Mental Health and Parental Factors among Adolescents during the COVID Pandemic in Malaysia
Bibliographic record
Abstract
Purpose: The study aims to determine the prevalence of mental health problems among early adolescents and their associations with parental relationships. Methods: A cross-sectional study was conducted on 535 adolescents aged 13 to 14 on the east coast of Peninsular Malaysia using online surveys from February 2021 to April 202. Mental health status was assessed using the Depression, Anxiety and Stress Scale- 21 (DASS-21), and parental or guardian supervision, connectedness, bonding, respect for privacy, physical activity, and risk behaviours were asked using the Malaysian Global School-based Student's Health Survey. Multiple logistic regression analysis was done to examine the associations of the variables. Results: The prevalence of depression, anxiety and stress were 28.2%, 38.1% and 18.5%, respectively. Adolescent with low parental/guardian connectedness and bonding were associated with depression (AOR = 3.82, 95% CI =1.80 – 8.08), anxiety (AOR 2.17,95% CI = 1.34 – 3.50) and stress (AOR 2.29, 95% CI = 1.13 – 4.65). Low parental supervision (AOR = 2.37, 95% CI = 1.19 – 4.54), low academic performance (AOR = 3.57, 95% CI = 1.10 – 11.62), stress (AOR = 8.56, 95% CI = 4.38 – 16.70) and anxiety AOR = 7.83, 95% CI = 4.48 – 13.70) were predictors for depression. Adolescent who had divorced or separated parents/guardians (AOR = 3.57, 95%CI = 1.10 – 11.62) and married parents/guardian but living apart due to working (AOR = 3.57, 95% CI = 1.10 – 11.62) were higher risk for stress. Conclusions: Depression and anxiety were prevalent among adolescents in Malaysia. Poor relationship with parents or guardians was a significant factor for mental health problems among adolescents during the COVID pandemic.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".