The DOI matches its Crossref record; 62 of the 62 references it cites were found in a registry or an index.
Response to a relational agent by hospital patients with depressive symptoms
Open accessAbstract
Depression affects approximately 15% of the US population, and is recognized as an important risk factor for poor outcomes among patients with various illnesses. Automated health education and behavior change programs have the potential to help address many of the shortcomings in health care. However, the role of these systems in the care of patients with depression has been insufficiently examined. In the current study, we sought to evaluate how hospitalized medical patients would respond to a computer animated conversational agent that has been developed to provide information in an empathic fashion about a patient's hospital discharge plan. In particular, we sought to examine how patients who have a high level of depressive symptoms respond to this system. Therapeutic alliance-the trust and belief that a patient and provider have in working together to achieve a desired therapeutic outcome- was used as the primary outcome measure, since it has been shown to be important in predicting outcomes across a wide range of health problems, including depression. In an evaluation of 139 hospital patients who interacted with the agent at the time of discharge, all patients, regardless of depressive symptoms, rated the agent very high on measures of satisfaction and ease of use, and most preferred receiving their discharge information from the agent compared to their doctors or nurses in the hospital. In addition, we found that patients with symptoms indicative of major depression rated the agent significantly higher on therapeutic alliance compared to patients who did not have major depressive symptoms. We conclude that empathic agents represent a promising technology for patient assessment, education and counseling for those most in need of comfort and caring in the inpatient setting.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Previous studies have demonstrated that chatbot interventions improve psychological difficulties including major depressive disorder [15], panic disorder [16], posttraumatic stress disorder [17], antipsychotic medication adherence [18], and perceived stress [19].”
From A Cognitive Behavioral Therapy Chatbot (Otis) for Health Anxiety Management: Mixed Methods Pilot Study (2022) · cites this paper as [15]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Designing for certain character traits, such as empathy, in a chatbot can increase the likelihood of users establishing relationships with it (Bickmore et al., 2010).”
From My Chatbot Companion - a Study of Human-Chatbot Relationships (2021) · cites this paper as Bickmore et al., 2010
In the citing paper
“In one example, patients reported high satisfaction with a conversational agent that delivered hospital discharge instructions, and patients with depression and/or low health literacy reported stronger therapeutic alliance with the agent.”
From Behavioral Intervention Technologies: Evidence review and recommendations for future research in mental health (2013) · cites this paper as [57]
In the citing paper
“The agent also elicited more questions from those with lower health literacy, suggesting such agents may have the potential to provide health information in a supportive, non-threatening manner (57).”
From Behavioral Intervention Technologies: Evidence review and recommendations for future research in mental health (2013) · cites this paper as [57]
In the citing paper
“The agent also elicited more questions from those with lower health literacy, suggesting such agents may have the potential to provide health information in a supportive, non-threatening manner (57).”
From Behavioral Intervention Technologies: Evidence review and recommendations for future research in mental health (2013) · cites this paper as [57]
In the citing paper
“In one example, patients reported high satisfaction with a conversational agent that delivered hospital discharge instructions, and patients with depression and/or low health literacy reported stronger therapeutic alliance with the agent.”
From Behavioral Intervention Technologies: Evidence review and recommendations for future research in mental health (2013) · cites this paper as [57]
In the citing paper
“The study for symptoms of depression noted that the written chatbot showed an accuracy of 99.2% and a specificity of 99.7% [52].”
From A systematic review on healthcare artificial intelligent conversational agents for chronic conditions (2022) · cites this paper as [52]
In the citing paper
“Other use of conversational agents include replacing nurses to provide hospital discharge planning, for collecting relevant health information (such as public health surveys), for training health-care providers by simulating patients, and for providing public health information and education.3,5–9”
From Ethical implications of conversational agents in global public health (2020) · cites this paper as [7]
In the citing paper
“Thus, users may experience less anxiety when discussing private concerns, such as disease exposure risk behaviours, with a conversational agent than they would with another person.3,4,7”
From Ethical implications of conversational agents in global public health (2020) · cites this paper as [7]
In the citing paper
“conversational agents (ie, computer programs that imitate interaction with human beings) have shown promising results with respect to patient satisfaction [15]”
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
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
ELIZA—a computer program for the study of natural language communication between man and machine
Weizenbaum, J. (1966) · Communications of the ACM · doi:10.1145/365153.365168 · Cited by 4,452
Development and validation of the State Hope Scale.
