Psychological interventions for reducing fear avoidance beliefs among people with chronic back pain.
Bibliographic record
Abstract
OBJECTIVE: Chronic back pain (CBP) is responsible for considerable suffering across the world and is frequently associated with decreased functional capacity, quality of life, and substantial health care costs. Fear avoidance beliefs (FAB) comprise cognitions and fears about the potential for physical activities to produce pain and harm and are common among people with CBP. Collectively, research shows that FAB are frequently associated with low levels of physical activity, poorer work outcomes, and disability. Therefore, the purpose of this systematic review is to systematically locate and synthesize the current evidence regarding the effectiveness of psychological interventions on fear avoidance beliefs and fear avoidance behavior in patients with CBP. DESIGN: A systematic literature search was conducted based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and included the databases Web of Science, PubMed, Cochrane, CINAHL, Medline, and PsycINFO. RESULTS: A total of 5,052 records were identified resulting in 2,448 documents after duplicates were removed. We screened 147 studies full text. Twenty-two studies were included in the qualitative synthesis. FAB were assessed by the Fear Avoidance Beliefs Questionnaire, the Tampa Scale of Kinesiophobia and the Avoidance Exercise Questionnaire. Interventions included cognitive behavior therapy (CBT), psychoeducation (PE), and other psychological approaches like motivational interviewing. Twelve of 22 studies demonstrated significant improvements in FAB for people with CBP who underwent a PE or CBT intervention or a different psychological approach. CONCLUSION: CBT and PE interventions are mainly used to address FAB among people with CBP. However, there is still inconsistent evidence as to which psychological interventions are most effective to treat FAB among people with CBP. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".