Pleasure and Satisfaction as Predictors of Future Cigarette and E-Cigarette Use: A Novel Two-Stage Modeling Approach.

INTRODUCTION: Subjective experience of e-cigarettes may be an important factor in helping people who use combustible cigarettes switch completely to e-cigarettes to reduce harms from smoking. This paper describes a novel two-stage analysis using pleasure and satisfaction responses from Ecological Momentary Assessments (EMA) of both cigarette and e-cigarette use to predict future cigarette and e-cigarette tobacco use. METHODS: This observational study included adult users of cigarettes and e-cigarettes who provided 7-days of EMA, capturing cigarette and e-cigarette use, followed by biweekly reports of cigarette and e-cigarette use over one year. Participants were 279 adults who provided both cigarette and e-cigarette responses during the EMA. We employed a two-stage analytic approach in which EMA data were used to predict subsequent levels of cigarette and e-cigarette use. In the first stage, EMA responses of cigarette and e-cigarette events were modeled via a mixed-effects location scale (MELS) model to yield summaries of participants' means and variability on event-related ratings of pleasure and satisfaction. These EMA summaries served as predictors in the second stage analysis of the biweekly post-EMA longitudinal cigarette and e-cigarette use data. RESULTS: EMA pleasure and satisfaction ratings were similar for both products and predicted both longitudinal cigarette and e-cigarette use, even after controlling for baseline cigarette and e-cigarette dependence. Relatively higher levels of satisfaction with e-cigarettes were associated with greater decreases in cigarette use over time. CONCLUSIONS: Pleasure and satisfaction are important predictors of subsequent cigarette and e-cigarette use. IMPLICATIONS: Experienced subjective pleasure and satisfaction from e-cigarettes relative to cigarettes may be an important factor in helping individuals who smoke to switch completely to e-cigarettes as a harm reduction approach. In order to help sustain complete product switching and reduce dual use or relapse to smoking, e-cigarettes may need to deliver more satisfaction to the user compared to that experienced from cigarettes.

An Introduction and Practical Guide to Strategies for Analyzing Longitudinal Data in Clinical Trials of Smoking Cessation Treatment: Beyond Dichotomous Point-Prevalence Outcomes.

Conceptualizing tobacco dependence as a chronic relapsing condition suggests the need to use analytic strategies that reflect that premise. However, clinical trials for smoking cessation typically define the primary endpoint as a measure of abstinence at a single timepoint distal to the intervention, typically 3-12 months. This reinforces the concept of tobacco outcomes as a dichotomous state-one is, or is not, abstinent. Fortunately, there are several approaches available to handle longitudinal data that reflect the relapsing and remitting nature of tobacco use during treatment studies. In this paper, sponsored by the Society for Research on Nicotine and Tobacco's Treatment Research Network, we present an introductory overview of these techniques and their application in smoking cessation clinical trials. Topics discussed include models to examine abstinence outcomes (eg, trajectory models of abstinence, models for transitions in smoking behavior, models for time to event), models that examine reductions in tobacco use, and models to examine joint outcomes (eg, examining changes in the use of more than one tobacco product). Finally, we discuss three additional relevant topics (ie, heterogeneity of effects, handling missing data, and power and sample size) and provide summary information about the type of model that can be used based on the type of data collected and the focus of the study. We encourage investigators to familiarize themselves with these techniques and use them in the analysis of data from clinical trials of smoking cessation treatment. Implications Clinical trials of tobacco dependence treatment typically measure abstinence 3-12 months after participant enrollment. However, because smoking is a chronic relapsing condition, these measures of intervention success may not accurately reflect the common trajectories of tobacco abstinence and relapse. Several analytical techniques facilitate this type of outcome modeling. This paper is meant to be an introduction to these concepts and techniques to the global nicotine and tobacco research community including which techniques can be used for different research questions with visual summaries of which types of models can be used for different types of data and research questions.

Long-term exposure to ambient air pollution and measures of central hemodynamics and arterial stiffness among multiethnic Chicago residents.

