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Mechanisms of behavior change are the processes through which interventions are hypothesized to cause changes in outcomes. Latent growth curve mediation models (LGCMM) are recommended for investigating the mechanisms of behavior change because LGCMM models establish temporal precedence of change from the mediator to the outcome variable. The Correlated Augmented Mediation Sensitivity Analyses (CAMSA) App implements sensitivity analysis for LGCMM models to evaluate if a mediating path (mechanism) is robust to potential confounding variables. The CAMSA approach is described and applied to simulated data, and data from a research study exploring a mechanism of change in the treatment of substance use disorder.

Background Few intervention studies have integrated cultural tailoring, parenting, behavioral, and motivational strategies to address African American adolescent weight loss. Purpose The Families Improving Together (FIT) for Weight Loss trial was a randomized group cohort study testing the efficacy of a cultural tailoring, positive parenting, and motivational intervention for weight loss in overweight African American adolescents (N = 241 adolescent/caregiver dyads). Methods The trial tested an 8-week face-to-face group motivational plus family weight loss program (M + FWL) compared with a comprehensive health education control program. Participants were then rerandomized to an 8-week tailored or control online program to test the added effects of the online intervention on reducing body mass index and improving physical activity (moderate-to-vigorous physical activity [MVPA], light physical activity [LPA]), and diet. Results There were no significant intervention effects for body mass index or diet. There was a significant effect of the group M + FWL intervention on parent LPA at 16 weeks (B = 33.017, SE = 13.115, p = .012). Parents in the group M + FWL intervention showed an increase in LPA, whereas parents in the comprehensive health education group showed a decrease in LPA. Secondary analyses using complier average causal effects showed a significant intervention effect at 16 weeks for parents on MVPA and a similar trend for adolescents. Conclusions While the intervention showed some impact on physical activity, additional strategies are needed to impact weight loss among overweight African American adolescents.

BACKGROUND Effective COVID-19 vaccines have been available since early 2021 yet many Americans refuse or delayed uptake. As of mid-2022, still around 30% of US adults remain unvaccinated against COVID-19. The majority (81%) of these unvaccinated adults say they will “definitely not” be getting the COVID-19 vaccine. Understanding determinants of COVID-19 vaccine uptake is critical to reducing death and illness from the virus, as well as to inform future vaccine efforts, such as the more recent bivalent (omicron) booster. OBJECTIVE This study aimed to expand our understanding of psychosocial determinants of COVID-19 vaccine uptake. We focus on both COVID-19-specific factors, such as COVID-19 conspiracy beliefs, as well as more global personality attributes such as dogmatism, reactance, gender roles, political beliefs, and religiosity. METHODS We conducted an online survey in mid-2021 of a representative sample of 1376 adults measuring both COVID-19-specific beliefs and attitudes, as well as global personality attributes. COVID-19 vaccination status is reported in 3 levels: Vaccinated; Unvaccinated - May get it; Unvaccinated - Hard no. RESULTS Our analyses focused on the correlation of COVID-19 vaccination status with 10 psychosocial attributes: COVID-19-specific conspiracy theory beliefs; COVID-19 vaccine misinformation; COVID-19-related Rapture beliefs; general anti-vaccination beliefs; trait reactance; trait dogmatism; belief in 2020 election fraud; belief in a QAnon conspiracy; health care system distrust; and identification with traditional gender roles. We utilized a multivariate analysis of covariance (MANCOVA) to examine mean differences across vaccine status groups for each of the correlates while holding constant the effects of age, gender, race, income, education, political party, and Evangelicalism. Across the 10 psychosocial correlates, several different response scales were used. To allow for comparison of effects across correlates, measures of effect size were computed by converting correlates to z-scores and then examining adjusted mean differences in z-scores between the groups. We found that all 10 psychosocial variables were significantly associated with vaccination status. After general anti-vaccination beliefs, COVID-19 misinformation beliefs and COVID-19 conspiracy beliefs had the largest effect on vaccine uptake. CONCLUSIONS The association of these psychosocial factors with COVID-19 vaccine hesitancy may help explain why vaccine uptake has not shifted much amongst the Unvaccinated-Hard No group since vaccines became available. These findings deepen our understanding of those who remain resistant to getting vaccinated and can guide more effective tailored communications to reach them. Health communication professionals may apply lessons learned from countering related beliefs and personality attributes around issues such as climate change and other forms of vaccine hesitancy. For example, using motivational interviewing strategies that are equipped to handle resistance and provide correct information in a delicate manner that avoids reactance.

