Conversational Agents as Mediating Social Actors in Chronic Disease Management Involving Health Care Professionals, Patients, and Family Members: Multisite Single-Arm Feasibility Study
Open accessPublished version of a preprint
Abstract
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.
AI snapshot
Written from the paper’s full text.
TL;DR
In a multisite single-arm feasibility study, MAX, a conversational agent designed as a mediating social actor for pediatric asthma, was feasible and positively evaluated across patients, family members, and health care professionals. It showed high reach, strong patient-agent working alliance, 75.5% completion, improved asthma knowledge, and scalable delivery with most conversational turns handled by the agent.
Key findings
- Reach was 49.5% (49/99 recruited and eligible patient-family member teams started interacting with MAX); intervention completion was 75.5% (37/49).
- Patient-MAX working alliance was high across coaching sessions 2, 8, and 14 (means 6.34, 6.14, and 6.34, respectively), and acceptance ratings were above the neutral scale value of 4 (perceived usefulness 6.42, ease of use 6.75, enjoyment 6.47, control 5.53, intention to continue 5.58).
- Asthma knowledge increased significantly from pretest to posttest (7.73 to 8.79 with baseline observation carried forward, n=48, P<.001, d=0.91; 9.43 in complete cases, n=37, P<.001, d=1.19).
- Family members supported patients in 269/275 (97.8%) coaching sessions; 99.5% (15,078/15,152) of conversational turns were between patients and MAX versus 0.5% (74/15,152) between patients and health care professionals. Health care professionals took an average of 221 seconds to assess inhalation videos and 2.34 days to provide feedback.
Methods
- Single-arm feasibility study conducted in two home care settings and four secondary care settings in the German-speaking part of Switzerland; recruitment occurred January-April 2019.
- Participants were 10- to 15-year-old German-speaking patients with asthma who had smartphone access and a German-speaking family member able to receive SMS messages and support the patient every second intervention day; 99 patients were approached and 49 started interacting with MAX.
- Outcomes included reach, patient-conversational agent working alliance, acceptance, intervention completion, cognitive and behavioral skills, and human effort/responsiveness; analyses included descriptive statistics, paired-sample t tests for asthma knowledge, and qualitative feedback.
Limitations
- The paper states that this was a feasibility study with a limited sample, so results are not representative and must be interpreted with caution; only health care professionals from four hospitals and two cantonal patient organizations participated, leaving unclear whether MAX would work similarly with general practitioners.
- The paper states that qualitative open coding was performed by one author, social support was self-reported and incentivized and thus likely overestimated, and the MAX interface was not integrated into hospital or patient-organization information systems, likely overestimating efforts; only costs and efforts were reported, so no cost-effectiveness implications can be drawn.
- Evident from the text: the single-arm design without a control group limits causal conclusions about intervention effects, and the small, exploratory sample constrains generalizability.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
0 of 97 cited sources checked · 0 supported · 0 flagged
- Findingown data
Most conversational turns (99.5%) were conducted between patients and the conversational agent as opposed to between patients and health care professionals.
“Most of the conversational turns (99.5%) were conducted between patients and the conversational agent as opposed to between patients and health care professionals”
Quote in the paperSubstantial claim - Findingown data
The intervention completion rate was 75.5%.
“an intervention completion rate of 75.5%”
Quote in the paperNot a substantial claim - Findingown data
Family members supported the patients in 269 out of 275 (97.8%) coaching sessions.
“Family members supported the patients in 269 out of 275 (97.8%) coaching sessions.”
Quote in the paperSubstantial claim - Findingown data
It took health care professionals less than 4 minutes to assess the inhalation technique.
“it took health care professionals less than 4 minutes to assess the inhalation technique”
Quote in the paperNot a substantial claim - Findingown data
MAX achieved a strong patient-conversational agent working alliance.
“a strong patient-conversational agent working alliance”
Quote in the paperSubstantial claim
- Findingown data
MAX was highly accepted by all relevant stakeholders.
“high acceptance by all relevant stakeholders”
Quote in the paperSubstantial claim - Findingown data
The reach of MAX was 49.5% (49/99 of recruited and eligible patient-family member teams participated).
“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)”
Quote in the paperSubstantial claim - Findingown data
The session alliance inventory indicated high working alliance ratings between the young patients and the MAX conversational agent from the very beginning of the intervention until the end.
“The session alliance inventory indicated high working alliance ratings between the young patients and the MAX conversational agent from the very beginning of the intervention until the end (Table 1).”
Quote in the paperNot a substantial claim - Findingown data
Out of 275 coaching sessions in which a family member was asked to support the young patients, patients indicated 269 times (97.8%) that they were supported by a family member.
“Out of 275 coaching sessions, in which a family member was asked to support the young patients, patients indicated 269 times (97.8%) that they were supported by a family member.”
Quote in the paperNot a substantial claim - Findingown data
Paired-sample t tests revealed a significant increase in asthma knowledge scores and large effects with a complete case analysis (n=37, t36=-3.68, P<.001, d=1.19).
“Paired-sample t tests revealed a significant increase in scores and large effects with two approaches: a complete case analysis (n=37, t36=–3.68, P<.001, d=1.19) and with the baseline observation carried forward (n=48, t47=–3.54, P<.001, d=0.91).”
Quote in the paperSubstantial claim - Findingown data
The most frequent dropouts happened during onboarding (n=3) and Coaching Session 6 (n=3).
“Availability of a smartphone was the major reason for nonparticipation (n=14, 14%), and the most frequent dropouts happened during onboarding (n=3) and Coaching Session 6 (n=3).”
Quote in the paperNot a substantial claim - Findingown data
Health care professionals identified 0.9 inhalation mistakes in each video clip (N=42).
“In summary, health care professionals identified 0.9 inhalation mistakes in each video clip (N=42).”
Quote in the paperNot a substantial claim - Findingown data
Between 0.1 and 2.5 SMS reminders were sent out on average per patient by the MAX conversational agent.
“between 0.1 and 2.5 SMS reminders were sent out on average per patient by the MAX conversational agent (Table 1)”
Quote in the paperNot a substantial claim - Findingown data
Availability of a smartphone was the major reason for nonparticipation (n=14, 14%).
“Availability of a smartphone was the major reason for nonparticipation (n=14, 14%), and the most frequent dropouts happened during onboarding (n=3) and Coaching Session 6 (n=3).”
Quote in the paperNot a substantial claim - Findingown data
Paired-sample t tests revealed a significant increase in asthma knowledge scores and large effects with baseline observation carried forward (n=48, t47=-3.54, P<.001, d=0.91).
“Paired-sample t tests revealed a significant increase in scores and large effects with two approaches: a complete case analysis (n=37, t36=–3.68, P<.001, d=1.19) and with the baseline observation carried forward (n=48, t47=–3.54, P<.001, d=0.91).”
Quote in the paperSubstantial claim - Findingown data
Patients received feedback on their submitted video clips after an average of approximately 2.4 days.
“patients received feedback on their submitted video clips after an average of approximately 2.4 days (Table 2).”
Quote in the paperNot a substantial claim - Findingnone given
All of the 42 inhalation video clips had sufficient technical quality for evaluation.
“All of these clips had sufficient technical quality for evaluation.”
