Abstract Background Affective disorders are prevalent and highly disabling mental illnesses that severely impair emotional regulation, social functioning, and quality of life. Traditional care models often face challenges such as fragmented resources, low accessibility, and difficulties in sustained follow-up. The rapid advancement of digital finance technology offers a new pathway for integrating medical payment, personalized health management, and remote services. This study aims to develop and evaluate a mental health care platform incorporating digital finance support—including direct insurance payment, personalized health savings accounts, and incentive-based health behavior rewards—and to examine its effects on symptom alleviation, quality of life, and medical resource utilization efficiency among patients with affective disorders. Methods The study recruited 120 adult patients meeting the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria for affective disorders and randomly assigned them to Group A (n = 40), Group B (n = 40), and Group C (n = 40). Group A received a 12-week digital finance-supported mental health care platform intervention, providing structured psychoeducation, cognitive-behavioral training modules, remote counseling, medication reminders, and integration with digital finance tools for automated insurance settlement and health behavior incentives. Group B received conventional digital mental health intervention of equal duration without financial features, while Group C continued routine outpatient care with no systematic digital intervention. Assessments pre- and post-intervention included the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), World Health Organization Quality of Life-BREF (WHOQOL-BREF), and out-of-pocket medical expense records. Data were analyzed using repeated-measures ANOVA to examine group-by-time interactions and main effects, supplemented by ANCOVA to adjust for baseline differences. Analyses were conducted in SPSS 26.0 with α = 0.05. Results are reported with F (between-groups and error degrees of freedom in subscript), P, and η2 as the effect size measure. Post hoc comparisons were Bonferroni-corrected. Results After the intervention, Group A showed significantly greater improvements in affective symptoms, quality of life, and reduction in out-of-pocket medical expense ratios compared to Group B and Group C. Repeated-measures ANOVA revealed significant interaction effects between group (A, B, C) and time (pre- vs. post-intervention) for PHQ-9 (F(2,117) = 18.72, p.001), GAD-7 (F(2,117) = 16.55, p.001), WHOQOL-BREF total score (F(2,117) = 21.33, p.001), and out-of-pocket expense ratio (F(2,117) = 12.89, p.001). Post-hoc tests indicated that improvements in all measures were significantly greater in Group A than in Groups B and C (p.05), with effect sizes ranging from medium to large (η2 between 0.28 and 0.49). Discussion The digital finance-supported mental health platform significantly improved affective symptoms, quality of life, and reduced financial burden in patients with affective disorders. This integrated model may enhance synergistic care effects by combining medical and financial processes, improving treatment adherence, providing real-time incentives, and lowering access barriers. It also offers an innovative paradigm for equitable and accessible mental health services. Further studies could incorporate health economic evaluations and long-term follow-up to optimize sustainability and extend application across mental health contexts, supporting evidence-based integrated digital interventions for affective disorders.
Yue Zhu (Sun,) studied this question.