Evaluating the Effectiveness of an Intervention Integrating Technology and In-Person Sexual Health Education for Adolescents (In the Know): Protocol for a Cluster Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Access to a smartphone is nearly universal among American adolescents, and most of them have used the internet to seek health information. Integrating digital technologies into health program delivery may expand opportunities for youth to receive important health information, yet there are few rigorous studies assessing the effectiveness of this type of intervention. OBJECTIVE: The purpose of this study is to assess the effectiveness of In the Know (ITK), a program integrating in-person and technology-based sexual health education for underserved adolescents. METHODS: Youth were engaged in the development of the intervention, including the design of the digital technology and the curriculum content. The intervention focuses on 3 main areas: sexual health and contraceptive use, healthy relationships, and educational and career success. It includes an in-person, classroom component, along with a web-based component to complement and reinforce key content. A cluster randomized controlled trial is in progress among adolescents aged 13-19 years living in Fresno County, California. It is designed to examine the differences in self-reported health and behavioral outcomes among youth in the intervention and control groups at 3 and 9 months. Primary outcomes are condom and contraceptive use or no sex in the past 3 months and use of any clinical health services in the past 3 months. Secondary outcomes include the number of sexual partners in the past 3 months and knowledge of local clinical sexual health services. We will use mixed-effects linear and logistic regression models to assess differences between the intervention and control groups. RESULTS: Trial enrollment began in October 2017 and ended in March 2020 with a total of 1260 participants. The mean age of the participants is 15.73 (SD 1.83) years, and 69.98% (867/1239) of the participants report being Hispanic or Latino. Study results will be available in 2021. CONCLUSIONS: ITK has the potential to improve contraceptive and clinic use among underserved youth. This trial will inform future youth-focused health interventions that are considering incorporating technology. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/18060.
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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 | 0.067 | 0.057 |
| Meta-epidemiology (narrow) | 0.010 | 0.005 |
| Meta-epidemiology (broad) | 0.017 | 0.009 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.011 | 0.013 |
| Insufficient payload (model declined to judge) | 0.093 | 0.016 |
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".