Usability and acceptability assessment of an empathic virtual agent to prevent major depression
Open accessAbstract
In Human–Computer Interaction, the adaptation of the content and the way of how this content is communicated to the users in interactive sessions is a critical issue to promote the acceptability and usability of any computational system. We present a user‐adapted interactive platform to identify and provide an early intervention for symptoms of depression and suicide. In particular, we describe the work performed to assess users' system acceptability and usability. An empathic Virtual Agent is the main interface with the user, and it has been designed to generate the appropriate dialogues and emotions during the interactions according to the detected user's specific needs. This personalization is based on a dynamic user model nurtured with clinical, demographical and behavioural information. The evaluation was performed with 60 participants from the university community. The obtained results were promising, allowing the execution of a further clinical trial. The system's usability score was 75.7%, and the score of the user‐adapted content and the emotional responses of the Virtual Agent was 70.9%.
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Written from the paper’s full text.
TL;DR
The paper presents and evaluates a user-adapted interactive system with an empathic virtual agent for preventing depression and suicide in university students. In a pre-clinical usability/acceptability evaluation with 60 participants, usability was 75.7/100 and overall acceptability of content and virtual-agent emotional responses was 70.9%.
Key findings
- System Usability Scale score was 75.7/100, above the 68 benchmark cited from Sauro; 93.6% of the 60 participants fully completed the evaluation questionnaire.
- Session-content acceptability: length q14 weighted average 3.22/4, variability q15 2.66/4, content q16 2.97/4; overall session management score was 2.95/4.
- Virtual-agent acceptability: appearance/behavior score was 2.75/4; 66% disagreed or strongly disagreed that the agent was “distant and aloof” (q17), 57% perceived it as trustworthy (q18), 82% perceived it as “emotionally stable” (q19), and 48% considered it a decisive factor motivating system use (q20).
- No significant difference in virtual-agent acceptance was found based on participant gender; qualitative feedback asked for shorter questionnaires, better GUI, more university-context questions, more therapy-based activities, and improved avatar appearance.
Methods
- Design: pre-clinical usability and acceptability evaluation of the PrevenDep system before a clinical trial; participants watched pre-recorded videos of interactive sessions and then completed an online 22-question questionnaire over 15 days.
- Sample: 60 participants accessed the evaluation, recruited from approximately 100 professors, researchers, and final-degree students across four locations: Universitat Politècnica de València, Universitat de València, Universitat Jaume I, and CICESE-UT3.
- Measures and analysis: questionnaire sections covered demographics, SUS usability (q4–q13), session-content acceptability (q14–q16), virtual-agent acceptability (q17–q20), and free-text comments (q21–q22); responses used a 0–4 Likert scale, with SUS scored by the standard method and descriptive weighted averages plus qualitative comments reported.
Limitations
- Paper states: the evaluation was performed with professors and researchers before use with target users for security and ethical reasons, not as a clinical efficacy trial; full natural-language interaction was not implemented because current technology does not allow it free of errors; and avatar appearance requires deeper programming/customization.
- Evident from the text: participants evaluated pre-recorded videos rather than using the system themselves, so usability/acceptability may not reflect real interaction; the sample was largely academic staff/researchers rather than the target university-student population; and free-text completion was lower (65.8%) than for the first 20 questions (96.4%).
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- Findingown data
The system's usability was 75.7%.
“The system's usability was 75.7%”
Quote in the paperSubstantial claim - Findingown data
Participants valued the appearance and behavior of the virtual agent positively, with a score of 2.75 out of 4.
“Regarding the evaluation of the appearance and behavior of the virtual agent -as the main interface between the user and the system-, the participants also valued positively this component (getting a score of 2.75 out of 4).”
Quote in the paperSubstantial claim- Rests on an assumption: Evaluation via pre-recorded videos reflects the perceived acceptability and usability of the system.
- Findingown data
No significant difference was found in acceptance of the virtual agent based on participant gender.
“Nevertheless, in our evaluation we did not find any significant difference in the acceptance of virtual agent based on the gender of the participant.”
