Examining the Effects of Fathers' Residency Status on Childhood Obesity.

OBJECTIVE: To examine whether fathers' residency status is associated with increased BMI z-scores among young and pre-adolescent children. METHODS: Propensity score matching was used to examine the effects of fathers' residency status on child BMI z-scores for children between the ages of 2-5 and 9-11 years old. Fathers self-reported their residency status as either being residential or nonresidential, based on the amount of time they lived in the same household as the child enrolled in the study. We conducted a series of cross-sectional matched analyses using three waves of data from 1448 families who participated in the Fragile Families and Child Wellbeing Study. RESULTS: We did not find a difference in BMI z-scores among children based on their father's residency status for children between the ages of 2-5 years old but did find a marginally significant difference in BMI z-scores for children between 9 and 11 years old. CONCLUSIONS FOR PRACTICE: Our findings suggest that fathers' residency status is not associated with increased BMI z-scores among young children but may be slightly predictive of differences in BMI z-scores among pre-adolescent children. The results from our study begin to explore the scientific gains of analyzing the influence of diverse family structures on childhood obesity outcomes. Our focus on fathers' residency status adds to the literature by highlighting some of the risks and resources that fathers from diverse family structures bring to family functioning and children's health and wellbeing.

Intra-individual study of mindfulness: ecological momentary perspective in post-surgical lung cancer patients.

The period of recovery following a lung-cancer surgery presents unique challenges and psychological demands. The study utilized ecological momentary assessments (EMA) to repeatedly sample mindfulness states in a sample of mindfulness-untrained individuals following hospital discharge. Intra- and inter- individual variability was assessed to examine cancer patients' natural capacity to exhibit mindfulness states during two weeks of recovery. Fifty nine stage I lung cancer patients (61% women, mean age = 66.1, SD = 7.9) completed EMA twice a day for two weeks. Mean level of mindfulness in the sample was low and equaled .49 (SD = .51) on the 5 point scale, with older participants being less likely to endorse mindful states. Net variability in mindfulness, defined as the person-based standard deviation in momentary scores, equaled .42 (SD = .26), ranging for 0 to 1.3 and indicating very modest variability for most participants. Results of the multi-level variance partitioning model revealed 41.4% of variance in mindfulness scores at the inter-individual, 2.4% on the temporal (i.e., .2% weekly and 2.2% daily), and 56.2% on the momentary levels. Findings indicate that, for cancer patients recovering from surgery, the innate ability to exhibit mindfulness is limited. From the methodological standpoint, consideration of intra-individual variability has implications for conceptualization and design of EMA studies.

Reliability and Validity of the Vicarious Trauma Organizational Readiness Guide (VT-ORG).

The Vicarious Trauma Organizational Readiness Guide (VT-ORG) is an assessment of an organization's readiness to address vicarious trauma (VT), which is exposure to the traumatic experiences of people served. This study reports on the psychometric properties of the VT-ORG. Employees of first responder agencies (e.g., law enforcement, fire, emergency services) and victim assistance agencies are at a high risk for vicarious traumatization, which can lead to PTSD, substance use, and suicidal ideation, among other negative impacts. Organizations that do not address VT may see such effects as employee turnover, reduced efficiency, and negative work environments. The VT-ORG is an assessment tool designed to help organizations complete the first step of organizational change-conducting a needs assessment. Study participants were 3,018 employees across 13 first responder and victim assistance agencies who completed the 67-item VT-ORG and additional measures for evaluation of its validity and reliability. The VT-ORG was found to have excellent internal consistency (Cronbach's α = .98). A structural equation model demonstrated that the subscales of the VT-ORG predicted criterion measures of turnover intention, compassion satisfaction, and organizational resilience, with an overall model fit of CFI = .99, RMSEA = .053. This study found the VT-ORG to be a reliable and valid assessment of organizational responses to vicarious trauma.

Effect of a safe patient handling program on rehabilitation outcomes.

