Enhancing reproductive health among adolescent girls in India: results of an individualized RCT to study the efficacy of the go Nisha go mobile game
Bibliographic record
Abstract
BACKGROUND: Adolescent girls in India face significant barriers to accessing sexual and reproductive health (SRH) information and services. Digital interventions, particularly mobile-based ones, promise to deliver SRH education in a fun and engaging manner. These can be offered privately directly to the adolescent, allowing players to 'experience' the outcomes of their choices, receive tailored feedback, and the option to 'try again'. METHODS: This study evaluated the efficacy of "Go Nisha GoⓇ" (GNG), a low-end smartphone-based digital game for adolescent girls in India, using a two-armed, encouragement-led, randomized controlled trial (RCT). The study involved 1950 participants from Patna, Jaipur, and Delhi NCR. The intervention group received encouragement to play GNG, while the control group did not. Key constructs measured included menstrual health management (MHM), contraception knowledge, and agency. Data were collected at baseline and a ten-week follow-up. RESULTS: The intervention group showed significant improvements in various MHM parameters, contraception knowledge, and agency outcomes compared to the control group. Overall, 1697 out of 1993 participants completed the study after ten weeks (85%). The intervention group's awareness of menstrual hygiene products increased from 33 to 92%, while comprehensive knowledge of oral contraceptive pills (OCPs) rose from 2 to 17% (p < 0.0001). Confidence in negotiating contraception use increased from 60 to 85% (p < 0.0001), and the attitude of refusing sex when not ready improved from 61 to 85% (p < 0.0001).The subjects in the game group showed high levels of satisfaction with the app, with 74% discussing the game with others and 66% recommending it. The belief in negotiating marriage decisions with parents also improved more in the intervention group than in the control group. CONCLUSION: The findings of the first-ever RCT outcome evaluation for a digital mobile game app for enhancing SRH education among adolescent girls in low-resource settings support the efficacy of digital games for health like GNG. The game's engaging and interactive format effectively communicated complex and sensitive SRH information, empowered participants, and encouraged (p < 0.0001) critical health behaviors through informed decision-making. Future studies could explore the long-term sustainability of behavior changes induced by such interventions and their effectiveness across different settings and populations. TRIAL REGISTRATION NUMBER: CTRI/2023/03/050447. Date: March, 2023.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".