Quote in the paperNot a substantial claim - Findingown data
The average SUS score obtained was 75.7.
“Figure 9 presents the average result obtained from the collected responses corresponding to a value of 75.7 (gray line), which is above the average proposed by Jeff Sauro (orange line).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Sauro, 2011
Not checked in the free run.
- Findingown data
Participants rated the usability of the system as highly positive, with a score of 75.7 out of 100.
“The participants rated the usability of the system as highly positive (with a result 75.7 out of 100).”
Quote in the paperSubstantial claim- Rests on an assumption: Evaluation via pre-recorded videos reflects the perceived acceptability and usability of the system.
- Findingown data
Almost all comments suggested improvements to the appearance of the virtual agent rather than to its perceived behavior.
“Almost all of the comments suggested improvements to the appearance of the virtual agent more than to the perceived behavior.”
Quote in the paperNot a substantial claim - Findingown data
The user-adapted content and the emotional responses of the VA scored 70.9%.
“the user-adapted content and the emotional responses of the VA 70.9%”
Quote in the paperSubstantial claim - Findingown data
Acceptability of sessions' management (content, duration, variability) was positive, with a score of 2.95 out of 4.
“The results obtained regarding the level of acceptability concerning the sessions' management (content, duration and variability) have also been positive, obtaining a score of 2.95 out of 4.”
Quote in the paperSubstantial claim- Rests on an assumption: Evaluation via pre-recorded videos reflects the perceived acceptability and usability of the system.
- Findingown data
57% of participants perceived the virtual agent as trustworthy (q18).
“Complementarily, the 57% of the participants perceived the virtual agent as trustworthy (q18).”
Quote in the paperNot a substantial claim - Interpretationown data
Participants in the evaluation rated the system as having high usability.
“Therefore we can conclude that participants in our evaluation rated the system with a high usability feature.”
Quote in the paperSubstantial claim- Rests on an assumption: Evaluation via pre-recorded videos reflects the perceived acceptability and usability of the system.
- Study design and conductown data
Of the 60 participants, 93.6% fully completed the evaluation questionnaire.
“From 60 participants, the 93.6% fully complete the evaluation questionnaire.”
Quote in the paperNot a substantial claim - Premisecitation
The conveying of empathic reactions from the virtual agent to the information provided by the user is a key characteristic to increase the acceptability of these virtual peers in the users.
“As presented in different studies (Bickmore & Gruber, 2010) (Lisetti & L., 2008) the conveying of empathic reactions from the virtual agent to the information provided by the user is a key characteristic to increase the acceptability of these virtual peers in the users.”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Bickmore & Gruber, 2010
Not checked in the free run.
- cites Lisetti & L., 2008
Not checked in the free run.
- Interpretationown data
Participants' responses to section 3 indicated positive results, particularly for the assessment of session length (q14).
“Similarly to the obtained results from section 2, we can see that the responses of the participants indicate positive results, particularly the assessment of the length of the session (q14).”
Quote in the paperNot a substantial claim - Interpretationown data
The results showed a positive assessment for each of the four features about the virtual agent (q17-q20).
“The obtained results show a positive assessment in each of the features represented in the four questions (see Table 6 and Figure 11).”
Quote in the paperSubstantial claim
- Classified as probably not a substantial claim. 18
- May combine two claims. 13
Probably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataThe gender distribution of participants was 26 (43.3%) women, 33 (55%) men, and one participant (1.7%) omitted this information.
“the gender distribution included 26 (43.3%) women, 33 (55%) men, and one participant omitted this information (1.7%).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown dataThe qualitative suggestions indicated that more context-based questions (e.g., university context) and questions about perceived usefulness should be included.
“From the second group of suggestions we can observe that more context-based questions (i.e. from the university context) needs to be included, as well as some question(s) about the perceived usefulness from the target users regarding the contents offered by the system.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataThe collected comments could be grouped into those focused on how session contents are presented through the GUI (P4, P21, P37, P51) and those focused on the session contents themselves (P36, P44, P49, P50).