BACKGROUND Web-based tailored interventions offer rich opportunities for improved access to and personalization of behavioral interventions. However, despite the promise of this approach, the engagement and underrepresentation of minority groups remain major issues. OBJECTIVE This study evaluated whether engagement (log-in status and log-in duration) with different types of tailored behavioral content from the Families Improving Together for weight loss web-based intervention was associated with changes in moderate to vigorous physical activity (MVPA) among African American families with overweight or obesity. METHODS Parent-adolescent dyads were randomized to a web-based tailored intervention or web-based health education comparison program. The web-based intervention (N=119) was completed by parents and targeted 6 weight-related behaviors to support their adolescent children’s weight loss goals (session contents included energy balance, fast food, fruits and vegetables, physical activity [PA], sedentary behavior, and sweetened beverages). MVPA was measured using accelerometers at baseline and after the intervention. RESULTS Using a hierarchical approach, the log-in status and duration for each web-based session were used to evaluate the additive effects of engagement with different types of tailored behavioral content on MVPA after the web-based intervention. Among parents, logging in to the PA session was not associated with greater MVPA (B=−12.561, 95% CI −18.759 to −6.367), but MVPA increased with greater log-in duration for the PA (B=0.008, 95% CI 0.004-0.012) and sedentary behavior (B= 0.008, 95% CI 0.004-0.012) sessions. These results suggest that parents who logged in to the PA session had lower MVPA, but MVPA increased with greater log-in duration for the PA and sedentary behavior sessions. These associations remained even after accounting for engagement with other content sessions. However, these engagement effects did not translate to the adolescents. CONCLUSIONS The results of this study highlight the need to disentangle the impact of engagement with different tailored content to improve the efficacy of tailored web-based interventions, especially for promoting PA in African American families. CLINICALTRIAL ClinicalTrials.gov NCT01796067; https://clinicaltrials.gov/ct2/show/NCT01796067

This study evaluates whether parental provision of transportation for physical activity is associated with child/adolescent moderate-to-vigorous physical activity, while also evaluating community-level poverty. Self- and parental-reported surveys were administered with parents/caregivers and children in the Healthy Communities Study (N = 5138). Associations between individual-level demographics, community-level poverty, parental provision of transportation for physical activity, and moderate-to-vigorous physical activity were examined in multi-level models. Even when accounting for community-level poverty, which was significantly associated with lower moderate-to-vigorous physical activity, parental provision of transportation for physical activity was positively associated with greater moderate-to-vigorous physical activity. This study provides evidence for the importance of considering multiple systems of influence (e.g., community and individual factors) and considering how gaps in physical activity transportation for youth can be addressed in future health policies.

There is an increased interest in the use of personalized medicine approaches in the prevention or treatment of obesity, however, few studies have used these approaches to identify individual differences in treatment effects. The current study demonstrates the use of the predicted individual treatment effects framework to test for individual differences in the effects of the ACTION-PAC intervention, which targeted the treatment and prevention of obesity in a high school setting. We show how methods for personalized medicine can be used to test for significant individual differences in responses to an intervention and we discuss the potential and limitations of these methods. In our example, 25% of students in the preventive intervention, were predicted to have their BMI z-score reduced by 0.39 or greater, while at other end of the spectrum, 25% were predicted to have their BMI z-score increased by 0.09 or more. In this paper, we demonstrate and discuss the process of using methods for personalized medicine with interventions targeting adiposity and discuss the lessons learned from this application. Ultimately, these methods have the potential to be useful for clinicians and clients in choosing between treatment options, however they are limited in their ability to help researchers understand the mechanisms underlying these predictions.

Previous findings have been equivocal as to whether a single nucleotide polymorphism (rs2832407) in GRIK1, which encodes a glutamate receptor subunit, moderates the effects of topiramate treatment for drinking reduction. We leveraged intensive longitudinal data to provide greater precision and allow an examination of intermediate outcomes addressing this question. We used data from a randomized controlled trial (RCT) to test the hypotheses that topiramate treatment reduces daily heavy drinking, desire to drink, and positive alcohol expectancies and that these effects are stronger in rs2832407*C-allele homozygotes.Secondary data analysis of a randomized controlled trial SETTING: University of Pennsylvania Treatment Research Center in the United States of America PARTICIPANTS/CASES: Participants were 164 individuals (70% male, mean age=51.5, 36% rs2832407*C-allele homozygotes) who sought to reduce or stop drinking. Intervention and Comparator Participants were assigned to medication (topiramate or placebo), with stratification by genotype group (CC vs. AA/AC) and treatment goal (reduce versus abstain).Over the 12-week treatment period, participants completed daily interactive voice response (IVR) surveys.On any given day during treatment, participants who received topiramate had lower odds of IVR-reported heavy drinking (odds ratio [OR]=0.257, b (standard error [SE])=-1.351 (0.334), p0.001) and lower levels of desire to drink (b (SE)=-0.323 (0.122), p=0.001) and positive alcohol expectancies (b (SE)=-0.347 (0.138), p=0.013) than those who received placebo. Participants who received topiramate also reported greater reductions in positive alcohol expectancies over the first 2 weeks of treatment than those who received placebo (b (SE)=-0.028(0.008), p=0.001), but topiramate did not impact the daily rate of change in heavy drinking or desire to drink. Genotype did not moderate the effects of topiramate on any outcomes examined (ps0.05).Topiramate is an effective medication for individuals seeking to reduce heavy drinking. The effects are not moderated by the single nucleotide polymorphism rs2832407.

