Use of Electronic Entertainment and Communication Devices Among a Saudi Pediatric Population: Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: Excessive use of various electronic entertainment and communication devices, particularly among children, has been associated with increased behavioral problems. Despite children's escalating use of these devices, parents' awareness about the impact thereof is still lacking. OBJECTIVE: The objective of this study was to assess the use of electronic entertainment and communication devices among children attending a health care facility in Jeddah, Saudi Arabia, as well as the parental impression regarding the impact of electronic devices use on the behavior of their child. METHODS: A focused 15-item questionnaire was designed for this cross-sectional study involving mothers of children attending the Well Baby Clinic of King Abdulaziz University Hospital, Jeddah, Saudi Arabia from July 1, 2016 to November 30, 2016. RESULTS: This study included 190 mothers. The mean ages of the children, mothers, and fathers were 7.3 (SD 3.5), 35 (SD 6.5), and 43 (SD 8.3) years, respectively. Most children were of Saudi Arabian nationality (106/190, 55.8%). The most used device in this study was television (154/190, 81.0%), followed by mobile phones (134/190, 70.5%), and tablets (116/190, 61.0%). Computers were the least used device in this study (59/190, 31.0%). In total, 24.7% (47/190) of children in this study used electronic entertainment and communication devices for more than 4 hours per day. Most mothers (129/190, 67.9%) felt that their child spends too much time on electronic devices. Hyperactivity or behavioral problems were reported by 20.0% (38/190) of mothers in this study. Children spending longer hours on electronic devices were much more likely to be perceived to suffer from hyperactivity or behavioral problems (P=.01). CONCLUSIONS: Parental awareness is necessary to counteract the harmful effects of using electronic devices for a prolonged period. Parents require help to cope with this problem effectively.
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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 | 0.001 |
| 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 | 0.000 | 0.001 |
| 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".