“From the collected comments, we can identify that some of them are more focused on how the contents of the session are presented through the GUI (P4, P21, P37 and P51) and others in the contents of the sessions themselves (P36, P44, P49 and P50).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataThe qualitative suggestions indicated that more therapy-based activities were suggested.
“Moreover, we also observed that the inclusion of more therapy-based activities has been suggested.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataMany comments were positive, but many also addressed particular issues that can be improved before the pre-clinical trial.
“Many comments were positive but also many of them addressed particular issues that can be improved before the execution of the pre-clinical trial of the system.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
PremisecitationICT-based tools to prevent depression or other disorders might be a promising way forward.
“ICT-based tools to prevent depression or other disorders might be one promising way forward (Kazdin & Blase, 2011).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Kazdin & Blase, 2011
Not checked in the free run.
Classified as probably not a substantial claim.
Interpretationnone givenThe functionalities of each system component ensure a continuous user-adapted intervention, which is key to maximizing benefits for people with mental health problems.
“The functionalities of each component of the system ensure a continuous user-adapted intervention, a key aspect to maximize the benefits that this type of interventions can produce in people with problems related to mental health.”
Quote in the paperSubstantial claimMay combine two claims.
Study design and conductown dataParticipation was 96.4% for the first 20 questions and 65.8% for the last two questions (q21 and q22).
“Specifically, the participation in the first 20 questions was 96.4% and in the two last questions (q21 and q22) was 65.8%.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe FAtiMA architecture offers a generic appraisal framework where a set of different basic emotions and the coping behaviors can be generated according to a set of goals, preferences and action tendencies predefined for a virtual agent.
“Based on this theory, the FAtiMA architecture offers a generic appraisal framework where a set of different basic emotions and the coping behaviors can be generated according to a set of goals, preferences and action tendencies predefined for a virtual agent.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Dias, et al., 2014 source
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May combine two claims.
Interpretationown dataAll SUS results exceeded the threshold, indicating a good assessment of the perceived usability of the system.
“All the results exceed the threshold meaning a good assessment in the perceived usability of the system”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationEarly diagnosis and treatment of depression can relieve depression symptoms, prevent depression from returning, and help students succeed in college and university.
“Early diagnosis and treatment of depression can relieve depression symptoms, prevent depression from returning, and help students succeed in college and university (Cuijpers, et al., 2012).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Cuijpers, et al., 2012
Not checked in the free run.
Classified as probably not a substantial claim. May combine two claims.
PremisecitationThe cognitive evaluation (or appraisal) process leads to an emotional response (according to the relevance that the event has for the person), which in turn generates a specific behavior to cope with the appraised events.
“This cognitive evaluation (or appraisal) process leads to an emotional response (according to the relevance that the event has for the person), which in turn generates a specific behavior to cope with the appraised events.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Scherer, et al., 2001 source
Not checked in the free run.
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
PremisecitationPsychotherapy research needs to broaden to adopt large-scale public health strategies and treatments applicable to more patients in a simpler and cost-effective way.
“psychotherapy research needs to broaden in terms of adoption of large-scale public health strategies and treatments that can be applied to more patients in a simpler and cost-effective way (Emmelkamp, et al., 2014)”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Emmelkamp, et al., 2014
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Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationDifferent settings produce different contents in the sessions and the interaction can be more flexible or more restrictive in terms of variability and adaptability.
“As evaluated in (Bresó, et al., 2015), different settings produce different contents in the sessions and the interaction can be more flexible or more restrictive in terms of variability and adaptability.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Bresó, et al., 2015
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationThe SUS questionnaire was created by the Digital Equipment Corporation and mainly assesses perceived usability (subjective aspects of usability) on any system.
“The SUS questionnaire was created by the Digital Equipment Corporation and it is mainly focused on the assessment of perceived usability (subjective aspects of usability) on any system.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Brooke, 1996
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataThe evaluation questionnaire was online for 15 days and 60 participants accessed it.