Background Southeast Michigan is home to the second largest Middle Eastern and North African (MENA) US population. There is increasing interest in understanding correlates of psychosocial outcomes and health behaviors in this growing population. One potentially important health correlate is ethnic identity (EI). This paper reports the development, validity, and initial correlates of a new measure of MENA identity named the MENA-IM. Methods We used convenience sampling at locations frequented by individuals of MENA descent in southeast Michigan. We also measured EI centrality, religiosity, cultural mistrust, substance use, and health status to assess convergent and divergent validity. Exloratory and Confirmatory Factor Analysis identified three subscales, which were valid for both Arab and Chaldean respondents and were named (1) MENA cultural affiliation, (2) MENA media use, and (3) multicultural affiliation. We also created and tested a 20-item, single-factor version. Results We obtained data from 378 adults, 73% of whom identified as Arab and 27% as Chaldean. MENA-IM scores were higher among older, lower-educated, lower-income, non-US born, and Arabic-speaking respondents. Arab respondents reported significantly higher scores than Chaldeans. MENA-IM scores were positively associated with EI centrality and religiosity. Higher MENA-IM scores were found among those not reporting use of marijuana, alcohol, and opiates. Higher MENA-IM scores were also found among those without a self-reported history of heart disease and among those with better mental health status. Discussion The MENA-IM has strong psychometric properties and demonstrated initial evidence of convergent and discriminant validity. In general, values on the measure were associated with better psychosocial and health status. How the measure performs with MENA populations outside of Michigan and how it may relate to other health outcomes merit investigation.

Background Understanding determinants of metabolic risk has become a national priority given the increasingly high prevalence rate of this condition among U.S. adults. Purpose This study’s aim was to assess the impact of gene-by-neighborhood social environment interactions on waist circumference (WC) as a primary marker of metabolic risk in underserved African-American adults. Based on a dual-risk model, it was hypothesized that those with the highest genetic risk and who experienced negative neighborhood environment conditions would demonstrate higher WC than those with fewer risk factors. Methods This study utilized a subsample of participants from the Positive Action for Today’s Health environmental intervention to improve access and safety for walking in higher-crime neighborhoods, who were willing to provide buccal swab samples for genotyping stress-related genetic pathways. Assessments were conducted with 228 African-American adults at baseline, 12, 18, and 24 months. Results Analyses indicated three significant gene-by-environment interactions on WC outcomes within the sympathetic nervous system (SNS) genetic pathway. Two interactions supported the dual-risk hypotheses, including the SNS genetic risk-by-neighborhood social life interaction (b = −0.11, t(618) = −2.02, p = .04), and SNS genetic risk-by-informal social control interaction (b = −0.51, t(618) = −1.95, p = .05) on WC outcomes. These interactions indicated that higher genetic risk and lower social-environmental supports were associated with higher WC. There was also one significant SNS genetic risk-by-neighborhood satisfaction interaction (b = 1.48, t(618) = 2.23, p = .02) on WC that was inconsistent with the dual-risk pattern. Conclusions Findings indicate that neighborhood and genetic factors dually influence metabolic risk and that these relations may be complex and warrant further study. Trial Registration NCT01025726.

Background. The purpose of the current article is to demonstrate how formative process evaluation was used in a pilot study to optimize the design and implementation of two motivationally targeted community-based physical activity (PA) interventions for inactive African American women. Method. Fifteen African American women (M age: 41.6 years) were randomized to a challenge-focused program targeted toward high autonomous motivation or a rewards-focused program targeted toward low autonomous motivation. The challenge-focused program targeted enjoyment and valuation of PA and a team-based positive social climate through competitive intergroup activities and team-based goals, whereas the rewards-focused program targeted PA interest, competency, and partner-based social support through a walking program, individual-based goals with financial incentives, and partner-based action-plans. Results. Feedback from participants revealed high levels of acceptability of essential elements. Average weekly attendance exceeded the a priori goal of ≥75% of members in attendance each week. External systematic observation demonstrated that session content dose was ≥93% in both programs. Facilitator-level fidelity exceeded the a priori goal of averaging ≥3 on a 4-point scale for behavioral skills, communication, autonomy support, and session content. The process evaluation also revealed areas for improvement, including facilitator-level social support and behavioral skills at the group-level. Process data collected through FitBits revealed that participants were engaged in self-monitoring PA during the 6-week programs. Conclusions. The formative process evaluation demonstrated adequate levels of feasibility and acceptability and also provided key insights into adjustments needed before proceeding with implementing the motivationally targeted group-based programs in a larger randomized study.

Mechanisms of behavior change are the processes through which interventions are hypothesized to cause changes in outcomes. Latent growth curve mediation models (LGCMM) are recommended for investigating the mechanisms of behavior change because LGCMM models establish temporal precedence of change from the mediator to the outcome variable. The Correlated Augmented Mediation Sensitivity Analyses (CAMSA) App implements sensitivity analysis for LGCMM models to evaluate if a mediating path (mechanism) is robust to potential confounding variables. The CAMSA approach is described and applied to simulated data, and data from a research study exploring a mechanism of change in the treatment of substance use disorder.

