Screen use and internet addiction among parents of young children: A nationwide Canadian cross-sectional survey
Bibliographic record
Abstract
OBJECTIVES: To establish the factorial structure and internal consistency of the Internet Addiction Test (IAT) in parents, the level and correlates of problematic internet use, and patterns and types of screen use. STUDY DESIGN: Data were collected through an online questionnaire about preconception health among Canadian women and men with ≥1 child. The questionnaire included the IAT and questions about time spent on screens by device type, use of screens during meals and in the bedroom, and perceptions of overuse. Factor analysis was completed to determine the factorial structure of the IAT, with multivariable linear regression used to determine correlates of the IAT. RESULTS: The sample included 1,156 respondents (mean age: 34.3 years; 83.1% female). The IAT had two factors: "impairment in time management" and "impairment in socio-emotional functioning" of which respondents had more impairment in time management than socio-emotional functioning. Based on the original IAT, 19.4% of respondents would be classified as having a mild internet use problem with 3.0% having a moderate or severe issue. In the multivariable model, perceived stress (b = .28, SE = .05, p < .001) and depressive symptoms (b = .24, SE = .10, p = .017) were associated with higher IAT scores. Handheld mobile devices were the most common type of screen used (mean = 3 hours/day) followed by watching television (mean = 2 hours/day). CONCLUSION: Parents spent a significant portion of their time each day using screens, particularly handheld mobile devices. The disruption caused by mobile devices may hinder opportunities for positive parent-child interactions, demonstrating the need for resources to support parents ever-growing use of technologies.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".