Normative Data and Mental Health Construct Validity for the Rosenberg Self-Esteem Scale in British Adolescents
Bibliographic record
Abstract
ABSTRACT Self-esteem is a potentially important measure for screening problems of social adaptation which underlie and predict mental health problems. Measuring change in self-esteem is also an important way of assessing success of therapeutic programmes of various kinds. The usefulness of the Rosenberg Self-Esteem Scale (RSES) is indicated from a review of various studies in Canada and America. In the present study, a stratified sample of four comprehensive schools in England, and of classes in two sixth form colleges yielded normative data on the Likert-scaled RSES for 665 male and 665 female pupils aged 12 to 19. Among the measures completed was the Rosenberg Self-Esteem Scale (RSES). In each age group females had significantly lower self-esteem than males, and females were more than twice as likely to have “devastated” self-esteem. Some evidence of construct validity is available for both sex groups within age categories, from significant correlations with previously validated measures of mental health problem categories, using scales from the Ontario Child Health Survey.
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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 | 0.000 |
| 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".