Objective Numerous behavioral treatments for alcohol use disorder (AUD) are effective, but there are substantial individual differences in treatment response. This study examines the potential use of new methods for personalized medicine to test for individual differences in the effects of cognitive behavioral therapy (CBT) versus motivational enhancement therapy (MET) and to provide predictions of which will work best for individuals with AUD. We highlight both the potential contribution and the limitations of these methods. Method We performed secondary analyses of abstinence among 1,144 participants with AUD participating in either outpatient or aftercare treatment who were randomized to receive either CBT or MET in Project MATCH. We first obtained predicted individual treatment effects (PITEs), as a function of 19 baseline client characteristics identified a priori by MATCH investigators. Then, we tested for the significance of individual differences and examined the predicted individual differences in abstinence 1 year following treatment. Predictive intervals were estimated for each individual to determine if they were 80% more likely to achieve abstinence in one treatment versus the other. Results Results indicated that individual differences in the likelihood of abstinence at 1 year following treatment were significant for those in the outpatient sample, but not for those in the aftercare sample. Individual predictive intervals showed that 37% had a better chance of abstinence with CBT than MET, and 16% had a better chance of abstinence with MET. Obtaining predictions for a new individual is demonstrated. Conclusions Personalized medicine methods, and PITE in particular, have the potential to identify individuals most likely to benefit from one versus another intervention. New personalized medicine methods play an important role in putting together differential effects due to previously identified variables into one prediction designed to be useful to clinicians and clients choosing between treatment options. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Regression mixture models are one increasingly utilized approach for developing theories about and exploring the heterogeneity of effects. In this study we aimed to extend the current use of regression mixtures to a repeated regression mixture method when repeated measures, such as diary-type and experience-sampling method, data are available. We hypothesized that additional information borrowed from the repeated measures would improve the model performance, in terms of class enumeration and accuracy of the parameter estimates. We specifically compared three types of model specifications in regression mixtures: (a) traditional single-outcome model; (b) repeated measures models with three, five, and seven measures; and (c) a single-outcome model with the average of seven repeated measures. The results showed that the repeated measures regression mixture models substantially outperformed the traditional and average single-outcome models in class enumeration, with less bias in the parameter estimates. For sample size, whereas prior recommendations have suggested that regression mixtures require samples of well over 1,000 participants, even for classes at a large distance from each other (classes with regression weights of .20 vs. .70), the present repeated measures regression mixture models allow for samples as low as 200 participants with an increased number (i.e., seven) of repeated measures. We also demonstrate an application of the proposed repeated measures approach using data from the Sleep Research Project. Implications and limitations of the study are discussed.

The purpose of the study was to explore whether gender or ethnicity moderated the links between language skills and teacher ratings of problem behaviour and between language and social skills in 38...

Objective This study set out to examine the role of parenting practices in protecting or exacerbating the negative effects of parent and adolescent stress on adolescent body mass index (BMI) over time. Separate longitudinal models were conducted to evaluate how parenting practices interacted with parental perceived stress and adolescent perceived stress in predicting adolescent BMI. Methods Baseline data were collected from 148 African American adolescents (Mage = 12.93, SD = 1.75; Mz-BMI = 0.78, SD = 0.50; MBMI%-ile = 96.7, SD = 3.90) and their caregivers (Mage = 44.45, SD = 8.65; MBMI = 37.63, SD = 8.21) enrolled in the Families Improving Together for Weight Loss trial. Adolescents self-reported their perceptions of caregiver parenting style and feeding practices. Both caregivers and adolescents self-reported their perceptions of chronic stress. BMI for parents and adolescents was assessed objectively at baseline and 16 weeks post-intervention. Results Hierarchical regression models predicting adolescent BMI z-score (z-BMI) indicated a significant interaction between parental perceived stress and parental pressure to eat. Simple slopes analyses demonstrated that for those parents that exhibit higher pressure to eat, parent stress was positively associated with adolescent z-BMI. Conclusions These findings provide preliminary support suggesting that certain parenting practices interact with chronic stress on adolescent weight-related outcomes and that future interventions may consider integrating these factors.

The purpose of this study was to examine the relationship between language skills and behavioural problems and the potential moderating role of the quality of classroom emotional support in this relationship among 242 preschool children from low-income families. The Preschool Language Scale-5 was administered individually to each child. The quality of classroom emotional support was measured using the Emotional Support domain of the Classroom Assessment Scoring System for Pre-Kindergarten. Teachers and parents completed the Child Behaviour Checklist for Ages 1½-5. Results indicated the inverse relationship between language skills and behaviour problems varied by the level of classroom emotional support provided by teachers. Specifically, children with lower language skills exhibited higher levels of behaviour problems in classrooms where teachers provided lower levels of emotional support. Findings from this study have important implications for enhancing teachers' emotional support aimed at children with lower language skills and for future research.

There is an increased interest in the use of personalized medicine approaches in the prevention or treatment of obesity, however, few studies have used these approaches to identify individual differences in treatment effects. The current study demonstrates the use of the predicted individual treatment effects framework to test for individual differences in the effects of the ACTION-PAC intervention, which targeted the treatment and prevention of obesity in a high school setting. We show how methods for personalized medicine can be used to test for significant individual differences in responses to an intervention and we discuss the potential and limitations of these methods. In our example, 25% of students in the preventive intervention, were predicted to have their BMI z-score reduced by 0.39 or greater, while at other end of the spectrum, 25% were predicted to have their BMI z-score increased by 0.09 or more. In this paper, we demonstrate and discuss the process of using methods for personalized medicine with interventions targeting adiposity and discuss the lessons learned from this application. Ultimately, these methods have the potential to be useful for clinicians and clients in choosing between treatment options, however they are limited in their ability to help researchers understand the mechanisms underlying these predictions.

