College Students' Day-to-Day Maladaptive Drinking Responses to Stress Severity and Stressor-Related Guilt and Anger.

BACKGROUND: Stress is a common part of college students' daily lives that may influence their physical activity (PA) and alcohol use. Understanding features of daily stress processes that predict health behaviors could help identify targets for just-in-time interventions. PURPOSE: This study used intensive longitudinal data to examine whether prior day stress processes predict current day PA or alcohol use. METHODS: Participants (N=58, Mage=20.5, 59% women, 70% White) were 18-to-25-year-old students who engaged in binge drinking at least twice monthly and used cannabis or tobacco in the past year. They wore activity (activPAL4) and alcohol (Secure Continuous Remote Alcohol Monitor) monitors for 11 days to assess daily PA (e.g., step counts) and alcohol use (e.g., drinking day), and completed daily surveys about yesterday's stress, including number of stressors (i.e., frequency), stressor intensity (i.e., severity), and frequency of affective states (e.g., guilt). Multilevel models examined prior day stress predicting current day PA or alcohol use. RESULTS: Participants had higher odds of current day drinking (odds ratio=1.21) and greater area under the curve (B=0.08) when they experienced greater than usual stress severity the prior day. Participants had higher current day peak transdermal alcohol concentration (B=0.12) and area under the curve (B=0.11) when they more frequently experienced guilt due to stressors the prior day. CONCLUSIONS: College students' unhealthy response of increasing alcohol use due to stress could adversely impact health outcomes. There is a critical need for interventions addressing students' ability to effectively manage and respond to the stress-inducing, daily demands of student life.

College students experience stress regularly, which may influence their physical activity (PA) and drinking behaviors. Understanding how daily stress predicts health behaviors could be useful for stress-reduction interventions. This study examined whether prior day stress predicted current day PA or alcohol use. Participants (N = 58) were 18- to 25-year-old college students who binge drank at least twice per month and used cannabis or tobacco in the past year. They wore PA and alcohol sensors for 11 days to assess daily PA and alcohol use, and completed daily surveys about yesterday's stress, including the number of stressors experienced (i.e., frequency), stressor intensity (i.e., severity), and mood responses related to stress (anger, anxiety, guilt, sadness). Participants were 21% more likely to drink and drank at higher intensity when they experienced greater than usual stress severity the prior day. Participants had higher current day alcohol use intensity when they more frequently experienced guilt due to stressors the prior day. College students' unhealthy response of increasing alcohol use due to stress could negatively impact short- and long-term health outcomes. There is a critical need for interventions addressing students' ability to effectively manage and respond to the stress-inducing, daily demands of student life.

Leveraging behavioral science and artificial intelligence to support mental health in the workplace: a pilot study.

Introduction: Many American employers seek to alleviate employee mental health symptoms through resources like employee assistance programs (EAPs), yet these programs are often underutilized. This pilot study explores the design of a behavioral science-based email campaign targeting engagement with stress management and mental health resources via an EAP, among employees of a large home builder in the Southeastern US. Methods: Behavioral designers created a behavioral science intervention using a multi-step design approach and evidence based behavioral strategies. For this pilot intervention, employees received either a treatment message [i.e., behavioral science message assembled and delivered via the behavioral reinforcement learning (BRL) agent] or a control message (i.e., a single generic, supportive message with a stock photo) with a call to action to utilize their EAP. Results: A total of 773 employees received emails over the course of 1 year. Engagement was high, with an 80% email open rate. Over 170 employees (22%, 159 treatment and 14 control) clicked the CTA and logged into the EAP site at least once. Discussion: This pilot study suggests that using behavioral science and artificial intelligence can improve employee usage of EAP, specifically with the intention of exploring mental health and stress management resources, compared to benchmark rates of 5% per year.

Responses to a COVID-19 vaccination intervention: Qualitative analysis of 17K unsolicited SMS replies.

