Since the advent of the Internet, social critics have debated its effects on intimacy and social relationships. I show how, by writing detailed descriptions of their illness experiences, participants in online support groups create emotionally vibrant, empathic communities in which emotional rhetoric frames various moral dilemmas. I illustrate my argument with a detailed analysis of “emotion talk” among members of an HIV/AIDS support group over a 2-year period. My findings add to current debates by encouraging sociologists to consider the emotional dynamics within the online support group as a moral, rather than just psychological or therapeutic, component of interaction.

The fast and seemingly uncontrollable spread of the novel coronavirus disease (COVID-19) poses great challenges to an already overloaded health system worldwide. It thus exemplifies an urgent need for fast and effective triage. Such triage can help in the implementation of the necessary measures to prevent patient deterioration and conserve strained hospital resources. We examine two types of machine learning models, a multilayer perceptron artificial neural networks and decision trees, to predict the severity level of illness for patients diagnosed with COVID-19, based on their medical history and laboratory test results. In addition, we combine the machine learning models with a LIME-based explainable model to provide explainability of the model prediction. Our experimental results indicate that the model can achieve up to 80% prediction accuracy for the dataset we used. Finally, we integrate the explainable machine learning models into a mobile application to enable the usage of the proposed models by medical staff worldwide.

Introduction: Vaccines have contributed to substantial reductions of morbidity and mortality from vaccine-preventable diseases, mainly in children. However, vaccine hesitancy was listed by the World Health Organization (WHO) in 2019 as one of the top ten threats to world health. Aim: To employ machine-learning strategies to assess how on-line content regarding vaccination affects vaccine hesitancy. Methods: We collected social media posts and responses from vaccination discussion groups and forums on leading social platforms, including Facebook and Tapuz (A user content website that contains blogs and forums). We investigated 65,603 records of children aged 0–6 years who are insured in Maccabi’s Health Maintenance Organization (HMO). We applied three machine learning algorithms (Logistic regression, Random forest and Neural networks) to predict vaccination among Israeli children, based on demographic and social media traffic. Results: Higher hesitancy was associated with more social media traffic, for most of the vaccinations. The addition of the social media traffic features improved the performances of most of the models. However, for Rota virus, Hepatitis A and hepatitis B, the performances of all algorithms (with and without the social media features) were close to random (accuracy up to 0.63 and F1 up to 0.65). We found a negative association between on-line discussions and vaccination. Conclusions: There is an association between social media traffic and vaccine hesitancy. Policy makers are encouraged to perceive social media as a main channel of communication during health crises. Health officials and experts are encouraged to take part in social media discussions, and be equipped to readily provide the information, support and advice that the public is looking for, in order to optimize vaccination actions and to improve public health

Background: The heavy reliance on remote patient care (RPC) during the COVID-19 health crisis may have expedited the emergence of digital health tools that can contribute to safely and effectively moving the locus of care from the hospital to the community. Understanding how laypersons interpret the personal health information accessible to them via electronic patient records (EPRs) is crucial to healthcare planning and the design of services. Yet we still know little about how the format in which personal medical information is presented in the EPR (numerically, verbally, or graphically) affects individuals’ understanding of the information, their assessment of its gravity, and the course of action they choose in response. Methods: We employed an online questionnaire to assess respondents’ reactions to 10 medical decision-making scenarios, where the same information was presented using different formats. In each scenario, respondents were presented with real (anonymized) patient lab results using either numeric expressions, graphs, or verbal expressions. Participants were asked to assess the gravity of the hypothetical patient’s condition and the course of action they would follow if they were that patient. The questionnaire was distributed to more than 300 participants, of whom 225 submitted usable responses. Results: Laypersons were more likely to overestimate the gravity of the information when it was presented either numerically or graphically compared to the narrative format. High perceived gravity was most likely to produce an inclination to actively seek medical attention, even when unwarranted. “Don’t know” responses were most likely to produce an inclination to either search the Internet or wait for the doctor to call. Policy recommendations: We discuss the study’s implications for the effective design of lab results in the patient portals. We suggest (1) that graphs, tables, and charts would be easier to interpret if coupled with a brief verbal explanation; (2) that highlighting an overall level of urgency may be more helpful than indicating a diversion from the norm; and (3) that statements of results should include the type of follow-up required.

This paper problematizes gift relations in criminal organizations. It adopts a symbolic interaction perspective to focus scholarly attention on the way in which actants skillfully maneuver within the social expectations inherent in gift‐giving relations. The study is based on insights from twenty interviews with ex‐convicts and ten interviews with police officers or associates, and an in‐depth analysis of memoirs, police reports, and newspaper articles. Our study expands the scope of symbolic interactionism by considering how the exchange of gifts and favors is emotionally stylized to achieve both social and operative goals. We aim to carefully deconstruct the performance of gift‐giving and favor exchange in Israeli crime organizations, to understand how it is orchestrated to elicit genuine feelings among givers and recipients, as well as to control the use of violence. Finally, we identify gift‐giving as a double‐edged sword designed to lure recruits into a network of binding obligations, only to form a durable system of credit and debt wherein any transgressions are strictly punished.