Snyder, C. R. R., Sympson, S. C., Ybasco, F. C., Borders, T. F., Babyak, M. A., & Higgins, R. L. (1996) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.70.2.321 · Cited by 3,584
Development and validation of the working alliance inventory
Horvath, A. O., & Greenberg, L. S. (1989) · Journal of Counseling Psychology · doi:10.1037//0022-0167.36.2.223 · Cited by 3,520
The world health report 2001 - Mental health: new understanding, new hope
Sayers, J. (2001) · Europe PMC (PubMed Central) · doi:10.1590/s0042-96862001001100014 · Cited by 3,307
ELIZA — a computer program for the study of natural language communication between man and machine
Weizenbaum, J. (1983) · Communications of the ACM · doi:10.1145/357980.357991 · Cited by 2,807
Hasin, D. S., Goodwin, R. D., Stinson, F. S., & Grant, B. F. (2005) · Archives of General Psychiatry · doi:10.1001/archpsyc.62.10.1097 · Cited by 1,645
A Reengineered Hospital Discharge Program to Decrease Rehospitalization
Jack, B. W., Chetty, V. K., Anthony, D., Greenwald, J. L., Sanchez, G. M., Johnson, A. E., Forsythe, S. R., O'Donnell, J. K., Paasche‐Orlow, M. K., Manasseh, C., et al. (2009) · Annals of Internal Medicine · doi:10.7326/0003-4819-150-3-200902030-00007 · Cited by 1,613
Self-citationRapid estimate of adult literacy in medicine: a shortened screening instrument.
Davis, T. C., Long, S. W., Jackson, R. H., Mayeaux, E. J., George, R. B., Murphy, P. W., & Crouch, M. A. (1993) · PubMed · Cited by 1,597
Health Literacy: Report of the Council on Scientific Affairs
American Medical Association Ad Hoc Committee on Health Literacy for the Council on Scientific Affairs (1999) · JAMA · doi:10.1001/jama.281.6.552 · Cited by 1,515
Flagged first, then by citations
Research works printed but not linked: 4
- Bickmore, T., Pfeifer, L., 2008. Relational agents for antipsychotic medication adherence. In: Proceedings of the CHI’08 Workshop on Technology in Mental Health, Florence, Italy.
- Lisetti, C., 2008. Embodied computer agents for psychotherapy. Paper presented at the CHI 2008 Workshop on Technology in Mental Health.
- Pratt, 2008, Depression in the United States household population, NCHS Data Brief, 1
- Wright, 2004, Computer-assisted cognitive-behavior therapy, vol. 23, 55
Cited by
Sorted by citations
Items 101–200 of 218
Integrating avatar technology into a telemedicine application in heart failure patients
Gingele, A. J., Amin, H., Vaassen, A., Schnur, I., Pearl, C., Rocca, H. B., & Boyne, J. J. (2023) · Wiener klinische Wochenschrift · doi:10.1007/s00508-022-02150-8 · Cited by 20
Künstliche Intelligenz in der Hochschulbildung
Schmohl, T., Watanabe, A., & Schelling, K. (2023) · transcript Verlag eBooks · doi:10.14361/9783839457696 · Cited by 48
Burgermaster, M., Desai, P. M., Heitkemper, E., Juul, F., Mitchell, E. G., Turchioe, M. R., Albers, D. J., Levine, M. E., Larson, D. N., & Mamykina, L. (2023) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2023.104419 · Cited by 18
The Impact of Virtual Humans on Psychosomatic Medicine
Loveys, K., Sagar, M. A., Antoni, M. H., & Broadbent, E. (2023) · Psychosomatic Medicine · doi:10.1097/psy.0000000000001227 · Cited by 18
Bridging the Health Disparity of African Americans Through Conversational Agents
Kim, J., Park, S. Y., & Robert, L. (2020) · Digital Government Research and Practice · doi:10.1145/3428122 · Cited by 19
Design of a Chatbot to Assist the Elderly
Valtolina, S., & Marchionna, M. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-79840-6_10 · Cited by 17