OBJECTIVES: To examine whether long-term air pollution exposure is associated with central hemodynamic and brachial artery stiffness parameters. METHODS: We assessed central hemodynamic parameters including central blood pressure, cardiac parameters, systemic vascular compliance and resistance, and brachial artery stiffness measures [including brachial artery distensibility (BAD), compliance (BAC), and resistance (BAR)] using waveform analysis of the arterial pressure signals obtained from a standard cuff sphygmomanometer (DynaPulse2000A, San Diego, CA). The long-term exposures to particles with an aerodynamic diameter < 2.5 µm (PM2.5) and nitrogen dioxide (NO2) for the 3-year periods prior to enrollment were estimated at residential addresses using fine-scale intra-urban spatiotemporal models. Linear mixed models adjusted for potential confounders were used to examine associations between air pollution exposures and health outcomes. RESULTS: The cross-sectional study included 2,387 Chicago residents (76% African Americans) enrolled in the ChicagO Multiethnic Prevention And Surveillance Study (COMPASS) during 2013-2018 with validated address information, PM2.5 or NO2, key covariates, and hemodynamics measurements. We observed long-term concentrations of PM2.5 and NO2 to be positively associated with central systolic, pulse pressure and BAR, and negatively associated with BAD, and BAC after adjusting for relevant covariates. A 1-µg/m3 increment in preceding 3-year exposures to PM2.5 was associated with 1.8 mmHg higher central systolic (95% CI: 0.98, 4.16), 1.0 mmHg higher central pulse pressure (95% CI: 0.42, 2.87), a 0.56%mmHg lower BAD (95% CI: -0.81, -0.30), and a 0.009 mL/mmHg lower BAC (95% CI: -0.01, -0.01). CONCLUSION: This population-based study provides evidence that long-term exposures to PM2.5 and NO2 is related to central BP and arterial stiffness parameters, especially among African Americans.

Associations of obesity, movement behaviors, and socioeconomic status with fundamental movement skills in children: Results from the REACT project.

OBJECTIVE: To investigate the relationship of biological characteristics (age, sex, and obesity), movement behaviors (physical activity and sedentary time), and family socioeconomic status with fundamental movement skills (FMS) in primary school children. METHODS: This cross-sectional study sampled 1014 children (537 girls) aged 6 to 10 years from 25 primary schools in Matosinhos, north of Portugal. Five object control skills (dribbling, kicking, catching, throwing, and underarm rolling) were assessed with a categorical scale using the Meu Educativo® platform. Body Mass Index (BMI) was calculated and transformed into z-scores. Moderate-to-vigorous physical activity (MVPA) and sedentary time were monitored with accelerometry (ActiGraph wGT3X-BT) for seven consecutive days. Family socioeconomic status (SES) was obtained from the Portuguese social support system. Ordinal multilevel logistic regression was used to analyze the associations of weight status, MVPA, sedentary time and SES with FMS, adjusted for sex and age. RESULTS: Boys (odds ratio (OR) = 6.54; 95% CI: 5.13-8.36) and older children (OR = 2.04; 95% CI: 1.85-2.26) were more likely to achieve higher FMS scores. Children with obesity (OR = 0.60; 95% CI: 0.45-0.80), those less active (OR = 0.56; 95% CI: 0.42-0.75) and children with more sedentary time (OR = 0.86; 95%CI: 0.77-0.97) were less likely to score high on FMS. Family SES was not significantly associated with FMS scores. CONCLUSION: Primary school children's FMS are significantly related to biological and behavioral factors but not to family SES. These findings highlight the need for suitable strategies to enhance children's FMS proficiency, considering differences in these characteristics. Fostering adequate motor skill proficiency levels will assist in establishing a robust foundation for healthy lifestyles of all children.

Individual and school correlates of body mass index and cardiorespiratory fitness in primary school children from the REACT project: A multivariate multilevel analysis.