“The questionnaire was online during 15 days and a total of 60 participants accessed to the evaluation.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationA previous study performed a functional evaluation of the system components through simulations.
“In a previous study we perform a functional evaluation of the components through a set of simulations (Bresó, et al., 2015).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Bresó, et al., 2015
Not checked in the free run.
Classified as probably not a substantial claim. May combine two claims.
Interpretationown dataThe obtained results were promising, allowing the execution of a further clinical trial.
“The obtained results were promising, allowing the execution of a further clinical trial.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
InterpretationreasoningImproving the suggested features of the virtual agent's appearance would positively influence perception of more suitable behavior and could help optimize system effectiveness.
“The further improvement of the suggested features in the appearance of the virtual agent would even positively influence the perception of a more suitable behavior during the interactive sessions, which in turn could help to optimize the effectiveness of the system.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationown dataThe acceptability results can be summarized as 70.9%, reflecting that participants rated a high level of acceptability of the framework.
“We can summarize these acceptability results as a percentage of 70.9% reflecting that the participants have rated a high level of acceptability of the framework.”
Quote in the paperSubstantial claim- Rests on an assumption: Evaluation via pre-recorded videos reflects the perceived acceptability and usability of the system.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationPeople usually feel more comfortable when interviewed by media-mediated electronic doctors and are more likely to release their flinched mind during the consultation process in contrast to human doctors.
“Regarding the use of virtual agents, there are supporting studies suggesting that people usually feel more comfortable when interviewed by media-mediated electronic doctors and are more likely to release their flinched mind during the consultation process in contrast to human doctors (Yoshida, et al., 2002).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Yoshida, et al., 2002
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Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationMany people experience the first symptoms of depression during their college or university years.
“Unfortunately, many people experience the first symptoms of depression during their college or university years (Pelkonen, et al., 2005).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Pelkonen, et al., 2005
Not checked in the free run.
The paper relies on this without support.
Depression and suicide are two major problems in the global society and are closely related.
“Both, depression and suicide are two major problems in the global society and are close related.”
The paper relies on this without support.
If depression symptoms are not opportunely detected and the individual does not receive appropriate support, in some cases the person commits suicide.
“If these symptoms are not opportunely detected and the individual does not receive an appropriate support, in some cases the person commits suicide.”
The paper relies on this without support.
University students are exposed to a challenging and competitive environment in which they must overcome new situations, stress, academic challenges, or social relationships.
“University students are exposed to challenging and competitive environment in which they must to overcome new situations, stress, academic challenges, or social relationships.”
The paper relies on this without support.
In order to optimize the effectiveness of these tools, a high level of personalization is required during the course of a session and through every session.
“Nevertheless, in order to optimize the effectiveness of these tools, a high level of personalization is required during the course of a session and through every session.”
The authors state this as an assumption.
The events produced in a person's environment are constantly evaluated by the individual.
“The key assumption of the appraisal theory of emotions is that the events produced in a person's environment are constantly evaluated by the individual.”
The paper relies on this without support.
Realism in the appearance and behaviour in a virtual agent are key issues to achieve good levels of acceptability in the target users.
“Realism in the appearance and behaviour in a virtual agent are key issues to achieve good levels of acceptability in the target users.”
The paper relies on this without support.
Offering adequate support during these periods helps to prevent depression and suicide.
“Offering adequate support during these periods helps to prevent depression and suicide.”
The paper relies on this without support.
Depression and suicidal ideation have an enormous prevalence, especially in young people.
“given the enormous prevalence of depression and suicidal ideation, especially in young people.”
The paper relies on this without support.
A good relationship between a virtual agent and the user is essential to promote continuous use of the system and to establish a therapeutic alliance that benefits the user.
“The building of a good relationship between a virtual agent and the user is essential to promote a continuous use of the system and a key ingredient to establish a therapeutic alliance that benefit the user.”
The paper relies on this without support.
The current state of technology does not allow full natural language interaction free of errors.
