Studying Multivariate Change Using Multilevel Models and Latent Curve Models

Disease stage-specific atrophy markers in Alzheimer's disease

INTRODUCTION

Structural MRI often lacks diagnostic, prognostic, and monitoring value in Alzheimer's disease (AD), particularly in early disease stages. To improve its utility, we aimed to identify optimal MRI readouts for different use cases.

METHODS

We included 363 older adults; healthy controls (HC) who were negative or positive for amyloidbeta (Aβ) and Aβ-positive patients with subjective cognitive decline (SCD), mild cognitive impairment, or dementia of the Alzheimer type. MRI and neuropsychological assessments were administered annually for up to three years.

RESULTS

Accelerated atrophy of distinct MTL subregions was evident already during preclinical AD. Symptomatic disease stages most notably differed in their hippocampal and parietal atrophy signatures. Associations of atrophy markers and cognitive inventories varied by intended use and disease stage.

DISCUSSION

With the appropriate readout, MRI can detect abnormal atrophy already during preclinical AD. To optimize performance, MRI readouts should be tailored to the targeted disease stage and intended use.

Corresponding Changes in Sleep and Discrimination: A Three-year Longitudinal Study Among Ethnically/Racially Diverse Adolescents

Although research has established the immediate, detrimental impact of discrimination on sleep, how changes in experiences of discrimination may be related to changes in sleep duration over multiple years is less clear. This three-year longitudinal study investigated: (1) intercept-only and linear trajectories of sleep and everyday discrimination across three years of high school; (2) ethnic/racial differences in these trajectories; and (3) the associations between changes in sleep and changes in everyday discrimination. The sample consisted of ethnically/racially minoritized adolescents from five northeast U.S. public high schools (n = 329; 70% female, 30% male, 0% non-binary; 42% Asian, 21% Black, 37% Latiné; Mage = 14.72, SD = 0.54). Latent growth curve models found that both sleep duration and everyday discrimination declined linearly throughout the first three years of high school and varied by race/ethnicity. Asian adolescents reported longer sleep duration in the 9th grade relative to Black and Latiné adolescents but underwent a significant decline such that these differences were no longer significant in the 10th and 11th grades. In addition, Black and Latiné, but not Asian, adolescents reported a significant decline in discrimination from the 9th-11th grades. Although average sleep duration declined for the entire sample, slower declines in discrimination were associated with faster decreases in sleep duration. This was particularly salient among Black adolescents. The current study contributes to research on ethnic/racial disparities in sleep by highlighting that everyday discrimination can have both an immediate and cumulative detrimental impact on sleep duration.

The role of emotion dysregulation and interpersonal dysfunction in nonsuicidal self-injury during dialectical behavior therapy for borderline personality disorder

Dialectical Behaviour Therapy (DBT) is an evidence-based treatment for borderline personality disorder (BPD), with findings demonstrating improvements in various BPD features and related behaviours, such as nonsuicidal self-injury (NSSI). Theory and research suggest that reductions in emotion dysregulation and interpersonal dysfunction could account for at least some of the reduction in NSSI observed during the course of DBT. The current research investigated: 1) the trajectory of changes in emotion dysregulation, interpersonal dysfunction, and NSSI over the course of DBT, and 2) whether changes in emotion dysregulation mediate the relationship between changes in interpersonal dysfunction and changes in NSSI over treatment. One hundred and twenty individuals with BPD enrolled in a multi-site randomized-clinical trial were assessed at five timepoints over 12 months of standard DBT. Results indicated that interpersonal dysfunction and NSSI decreased over the course of DBT. Emotion dysregulation decreased in a quadratic manner such that most of the gains in emotion dysregulation occurred in earlier phases of DBT. Although changes in interpersonal dysfunction predicted changes in emotion dysregulation, changes in emotion dysregulation did not mediate the relationship between changes in interpersonal dysfunction and changes in NSSI.

Recalling and anticipating positive events to improve the positive affect and mental health of adolescents: A cluster randomized controlled trial in secondary schools

This cluster randomized controlled trial examined the effectiveness of Positive Events Training (PET), a combined group training aimed at simultaneously improving positive autobiographical memory (AM) and episodic future thinking (EFT) among adolescents (12-16 years). Delivered as a universal school-based program, PET was compared with an active (creative writing) control group (CREAT). Effects on resilience, wellbeing, positive emotions, emotional response styles towards positive emotions (savoring, dampening), anhedonia, depressive symptoms, and multiple AM and EFT indices were examined. Adolescents (NPET = 95, NCREAT = 93) completed self-report scales at baseline, post-training and two-month follow-up. Multilevel models revealed that PET led to significant improvements in certain AM and EFT skills. Moreover, a decrease in anhedonia was observed at post-training. However, this effect did not withstand correction for multiple testing. Absence of changes in the other outcomes should be interpreted within the context of the universal school-based approach and the potential limited scope for detectable changes. Exploratory analyses suggest the importance of further investigating PET's potential in addressing positive affect dysregulations in indicated samples, and exploring perceived likelihood of generated future events and dampening as potential underlying mechanisms. Study limitations and future directions to maximize the demonstrated potential of PET are discussed.

Considering between- and within-person relations in auto-regressive cross-lagged panel models for developmental data

Longitudinal data can provide inferences at both the between-person and within-person levels of analysis, but only to the extent that the statistical models chosen for data analysis are specified to adequately capture these distinct sources of association. The present work focuses on auto-regressive cross-lagged panel models, which have long been used to examine time-lagged reciprocal relations and mediation among multiple variables measured repeatedly over time. Unfortunately, many common implementations of these models fail to distinguish between-person associations among individual differences in the variables' amounts and changes over time, and thus confound between-person and within-person relations either partially or entirely, leading to inaccurate results. Furthermore, in the increasingly complex model variants that continue to be developed, what is not easily appreciated is how substantial differences in interpretation can be created by what appear to be trivial differences in model specification. In the present work, we aimed to (a) help analysts become better acquainted with the some of the more common model variants that fall under this larger umbrella, and (b) explicate what characteristics of one's data and research questions should be considered in selecting a model. Supplementary Materials include annotated model syntax and output using Mplus, lavaan in R, and sem in Stata to help translate these concepts into practice.

Examining the Bidirectional Nature of Loneliness and Anxiety Among Older Adults in Daily Life

OBJECTIVES

Loneliness in later life increases the risk for adverse health outcomes; however, less is known about how loneliness is maintained. Anxiety may play an important role in maintaining loneliness, but little is known about how this connection plays out over time in daily life. This study thus focused on the within-person associations between momentary loneliness and anxiety among older adults.

METHODS

Participants were 317 diverse older adults (40% Black; 13% Hispanic, mean age = 77.45 years, 67% women) systematically recruited from the Bronx, NY, who completed ecological momentary assessments 5 times daily for 14 consecutive days. Multilevel models tested bidirectional contemporaneous, momentary cross-lagged (t - 1), day-level cross-lagged (average day to end of day), and day-to-day cross-lagged associations between loneliness and anxiety. Separate sensitivity analyses controlled for concurrent overall mood valence or depressed state. Gender and mild cognitive impairment (MCI) status were tested as moderators at all timescales.

