Objective: Investigating the role of combat exposure on behavioral outcomes has been limited due to ethical and logistical constraints. Method: Using a large data set from UK BioBank of U.K. citizens (n = 157,161), we created hypothetical randomized experiments, with treatment conditions for combat exposure or no combat exposure matched for relevant covariates and compared differences in combat exposure groups on a broad range of alcohol-related and subjective well-being outcomes. Additionally, using a randomization-based approach, we calculated 95% Fisherian intervals for constant treatment effects consistent with the matched data and the hypothetical combat exposure intervention. Results: Results suggest that combat exposure plays a role in several negative outcomes related to alcohol behavior and subjective well-being, such as increased typical daily alcohol consumption (estimated average causal effect [ACE] = 0.0545, Fisher p-value = .0119) and less general health happiness (estimated ACE = -0.1077, Fisher p-value < 1/100,000). Conclusions: This study expands our current understanding of the role of combat exposure on many alcohol and subjective well-being-related measures. We also show that the Rubin Causal Model provides a rigorous and valid approach to better understand myriad other issues in psychological science.

ObjectivesSleep disruption is prevalent among children placed in foster care, elevating risk for a range of deleterious outcomes. Theoretically, achieving permanency via adoption may have a positive influence on children's sleep via the presence of various factors, but little is known about the sleep health of children adopted from foster care, including predictors and moderators of sleep health.MethodThe current study included 226 parents who adopted a child from foster care in the U.S. (aged 4-11 years) within the past two years and a propensity score matched sample of 379 caregivers of children currently in foster care. Both samples completed online questionnaires about their child's sleep, physical, and mental health.ResultsComparatively, children in foster care experienced more nightmares, night terrors, moving to someone else's' bed during the night, and worse overall sleep quality, whereas adopted children were reported to experience significantly more nighttime awakenings. In the adopted sample, a greater number of prior foster placements unexpectedly predicted lower total sleep disturbance scores, but this relationship was moderated by parent-child interactions around sleep. In general, greater parental involvement in children's sleep was associated with lower levels of child sleep disturbance.ConclusionsFindings suggest that while specific sleep problems might remit after children in foster care achieve permanence, nighttime sleep fragmentation often persists. Parent-child interactions surrounding sleep may be pivotal in improving sleep health in this population.

Across three online studies, we examined the relationship between the Fear of Missing Out (FoMO) and moral cognition and behavior. Study 1 (N = 283) examined whether FoMO influenced moral awareness, judgments, and recalled and predicted behavior of first-person moral violations in either higher or lower social settings. Study 2 (N = 821) examined these relationships in third-person judgments with varying agent identities in relation to the participant (agent = stranger, friend, or someone disliked). Study 3 (N = 604) examined the influence of recalling activities either engaged in or missed out on these relationships. Using the Rubin Causal Model, we created hypothetical randomized experiments from our real-world randomized experimental data with treatment conditions for lower or higher FoMO (median split), matched for relevant covariates, and compared differences in FoMO groups on moral awareness, judgments, and several other behavioral outcomes. Using a randomization-based approach, we examined these relationships with Fisher Tests and computed 95% Fisherian intervals for constant treatment effects consistent with the matched data and the hypothetical FoMO intervention. All three studies provide evidence that FoMO is robustly related to giving less severe judgments of moral violations. Moreover, those with higher FoMO were found to report a greater likelihood of committing moral violations in the past, knowing people who have committed moral violations in the past, being more likely to commit them in the future, and knowing people who are likely to commit moral violations in the future.

