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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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.
“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]
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Experimental — accuracy not yet measuredA growing number of studies report effectiveness of chatbots in improving symptoms of depression.
“depression [10,24,25]”
A growing number of studies report effectiveness of chatbots in reducing perceived stress.
“as well as their effectiveness in reducing perceived stress [16-25]”
A growing number of studies report effectiveness of chatbots in improving symptoms of anxiety.
“thereby improving symptoms of anxiety [10,23-25]”
Overall, our quantitative and qualitative findings are aligned with recent chatbot evaluation studies and will inform our design decisions for future developments.
“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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Chametka, P., Maqsood, S., & Chiasson, S. (2023) · Conference on Privacy, Security and Trust · doi:10.1109/pst58708.2023.10320174 · Cited by 12 · see citing works
“There are over 20 available mental health chatbots pur-portedly to help users manage different mental illnesses such as anxiety, postpartum depression, and substance abuse [5], [6], [7].”
BackgroundMethodA Review of Quality Assurance Research of Dialogue Systems
Li, X., Tao, C., Gao, J. Z., & Guo, H. (2022) · IEEE International Conference on Artificial Intelligence Testing (AITest) · doi:10.1109/aitest55621.2022.00021 · Cited by 12 · see citing works
“For example, Daley et al. [7] tried to evaluate the effectiveness of a mental health chatbot in reducing anxiety, depression and stress by collecting and analyzing the self-report scales of pre-and post-intervention respectively.”
BackgroundA conversational agent framework for mental health screening: design, implementation, and usability
Boian, R., Bucur, A.-M., Todea, D., Luca, A., Rebedea, T. E., & Podina, I. R. (2024) · Behaviour and Information Technology · doi:10.1080/0144929x.2024.2332934 · Cited by 11 · see citing works
“Other notable mentions include Vitalk (Daley et al. 2020; Hungerbuehler et al. 2021), Wysa (Inkster, Sarda, and Subramanian 2018), Woebot (Fitzpatrick, Darcy, and Vierhile 2017), Youper (Mehta et al. 2021), Owlie (Falala-Séchet et al. 2019), Help4Mood (Burton et al. 2016), and Elena + (Ollier et al. 2023).”
Mental Healthcare Chatbot Based on Custom Diagnosis Documents Using a Quantized Large Language Model
Kumar, A., Sharma, S., Gupta, S., & Kumar, D. (2024) · International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) · doi:10.1109/icrito61523.2024.10522371 · Cited by 10 · see citing works
“A preliminary evaluation of Vitalk, a mental health chatbot in Brazil, has demonstrated the potential of chatbots in reducing anxiety, depression, and stress symptoms [9].”
BackgroundEthical approval and informed consent in mental health research: a scoping review
Cilar, L., & Štiglic, G. (2025) · AI & Society · doi:10.1007/s00146-025-02364-0 · Cited by 10 · see citing works
“On the other hand, Daley et al. (2020) clarified that they did not pursue ethical approval for their study involving human participants, citing that it was not mandated by local laws or institutional guidelines.”
Aghakhani, S., Carre, N., Mostovoy, K., Shafer, R. W., Baeza‐Hernandez, K., Entenberg, G. A., Testerman, A., & Bunge, E. L. (2023) · Frontiers in Digital Health · doi:10.3389/fdgth.2023.1251016 · Cited by 8 · see citing works
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“In addition to relatively simple indicators of user engagement such as the frequency of user inputs and interactions [149, 150], measures like gaze patterns, backchannel responses (e.g., nodding, verbal acknowledgments such as “uh-huh”), facial expressions, and body postures can effectively serve…”
Anxiety Assistance Mobile Apps Chatbot Using Cognitive Behavioural Therapy
Sulaiman, S., Mansor, M., Wahid, R. A., & Azhar, N. A. A. N. (2022) · International Journal of Artificial Intelligence · doi:10.36079/lamintang.ijai-0901.349 · Cited by 7 · see citing works
“A study conducted in Brazil using a chatbot to improve mental health within one month shows a promising result [14].”
BackgroundKo, S., & Woo, H. (2025) · JMIR mhealth and uhealth · doi:10.2196/64622 · Cited by 6 · see citing works
Keyan, D., Hall, J., Jordan, S., Watts, S., Au, T. M., Dawson, K. S., Sway, R. A., Crawford, J., Sorsdahl, K. R., Luitel, N. P., et al. (2025) · Frontiers in Digital Health · doi:10.3389/fdgth.2025.1528580 · Cited by 10 · see citing works
“Iterative design development occurred throughout the cultural adaptation and re fi nement process.”
Aggarwal, A., Chen, S.-T., Lee, J., Tracy, A., Qiao, S., Li, X.-M., & Yang, C.-H. (2024) · Mental Health Science · doi:10.1002/mhs2.55 · Cited by 3 · see citing works
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“Among other groups, primarily general adult populations residing in underserved areas [40, 41, 44, 45] the topics examined included mental health [41, 45] promotion of healthy lifestyles [40] and HIV prevention [44].”
