“If You Let Them, They Will Be on It 24 Hours a Day”: Qualitative Study Conducted in the United States Exploring Brazilian Immigrant Mothers’ Beliefs, Attitudes, and Practices Related to Screen Time Behaviors of Their Preschool-Age Children
Bibliographic record
Abstract
BACKGROUND: The increasing prevalence of excessive screen time (ST) among children is a growing public health concern, with evidence linking it to an increased risk of overweight and obesity among children. OBJECTIVE: This study aimed to explore the beliefs, attitudes, and practices of Brazilian immigrant mothers living in the United States related to their preschool-age children's ST behaviors. METHODS: A qualitative study comprising 7 focus group discussions (FGDs) was conducted with Brazilian immigrant mothers living in the United States. All FGDs were audio-recorded and professionally transcribed verbatim. The Portuguese transcripts were analyzed using thematic analysis. RESULTS: In total, 37 women participated in the FGDs. Analyses revealed that although most mothers expressed concerns for their preschool-age children's ST, nearly all viewed ST as an acceptable part of their children's daily lives. Furthermore, mothers perceived that ST has more benefits than disadvantages. The mothers' positive beliefs about (eg, educational purposes and entertainment) and perceived functional benefits of ST (eg, ability to keep children occupied so tasks can be completed and facilitation of communication with family outside the United States) contributed to their acceptance of ST for their preschool-age children. Nevertheless, most mothers spoke of needing to balance their preschool-age children's ST with other activities. Mothers reported using several parenting practices including monitoring time and content, setting limits and having rules, and prompting their children to participate in other activities to manage their preschool-age children's ST. CONCLUSIONS: This study provides new information on the beliefs, attitudes, and practices of Brazilian immigrant mothers living in the United States related to their preschool-age children's ST. Study findings revealed several potentially modifiable maternal beliefs and parenting practices that may provide important targets for parenting- and family-based interventions aimed at limiting preschool-age children's ST.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".