Improving Bystander Self-efficacy to Prevent Violence Against Women Through Interpersonal Communication Using Mobile Phone Entertainment Education: Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Violence against women is a major challenge worldwide and in India. Patriarchal social and gender norms suppress disclosure of violence experienced by women. Stimulating interpersonal communication about a normatively stigmatized but prevalent topic could offer an avenue toward boosting bystander self-efficacy to intervene and prevent violence against women. OBJECTIVE: In this study, to reduce violence against women as the distal goal, we adopted a two-pronged strategy grounded in Carey's model of communication, approaching the issue in an incremental way. First, we aimed to explore whether the intervention promoted interpersonal communication about violence against women as an initial step. Second, we examined whether the intervention improved women's self-efficacy to intervene when they witness violence in their community through interpersonal communication. Our model is based on the social cognitive theory that posits observational learning (ie, hearing about other women interfering to stop violence) fosters self-efficacy, a proxy for behavior change. METHODS: We conducted a randomized controlled trial of women of reproductive age using a 2-arm study design embedded within a parent trial implemented in Odisha, India. In total, 411 participants were randomly assigned to the violence against women intervention arm or a control arm if they were active mobile phone owners and assigned to the treatment arm of the parent trial. Participants received 13 entertainment education episodes daily as phone calls. The intervention included program-driven, audience-driven, and responsive interaction strategies to facilitate the active engagement of participants. Audience-driven interactions were incorporated throughout the episodes using an interactive voice response system, which allowed participants to like or replay individual episodes through voice-recognition or touch-tone keypad. Our primary analysis involved a structural equation model with interpersonal communication as a potential mediator on the pathway between intervention exposure and bystander self-efficacy to prevent violence against women. RESULTS: The findings from structural equation modeling demonstrated the significant mediating effect of interpersonal communication on the relationship between program exposure and bystander self-efficacy. Exposure was positively related to interpersonal communication (β=.21, SE=.05; z=4.31; P<.001) and bystander self-efficacy (β=.19, SE=.05; z=3.82; P<.001). CONCLUSIONS: Our results demonstrate participant engagement in interpersonal communication following exposure to a "light" entertainment education program with audio-only format via feature phones in rural settings can result in improved self-efficacy to prevent violence against women. This elevates the role of interpersonal communication as a mechanism of behavior change in mobile phone-based interventions, given that most entertainment education interventions tend to be mass media based. Our findings also show the potential of changing the environment where witnesses of violence deem it worthy of intervention and perceive higher efficacy to stop violence in the community, rather than putting the onus on the perpetrator, to prevent any counterproductive effects. TRIAL REGISTRATION: Clinical Trials Registry-India CTRI/2018/10/016186; https://tinyurl.com/bddp4txc.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".