Theresa Schachner

Last Name

Schachner

First Name

Theresa

ORCID

0000-0002-5505-8811

Organisational unit

01359 - Lehre Management, Technologie u. Ök.

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Publications 1 - 8 of 8

Leveraging Influencers to Reach and Engage Vulnerable Individuals With a Digital Health Intervention: Quasi-Experimental Field Study
Nißen, Marcia; Harperink, Samira; Joshi, Priyam; et al. (2025)
Journal of Medical Internet Research
Background: Noncommunicable diseases are the leading cause of death, present economic challenges to health care systems worldwide, and disproportionally affect vulnerable individuals with low socioeconomic status (SES). While digital health interventions (DHIs) offer scalable and cost-effective solutions to promote health literacy and encourage behavior change, key challenges concern how to effectively reach and engage vulnerable individuals. To this end, social media influencers provide a unique opportunity to reach millions, and lasting engagement can be ensured through the design of DHIs in a manner that specifically appeals to low-SES individuals through alignment with their social background. Objective: The objectives of this study were 2-fold: to assess the effectiveness of leveraging influencers to reach vulnerable individuals (as measured via app downloads per stream viewers) and evaluate how the design of a DHI can improve engagement among this group (as measured via completion of the intervention). Methods: This study used a cross-sectional, quasi-experimental field design to assess both (1) the effectiveness of influencers in reaching vulnerable individuals and (2) the impact of specific design elements—such as gamification and storytelling—on user engagement using a stress management DHI featuring a slow-paced breathing exercise. In total, 3 differently designed versions of this DHI were developed following a fractional factorial design (StressLess, Breeze, and TragicKingdom). Reach was calculated as the number of downloads per viewers per stream and influencer. Engagement with the DHI was measured via number of conversational turns and milestone and intervention completion rates. Participants’ SES and technology acceptance were evaluated through a postintervention survey. Descriptive statistics, chi-square tests, and ANOVAs were used to examine the effects of the DHI design on reach and engagement metrics. Results: The recruitment via 8 influencers (total streams=25; total viewers=12,667) generated 220 downloads. The average reach ratio across streams amounted to 16.2% (SD 15.5%), with significant differences between conditions (ꭓ22=8.0, P=.02; StressLess: 8.1%, SD 9.3%; Breeze: 14%, SD 10.5%; TragicKingdom: 28.4%, SD 17.6%). The intervention completion rate across all DHI versions amounted to 7.7% (17/220), with no significant differences between conditions (P=.48). Conclusions: This work provides the first evidence that recruitment via influencers yields high reach ratios, moving far beyond the reach of traditional social media platforms. Nonetheless, based on the data collected, the ability to leverage such platforms to recruit vulnerable individuals remains unclear. In addition, while engagement with the promoted interventions was initially high, the completion rate of the full breathing exercise was comparably low, indicating that the influencer promotion strategy cannot fully overcome the well-documented adherence barriers in digital health.
Leveraging Influencers to Reach and Engage Vulnerable Individuals: A Quasi-Experimental Field Study with a Digital Health Intervention (Preprint)
Nißen, Marcia; Harperink, Samira; Joshi, Priyam; et al. (2025)
JMIR Preprints
Background: Non-communicable diseases (NCDs) are the leading cause of death, present economic challenges to healthcare systems worldwide, and disproportionally affect vulnerable individuals of low socioeconomic status (SES). While digital health interventions (DHIs) offer scalable and cost-effective solutions to promote health literacy and encourage behavior change, key challenges concern how to effectively (a) REACH and (b) ENGAGE vulnerable individuals. To this end, (a) social media influencers provide a unique opportunity to reach millions; and (b), ensure lasting engagement by designing DHIs in a manner that specifically appeals to low SES individuals through alignment with their social background. Objective: The objectives of this study are twofold: To assess the effectiveness of leveraging influencers to reach vulnerable individuals (as measured via app downloads per stream viewers) and to evaluate how the design of a DHI can improve engagement among this group (as measured via completion of intervention). Methods: This study utilized a cross-sectional, quasi-experimental field design to assess both (a) the effectiveness of influencers reaching vulnerable individuals and (b) the impact of specific design elements—such as gamification and storytelling—on user engagement with a stress-management DHI featuring a slow-paced breathing exercise. Three differently designed versions of this DHI were developed following a fractional factorial design (i.e., STRESSLESS, BREEZE, and TRAGICKINGDOM). Reach was calculated as the number of downloads per viewers per stream and influencer. Engagement with the DHI was measured via number of