Ruiz, J. G., Andrade, A. D., Anam, R., Lisigurski, M. Z., Karanam, C., & Sharit, J. (2013) · The Science of Diabetes Self-Management and Care · doi:10.1177/0145721713508825 · Cited by 16
Lüscher, J., Kowatsch, T., Boateng, G., Santhanam, P., Bodenmann, G., & Scholz, U. (2019) · JMIR Research Protocols · doi:10.2196/13685 · Cited by 18
Modeling an Augmented Reality Game Environment to Enhance Behavior of ADHD Patients
Alqithami, S., Alzahrani, M., Alzahrani, A., & Mostafa, A. M. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-37078-7_18 · Cited by 15
Koebel, K., Lacayo, M., Murali, M., Tarnanas, I., & Çöltekin, A. (2022) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-94890-0_2 · Cited by 14
Cognitive Architecture of an Agent for Human-Agent Dialogues
Baskar, J., & Lindgren, H. (2014) · Communications in computer and information science · doi:10.1007/978-3-319-07767-3_9 · Cited by 14
A serious-gamification blueprint towards a normalized attention
Alqithami, S. (2021) · Brain Informatics · doi:10.1186/s40708-021-00127-3 · Cited by 14
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
A Multipurpose Goal Model for Personalised Digital Coaching
Baskar, J., Janols, R., Guerrero, E., Nieves, J. C., & Lindgren, H. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-70887-4_6 · Cited by 14
KlimaKarl – A Chatbot to Promote Employees’ Climate-Friendly Behavior in an Office Setting
Hillebrand, K., & Johannsen, F. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-82405-1_1 · Cited by 15
Han, H. J., Mendu, S., Jaworski, B. K., Owen, J. E., & Abdullah, S. (2023) · JMIR Formative Research · doi:10.2196/45894 · Cited by 13
Mobile/VR/Robotics/IoT-Based Chatbots and Intelligent Personal Assistants for Social Inclusion
Karyotaki, M., Drigas, A. S., & Skianis, C. (2024) · International Journal of Interactive Mobile Technologies (iJIM) · doi:10.3991/ijim.v18i08.46473 · Cited by 12
MacNeill, A. L., MacNeill, L., Luke, A., & Doucet, S. A. (2024) · Journal of Medical Internet Research · doi:10.2196/49387 · Cited by 18
Use of Relational Agents to Improve Family Communication in Type 1 Diabetes: Methods
Thompson, D. I., Cullen, K. W., REDONDO, M. J., & Anderson, B. J. (2016) · JMIR Research Protocols · doi:10.2196/resprot.5817 · 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 Survey of Conversational Agents and Their Applications for Self-Management of Chronic Conditions
Park, M. S., Upama, P. B., Anik, A. A., Ahamed, S. I., Luo, J., Tian, S., Rabbani, M., & Oh, H. (2023) · IEEE Annual International Computer Software and Applications Conference (COMPSAC) · doi:10.1109/compsac57700.2023.00162 · Cited by 14
Interactive Robots: Therapy Robots
Akyazı, K. G., & BAŞTEMUR, Ş. (2023) · Psikiyatride Guncel Yaklasimlar - Current Approaches in Psychiatry · doi:10.18863/pgy.1242958 · Cited by 11
Zsoldos, I., Trân, E., Fournier, H., Tarpin-Bernard, F., Fruitet, J., Fouillen, M., Bailly, G., Elisei, F., Bouchot, B., Constant, P., et al. (2024) · JMIR Rehabilitation and Assistive Technologies · doi:10.2196/48129 · Cited by 11
Papadimitriou, C., Clayman, M. L., Mallinson, T., Weaver, J., Guernon, A., Meehan, A. J., Kot, T., Ford, P., Ideishi, R. I., Prather, C. P., et al. (2024) · Health Expectations · doi:10.1111/hex.14162 · Cited by 10
Liu, X., Jin, X., Cen, W., Liu, Y., Luo, S., You, J., & Tian, S. (2024) · BMC Public Health · doi:10.1186/s12889-024-19696-z · Cited by 10
Immel, D., Hilpert, B., Schwarz, P., Hein, A., Gebhard, P., Barton, S., & Hurlemann, R. (2025) · JMIR Formative Research · doi:10.2196/59527 · Cited by 10
