Mental Health Chatbot for Young Adults With Depressive Symptoms During the COVID-19 Pandemic: Single-Blind, Three-Arm Randomized Controlled Trial
BackgroundDepression has a high prevalence among young adults, especially during the COVID-19 pandemic. However, mental health services remain scarce and underutilized worldwide. Mental health chatbots are a novel digital technology to provide fully automated interventions fo...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
JMIR Publications
2022-11-01
|
| Series: | Journal of Medical Internet Research |
| Online Access: | https://www.jmir.org/2022/11/e40719 |
| _version_ | 1797734572017844224 |
|---|---|
| author | Yuhao He Li Yang Xiaokun Zhu Bin Wu Shuo Zhang Chunlian Qian Tian Tian |
| author_facet | Yuhao He Li Yang Xiaokun Zhu Bin Wu Shuo Zhang Chunlian Qian Tian Tian |
| author_sort | Yuhao He |
| collection | DOAJ |
| description |
BackgroundDepression has a high prevalence among young adults, especially during the COVID-19 pandemic. However, mental health services remain scarce and underutilized worldwide. Mental health chatbots are a novel digital technology to provide fully automated interventions for depressive symptoms.
ObjectiveThe purpose of this study was to test the clinical effectiveness and nonclinical performance of a cognitive behavioral therapy (CBT)–based mental health chatbot (XiaoE) for young adults with depressive symptoms during the COVID-19 pandemic.
MethodsIn a single-blind, 3-arm randomized controlled trial, participants manifesting depressive symptoms recruited from a Chinese university were randomly assigned to a mental health chatbot (XiaoE; n=49), an e-book (n=49), or a general chatbot (Xiaoai; n=50) group in a ratio of 1:1:1. Participants received a 1-week intervention. The primary outcome was the reduction of depressive symptoms according to the 9-item Patient Health Questionnaire (PHQ-9) at 1 week later (T1) and 1 month later (T2). Both intention-to-treat and per-protocol analyses were conducted under analysis of covariance models adjusting for baseline data. Controlled multiple imputation and δ-based sensitivity analysis were performed for missing data. The secondary outcomes were the level of working alliance measured using the Working Alliance Questionnaire (WAQ), usability measured using the Usability Metric for User Experience-LITE (UMUX-LITE), and acceptability measured using the Acceptability Scale (AS).
ResultsParticipants were on average 18.78 years old, and 37.2% (55/148) were female. The mean baseline PHQ-9 score was 10.02 (SD 3.18; range 2-19). Intention-to-treat analysis revealed lower PHQ-9 scores among participants in the XiaoE group compared with participants in the e-book group and Xiaoai group at both T1 (F2,136=17.011; P<.001; d=0.51) and T2 (F2,136=5.477; P=.005; d=0.31). Better working alliance (WAQ; F2,145=3.407; P=.04) and acceptability (AS; F2,145=4.322; P=.02) were discovered with XiaoE, while no significant difference among arms was found for usability (UMUX-LITE; F2,145=0.968; P=.38).
ConclusionsA CBT-based chatbot is a feasible and engaging digital therapeutic approach that allows easy accessibility and self-guided mental health assistance for young adults with depressive symptoms. A systematic evaluation of nonclinical metrics for a mental health chatbot has been established in this study. In the future, focus on both clinical outcomes and nonclinical metrics is necessary to explore the mechanism by which mental health chatbots work on patients. Further evidence is required to confirm the long-term effectiveness of the mental health chatbot via trails replicated with a longer dose, as well as exploration of its stronger efficacy in comparison with other active controls.
Trial RegistrationChinese Clinical Trial Registry ChiCTR2100052532; http://www.chictr.org.cn/showproj.aspx?proj=135744 |
| first_indexed | 2024-03-12T12:46:18Z |
| format | Article |
| id | doaj.art-4b9a1f9aea4340f681c331f9cef18a00 |
| institution | Directory Open Access Journal |
| issn | 1438-8871 |
| language | English |
| last_indexed | 2024-03-12T12:46:18Z |
| publishDate | 2022-11-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | Journal of Medical Internet Research |
| spelling | doaj.art-4b9a1f9aea4340f681c331f9cef18a002023-08-28T23:18:56ZengJMIR PublicationsJournal of Medical Internet Research1438-88712022-11-012411e4071910.2196/40719Mental Health Chatbot for Young Adults With Depressive Symptoms During the COVID-19 Pandemic: Single-Blind, Three-Arm Randomized Controlled TrialYuhao Hehttps://orcid.org/0000-0003-3969-7530Li Yanghttps://orcid.org/0000-0002-7947-0392Xiaokun Zhuhttps://orcid.org/0000-0002-4072-3778Bin Wuhttps://orcid.org/0000-0001-8349-0188Shuo Zhanghttps://orcid.org/0000-0001-5621-6300Chunlian Qianhttps://orcid.org/0000-0001-7389-092XTian Tianhttps://orcid.org/0000-0003-4197-3186 BackgroundDepression has a high prevalence among young adults, especially during the COVID-19 pandemic. However, mental health services remain scarce and underutilized worldwide. Mental health chatbots are