Plos One
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We investigated the association between socioeconomic status (SES) and screening for diabetic retinopathy (DR) and diabetic nephropathy (DN) in community-dwelling diabetics. We analyzed data from 22,134 people with diabetes aged ≥19 years at the time of the nationwide 2015 Korean Community Health Survey. Multiple logistic regression analysis was used to explore the relationship between SES and screening for DR and DN both before and after adjustment for health behaviors, comorbidities, and educational level. ⋯ Similar findings were obtained when the analysis was limited to those who had been educated about diabetes. In conclusion, socioeconomic inequalities were evident in terms of screening for DR and DN in community-dwelling Korean diabetics, regardless of whether they had reported receiving diabetes education. Tailored public health policies (and societal attention) are required to aid the socioeconomically disadvantaged.
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Efforts to detect patient deterioration early have led to the development of early warning score (EWS) models. However, these models are disease-nonspecific and have shown variable accuracy in predicting unexpected critical events. Here, we propose a simpler and more accurate method for predicting risk in respiratory ward patients. ⋯ The SF ratio displayed better or comparable predictive accuracy for unexpected ICU transfer (AUROC: 0.744) compared to MEWS (0.744 vs. 0.653, P = 0.03), NEWS (0.744 vs. 0.667, P = 0.04), and ViEWS (0.744 vs. 0.675, P = 0.06). For in-hospital mortality, although there was no statistical difference, the AUROC of the SF ratio (0.660) was higher than that of each of the preexisting EWS models. In comparison with the preexisting EWS models, the SF ratio showed better or comparable predictive accuracy for unexpected ICU transfers in the respiratory wards.
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Since the shooting of Black teenager Michael Brown by White police officer Darren Wilson in Ferguson, Missouri, the protest hashtag #BlackLivesMatter has amplified critiques of extrajudicial killings of Black Americans. In response to #BlackLivesMatter, other Twitter users have adopted #AllLivesMatter, a counter-protest hashtag whose content argues that equal attention should be given to all lives regardless of race. ⋯ In addition, we show that a significant portion of #AllLivesMatter use stems from hijacking by #BlackLivesMatter advocates. Beyond simply injecting #AllLivesMatter with #BlackLivesMatter content, these hijackers use the hashtag to directly confront the counter-protest notion of "All lives matter." Our findings suggest that Black Lives Matter movement was able to grow, exhibit diverse conversations, and avoid derailment on social media by making discussion of counter-protest opinions a central topic of #AllLivesMatter, rather than the movement itself.
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Observational Study
Caring for the caregivers: Evaluation of the effect of an eight-week pilot mindful self-compassion (MSC) training program on nurses' compassion fatigue and resilience.
Nurses vicariously exposed to the suffering of those in their care are at risk of compassion fatigue. Emerging research suggests that self-compassion interventions may provide protective factors and enhance resilience. This pilot study examined the effect of an eight-week Mindful Self-Compassion (MSC) training intervention on nurses' compassion fatigue and resilience and participants' lived experience of the effect of the training. ⋯ This is the first study to examine the effect of a pilot (MSC) training program on nurses' compassion fatigue and resilience in this new area of research. It provides some preliminary empirical evidence in support of the theorized benefits of self-compassion training for nurses. However, further research, such as a Randomized Control Trial (RCT) with a larger sample size and a longitudinal study, is required to see if the benefits of self-compassion training are sustainable.
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Stack Overflow is a popular crowdsourced question and answer website for programming-related issues. It is an invaluable resource for software developers; on average, questions posted there get answered in minutes to an hour. Questions about well established topics, e.g., the coercion operator in C++, or the difference between canonical and class names in Java, get asked often in one form or another, and answered very quickly. ⋯ Interestingly, no operationalization of bounty amount shows significance in our models. In practice, our findings confirm the value of bounties in enhancing expert participation. In addition, they show that the Stack Overflow style of crowdsourcing, for all its glory in providing answers about established programming knowledge, is less effective with new API questions.