The DOI matches its Crossref record; 34 of the 35 references it cites were found in a registry or an index.
Preliminary Evaluation of the Engagement and Effectiveness of a Mental Health Chatbot
Open accessAbstract
Background: Mental health difficulties are highly prevalent, yet access to support is limited by barriers of stigma, cost, and availability. These issues are even more prevalent in low- and middle-income countries, and digital technology is one potential way to overcome these barriers. Digital mental health interventions are effective but often struggle with low engagement rates, particularly in the absence of human support. Chatbots could offer a scalable solution, simulating human support at a lower cost. Objective: To complete a preliminary evaluation of engagement and effectiveness of Vitalk, a mental health chatbot, at reducing anxiety, depression and stress. Methods: Real world data was analyzed from 3,629 Vitalk users who had completed the first phase of a Vitalk program (“less anxiety,” “less stress” or “better mood”). Programs were delivered through written conversation with a chatbot. Engagement was calculated from the number of responses sent to the chatbot divided by days in the program. Results: Users sent an average of 8.17 responses per day. For all three programs, target outcome scores reduced between baseline and follow up with large effect sizes for anxiety (Cohen's d = −0.85), depression (Cohen's d = −0.91) and stress (Cohen's d = −0.81). Increased engagement resulted in improved post-intervention values for anxiety and depression. Conclusion: This study highlights a chatbot's potential to reduce mental health symptoms in the general population within Brazil. While findings show promise, further research is required.
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“These intervention strategies based on positive psychology, CBT, and mindfulness practices have been recently deployed by fully automated conversational agents targeting anxiety, stress, and depression, with promising results in terms of efficacy and acceptability by users [10,16,24,25].”
From Engagement and effectiveness of a healthy-coping intervention via chatbot for university students during the COVID-19 pandemic: Mixed methods proof-of-concept study (2021) · cites this paper as [25]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
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“depression [10,24,25]”
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“as well as their effectiveness in reducing perceived stress [16-25]”
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“thereby improving symptoms of anxiety [10,23-25]”
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“Overall, our quantitative and qualitative findings are aligned with recent chatbot evaluation studies [10,23-25] and will inform our design decisions for future developments.”
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Cites
Statistical Power Analysis for the Behavioral Sciences
Muller, K. E., & Cohen, J. (1989) · Technometrics · doi:10.2307/1270020 · Cited by 99,603
The PHQ-9: Validity of a brief depression severity measure
Kroenke, K., Spitzer, R. L., & Williams, J. B. W. (2001) · Journal of General Internal Medicine · doi:10.1046/j.1525-1497.2001.016009606.x · Cited by 44,910
A Brief Measure for Assessing Generalized Anxiety Disorder: The GAD-7
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“The total scores are divided into four categories: none (0–4), mild (5–9), moderate (10–14) and severe (15+) symptoms (20, 21).”
BackgroundLovibond, P. F., & Lovibond, S. H. (1995) · Behaviour Research and Therapy · doi:10.1016/0005-7967(94)00075-u · Cited by 14,523 · cited 1×
“Total scores are doubled and divided into five categories: normal (0–14), mild (15–18), moderate (19–25), severe (26–33) and extremely severe (34+) levels of stress (24, 25).”
BackgroundJacobson, N. S., & Truax, P. (1991) · Journal of Consulting and Clinical Psychology · doi:10.1037/0022-006x.59.1.12 · Cited by 7,770 · cited 1×
“Spre is the standard deviation of pre-intervention values and r is the reliability obtained in validation studies of each scale (28).”
MethodFitzpatrick, K. K., Darcy, A., & Vierhile, M. (2017) · JMIR Mental Health · doi:10.2196/mental.7785 · Cited by 2,730
Barriers to mental health treatment: results from the WHO World Mental Health surveys
Andrade, L. H., Alonso, J., Mneimneh, Z., Wells, J. E., Al-Hamzawi, A., Borges, G., Bromet, E., Bruffaerts, R., de Girolamo, G., de Graaf, R., et al. (2014) · Psychological Medicine · doi:10.1017/s0033291713001943 · Cited by 1,289 · cited 1×
“Reasons cited for this discrepancy include structural barriers such as a lack of availability, high cost and attitudinal barriers such as perceived stigma (3, 4).”
BackgroundInkster, B., Sarda, S., & Subramanian, V. (2018) · doi:10.2196/preprints.12106 · Cited by 1,063
Chatbots and Conversational Agents in Mental Health: A Review of the Psychiatric Landscape
Vaidyam, A. N., Wisniewski, H., Halamka, J. D., Kashavan, M. S., & Torous, J. B. (2019) · The Canadian Journal of Psychiatry · doi:10.1177/0706743719828977 · Cited by 1,048 · cited 3×
“The use of chatbots appears feasible and acceptable to users (15, 16), but there is less certainty on effectiveness.”
BackgroundThe impact of guidance on Internet-based mental health interventions — A systematic review
Baumeister, H., Reichler, L., Munzinger, M., & Lin, J. (2014) · Internet Interventions · doi:10.1016/j.invent.2014.08.003 · Cited by 1,037
Flagged first, then by citations
1 of the 35 references couldn’t be matched to a known paper.
Research works printed but not linked: 2
- 2018, The Burden of Mental Disorders in the Region of the Americas
- Beck, 2011, Cognitive Behavior Therapy, Second Edition: Basics and Beyond, 391
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Items 101–101 of 101
Yaacob, N. M., Doheir, M., Algumaei, A. H., Al-Andoli, M. N., Alsayaydeh, J. A. J., Elzamly, A., & Basari, A. S. (2026) · Frontiers in Child and Adolescent Psychiatry · doi:10.3389/frcha.2026.1905782
“A three-step search strategy and standardized procedures for screening and data charting were applied.”
Influential
Metadata
- Authors
- Daley, K., Hungerbuehler, I., Cavanagh, K., Claro, H. G., Swinton, P. A., & Kapps, M.
- Affiliations
- University of Sussex (GB)
- Universidade de São Paulo (BR)
- Robert Gordon University (GB)
- Corresponding author
- Daley, Kate
- ORCID
- Venue
- Frontiers in Digital Health
- Publisher
- Frontiers Media SA
- Published
- 2020-11-30
- Volume
- 2
- Pages
- 576361-576361
- ISSN
- 2673-253X (ISSN-L)
- PMC
- PMC8521874
- OpenAlex
- W3110570584
- Cited by
- 101
- References
- 35
- Citations by year
- 2026: 15 · 2025: 29 · 2024: 26 · 2023: 24 · 2022: 5 · 2021: 2
- FWCI
- 6.99
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Digital Health (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Sussex Research Online (University of Sussex) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Open Access Institutional Repository at Robert Gordon University (Robert Gordon University) (submittedVersion, cc-by)
- OSF Preprints (OSF Preprints) (submittedVersion)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Medicine › Psychiatry and Mental health › Mental Health Treatment and Access
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Keywords
- mental health chatbots, user engagement, anxiety, depression, stress, digital mental health interventions, low- and middle-income countries, Brazil
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