At the Frontiers of Modeling Intensive Longitudinal Data: Dynamic Structural Equation Models for the Affective Measurements from the COGITO Study

Daily Implications of Felt Love for Sleep Quality

This study introduces the concept of felt love as the monadic experience of love, a parallel of dyadic love, and presents a study examining the relationships between daily felt love and sleep quality across 28 days. Before beginning the daily protocol, participants answered 60 questions assessing common situations that may make people feel loved. These questions were used to establish a consensus on the meaning of felt love for the specific participants under study. During the daily life study, participants (N = 52) provided self-reports via smartphone surveys for 28 days. Each morning upon waking, participants assessed their subjective sleep quality, and each evening positive affect was assessed with a set of 5 questions. Participants also rated how much they felt loved at 6 semirandom times throughout the day. Felt love measures were aggregated to obtain daily means and individual means across the study. Variability in felt love was quantified by calculating within-day and between-day standard deviations. Multilevel modeling was used to account for repeated measurements for each participant across the study, and the final model includes age, sex, positive affect, and felt love as predictors of sleep quality. Participants who reported higher positive affect and higher within-day felt love variability reported better overall sleep quality. However, overall mean levels of felt love did not significantly predict sleep quality, nor were there effects at the daily level. These results suggest that experiencing a range of felt love intensities within an average day is associated with better sleep quality.

Positive Youth Development in 2020: Theory, Research, Programs, and the Promotion of Social Justice

We use Hamilton's (1999) tripartite conception of the positive youth development (PYD) literature - that is, PYD as a theoretical construct, PYD as a frame for program design, and PYD as an instance of specific youth development programs - as a framework for reviewing scholarship involved in the PYD field across the second decade of the 21st century. Advances were made in all three domains and, as well, new issues emerged; chief among them was a focus on the promotion of social justice. We discuss ways in which social justice issues are being addressed within each of these domains and we present a vision for enhancing the PYD-social justice relation in future scholarship involving theory, research, program design, and community-based PYD programs.

Psychopathological networks: Theory, methods and practice

In recent years, network approaches to psychopathology have sparked much debate and have had a significant impact on how mental disorders are perceived in the field of clinical psychology. However, there are many important challenges in moving from theory to empirical research and clinical practice and vice versa. Therefore, in this article, we bring together different points of view on psychological networks by methodologists and clinicians to give a critical overview on these challenges, and to present an agenda for addressing these challenges. In contrast to previous reviews, we especially focus on methodological issues related to temporal networks. This includes topics such as selecting and assessing the quality of the nodes in the network, distinguishing between- and within-person effects in networks, relating items that are measured at different time scales, and dealing with changes in network structures. These issues are not only important for researchers using network models on empirical data, but also for clinicians, who are increasingly likely to encounter (person-specific) networks in the consulting room.

Interaction Effects in Cross-Lagged Panel Models: SEM with Latent Interactions Applied to Work-Family Conflict, Job Satisfaction, and Gender

Researchers often combine longitudinal panel data analysis with tests of interactions (i.e., moderation). A popular example is the cross-lagged panel model (CLPM). However, interaction tests in CLPMs and related models require caution because stable (i.e., between-level, B) and dynamic (i.e., within-level, W) sources of variation are present in longitudinal data, which can conflate estimates of interaction effects. We address this by integrating literature on CLPMs, multilevel moderation, and latent interactions. Distinguishing stable B and dynamic W parts, we describe three types of interactions that are of interest to researchers: 1) purely dynamic or WxW; 2) cross-level or BxW; and 3) purely stable or BxB. We demonstrate estimating latent interaction effects in a CLPM using a Bayesian SEM in Mplus to apply relationships among work-family conflict and job satisfaction, using gender as a stable B variable. We support our approach via simulations, demonstrating that our proposed CLPM approach is superior to a traditional CLPMs that conflate B and W sources of variation. We describe higher-order nonlinearities as a possible extension, and we discuss limitations and future research directions.

Function and Emotion in Everyday Life With Type 1 Diabetes (FEEL-T1D): Protocol for a Fully Remote Intensive Longitudinal Study

BACKGROUND

Although short-term blood glucose levels and variability are thought to underlie diminished function and emotional well-being in people with type 1 diabetes (T1D), these relationships are poorly understood. The Function and Emotion in Everyday Life with T1D (FEEL-T1D) study focuses on investigating these short-term dynamic relationships among blood glucose levels, functional ability, and emotional well-being in adults with T1D.

OBJECTIVE

The aim of this study is to present the FEEL-T1D study design, methods, and study progress to date, including adaptations necessitated by the COVID-19 pandemic to implement the study fully remotely.

METHODS

The FEEL-T1D study will recruit 200 adults with T1D in the age range of 18-75 years. Data collection includes a comprehensive survey battery, along with 14 days of intensive longitudinal data using blinded continuous glucose monitoring, ecological momentary assessments, ambulatory cognitive tasks, and accelerometers. All study procedures are conducted remotely by mailing the study equipment and by using videoconferencing for study visits.

RESULTS

The study received institutional review board approval in January 2019 and was funded in April 2019. Data collection began in June 2020 and is projected to end in December 2021. As of June 2021, after 12 months of recruitment, 124 participants have enrolled in the FEEL-T1D study. Approximately 87.6% (7082/8087) of ecological momentary assessment surveys have been completed with minimal missing data, and 82.0% (82/100) of the participants provided concurrent continuous glucose monitoring data, ecological momentary assessment data, and accelerometer data for at least 10 of the 14 days of data collection.

CONCLUSIONS

Thus far, our reconfiguration of the FEEL-T1D protocol to be implemented remotely during the COVID-19 pandemic has been a success. The FEEL-T1D study will elucidate the dynamic relationships among blood glucose levels, emotional well-being, cognitive function, and participation in daily activities. In doing so, it will pave the way for innovative just-in-time interventions and produce actionable insights to facilitate tailoring of diabetes treatments to optimize the function and well-being of individuals with T1D.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/30901.

