Factorial validity of the center for epidemiologic studies-depression (CES-D) scale in military peacekeepers
Bibliographic record
Abstract
Despite widespread use of the Center for Epidemiologic Studies Depression Scale [CES-D], there are no investigations that examine its factor structure in a military sample. Separate confirmatory factor analyses were performed on responses to the CES-D obtained from 102 female and 102 male Canadian military peacekeepers in order to compare the fit of a four-factor intercorrelated (lower-order) model to a four-factor hierarchical (higher-order) model. The intercorrelated and hierarchical models fit the data well for both women and men, with hierarchical models fitting the data slightly better for women than men. These findings suggest that, for military women and men, the CES-D can be used to measure a set of distinct but interrelated depressive symptoms as well as a global construct of depression. Implications and future directions are discussed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".