The Center for Epidemiologic Studies Depression Scale: A Review with a Theoretical and Empirical Examination of Item Content and Factor Structure
Bibliographic record
Abstract
BACKGROUND: The Center for Epidemiologic Studies Depression Scale (CES-D; Radloff, 1977) is a commonly used freely available self-report measure of depressive symptoms. Despite its popularity, several recent investigations have called into question the robustness and suitability of the commonly used 4-factor 20-item CES-D model. The goal of the current study was to address these concerns by confirming the factorial validity of the CES-D. METHODS AND FINDINGS: Differential item functioning estimates were used to examine sex biases in item responses, and confirmatory factor analyses were used to assess prior CES-D factor structures and new models heeding current theoretical and empirical considerations. Data used for the analyses included undergraduate (n = 948; 74% women), community (n = 254; 71% women), rehabilitation (n = 522; 53% women), clinical (n =84; 77% women), and National Health and Nutrition Examination Survey (NHANES; n = 2814; 56% women) samples. Differential item functioning identified an item as inflating CES-D scores in women. Comprehensive comparison of the several models supported a novel, psychometrically robust, and unbiased 3-factor 14-item solution, with factors (i.e., negative affect, anhedonia, and somatic symptoms) that are more in line with current diagnostic criteria for depression. CONCLUSIONS: Researchers and practitioners may benefit from using the novel factor structure of the CES-D and from being cautious in interpreting results from the originally proposed scale. Comprehensive results, implications, and future research directions 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 | 0.022 | 0.039 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.013 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".