Strategies to Increase Latino Immigrant Youth Engagement in Health Promotion Using Social Media: Mixed-Methods Study
Bibliographic record
Abstract
BACKGROUND: Generating participant engagement in social media applications for health promotion and disease prevention efforts is vital for their effectiveness and increases the likelihood of effecting sustainable behavior change. However, there is limited evidence regarding effective strategies for engaging Latino immigrant youth using social media. As part of the Avance Center for the Advancement of Immigrant/Refugee Health in Washington, DC, USA, we implemented Adelante, a branded primary prevention program, to address risk factors for co-occurring substance use, sexual risk, and interpersonal violence among Latino immigrant adolescents aged 12 to 19 years in a Washington, DC suburb. OBJECTIVE: The objectives of this study were to (1) characterize Adelante participant Facebook reach and engagement and (2) identify post content and features that resulted in greater user engagement. METHODS: We established the Adelante Facebook fan page in October of 2013, and the Adelante social marketing campaign used this platform for campaign activities from September 2015 to September 2016. We used Facebook Insights metrics to examine reach and post engagement of Adelante Facebook page fans (n=743). Data consisted of Facebook fan page posts between October 1, 2013 and September 30, 2016 (n=871). We developed a 2-phased mixed-methods analytical plan and coding scheme, and explored the association between post content categories and features and a composite measure of post engagement using 1-way analysis of variance tests. P<.05 determined statistical significance. RESULTS: Posts on the Adelante Facebook page had a total of 34,318 clicks, 473 comments, 9080 likes or reactions, and 617 shares. Post content categories that were statistically significantly associated with post engagement were Adelante program updates (P<.001); youth achievement showcases (P=.001); news links (P<.001); social marketing campaign posts (P<.001); and prevention topics, including substance abuse (P<.001), safe sex (P=.02), sexually transmitted disease prevention (P<.001), and violence or fighting (P=.047). Post features that were significantly associated with post engagement comprised the inclusion of photos (P<.001); Spanish (P<.001) or bilingual (P=.001) posts; and portrayal of youth of both sexes (P<.001) portrayed in groups (P<.001) that were facilitated by adults (P<.001). CONCLUSIONS: Social media outreach is a promising strategy that youth programs can use to complement in-person programming for augmented engagement. The Latino immigrant youth audience in this study had a tendency toward more passive social media consumption, having implications for outreach strategies and engagement measurement in future studies. While study findings confirmed the utility of social marketing campaigns for increasing user engagement, findings also highlighted a high level of engagement among youth with posts that covered casual, day-to-day program activity participation. This finding identifies an underexplored area that should be considered for health messaging, and also supports interventions that use peer-to-peer and user-generated health promotion approaches.
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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 | 0.020 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".