A mediation meta-analysis of the role of maternal responsivity in the association between socioeconomic risk and children's language

This meta-analysis tested maternal responsivity as a mediator of the association between socioeconomic risk and children's preschool language abilities. The search included studies up to 2017 and meta-analytic structural equation modeling, allowed us to examine the magnitude of the indirect effect across 17 studies (k = 19). The meta-analysis included 6433 predominantly White, English speaking children (M_age  = 36 months; 50% female) from Western, industrialized countries. All paths in the model were statistically significant, notably, the indirect effect was significant (b = -.052), showing that maternal responsivity may be a proximal intervening variable between socioeconomic risk and children's language development. Moderator analyses found that the indirect effect was stronger for sensitive parenting than warmth and when parenting was assessed in the family home.

Fitting Multilevel Vector Autoregressive Models in Stan, JAGS, and Mplus

The influx of intensive longitudinal data creates a pressing need for complex modeling tools that help enrich our understanding of how individuals change over time. Multilevel vector autoregressive (mlVAR) models allow for simultaneous evaluations of reciprocal linkages between dynamic processes and individual differences, and have gained increased recognition in recent years. High-dimensional and other complex variations of mlVAR models, though often computationally intractable in the frequentist framework, can be readily handled using Markov chain Monte Carlo techniques in a Bayesian framework. However, researchers in social science fields may be unfamiliar with ways to capitalize on recent developments in Bayesian software programs. In this paper, we provide step-by-step illustrations and comparisons of options to fit Bayesian mlVAR models using Stan, JAGS and Mplus, supplemented with a Monte Carlo simulation study. An empirical example is used to demonstrate the utility of mlVAR models in studying intra- and inter-individual variations in affective dynamics.

An informatics approach to examine decision-making impairments in the daily life of individuals with depression

Mental health informatics studies methods that collect, model, and interpret a wide variety of data to generate useful information with theoretical or clinical relevance to improve mental health and mental health care. This article presents a mental health informatics approach that is based on the decision-making theory of depression, whereby daily life data from a natural sequential decision-making task are collected and modeled using a reinforcement learning method. The model parameters are then estimated to uncover specific aspects of decision-making impairment in individuals with depression. Empirical results from a pilot study conducted to examine decision-making impairments in the daily lives of university students with depression are presented to illustrate this approach. Future research can apply and expand on this approach to investigate a variety of daily life situations and psychiatric conditions and to facilitate new informatics applications. Using this approach in mental health research may generate useful information with both theoretical and clinical relevance and high ecological validity.

A Person- and Time-Varying Vector Autoregressive Model to Capture Interactive Infant-Mother Head Movement Dynamics

Head movement is an important but often overlooked component of emotion and social interaction. Examination of regularity and differences in head movements of infant-mother dyads over time and across dyads can shed light on whether and how mothers and infants alter their dynamics over the course of an interaction to adapt to each others. One way to study these emergent differences in dynamics is to allow parameters that govern the patterns of interactions to change over time, and according to person- and dyad-specific characteristics. Using two estimation approaches to implement variations of a vector-autoregressive model with time-varying coefficients, we investigated the dynamics of automatically-tracked head movements in mothers and infants during the Face-Face/Still-Face Procedure (SFP) with 24 infant-mother dyads. The first approach requires specification of a confirmatory model for the time-varying parameters as part of a state-space model, whereas the second approach handles the time-varying parameters in a semi-parametric ("mostly" model-free) fashion within a generalized additive modeling framework. Results suggested that infant-mother head movement dynamics varied in time both within and across episodes of the SFP, and varied based on infants' subsequently-assessed attachment security. Code for implementing the time-varying vector-autoregressive model using two R packages, dynr and mgcv, is provided.

Prospective and Concurrent Affective Dynamics in Self-Injurious Thoughts and Behaviors: An Examination in Young Adult Women

Affective dynamics, assessed using ecological momentary assessment (EMA), provide a nuanced understanding of within-person fluctuations of negative affect (NA) and positive affect (PA) in daily life. NA and PA dynamics have been associated with psychopathology and response to psychological treatments. NA and PA dynamics have been rarely studied concurrently in association with self-injurious thoughts and behaviors (SITB), transdiagnostic difficulties encountered regularly in clinical and community settings. Here we present EMA data from a large, diverse sample of young adult women with high rates of SITB to examine NA and PA dynamics (mean intensity, variability, and inertia). Specifically, we considered the prospective associations between past-year suicidal thoughts and past-year nonsuicidal self-injury and affective dynamics, as well as the concurrent associations between affective dynamics, EMA-reported suicidal thoughts, and EMA-reported urges for nonsuicidal self-injury. Results demonstrate that elevated mean NA and NA variability are robustly associated with all types of SITB assessed prospectively or concurrently. Interestingly, these associations were weakest for past-year nonsuicidal self-injurious behaviors, relative to past-year and concurrent suicidal or nonsuicidal self-injurious thoughts. Past-year suicidal thoughts further predicted increased NA inertia. Decreased PA inertia was associated with past-year nonsuicidal self-injury behavior, as well as concurrent EMA suicidal thoughts. We found no associations (prospective or concurrent) between SITB and mean PA intensity or PA variability. These results highlight the importance of understanding affective processes to develop real-world interventions to prevent nonsuicidal self-injury and suicidal behavior in daily life.

Using Technology to Assess Bidirectionality between Daily Pain and Physical Activity: The Role of Marginalization during Emerging Adulthood

Emerging adulthood is often overlooked as a developmental time period critical to shaping future health outcomes. Recurrent pain is a commonly experienced health concern within this age group, particularly headaches and low back pain, and early experiences of recurrent pain are related to subsequent chronic pain and disability. Furthermore, adults from marginalized populations report more frequent and severe recurrent pain. Many studies have demonstrated the therapeutic effect of physical activity on pain relief; however, others have demonstrated that physical activity can also exacerbate pain symptoms. Therefore, the current study aimed to (1) assess a bidirectional relationship between reported pain and engagement in physical activity among an emerging adult sample (N = 265) and (2) determine whether sociodemographic factors moderate this relationship. Using longitudinal daily reported pain and ActiGraph monitor data collected over two weeks, a novel dynamic structural equation modeling approach was employed. Results indicated no significant cross-lagged relationships between pain and physical activity, and no significant moderation effects. These findings suggest that a bidirectional relationship does not exist among a diverse college sample of emerging adults even after considering sociodemographic moderators. Excellent retention and few missing data suggest that using accelerometers and daily diaries are feasible methods to collect data in this population. Sample considerations and future analytical approaches are discussed.