RESULTS

Significant bidirectional associations between loneliness and anxiety were found at the contemporaneous and momentary cross-lagged (t - 1) timescales. Higher average daily loneliness predicted higher end-of-day anxiety, but not vice versa. Loneliness and anxiety were not significantly associated from day to day. Sensitivity analyses revealed some associations varied depending on inclusion of either concurrent mood valence or depressed state. Neither gender nor MCI status moderated associations at any timescale.

DISCUSSION

Findings shed light on the complex temporal ordering of loneliness and anxiety in daily life and extend contemporary theoretical notions of loneliness, including the possibility of interventions that target key moments in daily life.

Bringing Order to Life: Temporal Order Effects during the Recall of Important Autobiographical Memories in Young and Old Adults

OBJECTIVE

The present study investigated whether younger and older adults differ in the extent to which they order their important autobiographical memories (AMs) in a chronological way during recall. Moreover, the number of autobiographical memories to be recalled was systematically varied in order to examine whether manipulating the size of the search sample affects the use of a chronological recall strategy.

METHODS

Data come from 118 younger adults (M = 23.12, SD = 3.33) and 124 older adults (M = 69.79, SD = 8.94) who recalled either seven or thirteen important AMs.

RESULTS

Using multilevel linear growth models, a temporal order effect for younger and older adults was found. For older adults, the temporal order effect was much more pronounced. The number of recalled events, however, did not affect the temporal order effect.

CONCLUSION

Our findings point to a higher need for a structured search or a stronger engagement in autobiographical reasoning processes in older age. Furthermore, asking for important AMs encourages participants to provide a comprehensive overview of their life independent of the number of important AMs to be recalled.

The Hitchhiker's guide to longitudinal models: A primer on model selection for repeated-measures methods

Longitudinal data are becoming increasingly available in developmental neuroimaging. To maximize the promise of this wealth of information on how biology, behavior, and cognition change over time, there is a need to incorporate broad and rigorous training in longitudinal methods into the repertoire of developmental neuroscientists. Fortunately, these models have an incredibly rich tradition in the broader developmental sciences that we can draw from. Here, we provide a primer on longitudinal models, written in a beginner-friendly (and slightly irreverent) manner, with a particular focus on selecting among different modeling frameworks (e.g., multilevel versus latent curve models) to build the theoretical model of development a researcher wishes to test. Our aims are three-fold: (1) lay out a heuristic framework for longitudinal model selection, (2) build a repository of references that ground each model in its tradition of methodological development and practical implementation with a focus on connecting researchers to resources outside traditional neuroimaging journals, and (3) provide practical resources in the form of a codebook companion demonstrating how to fit these models. These resources together aim to enhance training for the next generation of developmental neuroscientists by providing a solid foundation for future forays into advanced modeling applications.

Multilevel SEM with random slopes in discrete data using the pairwise maximum likelihood

Pairwise maximum likelihood (PML) estimation is a promising method for multilevel models with discrete responses. Multilevel models take into account that units within a cluster tend to be more alike than units from different clusters. The pairwise likelihood is then obtained as the product of bivariate likelihoods for all within-cluster pairs of units and items. In this study, we investigate the PML estimation method with computationally intensive multilevel random intercept and random slope structural equation models (SEM) in discrete data. In pursuing this, we first reconsidered the general 'wide format' (WF) approach for SEM models and then extend the WF approach with random slopes. In a small simulation study we the determine accuracy and efficiency of the PML estimation method by varying the sample size (250, 500, 1000, 2000), response scales (two-point, four-point), and data-generating model (mediation model with three random slopes, factor model with one and two random slopes). Overall, results show that the PML estimation method is capable of estimating computationally intensive random intercept and random slopes multilevel models in the SEM framework with discrete data and many (six or more) latent variables with satisfactory accuracy and efficiency. However, the condition with 250 clusters combined with a two-point response scale shows more bias.

Adaptive data-driven selection of sequences of biological and cognitive markers in pre-clinical diagnosis of dementia

Effective clinical decision procedures must balance multiple competing objectives such as time-to-decision, acquisition costs, and accuracy. We describe and evaluate POSEIDON, a data-driven method for PrOspective SEquentIal DiagnOsis with Neutral zones to individualize clinical classifications. We evaluated the framework with an application in which the algorithm sequentially proposes to include cognitive, imaging, or molecular markers if a sufficiently more accurate prognosis of clinical decline to manifest Alzheimer's disease is expected. Over a wide range of cost parameter data-driven tuning lead to quantitatively lower total cost compared to ad hoc fixed sets of measurements. The classification accuracy based on all longitudinal data from participants that was acquired over 4.8 years on average was 0.89. The sequential algorithm selected 14 percent of available measurements and concluded after an average follow-up time of 0.74 years at the expense of 0.05 lower accuracy. Sequential classifiers were competitive from a multi-objective perspective since they could dominate fixed sets of measurements by making fewer errors using less resources. Nevertheless, the trade-off of competing objectives depends on inherently subjective prescribed cost parameters. Thus, despite the effectiveness of the method, the implementation into consequential clinical applications will remain controversial and evolve around the choice of cost parameters.

Conceptualizing and Examining Change in Communication Research

Communication research often focuses on processes of communication, such as how messages impact individuals over time or how interpersonal relationships develop and change. Despite their importance, these change processes are often implicit in much theoretical and empirical work in communication. Intensive longitudinal data are becoming increasingly feasible to collect and, when coupled with appropriate analytic frameworks, enable researchers to better explore and articulate the types of change underlying communication processes. To facilitate the study of change processes, we (a) describe advances in data collection and analytic methods that allow researchers to articulate complex change processes of phenomena in communication research, (b) provide an overview of change processes and how they may be captured with intensive longitudinal methods, and (c) discuss considerations of capturing change when designing and implementing studies. We are excited about the future of studying processes of change in communication research, and we look forward to the iterations between empirical tests and theory revision that will occur as researchers delve into studying change within communication processes.

Extracellular Vesicle-Encapsulated microRNAs as Novel Biomarkers of Lung Health

Rationale: Early detection of respiratory diseases is critical to facilitate delivery of disease-modifying interventions. Extracellular vesicle-enriched microRNAs (EV-miRNAs) may represent reliable markers of early lung injury. Objectives: Evaluate associations of plasma EV-miRNAs with lung function. Methods: The prospective NAS (Normative Aging Study) collected plasma EV-miRNA measurements from 1996-2015 and spirometry every 3-5 years through 2019. Associations of EV-miRNAs with baseline lung function were modeled using linear regression. To complement the individual miRNA approach, unsupervised machine learning was used to identify clusters of participants with distinct EV-miRNA profiles. Associations of EV-miRNA profiles with multivariate latent longitudinal lung function trajectories were modeled using log binomial regression. Biological functions of significant EV-miRNAs were explored using pathway analyses. Results were replicated in an independent sample of NAS participants and in the HEALS (Health Effects of Arsenic Longitudinal Study). Measurements and Main Results: In the main cohort of 656 participants, 51 plasma EV-miRNAs were associated with baseline lung function (false discovery rate-adjusted P value < 0.05), 28 of which were replicated in the independent NAS sample and/or in the HEALS cohort. A subset of participants with distinct EV-miRNA expression patterns had increased risk of declining lung function over time, which was replicated in the independent NAS sample. Significant EV-miRNAs were shown in pathway analyses to target biological pathways that regulate respiratory cellular immunity, the lung inflammatory response, and airway structural integrity. Conclusions: Plasma EV-miRNAs may represent a robust biomarker of subclinical lung injury and may facilitate early identification and treatment of patients at risk of developing overt lung disease.

