Religiousness has been shown to have an inverse relationship with at least some types of addiction. The present study examined whether intrinsic religiousness predicts substance addiction in a sample of participants that included mostly undergraduate students from the Appalachian region, as well as some participants surveyed with the use of social media advertisements. Intrinsic religiousness has been defined as internalizing the tenets of one’s faith. Participants self-reported their religiousness using the Religious Surrender and Attendance Scale – 3 (RSAS-3), which has been shown to measure intrinsic religiousness. Substance use was measured by the TCU Drug Screen V (TCUDS). Religiousness, as measured by the RSAS-3, predicted lower levels of substance use addiction as measured by the TCUDS both continuously and dichotomized: X2 (1, N=517) =8.296, p=.004. The odds ratio for the model was 3.724 95% CI [1.305, 10.625] meaning that the odds of being addicted to a substance was 3.724 times more likely for someone who did not meet the threshold for being high in religious commitment than for someone who did. The present study extends findings regarding religiousness and addiction but further research should be done to analyze different theological traditions and their relationship with health outcomes.

Introduction: Over the last decades, our understanding of the cognitive, motivational, and neural processes involved in addictive behavior has increased enormously. A plethora of laboratory-based and cross-sectional studies has linked cognitive-behavioral measures to between-subject differences in drinking behavior. However, such laboratory-based studies inevitably suffer from small sample sizes and the inability to link temporal fluctuations in task measures to fluctuations in real-life substance use. To overcome these problems, several existing behavioral tasks have been transferred to smartphones to allow studying cognition in the field. Method: In this narrative review, we first summarize studies that used existing behavioral tasks in the laboratory and self-reports of substance use with ecological momentary assessment (EMA) in the field. Next, we review studies on psychometric properties of smartphone-based behavioral tasks. Finally, we review studies that used both smartphone-based tasks and self-reports with EMA in the field. Results: Overall, studies were scarce and heterogenous both in tasks and in study outcomes. Nevertheless, existing findings are promising and point toward several methodological recommendations: concerning psychometrics, studies show that – although more systematic studies are necessary – task validity and reliability can be improved, for example, by analyzing several measurement sessions at once rather than analyzing sessions separately. Studies that use tasks in the field, moreover, show that power can be improved by choosing sampling schemes that combine time-based with event-based sampling, rather than relying on time-based sampling alone. Increasing sampling frequency can further increase power. However, as this also increases the burden to participants, more research is necessary to determine the ideal sampling frequency for each task. Conclusion: Although more research is necessary to systematically study both the psychometrics of smartphone-based tasks and the frequency at which task measures fluctuate, existing studies are promising and reveal important methodological recommendations useful for researchers interested in implementing behavioral tasks in EMA studies.