OBJECTIVE: This paper examines the relationship between body mass index (BMI) and cardiorespiratory fitness (CRF) using a multivariate multilevel approach and investigates the links between individual and school-related correlates with children's BMI and CRF. METHODS: This cross-sectional sample included 1014 children (6-10 years) from 25 Portuguese primary schools. BMI was calculated, and CRF was assessed with the PACER test. Fundamental movement skills (FMS) included five object control tasks. Moderate-to-vigorous physical activity (MVPA), sleep, and sedentary time were assessed with the ActiGraph wGT3X-BT accelerometer. Socioeconomic status (SES) and school variables were also obtained. A multivariate multilevel model was used, and alpha was set at 5%. RESULTS: BMI and CRF systematically increased with age. Most of the joint variance (94.4%) was explained at the child level, and BMI and CRF were correlated at this level (ρ = -.37). More active children demonstrated higher CRF levels and had lower BMI levels; sedentary and sleep time were not significantly associated with BMI or CRF. FMS were positively associated with CRF but were not significantly associated with BMI. Children at higher SES were more fit and had lower BMI than their peers of lower SES. Finally, school-level variables were not significantly related to BMI and CRF. CONCLUSION: BMI and CRF had a low but statistically significant negative correlation in this sample of children. Most of the variation in BMI and CRF was explained by child-level characteristics.

A multivariate multilevel approach to unravel the associations between individual and school factors on children's motor performance in the REACT project.

OBJECTIVE: The aim was to (1) estimate the relationship between physical fitness (PF) and object control fundamental movement skills (FMS), (2) identify child characteristics that relate with PF and FMS, and (3) examine associations between the school environment, PF, and FMS. METHODS: The sample included 1014 Portuguese children aged 6-10 years from the REACT project. PF was assessed via running speed, shuttle run, standing long jump, handgrip, and the PACER test. Object control FMS were assessed with stationary dribble, kick, catch, overhand throw, and underhand roll. Test performances were transformed into z-scores, and their sum was expressed as overall PF and FMS. Child-level variables included body mass index (BMI) z-scores, accelerometer-measured sedentary time and moderate-to-vigorous physical activity, and socioeconomic status (SES). School size, physical education classes, practice areas, and equipment were also assessed. RESULTS: Approximately, 90% of the variance in object control PF and FMS was at the child level, and 10% at the school level. The correlation between PF and object control FMS was .62, which declined to .43 with the inclusion of covariates. Older, more active, and higher SES children had higher object control PF and FMS, and boys outperformed girls. BMI was negatively associated with PF but not with object control FMS. Sedentary time and number of physical education classes were not significant predictors. Most school predictors did not jointly associate with PF and object control FMS. CONCLUSION: PF and object control FMS z-scores were moderately related. Not all child characteristics were associated with both PF and object control FMS, and their effect sizes were different. School characteristics only explained 10% of the total variation in PF and object control FMS.

Is there an association between proficiency in fundamental movement skills and mderate-to-vigorous physical activity in childhood on weekdays and weekends? The REACT project.

OBJECTIVE: The present study probes into the association between children's fundamental movement skills (FMS) and moderate-to-vigorous physical activity (MVPA) during weekdays and weekends. METHODS: This cross-sectional sample included 1014 children aged 6-10 years from the REACT project. Physical activity was assessed with accelerometry, and five FMS (stationary dribble, kick, catch, overhand throw, and underhand roll) were assessed with the digital platform Meu Educativo®. Three groups were formed based on the frequency of FMS that each child mastered: group 1 (wizard level in four or five FMS); group 2 (wizard level in two or three FMS); and group 3 (wizard level in at most one skill). Multilevel models were used to analyze the data treating children (level-1) nested within schools (level-2). RESULTS: Compared to group 1, groups 2 (-12.9 ± 2.3 min day-1) and 3 (-23.9 ± 2.4 min day-1) were less physically active during weekdays and weekends (group 2: -14.7 ± 2.7 min day-1 and group 3: -22.4 ± 2.9 min day-1), independent of age and sex. There was a decline in MVPA during the weekend. Further, on average, boys were more active than girls, and with increasing age, children were less active. CONCLUSION: On average, children with higher FMS levels are generally more physically active than their peers with lower FMS levels. Even though MVPA tends to decline on weekends, FMS proficiency is a significant factor in maintaining 60 min of MVPA on weekends.

Fast estimation of mixed-effects location-scale regression models.

As a result of advances in data collection technology and study design, modern longitudinal datasets can be much larger than they historically have been. Such "intensive" longitudinal datasets are rich enough to allow for detailed modeling of the variance of a response as well as the mean, and a flexible class of models called mixed-effects location-scale (MELS) regression models are commonly used to do so. However, fitting MELS models can pose computational challenges related to the numerical evaluation of multi-dimensional integrals; the slow runtime of current methods is inconvenient for data analysis and makes bootstrap inference impractical. In this paper, we introduce a new fitting technique, called FastRegLS, that is considerably faster than existing techniques while still providing consistent estimators for the model parameters.