Highlights • COVID-19 Social Distance Attitude Scale has positive and negative attitude factors. • This scale shows high internal consistency with construct and predictive validity. • Holding highly negative attitudes reduces the effect of holding positive beliefs. • Perceived COVID risk & severity correlated with high positive/low negative attitudes. • Social distance attitude factors related to demographics and political party., Objective Our goal was to develop a scale to assess social distance attitudes related to COVID-19. Methods We performed an online national survey of US adults (n = 1,074) to assess social distance attitudes, COVID-19 related beliefs and behaviors, and demographics. We assessed scale structure using confirmatory factor analysis and evaluated internal consistency and validity. We assessed association of scale factors with respondent characteristics. Results Confirmatory factor analysis supported a hypothesized two-factor solution. Internal consistency was high for both positive (Alpha = 0.92) and negative (Alpha = 0.91) attitude factors. Analyses supported construct and predictively validity with expected associations between scale factors and perceived norms and behavior (e.g. trips out of the home). We found an interaction suggesting that holding highly negative attitudes reduced the effect of holding positive beliefs. Both attitude factors were related to age, gender, race/ethnicity, and political affiliation. Perceived COVID-19 risk (to others but not for self) and perceived severity were consistently associated with higher positive and lower negative attitudes. Conclusion This COVID-19 Social Distance Attitude Scale contains positive and negative factors with high internal consistency and construct and predictive validity. Practice Implication A greater understanding and ongoing assessment of COVID-19 social distance attitudes could inform policymakers, researchers, and clinicians who seek to promote protective social distance behaviors.

Background A central component of the public health strategy to control the COVID-19 pandemic involves encouraging mask wearing and social distancing to protect individuals from acquiring and transmitting the virus. Objective This study aims to understand the psychological factors that drive adoption or rejection of these protective behaviors, which can inform public health interventions to control the pandemic. Methods We conducted an online survey of a representative sample of 1074 US adults and assessed three novel potential predictors of COVID-19 behaviors: trait reactance, COVID-19 conspiracy beliefs, and COVID-19 apocalypse beliefs. Key outcomes (dependent variables) included an index of COVID-19 protective behaviors, the number of trips taken from the home, and COVID-19 knowledge. Results In bivariate analyses, all three predictors were significantly correlated in the hypothesized direction with the three COVID-19 outcomes. Specifically, each predictor was negatively (P Conclusions This study can inform the development of health communication interventions to encourage the adoption of COVID-19 protective behaviors. Interestingly, we found that higher scores of all three novel predictors were associated with lower COVID-19 knowledge, suggesting that lack of an accurate understanding of the virus may be driving some of these attitudes; although, it is also possible that these attributes may interfere with one’s willingness or ability to seek and absorb accurate health information. These individuals may be particularly immune to accepting new information and yielding their beliefs. Health communication professionals may apply lessons learned from countering similar beliefs around climate change and vaccine hesitancy. Messages designed for individuals prone to reactance may be more effective if they minimize controlling language and emphasize the individual’s independence in adopting these behavioral recommendations. Messaging for those who possess conspiracy beliefs should similarly not assume that providing evidence contrary to these beliefs will alone alter behavior. Other communication techniques such as rolling with resistance, a strategy used in motivational interviewing, may be helpful. Messaging for those with apocalyptic beliefs may require using religious leaders as the message source and using scripture that would support the adoption of COVID-19 protection behaviors.

BACKGROUND A central component of the public health strategy to control the COVID-19 pandemic involves encouraging mask wearing and social distancing to protect individuals from acquiring and transmitting the virus. OBJECTIVE This study aims to understand the psychological factors that drive adoption or rejection of these protective behaviors, which can inform public health interventions to control the pandemic. METHODS We conducted an online survey of a representative sample of 1074 US adults and assessed three novel potential predictors of COVID-19 behaviors: trait reactance, COVID-19 conspiracy beliefs, and COVID-19 apocalypse beliefs. Key outcomes (dependent variables) included an index of COVID-19 protective behaviors, the number of trips taken from the home, and COVID-19 knowledge. RESULTS In bivariate analyses, all three predictors were significantly correlated in the hypothesized direction with the three COVID-19 outcomes. Specifically, each predictor was negatively (P CONCLUSIONS This study can inform the development of health communication interventions to encourage the adoption of COVID-19 protective behaviors. Interestingly, we found that higher scores of all three novel predictors were associated with lower COVID-19 knowledge, suggesting that lack of an accurate understanding of the virus may be driving some of these attitudes; although, it is also possible that these attributes may interfere with one’s willingness or ability to seek and absorb accurate health information. These individuals may be particularly immune to accepting new information and yielding their beliefs. Health communication professionals may apply lessons learned from countering similar beliefs around climate change and vaccine hesitancy. Messages designed for individuals prone to reactance may be more effective if they minimize controlling language and emphasize the individual’s independence in adopting these behavioral recommendations. Messaging for those who possess conspiracy beliefs should similarly not assume that providing evidence contrary to these beliefs will alone alter behavior. Other communication techniques such as rolling with resistance, a strategy used in motivational interviewing, may be helpful. Messaging for those with apocalyptic beliefs may require using religious leaders as the message source and using scripture that would support the adoption of COVID-19 protection behaviors.