“As the current state of the technology does not allow a full natural language interaction free of errors, we decided to maintain the input from the user through the buttons and other controls such as combo boxes included in the GUI and not to receive the input from the user through natural language processing.”
The paper relies on this without support.
The system should adapt the length of each session according to the user's status and the clinician's requirements.
“The produced length of a session is highly important taking into account that the system should adapt the length of each session according to the status (e.g.mood) detected in the user and at the same time meeting the clinician's requirements (i.e. the scheduling of certain activities a minimum number of times per week).”
The paper relies on this without support.
Evaluation via pre-recorded videos reflects the perceived acceptability and usability of the system.
“In this study we present an initial evaluation about the perceived acceptability and usability involving 60 participants who answered a questionnaire after watching a set of pre-recorded videos containing different interactive sessions.”
The paper relies on this without support.
A sample of 60 participants is adequate to evaluate the usability and acceptability of the system.
“The questionnaire was online during 15 days and a total of 60 participants accessed to the evaluation.”
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 usability level (SUS score of 61.6) is comparable with the 2 psychological therapy chatbots with SUS scores of 63.6 and 57.0 but lower than that of asthma management (SUS score of about 83) and depression prevention chatbots (SUS score of approximately 75.7).
“This level of usability (SUS scores of 61.6) is comparable with the 2 psychological therapy chatbots with SUS scores of 63.6 and 57.0 [34] but lower than that of asthma management (SUS score of about 83) [35] and depression prevention chatbots (SUS score of approximately 75.7) [36].”
From Feasibility, Usability, and Effectiveness of a Machine Learning–Based Physical Activity Chatbot: Quasi-Experimental Study (2021) · cites this paper as [36]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Daily-use motivation is assigned to the wrong question
MinorThe results text identifies q19 as assessing whether the agent motivates daily use, whereas the questionnaire assigns that statement to q20. Q19 asks whether the agent is emotionally stable.
“how much the virtual agent contributes to the motivation of the user to execute the system every day (q19).”
“q20 The behavior of the virtual agent motivates the daily use of the PrevenDep system.”
Gender figure cites the age question
MinorThe figure caption attributes gender distribution to q1, but the questionnaire defines q1 as age and q2 as gender.
“Figure5: Participants gender distribution obtained from question q1 of the demographic section, in the evaluation questionnaire.”
“q1 Please provide your age q2 Please provide your gender q3 Please provide the institution where you usually develop your work”
Disagreement with the 'distant and aloof' statement is misstated
MinorFor q17, 26% strongly disagreed and 36% disagreed, totaling 62%, not 66%. The counts likewise total 36 of 58 respondents, or about 62%.
Reported 66 · recomputed 62
“The 66% of the participants were disagreed or strongly disagreed with the sentence that defines the virtual agents as "distant and aloof" (q17).”
Age groups are repeated instead of matching the plotted categories
MinorThe prose assigns the groups of 15, 12, and 9 participants all to ages 31-35. The age-distribution figure instead labels these successive groups 31-35, 36-40, and 41-45.
“15 people (25%) between 31 and 35; 12 participants (20%) from 31 to 35; 9 participants (15%) between 31 and 35”
“0,03 0,30 0,25 0,20 0,15 0,07 0,00 0,20 0,40 0,60 0,80 1,00 under 25 [26,30] [31,35] [36,40] [41,45] over 46”
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Yoshida, A., Hagita, Y., YAMAZAKI, K., & Yamaguchi, T. (2002) · IEEE RO-MAN · doi:10.1109/roman.1993.367690 · Cited by 6 · see citing works
Ecounsellor : an avatar for student exam stress management
Li, M., Kavakli, M., & Rudra, T. (2012) · International Conference on Information Management · Cited by 5 · see citing works
Rajamanickam, M. R. (2011) · cIRcle (University of British Columbia) · doi:10.14288/1.0052139 · Cited by 1 · see citing works
Flagged first, then by citations
Research works printed but not linked: 5
- Bole Williams B., 2013, Suicide Prevention
- Bresó A., 2016, Intelligent virtual agents applied in mental health care: a survey [under review], Journal of Medical Systems
- LisettiL. C.2008Embodied conversational agents for psychotherapy.In CHI 2008 Workshop on Technology in Mental Health.
