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Reporting Mental Health Symptoms: Breaking Down Barriers to Care with Virtual Human Interviewers
Open accessAbstract
A common barrier to healthcare for psychiatric conditions is the stigma associated with these disorders. Perceived stigma prevents many from reporting their symptoms. Stigma is a particularly pervasive problem among military service members, preventing them from reporting symptoms of combat-related conditions like posttraumatic stress disorder (PTSD). However, research shows increased reporting by service members when anonymous assessments are used. For example, service members report more symptoms of PTSD when they anonymously answer the Post-Deployment Health Assessment (PDHA) symptom checklist compared to the official PDHA, which is identifiable and linked to their military records. To investigate the factors that influence reporting of psychological symptoms by service members, we used a transformative technology: automated virtual humans that interview people about their symptoms. Such virtual human interviewers allow simultaneous use of two techniques for eliciting disclosure that would otherwise be incompatible; they afford anonymity while also building rapport. We examined whether virtual human interviewers could increase disclosure of mental health symptoms among active-duty service members that just returned from a year-long deployment in Afghanistan. Service members reported more symptoms during a conversation with a virtual human interviewer than on the official PDHA. They also reported more to a virtual human interviewer than on an anonymized PDHA. A second, larger sample of active-duty and former service members found a similar effect that approached statistical significance. Because respondents in both studies shared more with virtual human interviewers than an anonymized PDHA -even though both conditions control for stigma and ramifications for service members’ military records- virtual human interviewers that build rapport may provide a superior option to encourage reporting.
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“Researchers further found that relational agents, which were built based on the theory of rapport, can induce users' openness (77, 78).”
From Digital Therapeutic Alliance With Fully Automated Mental Health Smartphone Apps: A Narrative Review (2022) · cites this paper as [78]
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“It is purported that embodiment makes conversations with chatbots more empathetic and facilitates effective rapport with users [19,42,43].”
From Effectiveness and safety of using chatbots to improve mental health: systematic review and meta-analysis (2020) · cites this paper as [42]
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“This may make artificial intelligence chatbots more effective in building rapport with users, thereby improving their mental health [42].”
From Effectiveness and safety of using chatbots to improve mental health: systematic review and meta-analysis (2020) · cites this paper as [42]
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“chatbots may encourage interaction by those who have traditionally been reluctant to seek mental health advice due to stigmatization [6, 12].”
From An overview of the features of chatbots in mental health: A scoping review (2019) · cites this paper as [12]
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“Most previous chatbot research relied on either finite-state (ie, dialog consisting of a sequence of predetermined steps or states) or frame-based systems (ie, dialog is not predetermined but dependent on the content of the user’s input and the information that the system has to elicit) [34-36].”
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Citations
Cites
Combat Duty in Iraq and Afghanistan, Mental Health Problems, and Barriers to Care
Hoge, C. W., Castro, C. A., Messer, S. C., McGurk, D., Cotting, D. I., & Koffman, R. L. (2004) · New England Journal of Medicine · doi:10.1056/nejmoa040603 · Cited by 4,778
Psychometric properties of the PTSD checklist (PCL)
Blanchard, E. B., Jones-Alexander, J., Buckley, T. C., & Forneris, C. A. (1996) · Behaviour Research and Therapy · doi:10.1016/0005-7967(96)00033-2 · Cited by 3,997
Hoge, C. W., Auchterlonie, J. L., & Milliken, C. S. (2006) · JAMA · doi:10.1001/jama.295.9.1023 · Cited by 2,027
Self-disclosure in computer-mediated communication: The role of self-awareness and visual anonymity
Joinson, A. N. (2001) · European Journal of Social Psychology · doi:10.1002/ejsp.36 · Cited by 1,458
Link, B. G., Struening, E. L., Neese-Todd, S., Asmussen, S., & Phelan, J. C. (2001) · Psychiatric Services · doi:10.1176/appi.ps.52.12.1621 · Cited by 1,254
Thornicroft, G., Brohan, E., Rose, D. S., Sartorius, N., & Leese, M. (2009) · The Lancet · doi:10.1016/s0140-6736(08)61817-6 · Cited by 1,189
It's only a computer: virtual humans increase willingness to disclose
Lucas, G. M., Gratch, J., King, A., & Morency, L.-P. (2014) · Computers in Human Behavior · doi:10.1016/j.chb.2014.04.043 · Cited by 977
Self-citationThe nature of rapport and its nonverbal correlates
Tickle-Degnen, L., & Rosenthal, R. (1990) · Psychological Inquiry · doi:10.1207/s15327965pli0104_1 · Cited by 960 · cited 2×
“Tickle-Degnen and Rosenthal (1990) suggest several features of “the human element” that are important in increasing rapport, including both verbal and non-verbal behavior.”
