Prediction of Teenager Depression Based on Social Skill, Peer Attachment, Parental Attachment and Self-esteem
Bibliographic record
Abstract
The study examined prediction of teenager depression based on social skill, peer attachment, parental attachment and self-esteem. The type of this study is descriptive-corolation. Data from survey of 382 high school daughter students in basis of morgan sampling table were used. At this study we used Multistage Cluster Method for sampeling. Information of this study collecting by Kutcher Adolescent Depression Scale (2002), Social Skills Inventory and Foster teen Ayndrbytzn TISS (1992), Test Adolescent Attachment to Parent and Peer (IPPA-R) (1978) and Ruchester Self-Esteem Scale (1998). The Statistical method used for data analysis in the study is Multivariable regression and Pearson correlation. The results indicated that there was reversed significant relation between teenager Depression and Social Skills. There was also reverse significant realation between Depression, Peer and Parent Attachment and Self-Esteem. Furthermore it revealed that between mother attachment and father attachment, mother attachment had more share on prediction of adolescence depression. Among three variables of social skills, parental attachment, peer attachment and self-esteem the social skill had the least effect on prediction of adolescent depression but others had a significant effect.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".