Safety and accuracy of digitally supported primary and secondary urgent care telephone triage in England: an observational study using routine data by Vanashree Sexton, Catherine Grimley, Jeremy Dale, Helen Atherton, Gary Abel

“…Non-clinician primary triage is risk averse, reflected in its high sensitivity but low specificity. …”
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Presenting the model of portfolio management in investment funds based on behavioral financial variables by Seyed Mohammad Hadi Shahamat, Mahdi Mohammad Bagheri, Ali Raispour Rajabali, Mohsen Zayandeh Roudi

“…In the second level, the components influencing the first level, i.e. paying attention to self-control behaviors, having a written investment strategy, paying attention to the principles of mental accounting; and in the third level, the components influencing the second level, which include behavioral optimism and pessimism, Paying attention to risk-averse and risk-taking behaviors and, controlling mass behaviors; and the most effective component at the fourth level includes the effect of inclination. …”
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Robotic Surgery from a Gynaecological Oncology Perspective: A Global Gynaecological Oncology Surgical Outcomes Collaborative Led Study (GO SOAR3) by Faiza Gaba, Karen Ash, Oleg Blyuss, Dhivya Chandrasekaran, Marielle Nobbenhuis, Thomas Ind, Elly Brockbank, on behalf of the GO SOAR Collaborators

“…Our data suggest gender differences in the robotics learning curve with men six times more likely to state robotic surgery had negatively impacted their situational awareness in the operating theatre (OR = 6.35, <i>p</i> ≤ 0.001) and 2.5 times more likely to state it had negatively impacted their surgical ability due to lack of haptic feedback in comparison to women (OR = 2.62, <i>p</i> = 0.046). Women were more risk-averse in case selection, but there were no self-reported differences in the intra-operative complication rates between male and female surgeons (OR = 1, <i>p</i> = 0.1). …”
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Presenting a model to explain unfavorable risk and favorable risk according to psychological variables in predicting market fluctuations in the Iranian capital market. by Hasan Rezaeikangi, Mahdi Mohammad Bagheri, Hojat Babaei, Ali Raeispour Rajabali

“…The research components include: financing, marketing communications, information accuracy, bankruptcy financial indicators, bankruptcy non-financial indicators, political factors, interpretation of fluctuations, economic factors, factors related to the stock market, factors related to the company, brokerages, personality, optimistic behavior, over-trusting behavior, risk-averse behavior, emotional behavior, financial education, monitoring and evaluation, rules and regulations, economic added value, company value, individual satisfaction, and economic growth. …”
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