T2 Coach: A Qualitative Study of an Automated Health Coach for Diabetes Self-Management
Mitchell, E. G., Desai, P., Smaldone, A. M., Cassells, A. N., Tobin, J. N., Albers, D. J., Levine, M. E., & Mamykina, L. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3714404 · Cited by 9
Innovations in CBT treatment for hoarding: Transcending office walls
Muroff, J. R., & Otte, S. (2019) · Journal of Obsessive-Compulsive and Related Disorders · doi:10.1016/j.jocrd.2019.100471 · Cited by 10
Rasouli, S., Ghafurian, M., & Dautenhahn, K. (2025) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3718084 · Cited by 13
You, C., Ghosh, R., Vilaro, M. J., Venkatakrishnan, R., Venkatakrishnan, R., Maxim, A., Peng, X., Tamboli, D. N. A., & Lok, B. C. L. (2025) · Frontiers in Digital Health · doi:10.3389/fdgth.2025.1655860 · Cited by 10
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
A Review of Virtual Therapists in Anxiety and Phobias Alleviating Applications
Mitruț, O., Moldoveanu, A. D. B., Petrescu, L., Petrescu, C., & Moldoveanu, F. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-77599-5_6 · Cited by 9
Conversational agents on smartphones and the web
Bickmore, T., & O’Leary, T. K. (2022) · Elsevier eBooks · doi:10.1016/b978-0-323-90045-4.00010-1 · Cited by 9
Self-citationDewi, D. A., Julia, J., & Jonathan, C. (2022) · Mimbar Sekolah Dasar · doi:10.53400/mimbar-sd.v9i1.44460 · Cited by 8
Kulkarni, S. (2022) · Wiley eBooks · doi:10.1002/9781119792376.ch6 · Cited by 8
What patients want from healthcare chatbots: insights from a mixed-methods study
Dellavalle, N. S., Ellis, J. R., Moore, A., Akerson, M., Andazola, M., Campbell, E. G., & DeCamp, M. W. (2025) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocaf164 · Cited by 9
Schachner, T., Gross, C., Hasl, A., von Wangenheim, F., & Kowatsch, T. (2020) · Journal of Medical Internet Research · doi:10.2196/22919 · Cited by 7
Development of multimodal sentiment recognition and understanding
Tao, J., Fan, C., Lian, Z., Lyu, Z., Shen, Y., & Liang, S. (2024) · Journal of Image and Graphics · doi:10.11834/jig.240017 · Cited by 8
Chen, T., Shen, Y., Chen, X., & Zhang, L. (2024) · ACM Transactions on Asian and Low-Resource Language Information Processing · doi:10.1145/3676962 · Cited by 7
Igarashi, T., Iijima, K., Nitta, K., & Chen, Y. (2024) · Healthcare · doi:10.3390/healthcare12181821 · Cited by 8
van Vliet, M. H. M., Versluis, A., Chavannes, N. H., Scheltinga, B. L., Albers, N., Penfornis, K. M., Baccinelli, W., & Meijer, E. (2024) · Digital Health · doi:10.1177/20552076241300020 · Cited by 7
Human-Agent Dialogues on Health Topics - An Evaluation Study
Baskar, J., & Lindgren, H. (2015) · Communications in computer and information science · doi:10.1007/978-3-319-19033-4_3 · Cited by 7
Designing behavioral self-regulation application for preventive personal mental healthcare
Hirano, M., Ogura, K., Kitahara, M., Sakamoto, D., & Shimoyama, H. (2017) · Health Psychology Open · doi:10.1177/2055102917707185 · Cited by 7
Kuhail, M. A., Mrabet, J., Hijazi, R., & Thomas, J. (2025) · Human Behavior and Emerging Technologies · doi:10.1155/hbe2/8825536 · Cited by 6
Modeling an AR Serious Game to Increase Attention of ADHD Patients
Alqithami, S. (2020) · IEEE Annual International Computer Software and Applications Conference (COMPSAC) · doi:10.1109/compsac48688.2020.00-63 · Cited by 6
How animal-persona chatbots enhance empathy and positive attitudes toward animals
Li, J., Patwari, A., & Lee, Y. (2025) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2025.103647 · Cited by 7
