id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-309273-gtvi37gh	Flesia, Luca	Predicting Perceived Stress Related to the Covid-19 Outbreak through Stable Psychological Traits and Machine Learning Models	2020-10-19		.txt	text/plain	7901	381	45	Finally, with the goal of anticipating persons in need of treatment and improving the targeting and overall effectiveness of preventive programs, we aimed at developing machine learning models to predict individual psychological responses to the COVID-19 pandemic, based on sociodemographic and psychological variables with maximal sensitivity in classifying subjects with high versus low levels of perceived stress. To better understand the role of stable psychological traits in predicting the level of perceived stress (PSS-10 score), a second multiple linear regression was run, adding to the previous model the scores of the five coping styles measured by the COPE-NVI-25 (COPE positive, COPE problem, COPE avoidance, COPE religion and COPE support), the BSCS total score, the internal LOC score, and the scores for the five personality traits measured by the BFI-10 (BFI-10 agreeableness, BFI-10 conscientiousness, BFI-10 emotional stability, BFI-10 extraversion and BFI-10 openness).	./cache/cord-309273-gtvi37gh.txt	./txt/cord-309273-gtvi37gh.txt