Cognitive Change and Relaxation as Key Mechanisms of Treatment Outcome in Chronic Pain: Evidence From Routine Care

Despite effective treatment approaches within the cognitive behavioral framework general treatment effects for chronic pain are rather small to very small. Translation from efficacy trials to naturalistic settings is questionable. There is an urgent need to improve the effectiveness of well-established treatments, such as cognitive-behavior therapy (CBT) and the investigation of mechanisms of change is a promising opportunity. We performed secondary data analysis from routine data of 1,440 chronic pain patients. Patients received CBT in a multidisciplinary setting in two inpatient clinics. Effect sizes and reliable change indices were computed for pain-related disability and depression. The associations between changes in the use of different pain coping skills (cognitive restructuring, activity despite pain, relaxation techniques and mental distraction) and changes in clinical outcomes were analyzed in structural equation models. Pre-post effect sizes range from g = 0.47 (disability) to g = 0.89 (depression). Changes in the use of cognitive restructuring, relaxation and to a lesser degree mental distraction were associated with changes in disability and depression. Effects from randomized trials can be translated to naturalistic settings. The results complement experimental research on mechanisms of change in the treatment of chronic pain and indicate an important role of cognitive change and relaxation as mechanisms of change. Our findings cautiously suggest that clinicians should optimize these processes in chronic pain patients to reduce their physical and emotional disability.

Second-by-second infant and mother emotion regulation and coregulation processes

Context-appropriate infant physiological functioning may support emotion regulation and mother-infant emotion coregulation. Among a sample of 210 low-income Mexican-origin mothers and their 24-week-old infants, dynamic structural equation modeling (DSEM) was used to examine whether within-infant vagal functioning accounted for between-dyad differences in within-dyad second-by-second emotion regulation and coregulation during free play. Vagal functioning was captured by within-infant mean and variability (standard deviation) of respiratory sinus arrhythmia (RSA) during free play. Infant emotion regulation was quantified as emotional equilibria (within-person mean), volatility (within-person deviation from equilibrium), carryover (how quickly equilibrium is restored following a disturbance), and feedback loops (the extent to which prior affect dampens or amplifies subsequent affect) in positive and negative affect during free play; coregulation was quantified as the influence of one partner's affect on the other's subsequent affect. Among infants with lower RSA variability, positive affect fluctuated around a higher equilibrium, and negative affect fluctuated around a lower equilibrium; these infants exhibited feedback loops where their positive affect dampened their subsequent negative affect. As expected, infants with higher mean RSA exhibited more volatility in positive affect, feedback loops between their positive and negative affect, and stronger mother-driven emotion coregulation. The results highlight differences in simultaneously occurring biological and emotion regulation.

Being Trapped and Seeing No Way Out - Effects of Entrapment on Treatment Outcome in an Interdisciplinary Pain Treatment

BACKGROUND

Entrapment describes a feeling of being stuck in an inescapable aversive situation. This feeling often arises in the context of uncontrollable and/or chronic stress and is associated with various psychopathologies.

OBJECTIVE

Owing to the nature of their disease, also chronic pain, patients might experience their situation as unremitting and inescapable. The aim of the present study was to examine the role of entrapment in patients with a chronic pain disorder and the association of entrapment with treatment outcome.

METHODS

A total of 189 patients with a chronic pain disorder where psychological factors play a decisive role in its severity, exacerbation, and maintenance (International Classification of Diseases, ICD-10: F45.41, "Chronic pain disorder with somatic and psychologic factors") receiving inpatient care completed a set of standardized self-report questionnaires at intake and discharge of an interdisciplinary pain treatment. To analyze the effects of entrapment on pain-related interference and psychologic distress, hierarchical linear models were used.

RESULTS

Over treatment, reduced levels of entrapment were observed, which were associated with decreases in psychologic distress and pain-related interference at discharge.

CONCLUSION

Results support the relevance of entrapment in chronic pain and its treatment. To further improve interdisciplinary pain treatments, entrapment should be assessed and targeted by according interventions.

Exploring temporal relationships among worrying, anxiety, and somatic symptoms

OBJECTIVES

The role of anxiety symptoms in the development of functional somatic symptoms (FSS) is unknown. Somatic symptoms may be triggered by or give rise to anxiety symptoms. This study aimed to 1) explore interrelationships among within-day worrying, feeling anxious, and somatic symptoms, and 2) investigate the association between these interrelationships and overall level of FSS.

METHODS

This study included 767 participants (83% females, mean age 39 years), who were recruited through an online crowdsourcing study in the Dutch general population. Somatic, and anxiety symptoms were reported thrice daily (6-h intervals) for 30 days using electronic diaries. FSS were assessed at baseline (PHQ-15). Temporal relationships among worrying, feeling anxious, and somatic symptoms were modeled using a multilevel vector autoregressive model.

RESULTS

We observed large heterogeneity in the within-person interrelationships among worrying, feeling anxious and somatic symptoms. Averaged over participants, higher-than-usual somatic symptoms were associated with increases in levels of worrying six hours later (B = 0.017, 95% CI [0.006, 0.027]). At the between-person level, FSS levels predicted the persistence of feeling anxious (B = 0.230 95% CI [0.105, 0.350]) and the carry-over of worrying to feeling anxious over six-hours (B = 0.159, 95% CI [0.031, 0.283]).

CONCLUSIONS

In contrast to what we expected, higher levels of somatic symptoms over multiple weeks were associated with the persistence and carry-over of within-day anxiety-related symptoms. One within-person association between psychological and somatic symptoms during the day was observed, suggesting that, over a time span of 6-h, anxiety symptoms relate to somatic symptoms only in a minority of people from the general population.

