Self-acceptance and Fertility Choices: A Mixed-methods Study on Indian Women

Context: Infertility presents significant psychological challenges, influencing women’s decisions to pursue in vitro fertilisation (IVF) or adoption. Self-acceptance, the ability to accept oneself unconditionally, may mitigate distress and guide fertility choices. Aims: This mixed-methods study investigated self-acceptance as a predictor of choosing IVF versus adoption and explored the emotional experiences and psychological impacts of fertility decision-making. Settings and Design: A cross-sectional study of 60 women (30 IVF, 30 adoption). Subjects and Methods: Binary logistic regression to examine self-acceptance (Unconditional Self-Acceptance Questionnaire) as a predictor of parenthood choice. Qualitative interviews with 10 participants (5 IVF, 5 adoptions) explored emotional experiences through four questions on grief, coping, self-worth and psychological impact, analysed via thematic analysis. Results: Logistic regression revealed a marginally significant negative association between self-acceptance and choosing IVF ( B = −0.0405, P = 0.065, odds ratios = 0.960, 95% confidence interval [0.920 –1.00]), explaining 7.93% of variance (Nagelkerke r 2 = 0.0793). The predicted probability of choosing IVF decreased from 0.89 to 0.34 as self-acceptance scores increased from 60 to 120. Qualitative findings identified two themes: ‘Journey toward opting for adoption’, where self-acceptance fostered emotional resilience (e.g., redefining motherhood through self-compassion) and ‘journey toward opting for IVF’, marked by psychological toll (e.g., guilt, sadness and emotional volatility). Conclusions: Higher self-acceptance may favour adoption by enhancing emotional resilience, while the psychological toll of IVF reflects barriers to self-acceptance. These findings suggest self-acceptance’s role in fertility decisions, advocating for interventions such as Acceptance and Commitment Therapy or mindfulness in counselling. Further research with larger, diverse samples is needed to confirm these trends.