Mobile Phone Use and its Association With Sitting Time and Meeting Physical Activity Recommendations in a Mexican American Cohort
Bibliographic record
Abstract
BACKGROUND: The benefits of physical activity (PA) are well-documented. Mobile phones influence PA by promoting screen-based sedentary time, providing prompts or reminders to be active, aiding in tracking and monitoring PA, or providing entertainment during PA. It is not known how mobile phone use is associated with PA and sitting time in Mexican Americans, and how mobile phone users may differ from nonusers. OBJECTIVE: To determine the associations between mobile phone use, PA, and sitting time and how these behaviors differ from mobile phone nonusers in a sample of 2982 Mexican-American adults from the Mano a Mano cohort. METHODS: Differences in meeting PA recommendations and sitting time between mobile phone users and nonusers were examined using chi-square and analysis of variance tests. Logistic regression was used to examine associations between mobile phone use, PA, and sitting. RESULTS: Mobile phone users were more likely to be obese by body mass index criteria (≥30 kg/m(2)), younger, born in the United States and lived there longer, more educated, and sit more hours per day but more likely to meet PA recommendations than nonusers. Males (odds ratio [OR] 1.42, 95% CI 1.16-1.74), use of text messaging (OR 1.26, 95% CI 1.03-1.56), and having a higher acculturation score (OR 1.27, 95% CI 1.07-1.52) were associated with higher odds of meeting PA recommendations. Sitting more hours per day was associated with being male, obese, born in the United States, a former alcohol drinker, and having at least a high school education. Among nonusers, being born in the United States was associated with higher odds of more sitting time, and being married was associated with higher odds of meeting PA recommendations. CONCLUSIONS: Mobile phone interventions using text messages could be tailored to promote PA in less acculturated and female Mexican American mobile phone users.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".