Quote in the paperNot a substantial claim - Findingown data
The average time of the app onboarding process (excluding study-specific discussions) was approximately 15 minutes.
“the average time of the app onboarding process (excluding study-specific discussions) was approximately 15 minutes.”
Quote in the paperNot a substantial claim - Findingnone given
There was a clear difference in the assessment time of the inhalation video clips between the primary and secondary care settings.
“Furthermore, since there was a clear difference in the assessment time of the inhalation video clips between the primary and secondary care settings, a dedicated and specialized expert may be considered for this task.”
Quote in the paperNot a substantial claim - Findingown data
Qualitative feedback suggested several valued and important features, as well as challenges and potential improvements of the intervention.
“The qualitative feedback suggested several valued and important features, as well as challenges and potential improvements of the intervention.”
Quote in the paperNot a substantial claim - Findingown data
Participants indicated that the conversational agent had too many predefined answer options.
“Even though the text-based conversational agent was perceived as positive and engaging, participants indicated that the conversational agent had too many predefined answer options.”
Quote in the paperNot a substantial claim - Premisecitation
Patients require specialized cognitive and behavioral skills to deal with their condition.
“In addition, patients require specialized cognitive and behavioral skills to deal with their condition [4,5].”
Quote in the paperSubstantial claim0 of 2 sources checked - Premisecitation
Digital health interventions can educate and engage patients through a direct channel that supports communication with physicians and health care professionals.
“Digital health interventions are emerging tools for the management of chronic diseases, as they can educate and engage patients through a direct channel that supports communication with physicians and health care professionals [7,8]”
Quote in the paperSubstantial claim0 of 2 sources checked - Interpretationown data
Conversational agents designed as mediating social actors involving health care professionals, patients, and family members are accepted in such a 'team player' role.
“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”
Quote in the paperSubstantial claim- Rests on an assumption: Conversational agents can act as mediating social actors, taking over a significant amount of intervention delivery in a scalable manner and coordinating communication among health care professionals, family members, and patients if required.
- Interpretationown data
Conversational agents designed as mediating social actors show potential to improve health-relevant outcomes in chronic disease management.
“but also show potential to improve health-relevant outcomes in chronic disease management.”
Quote in the paperSubstantial claim- Rests on an assumption: Conversational agents can act as mediating social actors, taking over a significant amount of intervention delivery in a scalable manner and coordinating communication among health care professionals, family members, and patients if required.
- Premisecitation
Digital health interventions enable the scale up of personalized and behavioral interventions at low cost.
“and enable the scale up of personalized and behavioral interventions at low cost [1,9].”
Quote in the paperSubstantial claim0 of 2 sources checked - Interpretationnone given
The MAX conversational agent is the first (to the best of our knowledge) conversational agent that takes over the role of a scalable social actor framed as a scalable assistant of a health care professional that mediates communication among various relevant stakeholders in the context of chronic disease management.
“the current conversational agent is the first (to the best of our knowledge) that takes over the role of a scalable social actor framed as a scalable assistant of a health care professional that mediates communication among various relevant stakeholders in the context of chronic disease management.”
Quote in the paperSubstantial claim0 of 7 sources checked- cites [63] source
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- cites [96] source
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- Interpretationcitation
This is the first assessment of this type of mediating conversational agent outside of a lab setting, in a realistic longitudinal intervention field study in a complex sociotechnical system with various stakeholders.
“This is also the first assessment of this type of mediating conversational agent outside of a lab setting, as many other conversational agents have been assessed [96], but rather in a realistic longitudinal intervention field study in a complex sociotechnical system with various stakeholders.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [96] source
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- Premisecitation
There is evidence that shared decision making and collaboration among patients, parents, and health care professionals are key success factors in guided asthma self-management programs with improved adherence and health outcomes.
“Moreover, there is evidence that shared decision making and collaboration among patients, parents, and health care professionals are key success factors in guided asthma self-management programs with improved adherence and health outcomes [55].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [55] source
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- Interpretationown data
With the MAX conversational agent, the study was able to show how to extend the reach of health care professionals into the everyday lives of patients in an efficient way without compromising the quality of care and working alliance.
“With the MAX conversational agent, we were also able to show how to extend the reach of health care professionals into the everyday lives of patients in an efficient way without compromising the quality of care and working alliance.”
Quote in the paperSubstantial claim - Premisecitation
Young patients still face problems related to both cognitive and behavioral skills that hinder their ability to effectively administer asthma medications.
“However, young patients still face problems related to both cognitive and behavioral skills that hinder their ability to effectively administer asthma medications [30-35].”
Quote in the paperSubstantial claim0 of 6 sources checked - Interpretationown data
The MAX conversational agent was able to motivate family members to support the young patients most of the time when asked (97.8%).
“Moreover, the MAX conversational agent was able to motivate family members to support the young patients most of the time when asked (97.8%).”
Quote in the paperSubstantial claim - Premisecitation
Due to absent or insufficient motivation strategies such as interactivity, proper incentives and rewards, and experiential value, the effects of digital interventions in asthma are prone to be negatively affected by the temporal decline in patients' engagement and motivation.
“Additionally, due to absent or insufficient motivation strategies such as interactivity, proper incentives and rewards [48], and experiential value [49-51], the effects of the previously reported digital interventions in asthma, such as the health condition of the young patients, are prone to be negatively affected by the temporal decline in the patients’ engagement and motivation [10,52-54].”
Quote in the paperSubstantial claim0 of 8 sources checked- cites [48] source
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- Interpretationown data
In terms of human effort and responsiveness of health care professionals, it can be concluded that the MAX intervention is scalable since most of the conversational turns (99.5%) involved the patients and the MAX conversational agent.
“In terms of human effort and responsiveness of health care professionals, it can be concluded that the MAX intervention is scalable since most of the conversational turns (99.5%) involved the patients and the MAX conversational agent.”
Quote in the paperSubstantial claim - Interpretationown data
Conversational agents framed as digital assistants of health care professionals have the potential to improve cognitive and behavioral skills in chronic disease management, with asthma in children as one specific example.
“We have shown that conversational agents framed as digital assistants of health care professionals have the potential to improve cognitive and behavioral skills in chronic disease management, with asthma in children as one specific example.”
Quote in the paperSubstantial claim- Rests on an assumption: The observed improvements in cognitive and behavioral skills are attributable to the MAX intervention rather than other factors.
- Interpretationreasoning
A unique advantage of MAX is its use of a three-component intervention that involves health care professionals, the digital assistant MAX, and family members to support young patients as they work on specific tasks to expand asthma knowledge and improve behavioral skills.
“A unique advantage of MAX is its use of a three-component intervention that involves health care professionals, the digital assistant MAX, and family members to support young patients as they work on specific tasks to expand asthma knowledge and improve behavioral skills.”
Quote in the paperSubstantial claim - Premisecitation
At least 20 participants were required according to heuristics in usability engineering to identify a relevant amount of usability problems.