conversational turns, and milestone and intervention completion rates. Participants' SES and technology acceptance were evaluated through a post-intervention survey. Descriptive statistics, ꭓ2-tests, and ANOVAs were used to examine effects of the DHI design on reach and engagement metrics. Results: The recruitment via eight influencers (Total Streams = 25; Total Viewers = 12,667) generated 220 downloads. The average reach ratio across streams amounted to 16.2%, with significant differences between conditions, ꭓ2(2) = 8.04, p = .018: STRESSLESS: 8.1%; BREEZE: 14.0%; TRAGICKINGDOM: 28.4%. The intervention completion rate across all DHI versions amounted to 7.7% (17 out of 220), with no significant differences between conditions. Conclusions: This work provides first evidence that recruitment via influencers yields high reach ratios, moving far beyond the reach of traditional social media platforms. Nonetheless, based on the data collected, the ability to leverage such platforms to recruit and engage vulnerable individuals with DHIs remains unclear. Additionally, while engagement with the promoted interventions was initially high, completion rate of the full breathing exercise was comparably low, indicating that influencer promotion strategy cannot fully overcome the well-documented adherence barriers in digital health.
Deliberative and Paternalistic Interaction Styles for Conversational Agents in Digital Health: Procedure and Validation Through a Web-Based Experiment
Schachner, Theresa; Gross, Christoph; Hasl, Andrea; et al. (2021)
Journal of Medical Internet Research
Background: In recent years, the number of people suffering from chronic conditions that require ongoing medical support reaching into the everyday lives of patients is constantly increasing. Global health systems are, however, not adequately equipped for this extraordinarily time-consuming and cost-intensive development. Here, conversational agents (CAs) can offer easily scalable and ubiquitous support. However, different aspects have not yet been sufficiently investigated to fully exploit their potential. One such trait is the interaction style between patients and CAs. In human-to-human settings, the interaction style is an imperative part of the relationship between patients and physicians. The patient-physician interaction is recognized as critical success factor for patient's satisfaction, treatment adherence, and subsequent treatment outcome. However, it remains so far effectively unknown how different interaction styles can be implemented into CA relationships and if these are recognizable by users. Objective: The objective of this paper is to develop an operationalization scheme to induce two specific interaction styles into CA-patient dialogues and subsequently test and validate them in a chronic healthcare context. Methods: Based on the Roter Interaction Analysis System (RIAS) and iterative evaluations by scientific experts and medical healthcare professionals, we identified 15 communication components that characterize the two operationalized interaction styles, i.e., the deliberative and paternalistic interaction style. These communication components were used to develop two CA variations, each representing one of the two interaction styles. We assessed them in an online between-subject experiment. Here, participants were asked to put themselves in the position of a patient suffering from chronic obstructive pulmonary disease (COPD). Participants were randomly assigned to interact with one of the two CAs and subsequently asked to identify the respective interaction style. A chi-square test was used to assess the correct identification of the CA-patient interaction style. Results: 88 individuals (48% female, mean age= 31.5 years) fulfilled the inclusion criteria and participated in the online experiment. Participants in both the paternalistic and deliberative condition correctly identified the underlying interaction style of the CAs in more than 80% of the assessments (X2 (1, 88) = 38.23, P = .000; rφ = .68). The validation of the operationalization scheme was hence successful. Conclusions: We developed an operationalization scheme tailored for a medical context to induce a paternalistic, respectively, deliberative interaction style into a written interaction between a patient and a CA. We successfully tested and validated the operationalization scheme in an online experiment with 88 participants. Future research should implement and test the operationalization scheme with actual chronic patients and compare results between medical conditions. The operationalization scheme can further be used as a starting point to develop dynamic CAs that adapt their interaction style to their users.
Non-pharmaceutical interventions and epigenetic aging in adults: Protocol for a scoping review
Liebich, Alina; Zheng, Shenglin; Schachner, Theresa; et al. (2024)
PLoS ONE