- Organization W. H., 2014, Preventing Suicide: A Global Imperative
- Sauro J., 2011, A Practical Guide to the System Usability Scale: Background, Benchmarks & Best Practices
Cited by
Sorted by citations
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
“Chatbots were used in ten studies as a screening tool for several disorders such as dementia [34-36], tobacco and alcohol use disorders [37], stress [15], and symptoms of depression and suicide [38].”
MethodArtificially intelligent chatbots in digital mental health interventions: a review
Boucher, E. M., Harake, N. R., Ward, H. E., Stoeckl, S. E., Vargas, J., Minkel, J., Parks, A. C., & Zilca, R. (2021) · Expert Review of Medical Devices · doi:10.1080/17434440.2021.2013200 · Cited by 440 · see citing works
Survey of conversational agents in health
Montenegro, J. L. Z., da Costa, C. A., & da Rosa Righi, R. (2019) · Expert Systems with Applications · doi:10.1016/j.eswa.2019.03.054 · Cited by 322 · see citing works
Perceptions and opinions of patients about mental health chatbots: scoping review
Abd-Alrazaq, A. A., Alajlani, M., Ali, N., Denecke, K., Bewick, B. M., & Househ, M. (2021) · Journal of Medical Internet Research · doi:10.2196/17828 · Cited by 301 · see citing works
“The ease of use and usability of chatbots were assessed in 20 studies [33,34,36,39,43,46-51 ,53-61].”
InfluentialTechnical metrics used to evaluate health care chatbots: scoping review
Abd-Alrazaq, A., Safi, Z., Alajlani, M., Warren, J., Househ, M., & Denecke, K. (2020) · Journal of Medical Internet Research · doi:10.2196/18301 · Cited by 150 · see citing works
Chatbots to Support Young Adults’ Mental Health: An Exploratory Study of Acceptability
Koulouri, T., Macredie, R. D., & Olakitan, D. (2022) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/3485874 · Cited by 127 · see citing works
“Bresó et al. [2016] presented an ECA capable of generating responses and emotions to diagnose and provide support for depression.”
BackgroundFonseka, T. M., Bhat, V., & Kennedy, S. H. (2019) · Australian & New Zealand Journal of Psychiatry · doi:10.1177/0004867419864428 · Cited by 126 · see citing works
“AI conversational programs have high usability scores and are well regarded for their user-adapted content and emotional responses (Bresó et al., 2016).”
BackgroundWutz, M., Hermes, M., Winter, V., & Köberlein–Neu, J. (2023) · Journal of Medical Internet Research · doi:10.2196/46548 · Cited by 111 · see citing works
“Therefore, this relationship should also exist between users and the technology [13,15,16,23,26,54,76,78,79,82,84,87,88,94,105,112-114].”
InfluentialReimagining Healthcare: Unleashing the Power of Artificial Intelligence in Medicine
Iqbal, J., Jaimes, D. C. C., Makineni, P., Subramani, S., Hemaida, S., Thugu, T. R., Butt, A. N., Sikto, J. T., Kaur, P., Lak, M. A., et al. (2023) · Cureus · doi:10.7759/cureus.44658 · Cited by 109 · see citing works
“After the user enters the symptoms they are experiencing into the chatbot, it gives them a medical diagnosis, prognosis, and therapeutic plan (as well as information concerning the diagnosis) [96-105].”