Motivation for physical activity and sedentary behaviors (e.g., desires, urges, wants, cravings) varies from moment to moment. According to the WANT model, these motivation states may be affectively-charged (e.g., felt as tension), particularly after periods of maximal exercise or extended rest. The purpose of this study was to examine postulates of the WANT model utilizing a mixed-methods approach. We hypothesized that: (1) qualitative evidence would emerge from interviews to support this model, and (2) motivation states would quantitatively change over the course of an interview period. Seventeen undergraduate students (mean age = 18.6y, 13 women) engaged in focus groups where 12 structured questions were presented. Participants completed the "right now" version of the CRAVE scale before and after interviews. Qualitative data were analyzed with content analysis. A total of 410 unique lower-order themes were classified and grouped into 43 higher order themes (HOTs). From HOTs, six super higher order themes (SHOTs) were designated: (1) wants and aversions, (2) change and stability, (3) autonomy and automaticity, (4) objectives and impulses, (5) restraining and propelling forces, and (6) stress and boredom. Participants stated that they experienced desires to move and rest, including during the interview, but these states changed rapidly and varied both randomly as well as systematically across periods of minutes to months. Some also described a total absence of desire or even aversion to move and rest. Of note, strong urges and cravings for movement, typically from conditions of deprivation (e.g., sudden withdrawal from exercise training) were associated with physical and mental manifestations, such as fidgeting and feeling restless. Urges were often consummated with behavior (e.g., exercise sessions, naps), which commonly resulted in satiation and subsequent drop in desire. Importantly, stress was frequently described as both an inhibitor and instigator of motivation states. CRAVE-Move increased pre-to-post interviews (p < .01). CRAVE-Rest demonstrated a trend to decline (p = .057). Overall, qualitative and quantitative data largely corroborated postulates of the WANT model, demonstrating that people experience wants and cravings to move and rest, and that these states appear to fluctuate significantly, especially in the context of stress, boredom, satiety, and deprivation.

IntroductionMotivation to be physically active and sedentary is a transient state that varies in response to previous behavior. It is not known: (a) if motivational states vary from morning to evening, (b) if they are related to feeling states (arousal/hedonic tone), and (c) whether they predict current behavior and intentions. The primary purpose of this study was to determine if motivation states vary across the day and in what pattern. Thirty adults from the United States were recruited from Amazon MTurk.MethodsParticipants completed 6 identical online surveys each day for 8 days beginning after waking and every 2–3 h thereafter until bedtime. Participants completed: (a) the CRAVE scale (Right now version) to measure motivation states for Move and Rest, (b) Feeling Scale, (c) Felt Arousal Scale, and (d) surveys about current movement behavior (e.g., currently sitting, standing, laying down) and intentions for exercise and sleep. Of these, 21 participants (mean age 37.7 y; 52.4% female) had complete and valid data.ResultsVisual inspection of data determined that: a) motivation states varied widely across the day, and b) most participants had a single wave cycle each day. Hierarchical linear modelling revealed that there were significant linear and quadratic time trends for both Move and Rest. Move peaked near 1500 h when Rest was at its nadir. Cosinor analysis determined that the functional waveform was circadian for Move for 81% of participants and 62% for Rest. Pleasure/displeasure and arousal independently predicted motivation states (all p's < .001), but arousal had an association twice as large. Eating, exercise and sleep behaviors, especially those over 2 h before assessment, predicted current motivation states. Move-motivation predicted current body position (e.g., laying down, sitting, walking) and intentions for exercise and sleep more consistently than rest, with the strongest prediction of behaviors planned for the next 30 min.DiscussionWhile these data must be replicated with a larger sample, results suggest that motivation states to be active or sedentary have a circadian waveform for most people and influence future behavioral intentions. These novel results highlight the need to rethink the traditional approaches typically utilized to increase physical activity levels.

The present study examines the benefits of an in-person intergenerational contact program called SAGE (Successful Aging and Inter-Generational Experiences). The SAGE Program pairs older adults (M age 85 years) and younger adults (M age 23 years) for 2 to 3-hour weekly meetings over a 7-week period, where participants can share memories, skills, and values, and foster new perspectives and friendships. We expected the SAGE Program to benefit both older and younger participants with respect to identity processes, subjective well-being, positive mood, and wisdom while reducing ageist beliefs compared to old and young participants serving as their matched controls. Overall, participants in the SAGE Program reported greater identity synthesis,subjective well-being, and positive mood. Exploratory analyses suggested that identity synthesis is a likely mediator of that effect. The SAGE Program did not reduce ageist beliefs, but age differences in ageism were found. We address additional results,limitations, and future research directions.