Joint modeling the frequency and duration of accelerometer-measured physical activity from a lifestyle intervention trial.

Physical activity (PA) guidelines recommend that PA be accumulated in bouts of 10 minutes or more in duration. Recently, researchers have sought to better understand how participants in PA interventions increase their activity. Participants can increase their daily PA by increasing the number of PA bouts per day while keeping the duration of the bouts constant; they can keep the number of bouts constant but increase the duration of each bout; or participants can increase both the number of bouts and their duration. We propose a novel joint modeling framework for modeling PA bouts and their duration over time. Our joint model is comprised of two sub-models: a mixed-effects Poisson hurdle sub-model for the number of bouts per day and a mixed-effects location scale gamma regression sub-model to characterize the duration of the bouts and their variance. The model allows us to estimate how daily PA bouts and their duration vary together over the course of an intervention and by treatment condition and is specifically designed to capture the unique distributional features of bouted PA as measured by accelerometer: frequent measurements, zero-inflated bouts, and skewed bout durations. We apply our methods to the Make Better Choices study, a longitudinal lifestyle intervention trial to increase PA. We perform a simulation study to evaluate how well our model is able to estimate relationships between outcomes.

Introducing a Real-Time Method for Identifying the Predictors of Noncompliance with Event-Based Reporting of Tobacco Use in Ecological Momentary Assessment.

BACKGROUND: Little is known about the factors that bias event-based (i.e., self-initiated) reporting of health behaviors in ecological momentary assessment (EMA) due to the difficulty inherent to tracking failures to self-initiate reports. PURPOSE: To introduce a real-time method for identifying the predictors of noncompliance with event-based reporting. METHODS: N = 410 adults who used both cigarettes and e-cigarettes completed a 1-week EMA protocol that combined random reporting of current contexts with event-based reporting of tobacco use. Each random assessment first asked if participants were currently using tobacco and, if so, the assessment converted into a "randomly captured" event report-indicating failure to self-initiate that report. Multilevel modeling tested predictors of failing to complete random reports and failing to self-initiate event reports. RESULTS: On the person level, male sex, higher average cigarette rate, and higher average cigarette urge each predicted missing random reports. The person-level predictors of failing to self-initiate event reports were older age, higher average cigarette and e-cigarette rates, higher average cigarette urge, and being alone more on average; the moment-level predictors were lower cigarette urge, lower positive affect, alcohol use, and cannabis use. Strikingly, the randomly captured events comprised more of the total EMA reports (28%) than did the self-initiated event reports (24%). These report types were similar across most variables, with some exceptions, such as momentary cannabis use predicting the random capture of tobacco events. CONCLUSIONS: This study demonstrated a method of identifying predictors of noncompliance with event-based reporting of tobacco use and enhancing the real-time capture of events.

This study introduced a real-time method for identifying person- and moment-level predictors of failing to self-initiate tobacco event reports during ecological momentary assessment (EMA), and for capturing a large number of events that would have likely otherwise been missed. The method has implications for behavioral health research more broadly.

Detecting influential subjects in intensive longitudinal data using mixed-effects location scale models.

BACKGROUND: Collection of intensive longitudinal health outcomes allows joint modeling of their mean (location) and variability (scale). Focusing on the location of the outcome, measures to detect influential subjects in longitudinal data using standard mixed-effects regression models (MRMs) have been widely discussed. However, no existing approach enables the detection of subjects that heavily influence the scale of the outcome. METHODS: We propose applying mixed-effects location scale (MELS) modeling combined with commonly used influence measures such as Cook's distance and DFBETAS to fill this gap. In this paper, we provide a framework for researchers to follow when trying to detect influential subjects for both the scale and location of the outcome. The framework allows detailed examination of each subject's influence on model fit as well as point estimates and precision of coefficients in different components of a MELS model. RESULTS: We simulated two common scenarios in longitudinal healthcare studies and found that influence measures in our framework successfully capture influential subjects over 99% of the time. We also re-analyzed data from a health behavior study and found 4 particularly influential subjects, among which two cannot be detected by influence analyses via regular MRMs. CONCLUSION: The proposed framework can help researchers detect influential subject(s) that will be otherwise overlooked by influential analysis using regular MRMs and analyze all data in one model despite influential subjects.

