This study shows across hundreds of statistical models that marijuana use is less likely following higher experiences of negative affect and more likely following higher experiences of positive affect in regularly using college students.

This study meta-analyzed individual participant data from 12,394 individuals across 69 studies in which participants reported their emotional state and alcohol use for multiple days. Contrary to theoretical models of alcohol use, the findings indicated that people are not more likely to drink and do not consume more alcohol on days that they report higher negative affect but are more likely to drink on days that they report higher positive affect.

Most people experience the feeling of mental fatigue on a daily basis. Previous research shows that mental fatigue impacts information processing and decision making. However, the proximal causes of mental fatigue are not yet well understood. In this research, we test the opportunity cost model of mental fatigue, which proposes that people become more fatigued when the next-best alternative to the current task is higher in value. In 4 preregistered experiments (N = 430), participants repeatedly reported their current level of fatigue and chose to perform a paid labor task versus an unpaid leisure task. In Study 1, all participants were offered the same labor/leisure choice. In Studies 2 and 3, we manipulated the opportunity costs of a labor task by varying the value of an alternative leisure task. In Study 4, we manipulated the opportunity costs of a labor task by varying the value of that labor task. In all studies, we found that people were more likely to choose for leisure as they became more fatigued. In Studies 2 through 4, we did not find that the manipulated leisure value influenced the amount of fatigue participants experienced nor the likelihood to choose for leisure. However, in exploratory analyses, in all studies, we found that participants who reported to value the leisure task more got more fatigued during labor and less fatigued during leisure. Collectively, these results provide cautious support for the opportunity cost model, but they also show that cost-benefit analyses relating to labor and leisure tasks are fleeting.

Nowadays, many people take short breaks with their smartphone at work. The decision whether to continue working or to take a smartphone break is a so-called labour versus leisure decision. Motivational models predict that people are more likely to switch from labour (work) to leisure (smartphone) the more fatigue or boredom they experience. In turn, fatigue and boredom are expected to decrease after the smartphone was used. However, it is not yet clear how smartphone use at work relates to fatigue and boredom. In this study, we tested these relationships in both directions. Participants (n = 83, all PhD candidates) reported their current level of fatigue and boredom every hour at work while an application continuously logged their smartphone use. Results indicate that participants were more likely to interact with their smartphone the more fatigued or bored they were, but that they did not use it for longer when more fatigued or bored. Surprisingly, participants reported increased fatigue and boredom after having used the smartphone (more). While future research is necessary, our results (i) provide real-life evidence for the notion that fatigue and boredom are temporally associated with task disengagement, and (ii) suggest that taking a short break with the smartphone may have phenomenological costs.