BackgroundThomas, J. L., Wilk, J. E., Riviere, L. A., McGurk, D., Castro, C. A., & Hoge, C. W. (2010) · Archives of General Psychiatry · doi:10.1001/archgenpsychiatry.2010.54 · Cited by 942
Fear, N. T., Jones, M., Murphy, D., Hull, L., Iversen, A. C., Coker, B., Machell, L., Sundin, J., Woodhead, C., Jones, N., et al. (2010) · The Lancet · doi:10.1016/s0140-6736(10)60672-1 · Cited by 606
Flagged first, then by citations
Research works printed but not linked: 7
- Haylan, 2005, Challenges Ahead. Head Movements and Other Social Acts in Conversation
- 2014, Treatment for Posttraumatic Stress Disorder in Military and Veteran Populations: Final Assessment
- 2010, The Numbers Count: Mental Disorders in America
- Sebestik, 1988, “Initial experiences with CAPI,”, 357
- Vincenzes, 2013, Comparison of civilian trauma and combat trauma, Vistas Online, 45, 1
- 2011, The Global Economic Burden of Non-Communicable Diseases
- 2004, The Global Burden of Disease: 2004 Update
Cited by
Sorted by citations
Items 101–200 of 308
Moore, J. R., & Caudill, R. L. (2019) · Psychiatric Clinics of North America · doi:10.1016/j.psc.2019.08.007 · Cited by 25
The Implications of Embodied Artificial Intelligence in Mental Healthcare for Digital Wellbeing
Fiske, A., Henningsen, P., & Buyx, A. (2020) · Philosophical studies series · doi:10.1007/978-3-030-50585-1_10 · Cited by 27
Conversational Agents for Mental Health and Wellbeing
Callejas, Z., & Griol, D. (2021) · Logic, argumentation & reasoning · doi:10.1007/978-3-030-61438-6_11 · Cited by 23
Chatbots in the Field of Mental Health: Challenges and Opportunities
Viduani, A. C., Cosenza, V., Araújo, R., & Kieling, C. (2023) · Springer eBooks · doi:10.1007/978-3-031-10698-9_8 · Cited by 25
Barger, A. S. (2025) · Frontiers in Psychology · doi:10.3389/fpsyg.2024.1364054 · Cited by 27
Jackson‐Triche, M., Vetal, D., Turner, E.-M., Dahiya, P., & Mangurian, C. V. (2023) · Journal of Medical Internet Research · doi:10.2196/40635 · Cited by 22
A narrative review of the active ingredients in psychotherapy delivered by conversational agents
Herbener, A. B., Klincewicz, M., & Damholdt, M. F. (2024) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2024.100401 · Cited by 23
AI-Based Prediction and Prevention of Psychological and Behavioral Changes in Ex-COVID-19 Patients
Ćosić, K., Popović, S., Šarlija, M., Kesedžić, I., Gambiraža, M., Dropuljić, B., Mijić, I., Henigsberg, N., & Jovanović, T. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.782866 · Cited by 27
"I've talked without intending to": Self-disclosure and Reciprocity via Embodied Avatar
Ichino, J., Ide, M., Yokoyama, H., Asano, H., Miyachi, H., & Okabe, D. (2022) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3555583 · Cited by 22
Stock, A., Schlögl, S., & Groth, A. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-35894-4_13 · Cited by 21
McAlister, K. L., Baez, L. M., Huberty, J., & Kerppola, M. (2025) · JMIR Formative Research · doi:10.2196/72469 · Cited by 31
Pregnancy in the time of COVID-19: towards Fetal monitoring 4.0
Kahankova, R. V., Barnova, K., Jaroš, R., Pavlíček, J., Snåšel, V., & Martínek, R. (2023) · BMC Pregnancy and Childbirth · doi:10.1186/s12884-023-05349-3 · Cited by 24
Zalake, M. S., Tavassoli, F., Duke, K., George, T. J., Modave, F., Neil, J., Krieger, J. L., & Lok, B. C. (2019) · Journal on Multimodal User Interfaces · doi:10.1007/s12193-020-00357-5 · Cited by 41
Voice Assistants for Mental Health Services: Designing Dialogues with Homebound Older Adults
Wong, N., Jeong, S., Reddy, M. C., Stamatis, C. A., Lattie, E. G., & Jacobs, M. L. (2024) · Designing Interactive Systems Conference · doi:10.1145/3643834.3661536 · Cited by 22
Liu, C., Su, M., Xiang, Y., Huang, Y., Yang, Y., Kang Zhang, A., & Fan, M. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3714228 · Cited by 27
On the Generation of Medical Dialogs for COVID-19
Zhou, M., Li, Z., Tan, B., Zeng, G., Yang, W., He, X., Ju, Z., Chakravorty, S., Chen, S., Yang, X., et al. (2021) · doi:10.18653/v1/2021.acl-short.112 · Cited by 16
Can Gestural Filler Reduce User-Perceived Latency in Conversation with Digital Humans?
