Effects of individual differences, society, and culture on youth‐rated problems and strengths in 38 societies
Bibliographic record
Abstract
BACKGROUND: Clinicians increasingly serve youths from societal/cultural backgrounds different from their own. This raises questions about how to interpret what such youths report. Rescorla et al. (2019, European Child & Adolescent Psychiatry, 28, 1107) found that much more variance in 72,493 parents' ratings of their offspring's mental health problems was accounted for by individual differences than by societal or cultural differences. Although parents' reports are essential for clinical assessment of their offspring, they reflect parents' perceptions of the offspring. Consequently, clinical assessment also requires self-reports from the offspring themselves. To test effects of individual differences, society, and culture on youths' self-ratings of their problems and strengths, we analyzed Youth Self-Report (YSR) scores for 39,849 11-17 year olds in 38 societies. METHODS: Indigenous researchers obtained YSR self-ratings from population samples of youths in 38 societies representing 10 culture cluster identified in the Global Leadership and Organizational Behavioral Effectiveness study. Hierarchical linear modeling of scores on 17 problem scales and one strengths scale estimated the percent of variance accounted for by individual differences (including measurement error), society, and culture cluster. ANOVAs tested age and gender effects. RESULTS: Averaged across the 17 problem scales, individual differences accounted for 92.5% of variance, societal differences 6.0%, and cultural differences 1.5%. For strengths, individual differences accounted for 83.4% of variance, societal differences 10.1%, and cultural differences 6.5%. Age and gender had very small effects. CONCLUSIONS: Like parents' ratings, youths' self-ratings of problems were affected much more by individual differences than societal/cultural differences. Most variance in self-rated strengths also reflected individual differences, but societal/cultural effects were larger than for problems, suggesting greater influence of social desirability. The clinical significance of individual differences in youths' self-reports should thus not be minimized by societal/cultural differences, which-while important-can be taken into account with appropriate norms, as can gender and age differences.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".