Poorer subjective mental health among girls: Artefact or real? Examining whether interpretations of what shapes mental health vary by sex
Bibliographic record
Abstract
BACKGROUND: Despite reporting poorer self-rated mental health (SRMH) than boys, girls exhibit greater resilience and academic achievement, and less risk taking or death by suicide. Might this apparent paradox be an artefact arising from girls' and boys' different interpretations of the meaning of SRMH? We examined whether the indicator, SRMH, had a different meaning for girls and boys. METHODS: In 2021-2, we circulated social media invitations for youth age 13-18 to complete an online survey about their mental health, and which of 26 individual and social circumstances shaped that rating. All data were submitted anonymously with no link to IP addresses. After comparing weightings for each characteristic, factor analyses identified domains for the whole group and for girls and boys. RESULTS: Poor SRMH was reported by 47% of 506 girls and 27.8% of 216 boys. In general, circumstances considered important to this rating were similar for all, although boys focussed more on sense of identity, self-confidence, physical well-being, exercise, foods eaten and screen time, while girls paid more attention to having a boyfriend or girlfriend, comparisons with peers, and school performance. With factor analysis and common to boys and girls, domains of resilience, behavior/community, family, relationships with peers and future vision emerged. Girls' poorer SRMH did not arise from a more expansive interpretation of mental health. Instead, it may reflect perceived or real disadvantages in individual or social circumstances. Alternatively, girls' known greater resilience may propel lower SRMH which they use intuitively to motivate future achievement and avoid the complacency of thinking that 'all is well'. CONCLUSIONS: The relative similarity of attributes considered before rating one's mental health suggests validity of this subjective measure among girls and boys.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".