Disguised Distress in Children and Adolescents “Flying Under The Radar”
Bibliographic record
Abstract
It is now recognized that there is a very high prevalence of psychological disorders among children and adolescents and relatively few receive psychological treatment. In the current article, we present the argument that levels of distress and dysfunction among young people are substantially underestimated and the prevalence of psychological problems is higher than realized because of a variety of factors. In particular, it is suggested that psychological problems are underestimated due, in part, to the presence of subthreshold conditions that do not meet diagnostic criteria yet involve substantial distress and impairment. In addition, we focus on a subset of children and adolescents who experience profound distress yet keep it hidden or disguised because of a personality style characterized by self-concealment and a tendency to engage in perfectionistic self-presentation. The characteristics of these students who are “flying under the radar” are described with a discussion of associated familial, cultural, and school factors that reduce the likelihood of these students ever seeking help. Given our premise that psychological problems are substantially underestimated, it is apparent that schools have a vitally important role in mental health promotion in terms of the need for proactive system-wide preventive interventions led by school mental health counsellors. Broad programs are needed to bolster levels of resilience and the willingness to seek help among all children and adolescents but especially among those students who would otherwise not be on anyone’s radar screen.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".