Introduction: Aging is the strongest risk factor for most chronic diseases. The rising burden of an aging population and non-communicable diseases (NCDs), contributes to escalating costs for society. Several non-pharmaceutical interventions can lower the risk of NCDs, including common mental disorders (CMDs), and may slow down biological aging, as evidenced by outcome markers such as epigenetic clocks. However, a comprehensive overview of whether and which non-pharmaceutical interventions may impact human epigenetic aging is missing. Synthesizing evidence of interventions on epigenetic aging that can be adopted by a wider population is key to guide healthy aging initiatives and to reduce the burden of NCDs and CMDs. This scoping review will identify and assess non-pharmaceutical interventions aimed to slow down epigenetic aging, including their intervention components, and the mode used for intervention delivery.
Voice-based Conversational Agents for the Prevention and Management of Chronic and Mental Conditions: A Systematic Literature Review
Bérubé, Caterina; Schachner, Theresa; Keller, Roman; et al. (2021)
Journal of Medical Internet Research
Background: Chronic and mental health conditions are increasingly prevalent worldwide. As devices in our everyday lives offer more and more voice-based self-service, voice-based conversational agents (VCAs) have the potential to support the prevention and management of these conditions in a scalable manner. However, evidence on VCAs dedicated to the prevention and management of chronic and mental health conditions is unclear. Objective: This study provides a better understanding of the current methods used in the evaluation of health interventions for the prevention and management of chronic and mental health conditions delivered through VCAs. Methods: We conducted a systematic literature review using PubMed MEDLINE, Embase, PsycINFO, Scopus, and Web of Science databases. We included primary research involving the prevention or management of chronic or mental health conditions through a VCA and reporting an empirical evaluation of the system either in terms of system accuracy, technology acceptance, or both. A total of 2 independent reviewers conducted the screening and data extraction, and agreement between them was measured using Cohen kappa. A narrative approach was used to synthesize the selected records. Results: Of 7170 prescreened papers, 12 met the inclusion criteria. All studies were nonexperimental. The VCAs provided behavioral support (n=5), health monitoring services (n=3), or both (n=4). The interventions were delivered via smartphones (n=5), tablets (n=2), or smart speakers (n=3). In 2 cases, no device was specified. A total of 3 VCAs targeted cancer, whereas 2 VCAs targeted diabetes and heart failure. The other VCAs targeted hearing impairment, asthma, Parkinson disease, dementia, autism, intellectual disability, and depression. The majority of the studies (n=7) assessed technology acceptance, but only few studies (n=3) used validated instruments. Half of the studies (n=6) reported either performance measures on speech recognition or on the ability of VCAs to respond to health-related queries. Only a minority of the studies (n=2) reported behavioral measures or a measure of attitudes toward intervention-targeted health behavior. Moreover, only a minority of studies (n=4) reported controlling for participants’ previous experience with technology. Finally, risk bias varied markedly. Conclusions: The heterogeneity in the methods, the limited number of studies identified, and the high risk of bias show that research on VCAs for chronic and mental health conditions is still in its infancy. Although the results of system accuracy and technology acceptance are encouraging, there is still a need to establish more conclusive evidence on the efficacy of VCAs for the prevention and management of chronic and mental health conditions, both in absolute terms and in comparison with standard health care.
Personalization of Conversational Agent-Patient Interaction Styles for Chronic Disease Management: Two Consecutive Cross-sectional Questionnaire Studies
Gross, Christoph; Schachner, Theresa; Hasl, Andrea; et al. (2021)
Journal of Medical Internet Research
Background: Conversational agents (CAs) for chronic disease management are receiving increasing attention in academia and the industry. However, long-term adherence to CAs is still a challenge and needs to be explored. Personalization of CAs has the potential to improve long-term adherence and, with it, user satisfaction, task efficiency, perceived benefits, and intended behavior change. Research on personalized CAs has already addressed different aspects, such as personalized recommendations and anthropomorphic cues. However, detailed information on interaction styles between patients and CAs in the role of medical health care professionals is scant. Such interaction styles play essential roles for patient satisfaction, treatment adherence, and outcome, as has been shown for physician-patient interactions. Currently, it is not clear (1) whether chronically ill patients prefer a CA with a paternalistic, informative, interpretive, or deliberative interaction style, and (2) which factors influence these preferences. Objective: We aimed to investigate the preferences of chronically ill patients for CA-delivered interaction styles. Methods: We conducted two studies. The first study included a paper-based approach and explored the preferences of chronic obstructive pulmonary disease (COPD) patients for paternalistic, informative, interpretive, and deliberative CA-delivered interaction styles. Based on these results, a second study assessed the effects of the paternalistic and deliberative interaction styles on the relationship