Optimizing the management low back pain: directions from population health, stratified care approaches, and challenges with implementation
Bibliographic record
Abstract
Low back pain (LBP) is a leading cause of disability worldwide. About 90% of LBP is of unknown etiology, and called non-specific LBP. This led to uncertainty in the management of non-specific LBP and hence the research focus is on identifying risk factors for developing non-specific LBP and predictors of persistent pain and disability. Little research has gone beyond disability to identify how LBP affects general health perception, which is associated with increased health care utilization and death. The global aim of this PhD thesis was to contribute evidence on how LBP impacts on health perception and uncover the challenges and solutions of implementing stratified care approaches (SCAs). This thesis consists of 4 manuscripts. Data from the National Health and Nutrition Examination Survey (NHANES) database between 1999 and 2004 was used to estimate the extent to which LBP is associated with self-rated health (SRH) and factors contributing to lower ratings of SRH (Manuscript 1). Among the 8,730 men and women between 20 and 60 years of age, 3,306 (39%) reported LBP and 1/3 of those with LBP reported sciatica. In total 10.9% reported health as consistently fair or poor (F/P) while 45.9% reported consistently excellent, very good (EVG) health. The modifiable factors associated with lower SRH were: morbid obesity, smoking, alcohol consumption, depression, physical inactivity, disability, and working status. The SCAs have been recommended to manage people with non-specific LBP. Recently, the use of SCAs to guide treatment have been shown to be associated with lower costs, better recovery and patient satisfaction. However, clinicians do not uniformly use these in practice. To identify professional barriers to the use of SCAs in clinical practice among Canadian physiotherapists and chiropractors, we completed a qualitative study using individual telephone interviews underpinned by the Theoretical Domains Framework (Manuscript 2). Different barriers and facilitators were identified for each discipline. Factors perceived as strongly influencing the use of SCAs clustered around three theoretical domains for physiotherapists and seven key domains for chiropractors. To improve the uptake and application of SCAs, a systematic review was conducted to summarize the evidence about the effectiveness of knowledge translation (KT) interventions to improve the uptake and application of best available evidence on musculoskeletal disorders among musculoskeletal professionals (Manuscript 3). Findings suggested an over-reliance on educational approaches, specifically interactive meetings, with variable and inconsistent impact on professional outcomes. Nonetheless, few interventions had large effects on changing behavioural practice. This study helped identify components to design a KT intervention to implement SCAs. A barrier to the use of SCAs internationally is the availability of a valid translation and cross-cultural adaptation of specific tools into languages other than English. A systematic review was conducted to estimate the extent to which the translation of STarT Back screening tool, a SCA that uses a biopsychosocial model of management, meets the translation standards and psychometric validation in languages other than the source language which is English (Manuscript 4). This study identified a number of translational, cultural, and psychometric barriers for using STarT Back screening tool. Only 2 out of 11 versions fulfilled all the translation requirements. None had tested all the psychometric properties, and when performed, these were not adequately conducted. Overall, the quality assessment of the versions had a "Poor" total summary score except 2 versions were of "Fair" quality. These four manuscripts have contributed unique information regarding the health effects of non-specific LBP and what strategies are needed to develop a tailored theory-based intervention to help implement SCAs into 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 | 0.165 | 0.186 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.020 | 0.019 |
| Open science | 0.012 | 0.028 |
| Research integrity | 0.016 | 0.025 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".