Parenting under pressure: stress is associated with mothers’ and fathers’ media parenting practices in Canada
Bibliographic record
Abstract
Stress may influence the parenting practices employed by parents to manage their children’s screen-time. The objective of this study was to examine cross-sectional associations between family stress and media parenting practices. Using the Guelph Family Health Study Pilot 2 cohort, data was collected from 64 parents from 39 families. Linear regression using generalized estimating equations was used to examine associations between family-based stress and screen parenting practices, stratified by mothers and fathers. Models were adjusted for household income, the number of children in the family, child sex, and age. General stress was positively associated with mothers’ use of screen-based devices in front of their child(ren) and negatively associated with mothers’ monitoring and limit-setting. Fathers’ general stress was positively associated with limit-setting. Parenting distress was positively associated with mothers’ modeling screen use. Fathers’ parenting distress was negatively associated with limit-setting and positively associated with mealtime screen use. Household chaos was positively associated with monitoring screen-time for both mothers and fathers and positively associated with fathers’ limit-setting. These results suggest that associations between family stress and media parenting practices differ among mothers and fathers. Programs aimed to reduce children’s screen-time should consider these differences in their messaging to parents.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".