OBJECTIVE: To evaluate the effect of a safe patient handling (SPH) program on rehabilitation mobility outcomes. DESIGN: Retrospective cohort study. SETTING: A rehabilitation unit in a hospital system. PARTICIPANTS: Consecutive patients (N=1291) over a 1-year period without an SPH program in place (n=507) and consecutive patients over a 1-year period with an SPH program in place (n=784). INTERVENTIONS: The SPH program consisted of administrative policies and patient handling technologies. The policies limited manual patient handling. Equipment included ceiling- and floor-based dependent lifts, sit-to-stand assists, ambulation aides, friction-reducing devices, motorized hospital beds and shower chairs, and multihandled gait belts. MAIN OUTCOME MEASURES: The mobility subscale of the FIM. RESULTS: Patients rehabilitated in the group with SPH achieved similar outcomes to patients rehabilitated in the group without SPH. A significant difference between groups was noted for patients with initial mobility FIM scores of 15.1 and higher after controlling for initial mobility FIM score, age, length of stay, and diagnosis. Those patients performed better with SPH. CONCLUSIONS: SPH programs do not appear to inhibit recovery. Fears among therapists that the use of equipment may lead to dependence may be unfounded.

Using the time-varying effect model (TVEM) to examine dynamic associations between negative affect and self confidence on smoking urges: differences between successful quitters and relapsers.

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.

Conceptualizing and Estimating Process Speed in Studies Employing Ecological Momentary Assessment Designs: A Multilevel Variance Decomposition Approach.

Researchers have been making use of ecological momentary assessment (EMA) and other study designs that sample feelings and behaviors in real time and in naturalistic settings to study temporal dynamics and contextual factors of a wide variety of psychological, physiological, and behavioral processes. As EMA designs become more widespread, questions are arising about the frequency of data sampling, with direct implications for participants' burden and researchers' ability to capture and study dynamic processes. Traditionally, spectral analytic techniques are used for time series data to identify process speed. However, the nature of EMA data, often collected with fewer than 100 measurements per person, sampled at randomly spaced intervals, and replete with planned and unplanned missingness, precludes application of traditional spectral analytic techniques. Building on principles of variance partitioning used in the generalizability theory of measurement and spectral analysis, we illustrate the utility of multilevel variance decompositions for isolating process speed in EMA-type data. Simulation and empirical data from a smoking-cessation study are used to demonstrate the method and to evaluate the process speed of smoking urges and quitting self-efficacy. Results of the multilevel variance decomposition approach can inform process-oriented theory and future EMA study designs.

Associations between menarcheal timing and behavioral developmental trajectories for girls from age 6 to age 15.

Substantial evidence from cross-sectional and short time-span longitudinal studies exists about negative associations between early pubertal maturation on a number of psychological outcomes. The objective of the present study was to assess the association between early maturation and developmental trajectories of social skills and internalizing and externalizing problems in girls from grades 1 through 9, including pre- and post-pubertal periods. The sample came from the NICHD Study of Early Child Care and Youth Development and included 398 Caucasian and 60 African American girls. Multilevel modeling revealed early maturing Caucasian girls were at risk for higher internalizing and externalizing problems and experiencing higher levels of problems pre-pubertally. African American youth had lower social skills and internalizing problems with no group differences due to early pubertal development. Findings are discussed in light of literature on continuity of girls' psychosocial development before and during the pubertal transition.

Scalar-on-function regression for predicting distal outcomes from intensively gathered longitudinal data: Interpretability for applied scientists.

Researchers are sometimes interested in predicting a distal or external outcome (such as smoking cessation at follow-up) from the trajectory of an intensively recorded longitudinal variable (such as urge to smoke). This can be done in a semiparametric way via scalar-on-function regression. However, the resulting fitted coefficient regression function requires special care for correct interpretation, as it represents the joint relationship of time points to the outcome, rather than a marginal or cross-sectional relationship. We provide practical guidelines, based on experience with scientific applications, for helping practitioners interpret their results and illustrate these ideas using data from a smoking cessation study.

Musculoskeletal pain associated with recreational yoga participation: A prospective cohort study with 1-year follow-up.

BACKGROUND: Yoga is a popular complementary therapy for musculoskeletal pain. There are few studies however, that have examined the risks of recreational participation for causing musculoskeletal pain. OBJECTIVES: To examine the relationship between musculoskeletal pain and recreational yoga participation. METHODS: This was a prospective cohort study with one-year follow-up. Data were collected via electronic questionnaires, one year apart. Outcomes included incidence and impact of pain caused by yoga and prevalence of pain caused, exacerbated, unaffected, and improved by yoga. Predictors included age, experience, hours of participation, and intensity of participation. RESULTS: The final sample included 354 participants from two suburban yoga studios. The incidence rate of pain caused by yoga was 10.7%. More than one-third of incident cases resulted in lost yoga participation time and/or symptoms lasting more than 3 months. None of the risk factors at baseline increased the risk for subsequent incident cases of pain caused by yoga. CONCLUSIONS: Yoga can cause musculoskeletal pain. Participants may benefit from disclosure of practice to their healthcare professionals and by informing teachers of injuries they may have prior to participation. Yoga teachers should also discuss the risks for injury with their students.