“to identify a relevant amount of usability problems, at least 20 participants were required according to heuristics in usability engineering [90].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [90] NielsenJLandauerTKModel of the finding of usability problems1993ACM Conference on Human Factors in Computing Systems (CHI)1993Netherlands206213
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- Premisecitation
The design of MAX was driven by an interdisciplinary effort that resulted in a conceptual model with intervention components informed by human behavior and experiential learning theories, findings from technology acceptance research, and prior experiences of the authors with conversational agents.
“The design of MAX was driven by an interdisciplinary effort that resulted in a conceptual model with intervention components informed by human behavior and experiential learning theories [61,65,66], findings from technology acceptance research [49,51,58,102], and prior experiences of the authors with conversational agents that support health care professionals and young adolescent patients [67,68]”
Quote in the paperNot a substantial claim0 of 9 sources checked- cites [61] source
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- cites [65] source
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- cites [66] Kolb, DA, 1984, Experience as the source of learning and development
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- cites [49] source
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- Interpretationcitation
By applying a scalable conversational agent for asthma specifically, the MAX intervention can provide greater health care professional interaction at reduced cost.
“By applying a scalable conversational agent for asthma specifically, the MAX intervention can provide greater health care professional interaction at reduced cost, which has been a key concern in past asthma interventions [113].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [113] source
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- Study design and conductown data
Only health care professionals from four hospitals and two cantonal patient organizations of the Swiss Lung Association participated in this study.
“Further, only health care professionals from four hospitals (eg, pediatric pneumologists) and two cantonal patient organizations of the Swiss Lung Association participated in this study.”
Quote in the paperSubstantial claim - Study design and conductown data
The inductive open coding of the interviews was performed by one author only, resulting in a certain bias of the qualitative results.
“Another limitation of this study pertains to the inductive open coding of the interviews that was performed by one author only (SH), resulting in a certain bias of the qualitative results.”
Quote in the paperNot a substantial claim - Premisecitation
A systematic review of 15 different digital interventions for pediatric asthma management showed that 87% of the interventions improved medication and behavioral adherence.
“A systematic review of 15 different digital interventions for pediatric asthma management showed that 87% of the interventions improved medication and behavioral adherence, and 53% demonstrated improved health outcomes [113].”
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- Premisecitation
These mobile health apps have not included scalable text-based health care conversational agents to support communication with health care professionals.
“Although these mobile health apps offer a range of features (eg, automated personalized texts, interactive websites, and online modules) to inform patients about asthma, they have not included scalable text-based health care conversational agents to support communication with health care professionals.”
Quote in the paperSubstantial claim0 of 4 sources checked - Interpretationreasoning
Since the social support assessment was self-reported by the young patients and linked to additional points for the MAX intervention, the supportive involvement of family members was overestimated.
“In addition, since the social support assessment was self-reported by the young patients and linked to additional points for the MAX intervention (to increase the chance to be among the winners), it can be assumed that the supportive involvement of family members was overestimated.”
Quote in the paperNot a substantial claim - Premisecitation
A systematic review of 15 different digital interventions for pediatric asthma management showed that 53% demonstrated improved health outcomes.
“A systematic review of 15 different digital interventions for pediatric asthma management showed that 87% of the interventions improved medication and behavioral adherence, and 53% demonstrated improved health outcomes [113].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [113] source
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- Interpretationown data
The MAX intervention is scalable.
“it can be concluded that the MAX intervention is scalable since most of the conversational turns (99.5%) involved the patients and the MAX conversational agent.”
Quote in the paperSubstantial claim - Premisecitation
Previous studies in other health domains have demonstrated promising results in using conversational agents to improve outcomes, such as promoting physical activity for childhood obesity.
“Previous studies in other health domains have demonstrated promising results in using conversational agents to improve outcomes, such as promoting physical activity for childhood obesity [104,114].”
Quote in the paperNot a substantial claim0 of 2 sources checked
- The quote only partly states this claim. 2
- Classified as probably not a substantial claim. 32
- May combine two claims. 29
The quote only partly states this claim.
Findingown dataMAX led to improved behavioral skills (inhalation technique) in patients.
“MAX led to improved cognitive and behavioral skills”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataIt took health care professionals 3 days to deliver related feedback to the patients.
“and 3 days to deliver related feedback to the patients”
Quote in the paperNot a substantial claimThe quote only partly states this claim.
Findingown dataMAX led to improved cognitive skills (knowledge about asthma) in patients.
“MAX led to improved cognitive and behavioral skills”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataParticipants who finished the intervention (n=37) did so on average within 3 weeks, which was within the incentivized duration of 4 weeks.
“Participants who finished the intervention (n=37) did so on average within 3 weeks, which was within the incentivized duration of 4 weeks.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataAll mean values of technology acceptance perceptions lie clearly above the neutral scale value of 4, indicating positive evaluations of the mobile app.
“All mean values lie clearly above the neutral scale value of 4, indicating positive evaluations of the mobile app.”
Quote in the paperNot a substantial claim- Rests on an assumption: The single-item measures used to assess technology acceptance are sufficient to validly measure the constructs.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown dataFor two video clips, three serious inhalation mistakes were identified, eliciting a feedback to resend a corrected video clip; after resubmission, no severe inhalation mistakes could be identified in the second video clip.
“For two video clips, three serious inhalation mistakes were identified, eliciting a feedback to resend a corrected video clip. After resubmission, no severe inhalation mistakes could be identified in the second video clip.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown data99.5% (15,078/15,152) of conversational turns took place between patients and the MAX conversational agent, and only 0.5% (74/15,152) occurred between patients and health care professionals.
“99.5% (15,078/15,152) took place between patients and the MAX conversational agent, and only 0.5% (74/15,152) occurred between patients and health care professionals (Table 1).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe intervention completion rate was 75.5%, as 37 out of the 49 patients finished the intervention.
“The intervention completion rate was 75.5%, as 37 out the 49 patients finished the intervention.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataPatients learned new aspects about asthma management and enjoyed the coaching sessions.
“Moreover, patients learned new aspects about asthma management and enjoyed the coaching sessions.”
Quote in the paperNot a substantial claim- Rests on an assumption: The single-item measures used to assess technology acceptance are sufficient to validly measure the constructs.
May combine two claims.
Findingown dataIt took health care professionals less than 4 minutes to assess the inhalation technique and 3 days to deliver that feedback to the patients.
“In addition, it took them less than 4 minutes to assess the inhalation technique and 3 days to deliver that feedback to the patients.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataOverall, 42 inhalation video clips were recorded and submitted to the health care professionals.
“Overall, 42 inhalation video clips were recorded and submitted to the health care professionals (Table 2).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIt took health care professionals an average of 221 seconds to assess the video clips, with a clear difference observed between health care settings (average of 410 seconds in the primary care setting and 127 seconds in the secondary care setting).
“it took health care professionals an average of 221 seconds to assess the videos clips, with a clear difference observed between health care settings (average of 410 seconds in the primary care setting and 127 seconds in the secondary care setting; see Table 2).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataFor the gender-specific choices of the MAX conversational agent, all participants chose the character corresponding to their own indicated gender.
“For the gender-specific choices of the MAX conversational agent, all participants chose the character corresponding to their own indicated gender.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataReach of the MAX intervention was 49.5%, with 49 out of 99 approached patients downloading the app and starting to interact with the MAX conversational agent.
