Relationship between Screen Time, Sleep Duration, Parent-Child Interaction and Psychosocial Adjustment among Preschool Children in Selangor, Malaysia
Bibliographic record
Abstract
The current study aimed to determine the relationship between screen time, sleep duration, parent-child interaction and psychosocial adjustment among preschool children in Selangor, Malaysia. The study also intended to assess whether difference exists in psychosocial adjustment between male and female, examine whether sleep duration and parent-child interaction mediate the relationship between screen time and psychosocial adjustment as well as explore on unique predictors of psychosocial adjustment. Multistage cluster sampling method was employed to select the sample in the study. The sample consisted of 392 parents (either mother or father) of preschool children aged between four to six years old in Selangor, Malaysia. Screen Time Questionnaire (STQ) was applied to measure screen time while the Children’s Sleep Habits Questionnaire (CSHQ) was used to assess sleep duration. Besides, the Parent-Child Interaction Checklist and the Strengths and Difficulties Questionnaire (SDQ) were utilized to evaluate parent-child interaction and psychosocial adjustment respectively. Findings demonstrated that there was a significant difference in psychosocial adjustment in terms of hyperactivity, peer problems, prosocial behaviour, and total difficulties between boys and girls. Besides, screen time significantly correlated with parent-child interaction. Results also revealed that child’s gender, father’s years of education, child calming screen time, and parent-child interaction significantly predicted psychosocial adjustment. However, mediation analysis was unable to be conducted to test the mediating role of sleep duration and parent-child interaction on the relationship between screen time and psychosocial adjustment, as screen time did not correlate significantly with psychosocial adjustment in overall.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".