The development of effective interventions for COVID-19 vaccination has proven challenging given the unique and evolving determinants of that behavior. A tailored intervention to drive vaccination uptake through machine learning-enabled personalization of behavior change messages unexpectedly yielded a high volume of real-time short message service (SMS) feedback from recipients. A qualitative analysis of those replies contributes to a better understanding of the barriers to COVID-19 vaccination and demographic variations in determinants, supporting design improvements for vaccination interventions. OBJECTIVE: The purpose of this study was to examine unsolicited replies to a text message intervention for COVID-19 vaccination to understand the types of barriers experienced and any relationships between recipient demographics, intervention content, and reply type. METHOD: We categorized SMS replies into 22 overall themes. Interrater agreement was very good (all κpooled > 0.62). Chi-square analyses were used to understand demographic variations in reply types and which messaging types were most related to reply types. RESULTS: In total, 10,948 people receiving intervention text messages sent 17,090 replies. Most frequent reply types were "already vaccinated" (31.1%), attempts to unsubscribe (25.4%), and "will not get vaccinated" (12.7%). Within "already vaccinated" and "will not get vaccinated" replies, significant differences were observed in the demographics of those replying against expected base rates, all p > .001. Of those stating they would not vaccinate, 34% of the replies involved mis-/disinformation, suggesting that a determinant of vaccination involves nonvalidated COVID-19 beliefs. CONCLUSIONS: Insights from unsolicited replies can enhance our ability to identify appropriate intervention techniques to influence COVID-19 vaccination behaviors. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Feasibility of a Reinforcement Learning-Enabled Digital Health Intervention to Promote Mammograms: Retrospective, Single-Arm, Observational Study.

BACKGROUND: Preventive screenings such as mammograms promote health and detect disease. However, mammogram attendance lags clinical guidelines, with roughly one-quarter of women not completing their recommended mammograms. A scalable digital health intervention leveraging behavioral science and reinforcement learning and delivered via email was implemented in a US health system to promote uptake of recommended mammograms among patients who were 1 or more years overdue for the screening (ie, 2 or more years from last mammogram). OBJECTIVE: The aim of this study was to establish the feasibility of a reinforcement learning-enabled mammography digital health intervention delivered via email. The research aims included understanding the intervention's reach and ability to elicit behavioral outcomes of scheduling and attending mammograms, as well as understanding reach and behavioral outcomes for women of different ages, races, educational attainment levels, and household incomes. METHODS: The digital health intervention was implemented in a large Catholic health system in the Midwestern United States and targeted the system's existing patients who had not received a recommended mammogram in 2 or more years. From August 2020 to July 2022, 139,164 eligible women received behavioral science-based email messages assembled and delivered by a reinforcement learning model to encourage clinically recommended mammograms. Target outcome behaviors included scheduling and ultimately attending the mammogram appointment. RESULTS: In total, 139,164 women received at least one intervention email during the study period, and 81.52% engaged with at least one email. Deliverability of emails exceeded 98%. Among message recipients, 24.99% scheduled mammograms and 22.02% attended mammograms (88.08% attendance rate among women who scheduled appointments). Results indicate no practical differences in the frequency at which people engage with the intervention or take action following a message based on their age, race, educational attainment, or household income, suggesting the intervention may equitably drive mammography across diverse populations. CONCLUSIONS: The reinforcement learning-enabled email intervention is feasible to implement in a health system to engage patients who are overdue for their mammograms to schedule and attend a recommended screening. In this feasibility study, the intervention was associated with scheduling and attending mammograms for patients who were significantly overdue for recommended screening. Moreover, the intervention showed proportionate reach across demographic subpopulations. This suggests that the intervention may be effective at engaging patients of many different backgrounds who are overdue for screening. Future research will establish the effectiveness of this type of intervention compared to typical health system outreach to patients who have not had recommended screenings as well as identify ways to enhance its reach and impact.

