Patterns of parent screen use, child screen time, and child socio‐emotional problems at 5 years
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Digital media screens have become an essential part of our family life. However, we have insufficient knowledge about parental screen use patterns and how these affect children's socio‐emotional development. In total, 867 Canadian parents of 5‐year‐old children from the TARGet Kids! Cohort (73.1% mothers, mean ± SD age = 38.88 ± 4.45 years) participated in this study from 2014 to the end of 2019. Parents reported parental and child time on television (TV) and handheld devices and completed the Strengths and Difficulties Questionnaire (SDQ). Latent profile analysis identified six latent profiles of parent screen use: low handheld users (P1, reference; n = 323), more TV than handheld (P2; n = 261), equal TV and handheld (P3; n = 177), more handheld than TV (P4; n = 57), high TV and handheld (P5; n = 38), and extremely high TV and handheld (P6; n = 11). Parents that were more likely to belong to P6 were also more likely to be living in single‐parent households compared to P1 (estimate = −1.49 ± 0.70), p = .03). High membership probability for P2 (estimate = −0.67 ± 0.32, p = .04) and P4 (estimate = −1.42 ± 0.40, p < 0.001) was associated with lower household income compared to P1. Children of parents with higher P4 (χ 2 = 12.32, p < 0.001) or P5 (χ 2 = 9.54, p = .002) membership probability had higher total screen time compared to P1. Finally, a higher likelihood to belong to P6 (χ 2 = 6.82, p = .009) was associated with a higher SDQ Total Difficulties Score compared to P1. Thus, patterns of parent screen use were associated with child screen use and child socio‐emotional problems. The emerging link between parental screen use profiles and child behaviors suggests the need for more research on parent screen time.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it