Hofstede’s Cultural Dimensions as a Moderator of the Relationship between Ambidextrous Learning and Corporate Sustainability in Born Global Firms

This research analyzes the moderation effects of Hofstede’s Cultural Dimensions (Power Distance, Uncertainty Avoidance and Indulgence) in the relationship between Ambidextrous learning and corporate sustainability in born global firms. The data were collected from exporting firms characterized by beginning international operations in the first three years and were thus classified as Born Global. A panel Dynamic Structural Equation Model (DSEM) was used to test the research hypothesis. One of the methodological contributions is the exploration of dynamic social behaviors that are difficult to study, specifically over time. Here, DSEM becomes in a data analysis technique that allows us to analyze this type of phenomena. The research results show that the relationship between Ambidextrous learning (AL) and Corporate Sustainability (CS) is positive in the short- and long-term. The cultural dimension’s Power Distance and Uncertainty Avoidance moderates the relation between (AL) and (CS) and this dimension can predict their inertia. However, while Uncertainty Avoidance has a moderating effect, it does not predict future behaviors. Published literature on the Born Global company. that includes the moderation of Hofstede’s dimensions (Power distance, Avoidance of uncertainty, and Indulgence) from a company perspective that study the relationship between Ambidextrous Learning and Corporate Sustainability is scarce.

Integrating state dynamics and trait change: A tutorial using the example of stress reactivity and change in well-being

Recent theoretical accounts on the causes of trait change emphasize the potential relevance of states. In the same vein, reactions to daily stress have been shown to prospectively predict change in well-being, speaking for the proposition that state dynamics can be a precursor to long-term change in more stable individual-differences characteristics. A common analysis approach towards linking state dynamics such as stress reactivity and change in some more stable individual differences characteristic has been a two-step approach, modeling state dynamics and trait change separately. In this paper, we elaborate on one-step procedures to simultaneously model state dynamics and trait change, realized in the multilevel structural equation modeling framework. We highlight three distinct advantages over the two-step approach which pre-exists in the methodological literature, and we disseminate these advantages to a larger audience. We target a readership of substantive researchers interested in the relationships between state dynamics and traits or trait change, and we provide them with a tutorial style paper on state-of-the-art methods on these topics.

Assessing the Impact of Green Hiring on Sustainable Performance: Mediating Role of Green Performance Management and Compensation

The global need to preserve ecology has propelled the green movement across the globe. An emerging managerial challenge for all organizations is to protect natural resources by reducing their negative impact on the environment and increase sustainable performance. Greening is the need of the age to conserve natural resources. This study investigates the impact of green human resource management practice—i.e., green hiring—on the sustainable performance of public and private healthcare organizations. A quantitative research approach was used for data collection. Scale survey of 160 responses was gathered from public and private healthcare organizations. Partial least square–structural equation modeling was used for data analysis. The study results suggest that green recruitment has a positive and significant impact on environmental performance, economic performance, and social performance. Path coefficients test also revealed that green performance management and compensation significantly mediate the relationship between green hiring and sustainable performance of public and private healthcare organizations. This study is helpful for organizations in adapting GHRM practices that will benefit the organizations in all ways. This study also provides a better understanding to policymakers on how to promote GHRM practices and increase sustainability in organizations.

For whom should psychotherapy focus on problem coping? A machine learning algorithm for treatment personalization

OBJECTIVE

We aimed to develop and test an algorithm for individual patient predictions of problem coping experiences (PCE) (i.e., patients' understanding and ability to deal with their problems) effects in cognitive-behavioral therapy. Method: In an outpatient sample with a variety of diagnoses (n=1010), we conducted Dynamic Structural Equation Modelling to estimate within-patient cross-lagged PCE effects on outcome during the first ten sessions. In a randomly selected training sample (2/3 of the cases), we tried different machine learning algorithms (i.e., ridge regression, LASSO, elastic net, and random forest) to predict PCE effects (i.e., the degree to which PCE was a time-lagged predictor of symptoms), using baseline demographic, diagnostic, and clinically-relevant patient features. Then, we validated the best algorithm on a test sample (1/3 of the cases).

RESULTS

The random forest algorithm performed best, explaining 14.7% of PCE effects variance in the training set. The results remained stable in the test set, explaining 15.4% of PCE effects variance.

CONCLUSIONS

The results show the suitability to perform individual predictions of process effects, based on patients' initial information. If the results are replicated, the algorithm might have the potential to be implemented in clinical practice by integrating it into monitoring and therapist feedback systems.

Emotional Responses to Stressors in Everyday Life Predict Long-Term Trajectories of Depressive Symptoms

BACKGROUND

Individuals' emotional responses to stressors in everyday life are associated with long-term physical and mental health. Among many possible risk factors, the stressor-related emotional responses may play an important role in future development of depressive symptoms.

PURPOSE

The current study examined how individuals' positive and negative emotional responses to everyday stressors predicted their subsequent changes in depressive symptoms over 18 months.

METHODS

Using an ecological momentary assessment approach, participants (n = 176) reported stressor exposure, positive affect (PA), and negative affect (NA) five times a day for 1 week (n = 5,483 observations) and provided longitudinal reports of depressive symptoms over the subsequent 18 months. A multivariate multilevel latent growth curve model was used to directly link the fluctuations in emotions in response to momentary stressors in everyday life with the long-term trajectory of depressive symptoms.

RESULTS

Adults who demonstrated a greater difference in stressor-related PA (i.e., relatively lower PA on stressor vs. nonstressor moments) reported larger increases in depressive symptoms over 18 months. Those with greater NA responses to everyday stressors (i.e., relatively higher NA on stressor vs. nonstressor moments), however, did not exhibit differential long-term changes in depressive symptoms.

CONCLUSIONS

Adults showed a pattern consistent with both PA and NA responses to stressors in everyday life, but only the stressor-related changes in PA (but not in NA) predicted the growth of depressive symptoms over time. These findings highlight the important-but often overlooked-role of positive emotional responses to everyday stressors in long-term mental health.

Dynamics of sleep, sedentary behavior, and moderate-to-vigorous physical activity on school versus nonschool days

STUDY OBJECTIVES

Studies examining time-use activity behaviors (sleep, sedentary behavior, and physical activity) on school days compared with nonschool days have examined these behaviors independently, ignoring their interrelated nature, limiting our ability to optimize the health benefits of these behaviors. This study examines the associations of school-day (vs. nonschool day) with time-use activity behaviors.

METHODS

Time series data (6,642 days) from Fitbits (Charge-2) were collected (n = 196, 53% female, 5-10 years). We used a variable-centered dynamic structural equation modeling approach to estimate day-to-day associations of time-use activity behaviors on school days for each child. We then used person-centered cluster analyses to group individuals based on these estimates.