Latent class mediation modeling is designed to estimate the mediation effect when both the mediator and the outcome are latent class variables. We suggest using an adjusted one-step approach in which the latent class models for the mediator and the outcome are estimated first to decide on the number of classes, then the latent class models and the mediation model are jointly estimated. We present both an empirical demonstration and a simulation study to compare the performance of this one-step approach to a standard three-step approach with modal assignment (modal) and four different modern three-step approaches. Results from the study indicate that unadjusted modal, which ignores the classification errors of the latent class models, produced biased mediation effects. On the other hand, the adjusted one-step approach and the modern three-step approaches performed well with respect to bias for estimating mediation effects, regardless of measurement quality (i.e., model entropy) and latent class size. Among the three-step approaches we investigated, the maximum likelihood method with modal assignment and the BCH (Bolck, Croon, & Hagenaars, 2004) correction with robust standard error estimators are good alternatives to the adjusted one-step approach, given their unbiased standard error estimations.

The development and evaluation of mindfulness-based interventions for a variety of psychological and medical disorders have grown exponentially over the past 20 years. Yet, calls for increasing the rigor of mindfulness research and recognition of the difficulties of conducting research on the topic of mindfulness have also increased. One of the major difficulties is the measurement of mindfulness, with varying definitions across studies and ambiguity with respect to the meaning of mindfulness. There is also concern about the reproducibility of findings given few attempts at replication. The current secondary analysis addressed the issue of reproducibility and robustness of the construct of self-reported mindfulness across two separate randomized clinical trials of mindfulness-based relapse prevention (MBRP), as an aftercare treatment for substance use disorder. Specifically, we tested the robustness of our previously published findings, which identified a latent construct of mindfulness as a significant mediator of the effect of MBRP on reducing craving following treatment. First, we attempted to replicate the findings in a separate randomized clinical trial of MBRP. Second, we conducted sensitivity analyses to test the assumption of the no-omitted confounder bias in a mediation model. The effect of MBRP on self-reported mindfulness and overall mediation effect failed to replicate in a new sample. The effect of self-reported mindfulness in predicting craving following treatment did replicate and was robust to the no-omitted confounder bias. The results of this work shine a light on the difficulties in the measurement of mindfulness and the importance of examining the robustness of findings.

This study examined the cross-sectional structure of working memory (WM) among elementary school English learners (ELs). A battery of WM tasks was administered in Spanish (L1) and English (L2) within five age groups (ages 6, 7, 8, 9, & 10). Confirmatory factor analysis showed a three-factor structure of WM emerged in both L1 and L2 administrations for each age group. The important findings, however, were: (1) the separation between the executive component and storage component (phonological loop) structure of WM increased as a function of age within both language systems, (2) the structure of WM supported a domain general phonological storage component and a domain general executive system across both language systems, and (3) the visual-spatial WM system shared minimal variance with the executive system. Taken together, the findings support Baddeley's multicomponent model (e.g., Baddeley & Logie, 1999. The multiple-component model. In A. Miyake & P. Shah (Eds.), Models of working memory: Mechanisms of active maintenance and executive control (pp. 28-61). Cambridge: Cambridge University Press) as a good fit to the structure of WM in EL children's English and Spanish language system.

Regression mixture models are becoming more widely used in applied research. It has been recognized that these models are quite sensitive to underlying assumptions, yet many of these assumptions are not directly testable. We discuss a diagnostic tool based on reconstructed residuals that can help uncover violations of model assumptions. These residuals are found by using the posterior probability of class membership to assign, based on a multinomial distribution, a class to each observation. Standard residual checks can be applied to these posterior draw residuals to explore violations of the model assumptions. We present several illustrations of the diagnostic tool.

OBJECTIVE: Few studies have found support for coping as a mechanism of behavior change (MOBC) following coping skills training interventions for alcohol use disorder (AUD). One potential reason for null findings is heterogeneity in the patterns of coping skills acquired during treatment. This study sought to identify latent classes of coping and to test the latent class variable as a mediator of the effect of a combined behavioral intervention for AUD. METHOD: Secondary analyses of data from the Combined Pharmacotherapies and Behavioral Interventions for Alcohol Dependence (COMBINE) Study (N = 1,124; mean age = 44.4 years; 69.1% male; 23.2% non-White), a multisite study of medication and behavioral treatments for individuals with AUD. Latent class mediation models were estimated to test whether patterns of alcohol-specific coping mediated the effect of combined behavioral intervention with medication management, as compared with medication management only, on drinking outcomes 12 months following treatment. RESULTS: Three classes were identified, which differed in repertoire broadness, or the degree in which a wide range of different skills were used. Coping repertoire class was a significant mediator of the effect of the combined behavioral intervention on drinking outcomes. Receiving the combined behavioral intervention, in addition to medication management, predicted a greater likelihood of expected classification in the broad coping repertoire class, which in turn was associated with significant improvements in drinking outcomes. CONCLUSIONS: Using the novel methodological approach of latent class mediation, this study identified coping repertoire as a significant mediator of behavioral intervention efficacy for AUD. Future work examining heterogeneity in mediators and outcomes may help refine AUD treatment to be maximally effective.