BackgroundHuq, S. M., Maskeliūnas, R., & Damaševičius, R. (2022) · Disability and Rehabilitation Assistive Technology · doi:10.1080/17483107.2022.2146768 · Cited by 85 · see citing works
Martínez-Miranda, J., Martínez, A., Ramos, R., Aguilar, H., Jiménez, L., Arias, H., Rosales, G., & Valencia, E. (2019) · Journal of Medical Systems · doi:10.1007/s10916-019-1387-1 · Cited by 79 · see citing works
Self-citationInformation and Communication Technology Use in Suicide Prevention: Scoping Review
Rassy, J., Bardon, C., Dargis, L., Côté, L., Corthésy-Blondin, L., Mörch, C., & Labelle, R. J. (2021) · Journal of Medical Internet Research · doi:10.2196/25288 · Cited by 72 · see citing works
“Examples of these programs included Empowering a Multimodal Pathway Toward Healthy Youth [63], Reframe-IT [88], Fitmindkit [102], Safe conversation [103], Latitudes [103] and PrevenDep [104].”
Søgaard Neilsen, A., & Wilson, R. L. (2019) · International Journal of Mental Health Nursing · doi:10.1111/inm.12527 · Cited by 71 · see citing works
To, Q. G., Green, C., & Vandelanotte, C. (2021) · JMIR mHealth and uHealth · doi:10.2196/28577 · Cited by 68 · see citing works
“This level of usability (SUS scores of 61.6) is comparable with the 2 psychological therapy chatbots with SUS scores of 63.6 and 57.0 [34] but lower than that of asthma management (SUS score of about 83) [35] and depression prevention chatbots (SUS score of approximately 75.7) [36].”
ResultInfluentialMartínez-Miranda, J. (2017) · Journal of Medical Systems · doi:10.1007/s10916-017-0784-6 · Cited by 51 · see citing works
“The study presented in [33] describes the development of an interactive system containing an empathic ECA (see Fig.”
BackgroundSelf-citationNatural language processing for cognitive therapy: Extracting schemas from thought records
Burger, F., Neerincx, M. A., & Brinkman, W. (2021) · PLoS ONE · doi:10.1371/journal.pone.0257832 · Cited by 31 · see citing works
Conversational agents for depression screening: A systematic review
Otero-González, I., Pacheco-Lorenzo, M. R., Iglesias, M. J. F., & Anido, L. (2023) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2023.105272 · Cited by 26 · see citing works
My Virtual Colleague: A State-of-the-Art Analysis of Conversational Agents for the Workplace
Feng, S., & Buxmann, P. (2020) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2020.020 · Cited by 24 · see citing works
“In the area of health care several applications were proposed, such as a virtual discharge nurse [55, 56], as a counsellor for mental health issues [57, 58] and stress relief [59], as a trustworthy partner to talk about sensitive topics [60], to facilitate scalable depression and suicidal prevention [61, 62], to enabl…”
BackgroundProvoost, S., Kleiboer, A. M., Ornelas, J., Bosse, T., Ruwaard, J., Rocha, A., Cuijpers, P. J., & Riper, H. M. (2020) · Trials · doi:10.1186/s13063-020-04777-2 · Cited by 19 · see citing works
“Another pre–post-test pilot study investigated the acceptability and usability of a user-adapted, ECAsupported interactive platform addressing depression and suicide symptoms in a convenience sample of N = 60 participants [18].”
CiF-CK: An architecture for social NPCS in commercial games
Guimarães, M., Santos, P. A., & Jhala, A. H. (2017) · IEEE Conference on Computational Intelligence and Games (CIG) · doi:10.1109/cig.2017.8080425 · Cited by 19 · see citing works
“Based on cognitive appraisal theory of emotions [21], the FAtiMA architecture offers a generic appraisal framework where a set of different basic emotions and the coping behaviours can be generated according to a set of goals and preferences for a virtual agent [22].”
BackgroundSuryanto, T. L. M., Wibawa, A. P., Hariyono, H., & Nafalski, A. (2023) · International Journal of Robotics and Control Systems · doi:10.31763/ijrcs.v3i4.1195 · Cited by 21 · see citing works
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 15 · see citing works
“Chatbots and conversational agents may significantly address therapeutic messages targeting depressive symptoms (Fitzpatrick, Darcy and Vierhile, 2017) and, where detected, suicide risk (Bresó et al., 2016; Philip et al., 2017).”