Kim, J., Jin, X., Xu, K., Chen, X., & Yang, H. (2024) · The Social Science Journal · doi:10.1080/03623319.2024.2421610 · Cited by 6
Six, S., Schlesener, E. A., Hill, V., Babu, S. V., & Byrne, K. A. (2025) · JMIR Mental Health · doi:10.2196/67381 · Cited by 12
Assessing Synthetic Voices for Mental Health Chatbots
Amorese, T., McConvey, G., Cuciniello, M., Cordasco, G., Bond, R., Mulvenna, M. D., Ennis, E., Callejas, Z., & Esposito, A. A. (2023) · Lecture notes in networks and systems · doi:10.1007/978-981-99-3043-2_6 · Cited by 5
An Analysis of Use Intention of Pet Disease Consultation Chatbot
Huang, D.-H., & Chueh, H.-E. (2020) · International Conference on E-Society, E-Education and E-Technology (ICSET) · doi:10.1145/3421682.3421693 · Cited by 5
Adaptive human-agent dialogues for reasoning about health
Baskar, J. (2014) · DiVA at Umeå University (Umeå University) · Cited by 5
Rodrigues, T. C., Reijnders, T., Breeman, L. D., Janssen, V. R., Kraaijenhagen, R. A., Atsma, D. E., & Evers, A. W. M. (2023) · JMIR Formative Research · doi:10.2196/38803 · Cited by 5
MODELLING THERAPEUTIC EMPATHY IN A VIRTUAL AGENT TO SUPPORT THE REMOTE TREATMENT OF MAJOR DEPRESSION
Martı́nez-Miranda, J., Bresó, A., & Garcia-Gomez, J. M. (2012) · International Conference on Agents and Artificial Intelligence (ICAART) · doi:10.5220/0003833302640269 · Cited by 4
Keller, R., Yao, J., Teepe, G. W., Hartmann, S., Lohse, K.-M., von Wangenheim, F., Müller‐Riemenschneider, F., Mair, J. L., & Kowatsch, T. (2021) · International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC) · doi:10.5220/0010412708110816 · Cited by 4
Rodrigues, T. C., Reijnders, T., de Buisonjé, D. R., Santhanam, P., Kowatsch, T., Breeman, L. D., Janssen, V. R., Kraaijenhagen, R. A., Atsma, D. E., & Evers, A. W. M. (2021) · doi:10.2196/preprints.30057 · Cited by 4
Suri, A., & Sindwani, G. (2025) · International Journal of Obstetric Anesthesia · doi:10.1016/j.ijoa.2025.104762 · Cited by 3
Kim, D. D., Zhang, J., Sagae, K., DeVon, H. A., Hoffmann, T. J., Rountree, L., & Fukuoka, Y. (2025) · Journal of Medical Internet Research · doi:10.2196/73184 · Cited by 4
Digital Humans for Depression Assessment and Intervention Support: Scoping Review
Cao, J., Gao, W., Wen, R., Li, C., Hoermann, S., Baghaei, N., & Billinghurst, M. (2025) · JMIR Mental Health · doi:10.2196/79954 · Cited by 3
Suh, J., Le, L., Shayegani, E., Ramos, G., Amores, J., Ong, D. C., Czerwinski, M. P., & Hernandez, J. (2026) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2026.3656531 · Cited by 12
MacNeill, A. L., Luke, A., & Doucet, S. A. (2025) · Digital Health · doi:10.1177/20552076241311066 · Cited by 3
A Bibliometric Analysis of Trust in Conversational Agents over the Past Fifteen Years
Aksoy, M., & Bush, A. (2025) · International Conference on Computing and Artificial Intelligence (ICCAI) · doi:10.1109/iccai66501.2025.00076 · Cited by 6
Marcoux, A., Tessier, M.-H., Grondin, F., Reduron, L. R., & Jackson, P. L. (2021) · Santé mentale au Québec · doi:10.7202/1081509ar · Cited by 5
Suryavanshi, N., Dhumal, G., Cox, S. R., Sangle, S. A., DeLuca, A. N., Santre, M., Gupta, A., Chander, G., & Hutton, H. E. (2022) · JMIR Formative Research · doi:10.2196/35835 · Cited by 4
Islam, A., Chaudry, B., & Islam, A. (2024) · mHealth · doi:10.21037/mhealth-23-46 · Cited by 2
Design and Evaluation of a Virtual Agent for Interpersonal Emotion Regulation in VR
Kang, S., Lee, G., Yang, H.-J., Kim, S.-H., Shin, J., Jeong, J., Lee, M., & Kim, S. (2025) · Proceedings - International Symposium on Mixed and Augmented Reality, ISMAR · doi:10.1109/ismar67309.2025.00159 · Cited by 2