quality between the CA and patients via hierarchical multiple linear regression analyses in an online experiment with COPD patients. Patients’ sociodemographic and disease-specific characteristics served as moderator variables. Results: Study 1 with 117 COPD patients revealed a preference for the deliberative (50/117) and informative (34/117) interaction styles across demographic characteristics. All patients who preferred the paternalistic style over the other interaction styles had more severe COPD (three patients, Global Initiative for Chronic Obstructive Lung Disease class 3 or 4). In Study 2 with 123 newly recruited COPD patients, younger participants and participants with a less recent COPD diagnosis scored higher on interaction-related outcomes when interacting with a CA that delivered the deliberative interaction style (interaction between age and CA type: relationship quality: b=−0.77, 95% CI −1.37 to −0.18; intention to continue interaction: b=−0.49, 95% CI −0.97 to −0.01; working alliance attachment bond: b=−0.65, 95% CI −1.26 to −0.04; working alliance goal agreement: b=−0.59, 95% CI −1.18 to −0.01; interaction between recency of COPD diagnosis and CA type: working alliance goal agreement: b=0.57, 95% CI 0.01 to 1.13). Conclusions: Our results indicate that age and a patient’s personal disease experience inform which CA interaction style the patient should be paired with to achieve increased interaction-related outcomes with the CA. These results allow the design of personalized health care CAs with the goal to increase long-term adherence to health-promoting behavior. --> Background: Conversational agents (CAs) for chronic disease management are receiving increasing attention in academia and the industry. However, long-term adherence to CAs is still a challenge and needs to be explored. Personalization of CAs has the potential to improve long-term adherence and, with it, user satisfaction, task efficiency, perceived benefits, and intended behavior change. Research on personalized CAs has already addressed different aspects, such as personalized recommendations and anthropomorphic cues. However, detailed information on interaction styles between patients and CAs in the role of medical health care professionals is scant. Such interaction styles play essential roles for patient satisfaction, treatment adherence, and outcome, as has been shown for physician-patient interactions. Currently, it is not clear (1) whether chronically ill patients prefer a CA with a paternalistic, informative, interpretive, or deliberative interaction style, and (2) which factors influence these preferences. Objective: We aimed to investigate the preferences of chronically ill patients for CA-delivered interaction styles. Methods: We conducted two studies. The first study included a paper-based approach and explored the preferences of chronic obstructive pulmonary disease (COPD) patients for paternalistic, informative, interpretive, and deliberative CA-delivered interaction styles. Based on these results, a second study assessed the effects of the paternalistic and deliberative interaction styles on the relationship quality between the CA and patients via hierarchical multiple linear regression analyses in an online experiment with COPD patients. Patients’ sociodemographic and disease-specific characteristics served as moderator variables. Results: Study 1 with 117 COPD patients revealed a preference for the deliberative (50/117) and informative (34/117) interaction styles across demographic characteristics. All patients who preferred the paternalistic style over the other interaction styles had more severe COPD (three patients, Global Initiative for Chronic Obstructive Lung Disease class 3 or 4). In Study 2 with 123 newly recruited COPD patients, younger participants and participants with a less recent COPD diagnosis scored higher on interaction-related outcomes when interacting with a CA that delivered the deliberative interaction style (interaction between age and CA type: relationship quality: b=−0.77, 95% CI −1.37 to −0.18; intention to continue interaction: b=−0.49, 95% CI −0.97 to −0.01; working alliance attachment bond: b=−0.65, 95% CI −1.26 to −0.04; working alliance goal agreement: b=−0.59, 95% CI −1.18 to −0.01; interaction between recency of COPD diagnosis and CA type: working alliance goal agreement: b=0.57, 95% CI 0.01 to 1.13). Conclusions: Our results indicate that age and a patient’s personal disease experience inform which CA interaction style the patient should be paired with to achieve increased interaction-related outcomes with the CA. These results allow the design of personalized health care CAs with the goal to increase long-term adherence to health-promoting behavior.
Conversational Agents (CAs) for Health Care for Chronic Diseases (HCD): Personalization and the CA-Patient Relationship
Schachner, Theresa (2021)
Conversational Agents as Mediating Social Actors in Chronic Disease Management Involving Health Care Professionals, Patients, and Family Members: Multisite Single-Arm Feasibility Study
Kowatsch, Tobias; Schachner, Theresa; Harperink, Samira; et al. (2021)
Journal of Medical Internet Research
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.

Publications 1 - 8 of 8

Theresa Schachner

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