Can Clinical Postpartum Muscle Assessment Help Predict the Severity of Postpartum Pelvic Girdle Pain? A Prospective Cohort Study

OBJECTIVE

The purpose of this study was to evaluate whether the clinical assessment of pelvic floor muscles and the diastasis recti abdominis could predict the severity of pelvic girdle pain during the first year postpartum.

METHODS

Between 2018 and 2020, 504 women were recruited to this prospective longitudinal cohort study. At 2 to 3 months postpartum, their pelvic floor muscles and diastasis recti abdominis were assessed using vaginal palpation, observation, and caliper measurement. The participants completed the Pelvic Girdle Questionnaire (PGQ) at 2 to 3, 6, 9, and 12 months postpartum. Mixed-effect models were used to determine how the results of pelvic floor muscle and diastasis recti abdominis assessments predicted the PGQ score. A sub-analysis for middle to high PGQ scores was conducted.

RESULTS

Maximal voluntary pelvic floor muscle contractions ≥3 (Modified Oxford Scale, scored from 0 to 5) predicted a decreased PGQ score (β = -3.13 [95% CI = -5.77 to -0.48]) at 2 to 3 months postpartum, with a higher prediction of a middle to high PGQ score (β = -6.39). Diastasis recti abdominis width did not have any significant correlation with the PGQ score. A sub-analysis showed that a diastasis recti abdominis width ≥35 mm predicted an increased PGQ score (β = 5.38 [95% CI = 1.21 to 9.55]) in women with pelvic girdle pain.

CONCLUSION

The distinction between weak and strong maximal voluntary pelvic floor muscle contractions is an important clinical assessment in women with postpartum pelvic girdle pain. The exact diastasis recti abdominis width, measured in millimeters, showed no clinical relevance. However, a diastasis recti abdominis width ≥35 mm was associated with a higher PGQ score, and further research about this cutoff point in relation to pain is needed.

IMPACT

This study highlights the importance of clinical assessment of pelvic floor muscles in patients with postpartum pelvic girdle pain. A better understanding of the role of this muscle group will enable more effective physical therapist treatment of pelvic girdle pain.

ECT-related anxiety during maintenance ECT: A prospective study

OBJECTIVE

Despite the established safety of electroconvulsive therapy (ECT), ECT-related anxiety (ERA) remains one of the most distressing complications of ECT. ERA is reported to diminish during an acute course of ECT, but it was never studied during maintenance ECT (M-ECT). Our aim was to study the trajectories of ERA during M-ECT and how they differ from trajectories during the acute course.

METHODS

Thirty-nine patients with unipolar or bipolar depression, retained for M-ECT after an acute ECT course, were included. ERA was assessed the morning before each ECT session using the ECT-related Anxiety Questionnaire (ERAQ).

RESULTS

ERA remained stable during M-ECT (RC = -0.05 (SE = 0.06), t(8.35) = -0.86, p = 0.42), while ERA declined significantly during the acute course (RC = -0.85 (SE = 0.30), t(33.6) = -2.81, p = 0.0082). During the acute course, patients with a psychotic depression were more anxious at baseline (t(32)= -2.42, p = 0.02), and showed a significant decline in ERAQ scores (RC = -1.65 (SE = 0.46), t(31.6) = -3.56, p = 0.0012), whereas patients with a non-psychotic depression were less anxious at baseline and retained stable ERAQ scores during the acute course (RC = -0.06 (SE = 0.41), t(32.1) = -0.14, p = 0.89). Whereas a correlation (r = 0.48) was noticed between the decline of depression severity and ERA during the acute course, this was not the case during M-ECT.

CONCLUSION

ERA runs a stable course during M-ECT, after having decreased during the acute course. During the acute course, ERA trajectories differed significantly between patients with a psychotic and non-psychotic depression. Decline of depression severity and ERA are significantly connected during the acute course of ECT. Both depression severity and ERA remain stable during M-ECT.

Ecologically unequal exchange and disparate death rates attributable to air pollution: A comparative study of 169 countries from 1991 to 2017

Ambient air pollution is among the most pressing environmental problems in our contemporary world that poses significant risks to global ecological and public health. This study analyzes cross-national heterogeneities in trajectories of death rates attributable to ambient air pollution. Compiling panel data from the Global Burden of Disease (GBD) study, the Direction of Trade Statistics (DOTS), and the World Development Indicators, we create a dataset that tracks 169 countries from 1991 to 2017. Using growth curve models (GCMs), we estimate country-specific trajectories of death rates attributable to air pollution, and condition them on time-invariant and time-varying independent variables. The results suggest that while the global death rate attributable to air pollution has been continuously decreasing, there are heterogeneities in countries' death rate trajectories based on their geographic location and position in the world economy. High-income countries of the global North have perpetually witnessed lower death rates attributable to air pollution compared to middle- and low-income countries of the global South. Moreover, our results indicate that increased export to high-income countries, as a proxy for ecologically unequal exchange, leads to higher death rates from air pollution in middle- and low-income countries.

Effectiveness and cost-effectiveness of a web-based routine assessment with integrated recommendations for action for depression and anxiety (RehaCAT+): protocol for a cluster randomised controlled trial for patients with elevated depressive symptoms in rehabilitation facilities

INTRODUCTION

The integration of a web-based computer-adaptive patient-reported outcome test (CAT) platform with persuasive design optimised features including recommendations for action into routine healthcare could provide a promising way to translate reliable diagnostic results into action. This study aims to evaluate the effectiveness and cost-effectiveness of such a platform for depression and anxiety (RehaCAT+) compared with the standard diagnostic system (RehaCAT) in cardiological and orthopaedic health clinics in routine care.

METHODS AND ANALYSIS

A two-arm, pragmatic, cluster-randomised controlled trial will be conducted. Twelve participating rehabilitation clinics in Germany will be randomly assigned to a control (RehaCAT) or experimental group (RehaCAT+) in a 1:1 design. A total sample of 1848 participants will be recruited across all clinics. The primary outcome, depression severity at 12 months follow-up (T3), will be assessed using the CAT Patient-Reported Outcome Measurement Information System Emotional Distress-Depression Item set. Secondary outcomes are depression at discharge (T1) and 6 months follow-up (T2) as well as anxiety, satisfaction with participation in social roles and activities, pain impairment, fatigue, sleep, health-related quality of life, self-efficacy, physical functioning, alcohol, personality and health economic-specific general quality of life and socioeconomic cost and benefits at T1-3. User behaviour, acceptance, facilitating and hindering factors will be assessed with semistructured qualitative interviews. Additionally, a smart sensing substudy will be conducted, with daily ecological momentary assessments and passive collection of smartphone usage variables. Data analysis will follow the intention-to-treat principle with additional per-protocol analyses. Cost-effectiveness analyses will be conducted from a societal perspective and the perspective of the statutory pension insurance.