“Reach was 49.5% with 49 out of 99 approached patients downloading the app and starting to interact with the MAX conversational agent.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingnone givenFor each patient, this intervention involved an average of 20 minutes of human effort, 10 automated SMS text messages, including three reminders, and additional costs for gift vouchers, including lottery winnings.
“For each patient, this intervention involved an average of 20 minutes of human effort, 10 automated SMS text messages, including three reminders, and additional costs for gift vouchers, including lottery winnings.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataThe text-based conversational agent was perceived as positive and engaging.
“the text-based conversational agent was perceived as positive and engaging”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationConversational agents have shown promising results with respect to therapeutic alliance.
“therapeutic alliance [16,17]”
Quote in the paperNot a substantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationChronic conditions present a significant risk to the global population and cause substantial financial and health-related burdens, resulting in low quality of life of those affected.
“Chronic conditions present a significant risk to the global population, and cause substantial financial and health-related burdens, resulting in low quality of life of those affected [1].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [1] source
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PremisecitationSuccessful disease management often requires a trustful collaboration among health care professionals, patients, and their families.
“Successful disease management often requires a trustful collaboration among health care professionals, patients, and their families [3].”
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PremisecitationSeveral recent studies have provided evidence supporting the patient benefits of digital interventions, particularly in children and adolescents.
“Indeed, several recent studies have provided evidence supporting the patient benefits of such digital interventions, particularly in children and adolescents [10-14].”
Quote in the paperNot a substantial claim0 of 5 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationConversational agents have shown promising results with respect to patient satisfaction.
“conversational agents (ie, computer programs that imitate interaction with human beings) have shown promising results with respect to patient satisfaction [15]”
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PremisecitationAsthma is associated with high financial and health costs, with total annual asthma costs in the United States estimated at US $56 billion in 2011.
“Asthma is associated with high financial and health costs, with total annual asthma costs in the United States estimated at US $56 billion in 2011 [23].”
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PremisecitationMobileCoach has already been used successfully for various clinical and public health interventions.
“The intervention was developed with the open-source software platform MobileCoach [67,83,84], which has already been used successfully for various clinical and public health interventions [17,68,77-79,85,86]”
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- cites [84] MobileCoach2021-02-06www.mobile-coach.eu
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- cites [86] source
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Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationAsthma affects approximately 235 million people and is one of the most common chronic diseases worldwide.
“Affecting approximately 235 million people, asthma is one of the most common chronic diseases worldwide [20].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [20] Asthma Fact SheetWorld Health Organization2020-04-13https://www.who.int/en/news-room/fact-sheets/detail/asthma
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationConversational agents have shown promising results with respect to treatment success.
“and treatment success [18].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [18] source
Not checked in the free run.
May combine two claims.
PremisecitationPoor technique during medication inhalation leads to reduced dispersion of the drug in the lungs, and subsequent decreased asthma stability and lowered clinical effectiveness of the delivered drug.
“Another common concern is poor technique during medication inhalation, leading to reduced dispersion of the drug in the lungs, and subsequent decreased asthma stability and lowered clinical effectiveness of the delivered drug [41-44].”
Quote in the paperSubstantial claim0 of 4 sources checkedMay combine two claims.
Interpretationown dataCompared to very similar conversational agent research targeting childhood obesity, physical inactivity, or the management of chronic pain, this intervention resulted in a high overall therapeutic goal achievement rate (75.5%) but also in improved asthma knowledge test scores and behavioral skills.
“Compared to very similar conversational agent research targeting childhood obesity [68], physical inactivity [77], or the management of chronic pain [17], this intervention resulted in a high overall therapeutic goal achievement rate (75.5%) but also in improved asthma knowledge test scores and behavioral skills (ie, no identified inhalation mistakes occurred after the feedback from health care”
Quote in the paperSubstantial claim0 of 3 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationDigital health interventions in the form of mobile apps can be particularly effective for children as they provide an attractive channel for education and management through the possible integration of multimedia content such as audio or video.
“Digital health interventions in the form of mobile apps can be particularly effective for children as they provide an attractive channel for education and management through the possible integration of multimedia content such as audio or video [19].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [19] source
Not checked in the free run.
May combine two claims.
Interpretationown dataThe results of this first feasibility study indicate an overall positive evaluation with respect to the reach of the intervention, the strong working alliance between patients and the MAX conversational agent, and high acceptance of the intervention by all relevant stakeholders.
“The results of this first feasibility study indicate an overall positive evaluation with respect to the reach of the intervention (ie, 49.5% of 99 young patients approached did install the app and started to interact with the MAX conversational agent), the strong working alliance between patients and the MAX conversational agent, and high acceptance of the intervention by all relevant stakeholders”
Quote in the paperSubstantial claim- Rests on an assumption: The single-item measures used to assess technology acceptance are sufficient to validly measure the constructs.
Classified as probably not a substantial claim.
Study design and conductcitationKnowledge about asthma was assessed by a validated health literacy quiz for children with asthma, with a quiz score ranging from 0 to 11.
“Knowledge about asthma (ie, cognitive skill) was assessed at the beginning of the intervention (ie, at the end of the introductory chat with the conversational agent MAX) and in the last session by a validated health literacy quiz for children with asthma, with a quiz score ranging from 0 (no knowledge) to 11 (good knowledge) [80,94] (see Multimedia Appendix 19).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [80] SchnyderMASantschiRAuf Spurensuche im FerienlagerEin Lerncomic über Asthma20122020-04-13https://www.lungenliga.ch/uploads/tx_pubshop/Lerncomic_Spurensuche.pdf
Not checked in the free run.
- cites [94] Schnyder, M, 2014, Begleitbericht Zur Entwicklung eines Lernmittels für Asthmakinder im Alter von 7 bis 12 Jahren
Not checked in the free run.
Probably not a substantial claim: may not pass S1 (asserted), S3 (load-bearing). May combine two claims.
PremisecitationConversational agents can be influential and engaging for young patients.
“It was previously suggested that conversational agents can be influential and engaging for young patients, and that open-text answers are highly appreciated [104].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [104] source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitationAcceptance of the intervention was assessed with instruments adapted from information systems research.
“perceived usefulness (“The app helped me to increase my knowledge about my asthma”), ease of use (“The app was easy to use”), enjoyment (“I found the app enjoyable”), control (“I could control many aspects of the app”), and usage intention (“How much would you like to continue working with MAX?”) were assessed by patients at the end of the intervention with instruments adapted from information”
Quote in the paperNot a substantial claim0 of 2 sources checkedMay combine two claims.
Study design and conductcitationThe study minimized the risk for smartphone addiction by limiting the amount of possible sessions to one per day and further including active exercises outside the digital environment of the app to increase social interaction and to counteract increasing smartphone usage among children.
“We minimized the risk for smartphone addiction [76] by limiting the amount of possible sessions to one per day and further including active exercises outside the digital environment of the app to increase social interaction and to counteract increasing smartphone usage among children [103].”
Quote in the paperNot a substantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenThe study was approved by the institutional review board of ETH Zurich (reference number: EK 2018-N-59).
“The study was approved by the institutional review board of ETH Zurich (reference number: EK 2018-N-59).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationDigital health interventions for asthma include numerous mobile health apps that provide patients with information and help them track symptoms or medications, often using a gamification component.
