Availability and night‐time use of electronic entertainment and communication devices are associated with short sleep duration and obesity among <scp>C</scp>anadian children
Bibliographic record
Abstract
UNLABELLED: What is already known about this subject Short sleep duration is a risk factor for obesity. Television (TV) in the bedroom has been shown to be associated with excess body weight in children. Children increasingly use other electronic entertainment and communication devices (EECDs) such as video games, computers, and smart phones. What this study adds Access to and night-time use of EECDs are associated with shortened sleep duration, excess body weight, poorer diet quality, and lower physical activity levels. Our findings reinforce existing recommendations pertaining to TV and Internet access by the American Academy of Pediatrics and suggest to have these expanded to restricted availability of video games and smart phones in children's bedrooms. BACKGROUND: While the prevalence of childhood obesity and access to and use of electronic entertainment and communication devices (EECDs) have increased in the past decades, no earlier study has examined their interrelationship. OBJECTIVE: To examine whether night-time access to and use of EECDs are associated with sleep duration, body weights, diet quality, and physical activity of Canadian children. METHODS: A representative sample of 3398 grade 5 children in Alberta, Canada, was surveyed. The survey included questions on children's lifestyles and health behaviours, the Harvard Youth/Adolescent Food Frequency questionnaire, a validated questionnaire on physical activity, and measurements of heights and weights. Random effect models were used to assess the associations of night-time access to and use of EECDs with sleep, diet quality, physical activity, and body weights. RESULTS: Sixty-four percent of parents reported that their child had access to one or more EECDs in their bedroom. Access to and night-time use of EECDs were associated with shortened sleep duration, excess body weight, poorer diet quality, and lower physical activity levels in a statistically significant manner. CONCLUSIONS: Limiting the availability of EECDs in children's bedrooms and discouraging their night-time use may be considered as a strategy to promote sleep and reduce childhood obesity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".