ETHICS AND DISSEMINATION

The study will be conducted according to the Declaration of Helsinki. The Ethics Committee of Ulm University, has approved the study (on 24 February 2021 ref. 509/20). Written informed consent will be obtained for all participants. Results will be published via peer-reviewed journals.

TRIAL REGISTRATION NUMBER

DRKS00027447.

Adapting the multilevel model for estimation of the reliable change index (RCI) with multiple timepoints and multiple sources of error

OBJECTIVE

One of the primary tools in the assessment of individual-level patient outcomes is Jacobson and Truax, (1991's) Reliable Change Index (RCI). Recent efforts to optimize the RCI have revolved around three issues: (a) extending the RCI beyond two timepoints, (b) estimating the RCI using scale scores from item response theory or factor analysis and (c) estimation of person- and time-specific standard errors of measurement.

METHOD

We present an adaptation of a two-stage procedure, a measurement error-corrected multilevel model, as a tool for RCI estimation (with accompanying Statistical Analysis System syntax). Using DASS-21 data from a community-based mental health center (N = 379), we illustrate the potential for the model as unifying framework for simultaneously addressing all three limitations in modeling individual-level RCI estimates.

RESULTS

Compared to the optimal-fitting RCI model (moderated nonlinear factor analysis scoring with measurement error correction), an RCI model that uses DASS-21 total scores produced errors in RCI inferences in 50.8% of patients; this was largely driven by overestimation of the proportion of patients with statistically significant improvement.

CONCLUSION

Estimation of the RCI can now be enhanced by the use of latent variables, person- and time-specific measurement errors, and multiple timepoints.

Dyadic analysis and the reciprocal one-with-many model: Extending the study of interpersonal processes with intensive longitudinal data

Newly available data streams from experience sampling studies and social media are providing new opportunities to study individuals' dyadic relations. The "one-with-many" (OWM) model (Kenny et al., 2006; Kenny & Winquist, 2001) was specifically constructed for and is used to examine features of multiple dyadic relationships that one set of focal persons (e.g., therapists, physicians) has with others (e.g., multiple clients, multiple patients). Originally, the OWM model was constructed for and applied to cross-sectional data. However, the model can be extended to accommodate and may be particularly useful for the analysis of intensive repeated measures data now being obtained through experience sampling and social media. This article (a) provides a practical tutorial on fitting the OWM model, (b) describes how the OWM model is extended for analysis of repeated measures data, and (c) illustrates application of the OWM model using reports about interpersonal behavior and benefits individuals experienced in 64,111 social interactions during 9 weeks of study (N = 150). Our presentation highlights the utility of the OWM model for examining interpersonal processes in everyday life. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

COVID-19 vaccine hesitancy: The effects of combining direct and indirect online opinion cues on psychological reactance to health campaigns

This study aims to examine whether and how user-generated comments and reaction emojis on COVID-19 vaccine-promoting Facebook posts induce psychological reactance to posts and vaccine hesitancy in audiences of the posts. An online experiment including 465 American adults showed that, compared with COVID-19 vaccine promotion posts accompanied by pro-vaccine comments, those accompanied by anti-vaccine comments provoked greater reactance in audiences through the mediating effects of bandwagon perception and the presumed influence of the posts on others. Greater reactance, in turn, increased audiences' COVID-19 vaccine hesitancy. Additionally, reaction emojis altered the comments' effects such that pro-vaccine comments triggered less reactance than anti-vaccine comments when the pro-vaccine comments were accompanied by agreement emojis (i.e., "like" and "love"); whereas there was no significant difference between pro-vaccine comments and anti-vaccine comments in reactance when the pro-vaccine comments were accompanied by rejection emojis (i.e., "angry" and "sad"). Furthermore, audiences' pre-existing attitudes did not affect the effects of opinion cues on their' reactance and vaccine hesitancy.

Impact of attention-deficit/hyperactivity disorder comorbidity on longitudinal course in Internet gaming disorder: a 3-year clinical cohort study

BACKGROUND

Although attention-deficit/hyperactivity disorder (ADHD) symptoms were identified as a key risk factor for Internet gaming disorder (IGD), the effect of ADHD comorbidity on longitudinal course of IGD in the clinical population remains to be further examined. This study aimed to investigate whether ADHD comorbidity in IGD patients affects the recovery, recurrence rates, and trajectories of IGD symptoms, and examine the relationship between the changes in IGD and ADHD symptoms.

METHODS

The study included 128 IGD patients without any psychiatric comorbidities (pure-IGD group) and 127 IGD patients with comorbid ADHD (ADHD-IGD group) aged 11 to 42 years. IGD and ADHD were diagnosed according to DSM-5 criteria at enrollment. Participants were offered 8-week treatment with additional care provided as needed and followed up over a 3-year period. IGD diagnosis was reassessed annually and used as a dichotomous outcome. The severity of IGD and ADHD symptoms was measured using the Young Internet Addiction Scale and the Korean ADHD rating scale, respectively, at baseline and each annual follow-up.

RESULTS

The recovery rates of IGD by Year 3 were 60% and 93% in ADHD-IGD and in pure-IGD groups, respectively. The ADHD-IGD group showed lower rates of recovery, higher odds of recurrence within 1 year, and higher severity of IGD symptoms over time than the pure-IGD group. Family environment was also associated with the trajectories of IGD symptoms. The changes in ADHD symptoms were significantly associated with the changes in IGD symptoms.

CONCLUSIONS

This study found that ADHD comorbidity in IGD patients was associated with poor clinical course of IGD and that the changes in ADHD symptoms were associated with the changes in IGD symptoms over time. Our findings suggest that evaluation and treatment of ADHD symptoms and family environment in IGD patients may be important in improving the prognosis of IGD.

Longitudinal Analysis of Patient-Reported Outcomes in Clinical Trials: Applications of Multilevel and Multidimensional Item Response Theory

With decades of advance research and recent developments in the drug and medical device regulatory approval process, patient-reported outcomes (PROs) are becoming increasingly important in clinical trials. While clinical trial analyses typically treat scores from PROs as observed variables, the potential to use latent variable models when analyzing patient responses in clinical trial data presents novel opportunities for both psychometrics and regulatory science. An accessible overview of analyses commonly used to analyze longitudinal trial data and statistical models familiar in both psychometrics and biometrics, such as growth models, multilevel models, and latent variable models, is provided to call attention to connections and common themes among these models that have found use across many research areas. Additionally, examples using empirical data from a randomized clinical trial provide concrete demonstrations of the implementation of these models. The increasing availability of high-quality, psychometrically rigorous assessment instruments in clinical trials, of which the Patient-Reported Outcomes Measurement Information System (PROMIS®) is a prominent example, provides rare possibilities for psychometrics to help improve the statistical tools used in regulatory science.