RESULTS

Within-participant analysis showed that on school days (vs. nonschool days), children (1) slept less (β = -0.17, 95% CI = -0.21, -0.13), (2) were less sedentary (β = -0.05, 95% CI = -0.09, -0.02), and (3) had comparable moderate-to-vigorous physical activity (MVPA; β = -0.05, 95% CI = -0.11, 0.00). Between-participant analysis showed that, on school days, children with higher sleep carryover experienced greater decreases in sleep (β = 0.44, 95% CI = 0.08, 0.71), children with higher body mass index z-score decreased sedentary behavior more (β = -0.41, 95% CI = -0.64, -0.13), and children with lower MVPA increased MVPA more (β = -0.41, 95% CI -0.64, -0.13). Cluster analysis demonstrated four distinct patterns of connections between time-use activity behaviors and school (High Activity, Sleep Resilient, High Sedentary, and Dysregulated Sleep).

CONCLUSIONS

Using a combination of person-centered and more traditional variable-centered approaches, we identified patterns of interrelated behaviors that differed on school, and nonschool days. Findings can inform targeted intervention strategies tailored to children's specific behavior patterns.

Do daily mood fluctuations activate ruminative thoughts as a mental habit? Results from an ecological momentary assessment study

It has been suggested that mental habits may underpin a heightened disposition to engage in rumination in response to negative mood. The aim of the current study was to assess the role of habit in the dynamic interplay between affect and ruminative thinking in the flow of daily life experiences. Using mobile ecological momentary assessment, 97 participants recorded affect and rumination ten times daily over six days, after completing measures of trait ruminative brooding and habitual characteristics of negative thinking (e.g. automaticity, lack of conscious awareness, intent and control). Momentary fluctuations in negative (increased) and positive (decreased) affect was prospectively associated with greater rumination-levels at the next sampling occasion. The degree to which affect triggered a subsequent ruminative response was moderated by habitual characteristics of negative thinking in a theoretically consistent way. Stronger temporal pairing of negative affect and rumination was also associated with greater emotional inertia but less carry-over of rumination from one moment to the next. Depression vulnerability may be in the form of rumination being habitually triggered in response to momentary fluctuations in affect, with deleterious effect on mood. The findings may have clinical implications, as targeting the habitual nature of rumination might help reduce depression vulnerability.

Emotional Variability and Inertia in Daily Life: Links to Borderline Personality and Depressive Symptoms

Borderline personality disorder (BPD) and depression are characterized by negative emotionality, yet BPD is also theorized to be linked with emotional variability. The present study extends past work to a larger time scale and notes the degree to which stress-related emotional responses are variable or persistent across stressors using novel analytic models. Participants (N = 164) were undergraduate students who completed daily assessments of negative emotional responses to interpersonal stressors for 2 weeks. BPD and depression were associated with greater negative emotional intensity and greater emotional variability in response to nonsocial stressors. Only BPD features were associated with greater emotional variability in response to social stressors. This study is limited by its reliance on self-report in a nonclinical sample and limited within-person assessments. Data point to distinct constellations of emotional dysfunction in BPD and depression. Pending replication, these data may inform targeting of emotional dysfunction in treatment.

Stress, Sleep, and Coping Self-Efficacy in Adolescents

Adults are thought to show a sleep-stress spiral in which greater stress worsens sleep quality, which amplifies stress, which leads to worse sleep. This study examined whether adolescents show a similar spiral, and if so, whether coping self-efficacy-believing one can cope with stress-interrupts the spiral. Temporal dynamics of perceived stress, sleep quality, and coping self-efficacy were tracked in 381 9th graders (49% female, mean age 14.43, age range 14-16) using daily surveys across two school weeks (3184 observations). Though expected associations were evident between individuals, only a unidirectional path was found within individuals from sleep quality to perceived stress via coping self-efficacy. This challenges the conventional bidirectional understanding of sleep-stress relations and suggests coping self-efficacy as an intervention target.

Inertia, innovation, and cross-lagged effects in negative affect and rumination: daily diary study among people living with HIV

OBJECTIVE

The aim of this study was to examine individual differences in the day-by-day relationship between negative affect (NA) and rumination in terms of their inertia, innovation, and cross-lagged effects among people living with HIV (PLWH).

METHODS

The participants were 217 PLWH with confirmed diagnoses of HIV and undergoing antiretroviral treatment. They assessed their NA and rumination for five consecutive days each evening via an online survey.

RESULTS

Results showed that inertia in NA is negatively related to inertia in rumination. Both innovations were unrelated. However, the individuals with relatively higher overall NA were also more reactive to external factors and/or had more variability in their daily lives, to which they respond with NA. Finally, the autoregressive effects were revealed to be important for spillover effects in a direction that is coherent with a given inertia. Thus, the direction of the cascade between daily NA and rumination depends on the area of major regulatory weakness.

CONCLUSION

The results support the view that intensity, inertia, and innovation are distinct dimensions in spite of the common assumption that higher overall intensity of emotions and coping should be strongly related or even synonymous to their perseveration.

A Little Autonomy Support Goes a Long Way: Daily Autonomy-Supportive Parenting, Child Well-Being, Parental Need Fulfillment, and Change in Child, Family, and Parent Adjustment Across the Adaptation to the COVID-19 Pandemic

This study examined the effects of daily parental autonomy support on changes in child behavior, family environment, and parental well‐being across 3 weeks during the COVID‐19 pandemic in Germany. Day‐to‐day associations among autonomy‐supportive parenting, parental need fulfillment, and child well‐being were also assessed. Parents (longitudinal N = 469; M_age = 42.93, SD_age = 6.40) of school children (6–19 years) reported on adjustment measures at two measurement occasions and completed up to 21 daily online questionnaires in the weeks between these assessments. Results from dynamic structural equation models suggested reciprocal positive relations among autonomy‐supportive parenting and parental need fulfillment. Daily parental autonomy support, parental need fulfillment, and child well‐being partially predicted change in adjustment measures highlighting the central role of daily parenting for children’s adjustment during the pandemic.

