The fine line between the cure and the illness: the risks of prescriptive emotionality and sociality for youth mental health
Bibliographic record
Abstract
School-based initiatives are increasingly promoted as solutions to the youth mental health crisis, with Social Emotional Learning (SEL) among the most widely adopted frameworks worldwide. While designed to foster healthy socio-emotional development, evidence for SEL's long-term mental health benefits remains mixed. Concerns are also growing that universal, non-targeted SEL programs may inadvertently pathologize normal developmental experiences, reinforce self-monitoring, or generate cultural mismatches that undermine resilience. In this personal view, we examine key challenges associated with universal (i.e., non-targeted and intended for all students regardless of baseline risk) school-based programs modeled on SEL. While acknowledging their potential to promote youth well-being, we argue that prescriptive approaches to emotions and sociality can foster confusion among families, resistance among youth, and unintended distress. We highlight risks stemming from conceptual ambiguities and variability in implementation. Rather than abandoning universal programs, we call for rigorous evaluation, cultural adaptation, and integration within broader ecosocial-strategies to foster authentic, context-sensitive resilience in youth.
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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 | 0.003 | 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 | 0.003 | 0.002 |
| 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".