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The overall goal of this study is to introduce latent class analysis (LCA) as an alternative approach to latent subgroup analysis. Traditionally, subgroup analysis aims to determine whether individuals respond differently to a treatment based on one or more measured characteristics. LCA provides a way to identify a small set of underlying subgroups characterized by multiple dimensions which could, in turn, be used to examine differential treatment effects. This approach can help to address methodological challenges that arise in subgroup analysis, including a high Type I error rate, low statistical power, and limitations in examining higher-order interactions. An empirical example draws on N  = 1,900 adolescents from the National Longitudinal Survey of Adolescent Health. Six characteristics (household poverty, single-parent status, peer cigarette use, peer alcohol use, neighborhood unemployment, and neighborhood poverty) are used to identify five latent subgroups: Low Risk, Peer Risk, Economic Risk, Household & Peer Risk, and Multi-Contextual Risk. Two approaches for examining differential treatment effects are demonstrated using a simulated outcome: 1) a classify-analyze approach and, 2) a model-based approach based on a reparameterization of the LCA with covariates model. Such approaches can facilitate targeting future intervention resources to subgroups that promise to show the maximum treatment response.

Confounding present in observational data impede community psychologists’ ability to draw causal inferences. This paper describes propensity score methods as a conceptually straightforward approach to drawing causal inferences from observational data. A step-by-step demonstration of three propensity score methods—weighting, matching, and subclassification—is presented in the context of an empirical examination of the causal effect of preschool experiences (Head Start vs. parental care) on reading development in kindergarten. Although the unadjusted population estimate indicated that children with parental care had substantially higher reading scores than children who attended Head Start, all propensity score adjustments reduce the size of this overall causal effect by more than half. The causal effect was also defined and estimated among children who attended Head Start. Results provide no evidence for improved reading if those children had instead received parental care. We carefully define different causal effects and discuss their respective policy implications, summarize advantages and limitations of each propensity score method, and provide SAS and R syntax so that community psychologists may conduct causal inference in their own research.

The COVID-19 pandemic has potential for long-lasting effects on college students' well-being. We examine changes from just before to during the pandemic in indicators of health and well-being and comprehensive profiles of health and well-being, along with links between covariates and profiles during the pandemic. 1,004 students participated in a longitudinal study that began in November 2019. Latent class analysis identified health and well-being profiles at both waves; covariates were included in relation to class membership. Mental health problems increased, whereas substance use, sexual behavior, physical inactivity, and food insecurity decreased. Six well-being classes were identified at each wave. Baseline class membership, sociodemographic characteristics, living situation, ethnicity, coping strategies, and belongingness were associated with profile membership at follow-up. COVID-19 has had significant and differential impacts on today's students; their health and well-being should be considered holistically when understanding and addressing long-term effects of this pandemic.

With technological advances, collection of intensive longitudinal data (ILD), such as ecological momentary assessments, becomes more widespread in prevention science. In ILD studies, researchers are often interested in the effects of time-varying covariates (TVCs) on a time-varying outcome to discover correlates and triggers of target behaviors (e.g., how momentary changes in affect relate to momentary smoking urges). Traditional analytical methods, however, impose important constraints, assuming a constant effect of the TVC on the outcome. In the current paper, we describe a time-varying effect model (TVEM) and its applications to data collected as part of a smoking-cessation study. Differentiating between groups of short-term successful quitters ( N  = 207) and relapsers ( N  = 40), we examine the effects of momentary negative affect and abstinence self-efficacy on the intensity of smoking urges in each subgroup in the 2 weeks following a quit attempt. Successful quitters demonstrated a rapid reduction in smoking urges over time, a gradual decoupling of the association between negative affect and smoking urges, and a consistently strong negative effect of self-efficacy on smoking urges. In comparison, relapsers exhibited a high level of smoking urges throughout the post-quit period, a time-varying and, generally, weak effect of self-efficacy on smoking urges, and a gradual reduction in the strength of the association between negative affect and smoking urges. Implications of these findings are discussed. The TVEM is made available to applied prevention researchers through a SAS macro.

