{"title":"人工智能集成应用GymBuddy和Elomia对心理障碍学生心理健康的影响","authors":"Jing Jiang, Yang Yang","doi":"10.1186/s40359-025-02640-0","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Objectives: </strong>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.</p><p><strong>Methodology: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":37867,"journal":{"name":"BMC Psychology","volume":"13 1","pages":"350"},"PeriodicalIF":2.7000,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"GymBuddy and Elomia, AI-integrated applications, effects on the mental health of the students with psychological disorders.\",\"authors\":\"Jing Jiang, Yang Yang\",\"doi\":\"10.1186/s40359-025-02640-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Objectives: </strong>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.</p><p><strong>Methodology: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>\",\"PeriodicalId\":37867,\"journal\":{\"name\":\"BMC Psychology\",\"volume\":\"13 1\",\"pages\":\"350\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2025-04-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BMC Psychology\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.1186/s40359-025-02640-0\",\"RegionNum\":3,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PSYCHOLOGY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Psychology","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1186/s40359-025-02640-0","RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, MULTIDISCIPLINARY","Score":null,"Total":0}
GymBuddy and Elomia, AI-integrated applications, effects on the mental health of the students with psychological disorders.
Background: 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.
Objectives: 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.
Methodology: 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.
Results: 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.
Conclusions: 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.
期刊介绍:
BMC Psychology is an open access, peer-reviewed journal that considers manuscripts on all aspects of psychology, human behavior and the mind, including developmental, clinical, cognitive, experimental, health and social psychology, as well as personality and individual differences. The journal welcomes quantitative and qualitative research methods, including animal studies.