scholarly journals Hybrid Ubiquitous Coaching With a Novel Combination of Mobile and Holographic Conversational Agents Targeting Adherence to Home Exercises: Four Design and Evaluation Studies

10.2196/23612 ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. e23612
Author(s):  
Tobias Kowatsch ◽  
Kim-Morgaine Lohse ◽  
Valérie Erb ◽  
Leo Schittenhelm ◽  
Helen Galliker ◽  
...  
Keyword(s):  
Health Care ◽  
Augmented Reality ◽  
Working Alliance ◽  
Heart Diseases ◽  
Evaluation Studies ◽  
Relative Advantage ◽  
Adherence Rate ◽  
Future Research ◽  
Conversational Agents ◽  
Promising Tool

Background Effective treatments for various conditions such as obesity, cardiac heart diseases, or low back pain require not only personal on-site coaching sessions by health care experts but also a significant amount of home exercises. However, nonadherence to home exercises is still a serious problem as it leads to increased costs due to prolonged treatments. Objective To improve adherence to home exercises, we propose, implement, and assess the novel coaching concept of hybrid ubiquitous coaching (HUC). In HUC, health care experts are complemented by a conversational agent (CA) that delivers psychoeducation and personalized motivational messages via a smartphone, as well as real-time exercise support, monitoring, and feedback in a hands-free augmented reality environment. Methods We applied HUC to the field of physiotherapy and conducted 4 design-and-evaluate loops with an interdisciplinary team to assess how HUC is perceived by patients and physiotherapists and whether HUC leads to treatment adherence. A first version of HUC was evaluated by 35 physiotherapy patients in a lab setting to identify patients’ perceptions of HUC. In addition, 11 physiotherapists were interviewed about HUC and assessed whether the CA could help them build up a working alliance with their patients. A second version was then tested by 15 patients in a within-subject experiment to identify the ability of HUC to address adherence and to build a working alliance between the patient and the CA. Finally, a 4-week n-of-1 trial was conducted with 1 patient to show one experience with HUC in depth and thereby potentially reveal real-world benefits and challenges. Results Patients perceived HUC to be useful, easy to use, and enjoyable, preferred it to state-of-the-art approaches, and expressed their intentions to use it. Moreover, patients built a working alliance with the CA. Physiotherapists saw a relative advantage of HUC compared to current approaches but initially did not see the potential in terms of a working alliance, which changed after seeing the results of HUC in the field. Qualitative feedback from patients indicated that they enjoyed doing the exercise with an augmented reality–based CA and understood better how to do the exercise correctly with HUC. Moreover, physiotherapists highlighted that HUC would be helpful to use in the therapy process. The longitudinal field study resulted in an adherence rate of 92% (11/12 sessions; 330/360 repetitions; 33/36 sets) and a substantial increase in exercise accuracy during the 4 weeks. Conclusions The overall positive assessments from both patients and health care experts suggest that HUC is a promising tool to be applied in various disorders with a relevant set of home exercises. Future research, however, must implement a variety of exercises and test HUC with patients suffering from different disorders.

scholarly journals Hybrid Ubiquitous Coaching With a Novel Combination of Mobile and Holographic Conversational Agents Targeting Adherence to Home Exercises: Four Design and Evaluation Studies (Preprint)

2020 ◽  
Author(s):  
Tobias Kowatsch ◽  
Kim-Morgaine Lohse ◽  
Valérie Erb ◽  
Leo Schittenhelm ◽  
Helen Galliker ◽  
...  
Keyword(s):  
Health Care ◽  
Augmented Reality ◽  
Working Alliance ◽  
Heart Diseases ◽  
Evaluation Studies ◽  
Relative Advantage ◽  
Adherence Rate ◽  
Future Research ◽  
Conversational Agents ◽  
Promising Tool

