Social Connections and Self-Perceived Depression: An Enhanced Model for Studying Teenagers’ Mental Wellbeing
Bibliographic record
Abstract
The rising prevalence of depression among teenagers in Malaysia as well as globally makes it a vital issue to study. The purpose of this research is to examine the effects of social connection and self-perceived depression towards the improved mental wellbeing of the teenagers of Malaysia. Moreover, the mediating role of self-perceived depression on the improvement of the mental wellbeing of teenagers is examined in this study. This study followed a questionnaire-based approach. The sample of this study included 289 students aged between 15 and 19 years from Klang Valley, Malaysia. Prior permission was obtained from school authorities as well as from parents to allow their children to participate in the survey. To find out the structural relationship between the variables, PLS-SEM was utilized. This study finds that stronger social connections with family and friends may result in reduced self-perceived depression among Malaysian teenagers. Moreover, self-perceived depression among the teenagers surveyed had a negative effect on their improved mental wellbeing. The findings of this study will significantly affect how depression theories are currently understood and have consequences for social work, services, and policy interventions regarding teenagers in Malaysia.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".