Validity and reliability of Meu Educativo®: A new tool to assess fundamental movement skills in school-aged children.

OBJECTIVES: There is evidence showing that children's proficiency in fundamental movement skills (FMS) is positively related to weight status, physical activity, fitness levels, cognitive development, as well as academic performance. Yet, the feasibility of FMS assessment is challenging, especially with relatively large samples of children. This article presents a new tool named Meu Educativo® to assess children's FMS levels, including its validity and reliability. METHODS: We relied on the validity evidence approach based on test content to develop the FMS assessment checklist and the rating system with a team of experts. In this article, we used five FMS (stationary dribbling, kick, overhand throw, catch the ball, and underhand roll). Further, we conducted a series of reliability studies and used percent agreement and Cohen's kappa (κ) as statistics. RESULTS: Experts agreed highly on the checklist's components in the five FMS. Inter-rater reliability ranged from 0.63 for stationary dribbling to 0.93 for overhand throw, and the intra-rater reliability ranged from 0.46 to 0.94. CONCLUSION: Based on the first results, Meu Educativo® was not only easy to use, but was also a reliable tool for FMS assessments. Notwithstanding the need for future studies, Meu Educativo® is a new tool that can be used by teachers, coaches, and motor development specialists dealing with school-aged children and researchers working with large samples.

Background, rationale, and methodological overview of the REACT project-return-to-action on growth, motor development, and health after the COVID-19 pandemic in primary school children.

OBJECTIVES: The REACT project was designed around two main aims: (1) to assess children's growth and motor development after the COVID-19 pandemic and (2) to follow their fundamental movement skills' developmental trajectories over 18 months using a novel technological device (Meu Educativo®) in their physical education classes. In this introductory article, the first of the Journal's special issue dedicated to REACT, our goal was to present the project rationale, its methodology, training and certification of the team, statistical approach, quality control, governance, and study management. METHODS: We sampled 1000 children (6-10 years of age) from 25 of the 32 primary schools in Matosinhos, northern Portugal. The protocol included a set of variables clustered around the child (growth, physical fitness, fundamental movement skills, and health behaviors), family (demographics, socioeconomic status, parental support for sports participation and physical activity), school (policies and practices for health behaviors, infrastructure for physical education and sports practices), and neighborhood and home environments (safety, sidewalks, sports facilities, as well as children electronic devices and play equipment at home). A set of standard protocols were implemented in REACT together with a rigorous system of training and certification of all members of the research team. This was complemented with a pilot study to assess, in loco, the quality of data acquisition, data entry, and control. DISCUSSION: Results from REACT will provide school administrators and teachers with novel and far-reaching information related to children's growth and motor development as well as health behaviors after the COVID-19 pandemic. It will also provide city-hall education officials with insight regarding children's physical fitness, fundamental movement skills, and sports practices that will be of great importance in devising novel intervention programs to increase health-enhancing physical activity, and combat sedentariness and obesity. Finally, it will offer parents a wealth of information regarding their children's growth, motor development, and health.

Statistical analysis of the longitudinal fundamental movement skills data in the REACT project using the multilevel ordinal logistic model.

OBJECTIVES: The REACT project was designed around two main aims: (1) to assess children's growth and motor development after the COVID-19 pandemic and (2) to follow their fundamental movement skills' developmental trajectories over 18 months using a novel technological device (Meu Educativo®) in their physical education classes. In this article, our goal is to describe statistical analysis of the longitudinal ordinal motor development data that was obtained from these children using the multilevel ordinal logistic model. METHODS: Longitudinal ordinal data are often collected in studies on motor development. For example, children or adolescents might be rated as having poor, good, or excellent performance levels in fundamental movement skills, and such ratings may be obtained yearly over time to assess changes in fundamental movement skills levels of performance. However, such longitudinal ordinal data are often analyzed using either methods for continuous outcomes, or by dichotomizing the ordinal outcome and using methods for binary data. These approaches are not optimal, and so we describe in detail the use of the multilevel ordinal logistic model for analysis of such data from the REACT project. Our intent is to provide an accessible description and application of this model for analysis of ordinal motor development data. DISCUSSION: Our analyses show both the between-subjects and within-subjects effects of age on motor development outcomes across three timepoints. The between-subjects effect of age indicate that children that are older have higher motor development ratings, relative to thoese that are younger, whereas the within-subject effect of age indicates higher motor development ratings as a child ages. It is the latter effect that is particularly of interest in longitudinal studies of motor development, and an important advantage of using the multilevel ordinal logistic model relative to more traditional methods.