Bootstrapping has been used as a diagnostic tool for validating model results for a wide array of statistical models. Here we evaluate the use of the non-parametric bootstrap for model validation in mixture models. We show that the bootstrap is problematic for validating the results of class enumeration and demonstrating the stability of parameter estimates in both finite mixture and regression mixture models. In only 44% of simulations did bootstrapping detect the correct number of classes in at least 90% of the bootstrap samples for a finite mixture model without any model violations. For regression mixture models and cases with violated model assumptions, the performance was even worse. Consequently, we cannot recommend the non-parametric bootstrap for validating mixture models. The cause of the problem is that when resampling is used influential individual observations have a high likelihood of being sampled many times. The presence of multiple replications of even moderately extreme observations is shown to lead to additional latent classes being extracted. To verify that these replications cause the problems we show that leave-k-out cross-validation where sub-samples taken without replacement does not suffer from the same problem.

Background Examining the data collection practices implemented by postsecondary education programs for students with intellectual and developmental disability represents the first step in documenting student progress, making programmatic data-based decisions, and evaluating the overall program effectiveness in preparing students for competitive employment.Method We administered a survey to a national sample of directors and coordinators (N = 52) of postsecondary education programs across the United States, who indicated that they collected data to gather information on student employment–related aspects and program effectiveness.Results Results suggest that a large number of programs collect employment data during student enrolment in the program, at graduation, and postgraduation, and make data-based decisions.Conclusions A wide variability exists in the type of data collection practices implemented by postsecondary education programs for students with intellectual and developmental disability in...

Evidence suggests that physical activity and alcohol use are positively related among young adults. Two studies have examined daily relations, and results have shown conflicting findings. We examined relations between physical activity and alcohol use at both within- and between-individual levels and investigated moderators of the relation at both levels. 269 college students wore accelerometers to collect physical activity data over a 2-week period. At the end of each day, they indicated whether or not they drank alcohol. Multilevel logistic regression indicated neither within- nor between-subject relations were statistically significant. Positive affect, negative affect, and drinking motives moderated these relations at the between-subject level. Contrary to previous research, we did not observe a relation between physical activity and alcohol use at the daily level. Unique features of the current study suggest next steps for future research examining the perplexing PA-alcohol relation in this population.

Regression mixture models are a statistical approach used for estimating heterogeneity in effects. This study investigates the impact of sample size on regression mixture’s ability to produce “stable” results. Monte Carlo simulations and analysis of resamples from an application data set were used to illustrate the types of problems that may occur with small samples in real data sets. The results suggest that (a) when class separation is low, very large sample sizes may be needed to obtain stable results; (b) it may often be necessary to consider a preponderance of evidence in latent class enumeration; (c) regression mixtures with ordinal outcomes result in even more instability; and (d) with small samples, it is possible to obtain spurious results without any clear indication of there being a problem.

Background Although it is a common practice to estimate dietary intake using three random 24-hour dietary recalls, some studies have suggested up to nine may be necessary to reliably estimate usual intake in youth. Given the resulting increase in resources and participant burden, more research is needed to determine whether this method is reliable, particularly in African-American youth at increased risk for obesity and other chronic diseases. Objective This study estimated the reliability with which 24-hour dietary recalls measure energy, fat, fruit, and vegetable intake in African-American youth and examined how reliability changes as a function of the number of recalls. Design This study used cross-sectional data collection across three studies. Participants/setting Participants were African-American youth (n=456, mean±standard deviation age 13.28±1.86 years, 64% were girls, mean±standard deviation body mass index [calculated as kg/m 2 ] 31.45±7.94) who completed random 24-hour dietary recalls (67% completed three) conducted by research assistants using the Automated Self-Administered 24-Hour recall system (n=258) or registered dietitian nutritionists using the Nutrition Data System for Research (n=198). Main outcome measures/statistical analyses Estimates provided by multilevel models were used to calculate the proportion of variance accounted for between individuals and the reliability of means within individuals as a function of the number of recalls. Results Reliability estimates for assessing dietary outcomes using one to three recalls ranged from 11% to 62%. To achieve 80% reliability, the following number of recalls would need to be conducted: 8 for energy intake, 13 for fat intake, 21 to 32 for fruit intake, and 21 to 25 for vegetable intake. Conclusions The common practice of assessing dietary intake with three recalls does so with low reliability in African-American youth. Until more objective methods for reliably estimating usual intake are developed, researchers who choose to use 24-hour dietary recalls are encouraged to include estimates of the measure's reliability in a priori power calculations for improved decision making regarding the number of observations and/or sample size.

This study conducted a secondary analysis using data from the National Longitudinal Transition Study–2 (NLTS-2) to examine the degree to which three of the four essential characteristics of self-determination (autonomy, psychological empowerment, and self-realization) predict enrollment in, and completion of, postsecondary education programs for students with disabilities. Results suggest autonomy and psychological empowerment influence students’ enrollment in postsecondary education programs; higher levels of autonomy in females increase their odds of enrolling in a 4-year university; and students attending a rural school with higher levels of psychological empowerment are less likely to enroll in a 4-year university. Self-realization was the only characteristic that affected students’ completion of a postsecondary education program. Implications of the findings for research and practice are discussed.