BACKGROUND Effective treatments for various conditions such as obesity, cardiac heart diseases, or low back pain require not only personal on-site coaching sessions by health care experts but also a significant amount of home exercises. However, nonadherence to home exercises is still a serious problem as it leads to increased costs due to prolonged treatments. OBJECTIVE To improve adherence to home exercises, we propose, implement, and assess the novel coaching concept of hybrid ubiquitous coaching (HUC). In HUC, health care experts are complemented by a conversational agent (CA) that delivers psychoeducation and personalized motivational messages via a smartphone, as well as real-time exercise support, monitoring, and feedback in a hands-free augmented reality environment. METHODS We applied HUC to the field of physiotherapy and conducted 4 design-and-evaluate loops with an interdisciplinary team to assess how HUC is perceived by patients and physiotherapists and whether HUC leads to treatment adherence. A first version of HUC was evaluated by 35 physiotherapy patients in a lab setting to identify patients’ perceptions of HUC. In addition, 11 physiotherapists were interviewed about HUC and assessed whether the CA could help them build up a working alliance with their patients. A second version was then tested by 15 patients in a within-subject experiment to identify the ability of HUC to address adherence and to build a working alliance between the patient and the CA. Finally, a 4-week n-of-1 trial was conducted with 1 patient to show one experience with HUC in depth and thereby potentially reveal real-world benefits and challenges. RESULTS Patients perceived HUC to be useful, easy to use, and enjoyable, preferred it to state-of-the-art approaches, and expressed their intentions to use it. Moreover, patients built a working alliance with the CA. Physiotherapists saw a relative advantage of HUC compared to current approaches but initially did not see the potential in terms of a working alliance, which changed after seeing the results of HUC in the field. Qualitative feedback from patients indicated that they enjoyed doing the exercise with an augmented reality–based CA and understood better how to do the exercise correctly with HUC. Moreover, physiotherapists highlighted that HUC would be helpful to use in the therapy process. The longitudinal field study resulted in an adherence rate of 92% (11/12 sessions; 330/360 repetitions; 33/36 sets) and a substantial increase in exercise accuracy during the 4 weeks. CONCLUSIONS The overall positive assessments from both patients and health care experts suggest that HUC is a promising tool to be applied in various disorders with a relevant set of home exercises. Future research, however, must implement a variety of exercises and test HUC with patients suffering from different disorders.

scholarly journals Conversational Agents in Health Care: Scoping Review and Conceptual Analysis (Preprint)

2019 ◽  
Author(s):  
Lorainne Tudor Car ◽  
Dhakshenya Ardhithy Dhinagaran ◽  
Bhone Myint Kyaw ◽  
Tobias Kowatsch ◽  
Shafiq Joty ◽  
...  
Keyword(s):  
Health Care ◽  
Scoping Review ◽  
Literature Search ◽  
Care Service ◽  
Health Care Service ◽  
Improve Patient Care ◽  
Future Research ◽  
Free Text ◽  
Conversational Agents ◽  
Service Support

BACKGROUND Conversational agents, also known as chatbots, are computer programs designed to simulate human text or verbal conversations. They are increasingly used in a range of fields, including health care. By enabling better accessibility, personalization, and efficiency, conversational agents have the potential to improve patient care. OBJECTIVE This study aimed to review the current applications, gaps, and challenges in the literature on conversational agents in health care and provide recommendations for their future research, design, and application. METHODS We performed a scoping review. A broad literature search was performed in MEDLINE (Medical Literature Analysis and Retrieval System Online; Ovid), EMBASE (Excerpta Medica database; Ovid), PubMed, Scopus, and Cochrane Central with the search terms “conversational agents,” “conversational AI,” “chatbots,” and associated synonyms. We also searched the gray literature using sources such as the OCLC (Online Computer Library Center) WorldCat database and ResearchGate in April 2019. Reference lists of relevant articles were checked for further articles. Screening and data extraction were performed in parallel by 2 reviewers. The included evidence was analyzed narratively by employing the principles of thematic analysis. RESULTS The literature search yielded 47 study reports (45 articles and 2 ongoing clinical trials) that matched the inclusion criteria. The identified conversational agents were largely delivered via smartphone apps (n=23) and used free text only as the main input (n=19) and output (n=30) modality. Case studies describing chatbot development (n=18) were the most prevalent, and only 11 randomized controlled trials were identified. The 3 most commonly reported conversational agent applications in the literature were treatment and monitoring, health care service support, and patient education. CONCLUSIONS The literature on conversational agents in health care is largely descriptive and aimed at treatment and monitoring and health service support. It mostly reports on text-based, artificial intelligence–driven, and smartphone app–delivered conversational agents. There is an urgent need for a robust evaluation of diverse health care conversational agents’ formats, focusing on their acceptability, safety, and effectiveness.