“Digital health interventions for asthma include numerous mobile health apps that provide patients with information and help them track symptoms or medications, often using a gamification component [45-47].”
Quote in the paperNot a substantial claim0 of 3 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
Interpretationnone givenGeneral ongoing costs include keeping the intervention content updated according to recent asthma management guidelines at a cost of approximately US $10,000 every 3 years.
“General ongoing costs include keeping the intervention content updated according to recent asthma management guidelines (at a cost of approximately US $10,000 every 3 years) and maintaining technical software (at a cost of approximately US $10,000 per year).”
Quote in the paperNot a substantial claim- Rests on an assumption: The MAX project team's cost estimates are accurate.
May combine two claims.
Study design and conductreasoningThe study was exploratory by nature and did not include a detailed power analysis to determine a particular sample size.
“Therefore, the study was exploratory by nature and did not include a detailed power analysis to determine a particular sample size.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationPrivacy issues with conversational agents and open-text answers were pointed out by prior work.
“However, privacy issues with conversational agents and open-text answers were pointed out by prior work [105], as conversational agents that are responsive to such inputs could potentially and unintentionally retrieve more and more personal information.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [105] source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationOpen-text answers are highly appreciated.
“It was previously suggested that conversational agents can be influential and engaging for young patients, and that open-text answers are highly appreciated [104].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [104] source
Not checked in the free run.
May combine two claims.
InterpretationreasoningSome data had to be stored in a redundant way in the MAX system, which likely resulted in an overestimation of efforts.
“Specifically, some data had to be stored in a redundant way (eg, contact number, patient name) in the MAX system, which likely resulted in an overestimation of efforts (eg, the duration of the onboarding process).”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningBased on the limited sample, the results are not representative and must be interpreted with caution.
“Based on our limited sample, it is clear that the results are not representative and must be interpreted with caution.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
InterpretationreasoningIt is not clear whether and to what degree the MAX intervention would work the same way with other relevant health care professionals such as a general practitioner.
“Therefore, it is not clear whether and to what degree the MAX intervention would work the same way with other relevant health care professionals such as a general practitioner.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Interpretationnone givenEstimates of the MAX project team indicate that the development of the current MAX intervention into a "product" would cost another US $100,000.
“In case none of these additional intervention components or studies is considered, estimates of the MAX project team indicate that the development of the current MAX intervention into a “product” would cost another US $100,000.”
Quote in the paperNot a substantial claim- Rests on an assumption: The MAX project team's cost estimates are accurate.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationNocturnal cough in adult asthma patients can be detected reliably with the microphone of a smartphone.
“For example, there is evidence that the number of nocturnal cough events is negatively correlated with asthma control [106,107], and that nocturnal cough in adult asthma patients can be detected reliably with the microphone of a smartphone [89,108].”
Quote in the paperNot a substantial claim0 of 2 sources checkedMay combine two claims.
Interpretationown dataConversational agents can take over the role of a mediating social actor in a complex health care setting with various stakeholders, and deliver a digital health intervention in a scalable way into the everyday life of patients and their family members.
“We have demonstrated that conversational agents can take over the role of a mediating social actor in a complex health care setting with various stakeholders, and deliver a digital health intervention in a scalable way into the everyday life of patients and their family members.”
Quote in the paperSubstantial claim- Rests on an assumption: The MAX intervention can be delivered in a scalable way into the everyday life of patients and their family members.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataWe have only reported the costs and efforts related to the MAX intervention, and therefore no implications regarding cost-effectiveness can be discussed.
“Finally, we have only reported the costs and efforts related to the MAX intervention, and therefore no implications regarding cost-effectiveness can be discussed.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitationWorking alliance between the patient and the conversational agent MAX was assessed with a German-adapted version of the Session Alliance Inventory after coaching sessions 2, 8, and 14.
“Working alliance between the patient and the conversational agent MAX was assessed with a German-adapted version of the Session Alliance Inventory [92] after coaching sessions 2, 8, and 14 (eg, “MAX and I respect each other” with answers anchored on a 7-point Likert scale ranging from 1 [“never”] to 8 [“always”]; see Multimedia Appendix 18).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [92] source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenThe inhalation technique of each patient was systematically assessed by the patient's responsible health care professional with the help of predefined evaluation criteria developed by health care professionals of the Swiss Lung Association and the participating pediatric pneumologists.
“The inhalation technique of each patient (ie, behavioral skill) was systematically assessed by the patient’s responsible health care professional with the help of predefined evaluation criteria These criteria were developed by health care professionals of the Swiss Lung Association and the participating pediatric pneumologists.”
Quote in the paperNot a substantial claim- Rests on an assumption: The predefined evaluation criteria used by health care professionals validly assess inhalation technique.
- Rests on an assumption: The health care professionals' assessments of inhalation technique are reliable.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThere is evidence that the number of nocturnal cough events is negatively correlated with asthma control.
“For example, there is evidence that the number of nocturnal cough events is negatively correlated with asthma control [106,107], and that nocturnal cough in adult asthma patients can be detected reliably with the microphone of a smartphone [89,108].”
Quote in the paperNot a substantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationConversational agents that are responsive to open-text inputs could potentially and unintentionally retrieve more and more personal information.
“However, privacy issues with conversational agents and open-text answers were pointed out by prior work [105], as conversational agents that are responsive to such inputs could potentially and unintentionally retrieve more and more personal information.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [105] source
Not checked in the free run.
May combine two claims.
Interpretationown dataThe MAX intervention extended the reach of health care professionals into the everyday lives of patients in an efficient way without compromising the quality of care and working alliance.
“With the MAX conversational agent, we were also able to show how to extend the reach of health care professionals into the everyday lives of patients in an efficient way without compromising the quality of care and working alliance.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningThe MAX conversational agent uses several communication channels (eg, in-app chat, email, and SMS), and therefore "lives" not only on a smartphone in the pocket of a patient but is rather omnipresent.
“For this purpose, the MAX conversational agent uses several communication channels (eg, in-app chat, email, and SMS), and therefore “lives” not only on a smartphone in the pocket of a patient but is rather omnipresent (ie, MAX appears on the phones of family members, such as via SMS, or on desktop or tablet computers of health care professionals, such as via emails and the web-based MAX interface”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Interpretationnone givenMaintaining technical software costs approximately US $10,000 per year.
“General ongoing costs include keeping the intervention content updated according to recent asthma management guidelines (at a cost of approximately US $10,000 every 3 years) and maintaining technical software (at a cost of approximately US $10,000 per year).”
Quote in the paperNot a substantial claim- Rests on an assumption: The MAX project team's cost estimates are accurate.
May combine two claims.
Study design and conductnone givenThis study was designed as a feasibility study with a limited number of participants.
“This study was designed as a feasibility study with a limited number of participants.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.
InterpretationreasoningNonspecialized health care experts may require significantly more time for the assessment of the inhalation video clips or would not have the expertise to do so without additional educational efforts.
“These nonspecialized health care experts may require significantly more time for the assessment of the inhalation video clips or would not have the expertise to do so without additional educational efforts.”
Quote in the paperNot a substantial claim
The paper relies on this without support.
