The effects of word of mouth (WOM) on the receiver's attitudes and intentions have been studied at length, but the question under which conditions WOM leads to a behavioural outcome (such as a purchase or switching decision) has received less attention. This paper studies the effects of WOM in the context of service provider switching. An empirical study is presented which researches whether perceived influence of a switching referral is related to subsequent switching behaviour, and whether the variables that have an effect on perceived influence of the switching referral also predict switching. Results show that the strength of WOM influence is determined by perceived communicator characteristics. Perceived risk dimensions, in turn, moderate these effects.
Background The working alliance refers to an important relationship quality between health professionals and clients that robustly links to treatment success. Recent research shows that clients can develop an affective bond with chatbots. However, few research studies have investigated whether this perceived relationship is affected by the social roles of differing closeness a chatbot can impersonate and by allowing users to choose the social role of a chatbot. Objective This study aimed at understanding how the social role of a chatbot can be expressed using a set of interpersonal closeness cues and examining how these social roles affect clients’ experiences and the development of an affective bond with the chatbot, depending on clients’ characteristics (ie, age and gender) and whether they can freely choose a chatbot’s social role. Methods Informed by the social role theory and the social response theory, we developed a design codebook for chatbots with different social roles along an interpersonal closeness continuum. Based on this codebook, we manipulated a fictitious health care chatbot to impersonate one of four distinct social roles common in health care settings—institution, expert, peer, and dialogical self—and examined effects on perceived affective bond and usage intentions in a web-based lab study. The study included a total of 251 participants, whose mean age was 41.15 (SD 13.87) years; 57.0% (143/251) of the participants were female. Participants were either randomly assigned to one of the chatbot conditions (no choice: n=202, 80.5%) or could freely choose to interact with one of these chatbot personas (free choice: n=49, 19.5%). Separate multivariate analyses of variance were performed to analyze differences (1) between the chatbot personas within the no-choice group and (2) between the no-choice and the free-choice groups. Results While the main effect of the chatbot persona on affective bond and usage intentions was insignificant (P=.87), we found differences based on participants’ demographic profiles: main effects for gender (P=.04, ηp2=0.115) and age (P<.001, ηp2=0.192) and a significant interaction effect of persona and age (P=.01, ηp2=0.102). Participants younger than 40 years reported higher scores for affective bond and usage intentions for the interpersonally more distant expert and institution chatbots; participants 40 years or older reported higher outcomes for the closer peer and dialogical-self chatbots. The option to freely choose a persona significantly benefited perceptions of the peer chatbot further (eg, free-choice group affective bond: mean 5.28, SD 0.89; no-choice group affective bond: mean 4.54, SD 1.10; P=.003, ηp2=0.117). Conclusions Manipulating a chatbot’s social role is a possible avenue for health care chatbot designers to tailor clients’ chatbot experiences using user-specific demographic factors and to improve clients’ perceptions and behavioral intentions toward the chatbot. Our results also emphasize the benefits of letting clients freely choose between chatbots.
BACKGROUND Successful management of chronic diseases requires a trustful collaboration between healthcare professionals, patients, and family members. Scalable conversational agents (CAs), designed to assist healthcare professionals, may play a significant role in supporting this collaboration in a scalable way by reaching out into the everyday lives of patients and their family members. Until now, however, it has not been clear whether CAs, in such a role, would be accepted and whether they can support this multi-stakeholder collaboration. OBJECTIVE With asthma in children representing a relevant target of chronic disease management, this work has two objectives: (1) To describe the design of MAX, a CA-delivered asthma intervention that supports healthcare professionals targeting child-parent teams in their everyday lives; (2) To assess the (a) reach of MAX, (b) CA-patient working alliance, (c) acceptance of MAX, (d) intervention completion rate, (e) cognitive and behavioral outcomes, and (f) human effort and responsiveness of healthcare professionals in primary and secondary care settings. METHODS MAX was designed to increase cognitive skills (i.e. knowledge about asthma) and behavioral skills (i.e. 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 CA-patient working alliance; (2) To offer hybrid (human- and CA-supported) ubiquitous coaching; (3) To provide an intervention with a high experiential value. An interdisciplinary team of computer scientists, asthma experts, and young patients with their parents developed the intervention collaboratively. The CA communicates with healthcare professionals via email, with patients via a mobile chat app and with a family member via SMS. A single-arm feasibility study in primary and secondary care settings was conducted to assess MAX. RESULTS Results indicate an overall positive evaluation of MAX with respect to its reach (49.5% (49 out of 99) of recruited and eligible patient-family member teams participated), a strong patient-CA working alliance, and a 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 CA as opposed to between patient and healthcare professional, thus indicating the scalability of MAX. In addition, it took healthcare professionals less than four minutes to assess the inhalation technique and three days to deliver that feedback to the patients. Several suggestions for improvement were made. CONCLUSIONS For the first time, this work provides evidence that CAs, designed as mediating social actors involving healthcare 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.
BACKGROUND Health professions education has undergone major changes with the advent and adoption of digital technologies worldwide. OBJECTIVE This study aims to map the existing evidence and identify gaps and research priorities to enable robust and relevant research in digital health professions education. METHODS We searched for systematic reviews on the digital education of practicing and student health care professionals. We searched MEDLINE, Embase, Cochrane Library, Educational Research Information Center, CINAHL, and gray literature sources from January 2014 to July 2020. A total of 2 authors independently screened the studies, extracted the data, and synthesized the findings. We outlined the key characteristics of the included reviews, the quality of the evidence they synthesized, and recommendations for future research. We mapped the empirical findings and research recommendations against the newly developed conceptual framework. RESULTS We identified 77 eligible systematic reviews. All of them included experimental studies and evaluated the effectiveness of digital education interventions in different health care disciplines or different digital education modalities. Most reviews included studies on various digital education modalities (22/77, 29%), virtual reality (19/77, 25%), and online education (10/77, 13%). Most reviews focused on health professions education in general (36/77, 47%), surgery (13/77, 17%), and nursing (11/77, 14%). The reviews mainly assessed participants’ skills (51/77, 66%) and knowledge (49/77, 64%) and included data from high-income countries (53/77, 69%). Our novel conceptual framework of digital health professions education comprises 6 key domains (context, infrastructure, education, learners, research, and quality improvement) and 16 subdomains. Finally, we identified 61 unique questions for future research in these reviews; these mapped to framework domains of education (29/61, 47% recommendations), context (17/61, 28% recommendations), infrastructure (9/61, 15% recommendations), learners (3/61, 5% recommendations), and research (3/61, 5% recommendations). CONCLUSIONS We identified a large number of research questions regarding digital education, which collectively reflect a diverse and comprehensive research agenda. Our conceptual framework will help educators and researchers plan, develop, and study digital education. More evidence from low- and middle-income countries is needed.
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