A scalable mental health intervention for depressive symptoms: evidence from a randomized controlled trial and large-scale real-world studies
Abstract Depressive symptoms pose a serious global threat to well-being, highlighting the need for scalable mental health interventions. E-mental health interventions offer promising population-level solutions, yet few are grounded in theory or tested on large samples. This study utilizes an innovat...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-08-01
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| Series: | npj Digital Medicine |
| Online Access: | https://doi.org/10.1038/s41746-025-01888-5 |
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| author | Jianjie Xu Zhuo Rachel Han Xiangxi Lv Lu Chen Ningning Mao Mengyu Miranda Gao Hanyi Zhang Yueqin Hu Shaozheng Qin James J. Gross Zhanjun Zhang |
| author_facet | Jianjie Xu Zhuo Rachel Han Xiangxi Lv Lu Chen Ningning Mao Mengyu Miranda Gao Hanyi Zhang Yueqin Hu Shaozheng Qin James J. Gross Zhanjun Zhang |
| author_sort | Jianjie Xu |
| collection | DOAJ |
| description | Abstract Depressive symptoms pose a serious global threat to well-being, highlighting the need for scalable mental health interventions. E-mental health interventions offer promising population-level solutions, yet few are grounded in theory or tested on large samples. This study utilizes an innovative e-mental health intervention based on the Extended Process Model of Emotion Regulation and examines the effectiveness of this theory-based intervention across a randomized controlled trial (RCT, N = 187; Chinese Clinical Trial Registry: ChiCTR2400081964; registration date: March 18th, 2024) and two extensive real-world studies (N study 2 = 11,554, N study 3 = 44,018) conducted with adults in China. The RCT confirmed the efficacy of this intervention, and both of the real-world e-mental health intervention studies showed a decrease in depressive symptoms (35–36%) and an increase in well-being (14–16%) over 21 days. These findings highlight the potential of theory-based e-mental health interventions as scalable solutions for early depression intervention and prevention, offering substantial societal and economic advantages. |
| format | Article |
| id | doaj-art-edff081f37fe409ba520ecb32ea09f67 |
| institution | Kabale University |
| issn | 2398-6352 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Digital Medicine |
| spelling | doaj-art-edff081f37fe409ba520ecb32ea09f672025-08-20T04:02:44ZengNature Portfolionpj Digital Medicine2398-63522025-08-018111510.1038/s41746-025-01888-5A scalable mental health intervention for depressive symptoms: evidence from a randomized controlled trial and large-scale real-world studiesJianjie Xu0Zhuo Rachel Han1Xiangxi Lv2Lu Chen3Ningning Mao4Mengyu Miranda Gao5Hanyi Zhang6Yueqin Hu7Shaozheng Qin8James J. Gross9Zhanjun Zhang10Beijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education, National Virtual Simulation Center for Experimental Psychology Education, Faculty of Psychology, Beijing Normal UniversityBeijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education, National Virtual Simulation Center for Experimental Psychology Education, Faculty of Psychology, Beijing Normal UniversityBeijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education, National Virtual Simulation Center for Experimental Psychology Education, Faculty of Psychology, Beijing Normal UniversityBeijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education, National Virtual Simulation Center for Experimental Psychology Education, Faculty of Psychology, Beijing Normal UniversityBeijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education, National Virtual Simulation Center for Experimental Psychology Education, Faculty of Psychology, Beijing Normal UniversityFaculty of Psychology, Beijing Normal UniversityBeijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education, National Virtual Simulation Center for Experimental Psychology Education, Faculty of Psychology, Beijing Normal UniversityFaculty of Psychology, Beijing Normal UniversityIDG/McGovern Institute for Brain Research & State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal UniversityDepartment of Psychology, Stanford UniversityIDG/McGovern Institute for Brain Research & State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal UniversityAbstract Depressive symptoms pose a serious global threat to well-being, highlighting the need for scalable mental health interventions. E-mental health interventions offer promising population-level solutions, yet few are grounded in theory or tested on large samples. This study utilizes an innovative e-mental health intervention based on the Extended Process Model of Emotion Regulation and examines the effectiveness of this theory-based intervention across a randomized controlled trial (RCT, N = 187; Chinese Clinical Trial Registry: ChiCTR2400081964; registration date: March 18th, 2024) and two extensive real-world studies (N study 2 = 11,554, N study 3 = 44,018) conducted with adults in China. The RCT confirmed the efficacy of this intervention, and both of the real-world e-mental health intervention studies showed a decrease in depressive symptoms (35–36%) and an increase in well-being (14–16%) over 21 days. These findings highlight the potential of theory-based e-mental health interventions as scalable solutions for early depression intervention and prevention, offering substantial societal and economic advantages.https://doi.org/10.1038/s41746-025-01888-5 |
| spellingShingle | Jianjie Xu Zhuo Rachel Han Xiangxi Lv Lu Chen Ningning Mao Mengyu Miranda Gao Hanyi Zhang Yueqin Hu Shaozheng Qin James J. Gross Zhanjun Zhang A scalable mental health intervention for depressive symptoms: evidence from a randomized controlled trial and large-scale real-world studies npj Digital Medicine |
| title | A scalable mental health intervention for depressive symptoms: evidence from a randomized controlled trial and large-scale real-world studies |
| title_full | A scalable mental health intervention for depressive symptoms: evidence from a randomized controlled trial and large-scale real-world studies |
| title_fullStr | A scalable mental health intervention for depressive symptoms: evidence from a randomized controlled trial and large-scale real-world studies |
| title_full_unstemmed | A scalable mental health intervention for depressive symptoms: evidence from a randomized controlled trial and large-scale real-world studies |
| title_short | A scalable mental health intervention for depressive symptoms: evidence from a randomized controlled trial and large-scale real-world studies |
| title_sort | scalable mental health intervention for depressive symptoms evidence from a randomized controlled trial and large scale real world studies |
| url | https://doi.org/10.1038/s41746-025-01888-5 |
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