Avatar-based depression self-management technology: promising approach to improve depressive symptoms among young adults
Open accessAbstract
Major depressive disorder is prevalent among American young adults and predisposes young adults to serious impairments in psychosocial functioning. Without intervention, young adults with depressive symptoms are at high risk for worsening of depressive symptoms and developing major depressive disorder. Young adults are not routinely taught effective depression self management skills to reduce depressive symptoms and preempt future illness. This study reports initial results of a randomized controlled trial among young adults (18-25 years of age) with depressive symptoms who were exposed to an avatar-based depression self-management intervention, eSMART-MH. Participants completed self-report measures of depressive symptoms at baseline and at 4, 8, and 12 weeks follow-up. Participants who received eSMART-MH had a significant reduction in depressive symptoms over 3 months, while individuals in the attention-control condition had no change in symptoms. In this study, eSMART-MH demonstrated initial efficacy and is a promising developmentally appropriate depression self-management intervention for young adults.
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Numerous studies have been conducted to assess different aspects of using chatbots for mental health, such as effectiveness, acceptability, usability, and adoption.
“Numerous studies have been conducted to assess different aspects of using chatbots for mental health, such as effectiveness [15, 16], acceptability [14, 17], usability [18, 19], and adoption [20, 21].”
From An overview of the features of chatbots in mental health: A scoping review (2019) · cites this paper as [16]
Significant improvements were observed on measures of depression, psychological distress, anxiety, fear of heights, and positive affect.
“Significant improvements were observed on measures of depression [25,26,31], psychological distress [34], anxiety [26], fear of heights [23] and positive affect [26,34].”
From Conversational agents in the treatment of mental health problems: mixed-method systematic review (2019) · cites this paper as [31]
One study did not report any measures of engagement.
“One study [31] did not report any measures of engagement.”
From Conversational agents in the treatment of mental health problems: mixed-method systematic review (2019) · cites this paper as [31]
Five controlled studies reported significant posttreatment improvements in psychological distress in the intervention group compared with a no treatment or information control group.
“Of the 13 studies included, 5 controlled studies reported significant posttreatment improvements in psychological distress in the intervention group compared with a no treatment or information control group [23,25,26,31,34].”
From Conversational agents in the treatment of mental health problems: mixed-method systematic review (2019) · cites this paper as [31]
This provides some support for the utility of conversational agents in treating mild-to-moderate psychological distress in adults.
“This provides some support for the utility of conversational agents in treating mild-to-moderate psychological distress in adults [23,25,26,31,34].”
From Conversational agents in the treatment of mental health problems: mixed-method systematic review (2019) · cites this paper as [31]
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Cites
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An overview of the features of chatbots in mental health: A scoping review
Abd-alrazaq, A. A., Alajlani, M., Alalwan, A. A., Bewick, B. M., Gardner, P., & Househ, M. (2019) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2019.103978 · Cited by 605 · see citing works
Conversational agents in the treatment of mental health problems: mixed-method systematic review
Gaffney, H., Mansell, W., & Tai, S. (2019) · JMIR Mental Health · doi:10.2196/14166 · Cited by 275 · see citing works
He, Y., Yang, L., Qian, C., Li, T., Su, Z., Zhang, Q., & Hou, X. (2023) · Journal of Medical Internet Research · doi:10.2196/43862 · Cited by 213 · see citing works
Chatbot features for anxiety and depression: a scoping review
Ahmed, A., Hassan, A., Aziz, S., Abd-alrazaq, A. A., Ali, N., Alzubaidi, M., Al-Thani, D., Elhusein, B., Siddig, M. A., Ahmed, M., et al. (2023) · Health Informatics Journal · doi:10.1177/14604582221146719 · Cited by 82 · see citing works
Pinto, M. D., Greenblatt, A. M., Hickman, R. L., Rice, H. M., Thomas, T. L., & Clochesy, J. M. (2016) · Perspectives in Psychiatric Care · doi:10.1111/ppc.12112 · Cited by 46 · see citing works
Self-citationMancone, S., Diotaiuti, P., Valente, G., Corrado, S., Bellizzi, F., Vilarino, G. T., & Andrade, A. (2023) · Behavioral Sciences · doi:10.3390/bs13070550 · Cited by 14 · see citing works
- Authors
- Pinto, M. D., Hickman, R. L., Clochesy, J., & Buchner, M.
- Affiliations
- Case Western Reserve University (US)
- University of South Florida (US)
- Venue
- Applied Nursing Research
- Publisher
- Elsevier BV
- Published
- 2013-02
- Volume
- 26
- Issue
- 1
- Pages
- 45-48
- ISSN
- 0897-1897 (ISSN-L)
- PMC
- PMC3551988
- OpenAlex
- W2053033463
- Cited by
- 75
- References
- 9
- Citations by year
- 2025: 6 · 2024: 7 · 2023: 10 · 2022: 7 · 2021: 8 · 2020: 2 · 2019: 9 · 2018: 8 · 2017: 5 · 2016: 4 · 2015: 4 · 2014: 3 · 2013: 2
- FWCI
- 4.03
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Applied Nursing Research (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (KL2TR000440)
- National Institute of Mental Health (L30MH091738)
- National Center for Advancing Translational Sciences
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Keywords
- depressive symptoms, young adults, major depressive disorder, digital mental health interventions, intervention efficacy
- MeSH terms
- Adolescent, Adult, Depression, Humans, Longitudinal Studies, Self Care, Young Adult
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