InfluentialMental Health Status and Influencing Factors of College Students
Yang, L. (2023) · International Journal of Fuzzy System Applications · doi:10.4018/ijfsa.334233 · Cited by 5 · see citing works
“The SCL-90 uses a simple and straightforward way, which is easy to be understood by the respondents (Daley et al., 2020).”
MethodKleinau, E., Lamba, T., Jaskiewicz, W., Gorentz, K., Hungerbuehler, I., Rahimi, D., Kokota, D., Maliwichi, L., Jamu, E. S., Zumazuma, A., et al. (2023) · medRxiv · doi:10.1101/2023.01.24.23284959 · Cited by 5 · see citing works
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Agrawal, R. N., Monteiro, K., Narasimhamurti, N. S., Sharma, S., Suryawanshi, A., Bariya, A., Narvekar, S., Bagnoli, L., Saxena, M., Magoun, L., et al. (2025) · JMIR Formative Research · doi:10.2196/73563 · Cited by 4 · see citing works
“The use of the chatbot improved the overall treatment experience for patients, and the findings are consistent with those of other chatbot studies [36,37].”
Hopman, K., Richards, D., & Norberg, M. M. (2025) · Behaviour and Information Technology · doi:10.1080/0144929x.2025.2477757 · Cited by 4 · see citing works
“Digital technology has been widely promoted as offering potential opportunity to tackle both structural (location and availability of services) and attitudinal (perceived stigma in accessing psychological services) barriers (Daley et al. 2020; Tiel-man et al. 2017).”
Quantum-Powered Industry 6.0 Innovations for Enhanced Catastrophe Management
Das, S., Chowdhury, A., & Sil, R. (2024) · Advances in Science, Technology & Innovation/Advances in science, technology & innovation · doi:10.1007/978-3-031-73350-5_5 · Cited by 4 · see citing works
Why Would University Students Use ChatGPT for Health Discourses? A Moderated Mediation Analysis
Vu, C. B., & Park, D. Y. (2025) · Journal of Consumer Health on the Internet · doi:10.1080/15398285.2025.2491042 · Cited by 4 · see citing works
“They have proven to be a scalable substitute for mental health support, such as alleviating symptoms of stress, anxiety, and depression by providing appropriate responses based on users’ input (Daley et al. 2020; Park and Kim 2023; Raile 2024).”
Inclusive AI-Driven Music Chatbots for Older Adults
Aziz, F., Law, E. L., Li, L., & Chen, S. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-91760-8_6 · Cited by 3 · see citing works
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Koch, A., Graczykowska, A., Szumiał, S., Rudnicka, P., & Marszał‐Wiśniewska, M. (2024) · Clinical Psychology & Psychotherapy · doi:10.1002/cpp.3055 · Cited by 3 · see citing works
COVID-19 and Psychological Distress in Africa
Ndasauka, Y. (2023) · Routledge eBooks · doi:10.4324/9781003425861 · Cited by 3 · see citing works
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“These expected results will contribute to the growing literature that supports CA use in improving health-and wellness-related outcome (Daley, 2020; Fitzpatrick et al., 2017; Gardiner et al., 2017; Hudlicka, 2013).”
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Meinert, E., Milne‐Ives, M., Taylor, E., Inkster, B., Paik, A., Ananthakrishnan, A., Orr, M., Costelloe, C., & Shankar, R. (2026) · International Journal of Social Psychiatry · doi:10.1177/00207640251415507 · Cited by 3 · see citing works
“…for digital health interventions (Baumel et al., 2019; Birnbaum et al., 2015; Meyerowitz-Katz et al., 2020; Pratap et al., 2020; Torous et al., 2020; Yeager & Benight, 2018) and engagement has been positively associated with improved mental health (Daley et al., 2020; Inkster et al., 2018).”
Depiction of conversational agents as health professionals: a scoping review
MacNeill, A. L., MacNeill, L., Yi, S., Goudreau, A., Luke, A., & Doucet, S. A. (2024) · JBI Evidence Synthesis · doi:10.11124/jbies-23-00029 · Cited by 2 · see citing works
Mustafa, S. H., Mohammed, E. A., CII SBPM Residency Program, R., Salih, A. M., Palani, K., CII SBPM Residency Program, R., Albushra, M. M. O., Makkawi, S. T., CII SBPM Residency Program, R., & Mustafa, A. H. (2024) · International Journal of Medical Sciences and Nursing Research · doi:10.55349/ijmsnr.2024411623 · Cited by 2 · see citing works
“[6, 7, 9, 22, 23] According to therapists, chatbots have the potential to enhance patient engagement in therapy goals and assist in completing assigned tasks, leading to faster progress.”
