Multicultural Adaptation of Mighty Girls for Widespread Dissemination: Pilot Study, App Development and Usability Testing, and Gauging Parent Support With Focus Groups
Bibliographic record
Abstract
BACKGROUND: Taking evidence-based interventions to scale is a challenge for prevention science. Mighty Girls is an evidence-based sexual health intervention program that combines classroom sessions with novel, cutting-edge technology (digital puppetry). The program was developed for 7th grade Latinas, but US school and community demographics rarely allow interventions targeting a single ethnic group. Additionally, digital puppetry is costly to scale up, and parent disapproval often prevents successful dissemination of adolescent sexual health programs. Intervening steps along the scaling-up pathway are needed to adapt the program prior to scaling up for dissemination. OBJECTIVE: The aims of this study were to create a multicultural adaptation of the Mighty Girls program using a mobile app that is less costly to disseminate and is acceptable to parents of 7th grade girls. METHODS: This study used a three-phase process to adapt Mighty Girls into Mighty Teens. All phases used purposive (nonprobability) sampling of low-income, multicultural, urban metropolitan groups (7th grade girls and their parents) within central Florida. Phase 1 involved two videotaped implementations of a multicultural adaptation of the classroom sessions, one involving focus groups (N=14) and the other serving as a single-group pretest-posttest pilot study (N=23). Phase 2 involved development of a narrative cell phone app prototype, which was subjected to usability testing (N=25). App usability and engagement were assessed qualitatively (observation, focus group, open-ended questions) and quantitatively. Phase 3 used focus groups to assess parent support for the program (N=6). Qualitative data were analyzed using descriptive content analysis. Quantitative data were analyzed using descriptive statistics and paired t tests. RESULTS: Qualitative findings supported classroom sessions being multicultural, and identified simple changes to improve engagement and learning. Quantitative findings from the second classroom session implementation pilot study indicated a significant pre-post difference in intention to delay sexual intercourse (P=.04). App usability and appeal were supported by a System Usability Scale score of 76 (exceeding 68 per the industry standard) and 83% (20/24) of participants agreeing they would recommend the app to friends. Parents (mothers) expressed only positive regard for program goals, and classroom session and app activities. CONCLUSIONS: This study adapted Mighty Girls into an engaging, easier-to-disseminate, multicultural program, termed Mighty Teens, that uses a narrative-generating app to support behavior change, and is likely to be accepted by parents of 7th grade girls. This study also provides evidence of the preliminary effectiveness of Mighty Teens classroom sessions. The sampling method and sample size were appropriate for adaptation, but research involving a more representative US sample is needed to confirm multicultural fit, parent receptivity, and program effectiveness. Study implications include integrating app use throughout the classroom sessions to build narrative-generating skills across the program and increasing the number of narratives produced, which should in turn increase the program's behavior change potency.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".