This scoping review summarized research on (a) seasonal differences in physical activity and sedentary behavior, and (b) specific weather indices associated with those behaviors.
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.
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).
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.
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.
El desarrollo de intervenciones efectivas para la vacunación contra el COVID-19 ha demostrado ser un desafío debido a los determinantes únicos y en evolución de ese comportamiento. Una intervención personalizada para impulsar la aceptación de la vacunación a través de la personalización de mensajes de cambio de comportamiento habilitada por aprendizaje automático produjo inesperadamente un gran volumen de comentarios por SMS (mensajería de texto) en tiempo real de los destinatarios. Un análisis cualitativo de esas respuestas contribuye a un mejor entendimiento de las barreras para la vacunación contra el COVID-19 y las variaciones demográficas en los determinantes, lo que respalda las mejoras en el diseño de las intervenciones de vacunación. Objetivo: El propósito de este estudio fue examinar las respuestas no solicitadas a una intervención de mensaje de texto para la vacunación contra el COVID-19 para comprender los tipos de barreras experimentadas y cualquier relación entre la demografía del destinatario, el contenido de la intervención y el tipo de respuesta. Método: Clasificamos las respuestas de SMS en 22 temas generales. El acuerdo entre evaluadores fue muy bueno (todos los κ agrupados > 0.62). Se utilizaron análisis de chi-cuadrado para comprender las variaciones demográficas en los tipos de respuesta y qué tipos de mensajes estaban más relacionados con los tipos de respuesta. Resultados: 10,948 personas que recibieron mensajes de texto de intervención enviaron 17,090 respuestas. Los tipos de respuesta más frecuentes fueron "ya vacunado" (31.1%), intentos de darse de baja (25.4%) y "no me voy a vacunar" (12.7%). Dentro de las respuestas "ya vacunado" y "no me voy a vacunar," se observaron diferencias significativas en la demografía de los que respondieron frente a las tasas base esperadas, todas p > .001. De los que afirmaron que no se vacunarían, el 34% de las respuestas incluían información errónea o desinformación, lo que sugiere que un factor determinante de la vacunación son las creencias sobre el COVID-19 no validadas. Conclusiones: Las perspectivas de las respuestas no solicitadas pueden mejorar nuestra capacidad para identificar técnicas de intervención adecuadas para influir en los comportamientos de vacunación contra el COVID-19.
Public Significance Statement
Understanding behavioral determinants of COVID-19 vaccination remains critical despite the success of COVID-19 vaccination experienced to date. In total, 10,948 people sent 17,090 unsolicited SMS replies to a machine-learning-enabled digital health intervention promoting COVID-19 vaccination in a southern state. Insights from the spontaneous SMS replies provide a contemporaneous understanding of the behavioral determinants to COVID-19 vaccination experienced by a diverse group of people and enhance interventionists' ability to identify applicable behavior change techniques to address changing behavioral determinants to, and to promote, COVID-19 vaccination behaviors.
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.
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.
Abstract
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.
Heavy drinking college students tended to drink more heavily following days when they experienced more stress or more intense feelings of guilt due to stress than usual.
Lay Summary
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.
Abstract
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.
When college students reported more sitting time or took more steps than usual during the day, they engaged in less alcohol use for that day.
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.
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).
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.
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.
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.
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.
N-Methyl-d-aspartate type glutamate receptors (NMDARs) are key mediators of synaptic activity-regulated gene transcription in neurons, both during development and in the adult brain. Developmental ...differences in the glutamate receptor ionotropic NMDA 2 (GluN2) subunit composition of NMDARs determines whether they activate the transcription factor cAMP-responsive element-binding protein 1 (CREB). However, whether the developmentally regulated GluN3A subunit also modulates NMDAR-induced transcription is unknown. Here, using an array of techniques, including quantitative real-time PCR, immunostaining, reporter gene assays, RNA-Seq, and two-photon glutamate uncaging with calcium imaging, we show that knocking down GluN3A in rat hippocampal neurons promotes the inducible transcription of a subset of NMDAR-sensitive genes. We found that this enhancement is mediated by the accumulation of phosphorylated p38 mitogen-activated protein kinase in the nucleus, which drives the activation of the transcription factor myocyte enhancer factor 2C (MEF2C) and promotes the transcription of a subset of synaptic activity-induced genes, including brain-derived neurotrophic factor (Bdnf) and activity-regulated cytoskeleton-associated protein (Arc). Our evidence that GluN3A regulates MEF2C-dependent transcription reveals a novel mechanism by which NMDAR subunit composition confers specificity to the program of synaptic activity-regulated gene transcription in developing neurons.
The National Cancer Institute's (NCI) Health Information National Trends Survey (HINTS) is a nationally representative survey of U.S. adults in which 12-17% of respondents report a cancer history. To ...increase representation from adult cancer survivors, in 2021, NCI sampled survivors from three Surveillance, Epidemiology, and End Results (SEER) program cancer registries: Iowa, New Mexico, and the Greater Bay Area. Sampling frames were stratified by time since diagnosis and race/ethnicity, with nonmalignant tumors and non-melanoma skin cancers excluded. Participants completed a self-administered postal questionnaire. The overall response rate for HINTS-SEER (N = 1,234) was 12.6%; a non-response bias analysis indicated few demographic differences between respondents and the pool of sampled patients in each registry. Most of the sample was 10+ years since diagnosis (n = 722; 60.2%); 392 respondents were 5 to < 10 years since diagnosis (29.6%); and 120 were < 5 years since diagnosis (10.2%). Common cancers included male reproductive (n = 304; 24.6%), female breast (n = 284; 23.0%), melanoma (n = 119; 9.6%), and gastrointestinal (n = 106; 8.6%). Tumors were mostly localized (67.8%; n = 833), with 22.4% (n = 282) regional, 6.2% (n = 72) distant, and 3.7% (n = 47) unknown. HINTS-SEER data are available by request and may be used for secondary analyses to examine a range of social, behavioral, and healthcare outcomes among cancer survivors.
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