Bibliographic record
Abstract
Adolescents may be particularly vulnerable to depression. Yet Public health nurses working with large groups of adolescents are often unable to recognize depressed youths due to the lack of simple, reliable screening tools. This exploratory study was undertaken in order to gain information that could be used to develop such a tool. Specifically, the following question was posed: 'Are there modes of relating interpersonally that can be used to distinguish the highly and moderately depressed adolescent from the non-depressed adolescent?' The answer was sought from information obtained from adolescent self-reports on Beck's Depression Inventory and an adapted and pre-tested form of McNair and Lorr's Interpersonal Behavior Inventory. These inventories were administered to twenty-five adolescents who attended a treatment centre for adolescents with emotional problems and seventy seven randomly selected adolescents who attended four Catholic high schools in Greater Vancouver. Adolescents were classified as non-depressed, moderately depressed and highly depressed on the basis of their scores on Beck's Depression Inventory. An analysis of variance was carried out to discover if there was a significant difference in interpersonal behavior scores of non-depressed, moderately depressed and highly depressed adolescents. A simple regression analysis and a multiple step-wise regression analysis was done to see if there was a significant correlation between any interpersonal behavior categories that could distinguish between the non-depressed, moderately depressed, and highly depressed adolescent. The findings supported the overall conclusion: adolescents who exhibit mistrust, competition and detachment most of the time or all of the time and exhibit dominance only some of the time or not all all, may be moderately or highly depressed adolescents. The findings did not support the generally held thesis that suppressed hostility is an important factor in the depressed person.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".