Kum, J., & Lee, M. (2022) · Applied Sciences · doi:10.3390/app122110972 · Cited by 21
Designing Chatbots for Guiding Online Peer Support Conversations for Adults with ADHD
Nordberg, O. E., Wake, J. D., Nordby, E. S., Flobak, E., Nordgreen, T., Mukhiya, S. K., & Guribye, F. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-39540-7_8 · Cited by 17
From Combat to COVID-19 – Managing the Impact of Trauma Using Virtual Reality
Rizzo, A., Hartholt, A., & Mozgai, S. (2021) · Journal of Technology in Human Services · doi:10.1080/15228835.2021.1915931 · Cited by 19
Self-citationCalibrating workers’ trust in intelligent automated systems
Lucas, G., Becerik-Gerber, B., & Roll, S. C. (2024) · Patterns · doi:10.1016/j.patter.2024.101045 · Cited by 28
Self-citationLangevin, R., Berry, A. B. L., Zhang, J., Fockele, C. E., Anderson, L., Hsieh, D. T., Hartzler, A. L., Duber, H. C., & Hsieh, G. (2023) · Applied Clinical Informatics · doi:10.1055/a-2035-5342 · Cited by 16
Stapleton, L., Liu, S., Liu, C., Hong, I., Chancellor, S., Kraut, R. E., & Zhu, H. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3641922 · Cited by 17
Emotion Recognition using Spatiotemporal Features from Facial Expression Landmarks
Golzadeh, H., Faria, D. R., Manso, L. J., Ekárt, A., & Buckingham, C. D. (2018) · IEEE International Conference on Intelligent Systems · doi:10.1109/is.2018.8710573 · Cited by 16
Hilty, D. M., Randhawa, K., Maheu, M. M., McKean, A. J. S., & Pantera, R. (2019) · Psychology and Cognitive Sciences - Open Journal · doi:10.17140/pcsoj-5-145 · Cited by 18
Dupuy, L., Micoulaud‐Franchi, J., & Philip, P. (2020) · Journal of Sleep Research · doi:10.1111/jsr.13094 · Cited by 16
Assessing Users' Mental Status from their Journaling Behavior through Chatbots
Kawasaki, M., Yamashita, N., Lee, Y., & Nohara, K. (2020) · ACM International Conference on Intelligent Virtual Agents (IVA) · doi:10.1145/3383652.3423870 · Cited by 17
Exploring the Design of LLM-based Agent in Enhancing Self-disclosure Among the Older Adults
Guo, Y., Wang, R., Huang, Z., Jin, T., Yao, X., Feng, Y.-L., Zhang, W., Yao, Y., & Mi, H. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713639 · Cited by 18
Employing Conversational Agents in Palliative Care: A Feasibility Study and Preliminary Assessment
Chatzimina, M., Koumakis, L., Kostas Marias, A., & Tsiknakis, M. (2019) · IEEE International Conference on Bioinformatics and Bioengineering (BIBE) · doi:10.1109/bibe.2019.00095 · Cited by 16
On the Generation of Medical Dialogues for COVID-19Preprint
Yang, W., Zeng, G., Tan, B., Ju, Z., Chakravorty, S., He, X., Chen, S., Yang, X., Wu, Q., Yu, Z., et al. (2020) · medRxiv · doi:10.1101/2020.05.08.20095810 · Cited by 15
Ricci, F., Giallanella, D., Gaggiano, C., Torales, J. C., Castaldelli-Maia, J. M., Liebrenz, M., Bener, A., & Ventriglio, A. (2024) · International Review of Psychiatry · doi:10.1080/09540261.2024.2384727 · Cited by 17
Simonovic, N., Taber, J. M., Scherr, C. L., Dean, M., Hua, J., Howell, J. L., Chaudhry, B. M., Wain, K. E., & Politi, M. C. (2022) · Journal of Behavioral Medicine · doi:10.1007/s10865-022-00384-5 · Cited by 16
Song, T., Pabst, F., Eck, U., & Navab, N. (2025) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2025.3549181 · Cited by 14
Play the Pain: A Digital Strategy for Play-Oriented Research and Action
Khalili‐Mahani, N., Holowka, E., Woods, S., Khaled, R., Roy, M., Lashley, M., Tristan Glatard, B., Timm‐Bottos, J., Dahan, A., Niesters, M., et al. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.746477 · Cited by 15