Children often face problems with technological solutions when they are not integrated into existing health care systems and do not allow for explicit support by health care professionals or family members.
“However, and in addition to shortcomings of asthma management related to cognitive and behavioral skills, children often face problems with such technological solutions when they are not integrated into existing health care systems and do not allow for explicit support by health care professionals or family members.”
The paper relies on this without support.
Without a dedicated party or mediator, it often becomes a challenge to integrate all relevant stakeholders (health care professionals, family members, and patients) into the disease management process.
“Without a dedicated party or mediator, it often becomes a challenge to integrate all of these relevant stakeholders (ie, health care professionals, family members, and the patients themselves) into the disease management process.”
The paper relies on this without support.
Conversational agents can act as mediating social actors, taking over a significant amount of intervention delivery in a scalable manner and coordinating communication among health care professionals, family members, and patients if required.
“Conversational agents, as part of such interventions, can act as mediating social actors; that is, they take over not only a significant amount of the intervention delivery in a scalable manner but also coordinate the communication among health care professionals, family members, and patients if required.”
The authors state this as an assumption.
The four distinct intervention components enabled an experiential learning cycle and were assumed to influence the outcomes of the intervention.
“Four distinct intervention components as depicted in Figure 1 enabled an experiential learning cycle [66], and were assumed to influence the outcomes of the intervention”
The authors state this as an assumption.
The need to self-regulate one’s experiences and actions (as an important predictor of engagement) is also true for digital interventions.
“Assuming that the need to self-regulate one’s experiences and actions (as an important predictor of engagement [70], as posited by self-determination theory) is also true for digital interventions”
The authors state this as an assumption.
There is a positive/negative reinforcement link that connects the outcomes of the conceptual model with the perceived characteristics of the app and working alliance with the conversational agent.
“Finally, we assume that there is a positive/negative reinforcement link that connects the outcomes of the conceptual model with the perceived characteristics of the app and working alliance with the conversational agent.”
The paper relies on this without support.
Specific cognitive skills required for asthma management include knowledge about asthma triggers and the importance of medication inhalation adherence, as well as behavioral skills such as the application of correct inhalation techniques.
“For asthma, specific cognitive skills required for disease management include knowledge about asthma triggers and the importance of medication inhalation adherence, as well as behavioral skills such as the application of correct inhalation techniques.”
The paper relies on this without support.
The predefined evaluation criteria used by health care professionals validly assess inhalation technique.
“These criteria were developed by health care professionals of the Swiss Lung Association and the participating pediatric pneumologists.”
The paper relies on this without support.
The health care professionals' assessments of inhalation technique are reliable.
“The inhalation technique of each patient (ie, behavioral skill) was systematically assessed by the patient’s responsible health care professional with the help of predefined evaluation criteria”
The paper relies on this without support.
The single-item measures used to assess technology acceptance are sufficient to validly measure the constructs.
“Single-item measures were used to reduce the burden of the intervention and answers were anchored on 7-point Likert scales ranging from “strongly disagree” (1) to “strongly agree” (7).”
The paper relies on this without support.
The observed improvements in cognitive and behavioral skills are attributable to the MAX intervention rather than other factors.
“We have shown that conversational agents framed as digital assistants of health care professionals have the potential to improve cognitive and behavioral skills in chronic disease management, with asthma in children as one specific example.”
The paper relies on this without support.
The MAX intervention can be delivered in a scalable way into the everyday life of patients and their family members.
“We have demonstrated that conversational agents can take over the role of a mediating social actor in a complex health care setting with various stakeholders, and deliver a digital health intervention in a scalable way into the everyday life of patients and their family members.”
The paper relies on this without support.
The MAX project team's cost estimates are accurate.
“In case none of these additional intervention components or studies is considered, estimates of the MAX project team indicate that the development of the current MAX intervention into a “product” would cost another US $100,000.”
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?
Relational agents offer a compelling interface for delivering JITAIs.
“relational agents—software that is designed to emulate conversations through voice or SMS text messages, also known as chatbots or digital coaches [31]—offer a compelling interface for delivering JITAIs.”
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.
The same participant count is assigned two different percentages
MinorTable 1 labels 12 nonfinishers as 25% in one row and 24% in another, although both rows use the same total of 49 participants.
“| | Participants not finishing the intervention | 12 (25) | 129.58 (59.86) |”
“| | Participants not finishing the intervention | 12 (24) | 20.75 (15.88) |”
Working-alliance response scale has conflicting endpoints
MinorA scale with integer responses from 1 through 8 has eight points, not seven.
“a 7-point Likert scale”
“ranging from 1 [“never”] to 8 [“always”]”
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Investigating conversational agents in healthcare: Application of a technical-oriented taxonomy
Denecke, K., & May, R. (2023) · Procedia Computer Science · doi:10.1016/j.procs.2023.01.413 · Cited by 12 · see citing works
Vinay, R., Уэтова, Е., Tommila, N. C., Biller‐Andorno, N., & Kowatsch, T. (2025) · JMIR Aging · doi:10.2196/76489 · Cited by 11 · see citing works
Self-citationUse of Telemedicine in Pediatric Services for 4 Representative Clinical Conditions: Scoping Review
