A quasi-experimental study was conducted in the eighth grade of two public schools located in Central Delhi. Two classes (95 participants) in the intervention school and three classes (108 participants) in the comparison school participated. The brief intervention was implemented across four 2-hour sessions for 1 month in the intervention school. Self-reported violence behavior (bullying, fighting, and victimization) was measured at baseline, posttest, and a 6-month follow-up in both schools. Students and teachers also provided feedback regarding feasibility and acceptability. The difference-in-difference analyses indicated nonphysical aggression, physical aggression, and victimization were significantly lower in the intervention group vis-à-vis comparison group at the 6-month follow-up, but not at baseline or immediate posttest, suggesting sleeper effects. Qualitative feedback indicated that the intervention was acceptable to students and suggested that implementation quality was a key to program effectiveness. These findings suggest that the intervention may curtail the increase in violent behavior in early adolescence.

Researchers, media outlets, and stakeholders in adolescent well-being have raised concerns that increased reliance on electronic communication during the COVID-19 pandemic may have led to a rise in cyberbullying among youth. This exploratory study examined potential changes in cyberbullying behaviors among adolescents in the U.S. and India using longitudinal survey data collected before and during COVID-19-related shutdowns. This study included 92 participants from the U.S. and 38 from India who took part in a cohort study, reporting on their experiences with cyberbullying perpetration and victimization at two time points. Our preliminary findings suggest that there was no significant increase in cyberbullying involvement in either country following the onset of the pandemic. The findings from our exploratory work offer early insights into adolescent digital engagement during a global crisis and highlight the importance of including youth from diverse contexts in cyberbullying research.

Introduction: High-quality anthropometric data is essential to creating effective nutrition policy, but there’s limited evidence on the quality of data from population-based household surveys in India, particularly at the sub-national level. Methods: We compared survey procedures implemented by the National Family Health Survey (NFHS), rounds 1, 2, 3, 4, and 5, and the Comprehensive National Nutrition Survey (CNNS). We conducted a disaggregated analysis at the state level to observe quality performance for height-for-age (HAZ), weight-for-age (WAZ), and weight-for-height (WHZ) z-scores for children under five years. Nine data quality parameters, guided by WHO-UNICEF guidelines, were assessed: completeness of birth date and anthropometric measurement, sex ratio, age-heaping, position mismatch, digit preferences, implausible values, z-score distribution and growth faltering graphs. Results: Survey methods improved over time, including enhanced training, increased use of computer-assisted devices, and real-time supervision. Consequently, from 1992 to 2020, there were improvements in anthropometric data quality, including more balanced age and sex distribution, increased completeness of birth date (from 53% to 95%) and anthropometric measures (from 60% to 91%), and decreased rounding of measurements. Steady albeit small improvements were observed in the standard deviation of HAZ (from 1.9 to 1.8) and WHZ (from 1.5 to 1.3). Implausible HAZ values were reduced from 5% to 2%. Data quality varied across states but generally showed a positive trend. Conclusions: Anthropometric data quality in Indian population-level surveys shows satisfactory progress, reflecting global advancement. However, gaps persist, particularly in errors in birth date and height and weight measurement. Continued efforts are needed to further enhance data quality through improved survey planning, training, data collection, real-time supervision, analysis, and reporting, together with the strengthening of administrative data and civil records. High implausible values, especially in surveys with otherwise strong data quality, likely reflect, at least in part, underlying population inequities.