Stratified Psychosocial Care in Assisted Reproductive Technologies: A Narrative Review and Conceptual Framework Across the IVF Pathway

Assisted reproductive technologies (ART), particularly in vitro fertilization (IVF), are characterized by substantial emotional burden, uncertainty, and repeated decision-making under probabilistic conditions. Although psychological distress is common among individuals and couples undergoing ART, psychosocial care remains inconsistently integrated into fertility pathways and is rarely tailored to individual needs. This narrative review synthesizes evidence concerning infertility-related distress, anxiety and depressive symptoms, couple functioning, treatment discontinuation, psychosocial screening, and psychological interventions across the IVF trajectory. Key phases of treatment, including pretreatment assessment, ovarian stimulation, embryo transfer, the waiting period, cycle outcome, and decisions regarding repetition or discontinuation, are described, and phase-specific psychological vulnerabilities are identified. On the basis of the available literature, we propose a conceptual stepped-care framework ranging from universal psychoeducation and routine monitoring to structured psychological interventions, couple-based care, and specialist psychiatric management. Practical screening thresholds, referral criteria, reassessment intervals, and a safety pathway for suicidal ideation are outlined. Particular attention is given to male-factor infertility, strategies for engaging male partners, and the ethical and data-governance requirements of digital mental health tools. Current evidence supports psychosocial interventions for improving emotional well-being and quality of life and suggests a potential role in treatment continuation, but their effects on pregnancy and live-birth outcomes remain uncertain. The proposed framework should therefore be regarded as a clinically informed conceptual model rather than a validated prediction algorithm. Prospective studies are required to assess its feasibility, predictive performance, cost-effectiveness, and impact on patient-centered outcomes.