scholarly journals The Effectiveness of Artificial Intelligence Conversational Agents in Health Care: Systematic Review (Preprint)

2020 ◽  
Author(s):  
Madison Milne-Ives ◽  
Caroline de Cock ◽  
Ernest Lim ◽  
Melissa Harper Shehadeh ◽  
Nick de Pennington ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Systematic Review ◽  
Health Care ◽  
Language Processing ◽  
Health Care Services ◽  
Interactive Voice Response ◽  
Future Research ◽  
Conversational Agents ◽  
Privacy And Security ◽  
Care Services

BACKGROUND The high demand for health care services and the growing capability of artificial intelligence have led to the development of conversational agents designed to support a variety of health-related activities, including behavior change, treatment support, health monitoring, training, triage, and screening support. Automation of these tasks could free clinicians to focus on more complex work and increase the accessibility to health care services for the public. An overarching assessment of the acceptability, usability, and effectiveness of these agents in health care is needed to collate the evidence so that future development can target areas for improvement and potential for sustainable adoption. OBJECTIVE This systematic review aims to assess the effectiveness and usability of conversational agents in health care and identify the elements that users like and dislike to inform future research and development of these agents. METHODS PubMed, Medline (Ovid), EMBASE (Excerpta Medica dataBASE), CINAHL (Cumulative Index to Nursing and Allied Health Literature), Web of Science, and the Association for Computing Machinery Digital Library were systematically searched for articles published since 2008 that evaluated unconstrained natural language processing conversational agents used in health care. EndNote (version X9, Clarivate Analytics) reference management software was used for initial screening, and full-text screening was conducted by 1 reviewer. Data were extracted, and the risk of bias was assessed by one reviewer and validated by another. RESULTS A total of 31 studies were selected and included a variety of conversational agents, including 14 chatbots (2 of which were voice chatbots), 6 embodied conversational agents (3 of which were interactive voice response calls, virtual patients, and speech recognition screening systems), 1 contextual question-answering agent, and 1 voice recognition triage system. Overall, the evidence reported was mostly positive or mixed. Usability and satisfaction performed well (27/30 and 26/31), and positive or mixed effectiveness was found in three-quarters of the studies (23/30). However, there were several limitations of the agents highlighted in specific qualitative feedback. CONCLUSIONS The studies generally reported positive or mixed evidence for the effectiveness, usability, and satisfactoriness of the conversational agents investigated, but qualitative user perceptions were more mixed. The quality of many of the studies was limited, and improved study design and reporting are necessary to more accurately evaluate the usefulness of the agents in health care and identify key areas for improvement. Further research should also analyze the cost-effectiveness, privacy, and security of the agents. INTERNATIONAL REGISTERED REPORT RR2-10.2196/16934

scholarly journals The Effectiveness of Artificial Intelligence Conversational Agents in Health Care: Systematic Review

10.2196/20346 ◽  
2020 ◽  
Vol 22 (10) ◽  
pp. e20346
Author(s):  
Madison Milne-Ives ◽  
Caroline de Cock ◽  
Ernest Lim ◽  
Melissa Harper Shehadeh ◽  
Nick de Pennington ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Systematic Review ◽  
Health Care ◽  
Language Processing ◽  
Health Care Services ◽  
Interactive Voice Response ◽  
Future Research ◽  
Conversational Agents ◽  
Privacy And Security ◽  
Care Services

