Two experience sampling studies examining the variation of self-control capacity and its relationship with core affect in daily life

Perceived stress moderates emotion regulation success in real-world contexts: an ecologically-valid multilevel investigation

BACKGROUND

Emotion regulation plays a crucial role in well-being in everyday life. Effective emotion regulation depends upon adaptively matching a given strategy to a given situation. Recent research has begun to explore these interactions in the context of daily reports of perceived stress, affect, and emotion regulation strategy usage. To further understand these differences in strategy efficacy in an ecologically valid context, we examined responses to real world stressors in a young adult sample.

METHODS

We surveyed a range of emotion regulation strategies, including two forms of cognitive reappraisal (i.e., reinterpretation, which involves cognitively reframing one's emotional responses, and psychological distancing, which involves adopting an objective, impartial perspective). Participants reported strategy usage, momentary perceived stress, and affect in response to multiple ecological momentary assessments over a period of 7 days.

RESULTS

Analyses of links between strategy usage and affect revealed that rumination was significantly negatively associated with more positive affect ratings. Further, a significant interaction between momentary perceived stress and reinterpretation usage was observed on affect, such that reinterpretation was more adaptive during situations perceived as less stressful.

CONCLUSION

These results provide further insight into the importance of situational context in determining the effectiveness of particular emotion regulation strategies.

The 24-hour rhythm in alcohol craving and individual differences in sleep characteristics and alcohol use frequency

BACKGROUND

Evidence implicates sleep/circadian factors in alcohol use, suggesting the existence of a 24-h rhythm in alcohol craving, which may vary by individual differences in sleep factors and alcohol use frequency. This study sought to (1) replicate prior findings of a 24-h rhythm in alcohol craving, and (2) examine whether individual differences in sleep timing, sleep duration, or alcohol use frequency are related to differences in the timing of the peak of the craving rhythm (i.e., the acrophase) or magnitude of fluctuation of the rhythm (i.e., amplitude). Finally, whether such associations varied by sex or racial identity was explored.

METHODS

Two-hundred fifteen adult drinkers (21 to 35 years of age, 72% male, 66% self-identified as White) completed a baseline assessment of alcohol use frequency and then smartphone reports of alcohol craving intensity six times a day across 10 days. Sleep timing was also recorded each morning of the 10-day period. Multilevel cosinor analysis was used to test the presence of a 24-h rhythm and to estimate acrophase and amplitude.

RESULTS

Multilevel cosinor analysis revealed a 24-h rhythm in alcohol craving. Individual differences in sleep timing or sleep duration did not predict rhythm acrophase or amplitude. However, alcohol use frequency moderated this rhythm wherein individuals who used alcohol more frequently in the 30 days prior to beginning the study had higher mean levels of craving and greater rhythm amplitudes (i.e., greater rhythmic fluctuations). Associations did not vary by sex or racial identity.

CONCLUSIONS

Results show that alcohol craving exhibits a systematic rhythm over the course of the 24 h and that the frequency of alcohol use may be relevant to the shape of this rhythm. Consideration of daily rhythms in alcohol craving may further our understanding of the mechanisms that drive alcohol use.

Smartphone keyboard interaction monitoring as an unobtrusive method to approximate rest-activity patterns: Inter-individual and metric-specific variations (Preprint)

BACKGROUND

Sleep is an important determinant of individuals' health and behavior during the wake phase. Novel research methods for field assessments are required to enable the monitoring of sleep over a prolonged period and across a large number of people. The ubiquity of smartphones offers new avenues for detecting rest-activity patterns in everyday life in a noninvasive an inexpensive manner and on a large scale. Recent studies provided evidence for the potential of smartphone interaction monitoring as a novel tracking method to approximate rest-activity patterns based on the timing of smartphone activity and inactivity throughout the 24-hour day. These findings require further replication and more detailed insights into interindividual variations in the associations and deviations with commonly used metrics for monitoring rest-activity patterns in everyday life.

OBJECTIVE

This study aimed to replicate and expand on earlier findings regarding the associations and deviations between smartphone keyboard-derived and self-reported estimates of the timing of the onset of the rest and active periods and the duration of the rest period. Moreover, we aimed to quantify interindividual variations in the associations and time differences between the 2 assessment modalities and to investigate to what extent general sleep quality, chronotype, and trait self-control moderate these associations and deviations.

METHODS

Students were recruited to participate in a 7-day experience sampling study with parallel smartphone keyboard interaction monitoring. Multilevel modeling was used to analyze the data.