a novel digital technology to provide fully automated interventions for depressive symptoms. ObjectiveThe purpose of this study was to test the clinical effectiveness and nonclinical performance of a cognitive behavioral therapy (CBT)–based mental health chatbot (XiaoE) for young adults with depressive symptoms during the COVID-19 pandemic. MethodsIn a single-blind, 3-arm randomized controlled trial, participants manifesting depressive symptoms recruited from a Chinese university were randomly assigned to a mental health chatbot (XiaoE; n=49), an e-book (n=49), or a general chatbot (Xiaoai; n=50) group in a ratio of 1:1:1. Participants received a 1-week intervention. The primary outcome was the reduction of depressive symptoms according to the 9-item Patient Health Questionnaire (PHQ-9) at 1 week later (T1) and 1 month later (T2). Both intention-to-treat and per-protocol analyses were conducted under analysis of covariance models adjusting for baseline data. Controlled multiple imputation and δ-based sensitivity analysis were performed for missing data. The secondary outcomes were the level of working alliance measured using the Working Alliance Questionnaire (WAQ), usability measured using the Usability Metric for User Experience-LITE (UMUX-LITE), and acceptability measured using the Acceptability Scale (AS). ResultsParticipants were on average 18.78 years old, and 37.2% (55/148) were female. The mean baseline PHQ-9 score was 10.02 (SD 3.18; range 2-19). Intention-to-treat analysis revealed lower PHQ-9 scores among participants in the XiaoE group compared with participants in the e-book group and Xiaoai group at both T1 (F2,136=17.011; P<.001; d=0.51) and T2 (F2,136=5.477; P=.005; d=0.31). Better working alliance (WAQ; F2,145=3.407; P=.04) and acceptability (AS; F2,145=4.322; P=.02) were discovered with XiaoE, while no significant difference among arms was found for usability (UMUX-LITE; F2,145=0.968; P=.38). ConclusionsA CBT-based chatbot is a feasible and engaging digital therapeutic approach that allows easy accessibility and self-guided mental health assistance for young adults with depressive symptoms. A systematic evaluation of nonclinical metrics for a mental health chatbot has been established in this study. In the future, focus on both clinical outcomes and nonclinical metrics is necessary to explore the mechanism by which mental health chatbots work on patients. Further evidence is required to confirm the long-term effectiveness of the mental health chatbot via trails replicated with a longer dose, as well as exploration of its stronger efficacy in comparison with other active controls. Trial RegistrationChinese Clinical Trial Registry ChiCTR2100052532; http://www.chictr.org.cn/showproj.aspx?proj=135744https://www.jmir.org/2022/11/e40719 |
| spellingShingle | Yuhao He Li Yang Xiaokun Zhu Bin Wu Shuo Zhang Chunlian Qian Tian Tian Mental Health Chatbot for Young Adults With Depressive Symptoms During the COVID-19 Pandemic: Single-Blind, Three-Arm Randomized Controlled Trial Journal of Medical Internet Research |
| title | Mental Health Chatbot for Young Adults With Depressive Symptoms During the COVID-19 Pandemic: Single-Blind, Three-Arm Randomized Controlled Trial |
| title_full | Mental Health Chatbot for Young Adults With Depressive Symptoms During the COVID-19 Pandemic: Single-Blind, Three-Arm Randomized Controlled Trial |
| title_fullStr | Mental Health Chatbot for Young Adults With Depressive Symptoms During the COVID-19 Pandemic: Single-Blind, Three-Arm Randomized Controlled Trial |
| title_full_unstemmed | Mental Health Chatbot for Young Adults With Depressive Symptoms During the COVID-19 Pandemic: Single-Blind, Three-Arm Randomized Controlled Trial |
| title_short | Mental Health Chatbot for Young Adults With Depressive Symptoms During the COVID-19 Pandemic: Single-Blind, Three-Arm Randomized Controlled Trial |
| title_sort | mental health chatbot for young adults with depressive symptoms during the covid 19 pandemic single blind three arm randomized controlled trial |
| url | https://www.jmir.org/2022/11/e40719 |
| work_keys_str_mv | AT yuhaohe mentalhealthchatbotforyoungadultswithdepressivesymptomsduringthecovid19pandemicsingleblindthreearmrandomizedcontrolledtrial AT liyang mentalhealthchatbotforyoungadultswithdepressivesymptomsduringthecovid19pandemicsingleblindthreearmrandomizedcontrolledtrial AT xiaokunzhu mentalhealthchatbotforyoungadultswithdepressivesymptomsduringthecovid19pandemicsingleblindthreearmrandomizedcontrolledtrial AT binwu mentalhealthchatbotforyoungadultswithdepressivesymptomsduringthecovid19pandemicsingleblindthreearmrandomizedcontrolledtrial AT shuozhang mentalhealthchatbotforyoungadultswithdepressivesymptomsduringthecovid19pandemicsingleblindthreearmrandomizedcontrolledtrial AT chunlianqian mentalhealthchatbotforyoungadultswithdepressivesymptomsduringthecovid19pandemicsingleblindthreearmrandomizedcontrolledtrial AT tiantian mentalhealthchatbotforyoungadultswithdepressivesymptomsduringthecovid19pandemicsingleblindthreearmrandomizedcontrolledtrial |