Mohr, D. C., Burns, M. N., Schueller, S. M., Clarke, G. N., & Klinkman, M. S. (2013) · Cited by 2
Prasad, M. L., Srinivasulu, C., Meenakshi, M. R., & Rohitha, P. (2023) · International Journal for Research in Applied Science and Engineering Technology · doi:10.22214/ijraset.2023.55295 · Cited by 2
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
Bonnaire, J., Dumas, G., & Cassell, J. (2024) · Frontiers in Neuroergonomics · doi:10.3389/fnrgo.2024.1290256 · Cited by 2
Deygout, F. (2019) · Biomedical Journal of Scientific & Technical Research · doi:10.26717/bjstr.2019.22.003727 · Cited by 3
»Wie kann ich dich unterstützen?«
Helten, A.-K., Wienkop, U., Wolff-Grosser, D., & Zitzmann, C. (2023) · transcript Verlag eBooks · doi:10.1515/9783839457696-008 · Cited by 2
Hwang, Y., Shin, D.-H., Baek, S., Suh, B., & Lee, J. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2109.01729 · Cited by 2
Chatbots as Motivational Agents
Le-Nguyen, H.-T., & Tran, T. T. (2023) · Advances in web technologies and engineering book series · doi:10.4018/978-1-6684-6234-8.ch006 · Cited by 1
Rodrigues, T. C., de Buisonjé, D. R., Reijnders, T., Santhanam, P., Kowatsch, T., Breeman, L. D., Janssen, V. R., Kraaijenhagen, R. A., Atsma, D. E., & Evers, A. W. M. (2024) · Internet Interventions · doi:10.1016/j.invent.2024.100726 · Cited by 1
THE HISTORY OF CHATBOTS: FROM IDEA TO USE IN APPLIED PSYCHOLOGY
Федоровна, Ф. И., & Freimanis, D. R. (2024) · Russian Journal of Education and Psychology · doi:10.12731/2658-4034-2024-15-2-484 · Cited by 1
Verma, R., Perera, A. I., Luxton, D. D., & Broadbent, E. (2026) · Postgraduate Medical Journal · doi:10.1093/postmj/qgag008 · Cited by 1
Borsari, B. E., Delacruz, J., Saiyed, A., Layton, J. F., Llanes, K. D., Mirzadegan, I. A., Cheng, J., Hargrave, A. S., Meacham, M. C., Catley, D., et al. (2026) · JMIR Formative Research · doi:10.2196/88125 · Cited by 2
Desgroseilliers, J., Hamel, C., Ogundokun, K., & Latulippe, K. (2026) · Medicine Advances · doi:10.1002/med4.70065 · Cited by 1
van Vliet, M. H. M., Meijer, E., Albers, N., Penfornis, K. M., Baccinelli, W., Scheltinga, B. L., van Eersel, R. A., Chavannes, N. H., & Versluis, A. (2026) · JMIR Human Factors · doi:10.2196/83456 · Cited by 1
A Case Study on Development of Mobile Chatbot for Promoting Creative Ideation
Jung, H., Park, C., Lee, J.-J., & Pak, S. Y. (2019) · Journal of Digital Contents Society · doi:10.9728/dcs.2019.20.11.2203 · Cited by 1
Chatbots by business vis-à-vis consumers: A new form of power and information asymmetry
Dāvida, Z. (2021) · SHS Web of Conferences · doi:10.1051/shsconf/202112905002 · Cited by 1
Designing Healthcare Relational Agents: A Conceptual Framework with User-Centered Design Guidelines
Islam, A., Chaudry, B., & Islam, A. (2023) · IEEE Symposium on Computers and Communications (ISCC) · doi:10.1109/iscc58397.2023.10218039 · Cited by 1
Artificial Intelligence in Cognitive Behavioral Therapy
Tzioumaki, N., Arvanitaki, E., & Xirakia, E. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-5072-1.ch010 · Cited by 1
컴퓨터 에이전트와 관계 맺기: 공감을 표현하는 컴퓨터 에이전트를 통한 동류의식 형성과 사회적 지지의 획득
Rheu, M., Kim, J. H., & 진전은영 (2017) · Korean Journal of Journalism & Communication Studies · doi:10.20879/kjjcs.2017.61.2.004 · Cited by 1
Security for People with Mental Illness in Telehealth Systems: A ProposalPreprint
Jiang, H. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2008.03406
van Bussel, M. V., Odekerken-Schröder, G., Ou, C., Swart, R., & Jacobs, M. (2022) · doi:10.2196/preprints.36535