Background The high demand for health care services and the growing capability of artificial intelligence have led to the development of conversational agents designed to support a variety of health-related activities, including behavior change, treatment support, health monitoring, training, triage, and screening support. Automation of these tasks could free clinicians to focus on more complex work and increase the accessibility to health care services for the public. An overarching assessment of the acceptability, usability, and effectiveness of these agents in health care is needed to collate the evidence so that future development can target areas for improvement and potential for sustainable adoption. Objective This systematic review aims to assess the effectiveness and usability of conversational agents in health care and identify the elements that users like and dislike to inform future research and development of these agents. Methods PubMed, Medline (Ovid), EMBASE (Excerpta Medica dataBASE), CINAHL (Cumulative Index to Nursing and Allied Health Literature), Web of Science, and the Association for Computing Machinery Digital Library were systematically searched for articles published since 2008 that evaluated unconstrained natural language processing conversational agents used in health care. EndNote (version X9, Clarivate Analytics) reference management software was used for initial screening, and full-text screening was conducted by 1 reviewer. Data were extracted, and the risk of bias was assessed by one reviewer and validated by another. Results A total of 31 studies were selected and included a variety of conversational agents, including 14 chatbots (2 of which were voice chatbots), 6 embodied conversational agents (3 of which were interactive voice response calls, virtual patients, and speech recognition screening systems), 1 contextual question-answering agent, and 1 voice recognition triage system. Overall, the evidence reported was mostly positive or mixed. Usability and satisfaction performed well (27/30 and 26/31), and positive or mixed effectiveness was found in three-quarters of the studies (23/30). However, there were several limitations of the agents highlighted in specific qualitative feedback. Conclusions The studies generally reported positive or mixed evidence for the effectiveness, usability, and satisfactoriness of the conversational agents investigated, but qualitative user perceptions were more mixed. The quality of many of the studies was limited, and improved study design and reporting are necessary to more accurately evaluate the usefulness of the agents in health care and identify key areas for improvement. Further research should also analyze the cost-effectiveness, privacy, and security of the agents. International Registered Report Identifier (IRRID) RR2-10.2196/16934

Adoption of internet of things (IOT) based wearables for healthcare of older adults – a behavioural reasoning theory (BRT) approach

2018 ◽  
Vol 12 (4) ◽  
pp. 169-185 ◽  
Author(s):  
Brijesh Sivathanu
Keyword(s):  
Older Adults ◽  
Health Care ◽  
Internet Of Things ◽  
Cross Sectional Study ◽  
Relative Effect ◽  
Relative Advantage ◽  
Future Research ◽  
Cross Sectional ◽  
Content Type ◽  
Adoption Factors

PurposeThe purpose of this paper is to utilize the novel approach of applying the behavioral reasoning theory (BRT) to examine the adoption of internet of things (IoT) based wearables for the healthcare of older adults and it aims to understand the relative effect of “reasons for” and “reasons against” adoption of IoT-based wearables for health care among older adults.Design/methodology/approachThe hypothesized relationships were established using the BRT and empirically tested using a representative sample of 815 respondents. The data were analyzed using the PLS-SEM method.FindingsThe findings of this study demonstrate that adoption intention of IoT-based wearables for the health care of older adults is influenced by “reason for” and “reason against” adoption. The finding shows that “reasons for” adoption are ubiquitous, relative advantage, compatibility and convenience and “reasons against” adoption are usage barrier, traditional barrier and risk barrier. Value of “openness to change” significantly influences the “reasons for” and “reasons against” adoption of IoT-based wearables.Research limitations/implicationsThis cross-sectional study is conducted only in the Indian context and future research can be conducted in other countries to generalize the results.Practical implicationsThis research highlighted both the adoption factors—“for” and “against,” which should be considered while developing marketing strategies for IoT-based wearables for health care of older adults. Adoption of IoT-based wearables for healthcare of older adults will increase when marketers endeavor to minimize the effects of the anti-adoption factors.Originality/valueThis is a unique study that examines the adoption of IoT-based wearables for healthcare among older people using the BRT, by probing the “reasons for” and “reasons against” adoption in a single framework.

