBP patients and the uptake of evidence-based practice (Beliefs about Consequences). Conclusions Several shared and unique barriers and facilitators to using the stratified care approaches for non-specific LBP among Canadian physiotherapists and chiropractors were identified. Findings may help inform the design of tailored theory-based knowledge translation interventions to increase the uptake of stratified care approaches in clinical practice.
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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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.020 | 0.010 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".