PCovR2: A flexible principal covariates regression approach to parsimoniously handle multiple criterion variables

Principal covariates regression (PCovR) allows one to deal with the interpretational and technical problems associated with running ordinary regression using many predictor variables. In PCovR, the predictor variables are reduced to a limited number of components, and simultaneously, criterion variables are regressed on these components. By means of a weighting parameter, users can flexibly choose how much they want to emphasize reconstruction and prediction. However, when datasets contain many criterion variables, PCovR users face new interpretational problems, because many regression weights will be obtained and because some criteria might be unrelated to the predictors. We therefore propose PCovR2, which extends PCovR by also reducing the criteria to a few components. These criterion components are predicted based on the predictor components. The PCovR2 weighting parameter can again be flexibly used to focus on the reconstruction of the predictors and criteria, or on filtering out relevant predictor components and predictable criterion components. We compare PCovR2 to two other approaches, based on partial least squares (PLS) and principal components regression (PCR), that also reduce the criteria and are therefore called PLS2 and PCR2. By means of a simulated example, we show that PCovR2 outperforms PLS2 and PCR2 when one aims to recover all relevant predictor components and predictable criterion components. Moreover, we conduct a simulation study to evaluate how well PCovR2, PLS2 and PCR2 succeed in finding (1) all underlying components and (2) the subset of relevant predictor and predictable criterion components. Finally, we illustrate the use of PCovR2 by means of empirical data.

High-frequency follow-up studies in musculoskeletal disorders: a scoping review

OBJECTIVES

This scoping review identifies research in musculoskeletal disorders that uses high frequency follow-up of symptoms. The aim was to investigate whether symptom variability is investigated as a predictor of disease outcome and how intensive follow-up methods are used in musculoskeletal research.

METHODS

Embase, MEDLINE and PsycInfo were searched using OVID, and the Institute of Electrical and Electronic Engineers was also searched using the Institute of Electrical and Electronic Engineers Xplore search engine. Studies were systematically reviewed in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses, but no meta-analysis was done because the priority in this study is to identify gaps in available literature.

RESULTS

Twenty-one papers were included. There was a mean of 54 patients per study (s.d. of 27.7). Two-thirds of the papers looked at how a symptom influences another in the short-term (subsequent assessment in the same day or next day), but none looked at the long-term. Only one study considered symptom variability investigating how higher variability in pain (defined by the s.d.) is associated with higher average pain severity and lower average sleep quality.

CONCLUSION

The methodology of musculoskeletal disorder research has changed from completing paper booklets to using electronic data capture (smartphones). There has also been a trend of collecting more intensive longitudinal data, but very little research utilizes these data to look at how symptom variability affects symptom outcomes. This demonstrates a gap in research where furthering understanding of this will help clinicians decide on the most important symptom to address in future patients.

Towards personalized assessment of fatigue perpetuating factors in patients with chronic fatigue syndrome using ecological momentary assessment: A pilot study

OBJECTIVE

This study aimed to explore the associations between cognitions, behaviours and affects and fatigue in chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME), and their relation to reduction of fatigue after cognitive behaviour therapy (CBT).

METHODS

In CFS/ME patients, 22 behaviours, cognitions and affects, potentially perpetuating fatigue were registered 5 times a day using ecological momentary assessment (EMA) and an actigraphy. Simultaneous Components Analysis (SCA) was used to identify components of perpetuation, that were tested for their associations with fatigue in multilevel vector autoregressive (VAR) modelling. Fatigue severity was measured pre- and posttreatment with the Checklist Individual Strength. The relationship between perpetuation (the strength and direction of the possible associations between fatigue and the components) and therapy outcome was investigated.

RESULTS

58 patients met inclusion criteria (m age = 36.5; 65.5% female) and data of 50 patients were analysed in the multilevel analysis. Two perpetuating components were found: "psychological discomfort" and "activity". For the total group, both perpetuating components did not predict fatigue on a following time-point. For individual patients the strength and direction of the associations varied. None of the associations between perpetuating components and fatigue significantly predicted treatment outcome.

CONCLUSION

Results suggest that there is heterogeneity in perpetuation of fatigue in CFS/ME. Investigating fatigue and perpetuators on an individual rather than group level could lead to new insights.

Measurement in Intensive Longitudinal Data

Technological advances have increased the prevalence of intensive longitudinal data as well as statistical techniques appropriate for these data, such as dynamic structural equation modeling (DSEM). Intensive longitudinal designs often investigate constructs related to affect or mood and do so with multiple item scales. However, applications of intensive longitudinal methods often rely on simple sums or averages of the administered items rather than considering a proper measurement model. This paper demonstrates how to incorporate measurement models into DSEM to (1) provide more rigorous measurement of constructs used in intensive longitudinal studies and (2) assess whether scales are invariant across time and across people, which is not possible when item responses are summed or averaged. We provide an example from an ecological momentary assessment study on self-regulation in adults with binge eating disorder and walkthrough how to fit the model in Mplus and how to interpret the results.

Precision clinical trials: a framework for getting to precision medicine for neurobehavioural disorders

The goal of precision medicine (individually tailored treatments) is not being achieved for neurobehavioural conditions such as psychiatric disorders. Traditional randomized clinical trial methods are insufficient for advancing precision medicine because of the dynamic complexity of these conditions. We present a pragmatic solution: the precision clinical trial framework, encompassing methods for individually tailored treatments. This framework includes the following: (1) treatment-targeted enrichment, which involves measuring patients' response after a brief bout of an intervention, and then randomizing patients to a full course of treatment, using the acute response to predict long-term outcomes; (2) adaptive treatments, which involve adjusting treatment parameters during the trial to individually optimize the treatment; and (3) precise measurement, which involves measuring predictor and outcome variables with high accuracy and reliability using techniques such as ecological momentary assessment. This review summarizes precision clinical trials and provides a research agenda, including new biomarkers such as precision neuroimaging, transcranial magnetic stimulation-electroencephalogram digital phenotyping and advances in statistical and machine-learning models. Validation of these approaches - and then widespread incorporation of the precision clinical trial framework - could help achieve the vision of precision medicine for neurobehavioural conditions.