Personalized Digital Health Communications to Increase COVID-19 Vaccination in Underserved Populations: A Double Diamond Approach to Behavioral Design.

The COVID-19 pandemic exacerbated pre-existing health disparities. People of historically underserved communities, including racial and ethnic minority groups and people with lower incomes and educational attainments, experienced disproportionate premature mortality, access to healthcare, and vaccination acceptance and adoption. At the same time, the pandemic increased reliance on digital devices, offering a unique opportunity to leverage digital communication channels to address health inequities, particularly related to COVID-19 vaccination. We offer a real-world, systematic approach to designing personalized behavior change email and text messaging interventions that address individual barriers with evidence-based behavioral science inclusive of underserved populations. Integrating design processes such as the Double Diamond model with evidence-based behavioral science intervention development offers a unique opportunity to create equitable interventions. Further, leveraging behavior change artificial intelligence (AI) capabilities allows for both personalizing and automating that personalization to address barriers to COVID-19 vaccination at scale. The result is an intervention whose broad component library meets the needs of a diverse population and whose technology can deliver the right components for each individual.

Daily Physical Activity, Sedentary Behavior and Alcohol Use in At-Risk College Students.

BACKGROUND: The college years present an opportunity to establish health behavior patterns that can track across adulthood. Health behaviors tend to cluster synergistically however, physical activity and alcohol have shown a positive association. PURPOSE: This study applied a multi-method approach to estimate between- and within-person associations between daily physical activity, sedentary behavior and alcohol use among polysubstance-using college students. METHODS: Participants were screened for recent binge drinking and either tobacco or cannabis use. They wore an activPAL4 activity monitor and a Secure Continuous Remote Alcohol Monitor continuously in the field for 11 days, and completed daily online questionnaires at the beginning of each day to report previous day physical activity, sedentary behavior, and alcohol consumption. RESULTS: Participants (N = 58, Mage = 20.5 years, 59% women, 69% White) reported meeting national aerobic physical activity guidelines (75%) and drinking 2-4 times in the past month (72%). On days when participants reported an hour more than usual of daily sedentary behavior, they reported drinking for less time than usual (γ = -.06). On days when participants took 1,000 more steps than usual, the longest episode of continuous transdermal alcohol detection was shorter (γ = -.03). CONCLUSIONS: Daily physical activity and sedentary behavior were negatively associated with time-based measures of alcohol use with the lowest risk on days characterized by both activity and sedentary behavior. Intensive longitudinal monitoring of time-based processes can provide new insights into risk in multiple behavior change and should be prioritized for future work.

Seasons, weather, and device-measured movement behaviors: a scoping review from 2006 to 2020.

BACKGROUND: This scoping review summarized research on (a) seasonal differences in physical activity and sedentary behavior, and (b) specific weather indices associated with those behaviors. METHODS: PubMed, CINAHL, and SPORTDiscus were searched to identify relevant studies. After identifying and screening 1459 articles, data were extracted from 110 articles with 118,189 participants from 30 countries (almost exclusively high-income countries) on five continents. RESULTS: Both physical activity volume and moderate-to-vigorous physical activity (MVPA) were greater in summer than winter. Sedentary behavior was greater in winter than either spring or summer, and insufficient evidence existed to draw conclusions about seasonal differences in light physical activity. Physical activity volume and MVPA duration were positively associated with both the photoperiod and temperature, and negatively associated with precipitation. Sedentary behavior was negatively associated with photoperiod and positively associated with precipitation. Insufficient evidence existed to draw conclusions about light physical activity and specific weather indices. Many weather indices have been neglected in this literature (e.g., air quality, barometric pressure, cloud coverage, humidity, snow, visibility, windchill). CONCLUSIONS: The natural environment can influence health by facilitating or inhibiting physical activity. Behavioral interventions should be sensitive to potential weather impacts. Extreme weather conditions brought about by climate change may compromise health-enhancing physical activity in the short term and, over longer periods of time, stimulate human migration in search of more suitable environmental niches.