Multi-Level Multi-Growth Models: New opportunities for addressing developmental theory using advanced longitudinal designs with planned missingness

Longitudinal models have become increasingly popular in recent years because of their power to test theoretically derived hypotheses by modeling within-person processes with repeated measures. Growth models constitute a flexible framework for modeling a range of complex trajectories across time in outcomes of interest, including non-linearities and time-varying covariates. However, these models can be expanded to include the effects of multiple growth processes at once on a single outcome. Here, I outline such an extension, showing how multiple growth processes can be modeled as a specific case of the general ability to include time-varying covariates in growth models. I show that this extension of growth models cannot be accomplished by statistical models alone, and that study design plays a crucial role in allowing for proper parameter recovery. I demonstrate these principles through simulations to mimic important theoretical conditions where modeling the effects of multiple growth processes can address developmental theory including, disaggregating the effects of age and practice or treatment in repeated assessments and modeling age- and puberty-related effects during adolescence. I compare how these models behave in two common longitudinal designs, cohort and accelerated, and how planned missingness in observations is key to parameter recovery. I conclude with directions for future substantive research using the method outlined here.

Order effects in the recall of autobiographical memories: evidence for an organisation along temporal and emotional features

Investigating the recall process of autobiographical memories (AMs) and, particularly, the order in which AMs are recalled has the potential to shed light on the organisation of autobiographical memory. However, research on order effects in the recall of AMs is relatively rare. Moreover, to date, no study addressed the question of where emotion fits into the organisation. The present study aimed to close this gap by examining whether emotional valence serves as one organising principle. Data come from 117 older adults (M = 74.11; SD = 7.06) who reported up to 39 AMs. The use of a multivariate multilevel model with autoregressive effects allows us to analyse the order effect within one person, as well as how the order effect differs between persons. The results replicated a temporal first-order effect that has been shown in previous studies and moreover, demonstrated a temporal second-order effect. Furthermore, our results indicated an emotional first-order effect that was even stronger than the temporal first-order effect and an emotional second-order effect. In addition, both first-order effects differed reliably between persons. Thus, the present study emphasises the need for considering emotion in current theoretical formulations of autobiographical memory and also of considering individual differences in the order of AMs recalled.

A cluster-randomized control trial targeting parents of pediatric cancer survivors with obesity: Rationale and study protocol of NOURISH-T

Approximately 40-50% of pediatric cancer survivors (PCS) are overweight or obese; increasing their risk for metabolic syndrome and other negative long-term physical health complications. Using our successful pilot trial testing the preliminary feasibility and efficacy of NOURISH for Healthy Transitions (NOURISH-T), we refined our intervention, now NOURISH-T+, and will implement these refinements in this larger, multi-site randomized control trial. Parents of PCS with overweight/obesity (BMI ≥ 85th%ile), age 5-12, ≥6 months off treatment are randomly assigned to the NOURISH-T+ intervention or Enhanced Usual Care (EUC) comparison. Parents in NOURISH-T+ will participate in a 6-session, manualized intervention, with an additional dietician session and 2 PCS sessions, as well as post-intervention booster sessions. EUC consists of a one-time informational session, nationally available brochures and follow-up check-ins. Both study conditions will be conducted remotely via a videoconferencing platform. Parents and PCS will be assessed on anthropometric measures, physical activity (PA) and dietary behaviors at baseline, 3-, 6-, and 12-months post-intervention. We will enroll a diverse group of 260 parents/PCS dyads from four pediatric oncology clinics with the aim of evaluating the efficacy of our intervention across diverse pediatric oncology clinics. Our main aim is to compare the impact of NOURISH-T+ with EUC on PCS BMI z-score. Secondary aims are to compare intervention impact on PCS PA and eating behaviors and parent BMI and behaviors as well as to explore potential moderators of the intervention. Our longer-term goal is to establish a framework for future translation and dissemination of NOURISH-T+.

Increases in social support co-occur with decreases in depressive symptoms and substance use problems among adults in permanent supportive housing: an 18-month longitudinal study

BACKGROUND

Social support is a well-known protective factor against depressive symptoms and substance use problems, but very few studies have examined its protective effects among residents of permanent supportive housing (PSH), a housing program for people with a history of chronic homelessness. We utilized unconditional latent growth curve models (LGCMs) and parallel process growth models to describe univariate trajectories of social support, depressive symptoms, and substance use problems and to examine their longitudinal associations in a large sample of adults residing in PSH.

METHODS

Participants were 653 adult PSH residents in North Texas (56% female; 57% Black; mean age: 51 years) who participated in a monthly health coaching program from 2014 to 2017. Their health behaviors were assessed at baseline and tracked every six months at three follow-up visits.

RESULTS

Unconditional LGCMs indicated that over time, social support increased, whereas depressive symptoms and substance use problems decreased. However, their rates of change slowed over time. Further, in parallel process growth models, we found that at baseline, individuals with greater social support tended to have less severe depressive symptoms and substance use problems (coefficients: - 0.67, p < 0.01; - 0.52, p < 0.01, respectively). Individuals with a faster increase in social support tended to have steeper rates of reduction in both depressive symptoms (coefficient: - 0.99, p < 0.01) and substance use problems (coefficient: - 0.98, p < 0.01), respectively.

CONCLUSIONS

This study suggests that plausibly, increases in social support, though slowing over time, still positively impact depressive symptoms and substance use problems among PSH residents. Future PSH programs could emphasize social support as an early component as it may contribute to clients' overall health.

Predicting Symptoms of Depression and Anxiety Using Smartphone and Wearable Data

Background: Depression and anxiety are leading causes of disability worldwide but often remain undetected and untreated. Smartphone and wearable devices may offer a unique source of data to detect moment by moment changes in risk factors associated with mental disorders that overcome many of the limitations of traditional screening methods. Objective: The current study aimed to explore the extent to which data from smartphone and wearable devices could predict symptoms of depression and anxiety. Methods: A total of N = 60 adults (ages 24-68) who owned an Apple iPhone and Oura Ring were recruited online over a 2-week period. At the beginning of the study, participants installed the Delphi data acquisition app on their smartphone. The app continuously monitored participants' location (using GPS) and smartphone usage behavior (total usage time and frequency of use). The Oura Ring provided measures related to activity (step count and metabolic equivalent for task), sleep (total sleep time, sleep onset latency, wake after sleep onset and time in bed) and heart rate variability (HRV). In addition, participants were prompted to report their daily mood (valence and arousal). Participants completed self-reported assessments of depression, anxiety and stress (DASS-21) at baseline, midpoint and the end of the study. Results: Multilevel models demonstrated a significant negative association between the variability of locations visited and symptoms of depression (beta = -0.21, p = 0.037) and significant positive associations between total sleep time and depression (beta = 0.24, p = 0.023), time in bed and depression (beta = 0.26, p = 0.020), wake after sleep onset and anxiety (beta = 0.23, p = 0.035) and HRV and anxiety (beta = 0.26, p = 0.035). A combined model of smartphone and wearable features and self-reported mood provided the strongest prediction of depression. Conclusion: The current findings demonstrate that wearable devices may provide valuable sources of data in predicting symptoms of depression and anxiety, most notably data related to common measures of sleep.

