Self-Perceived Health among School Going Adolescents in Pakistan: Influence of Individual, Parental and Life Style Factors?
Bibliographic record
Abstract
BACKGROUND: Adolescents are at substantial risk of acquiring behaviors which might influence their health status. This study was aimed to assess the proportion of school going adolescents (both males and females) with poor self-perceived health and its associated factors. METHODOLOGY: A cross-sectional study was conducted in three major cities of Pakistan i.e. Karachi, Lahore and Quetta. From each city, six (6) secondary schools were randomly selected (3 public and 3 private). Pre-tested, self-administered questionnaire was distributed to students. Binary logistic regression analysis was conducted to determine independent factors associated with poor self-perceived health. RESULTS: Approximately 29% adolescents (119/414) reported poor self-perceived health. Individual and parental factors significantly associated with poor self-perceived health were being male (AOR = 1.75, 95% CI: 1.09 - 2.79), living in extended family (AOR = 2.65, 95% CI: 1.66 - 4.22), unskilled employment of father (AOR = 2.17, 95% CI: 1.35 - 3.48), lack of parental-child communication (AOR = 1.74, 95% CI: 1.03 - 2.91) and unfair treatment by parents (AOR = 1.80, 95% CI: 1.09 - 2.96). Life style factors such as use of smokeless tobacco (AOR = 2.14, 95% CI: 1.26 - 3.96) and unhealthy diet (AOR = 3.60, 95% CI: 1.76 - 7.33) were associated with poor self-perceived health. CONCLUSION: Better employment opportunities for father, parental counseling and increase awareness for adolescents about healthy diet are recommended to improve adolescent self-perceived health in Pakistan.
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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 | 0.000 |
| 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".