Han, H. J., Mendu, S., Jaworski, B. K., Owen, J. E., & Abdullah, S. (2021) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/3460418.3479332 · Cited by 17
Sayis, B., & Güneş, H. (2024) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/3610978.3640721 · Cited by 14
Investigating the Possibility of Using an AR Mask to Support Online Psychological Counseling
Noh, H., Go, J., Song, S., Kim, S., & Kang, Y. (2024) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3637355 · Cited by 15
Academic stress detection based on multisource data: a systematic review from 2012 to 2024
Liu, S., Zhang, Y., Zhao, L., & Liu, Z. (2024) · Interactive Learning Environments · doi:10.1080/10494820.2024.2387744 · Cited by 14
Design and Evaluation of Virtual Human Mediated Tasks for Assessment of Depression and Anxiety
Egede, J., Price, D., Krishnan, D. B., Jaiswal, S., Elliott, N. A., Morriss, R. K., Trigo, M. J. G., Nixon, N. L., Liddle, P. F., Greenhalgh, C., et al. (2021) · ACM International Conference on Intelligent Virtual Agents (IVA) · doi:10.1145/3472306.3478361 · Cited by 13
Substance, discourse, and practice: a review of communication research on automation
Barbour, J. B., Jensen, J. T., Call, S. R., & Sharma, N. (2023) · Annals of the International Communication Association · doi:10.1080/23808985.2023.2183232 · Cited by 16
Natural Language Processing for Covid-19 Consulting System
Tripathy, S., Singh, R., & Ray, M. (2023) · Procedia Computer Science · doi:10.1016/j.procs.2023.01.112 · Cited by 13
Equivalence of chatbot and paper-and-pencil versions of the De Jong Gierveld loneliness scale
Miedes, A. C., Belmonte, Ó., Castillo, A., Gascó, A., Sansano‐Sansano, E., & Montoliu, R. (2020) · Current Psychology · doi:10.1007/s12144-020-01117-0 · Cited by 12
Population subgroup differences in the use of a COVID-19 chatbot
Schubel, L., Wesley, D. B., Booker, E. A., Lock, J., & Ratwani, R. M. (2021) · npj Digital Medicine · doi:10.1038/s41746-021-00405-8 · Cited by 12
DEPRA: An Early Depression Detection Analysis Chatbot
Kaywan, P., Ahmed, K. E. U., Miao, Y., Ibaida, A., & Gu, B. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-90885-0_18 · Cited by 12
A 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 14
Knowledge cues to human origins facilitate self-disclosure during interactions with chatbots
Warren-Smith, G., Laban, G., Pacheco, E.-M., & Cross, E. S. (2025) · Computers in Human Behavior Artificial Humans · doi:10.1016/j.chbah.2025.100174 · Cited by 13
Semantic similarity to improve question understanding in a virtual patient
Laleye, F. A. A., Blanié, A., Brouquet, A., Behnamou, D., & de Chalendar, G. (2020) · ACM Symposium on Applied Computing · doi:10.1145/3341105.3373936 · Cited by 11
Intelligent Conversational Agents in Global Health
Luxton, D. D., & Sirotin, A. P. (2020) · Springer eBooks · doi:10.1007/978-3-319-70134-9_11-1 · Cited by 11
Heim, C., & Heim, C. (2021) · Journal of University Teaching and Learning Practice · doi:10.53761/1.18.6.06 · Cited by 11
Moreno, X., & Moreno, F. G. (2024) · PLoS ONE · doi:10.1371/journal.pone.0304623 · Cited by 12
Colvin, A. D., & Benjamin, C. (2025) · Family Relations · doi:10.1111/fare.13145 · Cited by 10
Designing Chatbots to Treat Depression in Youth: Qualitative Study
Kuhlmeier, F. O., Bauch, L., Gnewuch, U., & Lüttke, S. (2025) · JMIR Human Factors · doi:10.2196/66632 · Cited by 11
Effects of a computer's human likeness on disclosure in psychosocial assessments: A randomised trial
Zhu, T., & Broadbent, E. (2025) · Computers in Human Behavior · doi:10.1016/j.chb.2025.108683 · Cited by 10
