Return-to-Work Self-Efficacy: Development and Validation of a Scale in Claimants with Musculoskeletal Disorders
Bibliographic record
Abstract
INTRODUCTION We report on the development and validation of a 10-item scale assessing self-efficacy within the return-to-work context, the Return-to-Work Self-Efficacy (RTWSE) scale. METHODS Lost-time claimants completed a telephone survey 1 month (n = 632) and 6 months (n = 446) after a work-related musculoskeletal injury. Exploratory (Varimax and Promax rotation) and confirmatory factor analyses of self-efficacy items were conducted with two separate subsamples at both time points. Construct validity was examined by comparing scale measurements and theoretically derived constructs, and the phase specificity of RTWSE was studied by examining changes in strength of relationships between the RTWSE Subscales and the other constructs at both time measures. RESULTS Factor analyses supported three underlying factors: (1) Obtaining help from supervisor, (2) Coping with pain (3) Obtaining help from co-workers. Internal consistency (alpha) for the three subscales ranged from 0.66 to 0.93. The total variance explained was 68% at 1-month follow-up and 76% at 6-month follow-up. Confirmatory factor analyses had satisfactory fit indices to confirm the initial model. With regard to construct validity: relationships of RTWSE with depressive symptoms, fear-avoidance, pain, and general health, were generally in the hypothesized direction. However, the hypothesis that less advanced stages of change on the Readiness for RTW scale would be associated with lower RTWSE could not be completely confirmed: on all RTWSE subscales, RTWSE decreased significantly for a subset of participants who started working again. Moreover, only Pain RTWSE was significantly associated with RTW status and duration of work disability. With regard to the phase specificity, the strength of association between RTWSE and other constructs was stronger at 6 months post-injury compared to 1 month post-injury. CONCLUSIONS A final 10-item version of the RTWSE has adequate internal consistency and validity to assess the confidence of injured workers to obtain help from supervisor and co-workers and to cope with pain. With regard to phase specificity, stronger associations between RTWSE and other constructs at 6-month follow-up suggest that the association between these psychological constructs consolidates over time after the disruptive event of the injury.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".