Pratiwi, P. S., & Tjondronegoro, D. (2017) · IEEE Life Sciences Conference (LSC) · doi:10.1109/lsc.2017.8268130 · Cited by 4 · see citing works
“Rule-based systems were used previously to support for monitoring[10] and diagnosis [11].”
MethodDigital 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 · see citing works
“Correspondingly, all digital humans support speech synthesis and audio output, but only 5 digital humans are capable of delivering empathy narration [22,27,29,30,35].”
InfluentialGuimarães, M., Santos, P. A., & Jhala, A. H. (2017) · Adaptive Agents and Multi-Agents Systems · doi:10.5555/3091125.3091441 · Cited by 3 · see citing works
Detecting depression through speech and text from casual talks with fully automated virtual humans
Gómez-Zaragozá, L., Altozano, A., Llanes-Jurado, J., Minissi, M. E., Alcañíz, M., & Marín‐Morales, J. (2025) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2025.103305 · Cited by 2 · see citing works
Prom week meets Skyrim: Developing a social agent architecture in a commercial game
Guimarães, M., Santos, P. A., & Jhala, A. H. (2017) · DSpace (Open University in the Netherlands) · Cited by 2 · see citing works
Li, X., Cui, W., Olatunji, S., & Piercy, C. W. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2026.2692012 · Cited by 1 · see citing works
Visually multimodal depression assessment based on key questions with weighted multi-task learning
Wang, P., Cao, M., Zhu, X., Wang, S., Ni, R., Yang, C., & Yang, B. (2025) · Signal Processing Image Communication · doi:10.1016/j.image.2025.117279 · Cited by 1 · see citing works
Link, M., Gerth, S., Belikova-Gerth, V., & Jesse, J. (2023) · Springer eBooks · doi:10.1007/978-3-658-42060-4_9
Biased Reasoning with Unbalanced Attention for Autopilot Flight Considering Anchoring EffectsPreprint
Zhou, Y., & Fu, S. (2024) · Research Square · doi:10.21203/rs.3.rs-4771973/v1
Quaternary Correlation Prediction Compensation for Heading Commands in Virtual Autopilot
Zhou, Y., & Fu, S. (2025) · Aerospace · doi:10.3390/aerospace12100936
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
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.13106339
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.13106345
Coulombe, S., Rickard, N. S., Pacheco, T., Francis, J., Vella-Brodrick, D., Dionne, É., Shestopaloff, A., Vokey, F., Hoang, N. B. L., Leitch, J., et al. (2026) · doi:10.2196/preprints.114548
- Authors
- Bresó, A., Martínez‐Miranda, J., Botella, C., Baños, R. M., & García‐Gómez, J. M.
- Affiliations
- Universitat Politècnica de València (ES)
- CONACYT Research Fellow – Centro de Investigación Científica y de Educación Superior de Ensenada Unidad de Transferencia Tecnológica (CICESE‐UT3) Tepic México
- Universitat Jaume I (ES)
- Universitat de València (ES)
- Grupo de Informática Biomédica, Instituto ITACA Universitat Politècnica de València Spain
- Corresponding author
- Bresó, A.
- Venue
- Expert Systems
- Publisher
- Wiley
- Published
- 2016-05-25
- Volume
- 33
- Issue
- 4
- Pages
- 297-312
- ISSN
- 0266-4720 (ISSN-L)
- 1468-0394
- OpenAlex
- W2398410084
- Cited by
- 36
- References
- 33
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 2 · 2023: 5 · 2022: 2 · 2021: 4 · 2020: 7 · 2019: 4 · 2018: 1 · 2017: 5
- FWCI
- 5.12
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Expert Systems (publishedVersion)
- RiuNet (Universitat Politècnica de València) (submittedVersion, cc-by-nc-nd)
- Funders
- Generalitat Valenciana
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
- Keywords
- depression prevention, suicide prevention, early intervention, usability evaluation, acceptability, personalized dialogue generation, university students
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Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-10.
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