Psychometric properties of the Beck Depression Inventory-Second Edition (BDI-II) in individuals with chronic pain
Bibliographic record
Abstract
Given the high prevalence of depression in individuals with chronic pain and the negative outcomes associated with such comorbidity, the importance of assessing depressive symptoms is widely acknowledged by chronic pain specialists. The BDI-II is a commonly employed measure of depressive symptomatology at pain centres; however, little is known about its psychometric properties in this population. This study evaluated factorial validity, internal consistency, and gender invariance of the BDI-II in 481 patients with chronic pain. Four competing models of the BDI-II factor structure were examined and confirmatory factor analysis supported the conceptualization of depression as a singular latent construct, within a hierarchical factor structure consisting of three first-order factors--Negative Attitude, Performance Difficulty, and Somatic Elements. Factor structure, item-total correlations, and correlations between subscale means and subjective pain experience support the inclusion of somatic items despite concerns regarding their overlap with pain symptoms. Internal consistency was good. Mean total scores were in the moderately severe range. Given the evidence of partial measurement invariance, an examination of mean gender differences was warranted. In contrast to the general population, the average scores of women and men were similar. Overall, results support the construct validity and internal consistency of the BDI-II for assessing depressive symptoms in both women and men with chronic pain. Results support the appropriateness of computing a total score and/or subscale scores. These results impact chronic pain researchers and clinicians, particularly given current trends toward empirically supported assessment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".