Social norms related to fertility may be driving pregnancy desire, timing and contraceptive use, but measurement has lagged. We validated a 10-item injunctive Fertility Norms Scale (FNS) and examined its associations with family planning outcomes among 1021 women and 1020 men in India. FNS captured expectations around pronatalism, childbearing early in marriage and community pressure. We assessed reliability and construct validity through Cronbachs alpha and exploratory factor analysis (EFA) respectively, examining associations with childbearing intention and contraceptive use. FNS demonstrated good reliability (α = 0.65-0.71) and differing sub-constructs by gender. High fertility norm among women was associated with greater likelihood of pregnancy intention [RRR = 2.35 (95% CI: 1.25,4.39); ARRR = 1.53 (95% CI: 0.70,3.30)], lower likelihood of delaying pregnancy [RRR = 0.69 (95% CI: 0.50,0.96); ARRR = 0.72 (95% CI: 0.51,1.02)] and greater ambivalence on delaying pregnancy [RRR = 1.92 (95% CI: 1.18,3.14); ARRR = 1.99 (95% CI: 1.21,3.28)]. Womens higher FNS scores were also associated with higher sterilization [RRR = 2.17 (95% CI: 1.28,3.66); ARRR = 2.24 (95% CI: 1.32,3.83)], but the reverse was noted for men [RRR = 0.61 (95% CI: 0.36,1.04); ARRR = 0.54 (95% CI: 0.32,0.94)]. FNS indicated better predictive value among women compared to men for key reproductive outcomes. This measure may be useful for social norms-focused evaluations in family planning and warrants cross-contextual study.

Intra-uterine devices (IUDs) are a safe and effective method to delay or space pregnancies and are available for free or at low cost in the Indian public health system; yet, IUD uptake in India remains low. Limited quantitative research using national data has explored factors that may affect IUD use. Machine Learning (ML) techniques allow us to explore determinants of low prevalence behaviors in survey research, such as IUD use. We applied ML to explore the determinants of IUD use in India among married women in the 4th National Family Health Survey (NFHS-4; N = 499,627), which collects data on demographic and health indicators among women of childbearing age. We conducted ML logistic regression (lasso and ridge) and neural network approaches to assess significant determinants and used iterative thematic analysis (ITA) to offer insight into related variable constructs generated from a series of regularized models. We found that couples' shared family planning (FP) goals were the strongest determinants of IUD use, followed by receipt of FP services and desire for no more children, higher wealth and education, and receipt of maternal and child health services. Findings highlight the importance of male engagement and family planning services for IUD uptake and the need for more targeted efforts to support awareness of IUD as an option for spacing, especially for those of lower SES and with lower access to care.