Southgate, G., Yassaee, A., Harmer, M., Livesey, H. F., Pryde, K., & Roland, D. (2022) · Journal of Medical Internet Research · doi:10.2196/38267 · Cited by 11 · see citing works
Skvortsova, A., Rodrigues, T. C., de Buisonjé, D. R., Kowatsch, T., Santhanam, P., Veldhuijzen, D. S., van Middendorp, H., & Evers, A. W. M. (2021) · Journal of Medical Internet Research · doi:10.2196/32130 · Cited by 11 · see citing works
Self-citationConversational 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 · see citing works
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Iio, M., Sato, M., Narita, M., Yamamoto‐Hanada, K., Oishi, T., Kishino, A., Kawaguchi, T., Nishi, R., Nagata, M., & Ohya, Y. (2022) · JMIR Formative Research · doi:10.2196/34509 · Cited by 8 · see citing works
Castro, Ó., Salamanca-Sanabria, A., Alattas, A., Teepe, G. W., Leidenberger, K., Fleisch, E., Car, L. T., Müller‐Riemenschneider, F., & Kowatsch, T. (2024) · Archives of Public Health · doi:10.1186/s13690-024-01424-z · Cited by 10 · see citing works
Self-citationReceptivity to mobile health interventions
Keller, R., von Wangenheim, F., Mair, J. L., & Kowatsch, T. (2022) · Elsevier eBooks · doi:10.1016/b978-0-323-90045-4.00006-x · Cited by 8 · see citing works
Self-citationCalvo, R. A., Peters, D., Moradbakhti, L., Cook, D., Rizos, G., Schuller, B. W., Kallis, C., Wong, E., & Quint, J. K. (2023) · JMIR Research Protocols · doi:10.2196/42965 · Cited by 8 · see citing works
Productivity of incident management with conversational bots-a review
Iparraguirre-Villanueva, O., Obregon-Palomino, L., Pujay-Iglesias, W., Sierra-Liñan, F., & Cabanillas-Carbonell, M. (2023) · IAES International Journal of Artificial Intelligence · doi:10.11591/ijai.v12.i4.pp1543-1556 · Cited by 9 · see citing works
A text-based conversational agent for asthma support: Mixed-methods feasibility study
Cook, D., Peters, D., Moradbakhti, L., Su, T., Re, M. D., Schuller, B. W., Quint, J. K., Wong, E., & Calvo, R. A. (2024) · Digital Health · doi:10.1177/20552076241258276 · Cited by 8 · see citing works
Pedagogical agents in K-12 education: a scoping review
Zhang, S., Jaldi, C. D., Schroeder, N. L., & Gladstone, J. R. (2024) · Journal of Research on Technology in Education · doi:10.1080/15391523.2024.2381229 · Cited by 6 · see citing works
Devittori, G., Akeddar, M., Retevoi, A., Schneider, F., Cvetkova, V., Dinacci, D., Califfi, A., Rossi, P., Petrillo, C., Kowatsch, T., et al. (2024) · IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob) · doi:10.1109/biorob60516.2024.10719881 · Cited by 5 · see citing works
Self-citationMair, J. L., Jabir, A. I., Salamanca-Sanabria, A., Castro, Ó., Zheng, S., Keller, R., Frese, B. F., Lim, C. S., Alattas, A., Negi, S., et al. (2025) · Scientific Reports · doi:10.1038/s41598-025-30960-z · Cited by 5 · see citing works
Self-citationVinay, R., Tommila, N. C., Schlögl, M., Klöppel, S., Biller‐Andorno, N., & Kowatsch, T. (2024) · Mensch und Computer (MuC) · doi:10.1145/3670653.3677521 · Cited by 5 · see citing works
Self-citationThe Development of Virtual Worlds as a Tool for Providing Virtual Grocery Store Tours
Lanningham‐Foster, L., Wolff, M. M., Woodall, S., & Hollis, J. (2022) · Dietetics · doi:10.3390/dietetics1020007 · Cited by 5 · see citing works
Brill, E., Vinay, R., Nißen, M., Joshi, P., Klöppel, S., & Kowatsch, T. (2025) · JMIR Formative Research · doi:10.2196/66885 · Cited by 5 · see citing works
Self-citationGenerative AI for Elderly Well-being through the Computer as Social Actor Paradigm
Pramod, D., & Patil, K. P. (2024) · International Conference on Contemporary Computing · doi:10.1145/3675888.3676033 · Cited by 4 · see citing works
Fallah, M., Bickmore, T., Ólafsson, S., Paasche‐Orlow, M. K., Mrkva, A., & Magnani, J. W. (2024) · ACM International Conference on Intelligent Virtual Agents (IVA) · doi:10.1145/3652988.3673955 · Cited by 4 · see citing works
HEALTHI: Workshop on Intelligent Healthy Interfaces
Hänsel, K., Sobolev, M., Kowatsch, T., & Calvo, R. A. (2022) · ACM International Conference on Intelligent User Interfaces (IUI) · doi:10.1145/3490100.3511169 · Cited by 4 · see citing works
Self-citationPsico Bot: a robot for psychological assessment of children and adolescents
de Lima, E. D. S., Scortegagna, S. A., & Marchi, A. C. B. D. (2024) · Ciencias Psicológicas · doi:10.22235/cp.v18i2.3428 · Cited by 4 · see citing works
Lee, D. J., Agarwal, A. K., Ali, Z. S., Xiong, R. A., Spencer, E. A., Hemmons, J. E., Lacko, H., & Delgado, M. K. (2022) · Urology · doi:10.1016/j.urology.2022.07.059 · Cited by 4 · see citing works
A Survey on Conversational Search and Applications in Biomedicine
Adatrao, N. S. K., Gadireddy, G. R., & Noh, J. (2023) · ACM Southeast Regional Conference (ACMSE) · doi:10.1145/3564746.3587001 · Cited by 4 · see citing works
Teepe, G. W., Lukic, Y. X., Kleim, B., Jacobson, N. C., Schneider, F., Santhanam, P., Fleisch, E., & Kowatsch, T. (2023) · BMC Psychology · doi:10.1186/s40359-023-01215-1 · Cited by 7 · see citing works
Self-citationRodrigues, 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 · see citing works
Self-citationBarth, J., Schläpfer, S., Schneider, F., Santhanam, P., Kowatsch, T., Heinz, P., Held, U., Eicher, M., & Witt, C. M. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-01688-x · Cited by 4 · see citing works
Self-citationScoping review: multiple stakeholders and child asthma management interventions
Adabla, S., Nabors, L., Sanyaolu, O., Olaniyan, A. C., & Bernstein, J. A. (2023) · Journal of Asthma · doi:10.1080/02770903.2023.2176775 · Cited by 3 · see citing works
Towards a Design Framework for Conversational Agents for Diabetes Prevention
Sawad, A. B., Alakhtar, R. A., Alturki, B., Narayan, B., Lin, S., Prasad, M., & Kocaballi, A. B. (2023) · Australian Conference on Computer-Human Interaction (OzCHI) · doi:10.1145/3638380.3638421 · Cited by 3 · see citing works
A Systematic Literature Review on How Conversational Agents are Transforming Healthcare
Antulay, N., & Adebesin, F. (2024) · Communications in computer and information science · doi:10.1007/978-3-031-71412-2_2 · Cited by 3 · see citing works
Khan, F., Wu, Y., Dray, J., Hemsley, B., & Kocaballi, A. B. (2025) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3706599.3719800 · Cited by 3 · see citing works
(Social) Trouble on the Road: Understanding and Addressing Social Discomfort in Shared Car Trips
Bremers, A. W. D., Friedman, N., Lee, S., Wu, T., Laurier, É., Jung, M. F., Ortiz, J., & Ju, W. G. (2024) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3640794.3665580 · Cited by 3 · see citing works
Digital Therapeutics for Healthy Longevity: A Roadmap
Leistner, T., & Kowatsch, T. (2023) · International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC) · doi:10.5220/0011778500003414 · Cited by 2 · see citing works
Self-citationSchläpfer, S., Barth, J., Heinz, P., Held, U., Kowatsch, T., & Witt, C. M. (2026) · Internet Interventions · doi:10.1016/j.invent.2026.100929 · Cited by 2 · see citing works
Self-citationEmpowering mental health professionals in asynchronous online psychotherapy with GenAI
