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The effect of artificial intelligence-empowered mobile health on psychological distress in women following abortion:
Wei Zhang1, Yuqi Yang2, Meimei Liu1
1Department of Gynecology, Inner Mongolia Maternity and Child Health Care Hospital, Hohhot, Inner Mongolia, China.
Background:
The number of abortions worldwide continues to rise, and abortion can have adverse physical and psychological effects. At present, there is little attention paid to the psychological distress experienced by women after abortion, such as anxiety and depression. Current interventions rely heavily on specific personnel, time, and location, which can be costly. Artificial Intelligence-Empowered Mobile Health can compensate for the shortcomings of current interventions, and these interventions are guided by Swanson's Theory of Caring.
Methods:
This study is a mixed-methods research protocol to be implemented at the Inner Mongolia Maternity and Child Health Care Hospital. A total of 100 women after abortion will be included and randomly assigned to either the intervention group or the standard care group. The intervention group will receive two weeks of Artificial Intelligence-Empowered Mobile Health intervention guided by Swanson's Theory of Caring, including medical knowledge about abortion, post-operative diet, and exercise guidance. The standard care group will receive standard prenatal care. The primary outcome is the change in depression levels, while secondary outcomes include anxiety, perceived stress, perceived social support, and other factors. This study uses IBM SPSS Statistics 27.0 and NVivo 12.0 for data analysis, employing descriptive statistics, normality tests, Mann-Whitney U, Wilcoxon, and chi-square tests.
Discussion:
This study pioneers an Artificial Intelligence-Empowered Mobile Health guided by Swanson's Theory of Caring, providing continuous post-abortion support to reduce psychological distress. It applies Large Language Models to Artificial Intelligence-Empowered Mobile Health for women experienced abortion, delivering timely, specialized care. This approach overcomes traditional barriers: offering real-time interaction, breaking spatiotemporal limits, lowering costs, and integrating expert knowledge to mitigate regional resource disparities, and also promoting health equity.