BackgroundAI and VR-Powered Interventions for Social Anxiety
Boadu, D. O., Boafo, F., Owusu-Ansah, L. A., & Mensah, S. (2025) · International Journal of Virtual and Augmented Reality · doi:10.4018/ijvar.367871 · Cited by 1 · see citing works
Personalized Mental Health Assistance: Integrating Emotion Prediction with GPT-Based Chatbot
A, M. K. K., Sekar, R., Abinaya, R., & Vijayaprabakaran, K. (2025) · IEEE International Students' Conference on Electrical, Electronics and Computer Science (SCEECS) · doi:10.1109/sceecs64059.2025.10940203 · Cited by 1 · see citing works
“Cameron et al [8] outlined the development of an interactive chatbot to assist mental health providers through digital intervention.”
Cheng, J., & Liao, Z. (2026) · Current Psychology · doi:10.1007/s12144-025-08680-4 · Cited by 1 · see citing works
“Third, research has assessed CAI effectiveness on patients’ mental health (Daley et al., 2020; Ogawa et al., 2022; Sabour et al., 2023 ; Tawfik et al., 2023; Wrightson-Hester et al., 2023).”
PsyRA – A Retrieval-Augmented Dialogue System for Mental Health Support
Hassaan, M., Shah, M. S. A., Uzaif, M., Afridi, Y. S., & Khattak, R. U. (2025) · International Journal of Innovations in Science and Technology · doi:10.33411/ijist/1365 · Cited by 1 · see citing works
A interação homem-máquina na psicoterapia
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Use of Chatbots to Support the Inclusion of People With Autism Spectrum Disorder
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De preguntas a soluciones: Innovación y sostenibilidad
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Agrawal, R. N., Monteiro, K., Narasimhamurti, N. S., Sharma, S., Suryawanshi, A., Bariya, A., Narvekar, S., Bagnoli, L., Saxena, M., Magoun, L., et al. (2024) · Research Square · doi:10.21203/rs.3.rs-5426475/v1 · Cited by 1 · see citing works
Design of a Social Chatbot with Gamification for user Profiling and Smoking Trigger Detection
Bosschaerts, K., Stragier, J., Steenwinckel, B., Marez, L. D., Hoecke, S. V., & Ongenae, F. (2023) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-031-34586-9_42
Health Worker Experiences of Using Digital Resources for the Improvement of Mental Well-Being
Lamba, T., Jamu, E. S., Kokota, D., Maliwichi, L., Zumazuma, A., Kleinau, E., Gorentz, K., Jaskiewicz, W., Rahimi, D., & Kapps, M. (2023) · Routledge eBooks · doi:10.4324/9781003425861-18
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A Structured Literature Review on Conversational Agents that Empower Health Interventions
Pietrantoni, N. (2023) · International Conference on Information Systems and Software Technologies (ICI2ST) · doi:10.1109/ici2st62251.2023.00024
“…B e h av i o r Emotion [67], [68], [70], [72], [73], [75], [85], [94]–[96], [98], [99], [102], [105], [107], [108], [110] Stress/Relaxation [63], [68], [83], [86], [89], [105], [108] Motivation [22], [63], [71], [73], [80], [83], [89], [93], [104], [109] Engagement [69], [73] Patient knowledge…”
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“A growing number of studies are reporting their acceptability and feasibility for users [57,58], as well as their effectiveness in reducing perceived stress [54], thereby improving symptoms of anxiety [59-61], depression [60,61], and insomnia [62].”
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Breathe and Relax: An Alexa-Based Voice Intervention for Stress Reduction and Emotional Well-Being
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“With the advancements in generative artificial intelligence (AI), chatbot technology represents a significant shift in therapeutic intervention, providing both immediacy and cost-effectiveness [26, 112].”
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“Mental health care stands out as an area where AI chatbots can offer continuous and personalized support for conditions like depression, anxiety, and ADHD [11], [15], [20], [21], [23], [27].”
MIbot: A Technological Solution to Mental Health Crisis of Prison Personnel
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NeuroBloom: Where AI Meets Inner Peace
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“Initially, digital mental health technologies predominantly utilized manual self-assessment techniques such as mood diaries and standardized questionnaires [8].”
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MediMate AI Health Companion with Memory-Driven Personalization
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“Daley et al [8] created a method to assess engagement and efficacy of the previously generated Chatbot Vitalk.”
Potel, J. T., & Kumashiro, M. (2026) · Behavioral Sciences · doi:10.3390/bs16081431
“…health chatbots over one month correlated with a significant reduction in stress, anxiety, and depression; in fact, roughly half of the participants who began the study with clinical symptoms ended the study a month later with their symptoms no longer flagging clinical concern (Daley et al., 2020).”
- 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
- Social Sciences › Psychology › Social Psychology › 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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