The study finds that it is the information seeking effectiveness rather than the social support which affects patient's perceived empathy in online health communities run by HCOs. The results indicate that HCOs that provide online health communities for their patients need to focus more on developing tools that will make information seeking more effective and efficient.
An understanding of the four models of consumer value cocreation can help HCOs adopt appropriate strategies and practices to embrace consumers as partners in the development and delivery of innovative health care products and services.
Undiagnosed and untreated depressive disorders have become a serious public health issue and it is prevalent among people of all ages, gender and race. Social media sites, such as Twitter, have become a major venue for people to express/disclose their thoughts and feelings. The tweets from these micro-blogging sites could be used to screen for and potentially detect depression. To date, studies in this area have focused on developing and validating the terms and vocabulary used by users with depression, or evaluating tweets related to depression by using terms that are synonymous with depression. This approach has not produced reliable findings. In this study, we depart from this approach and instead, base our analysis on research on depressive disorders, which indicates the critical significance of repetitive thoughts and ruminating behavior of people with depression. The current study and findings hold important implications for research on depression, social media, and public health informatics.
The use of mobile technology and mobile apps has become pervasive in our daily lives for completing a variety of daily tasks. Mobile health (mHealth) apps can provide an accessible platform for self-management among breast cancer (BC) survivors, as they recover from not just the intensive cancer treatments, but also their associated side-effects. They also offer a means to learn about survivorship topics and connect with peer survivors online, irrespective of their geographical location. This study is an attempt to assess the availability and characterize the self-management features of free mobile apps for breast cancer survivors on the Google Play (Android) and Apple App Store (iOS). Out of 249 such apps for the Android, only eight satisfied initial criteria, while only one of 174 iOS apps that met inclusion criteria was included for further analysis. A content analysis of the nine apps that met inclusion criteria was conducted to assess the inclusion of the following mHealth self-management features derived from the Chronic Care Model: symptom tracking; survivorship education; information-sharing with family and/or caregivers; scheduling follow-up visits; personal alerts and reminders; and social networking. Survivorship education was found to be the most common self-management feature among the apps reviewed, followed by social networking. The results of this study highlight the dearth of available mHealth resources for BC survivors. Future efforts in app development should involve survivors and healthcare providers to ensure comprehensive resources that address their unmet needs are made more accessible.
An understanding of the four dimensions of patient experience in online health communities and its implications on patient attitudes could help HCOs to design, deploy, and manage such online health communities more effectively.
BackgroundDrug repurposing (defined as discovering new indications for existing drugs) could play a significant role in drug development, especially considering the declining success rates of developing novel drugs. Typically, new indications for existing medications are identified by accident. However, new technologies and a large number of available resources enable the development of systematic approaches to identify and validate drug-repurposing candidates. Patients today report their experiences with medications on social media and reveal side effects as well as beneficial effects of those medications.ObjectiveOur aim was to assess the feasibility of using patient reviews from social media to identify potential candidates for drug repurposing.MethodsWe retrieved patient reviews of 180 medications from an online forum, WebMD. Using dictionary-based and machine learning approaches, we identified disease names in the reviews. Several publicly available resources were used to exclude comments containing known indications and adverse drug effects. After manually reviewing some of the remaining comments, we implemented a rule-based system to identify beneficial effects.ResultsThe dictionary-based system and machine learning system identified 2178 and 6171 disease names respectively in 64,616 patient comments. We provided a list of 10 common patterns that patients used to report any beneficial effects or uses of medication. After manually reviewing the comments tagged by our rule-based system, we identified five potential drug repurposing candidates.ConclusionsTo our knowledge, this is the first study to consider using social media data to identify drug-repurposing candidates. We found that even a rule-based system, with a limited number of rules, could identify beneficial effect mentions in patient comments. Our preliminary study shows that social media has the potential to be used in drug repurposing.
BackgroundThis paper adopts a communication and sociocultural perspective to analyze the factors behind the lag in electronic medical record (EMR) adoption in the United States. Much of the extant research on this topic has emphasized economic factors, particularly, lack of economic incentives, as the primary cause of the delay in EMR adoption. This prompted the Health Information Technology on Economic and Clinical Health Act that allow financial incentives through the Centers of Medicare and Medicaid Services for many health care organizations planning to adopt EMR. However, financial incentives alone have not solved the problem; many new innovations do not diffuse even when offered for free. Thus, this paper underlines the need to consider communication and sociocultural factors to develop a better understanding of the impediments of EMR adoption.ObjectiveThe objective of this paper was to develop a holistic understanding of EMR adoption by identifying and analyzing the impact of communication and sociocultural factors that operate at 3 levels: macro (environmental), meso (organizational), and micro (individual).MethodsWe use the systems approach to focus on the 3 levels (macro, meso, and micro) and developed propositions at each level drawing on the communication and sociocultural perspectives.ResultsOur analysis resulted in 10 propositions that connect communication and sociocultural aspects with EMR adoption.ConclusionsThis paper brings perspectives from the social sciences that have largely been missing in the extant literature of health information technology (HIT) adoption. In doing so, it implies how communication and sociocultural factors may complement (and in some instances, reinforce) the impact of economic factors on HIT adoption.
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