Background: Reports of physical activity (PA) measured via wrist-worn accelerometers in adolescents are limited. This study describes PA levels in adolescents at baseline of an obesity prevention and weight management trial. Methods: Adolescents (n = 930) at 8 high schools wore an accelerometer for 7 days, with average acceleration values of g, >150 mg, and >500 mg categorized as sedentary, moderate, and vigorous PA, respectively. In a 3-level mixed-effects generalized linear model, PA was regressed on sex, weight status, and day of week. Daily PA was nested within students, and students within schools, with random effects included for both. Results: Adolescents accumulated a median of 40 minutes daily of moderate to vigorous PA (MVPA). MVPA was significantly different for teens with obesity versus teens with normal weight (−5.4 min/d, P = .03); boys versus girls (16.3 min/d, P P P P Conclusions: Interventions to increase PA in adolescents may benefit from focusing on increasing weekend PA and increasing MVPA in girls.

This study examined the effects of a family-based health promotion intervention on the moderate-to-vigorous physical activity (MVPA), light physical activity, sedentary behavior, and fruit and vegetable intake of African American parents. Eighty-nine African American parents (41.5 ± 8.5 years; 92% females; 74% obese; 64%

Latent growth curve mediation models are increasingly used to assess mechanisms of behavior change. For latent growth mediation model, like any another mediation model, even with random treatment assignment, a critical but untestable assumption for valid and unbiased estimates of the indirect effects is that there should be no omitted variable that confounds indirect effects. One way to address this untestable assumption is to conduct sensitivity analysis to assess whether the inference about an indirect effect would change under varying degrees of confounding bias. We developed a sensitivity analysis technique for a latent growth curve mediation model. We compute the biasing effect of confounding on point and confidence interval estimates of the indirect effects in a structural equation modeling framework. We illustrate sensitivity plots to visualize the effects of confounding on each indirect effect and present an empirical example to illustrate the application of the sensitivity analysis.

This paper proposes a novel exploratory approach for assessing how the effects of level-2 predictors differ across level-1 units. Multilevel regression mixture models are used to identify latent classes at level-1 that differ in the effect of one or more level-2 predictors. Monte Carlo simulations are used to demonstrate the approach with different sample sizes and to demonstrate the consequences of constraining 1 of the random effects to zero. An application of the method to evaluate heterogeneity in the effects of classroom practices on students is used to show the types of research questions which can be answered with this method and the issues faced when estimating multilevel regression mixtures.

The Families Improving Together (FIT) randomized controlled trial tests the efficacy of integrating cultural tailoring, positive parenting, and motivational strategies into a comprehensive curriculum for weight loss in African American adolescents. The overall goal of the FIT trial is to test the effects of an integrated intervention curriculum and the added effects of a tailored web-based intervention on reducing z-BMI in overweight African American adolescents.The FIT trial is a randomized group cohort design the will involve 520 African American families with an overweight adolescent between the ages of 11-16 years. The trial tests the efficacy of an 8-week face-to-face group randomized program comparing M + FWL (Motivational Plus Family Weight Loss) to a comprehensive health education program (CHE) and re-randomizes participants to either an 8-week on-line tailored intervention or control on-line program resulting in a 2 (M + FWL vs. CHE group) × 2 (on-line intervention vs. control on-line program) factorial design to test the effects of the intervention on reducing z-BMI at post-treatment and at 6-month follow-up.The interventions for this trial are based on a theoretical framework that is novel and integrates elements from cultural tailoring, Family Systems Theory, Self-Determination Theory and Social Cognitive Theory. The intervention targets positive parenting skills (parenting style, monitoring, communication); cultural values; teaching parents to increase youth motivation by encouraging youth to have input and choice (autonomy-support); and provides a framework for building skills and self-efficacy through developing weight loss action plans that target goal setting, monitoring, and positive feedback.

Background African-American adults experience the highest rates of elevated blood pressure (BP), and this disparity may be linked to socioeconomic and neighborhood-related disadvantage. Based on a bioecological stress-buffering framework, relations of poverty and neighborhood environmental perceptions with BP were assessed using multilevel regression in at-risk African-American adults. Methods This cross-sectional study used baseline data that were collected in 2008 as part of the Positive Action for Today's Health (PATH) trial (N = 409), a community-based intervention to increase walking in low-income, high-crime neighborhoods. BP and perceived neighborhood crime and satisfaction were investigated as individual-level indicators of health and neighborhood environment. Census block groups (N = 22) served as geographic proxies for neighborhoods, and poverty was obtained using 2010 U.S. Census data, to characterize the neighborhood-level socioeconomic environment. Results There were no individual-level direct associations. Significant cross-product interactions demonstrated that with higher perceived crime, high satisfaction was associated with lower systolic (γ = 3.34) and diastolic (γ = -1.37) BP, but low satisfaction was associated with higher systolic (γ = 15.12) and diastolic (γ = 7.57) BP. Neighborhood-level poverty was associated with diastolic (γ = 11.48, SE = 4.08, P = 0.008) and systolic BP (γ = 12.79, SE = 6.33, P = 0.052). Variance in BP across block groups was low (intraclass correlation coefficients = 0.002-0.014) and there were no significant random effects. Conclusions Results supported hypotheses, with greater neighborhood satisfaction linked to lower systolic and diastolic BP when perceived crime was high. Neighborhood poverty was also linked to higher systolic and diastolic BP. Prevention efforts should further investigate whether attending to issues of poverty and related neighborhood perceptions reduces high BP in at-risk African-American communities.