Ecological momentary assessments (EMA) are ideal for capturing the dynamic nature of young adult substance use behavior in daily life and identifying contextual risk factors that signal higher-risk episodes. These methods could provide a signal to trigger real-time intervention delivery. Study compliance and engagement are common barriers to participation but may be improved by personalizing messages. This study compares compliance outcomes between one group of young adults receiving standard (generic) prompts at each assessment and another group that received additional personalization and an updated data dashboard (DD) showing study progress to date at 1 randomly selected prompt per day. The primary objectives are to (1) develop a real-time DD for giving participants personalized updates on their progress in the study and (2) examine its preliminary overall effects on study compliance and experiences. Secondary objectives are to identify person-, day-, and moment-level characteristics associated with study compliance and person-level characteristics associated with perceived usefulness of the DD. This is a protocol for Project ENGAGE, a 2-arm randomized controlled trial. Arm 1 (EMA group) is engaged in a standard EMA protocol, and arm 2 (EMA+DD group) is engaged in the same study but with additional personalization and feedback. Inclusion criteria are (1) previous participation in a recent college student survey about health behavior and mental health who indicated willingness to participate in future research studies and (2) indicated past-month alcohol use; lifetime marijuana, hashish, or Delta-8-tetrahydrocannabinol (THC) use; or some combination of these on that survey. All participants in this study completed a baseline survey; EMA at 11 AM, 2 PM, 5 PM, and 8 PM each day for 21 days; and an exit survey. Participants in arm 2 engaged in a microrandomized trial, receiving a personalized DD at 1 randomly selected prompt per day. Primary outcomes include whether a survey was completed, time to complete a survey, and subjective experiences in the study. Primary analyses will compare groups on overall study compliance and, for arm 2, use marginal models to assess the momentary effect of receiving 1 updated DD per day. Approval was granted by the university's institutional review board on February 8, 2023. Recruitment via direct email occurred on March 30 and April 6, 2023; data collection was completed by April 29, 2023. A total of 91 individuals participated in the study. Results have been accepted for publication in JMIR Formative Research. Results from the evaluation of this study will indicate whether providing (at randomly selected prompts) real-time, personalized feedback on a participant's progress in an EMA study improves study compliance. Overall, this study will inform whether a simple, automated DD presenting study compliance and incentives earned to date may improve young adults' compliance and engagement in intensive longitudinal studies. DERR1-10.2196/57664.

Objective Chronic pain is a critical public health issue affecting approximately 20% of the adult population in the United States. Given the opioid crisis, there has been an urgent focus on non-addictive pain management methods including mindfulness-based stress reduction (MBSR). Prior work has successfully used MBSR for pain management. However, ensuring longitudinal engagement in MBSR practices remains a serious challenge. In this work, we explore the utility of a voice interface to support MBSR home practice. Methods We interviewed 10 mindfulness program facilitators to understand how such a technology might fit in the context of the MBSR class and identify potential usability issues with our prototype. We then used directed content analysis to identify key themes and sub-themes within the interview data. Results Our findings show that facilitators supported the use of the voice interface for MBSR, particularly for individuals with limited motor function. Facilitators also highlighted the unique affordances of voice interfaces, including perceived social presence, to support sustained engagement. Conclusion We demonstrate the acceptability of a voice interface to support home practice for MBSR participants among trained mindfulness facilitators. Based on our findings, we outline design recommendations for technologies aiming to provide longitudinal support for mindfulness-based interventions. Future work should further these efforts toward making non-addictive pain management interventions accessible and efficacious for a wide audience of users.

This study enhances the understanding of resilience in forced migration through a psychological lens, highlighting the importance of identifying resilience determinants and evidence-based interventions. By fostering resilience, policymakers and practitioners can support the well-being and adaptive capacities of forcibly displaced Ukrainians, promoting psychological recovery, social integration, and positive long-term outcomes for affected individuals and communities. To determine the key resilience indicators, survey data were collected in 2023 from n = 502 Ukrainian refugees living in the U.S. (M age = 27 years). Individuals reported various psychological factors and cultural experiences, revealing high resilience and low-stress tolerance among forced Ukrainian migrants in the U.S., along with a strong correlation between their adopted acculturation strategies and their resilience and levels of traumatization.

