Assessing childhood and adolescent development of self-concepts via a self-referent encoding task.
Bibliographic record
Abstract
Self-concept, which reflects individuals' overarching views of themselves and their qualities, has been implicated in the development of depression. Studying developmental and sex differences in self-concept between middle childhood and mid-adolescence may speak to the processes by which early self-concept contributes to later depression risk; however, such an understanding requires valid assessment tools. We tested the measurement invariance of a widely used behavioral measure of self-concept, the Self-Referent Encoding Task (SRET), across sex and age from middle childhood (age 6) to mid-adolescence (age 15). Participants (n = 546) were assessed longitudinally four times over a 9-year follow-up at ages 6, 9, 12, and 15. The SRET showed measurement invariance, as well as moderate to high stability, across ages 9-15. Using findings of invariance to inform subsequent analyses of developmental differences in youth self-concept, we found that children's negative self-concepts became increasingly negative from ages 9 to 15. Children's positive self-concepts increased from ages 9 to 12 before decreasing to preadolescent levels of positivity from ages 12 to 15. We additionally found measurement invariance of the SRET across sex at ages 9, 12, and 15. No sex invariance was found at age 6. Boys and girls did not differ in positive or negative self-concept at age 9, 12, or 15. We make recommendations for the use of SRET indices in assessing youth self-concept. We also discuss implications for the developmental dynamics of youth self-concept across late childhood and adolescence. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".