Sleep and fundamental movement skills in primary schoolchildren: The REACT project.

OBJECTIVE: Whether sleep is related to fundamental movement skills (FMS) in the pediatric population is largely unknown. The objective of this study was to examine the association between sleep characteristics (duration, efficiency, regularity) and FMS proficiency levels in school-aged children. METHODS: This cross-sectional study included 996 children (mean age: 8.3 ± 1.2 years) from 25 of the 32 primary schools in Matosinhos, northern Portugal. Data collection occurred between January and June 2022. Sleep was assessed using an ActiGraph wGT3X-BT accelerometer worn on the wrist for 7 consecutive days. FMS proficiency levels were assessed in the schools with a new digital platform (Meu Educativo®) that evaluated five object control skills (dribble, kick, catch, throw, and underhand roll), with a total score ranging between 5 and 15. Multilevel ordinal logistic regression was used to test the associations between sleep characteristics and FMS proficiency levels. Covariates included age, sex, body mass index z-score, socioeconomic status, and moderate-to-vigorous physical activity. RESULTS: The results showed that sleep characteristics (duration, efficiency, and regularity) were not related to FMS proficiency. Being a boy, older age, and higher moderate-to-vigorous physical activity levels were all significantly associated with better FMS proficiency levels. There were no significant sex-by-age interactions. CONCLUSION: Sleep was not found to be related to FMS performance in children. This finding suggests that sleep is not a good correlate of FMS proficiency levels in school-aged children, and attention should be dedicated to other more important factors such as skill-learning-specific physical activity.

Sibling Resemblances in Physical Fitness in Three Distinct Regions in Peru: The Peruvian Sibling Study on Growth and Health.

We estimated sibling resemblance in health-related physical fitness (PF) and examined how individual characteristics and shared natural environment accounted for sibling similarities. The sample comprised 656 sibling pairs and 102 triplets (6-15 years of age), from three geographical areas of Peru. PF components included morphological (waist circumference, sum of skinfolds), muscular (handgrip strength, standing long jump), and motor (shuttle-run). Body mass index (BMI) and somatic maturation were also assessed. In general, sibling intraclass correlations differed significantly across sib-ship types for waist circumference and handgrip strength but were the same for sum of skinfolds, standing long jump, and shuttle-run. Further, in general, both individual characteristics and geographical area of residence significantly influenced the magnitude of sibling resemblance as well as the mean levels of PF. In conclusion, individual characteristics and shared natural environment jointly influenced the expression of PF in Peruvian siblings, revealing the importance of these features when designing individualized programs promoting fitness.

Defining R-squared measures for mixed-effects location scale models.

Ecological momentary assessment and other modern data collection technologies facilitate research on both within-subject and between-subject variability of health outcomes and behaviors. For such intensively measured longitudinal data, Hedeker et al extended the usual two-level mixed-effects model to a two-level mixed-effects location scale (MELS) model to accommodate covariates' influence as well as random subject effects on both mean (location) and variability (scale) of the outcome. However, there is a lack of existing standardized effect size measures for the MELS model. To fill this gap, our study extends Rights and Sterba's framework of R 2 $$ {R}^2 $$ measures for multilevel models, which is based on model-implied variances, to MELS models. Our proposed framework applies to two different specifications of the random location effects, namely, through covariate-influenced random intercepts and through random intercepts combined with random slopes of observation-level covariates. We also provide an R function, R2MELS, that outputs summary tables and visualization for values of our R 2 $$ {R}^2 $$ measures. This framework is validated through a simulation study, and data from a health behaviors study and a depression study are used as examples to demonstrate this framework. These R 2 $$ {R}^2 $$ measures can help researchers provide greater interpretation of their findings using MELS models.