The relationship between stressful events, emotion dysregulation, and anxiety symptoms among youth: longitudinal support for stress causation but not stress generation

INTRODUCTION

There is a clear bi-directional link between stressful events and depressive symptoms in adolescence, but the directionality of this link for anxiety symptoms remains underexamined. We critically evaluate the longitudinal relationship between stressors and anxiety among youth. Specifically, we examine whether stressors predict anxiety symptoms over a 1.5-year period (stress causation), and whether anxiety symptoms predict stressors over this period (stress generation). We examine potential influencing factors, including stressor type (independent vs. dependent) and emotion dysregulation (nonacceptance; goal-directed difficulty).

METHODS

Social, separation, and physical anxiety symptoms, and frequency and stressor type, were assessed every 3 months for 1.5 years among community youth (n = 528, ages 8-17). Baseline emotion dysregulation was assessed. Time-lagged analyses evaluated the bi-directional relationship of stress and anxiety over time, controlling for previous anxiety and depression.

RESULTS

Interpersonal stressors predicted subsequent physical and social anxiety symptoms, but anxiety did not predict subsequent stressors. Both nonacceptance and goal-directed difficulties predicted subsequent anxiety symptoms and stressors, but did not moderate the relationship.

CONCLUSION

The findings supported the stress causation model for youth anxiety, but not the stress generation model. Nonacceptance and goal-directed difficulty predicted greater subsequent anxiety symptoms and stressors. We discuss implications for prevention and intervention.

Bayesian Multivariate Mixed-Effects Location Scale Modeling of Longitudinal Relations Among Affective Traits, States, and Physical Activity

Intensive longitudinal studies and experience sampling methods are becoming more common in psychology. While they provide a unique opportunity to ask novel questions about within-person processes relating to personality, there is a lack of methods specifically built to characterize the interplay between traits and states. We thus introduce a Bayesian multivariate mixed-effects location scale model (M-MELSM). The formulation can simultaneously model both personality traits (the location) and states (the scale) for multivariate data common to personality research. Variables can be included to predict either (or both) the traits and states, in addition to estimating random effects therein. This provides correlations between location and scale random effects, both across and within each outcome, which allows for characterizing relations between any number of personality traits and the corresponding states. We take a fully Bayesian approach, not only to make estimation possible, but also because it provides the necessary information for use in psychological applications such as hypothesis testing. To illustrate the model we use data from 194 individuals that provided daily ratings of negative and positive affect, as well as their physical activity in the form of step counts over 100 consecutive days. We describe the fitted model, where we emphasize, with visualization, the richness of information provided by the M-MELSM. We demonstrate Bayesian hypothesis testing for the correlations between the random effects. We conclude by discussing limitations of the MELSM in general and extensions to the M-MELSM specifically for personality research.

Inherited and Environmental Moderators of Mother-Child Behavioral Contingency and Contingent Negativity at 27 Months

Previous research has shown that as depressive symptomology increases, mothers tend to show withdrawn or harsh interaction patterns with their children, and the quality of these interaction patterns have subsequently been linked to child behavior problems. However, little research has examined bidirectional influences between mothers and their children, and how these moment-to-moment contingencies differ based on heritable and environmental characteristics. We used data from the Early Growth and Development Study a prospective adoption study to examine how adoptive mothers' depressive symptoms and children's heritable tendencies for negative affectivity interact to predict the quality of mother-child interactions at child age 27-months. Results detected two distinct dyadic interaction patterns. The first was a withdrawn interaction style and was observed in children with a high heritable tendency for negative affect. In that style, mother and child interactions were not contingent upon each other, suggesting a lack of joint engagement. The second was a volatile interaction style, observed in children with a low heritable tendency for negative affect. In these cases, mother and child interactions were highly contingent but negative. Our findings demonstrate essential differences in how dyadic interaction patterns vary according to level of depressive symptomology and heritable tendency for negative affect.

Growth Modeling in a Diagnostic Classification Model (DCM) Framework-A Multivariate Longitudinal Diagnostic Classification Model

A multivariate longitudinal DCM is developed that is the composite of two components, the log-linear cognitive diagnostic model (LCDM) as the measurement model component that evaluates the mastery status of attributes at each measurement occasion, and a generalized multivariate growth curve model that describes the growth of each attribute over time. The proposed model represents an improvement in the current longitudinal DCMs given its ability to incorporate both balanced and unbalanced data and to measure the growth of a single attribute directly without assuming that attributes grow in the same pattern. One simulation study was conducted to evaluate the proposed model in terms of the convergence rates, the accuracy of classification, and parameter recoveries under different combinations of four design factors: the sample size, the growth patterns, the G matrix design, and the number of measurement occasions. The results revealed the following: (1) In general, the proposed model provided good convergence rates under different conditions. (2) Regarding the classification accuracy, the proposed model achieved good recoveries on the probabilities of attribute mastery. However, the correct classification rates depended on the cut point that was used to classify individuals. For individuals who truly mastered the attributes, the correct classification rates increased as the measurement occasions increased; however, for individuals who truly did not master the attributes, the correct classification rates decreased slightly as the numbers of measurement occasions increased. Cohen's kappa increased as the number of measurement occasions increased. (3) Both the intercept and main effect parameters in the LCDM were recovered well. The interaction effect parameters had a relatively large bias under the condition with a small sample size and fewer measurement occasions; however, the recoveries were improved as the sample size and the number of measurement occasions increased. (4) Overall, the proposed model achieved acceptable recoveries on both the fixed and random effects in the generalized growth curve model.

Dynamics of cytokines, immune cell counts and disease severity in patients with community-acquired pneumonia - Unravelling potential causal relationships

BACKGROUND

Community acquired pneumonia (CAP) is a severe and often rapidly deteriorating disease. To better understand its dynamics and potential causal relationships, we analyzed time series data of cytokines, blood and clinical parameters in hospitalized CAP patients.

METHODS

Time series data of 10 circulating cytokines, blood counts and clinical parameters were related to baseline characteristics of 403 CAP patients using univariate mixed models. Bivariate mixed models were applied to analyze correlations between the time series. To identify potential causal relationships, we inferred cross-lagged relationships between pairs of parameters using latent curve models with structured residuals.

RESULTS

IL-6 levels decreased faster over time in younger patients (P_adj = 0.06). IL-8, VCAM-1, and IL-6 correlated strongly with disease severity as assessed by the sequential organ failure assessment (SOFA) score (r = 0.49, 0.48, 0.46, respectively; all P_adj < 0.001). IL-6 and bilirubin correlated with respect to their mean levels and slopes over time (r = 0.36 and r = 0.46, respectively; P_adj < 0.001). A number of potential causal relationships were identified, e.g., a negative effect of ICAM-1 on MCP-1, or a positive effect of the level of creatinine on the subsequent VCAM-1 concentration (P < 0.001).

CONCLUSIONS

These results suggest that IL-6 trajectories of CAP patients are associated with age and run parallel to bilirubin levels. The time series analysis also unraveled directed, potentially causal relationships between cytokines, blood parameters and clinical outcomes. This will facilitate the development of mechanistic models of CAP, and with it, improvements in treatment or surveillance strategies for this disease.

TRIAL REGISTRATION

clinicaltrials.gov NCT02782013, May 25, 2016, retrospectively registered.

Understanding electroconvulsive therapy-related anxiety: a prospective study

AIMS OF STUDY

Although electroconvulsive therapy (ECT)-related anxiety is experienced by a significant proportion of patients, it remains understudied. Our aim was to study the course of ECT-related anxiety during ECT.

