id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-223560-ppu6idl2	Russo, Daniel	Predictors of Well-being and Productivity among Software Professionals during the COVID-19 Pandemic -- A Longitudinal Study	2020-07-24		.txt	text/plain	14058	811	57	Results include (1) the quality of social contacts predicted positively, and stress predicted an individual's well-being negatively when controlling for other variables consistently across both waves; (2) boredom and distractions predicted productivity negatively; (3) productivity was less strongly associated with all predictor variables at time two compared to time one, suggesting that software engineers adapted to the lockdown situation over time; and (4) the longitudinal study did not provide evidence that any predictor variable causal explained variance in well-being and productivity. Therefore, there is a compelling need for longitudinal applied research that draws on theories and findings from various scientific fields to identify variables that uniquely predict the well-being and productivity of software professionals during the 2020 quarantine, for both the current and potential future lockdowns. Second, this approach simultaneously allows us to test whether models developed in an organizational context such as the two-factor theory [48] can also predict people's well-being in general and whether variables that were associated with well-being for people being quarantined also explain productivity.	./cache/cord-223560-ppu6idl2.txt	./txt/cord-223560-ppu6idl2.txt