Exploring Idiographic Approaches to Children's Executive Function Performance: An Intensive Longitudinal Study

Traditional variable-centered research on executive functions (EFs) often infers intraindividual development using group-based averages. Such a method masks meaningful individuality and involves the fallacy of equating group-level data with person-specific changes. We used an intensive longitudinal design to study idiographic executive function fluctuation among ten boys from Grade 4. Each of the participants completed between 33 and 43 measurement occasions (M = 38.8) across approximately three months. Data were collected remotely using a computerized short version of the Dimensional Change Card Sort task. Multi-group analyses of three participant pairs (Participants 5 and 3, 5 and 2, and 5 and 6) demonstrated that Participant 5 differed from Participants 3 and 2 in different ways but Participants 5 and 6 were similar in all comparisons. Dynamic structural equation modeling demonstrated unique individual trajectories, which were not represented by the trajectory of group-averages. Although more than half of the participants showed a negative association between EFs and inattention, two participants showed a positive association between EF and inattention. This study demonstrated meaningful person-specific trajectories of EFs, suggesting that future study should undertake the analysis of individual development before data-aggregation or generalization from aggregate statistics to individuals.

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.

Individual differences in momentary pain-affect coupling and their associations with mental health in patients with chronic pain

OBJECTIVE

Pain and affect are generally associated. However, individuals may differ in the magnitude of the coupling between pain and affect, which may have important implications for their mental health. The present study uses ecological momentary assessments (EMA) to examine individual differences in momentary pain-affect coupling and their associations with depressive and anxiety symptoms.

METHODS

This study is a secondary data analysis of three primary EMA studies. Participants were a total of 290 patients with chronic pain. Results were synthesized across studies using meta-analytic techniques.

RESULTS

Individuals whose pain was more strongly concurrently coupled with affect (positively associated with negative affect or negatively associated with positive affect) reported higher levels of depressive and anxiety symptoms. Results from lagged analyses suggest that individual differences in affect reactivity to pain were not significantly associated with depressive or anxiety symptoms.

CONCLUSION

These findings suggest that individuals with greater concurrent coupling between pain and affect experience more mental health problems. Potential avenues for future research include intervention strategies that target the decoupling of pain and affect experiences in patients with chronic pain.

Comorbidity between depression and anxiety: assessing the role of bridge mental states in dynamic psychological networks

BACKGROUND

Comorbidity between depressive and anxiety disorders is common. A hypothesis of the network perspective on psychopathology is that comorbidity arises due to the interplay of symptoms shared by both disorders, with overlapping symptoms acting as so-called bridges, funneling symptom activation between symptom clusters of each disorder. This study investigated this hypothesis by testing whether (i) two overlapping mental states "worrying" and "feeling irritated" functioned as bridges in dynamic mental state networks of individuals with both depression and anxiety as compared to individuals with either disorder alone, and (ii) overlapping or non-overlapping mental states functioned as stronger bridges.

METHODS

Data come from the Netherlands Study of Depression and Anxiety (NESDA). A total of 143 participants met criteria for comorbid depression and anxiety (65%), 40 participants for depression-only (18.2%), and 37 for anxiety-only (16.8%) during any NESDA wave. Participants completed momentary assessments of symptoms (i.e., mental states) of depression and anxiety, five times a day, for 2 weeks (14,185 assessments). First, dynamics between mental states were modeled with a multilevel vector autoregressive model, using Bayesian estimation. Summed average lagged indirect effects through the hypothesized bridge mental states were compared between groups. Second, we evaluated the role of all mental states as potential bridge mental states.

RESULTS

While the summed indirect effect for the bridge mental state "worrying" was larger in the comorbid group compared to the single disorder groups, differences between groups were not statistically significant. The difference between groups became more pronounced when only examining individuals with recent diagnoses (< 6 months). However, the credible intervals of the difference scores remained wide. In the second analysis, a non-overlapping item ("feeling down") acted as the strongest bridge mental state in both the comorbid and anxiety-only groups.

CONCLUSIONS

This study empirically examined a prominent network-approach hypothesis for the first time using longitudinal data. No support was found for overlapping mental states "worrying" and "feeling irritable" functioning as bridge mental states in individuals vulnerable for comorbid depression and anxiety. Potentially, bridge mental state activity can only be observed during acute symptomatology. If so, these may present as interesting targets in treatment, but not prevention. This requires further investigation.

Do Mothers or Children Lead the Dance? Disentangling Individual and Influence Effects During Conflict

Are mother-child conflict discussions shaped by time-varying, reciprocal influences, even after accounting for stable contributions from each individual? Mothers were filmed discussing a conflict for 5 min, separately with their younger (ages 5-9, N = 217) and older (ages 7-13, N = 220) children. Each person's conflict constructiveness was coded in 20-s intervals and data were analyzed using dynamic structural equation modeling, which separates individual and influence effects. Children influenced their mothers' behavior under certain conditions, with evidence for developmental differences in the magnitude and direction of influence, whereas mothers did not influence their children under any circumstance. Results are discussed in the context of child effects on parent behavior and changes in parenting across middle childhood.

Using Vector Autoregression Modeling to Reveal Bidirectional Relationships in Gender/Sex-Related Interactions in Mother-Infant Dyads

Vector autoregression (VAR) modeling allows probing bidirectional relationships in gender/sex development and may support hypothesis testing following multi-modal data collection. We show VAR in three lights: supporting a hypothesis, rejecting a hypothesis, and opening up new questions. To illustrate these capacities of VAR, we reanalyzed longitudinal data that recorded dyadic mother-infant interactions for 15 boys and 15 girls aged 3 to 11 months of age. We examined monthly counts of 15 infant behaviors and 13 maternal behaviors (Seifer et al., 1994). VAR models demonstrated that infant crawling predicted a subsequently close feedback loop from mothers of boys but a subsequently open-ended, branched response from mothers of girls. A different finding showed that boys' standing independently predicted significant later increases of four maternal behaviors: rocking/jiggling, lifting, affectionate touching, and stimulation of infant gross-motor activity. In contrast, crawling by girls led mothers to later decrease the same maternal behaviors. Thus, VAR might allow us to identify how mothers respond differently during daily interactions depending on infant gender/sex. The present work intends to mainly showcase the VAR method in the specific context of the empirical study of gender/sex development.

