Screen Time and Socioemotional and Behavioural Difficulties Among Indigenous Children in Canada: Temps d'écran et difficultés socio-émotionnelles et comportementales chez les enfants autochtones du Canada
Bibliographic record
Abstract
Objectives To describe screen time levels and determine their association with socioemotional and behavioural difficulties among preschool-aged First Nations, Métis, and Inuit children. Method Data were taken from the Aboriginal Children's Survey, a nationally representative survey of 2–5-year-old Indigenous children in Canada. Socioemotional and behavioural difficulties were defined using parent/guardian reports on the Strengths and Difficulties Questionnaire. Multiple linear regression analyses were conducted separately for First Nations, Métis, and Inuit participants, and statistically adjusted for child age, child sex, and parent/guardian education. Statistical significance was set at P < 0.002 to adjust for multiple comparisons. Results Of these 2–5-year-old children ( mean [ M] = 3.57 years) 3,085 were First Nations (53.5%), 2,430 Métis (39.2%), and 990 Inuit (7.3%). Screen time exposure was high among First Nations ( M = 2 h and 58 min/day, standard deviation [ SD] = 1.89), Métis ( M = 2 h and 50 min [ SD = 1.83]), and Inuit children ( M = 3 h and 25 min [ SD = 2.20]), with 79.7% exceeding recommended guidelines (>1 h/day). After adjusting for confounders, screen time was associated with more socioemotional and behavioural difficulties among First Nations (total difficulties β = 0.15 [95% CI, 0.12 to 0.19]) and Métis ( β = 0.16 [95% CI, 0.12 to 0.20]) but not Inuit children ( β = 0.12 [95% CI, 0.01 to 0.23]). Conclusions Screen time exposure is high among Indigenous children in Canada, and is associated with more socioemotional and behavioural difficulties among First Nations and Métis children. Contributing factors could include enduring colonialism that resulted in family dissolution, lack of positive parental role models, and disproportionate socioeconomic disadvantage. Predictors of poor well-being should continue to be identified to develop targets for intervention to optimize the health and development of Indigenous children.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".