RESULTS

In total, 157 students participated in the study, with an overall response rate of 88.9% for the diaries. The results revealed moderate to strong relationships between the keyboard-derived and self-reported estimates, with stronger associations for the timing-related estimates (β ranging from .61 to .78) than for the duration-related estimates (β=.51 and β=.52). The relational strength between the time-related estimates was lower, but did not substantially differ for the duration-related estimates, among students experiencing more disturbances in their general sleep quality. Time differences between the keyboard-derived and self-reported estimates were, on average, small (<0.5 hours); however, large discrepancies were also registered for quite some nights. The time differences between the 2 assessment modalities were larger for both timing-related and rest duration-related estimates among students who reported more disturbances in their general sleep quality. Chronotype and trait self-control did not significantly moderate the associations and deviations between the 2 assessment modalities.

CONCLUSIONS

We replicated the positive potential of smartphone keyboard interaction monitoring for estimating rest-activity patterns among populations of regular smartphone users. Chronotype and trait self-control did not significantly influence the metrics' accuracy, whereas general sleep quality did: the behavioral proxies obtained from smartphone interactions appeared to be less powerful among students who experienced lower general sleep quality. The generalization and underlying process of these findings require further investigation.

Self-controlled responses to COVID-19: Self-control and uncertainty predict responses to the COVID-19 pandemic

Two online studies (Total N = 331) tested the hypothesis that individual differences in self-control and responses to uncertainty would predict adherence to Centers for Disease Control and Prevention (CDC, 2020a) guidelines, reported stockpiling, and intentions to engage in hedonic behavior in response to the COVID-19 pandemic. Trait self-control (b = 0.27, p = .015), desire for self-control (Study 1: b = 0.28, p = .001; Study 2: b = 0.27, p = .005), and cognitive uncertainty (b = 0.73, p < .001) predicted more CDC adherence. State self-control (Study 1: b = -0.15, p = .012; Study 2: b = -0.26, p < .001) predicted less stockpiling, whereas emotional uncertainty (b = 0.56, p < .001) and cognitive uncertainty (b = 0.61, p < .001) predicted more stockpiling. State self-control (b = -0.18, p = .003) predicted less hedonic behavior, whereas desire for self-control (b = 0.42, p < .001) and emotional uncertainty (b = 0.26, p = .018) predicted more hedonic behavior. Study 2 (pre-registered) also found that emotional uncertainty predicted more stockpiling and hedonic behavior for participants low in state self-control (stockpiling: b = -0.31, p < .001; hedonic behavior: b = 0.28, p = .025), but not for participants high in state self-control (stockpiling: b = 0.03, p = .795; hedonic behavior: b = -0.24, p = .066). These findings provide evidence that some forms of self-control and uncertainty influenced compliance with behavioral recommendations during the COVID-19 pandemic.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12144-021-02066-y.

Theory Integration for Lifestyle Behavior Change in the Digital Age: An Adaptive Decision-Making Framework

Despite the growing popularity of digital health interventions, limitations of traditional behavior change theories and a lack of theory integration hinder theory-driven behavior change applications. In this paper, we aim to review theories relevant to lifestyle behavior change from the broader psychology literature and then integrate these theories into a new theoretical framework called adaptive decision-making to address two specific problems. First, our framework represents lifestyle behaviors at two levels-one of individual daily decisions (action level) and one of larger behavioral episodes (reflection level)-to more closely match the temporal characteristics of lifestyle behaviors and their associated digital data. Second, the framework connects decision-making theories and learning theories to explain how behaviors and cognitive constructs dynamically influence each other, making it a suitable scaffold for building computational models. We map common digital intervention techniques onto the behavioral and cognitive processes in the framework and discuss possible contributions of the framework to both theory development and digital intervention design.

Is there a 24-hour rhythm in alcohol craving and does it vary by sleep/circadian timing?

Increasing evidence implicates sleep/circadian factors in alcohol use; however, the role of such factors in alcohol craving has received scant attention. Prior research suggests a 24-hour rhythm in related processes (e.g., reward motivation), but more research directly investigating a rhythm in craving is needed. Moreover, prior evidence is ambiguous whether such a rhythm in alcohol craving may vary by sleep/circadian timing. To examine these possibilities, 36 late adolescents (18-22 years of age; 61% female) with regular alcohol use but without a current alcohol use disorder were recruited to complete smartphone reports of alcohol craving intensity six times a day for two weeks. During these two weeks, participants wore wrist actigraphs and completed two in-lab assessments (on Thursday and Sunday) of dim light melatonin onset (DLMO). Average actigraphically derived midpoint of sleep on weekends and average DLMO were used as indicators of sleep and circadian timing, respectively. Multilevel cosinor analysis revealed a 24-hour rhythm in alcohol craving. Findings across the sleep and circadian timing variables converged to suggest that sleep/circadian timing moderated the 24-hour rhythm in alcohol craving. Specifically, people with later sleep/circadian timing had later timing of peak alcohol craving. These findings add to the growing evidence of potential circadian influences on reward-related phenomena and suggest that greater consideration of sleep and circadian influences on alcohol craving may be useful for understanding alcohol use patterns and advancing related interventions.