METHODS

Seventy-four patients with unipolar or bipolar depression, referred for ECT, were included. ECT-related anxiety was assessed the morning before each ECT session using the ECT-related Anxiety Questionnaire (ERAQ).

RESULTS

Female patients reported more anxiety than men (F(1,64.6) = 3.95, P = 0.05). Patients with a psychotic depression were more anxious before the start of ECT (F(64.8) = 4.57, P = 0.04), but experienced a significant decrease in ECT-related anxiety (t(63.9) = -3.63, P = 0.0006), whereas patients with a non-psychotic depression remained stable on anxiety during their ECT course (t(63,9) = 0.76, P = 0.45). In addition, we found a significant correlation between the decrease of ECT-related anxiety and the decrease of depression-severity (r = 0.35; P = 0.04).

CONCLUSION

There are individual differences in ECT-related anxiety trajectories during ECT. Both female patients and patients with psychotic depression experienced more ECT-related anxiety before the start of ECT. The severity of ECT-related anxiety decreased significantly in patients with a psychotic depression, but remained stable in patients without a psychotic depression during ECT. In addition, patients who showed a stronger decrease in depression-severity also showed a stronger decrease in ECT-related anxiety. A better understanding of ECT-related anxiety trajectories can help in designing anxiety-reducing interventions.

Within-person variability in curiosity during daily life and associations with well-being

OBJECTIVE

Curiosity promotes engagement in novel situations and the accruement of resources that promote well-being. An open question is the extent to which curiosity lability, the degree to which curiosity fluctuates over short timescales, impacts well-being.

METHOD

We use data from a 21-day daily diary as well as trait measures in 167 participants (mean age = 25.37 years, SD = 7.34) to test (a) the importance of curiosity lability for depression, flourishing, and life satisfaction, (b) day-to-day associations among curiosity and happiness, depressed mood, anxiety, and physical activity, and (c) the role of day's mood as a mediator between physical activity and curiosity.

RESULTS

We observe positive associations among curiosity lability and depression, as well as negative associations among curiosity lability and both life satisfaction and flourishing. Curiosity is higher on days of greater happiness and physical activity, and lower on days of greater depressed mood. We find evidence consistent with day's depressed mood and happiness being mediators between physical activity and curiosity.

CONCLUSIONS

Greater consistency in curiosity is associated with well-being. We identify several potential sources of augmentation and blunting of curiosity in daily life and provide support for purported mechanisms linking physical activity to curiosity via mood.

Incorporating physiology into the study of psychotherapy process

Increasing evidence indicates that psychological factors important to therapy effectiveness are associated with physiological activity. Knowledge of the physiological correlates of therapy process variables has the potential to provide unique insights into how and why therapy works, but little is currently known about the physiological underpinnings of specific therapy processes that facilitate client growth and change. The goal of this article is to introduce therapy process researchers to the use of physiological methods for studying therapy process variables. We do this by (a) presenting a conceptual framework for the study of therapy process variables, (b) providing an introductory overview of physiological systems with particular promise for the study of therapy process variables, (c) introducing the primary methods and methodological decisions involved in physiological research, and (d) demonstrating these principles and methods in a case of therapeutic presence during couple therapy. We close with a discussion of the promise and challenges in the study of physiological correlates of therapy process variables and consideration of future challenges and open questions in this line of research. Online supplemental materials include additional resources for therapy process researchers interested in getting started with physiological research. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Investigation of Longitudinal Data Analysis: Hierarchical Linear Model and Latent Growth Model Using a Longitudinal Nursing Home Dataset

The appropriate use of the data analysis method in a longitudinal design remains controversial in gerontological nursing research. The objective of the current study is to compare statistical approaches between a hierarchical-linear model (HLM) and a latent-growth model (LGM) in random effects, variance explained, growth trajectory, and model fitness. Secondary analysis of longitudinal data was used. Two variables were chosen to demonstrate the comparison between statistical methods. The HLM was superior in addressing unbalanced data in repeated-measures analysis of variance (ANOVA) and multivariate ANOVA because its nested data structure and random effects could be estimated. The LGM had advantages in modeling growth trajectories and model-fit comparisons. Superior to the HLM, the LGM reported more acceptable data fit, reporting a quadratic model, and successfully differentiated between and within components. The current research provides some evidence for applying appropriate statistical methods when addressing longitudinal datasets in gerontological nursing research. [Research in Gerontological Nursing, 12(6), 275-283.].

Impact of adolescent obesity on middle-age health of women given data MAR

We analyze adolescent BMI and middle-age systolic blood pressure (SBP) repeatedly measured on women enrolled in the Fels Longitudinal Study (FLS) between 1929 and 2010 to address three questions: Do adolescent-specific growth rates in body mass index (BMI) and menarche affect middle-age SBP? Do they moderate the aging effect on middle-age SBP? Have the effects changed over historical time? To address the questions, we propose analyzing a growth curve model (GCM) that controls for age, birth-year cohort, and historical time. However, several complications in the data make the GCM analysis nonstandard. First, the person-specific adolescent BMI and middle-age SBP trajectories are unobservable. Second, missing data are substantial on BMI, SBP, and menarche. Finally, modeling the latent trajectories for BMI and SBP, repeatedly measured on two distinct sets of unbalanced time points, are computationally intensive. We adopt a bivariate GCM for BMI and SBP with correlated random coefficients. To efficiently handle missing values of BMI, SBP, and menarche assumed missing at random, we estimate their joint distribution by maximum likelihood via the EM algorithm where the correlated random coefficients and menarche are multivariate normal. The estimated distribution will be transformed to the desired GCM for SBP that includes the random coefficients of BMI and menarche as covariates. We demonstrate unbiased estimation by simulation. We find that adolescent growth rates in BMI and menarche are positively associated with, and moderate, the aging effect on SBP in middle age, controlling for age, cohort, and historical time, but the effect sizes are at most modest. The aging effect is significant on SBP, controlling for cohort and historical time, but not vice versa.

Multivariate multilevel modeling of quality of life dynamics of HIV infected patients

BACKGROUND

Longitudinal quality of life (QoL) is an important outcome in many chronic illness studies aiming to evaluate the efficiency of care both at the patient and health system level. Although many QoL studies involve multiple correlated hierarchical outcome measures, very few of them use multivariate modeling. In this work, we modeled the long-term dynamics of QoL scores accounting for the correlation between the QoL scores in a multilevel multivariate framework and to compare the effects of covariates across the outcomes.

METHODS

The data is from an ongoing prospective cohort study conducted amongst adult women who were HIV-infected and on the treatment in Kwazulu-Natal, South Africa. Independent and related QoL outcome multivariate multilevel models were presented and compared.

RESULTS

The analysis showed that related outcome multivariate multilevel models fit better for our data used. Our analyses also revealed that higher educational levels, middle age, stable sex partners and higher weights had a significant effect on better improvements in the rate of change of QoL scores of HIV infected patients. Similarly, patients without TB co-infection, without thrombocytopenia, with lower viral load, with higher CD4 cell count levels, with higher electrolytes component score, with higher red blood cell (RBC) component score and with lower liver abnormality component score, were associated with significantly improved the rate of change of QoL, amongst HIV infected patients.