scholarly journals Conversational Agents in Health Care: Scoping Review and Conceptual Analysis

10.2196/17158 ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. e17158 ◽  
Author(s):  
Lorainne Tudor Car ◽  
Dhakshenya Ardhithy Dhinagaran ◽  
Bhone Myint Kyaw ◽  
Tobias Kowatsch ◽  
Shafiq Joty ◽  
...  
Keyword(s):  
Health Care ◽  
Scoping Review ◽  
Literature Search ◽  
Care Service ◽  
Health Care Service ◽  
Improve Patient Care ◽  
Future Research ◽  
Free Text ◽  
Conversational Agents ◽  
Service Support

Background Conversational agents, also known as chatbots, are computer programs designed to simulate human text or verbal conversations. They are increasingly used in a range of fields, including health care. By enabling better accessibility, personalization, and efficiency, conversational agents have the potential to improve patient care. Objective This study aimed to review the current applications, gaps, and challenges in the literature on conversational agents in health care and provide recommendations for their future research, design, and application. Methods We performed a scoping review. A broad literature search was performed in MEDLINE (Medical Literature Analysis and Retrieval System Online; Ovid), EMBASE (Excerpta Medica database; Ovid), PubMed, Scopus, and Cochrane Central with the search terms “conversational agents,” “conversational AI,” “chatbots,” and associated synonyms. We also searched the gray literature using sources such as the OCLC (Online Computer Library Center) WorldCat database and ResearchGate in April 2019. Reference lists of relevant articles were checked for further articles. Screening and data extraction were performed in parallel by 2 reviewers. The included evidence was analyzed narratively by employing the principles of thematic analysis. Results The literature search yielded 47 study reports (45 articles and 2 ongoing clinical trials) that matched the inclusion criteria. The identified conversational agents were largely delivered via smartphone apps (n=23) and used free text only as the main input (n=19) and output (n=30) modality. Case studies describing chatbot development (n=18) were the most prevalent, and only 11 randomized controlled trials were identified. The 3 most commonly reported conversational agent applications in the literature were treatment and monitoring, health care service support, and patient education. Conclusions The literature on conversational agents in health care is largely descriptive and aimed at treatment and monitoring and health service support. It mostly reports on text-based, artificial intelligence–driven, and smartphone app–delivered conversational agents. There is an urgent need for a robust evaluation of diverse health care conversational agents’ formats, focusing on their acceptability, safety, and effectiveness.

Barriers and Facilitators to Automated Patient Self-Scheduling for Health Care Organizations: Scoping Review (Preprint)

2021 ◽  
Author(s):  
Elizabeth Woodcock
Keyword(s):  
Health Care ◽  
Scoping Review ◽  
Health Care Organizations ◽  
National Policy ◽  
Outpatient Setting ◽  
The Body ◽  
Barriers And Facilitators ◽  
Organizational Level ◽  
Relative Advantage ◽  
Future Research

BACKGROUND Appointment management in the outpatient setting is important for health care organizations as waits and delays lead to poor outcomes. Automated patient self-scheduling of outpatient appointments has demonstrable advantages in the form of patients’ arrival rates, labor savings, patient satisfaction, and more. Despite evidence of the potential benefits of self-scheduling, organizational uptake of self-scheduling in health care has been limited. The goal of this scoping study is to identify the barriers and facilitators to self-scheduling for health care organizations. OBJECTIVE - METHODS A scoping review was conducted by searching four databases (PubMed, CINAHL, Business Source Ultimate and Scopus) and systematically reviewing peer-reviewed studies. The Consolidated Framework for Implementation Research (CFIR) framework was utilized to catalogue the studies. RESULTS Thirty-one full-text articles were included in the review. Results demonstrated that self-scheduling initiatives have increased over time, indicating the broadening appeal of self-scheduling. The body of literature regarding the intervention characteristics of self-scheduling, including evidence, relative advantage, and adaptability, is appreciable. The influence of national policy was the most-cited external factor, as defined by the CFIR framework. Scholarly pursuit lacked recommendations related to the framework’s inner setting, characteristics of individuals and process. Future discoveries regarding these CFIR domains may help detect, categorize, and appreciate organizational-level barriers and facilitators to self-scheduling to advance knowledge about this solution. CONCLUSIONS The scoping review catalogued evidence of the existence, advantages, and intervention characteristics of patient self-scheduling; gaps in knowledge of the uptake of self-scheduling by health care organizations were identified to inform future research.

