It is generally well-known, and scientifically well established, that music affects emotions and moods. However, only little is known about the influence of music on thoughts. This scarcity is particularly surprising given the importance of the valence of thoughts for psychological health and well-being. We presented excerpts of heroic- and sad-sounding music to n = 62 individuals, and collected thought probes after each excerpt, assessing the valence and the nature of thoughts stimulated by the music. Our results show that mind-wandering emerged during listening to either type of music (heroic, sad), and that the type of music strongly influenced the thought contents during mind-wandering. Heroic-sounding music evoked more positive, exciting, constructive, and motivating thoughts, while sad-sounding music evoked more calm or demotivating thoughts. The results thus indicate that music has a strong effect on the valence of thought contents during mind-wandering, with heroic music evoking more empowering and motivating thoughts, and sad music more relaxing or depressive thoughts. These findings have important implications for the use of music in everyday life to promote health and well-being in both clinical populations and healthy individuals.

Problematic gaming has been linked to poor sleep outcomes; however, these associations have not yet been synthesized quantitatively. This review employed a meta-analysis to investigate the relationship between problematic gaming and sleep-related outcomes. A search of Medline, Embase, Web of Science, PsycINFO, and Google Scholar identified a total of 763 studies, including 34 studies (n = 51,901 participants) eligible for inclusion. Papers were included if available in any European language, addressed problematic gaming, contained original data, and provided sufficient data for calculation of effect sizes. Two researchers independently extracted data using pre-defined fields including quality assessment. Sleep-related outcomes were meta-analyzed for sleep parameters that were reported by 5 or more papers. Significant overall effects were found for sleep duration (g = −0.238, 95% CI = −0.364, −0.112), poor sleep quality (OR = 2.02, 95% CI = 1.47, 2.78), daytime sleepiness (OR = 1.57, 95% CI = 1.00, 2.46) and sleep problems (OR = 2.60, 95% CI = 1.94, 3.47). Between-study heterogeneity was detected for all meta-analyses. Subgroup analyses showed a higher inverse effect size for adolescent samples compared to adult or non-specific age samples in terms of sleep duration. For daytime sleepiness, a larger effect size was found for studies based on single-item sleep measures compared to multi-item sleep measures. For sleep problems, the subgroup analysis showed the opposite with a higher effect size for studies based on single-item sleep measures than multi-item sleep measures. Across all sleep parameters, problematic gamers consistently reported a more adverse sleep status than non-problematic gamers.Systematic Review Registration:https://www.crd.york.ac.uk/PROSPERO/; record ID: CRD42020158955.

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The current paper aims to investigate if Tinder use predicts romantic relationship formation 1 year later and to identify demographic, personality, mental health, and substance use covariates in the relationship between Tinder use and romantic relationship formation. Data were collected by online surveys (two waves) among students in Bergen, Norway. The first survey was administered during fall 2015 (T1). The follow-up took place 1 year later (fall 2016, T2). The sample consisted of the 5253 participants who reported to be single at T1. The surveys included questions about Tinder use, demographics, personality (the Five-Factor Model's personality traits), mental health (i.e., symptoms of depression and anxiety), alcohol use, and use of illegal substances. Bivariate comparisons were conducted to assess differences in demographics, personality traits, mental health, and substance use between Tinder users and non-Tinder users. Further, crude and adjusted binary logistic regressions were employed to investigate if Tinder use at T1 predicted romantic relationship formation at T2, when controlling for relevant covariates. Tinder users differed from non-users on almost all included variables. Compared to non-users, Tinder users were younger and more likely to be men, born in Norway, childless, and non-religious. Tinder users had higher scores on extroversion and agreeableness and lower scores on openness compared to non-users. Further, compared to non-users, Tinder users reported more symptoms of anxiety and were more likely to have hazardous, harmful, or dependent alcohol use and to report use of illegal substances. Compared to non-users, Tinder users had a higher likelihood of having formed a romantic relationship at T2 in the crude model (p < 0.05) and when controlling for demographic (p < 0.05) and mental health (p < 0.05) covariates. However, when controlling for personality, substance use, and all included covariates, the difference in likelihood of romantic relationship formation was no longer significant. In conclusion, the current results suggest that Tinder users have a higher likelihood of forming romantic relationship longitudinally, but that this increased likelihood can be explained by Tinder users' personality and substance use characteristics.

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