Screening for common mental health disorders: a psychometric evaluation of a chatbot system
Podina, I. R., Bucur, A.-M., Fodor, L. A., & Boian, R. (2023) · Behaviour and Information Technology · doi:10.1080/0144929x.2023.2275164 · Cited by 13
Bots for Research: Minimising the Experimenter Effect
Wijenayake, S., van Berkel, N., & Gonçalves, J. (2020) · VBN Forskningsportal (Aalborg Universitet) · Cited by 10
Chaudry, B., & Islam, A. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph192113794 · Cited by 12
Rasouli, S., Ghafurian, M., & Dautenhahn, K. (2025) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3718084 · Cited by 13
Lee, J., Jung, K., Newman, E., Chow, E., & Chen, Y. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713244 · Cited by 15
Mental health apps lean on bots and unlicensed therapists
Barras, C. G. (2019) · Nature Medicine · doi:10.1038/d41591-019-00009-6 · Cited by 9
PRIMER: An Emotionally Aware Virtual Agent.
Gordon, C., Leuski, A., Benn, G., Klassen, E., Fast, E., Liewer, M., Hartholt, A., & Traum, D. R. (2019) · IUI Workshops · Cited by 9
Can intelligent agents improve data quality in online questiosnnaires? A pilot study
Söderström, A., Shatte, A. B. R., & Fuller‐Tyszkiewicz, M. (2021) · Behavior Research Methods · doi:10.3758/s13428-021-01574-w · Cited by 10
Portillo, G. A. O., Fletcher, J. B., Young, L. E., & Klausner, J. D. (2023) · mHealth · doi:10.21037/mhealth-22-33 · Cited by 9
On the Generation of Medical Dialogues for COVID-19Preprint
Yang, W., Zeng, G., Tan, B., Ju, Z., Chakravorty, S., He, X., Chen, S., Yang, X., Wu, Q., Yu, Z., et al. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2005.05442 · Cited by 22
A digital therapeutic alliance in digital mental health
Kaveladze, B., & Schueller, S. M. (2023) · Digital Therapeutics for Mental Health and Addiction · doi:10.1016/b978-0-323-90045-4.00009-5 · Cited by 8
Investigating Day-to-day Experiences with Conversational Agents by Users with Traumatic Brain Injury
Hu, Y., Lim, H., Johnson, H., O'Shaughnessy, J. M., Kakonge, L., Turkstra, L. S., Duff, M. C., Toma, C. L., & Mutlu, B. (2023) · International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS) · doi:10.1145/3597638.3608385 · Cited by 9
Cooney, O., Doherty, K., Barry, M., Coyle, D., Doherty, G. J., & Cowan, B. R. (2024) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3640794.3665540 · Cited by 10
Rizzo, A., Mozgai, S., Sigaras, A., Rubin, J. E., & Jotwani, R. (2025) · Journal of Medical Extended Reality · doi:10.1177/29941520251369450 · Cited by 7
Self-citationWhy Consumers Prefer Chatbots' Simulated Empathy: Revisiting the Empathy‐Honesty Trade‐Off
Ye, Z., Long, F., & Luo, L. (2026) · Journal of Consumer Behaviour · doi:10.1002/cb.70138 · Cited by 7
A Review on Trustworthiness of Digital Assistants for Personal Healthcare
Bailoni, T., & Dragoni, M. (2025) · ACM Computing Surveys · doi:10.1145/3714999 · Cited by 11
Steel, J. S., Godderis, L., & Luyten, J. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18041460 · Cited by 7
Ming, S., Mayfield, R., Cheng, H., Wang, K.-R., & Huang, Y. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3449111 · Cited by 7
DeTore, N. R., Balogun‐Mwangi, O., Eberlin, E. S., Dokholyan, K. N., Rizzo, A., & Holt, D. J. (2024) · Journal of Medical Extended Reality · doi:10.1089/jmxr.2024.0016 · Cited by 9
Self-citationPauw, L. S. (2023) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2023.101597 · Cited by 6
Eliciting User Self-disclosure using Reciprocity in Human-Voicebot Conversations