Feasibility and adherence paradigm to ecological momentary assessments in urban minority youth.

All adolescents in general, including ethnic and racial minorities, report high levels of cell phone use, making mobile technology a useful tool for assessment and intervention. Known health and education disparities based on minority status motivated us to conduct an in-depth investigation regarding feasibility of and adherence to the ecological momentary assessment (EMA) research protocol, studying daily life of urban minority youth. In addition, this paper presents a methodological approach to conceptualizing and reporting adherence in EMA studies. The sample was comprised of 126 youth (41.3% boys; 40.5% 7th and 59.5% 8th graders; 75.4% African American, and 20.6% Hispanic) who carried a mobile phone for 10 days, including 2 weekends and reported on activities, moods, and attitudes. Mean level of adherence was 81% for momentary and 93.8% for daily assessments; it decreased over time and was higher during the week compared to weekends. Adherence was lower on days when participants reported high levels of negative affect and on days when they were engaged in physical activities. Our findings underscore the importance of differentiating between human and technology-related factors when computing adherence rates and portray adherence as a complex and dynamic construct that can vary across individuals. Specific study recommendations and methodological discussion provide guidelines for designing future studies. (PsycINFO Database Record

Biomechanical Deficit Profiles Associated with ACL Injury Risk in Female Athletes.

PURPOSE: This study aimed to quantify the prevalence of biomechanical deficit patterns associated with anterior cruciate ligament injury risk and their interconnections in a large cohort of female athletes during an unanticipated cutting task. METHODS: High school female athletes (n = 721) performed an unanticipated cutting task in the biomechanics laboratory. Trunk and lower extremity three-dimensional kinetics and kinematics were measured and entered into a latent profile analysis model. RESULTS: Approximately 40% of female athletes demonstrated no biomechanical deficits and were categorized into the low risk group. The second most prevalent profile (24%) demonstrated a combination of high quadriceps and leg dominance deficits and was labeled as quadriceps-leg. The third most prevalent profile (22%) demonstrated a combination of trunk and leg dominance deficits and to lesser extent ligament dominance deficits and was labeled as trunk-leg-ligament. Finally, the fourth profile (14%) demonstrated very high ligament dominance deficits only and it was labeled as ligament dominance profile. CONCLUSIONS: This is the first study to identify the most common biomechanical profiles associated with anterior cruciate ligament injury during a cutting task in a large cohort of female athletes. Approximately 60% of female athletes belong to one of the high-risk profiles. With the exception of the ligament dominance profile, the current analysis indicates that risk profiles consist of a combination of biomechanical deficits. The findings provide important insight into the prevalence of biomechanical deficits and future directions for the development of injury prevention programs. The findings can be used to guide the development of quick and easy tests that accurately categorize athletes into one of the profiles and subsequently prescribe tailored injury prevention programs that will be more effective and efficient than the current generic ones.

Modeling intensive longitudinal data with mixtures of nonparametric trajectories and time-varying effects.

Behavioral scientists increasingly collect intensive longitudinal data (ILD), in which phenomena are measured at high frequency and in real time. In many such studies, it is of interest to describe the pattern of change over time in important variables as well as the changing nature of the relationship between variables. Individuals' trajectories on variables of interest may be far from linear, and the predictive relationship between variables of interest and related covariates may also change over time in a nonlinear way. Time-varying effect models (TVEMs; see Tan, Shiyko, Li, Li, & Dierker, 2012) address these needs by allowing regression coefficients to be smooth, nonlinear functions of time rather than constants. However, it is possible that not only observed covariates but also unknown, latent variables may be related to the outcome. That is, regression coefficients may change over time and also vary for different kinds of individuals. Therefore, we describe a finite mixture version of TVEM for situations in which the population is heterogeneous and in which a single trajectory would conceal important, interindividual differences. This extended approach, MixTVEM, combines finite mixture modeling with non- or semiparametric regression modeling, to describe a complex pattern of change over time for distinct latent classes of individuals. The usefulness of the method is demonstrated in an empirical example from a smoking cessation study. We provide a versatile SAS macro and R function for fitting MixTVEMs.

Modeling nonlinear time-dependent treatment effects: an application of the generalized time-varying effect model (TVEM).

