Further Validation of the BDI-II Among People With Chronic Pain Originating From Musculoskeletal Disorders
Bibliographic record
Abstract
OBJECTIVE: One criticism of the BDI-II for assessing depressive symptoms in people experiencing chronic pain has been the potential overlap between the physical or psychological origins of some of the symptoms. Furthermore, previous studies have reported both two-factor and three-factor solutions, so that the factor solution of the instrument in this population remains unclear. The main objective of the present study was to validate the BDI-II with a chronic pain population experiencing musculoskeletal disorders. Three specific objectives were: (1) to modify the BDI-II for people with musculoskeletal disorders by adding sub-questions to better identify the perceived cause of the depressive symptoms, (2) to assess the validity and reliability of this modified version of the BDI-II, and (3) to explore the perceptions of the causes/origins of symptoms reported on the BDI-II. Results of the confirmatory factor analysis supported the presence of three dimensions within the BDI- : Cognitive, Affective and Somatic. METHODS: A total of 206 participants experiencing chronic pain answered a modified version of the BDI-II, the CES-D and a sociodemographic questionnaire. RESULTS: Results confirmed the three-dimensional factorial structure of the BDI for this population. Overall, participants experienced higher levels of somatic symptoms compared to symptoms belonging to other dimensions. The percentages of answers to the sub-questions were also similarly distributed between "pain", and "pain and state of mind", regardless of the dimension. DISCUSSION: The importance of assessing somatic symptoms of depression in pain patients and of thoroughly examining the underlying perceived cause of symptoms, regardless of the dimension, are discussed.
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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 | 0.026 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 0.001 |
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".