Evaluation of Social Media Utilization by Latino Adolescents: Implications for Mobile Health Interventions
Bibliographic record
Abstract
BACKGROUND: Trends in social media use, including sending/receiving short message service (SMS) and social networking, are constantly changing, yet little is known about adolescent's utilization and behaviors. This longitudinal study examines social media utilization among Latino youths, and differences by sex and acculturation. OBJECTIVES: The purpose of this study was to examine Latino adolescents' social media utilization and behavior over a 16-month period, and to assess whether changes in use differed by sex and acculturation. METHODS: This study included 555 Latino youths aged 13-19 who completed baseline and 16-month follow-up surveys. Prevalence of social media utilization and frequency, by sex and acculturation categories, was examined using generalized estimating equations. RESULTS: Women are more likely to use SMS, but men are significantly more likely to SMS a girl/boyfriend (P=.03). The use of Internet by men and women to research health information increased over time. Facebook use declined over time (P<.001), whereas use of YouTube (P=.03) and Instagram (P<.001) increased, especially among women and more US acculturated youths. CONCLUSION: Social media is ubiquitous in Latino adolescents' lives and may be a powerful mode for public health intervention delivery.
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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 | 0.062 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".