Harmsen, W., van Waterschoot, J., Hendrickx, I., & Theune, M. (2023) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3571884.3604301 · Cited by 6
Randall, N., Saga, T., Kamino, W., Tsui, K. M., Šabanović, S., & Nagata, S. (2023) · IEEE RO-MAN · doi:10.1109/ro-man57019.2023.10309496 · Cited by 8
The Impact of Virtual Human Vocal Personality on Establishing Rapport
Maxim, A., Zalake, M. S., & Lok, B. C. L. (2023) · ACM International Conference on Intelligent Virtual Agents (IVA) · doi:10.1145/3570945.3607318 · Cited by 6
Change gently: an agent-based virtual interview training for college students with great shyness
Geng, W., Zhou, C., & Bian, Y. (2024) · Virtual Reality · doi:10.1007/s10055-024-01076-y · Cited by 6
Ethical considerations of digital therapeutics for mental health
Landers, C., Wies, B., & Ienca, M. (2022) · Elsevier eBooks · doi:10.1016/b978-0-323-90045-4.00007-1 · Cited by 7
"\"It patted my arm\": Investigating Social Touch from a Virtual Agent"
Boucaud, F., Pélachaud, C., & Thouvenin, I. (2023) · International Conference on Human-Agent Interaction (HAI) · doi:10.1145/3623809.3623853 · Cited by 6
Decision Model for a Virtual Agent that can Touch and be Touched
Boucaud, F., Pélachaud, C., & Thouvenin, I. (2021) · Adaptive Agents and Multi-Agents Systems · doi:10.65109/lkmx6264 · Cited by 7
Kim, J., & Bae, J. (2025) · Journal of Global Scholars of Marketing Science · doi:10.1080/21639159.2025.2458860 · Cited by 6
Mobile apps, AI, and teletherapy: a comprehensive review of digital mental health tools for nurses
Huang, W., Xing, Y., Zhao, F., & Wang, Y. (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2025.1686766 · Cited by 8
Das, P. J., Kyndait, P., Jamir, S. I., Baishya, D., Kalita, J. K., & Komu, L. T. (2024) · International Journal of Scientific Research in Science and Technology · doi:10.32628/ijsrst24116186 · Cited by 5
Ethics of Immersive Technologies
Hill, R. W. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108616188.004 · Cited by 5
Anisimova, A. S., Potemkina, A., Chervakov, P., Komza, V., Maksimov, D., Panin, I., Vaselyuk, A., & Samsonovich, A. V. (2022) · Procedia Computer Science · doi:10.1016/j.procs.2022.11.136 · Cited by 5
Systematic Representative Design and Clinical Virtual Reality
Mozgai, S., Hartholt, A., & Rizzo, A. (2019) · Psychological Inquiry · doi:10.1080/1047840x.2019.1693873 · Cited by 5
Self-citationZalake, M. S. (2020) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3334480.3375026 · Cited by 5
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Metadata
- Authors
- Lucas, G. M., Rizzo, A., Gratch, J., Scherer, S., Stratou, G., Boberg, J., & Morency, L.-P.
- Affiliations
- University of Southern California (US)
- Carnegie Mellon University (US)
- Corresponding author
- Lucas, Gale M.
- Venue
- Frontiers in Robotics and AI
- Publisher
- Frontiers Media SA
- Published
- 2017-10-12
- Volume
- 4
- ISSN
- 2296-9144 (ISSN-L)
- OpenAlex
- W2763552934
- Cited by
- 308
- References
- 53
- Citations by year
- 2026: 33 · 2025: 37 · 2024: 63 · 2023: 39 · 2022: 32 · 2021: 42 · 2020: 39 · 2019: 14 · 2018: 9
- FWCI
- 24.27
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Frontiers in Robotics and AI (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Defense Sciences Office, DARPA
- Army Research Office
- Topics
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Medicine › Psychiatry and Mental health › Mental Health Treatment and Access
- Keywords
- stigma, post-traumatic stress disorder, military personnel, anonymity, rapport building, disclosure, Afghanistan deployment
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