Just-in-time adaptive intervention to promote fluid consumption in patients with kidney stones.

OBJECTIVE: Kidney stones are painful and costly. Prevention guidelines emphasize a simple behavior change: increasing fluid intake and urine output. Unfortunately, adherence to those prevention guidelines is limited, and patients report forgetting or not being thirsty enough. This study evaluated the acceptability of using semiautomated tracking of fluid consumption to trigger just-in-time reminders to drink and increase the experienced automaticity of fluid intake. METHOD: In a single-group trial, participants with a history of kidney stones (n = 31) used the sipIT digital tools (H2OPal connected water bottle, H2OPal mobile app for self-tracking, Fitbit smartwatch app for gesture detection) for 3 months. RESULTS: The semiautomated monitoring system detected 46,654 drinking events. From baseline to 1-month follow-up, the experienced automaticity of fluid intake increased significantly (d = 0.50) and remained elevated at 3-month follow-up (d = 0.64). A major barrier to adherence (lack of thirst) decreased from baseline to follow-ups. Retention rates and participant feedback indicated that this digital tool was acceptable to patients. CONCLUSION: Semiautomated tracking of fluid consumption can be used to trigger just-in-time reminders. Based on this demonstration, the sipIT tools are ready for testing in a rigorous Phase II trial to evaluate efficacy for increasing fluid consumption and urine output as recommended for preventing the recurrence of kidney stones. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

A systematic review of physical activity, sedentary behavior, and substance use in adolescents and emerging adults.

The transition from adolescence into emerging adulthood is marked by changes in both physical activity and substance use. This systematic review characterized associations between movement behaviors (physical activity, sedentary behavior) and frequently used substances (alcohol, cannabis) among adolescents and emerging adults to inform lifestyle interventions that target multiple behavior change outcomes. This systematic review was guided by PRISMA. Electronic databases of PubMed, PsycINFO, and Web of Science were searched from inception through June 25, 2019. The search was designed to identify empirical studies reporting an association between physical activity or sedentary behavior and alcohol or cannabis, with search criteria determining eligibility based on several sampling characteristics (e.g., participants under 25 years of age). After identifying and screening 5,610 studies, data were extracted from 97 studies. Physical activity was positively associated with alcohol use among emerging adults, but the literature was mixed among adolescents. Sedentary behavior was positively associated with alcohol and cannabis use among adolescents, but evidence was limited among emerging adults. Self-report measures were used in all but one study to assess these behaviors. Physical activity is linked to greater alcohol use among emerging adults. Whereas existing studies demonstrate that sedentary behavior might serve as a risk marker for alcohol and cannabis use among adolescents, additional primary research is needed to explore these associations in emerging adults. Future work should also use device-based measures to account for timing of and contextual features surrounding activity and substance use in these populations.

Incorporating Behavior Change Strategies Into an Exercise Trial to Improve Physical Activity Maintenance Among Adults at High Risk for Type II Diabetes.

This study examined the feasibility and effects of a 1-hr physical activity (PA) behavior change (PABC) discussion session on PA, 12 weeks after completing an exercise trial. Adults at high risk of Type II diabetes were randomized to the PABC or a control group. PA was self-reported using the International Physical Activity Questionnaire. Chi-square tests compared the proportion of participants classified as moderately active or greater at the 12-week follow-up. Participants (N = 50) were M = 61.8 ± 5.5 years old and mostly female (80%). All participants completed the PABC discussion session, and compliance with the International Physical Activity Questionnaire at 12-week follow-up was 78%. Barrier self-efficacy increased immediately following the PABC (MΔ0.5 ± 0.9; t(22) = -2.45, p = .023). At 12-week follow-up, 88% in the PABC were moderately active or greater, compared with 50% in the control (p = .015). Incorporating a PABC discussion session as part of an exercise efficacy trial was feasible and may help improve PA maintenance.