This paper reports a two-part study examining the relationship between fear of missing out (FoMO) and maladaptive behaviors in college students. This project used a cross-sectional study to examine whether college student FoMO predicts maladaptive behaviors across a range of domains (e.g., alcohol and drug use, academic misconduct, illegal behavior). Participants (N = 472) completed hard copy questionnaire packets assessing trait FoMO levels and questions pertaining to unethical and illegal behavior while in college. Part 1 utilized traditional statistical analyses (i.e., hierarchical regression modeling) to identify any relationships between FoMO, demographic variables (socioeconomic status, living situation, and gender) and the behavioral outcomes of interest. Part 2 looked to quantify the predictive power of FoMO, and demographic variables used in Part 1 through the convergent approach of supervised machine learning. Results from Part 1 indicate that college student FoMO is indeed related to many diverse maladaptive behaviors spanning the legal and illegal spectrum. Part 2, using various techniques such as recursive feature elimination (RFE) and principal component analysis (PCA) and models such as logistic regression, random forest, and Support Vector Machine (SVM), showcased the predictive power of implementing machine learning. Class membership for these behaviors (offender vs. non-offender) was predicted at rates well above baseline (e.g., 50% at baseline vs 87% accuracy for academic misconduct with just three input variables). This study demonstrated FoMO’s relationships with these behaviors as well as how machine learning can provide additional predictive insights that would not be possible through inferential statistical modeling approaches typically employed in psychology, and more broadly, the social sciences. Research in the social sciences stands to gain from regularly utilizing the more traditional statistical approaches in tandem with machine learning.

Motivation for bodily movement, physical activity and exercise varies from moment to moment. These motivation states may be “affectively-charged,” ranging from instances of lower tension (e.g., desires, wants) to higher tension (e.g., cravings and urges). Currently, it is not known how often these states have been investigated in clinical populations (e.g., eating disorders, exercise dependence/addiction, Restless Legs Syndrome, diabetes, obesity) vs. healthy populations (e.g., in studies of motor control; groove in music psychology). The objective of this scoping review protocol is to quantify the literature on motivation states, to determine what topical areas are represented in investigations of clinical and healthy populations, and to discover pertinent details, such as instrumentation, terminology, theories, and conceptual models, correlates and mechanisms of action. Iterative searches of scholarly databases will take place to determine which combination of search terms (e.g., “motivation states” and “physical activity”; “desire to be physically active,” etc.) captures the greatest number of relevant results. Studies will be included if motivation states for movement (e.g., desires, urges) are specifically measured or addressed. Studies will be excluded if referring to motivation as a trait. A charting data form was developed to scan all relevant documents for later data extraction. The primary outcome is simply the extent of the literature on the topic. Results will be stratified by population/condition. This scoping review will unify a diverse literature, which may result in the creation of unique models or paradigms that can be utilized to better understand motivation for bodily movement and exercise.

Approximately 60% of college students report sleep disturbances. Sleep disturbances, such as insomnia, negatively influence physical energy, cognitive resources, and affective states that might inhibit executive functioning. To better delineate the variables that alter the college student insomnia and executive functioning relationship we examined sleepiness, sleep debt, and attention-deficit/hyperactivity disorder (ADHD) symptomatology. We expected insomnia to predict executive dysfunction, with a stronger relationship observed at higher levels of the focal moderator (i.e., sleepiness, sleep debt, or ADHD symptoms). Undergraduate participants (n = 472) completed a cross-sectional survey assessing insomnia, state sleepiness, sleep debt, ADHD symptomatology (inattention, hyperactivity, and impulsivity), and executive dysfunction. Hierarchical linear regressions showed that poor sleep had a negative influence on executive function when college students also had high levels of impulsivity, state sleepiness, or sleep debt. These results partially support our expectations and further the academic sleep-related literature while providing insight for counselors, academic advisors, or other professionals working with college student populations.