scholarly journals Conversational Agents as Mediating Social Actors in Chronic Disease Management Involving Health Care Professionals, Patients, and Family Members: Multisite Single-Arm Feasibility Study

10.2196/25060 ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. e25060
Author(s):  
Tobias Kowatsch ◽  
Theresa Schachner ◽  
Samira Harperink ◽  
Filipe Barata ◽  
Ullrich Dittler ◽  
...  
Keyword(s):  
Health Care ◽  
Chronic Disease ◽  
Disease Management ◽  
Family Member ◽  
Working Alliance ◽  
Health Care Professionals ◽  
Chronic Disease Management ◽  
Family Members ◽  
Conversational Agent ◽  
Conversational Agents

Background Successful management of chronic diseases requires a trustful collaboration between health care professionals, patients, and family members. Scalable conversational agents, designed to assist health care professionals, may play a significant role in supporting this collaboration in a scalable way by reaching out to the everyday lives of patients and their family members. However, to date, it remains unclear whether conversational agents, in such a role, would be accepted and whether they can support this multistakeholder collaboration. Objective With asthma in children representing a relevant target of chronic disease management, this study had the following objectives: (1) to describe the design of MAX, a conversational agent–delivered asthma intervention that supports health care professionals targeting child-parent teams in their everyday lives; and (2) to assess the (a) reach of MAX, (b) conversational agent–patient working alliance, (c) acceptance of MAX, (d) intervention completion rate, (e) cognitive and behavioral outcomes, and (f) human effort and responsiveness of health care professionals in primary and secondary care settings. Methods MAX was designed to increase cognitive skills (ie, knowledge about asthma) and behavioral skills (ie, inhalation technique) in 10-15-year-olds with asthma, and enables support by a health professional and a family member. To this end, three design goals guided the development: (1) to build a conversational agent–patient working alliance; (2) to offer hybrid (human- and conversational agent–supported) ubiquitous coaching; and (3) to provide an intervention with high experiential value. An interdisciplinary team of computer scientists, asthma experts, and young patients with their parents developed the intervention collaboratively. The conversational agent communicates with health care professionals via email, with patients via a mobile chat app, and with a family member via SMS text messaging. A single-arm feasibility study in primary and secondary care settings was performed to assess MAX. Results Results indicated an overall positive evaluation of MAX with respect to its reach (49.5%, 49/99 of recruited and eligible patient-family member teams participated), a strong patient-conversational agent working alliance, and high acceptance by all relevant stakeholders. Moreover, MAX led to improved cognitive and behavioral skills and an intervention completion rate of 75.5%. Family members supported the patients in 269 out of 275 (97.8%) coaching sessions. Most of the conversational turns (99.5%) were conducted between patients and the conversational agent as opposed to between patients and health care professionals, thus indicating the scalability of MAX. In addition, it took health care professionals less than 4 minutes to assess the inhalation technique and 3 days to deliver related feedback to the patients. Several suggestions for improvement were made. Conclusions This study provides the first evidence that conversational agents, designed as mediating social actors involving health care professionals, patients, and family members, are not only accepted in such a “team player” role but also show potential to improve health-relevant outcomes in chronic disease management.