OBJECTIVE: The goal of this article is to introduce to social and behavioral scientists the generalized time-varying effect model (TVEM), a semiparametric approach for investigating time-varying effects of a treatment. The method is best suited for data collected intensively over time (e.g., experience sampling or ecological momentary assessments) and addresses questions pertaining to effects of treatment changing dynamically with time. Thus, of interest is the description of timing, magnitude, and (nonlinear) patterns of the effect. METHOD: Our presentation focuses on practical aspects of the model. A step-by-step demonstration is presented in the context of an empirical study designed to evaluate effects of surgical treatment on quality of life among early stage lung cancer patients during posthospitalization recovery (N = 59; 61% female, M age = 66.1 years). Frequency and level of distress associated with physical symptoms were assessed twice daily over a 2-week period, providing a total of 1,544 momentary assessments. RESULTS: Traditional analyses (analysis of covariance [ANCOVA], repeated-measures ANCOVA, and multilevel modeling) yielded findings of no group differences. In contrast, generalized TVEM identified a pattern of the effect that varied in time and magnitude. Group differences manifested after Day 4. CONCLUSIONS: Generalized TVEM is a flexible statistical approach that offers insight into the complexity of treatment effects and allows modeling of nonnormal outcomes. The practical demonstration, shared syntax, and availability of a free set of macros aim to encourage researchers to apply TVEM to complex data and stimulate important scientific discoveries.

Randomized trial of a presurgical scheduled reduced smoking intervention for patients newly diagnosed with cancer.

OBJECTIVE: Cancer patients who smoke are advised to quit smoking to reduce treatment complications and future cancer risk. This study's main objective was to evaluate the efficacy of a novel, presurgical cessation intervention in newly diagnosed cancer patients scheduled for surgical hospitalization. METHOD: We conducted a parallel-arm, randomized controlled trial comparing the efficacy of our hospital-based, tobacco cessation "best practices" treatment model (BP; cessation counseling and nicotine replacement therapy) with BP enhanced by a behavioral tapering regimen (scheduled reduced smoking; BP + SRS) administered by a handheld computer before hospitalization for surgery. Cessation outcomes were short (hospital admission and 3 months) and longer-term (6 months) biochemically verified smoking abstinence. We hypothesized that BP + SRS would be superior to BP alone. One hundred eighty-five smokers were enrolled. RESULTS: Overall, 7-day-point prevalence, confirmed abstinence rates at 6 months for BP alone (32%) and BP + SRS (32%) were high; however, no main effect of treatment was observed. Patients who were older and diagnosed with lung cancer were more likely to quit smoking. CONCLUSION: Compared to best practices for treating tobacco dependence, a presurgical, scheduled reduced smoking intervention did not improve abstinence rates among newly diagnosed cancer patients.reserved).

Poisson Growth Mixture Modeling of Intensive Longitudinal Data: An Application to Smoking Cessation Behavior.

Intensive longitudinal data (ILD) have become increasingly common in the social and behavioral sciences; count variables, such as the number of daily smoked cigarettes, are frequently-used outcomes in many ILD studies. We demonstrate a generalized extension of growth mixture modeling (GMM) to Poisson-distributed ILD for identifying qualitatively distinct trajectories in the context of developmental heterogeneity in count data. Accounting for the Poisson outcome distribution is essential for correct model identification and estimation. In addition, setting up the model in a way that is conducive to ILD measures helps with data complexities - large data volume, missing observations, and differences in sampling frequency across individuals. We present technical details of model fitting, summarize an empirical example of patterns of smoking behavior change, and describe research questions the generalized GMM helps to address.

A time-varying effect model for intensive longitudinal data.

Understanding temporal change in human behavior and psychological processes is a central issue in the behavioral sciences. With technological advances, intensive longitudinal data (ILD) are increasingly generated by studies of human behavior that repeatedly administer assessments over time. ILD offer unique opportunities to describe temporal behavioral changes in detail and identify related environmental and psychosocial antecedents and consequences. Traditional analytical approaches impose strong parametric assumptions about the nature of change in the relationship between time-varying covariates and outcomes of interest. This article introduces time-varying effect models (TVEMs) that explicitly model changes in the association between ILD covariates and ILD outcomes over time in a flexible manner. In this article, we describe unique research questions that the TVEM addresses, outline the model-estimation procedure, share a SAS macro for implementing the model, demonstrate model utility with a simulated example, and illustrate model applications in ILD collected as part of a smoking-cessation study to explore the relationship between smoking urges and self-efficacy during the course of the pre- and postcessation period.