A shared-parameter location-scale mixed model to link the responsivity in self-initiated event reports and the event-contingent Ecological Momentary Assessments.

We address the issue of (non-) responsivity of self-initiated assessments in Ecological Momentary Assessment (EMA) or other mobile health (mHealth) studies, where subjects are instructed to self-initiate reports when experiencing defined events, for example, smoking. Since such reports are self-initiated, the frequency and determinants of nonresponse to these event reports is usually unknown, however it may be suspected that nonresponse of such self-initiated reports is not random. In this case, existing methods for missing data may be insufficient in the modeling of these observed self-initiated reports. In certain EMA studies, random prompts, distinct from the self-initiated reports, may be converted to event reports. For example, such a conversion can occur if during a random prompt a subject is assessed about the event (eg, smoking) and it is determined that the subject is engaging in the event at the time of the prompt. Such converted prompts can provide some information about the subject's non-responsivity of event reporting. Furthermore, such non-responsivity can be associated with the primary longitudinal EMA outcome (eg, mood) in which case a joint modeling of the non-responsivity and the mood outcome is possible. Here, we propose a shared-parameter location-scale model to link the primary outcome model for mood and a model for subjects' non-responsivity by shared random effects which characterize a subject's mood level, mood change pattern, and mood variability. Via simulations and real data analysis, our proposed model is shown to be more informative, have better coverage of parameters, and provide better fit to the data than more conventional models.

The Mood Boost from Tobacco Cigarettes is More Erratic with the Additions of Cannabis and Alcohol.

INTRODUCTION: A large body of literature indicates that nicotine results in an acute mood "boost," including increased positive affect and decreased negative affect. Young adults frequently engage in polysubstance use of cigarettes with cannabis and alcohol-a trend that is likely to accelerate with the expanding legalization of cannabis. However, little is known about whether polysubstance use, defined here as combustible tobacco cigarette use within the same hour as cannabis and alcohol, is associated with changes in the nicotine mood boost. The present study aimed to address this gap. METHODS: Young adults (N = 202, 52% female, mean age = 21 years at time 1) provided ecological moments assessment (EMA) reports of cigarette use over two 7-day bursts spaced 1 year apart. In each report, participants rated mood levels before and after smoking, and indicated cannabis and alcohol use. Mixed-effects location-scale modeling simultaneously tested changes in mood levels and variability related to smoking events with cannabis and/or alcohol compared with smoking-only events. RESULTS: From before to after smoking, positive affect increased and negative affect decreased, on average. Overall, the additions of cannabis and/or alcohol had nonsignificant associations with these mean changes. However, polysubstance use, as well as cigarette-cannabis co-use, were each associated with significantly greater within-person variability in the positive and negative affect changes related to smoking. CONCLUSIONS: The mood benefits associated with smoking were more erratic in the contexts of polysubstance use and cigarette-cannabis co-use. Potential implications for young adults' long-term nicotine use trajectories are discussed. IMPLICATIONS: Among young adults who smoke cigarettes, the mood "boost" from smoking may be more erratic-which is to say, more likely to be either amplified or attenuated-with the additions of cannabis and alcohol together, or cannabis alone. On occasions when young adults seek out cannabis and alcohol to enhance their smoking mood boost, but instead experience a dampening effect, they might consume more nicotine, contributing over time to greater dependence. Future investigation is warranted, with particular attention to nicotine-cannabis co-use.

How acute affect dynamics impact longitudinal changes in physical activity among children.

Research examined how acute affect dynamics, including stability and context-dependency, contribute to changes in children's physical activity levels as they transition from late-childhood to early-adolescence. Children (N = 151) (ages 8-12 years at baseline) participated in an ecological momentary assessment and accelerometry study with six semi-annual bursts (7 days each) across three years. A two-stage mixed-effects multiple location-scale model tested random intercept, variance, and slope estimates for positive affect as predictors of moderate-to-vigorous physical activity (MVPA). Multi-year declines in MVPA were greater for children who had greater subject-level variance in positive affect. Children who experienced more positive affect when alone did not experience steeper declines in physical activity. Interventions aiming for long-term modifications in children's physical activity may focus on buffering the effects of within-day fluctuations in affect or tailoring programs to fit the needs of "acute dynamic process phenotypes."