Bucher, A. M., Vashkite, I., Staehelin, D., Dolata, M., & Schwabe, G. (2026) · International Journal of Mental Health Systems · doi:10.1186/s13033-026-00700-5 · Cited by 2 · see citing works
Han, G. I., Lee, H. J., & Son, Y.-J. (2026) · Digital Health · doi:10.1177/20552076261450385 · Cited by 2 · see citing works
Reengineering eADVICE for Long Waitlists: A Tale of Two Systems and Conditions
Richards, D., Caldwell, P. H. Y., Abdulrahman, A., Huben, A. V., Waters, K. A., & Scott, K. M. (2024) · Electronics · doi:10.3390/electronics13142785 · Cited by 2 · see citing works
Integrating Waiting into the Experience: A Study on Visual Feedback Design for AI Doctor Agents
Chen, C., & He, J.-W. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2527847 · Cited by 2 · see citing works
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 · see citing works
Self-citationConversational Agents for Managing Chronic Diseases: A Systematic Review
Zakerabasali, S., Amiri, P., & Alipour, J. (2025) · Health Scope · doi:10.5812/healthscope-163131 · Cited by 1 · see citing works
Features of mobile health applications (mHealth apps) for asthma
Nikolov, P., & Petrova, G. (2026) · Pharmacia · doi:10.3897/pharmacia.73.e180488 · Cited by 1 · see citing works
Lucchini, A., Bozzon, A., & Colombo, S. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3790698 · Cited by 1 · see citing works
Vankit, S. A., Shama, N. S., Kadam, J., Motti, V., Laviola, J., Duchowski, A. T., & Volonte, M. (2026) · Computer Animation and Virtual Worlds · doi:10.1002/cav.70140 · Cited by 1 · see citing works
Cheng, S. C., Kopelovich, S. L., Si, D., Divina, M., Gao, N. S., Wang, M. Y., Kim, J. J., Li, Z., Blank, J. M., Brian, R., et al. (2024) · Journal of Technology in Behavioral Science · doi:10.1007/s41347-023-00378-3 · Cited by 2 · see citing works
Smriti, D., Kao, T. A., Rathod, R., Shin, J. Y., Peng, W., Williams, J. R., Mujib, M. I., Colosimo, M. M., & Huh, J. (2022) · doi:10.2196/preprints.38908
de Buisonjé, D. R., Reijnders, T., Rodrigues, T. C., Santhanam, P., Kowatsch, T., Lipman, S. A., Bijmolt, T. H. A., Breeman, L. D., Janssen, V. R., Kraaijenhagen, R. A., et al. (2022) · doi:10.2196/preprints.38339
Self-citationMartinengo, L., Jabir, A. I., Goh, W. W. T., Lo, N. Y. W., Ho, M. R., Kowatsch, T., Atun, R. A., Michie, S., & Car, L. T. (2022) · doi:10.2196/preprints.39243
Self-citationMair, J. L., Castro, Ó., Salamanca-Sanabria, A., Frese, B. F., von Wangenheim, F., Tai, E. S., Kowatsch, T., & Müller‐Riemenschneider, F. (2022) · Research Square · doi:10.21203/rs.3.rs-2068852/v1
Self-citationOllier, J., Mishra, R., Mair, J. L., Salamanca-Sanabria, A., Fleisch, E., von Wangenheim, F., & Kowatsch, T. (2022) · doi:10.2196/preprints.41296
Self-citationOllier, J., Suryapalli, P., Fleisch, E., von Wangenheim, F., Mair, J. L., Salamanca-Sanabria, A., & Kowatsch, T. (2022) · doi:10.2196/preprints.41300
Self-citationRodrigues, 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
Self-citationSato, T., Sano, T., Kumakawa, E., Fujimura, K., & Yamashita, N. (2025) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3706599.3720143
CHATBOT APLICADO EM CRIANÇAS VÍTIMAS DE VIOLÊNCIA SEXUAL: Estudo piloto
de Lima, E. D. S., Scortegagna, S. A., & Marchi, A. C. B. D. (2025) · Psicologia e Saúde em Debate · doi:10.22289/2446-922x.v11a2a14
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Self-citationMair, J. L., Castro, Ó., Salamanca-Sanabria, A., Frese, B. F., von Wangenheim, F., Tai, E. S., Kowatsch, T., & Müller‐Riemenschneider, F. (2023) · Figshare · doi:10.6084/m9.figshare.22688895
Self-citationMair, J. L., Castro, Ó., Salamanca-Sanabria, A., Frese, B. F., von Wangenheim, F., Tai, E. S., Kowatsch, T., & Müller‐Riemenschneider, F. (2023) · Figshare · doi:10.6084/m9.figshare.22688901
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Self-citationDhinagaran, D. A., Martinengo, L., Ho, M.-H. R., Joty, S., Kowatsch, T., Atun, R. A., & Car, L. T. (2022) · doi:10.2196/preprints.38740
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Self-citationMoradbakhti, L., Peters, D., Quint, J. K., Schuller, B., Cook, D., & Calvo, R. A. (2026) · JMIR Human Factors · doi:10.2196/80979
Shenoi, A., Li, T., Jabir, A. I., Pitkethly, A. J., Fleisch, E., Kowatsch, T., & Mair, J. L. (2026) · JMIR Formative Research · doi:10.2196/94036
Self-citationUse and Efficacy of Conversational AI in Health Management: An Integrative Review
Wang, Z., & Kamarudin, S. (2026) · Journal of Health Communication · doi:10.1080/10810730.2026.2682496
ElshikhIdris, M. A. M., Ali, A. S. H., Mahmoud, S. Y., Aziz, Y. M. S., Ali, I., Farah, S., & Altayeb, W. F. M. (2026) · Cureus · doi:10.7759/cureus.111334 · Cited by 1 · see citing works
Boateng, G., Santhanam, P., Fleisch, E., Lüscher, J., Pauly, T., Scholz, U., Bodenmann, G., & Kowatsch, T. (2026) · ACM Transactions on Computing for Healthcare · doi:10.1145/3833380
Self-citation
- Authors
- Kowatsch, T., Schachner, T., Harperink, S., Barata, F., Dittler, U., Xiao, G., Stanger, C., v Wangenheim, F., Fleisch, E., Oswald, H., & Möller, A.
- Affiliations
- University of St.Gallen (CH)
- ETH Zurich (CH)
- Furtwangen University (DE)
- Johns Hopkins University (US)
- Dartmouth College (US)
- Kantonsspital Winterthur (CH)
- Corresponding author
- Kowatsch, Tobias
- ORCID
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2021-02-17
- Volume
- 23
- Issue
- 2
- Pages
- e25060
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC7929753
- OpenAlex
- W3122673691
- Semantic Scholar
- 85bb70a2f7f6a60e2b1aba483a3e298c4e2f1dd1
- Cited by
- 103
- References
- 102
- Citations by year
- 2026: 15 · 2025: 11 · 2024: 23 · 2023: 20 · 2022: 29 · 2021: 5
- FWCI
- 21.63
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Zurich Open Repository and Archive (University of Zurich) (acceptedVersion, cc-by)
- Repository of Futwangen University of Applied Sciences (Furtwangen University) (submittedVersion, cc-by)
- Repository for Publications and Research Data (ETH Zurich) (submittedVersion, cc-by)
- Alexandria (UniSG) (University of St.Gallen) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion, cc-by)
- ETH Zürich Research Collection (cc-by)
- Zurich Open Repository and Archive (University of Zurich)
- Funders
- National Institute on Drug Abuse (P30DA029926)
- National Institute of Diabetes and Digestive and Kidney Diseases (R01DK124428)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Keywords
- chatbots, chronic disease management, childhood asthma, asthma self-management, therapeutic relationship, healthcare workers, inhaler technique, text messaging, intervention acceptance, feasibility, primary and secondary care, patient-centered design, family involvement in care, patient knowledge and skills
- MeSH terms
- Chronic Disease, Communication, Family, Feasibility Studies, Female, Health Personnel, Humans, Male, Patients
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.
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