BackgroundFor many eServices, end-user trust is a crucial prerequisite for use. Within the context of Telemedicine, the role of trust has hardly ever been studied. In this study, we explored what determines trust in portals that facilitate rehabilitation therapy, both from the perspective of the patient and the healthcare professional.MethodsWe held two focus groups with patients (total n = 15) and two with healthcare professionals (total n = 13) in which we discussed when trust matters, what makes up trust in a rehabilitation portal, what effect specific design cues have, and how much the participants trust the use of activity sensor data for informing treatment.ResultsTrust in a rehabilitation portal is the sum of trust in different factors. These factors and what makes up these factors differ for patients and healthcare professionals. For example, trust in technology is made up, for patients, mostly by a perceived level of control and privacy, while for healthcare professionals, a larger and different set of issues play a role, including technical reliability and a transparent data storage policy. Healthcare professionals distrust activity sensor data for informing patient treatment, as they think that sensors are unable to record the whole range of movements that patients make (e.g., walking and ironing clothes).ConclusionsThe set of factors that affect trust in a rehabilitation portal are different from the sets that have been found for other contexts, like eCommerce. Trust in telemedicine technology should be studied as a separate subject to inform the design of reliable interventions.
Background Trust is widely recognized as a crucial factor in successful physician–patient communication and patient engagement in treatment. However, with the rise of eHealth technologies, such as online patient portals, the role of trust and the factors that influence it need to be reconsidered. In this study, we aim to identify the factors that contribute to trust in an eHealth service and we aim to identify the consequences of trust in an eHealth service in terms of use. Methods The Patient Trust Assessment Tool was provided to new outpatients of a rehabilitation center in the Netherlands, that were expected to use the center’s online patient portal. Via this tool, we assessed five trust-related factors. This data was supplemented by questions about demographics (age, gender, rehabilitation treatment) and data about use (number of sessions, total time spent in sessions), derived from data logs. Data was analyzed via Partial Least Squares Structural Equation Modelling. Results In total, 93 patients participated in the study. Out of these participants, 61 used the portal at least once. The measurement model was considered good. Trust in the organization was found to affect trust in the care team (β = .63), trust in the care team affected trust in the treatment (β = .60). Both, trust in the care team and trust in the treatment influenced trust in the technology (β = .42 and .30, respectively). Trust in the technology affected the holistic concept trust in the service (β = .78). This holistic trust in the service finally, did not affect use. Conclusions This study shows that the formation of this trust is not unidimensional, but consists of different, separate factors (trust in the care organization, trust in the care team and trust in the treatment). Trust transfer does take place from offline to online health services. However, trust in the service does not directly affect the use of the eHealth technology.
Can you imagine to receive treatment through a robot? When talking about the future of healthcare, this is the vision many people have. Currently, the predominant role of social robots in care is entertaining patients. However, this does not have an impact on care process itself. In this paper, we focus on defining use cases other than merely keeping patients’ company by implementing a Pepper robot in inpatient rehabilitation setting, and expand upon usability testing the use cases. Our findings showed that, to ensure sustainable implementation of social robots in care organizations, we need excessive collaboration with the target population.
Background Clinical Decision Support Systems (CDSSs) are computerized systems using case-based reasoning to assist clinicians in making clinical decisions. Despite the proven added value to public health, the implementation of CDSS clinical practice is scarce. Particularly, little is known about the acceptance of CDSS among clinicians. Within the Back-UP project (Project Number: H2020-SC1-2017-CNECT-2-777090) a CDSS is developed with prognostic models to improve the management of Neck and/or Low Back Pain (NLBP). Therefore, the aim of this study is to present the factors involved in the acceptance of CDSSs among clinicians. Methods To assess the acceptance of CDSSs among clinicians we conducted a mixed method analysis of questionnaires and focus groups. An online questionnaire with a low-fidelity prototype of a CDSS (TRL3) was sent to Dutch clinicians aimed to identify the factors influencing the acceptance of CDSSs (intention to use, perceived threat to professional autonomy, trusting believes and perceived usefulness). Next to this, two focus groups were conducted with clinicians addressing the general attitudes towards CDSSs, the factors determining the level of acceptance, and the conditions to facilitate use of CDSSs. Results A pilot-study of the online questionnaire is completed and the results of the large evaluation are expected spring 2020. Eight clinicians participated in two focus groups. After being introduced to various types of CDSSs, participants were positive about the value of CDSS in the care of NLBP. The clinicians agreed that the human touch in NLBP care must be preserved and that CDSSs must remain a supporting tool, and not a replacement of their role as professionals. Conclusions By identifying the factors hindering the acceptance of CDSSs we can draw implications for implementation of CDSSs in the treatment of NLBP.
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