CONCLUSION

It is hoped that the article will help applied researchers to familiarize themselves with the models and including interpretation of results. Furthermore, three issues are highlighted: model building of multivariate multilevel outcomes, how this model can be used to assess multivariate assumptions, involving fixed effects (for example, to examine the size of the covariate effect varying across QoL domain scores) and random effects (for example, to examine the rate of change in one response variable associated to changes in the other).

Development of Emotion Regulation Dynamics Across Early Childhood: a Multiple Time-Scale Approach

Children should become more effective at regulating emotion as they age. Longitudinal evidence of such change, however, is scarce. This study uses a multiple-time scale approach to test the hypothesis that the self-regulation of emotion-the engagement of executive processes to influence the dynamics of prepotent emotional responses-becomes more effective as children move through early childhood. Second-by-second time-series data obtained from behavioral observation of 120 children (46% female) during an 8-min frustration-eliciting wait task completed at four ages (24 months, 36 months, 48 months, 5 years) were modeled using bivariate coupled differential equation models designed to capture age-related changes in the intrinsic dynamics and bidirectional coupling of prepotent and executive processes. Results revealed indirect influences of executive processes on the intrinsic dynamics of children's desire and frustration increased with age but also revealed complex and non-linear age-related changes in how specific aspects of the dynamic interplay between prepotent responses and executive processes influence the effectiveness of regulation at different ages. The findings illustrate the utility of using a dynamics system approach to articulate and study how specific aspects of emotion regulation change with age.

Interpersonal behavior in couple therapy: Concurrent and prospective associations with depressive symptoms and relationship distress

Objective: This study investigated associations between couples' interpersonal behavior, depressive symptoms, and relationship distress over the course of couple psychotherapy. Method: After every other session of Integrative Systemic Therapy (M = 13 sessions), N = 100 individuals within 50 couples rated their in-session affiliation and autonomy behavior using the circumplex-based Structural Analysis of Social Behavior Intrex. Concurrent and prospective associations of interpersonal behavior with depressive symptoms and relationship distress were evaluated via multivariate multilevel modeling using the Actor-Partner Interdependence Model. Results: An individual's hostility, as well as the partner's hostility, positively predicted an individual's concurrent depressive symptoms and relationship distress, as well as his or her relationship distress at the following session. Partner hostility during one session predicted an individual's subsequent depressive symptoms. During sessions in which individuals controlled the partner, and separated themselves from the partner, they reported more concurrent depressive symptoms and relationship distress, and more subsequent relationship distress. When partners separated themselves, individuals reported more concurrent depressive symptoms and relationship distress, and more subsequent relationship distress. Conclusions: Results underscore the importance of couples' in-session affiliation and autonomy behavior in the treatment of depressive symptoms and relationship distress within couple therapy.

Brain structure and cognitive ability in healthy aging: a review on longitudinal correlated change

Little is still known about the neuroanatomical substrates related to changes in specific cognitive abilities in the course of healthy aging, and the existing evidence is predominantly based on cross-sectional studies. However, to understand the intricate dynamics between developmental changes in brain structure and changes in cognitive ability, longitudinal studies are needed. In the present article, we review the current longitudinal evidence on correlated changes between magnetic resonance imaging-derived measures of brain structure (e.g. gray matter/white matter volume, cortical thickness), and laboratory-based measures of fluid cognitive ability (e.g. intelligence, memory, processing speed) in healthy older adults. To theoretically embed the discussion, we refer to the revised Scaffolding Theory of Aging and Cognition. We found 31 eligible articles, with sample sizes ranging from n = 25 to n = 731 (median n = 104), and participant age ranging from 19 to 103. Several of these studies report positive correlated changes for specific regions and specific cognitive abilities (e.g. between structures of the medial temporal lobe and episodic memory). However, the number of studies presenting converging evidence is small, and the large methodological variability between studies precludes general conclusions. Methodological and theoretical limitations are discussed. Clearly, more empirical evidence is needed to advance the field. Therefore, we provide guidance for future researchers by presenting ideas to stimulate theory and methods for development.

Recovery of physical activity after cesarean delivery and its relationship with pain

Pain and physical activity are tightly intertwined. Although their relationship has been explored in chronic pain conditions, we know little about the pattern of recovery in activity and its short- and long-term relationship with pain after surgery. We recruited 103 women undergoing elective cesarean delivery and acquired daily pain assessments and hourly steps in 98 of them for 2 months after surgery. Compliance was good, with 78% of subjects missing less than 7 days of activity. Study personnel required daily checking for compliance and 20 minutes per subject per week in study. Activity increased over the first 2 postoperative months in a log(time) manner. The slope of each modeled individual curve for activity was inversely correlated (r = -0.54; P < 0.0001) with worst daily pain. After removing these 2-month trends, pain and activity within an individual day were negatively associated with each point increase in pain being inversely associated with -119 steps (95% confidence interval [CI] = -214 to -25; P = 0.013). A patient's previous experience of pain was not associated with current activity as well as current activity was not associated with future pain scores. These data, although limited by the study of a single operation in a unique social circumstance with low risk of chronic postsurgical pain, demonstrate feasibility of measuring hourly activity for 2 months after surgery. Recovery from pain and inactivity are tightly correlated, and the negative relationship between within-day pain and activity without interday carryover relationships is in stark contrast to findings in chronic pain conditions.

Latent Growth Models with Floors, Ceilings, and Random Knots

In longitudinal/developmental studies, individual growth trajectories are sometimes bounded by a floor at the beginning of the observation period and/or a ceiling toward the end of the observation period (or vice versa), resulting in inherently nonlinear growth patterns. If the trajectories between the floor and ceiling are approximately linear, such longitudinal growth patterns can be described with a linear piecewise (spline) model in which segments join at knots. In these scenarios, it may be of specific interest for researchers to examine the timing when transition occurs, and in some occasions also to examine the levels of the floors and/or ceilings if they are not known and fixed. In the current study, we propose a reparameterized piecewise latent growth curve model so that a direct estimation of the random knots (and, if needed, a direct estimation of random floors and ceilings) is possible. We derive the model reparameterization using a 4-step structured latent curve modeling approach. We provide two illustrative examples to demonstrate how the proposed reparameterized models can be fitted to longitudinal growth data using the popular SEM software Mplus and we supply the full coding for applied researchers' reference.

Exploring the Formation of Exercise Habits with the Latent Growth Model

This study investigated the antecedent factors affecting exercise preparation and performance habits and provides basic data for the development of health promotion interventions, based on what was found to be most effective in improving intention and habit. The participants were 114 university students who were willing to participate regularly in exercise and physical activities and interested in forming exercise habits. After coding, we analyzed the complete data set through frequency analysis, reliability, and latent growth model analysis. The provision of early rewards positively affected an initial exercise preparation habit. Both initial consistency and development of consistency also positively affected the development of exercise preparation, and initial behavioral complexity positively affected initial exercise preparation. However, no factors influenced an exercise performance habit. Thus, forming an exercise preparation habit requires fun, personal control, and repetitive behavior while forming an exercise performance habit is particularly challenging. These results may help construct a program for continuous exercise participation.