The landscape of substance use behavior among young adults has observed rapid changes over time. Intensive longitudinal designs are ideal for examining and intervening in substance use behavior in real time but rely on high participant compliance in the study protocol, representing a significant challenge for researchers. This study aimed to evaluate the effect of including a personalized data dashboard (DD) in a text-based survey prompt on study compliance outcomes among college students participating in a 21-day ecological momentary assessment (EMA) study. Participants (N=91; 61/91, 67% female and 84/91, 92% White) were college students who engaged in recent alcohol and cannabis use. Participants were randomized to either complete a 21-day EMA protocol with 4 prompts/d (EMA Group) or complete the same EMA protocol with 1 personalized message and a DD indicating multiple metrics of progress in the study, delivered at 1 randomly selected prompt/d (EMA+DD Group) via a microrandomized design. Study compliance, completion time, self-reported protocol experiences, and qualitative responses were assessed for both groups. Levels of compliance were similar across groups. Participants in the EMA+DD Group had overall faster completion times, with significant week-level differences in weeks 2 and 3 of the study (P=.047 and P=.03, respectively). Although nonsignificant, small-to-medium effect sizes were observed when comparing the groups in terms of compensation level (P=.08; Cohen w=0.19) and perceived burden (P=.09; Cohen d=-0.36). Qualitative findings revealed that EMA+DD participants perceived that seeing their progress facilitated engagement. Within the EMA+DD Group, providing a DD at the moment level did not significantly impact participants' likelihood of completing the EMA or completion time at that particular prompt (all P>.05), with the exception of the first prompt of the day (P=.01 and P<.001). Providing a DD may be useful to increase engagement, particularly for researchers aiming to assess health behaviors shortly after a survey prompt is deployed to participants' mobile devices. RR2-10.2196/57664.

Substance use and use disorders in the United States have had significant and devastating impacts on individuals and communities. This escalating substance use crisis calls for urgent and innovative solutions to effectively detect and provide interventions for individuals in times of need. Recent mobile health (mHealth)-based approaches offer promising new opportunities to address these issues through ubiquitous devices. However, the design rationales, theoretical frameworks, and mechanisms through which users' perspectives and experiences guide the design and deployment of such systems have not been analyzed in any prior systematic reviews. In this paper, we systematically review these approaches and apps for their feasibility, efficacy, and usability. Further, we evaluate whether human-centered research principles and techniques guide the design and development of these systems and examine how the current state-of-the-art systems apply to real-world contexts. In an effort to gauge the applicability of these systems, we also investigate whether these approaches consider the effects of stigma and privacy concerns related to collecting data on substance use. Lastly, we examine persistent challenges in the design and large-scale adoption of substance use intervention apps and draw inspiration from other domains of mHealth to suggest actionable reforms for the design and deployment of these apps. Four databases (PubMed, IEEE Xplore, JMIR, and ACM Digital Library) were searched over a 5-year period (2016-2021) for articles evaluating mHealth approaches for substance use (alcohol use, marijuana use, opioid use, tobacco use, and substance co-use). Articles that will be included describe an mHealth detection or intervention targeting substance use, provide outcomes data, and include a discussion of design techniques and user perspectives. Independent evaluation will be conducted by one author, followed by secondary reviewer(s) who will check and validate themes and data. This is a protocol for a systematic review; therefore, results are not yet available. We are currently in the process of selecting the studies for inclusion in the final analysis. To the best of our knowledge, this is the first systematic review to assess real-world applicability, scalability, and use of human-centered design and evaluation techniques in mHealth approaches targeting substance use. This study is expected to identify gaps and opportunities in current approaches used to develop and assess mHealth technologies for substance use detection and intervention. Further, this review also aims to highlight various design processes and components that result in engaging, usable, and effective systems for substance use, informing and motivating the future development of such systems. DERR1-10.2196/35749.

The current study used latent profile analysis (LPA) to examine the implications of fathers' experiences of work stress for paternal behaviors with infants across multiple dimensions of parenting in a sample of fathers living in nonmetropolitan communities (N = 492). LPA revealed five classes of fathers based on levels of social—affective behaviors and linguistic stimulation measured during two father—infant interactions. Multinomial logistic regression analyses suggested that a less supportive work environment was associated with fathers' membership in multiple lower quality parenting classes. Greater work pressure and a nonstandard work schedule also predicted fathers' membership in the latent parenting classes, although these associations differed depending on the number of hours fathers spent in the workplace.