Risk behaviours as a dimension of mental health assessment in adolescents
Bibliographic record
Abstract
Summary Aim. An assessment of the health status in adolescence includes, among other variables, risk behaviours that may involve either direct or potential mental health risk. In the study two categories were introduced in the mental health assessment, defined as externalising (problem behaviour) and internalising (emotional disturbances) indicators. The first aim of the study was to estimate problem behaviour prevalence among students beginning secondary school, while the second objective was to analyse the relationships between internalisation and externalisation indicators. Material and method. The participants of the study were first grade students (N = 1123) of secondary schools in the City of Warsaw area. They responded to a Polish adaptation of a self-report Canadian questionnaire monitoring the adolescents’ mental health. The following externalising indicators of risk behaviours were used: getting drunk, problems due to alcohol drinking, drug use, problems caused by drug use, violence, law-breaking. The following internalising indicators were analysed: depressive symptoms (as measured by the CES-D scale), psychological distress (the GHQ–12 questionnaire by Goldberg), selfrated poor mental health, suicidal thoughts. Results. The presence of at least one of the risk behaviours was reported by a half of the sample (52%), more often by boys (59.9%). A high percentage of those manifesting problem behaviour were characterised by a higher intensity of experienced psychological stress, more severe depressive symptoms and worse self-rated psychological functioning. Those who reported symptoms of poor mental health, together with two or more problem behaviours constituted 14.9% of the sample. Conclusion. The group at risk for mental health constituted about a third of the sample studied, irrespective of gender. mental health / risk behaviours / adolescents
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.001 | 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".