A Multi-Group Investigation of the CES-D's Measurement Structure Across Adolescents, Young Adults and Middle-Aged Adults
Bibliographic record
Abstract
The aim of the present research was to investigate, via multi-group analyses, the dimensional structure of the CES-D (Radloff, 1977) across three age groups. For this, three studies were conducted on cross-sectional samples of French speaking respondents, varying in age and drawn from the Quebec educational system: 599 adolescent high school students, 291 young adults attending university, and 844 middle-aged adult employees of a school board. Five a priori hypothesized models were tested via structural equation modeling: a single-factor, two three-factors, a four-factor and a second-order factor model. The four-factor and the second-order factor model provided the best fit and the latter model remained largely invariant across the groups when tested via multi-group comparisons. Other psychometric characteristics of the French Canadian version of the scale (e.g., test-retest reliability, internal consistency, convergent-discriminant validity) were also shown to be satisfactory. Possible applications of subcomponent scores in research (based on the multidimensional structure of the scale), rather than the commonly used composite CES-D score, are discussed. Le but de cette recherche etait d'evaluer, a l'aide d'analyses multi-groupes, la structure factorielle de notre version francaise du CES-D (Radloff, 1977) parmi trois groupes d'âge. Trois etudes transversales ont ete realisees aupres d'echantillons francophones du Quebec provenant du systeme d'education : 599 eleves du secondaire, 291 etudiants a l'Universite et 844 employes d'une commission scolaire. Cinq modeles a priori ont ete evalues a l'aide d'analyses de modelisation par equations structurales : un modele unidimensionnel, deux modeles a trois dimensions, un modele a quatre facteurs et un modele hierarchique. Les deux derniers modeles se sont averes les meilleurs. Les analyses multi-groupes revelent que le modele hierarchique etait le plus invariant parmi les differents groupes d'âges. D'autres caracteristiques psychometriques de cette version canadienne francaise du CES-D, au niveau de la fiabilite temporelle, de la consistance interne et de la validite convergente-discriminante, se sont averees satisfaisantes. Les implications concernant l'utilisation des scores des dimensions plutot que du score total de l'ensemble de la mesure sont discutees.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".