Informational Power and Perceived Collective Benefit Affecting the Users' Preference for a Mobile Technology: Evidences From a Survey Study

Using artificial intelligence to examine online patient reviews

Healthcare consumers are increasingly turning to online sources such as educational websites, forums and social media platforms to share their experiences with medical services and to demystify the uncertainties associated with undergoing various procedures. This study demonstrates a non-invasive way of understanding the feelings and emotions that consumers share via electronic word of mouth. By using IBM Watson, a content analysis tool that harnesses artificial intelligence, we show how a large amount of unstructured qualitative data can be transformed into quantitative data that can be subsequently analysed to generate novel insights into what patients are sharing about their healthcare experiences online.

Assessment of Psychological Dimensions in Telemedicine Care for Gestational Diabetes Mellitus: A Systematic Review of Qualitative and Quantitative Studies

Background and Objective: Gestational Diabetes Mellitus (GDM) is a complex and wide spread problem and is considered one of the most frequent chronic metabolic conditions during pregnancy. According to a recent consensus conference held in Italy, new technologies can play a role in the so-called process of fertilization of the individual's ecosystem engagement, representing support for systemic collaboration among the main actors. The current systematic review aimed at providing an update of the literature about telemedicine for GDM, considering the role of psychological dimensions such as empowerment/self-efficacy, engagement and satisfaction.

Methods: The review was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. The data sources were PubMed, ScienceDirect, Cochrane, and Scopus databases.

Results: Thirteen articles were identified as eligible and relevant for the final qualitative synthesis, but none was specific for the topic of engagement. The quality or research bias of the studies presents methodological limits. Most studies had clinical outcomes as a primary object. Concerning empowerment and self-efficacy, there were only preliminary findings reporting any improvements derived from using telemedicine approaches. Conversely, there were more consistent and positive results concerning the satisfaction of patients and clinicians.

Conclusions: These results are not sufficient to state a conclusive evaluation of positive effects of telemedicine use for GDM care. A more in-depth investigation of engagement and empowerment dimensions is necessary, as some benefits for the management of chronic conditions were already detected. Further investigations will also be necessary concerning the acceptability and feasibility of telemedicine systems by clinicians.