scholarly journals The Personalization of Conversational Agents in Health Care: Systematic Review (Preprint)

2019 ◽  
Author(s):  
Ahmet Baki Kocaballi ◽  
Shlomo Berkovsky ◽  
Juan C Quiroz ◽  
Liliana Laranjo ◽  
Huong Ly Tong ◽  
...  
Keyword(s):  
Systematic Review ◽  
Health Care ◽  
Natural Language ◽  
Health Outcomes ◽  
Health Care Professionals ◽  
User Satisfaction ◽  
Future Research ◽  
User Engagement ◽  
Conversational Agents ◽  
Design Factor

BACKGROUND The personalization of conversational agents with natural language user interfaces is seeing increasing use in health care applications, shaping the content, structure, or purpose of the dialogue between humans and conversational agents. OBJECTIVE The goal of this systematic review was to understand the ways in which personalization has been used with conversational agents in health care and characterize the methods of its implementation. METHODS We searched on PubMed, Embase, CINAHL, PsycInfo, and ACM Digital Library using a predefined search strategy. The studies were included if they: (1) were primary research studies that focused on consumers, caregivers, or health care professionals; (2) involved a conversational agent with an unconstrained natural language interface; (3) tested the system with human subjects; and (4) implemented personalization features. RESULTS The search found 1958 publications. After abstract and full-text screening, 13 studies were included in the review. Common examples of personalized content included feedback, daily health reports, alerts, warnings, and recommendations. The personalization features were implemented without a theoretical framework of customization and with limited evaluation of its impact. While conversational agents with personalization features were reported to improve user satisfaction, user engagement and dialogue quality, the role of personalization in improving health outcomes was not assessed directly. CONCLUSIONS Most of the studies in our review implemented the personalization features without theoretical or evidence-based support for them and did not leverage the recent developments in other domains of personalization. Future research could incorporate personalization as a distinct design factor with a more careful consideration of its impact on health outcomes and its implications on patient safety, privacy, and decision-making.

scholarly journals The Personalization of Conversational Agents in Health Care: Systematic Review

10.2196/15360 ◽  
2019 ◽  
Vol 21 (11) ◽  
pp. e15360 ◽  
Author(s):  
Ahmet Baki Kocaballi ◽  
Shlomo Berkovsky ◽  
Juan C Quiroz ◽  
Liliana Laranjo ◽  
Huong Ly Tong ◽  
...  
Keyword(s):  
Systematic Review ◽  
Health Care ◽  
Natural Language ◽  
Health Outcomes ◽  
Health Care Professionals ◽  
User Satisfaction ◽  
Future Research ◽  
User Engagement ◽  
Conversational Agents ◽  
Design Factor

Background The personalization of conversational agents with natural language user interfaces is seeing increasing use in health care applications, shaping the content, structure, or purpose of the dialogue between humans and conversational agents. Objective The goal of this systematic review was to understand the ways in which personalization has been used with conversational agents in health care and characterize the methods of its implementation. Methods We searched on PubMed, Embase, CINAHL, PsycInfo, and ACM Digital Library using a predefined search strategy. The studies were included if they: (1) were primary research studies that focused on consumers, caregivers, or health care professionals; (2) involved a conversational agent with an unconstrained natural language interface; (3) tested the system with human subjects; and (4) implemented personalization features. Results The search found 1958 publications. After abstract and full-text screening, 13 studies were included in the review. Common examples of personalized content included feedback, daily health reports, alerts, warnings, and recommendations. The personalization features were implemented without a theoretical framework of customization and with limited evaluation of its impact. While conversational agents with personalization features were reported to improve user satisfaction, user engagement and dialogue quality, the role of personalization in improving health outcomes was not assessed directly. Conclusions Most of the studies in our review implemented the personalization features without theoretical or evidence-based support for them and did not leverage the recent developments in other domains of personalization. Future research could incorporate personalization as a distinct design factor with a more careful consideration of its impact on health outcomes and its implications on patient safety, privacy, and decision-making.

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