A Cognitive Behaviour Therapy Chatbot (Otis) for Health Anxiety Management: Pilot Study (Preprint)Preprint
Goonesekera, Y., & Donkin, L. (2022) · doi:10.2196/preprints.37877
»Wie kann ich dich unterstützen?«
Helten, A.-K., Wienkop, U., Wolff-Grosser, D., & Zitzmann, C. (2023) · Hochschulbildung: Lehre und Forschung · doi:10.14361/9783839457696-008 · Cited by 2
Validation of a chatbot as a tool for monitoring of chronic pain
Paes, V. Z. C., de Magalhães, A. C., Pinto, N. C., Veriato, T. S., de Sousa, M. V. P., & Fortunato, T. C. (2023) · Journal of Health Informatics · doi:10.59681/2175-4411.v15.iespecial.2023.1076
Rodrigues, T. C., de Buisonjé, D. R., Reijnders, T., Santhanam, P., Kowatsch, T., Breeman, L. D., Janssen, V. R., Kraaijenhagen, R. A., Atsma, D. E., & Evers, A. W. M. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4592380
Towards control in agents for human behavior change: an autism case
Brännström, A., & Nieves, J. C. (2024) · Journal of Intelligent & Fuzzy Systems · doi:10.3233/jifs-219335
SOHBET ROBOTLARININ SOSYAL MEDYA ÜZERİNDEN TEMATİK ANALİZİ
Aytaç, Z. (2024) · Ömer Halisdemir Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi · doi:10.25287/ohuiibf.1419988
Borsari, B. E., Delacruz, J., Saiyed, A., Layton, J. F., Llanes, K. D., Kanzaveli, T., Tsvetovat, M., Cheng, J., Catley, D., & Satterfield, J. M. (2024) · doi:10.2196/preprints.67672
Schlesener, E. A., Six, S., Byrne, K. A., & Babu, S. V. (2025) · ACM Symposium on Applied Perception · doi:10.1145/3736702.3744357
Ethics in Rehabilitation Psychology
Hanson, S. L., & Kerkhoff, T. R. (2025) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780197525456.013.0057
MacNeill, A. L., MacNeill, L., Luke, A., & Doucet, S. A. (2025) · Frontiers in Digital Health · doi:10.3389/fdgth.2025.1590514
Lu, X., Guha, S., Pfafman, R., Pater, J. A., Washington, C. L., & Nova, F. F. (2025) · doi:10.2196/preprints.85152
Provoost, S., Kleiboer, A. M., Ornelas, J., Bosse, T., Ruwaard, J., Rocha, A., Cuijpers, P. J., & Riper, H. M. (2020) · Figshare · doi:10.6084/m9.figshare.13106342
van Bussel, M. J. P., Odekerken‐Schröder, G., Ou, C., Swart, R., & Jacobs, M. (2022) · Figshare · doi:10.6084/m9.figshare.20277939
Metadata
- Authors
- Bickmore, T. W., Mitchell, S. E., Jack, B. W., Paasche-Orlow, M. K., Pfeifer, L. M., & O’Donnell, J.
- Affiliations
- Northeastern University (US)
- Boston University (US)
- Corresponding author
- Bickmore, Timothy W.
- Venue
- Interacting with Computers
- Publisher
- Oxford University Press (OUP)
- Published
- 2010-07
- Volume
- 22
- Issue
- 4
- Pages
- 289-298
- ISSN
- 0953-5438 (ISSN-L)
- PMC
- PMC2901553
- OpenAlex
- W1989452694
- Cited by
- 218
- References
- 62
- Citations by year
- 2026: 17 · 2025: 22 · 2024: 23 · 2023: 23 · 2022: 27 · 2021: 28 · 2020: 20 · 2019: 24 · 2018: 5 · 2017: 9 · 2016: 3 · 2015: 4 · 2014: 4 · 2013: 6 · 2012: 2
- FWCI
- 1.31
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Interacting with Computers (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health
- National Heart, Lung, and Blood Institute (R01HL081307)
- Topics
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Health Professions › General Health Professions › Patient-Provider Communication in Healthcare
- Keywords
- chatbots, depression, depressive symptoms, therapeutic relationship, discharge planning, patient satisfaction, ease of use, health education, inpatient care, patient-provider relationship
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
