Jiang Jing, Yang Yang
School of Architecture and Art Design, Southeast University ChengXian College, Nanjing, Jiangsu, 210088, China.
School of Civil and Transportation, Southeast University Chengxian College, Nanjing, Jiangsu, 210088, China.
BMC Psychol. 2025 Apr 8;13(1):350. doi: 10.1186/s40359-025-02640-0.
Digital mental health interventions, including AI-integrated applications, are increasingly utilized to support individuals with elevated symptoms of psychological distress. However, a gap exists in understanding their efficacy specifically for student populations.
This study aimed to investigate the effects of GymBuddy, an AI-powered fitness and accountability app, and Elomia, an AI-based mental health chatbot, on the mental health of students at risk for psychological distress.
A quasi-experimental study was conducted involving 65 participants who exhibited heightened psychological distress but did not have a formal diagnosis of a psychological disorder. Participants were randomly assigned to either the intervention group, which utilized GymBuddy and Elomia for structured mental health support, or the control group. Mental health outcomes such as anxiety, depression, and stress levels were assessed using standardized baseline, midpoint, and endpoint measures. Data were analyzed using Mixed ANOVA.
The mixed ANOVA analysis revealed significant improvements across all measured mental health outcomes, including somatic symptoms, anxiety and insomnia, social dysfunction, and severe depression. Significant main effects of time and group membership were observed for all variables, indicating overall symptom reduction and baseline differences between groups. Moreover, significant interaction effects for somatic symptoms (F(2, 70) = 59.96, p < 0.0001, η² = 0.63), anxiety and insomnia (F(2, 70) = 32.05, p < 0.0001, η² = 0.48), social dysfunction (F(2, 70) = 59.96, p < 0.0001, η² = 0.63), and severe depression (F(2, 70) = 32.05, p < 0.0001, η² = 0.48) indicated that participants in the intervention group experienced significantly greater reductions in psychological distress compared to the control group.
Our findings suggest that AI-integrated interventions like GymBuddy and Elomia may serve as effective tools for reducing psychological distress in student populations. Integrating AI technology into mental health interventions offers personalized support and guidance, addressing a crucial need in student populations. Further research is warranted to explore long-term outcomes and optimize the implementation of these interventions in educational settings.
包括集成人工智能的应用程序在内的数字心理健康干预措施越来越多地被用于帮助心理困扰症状加重的个体。然而，在了解其对学生群体的具体疗效方面仍存在差距。
本研究旨在调查一款名为GymBuddy的人工智能健身与责任追踪应用程序以及一款名为Elomia的人工智能心理健康聊天机器人对有心理困扰风险的学生心理健康的影响。
进行了一项准实验研究，涉及65名心理困扰加剧但未被正式诊断为心理障碍的参与者。参与者被随机分配到干预组或对照组，干预组使用GymBuddy和Elomia获得结构化心理健康支持。使用标准化的基线、中点和终点测量方法评估焦虑、抑郁和压力水平等心理健康结果。数据采用混合方差分析进行分析。
混合方差分析显示，所有测量的心理健康结果均有显著改善，包括躯体症状、焦虑和失眠、社会功能障碍以及重度抑郁。所有变量均观察到时间和组成员身份的显著主效应，表明总体症状减轻以及组间基线差异。此外，躯体症状（F(2, 70) = 59.96，p < 0.0001，η² = 0.63）、焦虑和失眠（F(2, 70) = 32.05，p < 0.0001，η² = 0.48）、社会功能障碍（F(2, 70) = 59.96，p < 0.0001，η² = 0.63）和重度抑郁（F(2, 70) = 32.05，p < 0.0001，η² = 0.48）的显著交互效应表明，与对照组相比，干预组参与者的心理困扰减轻程度显著更大。
我们的研究结果表明，像GymBuddy和Elomia这样的集成人工智能干预措施可能是减轻学生群体心理困扰的有效工具。将人工智能技术整合到心理健康干预中可提供个性化支持和指导，满足学生群体的一项关键需求。有必要进一步研究以探索长期结果并优化这些干预措施在教育环境中的实施。