Union members are better paid than their nonunion counterparts (Hirsch, 2004) and receive better fringe benefits, such as employer-provided health insurance and pensions (Buchmueller et al., 2004). Unions improve job safety, reduce occupational stress, and help create more cohesive organizational cultures (Baugher & Timmons Roberts, 2004; Hagedorn et al., 2016). However, to properly function and better workers’ lives, unions rely heavily on voluntary, unpaid involvement from members. Such involvement can take the form of leadership roles, participation in communal union activities, or even simply informal discussion of the union with others (Fiorito et al., 2010; Monnot et al., 2011; Parks et al., 1995; Tetrick et al., 2007). Unions failing to secure members’ voluntary engagement in often mundane, but necessary, activities will likely also fail to effectively launch their members into political activism (Yu, 2014). Thus, much research has attempted to understand the antecedents of union involvement (e.g., Bamberger et al., 1999; Fiorito et al., 2014). Most models of union involvement, such as the exchange-covenant model (Snape & Redman, 2004), hold that union members most reliably ABSTRACT. The success of organized labor is aided by worker involvement in voluntary, union-related activities such as leadership roles and the socialization of new members. Established models of the attitudinal antecedents of this involvement (e.g., the exchange-covenant model; Snape & Redman, 2004) hold that positive attitudes toward unions in general are involvement’s primary predictor, with effectiveness of one's own union being of secondary importance. However, these findings are gathered largely from high-socioeconomic status (SES) samples (e.g., university professors; see, e.g., Fiorito et al., 2014), and even more diversely sampled studies do not test for the influence of SES. Therefore, using a socioeconomically and occupationally diverse sample (n = 94), we examined whether established union involvement models apply equally to lowand high-SES union members. We found that, in high-SES individuals, general attitudes about unions positively predicted self-reports of past involvement, b = 0.70, t(79) = 2.57, p = .01, CI95%[.16, 2.15], and future involvement interest, b = 0.77, t(79) = 2.45, p = .02, CI95%[.15, 1.40]; results were null for average(past involvement p = .81, future p = .83) and low-SES workers (past involvement p = .10, future p = .24). Our findings indeed suggest that the exchange-covenant model is only applicable to high-SES union workers. General union attitudes are ostensibly irrelevant to overall involvement from their low-SES counterparts, possibly due to greater influence of social and material resource exchange on low-SES union members considering becoming involved in union activities. Future union involvement research should account for the influence of socioeconomic factors.

The popular business media argues that the "fear of missing out" (FoMO) on work-related opportunities harms employees' health and performance. Yet, these claims rely on the study of FoMO in college students in non-work contexts. Therefore, we explored workplace FoMO among employees across three studies. We first developed a measure and provided validation evidence for workplace FoMO among diverse employees (N = 324; Study 1) and MBA students (N = 223; Study 2). Using a third large employee sample (N = 300; Study 3), we tested whether workplace FoMO predicted health (i.e., work burnout and work well-being) and motivational outcomes (i.e., message-checking behaviors and work engagement). We also examined whether family-supportive organizational perceptions (FSOP) moderated these relationships. Results indicated that workplace FoMO is a distinct construct from other measures, including general FoMO. Workplace FoMO also predicted work burnout and message checking behavior, but not work well-being. Lower levels of FSOP strengthened the positive relationship between workplace FoMO and message checking behavior, but also produced a positive relationship between workplace FoMO and work well-being. Overall, FoMO appears to be relevant to the work context and predicts both employee well-being and behavior outcomes.