Latent growth curve model selection with Tabu search

The purpose of this research note is to introduce a latent growth curve reconstruction approach based on the Tabu search algorithm. The approach algorithmically enables researchers to optimally determine at both the individual and the group levels the order of the polynomial needed to represent the latent growth curve model. The procedure is illustrated using empirical data along with an easy to use computerized implementation.

Heightened Stress in Employed Individuals Is Linked to Altered Variability and Inertia in Emotions

Stress has been widely recognized as a key factor contributing to health outcomes and psychological well-being. While some growing evidence points to stress as having an effect on emotion dynamics characteristics, there has yet to be a test of how global perceptions of stress are associated with not only average levels of emotions but also the variability in the intensity of the emotions, as well as how emotions linger (inertia), and whether these characteristics differ by age. In an effort to better understand how stress influences the emotional experiences of individuals, we examined associations between perceived stress levels and emotion dynamics indices in a sample of 859 working individuals over 24 h. Participants ranged in age from 21 to 81 years. Each participant was prompted at approximately 28 min intervals throughout a 24 h period to report intensity of emotional states. Overall, individuals who were more stressed experienced lower mean levels of positive emotions (with the exception of higher levels of excitement) and higher mean levels of negative emotions. They also experienced more pronounced variability in both positive and negative emotions, and greater inertia in negative emotions. We also found some evidence for age-related differences in mean levels and variability in certain emotions. The relationship of emotion dynamics indices to stress levels was not moderated by age. Many of the stress–emotion dynamics associations did not remain statistically significant upon controlling for the mean level of momentary emotions, indicating that the mean is a large component in the association.

Studying Within-Person Variation and Within-Person Couplings in Intensive Longitudinal Data: Lessons Learned and to Be Learned

Intensive longitudinal designs (e.g., experience sampling methods, daily diary studies, or ambulatory assessments) continue to gain importance in psychological aging research. Empirical research using these designs has greatly facilitated our understanding of short-term within-person processes and has started to approach the question how these processes shape long-term development across the life span. The aim of this viewpoint article is to point out four key issues in intensive longitudinal designs that in our opinion require more attention than they are currently given: (a) improvement in measurement reliability, (b) the necessity to investigate inter-individual differences in short-term dynamics, (c) considerations of the time scale across which dynamic effects unfold, and (d) targeting causality by incorporating experimental methods in intensive longitudinal designs. We illustrate these four key issues by referring to a prominent example of within-person dynamics in prior empirical research: the within-person coupling of stressor occurrence and well-being (stress reactivity).

Affective Dynamics Across Internalizing and Externalizing Dimensions of Psychopathology

Little is known about pathogenic affective processes that cut across diverse mental disorders. The current study examines how dynamic features of positive and negative affect differ or converge across internalizing and externalizing disorders in a diagnostically diverse urban sample using bivariate dynamic structural equation modeling. One-hundred fifty-six young women completed semi-structured clinical interviews and a 21-day ecological momentary assessment protocol with seven assessments of affective states per day. Internalizing and externalizing dimensions of psychopathology were modeled using confirmatory factor analysis of mental disorders. After controlling for externalizing disorders, internalizing disorders were associated with higher negative affective mean intensity, higher negative affective variability (i.e., unique innovation variance), and lower positive affective variability. Conversely, externalizing disorders were associated with less persistent positive affect (i.e., lower inertia) and more variable positive emotionality. Results suggest internalizing and externalizing disorders have distinct affective dynamic signatures, which have implications for development of tailored interventions.

Affective dynamics among veterans: Associations with distress tolerance and posttraumatic stress symptoms

We tested a dynamic structural equation model (DSEM; Asparouhov, Hamaker, & Muthén, 2018) of positive and negative affect in 254 veterans with approximately 1.5 years of experience sampling data. The analysis provided estimates of several aspects of veteran's emotional experience including "trait" positive and negative affect (i.e., mean levels), inertia (i.e., tendency for emotions to self-perpetuate), innovation variance (conceptualized as lability, reactivity, or exposure to stressors), and cross-lagged associations between positive and negative affect. Veterans with higher trait negative affect had more negative affect inertia and innovation variance. This suggests a pattern whereby the veteran has more negative reactions, and negative emotions, in turn, tend to maintain themselves, contributing to higher trait negative affect. In contrast, veterans with higher trait positive affect exhibited more positive affect innovation variance (e.g., positive reactivity). Although veterans showed some consistency in dynamics across emotions (e.g., positive and negative reactivity were positively correlated), trait positive and negative affect were not significantly associated. Veterans with higher posttraumatic stress symptoms (PTSS) at baseline exhibited higher reactivity to negative events, less positive affect, and more negative affect during the follow-up. Veterans with higher distress tolerance reported not only lower PTSS but also a more adaptive pattern of affective experience characterized by lower inertia and reactivity in negative affect and more positive lagged associations between negative affect and subsequent positive affect. The results demonstrated that distress tolerance and PTSS in veterans were associated with dynamics of positive and negative emotion over time, suggesting specific differences in affect regulation processes. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Featured Article: Bidirectional Effects of Sleep and Sedentary Behavior Among Toddlers: A Dynamic Multilevel Modeling Approach

OBJECTIVE

To examine the bidirectional effects of objectively measured nighttime sleep and sedentary activity among toddlers.

METHOD

Actical accelerometer data were analyzed for 195 toddlers participating in an obesity prevention trial (mean age = 27 months). Toddlers wore the accelerometers for up to 7 consecutive days. Nighttime sleep was defined as the number of minutes asleep between the hours of 8 pm and 8 am the following morning. Sedentary behavior (in minutes) was defined using previously established Actical cut points for toddlers. Variables were lagged and parsed into latent within- and between-person components, using dynamic structural equation modeling (DSEM).

RESULTS

Toddlers spent an average of 172 min (∼3 hr) in sedentary activity and slept an average of 460 min (∼8 hr) per night. An autoregressive cross-lagged multilevel model revealed significant autoregression for both sleep and sedentary activity. Cross-lagged values revealed that decreased sleep predicted increased next-day sedentary activity, and sedentary activity predicted that night's sleep. For 89% of the sample, the within-person standardized cross-lagged effects of sleep on sedentary were larger than the cross-lagged effects of sedentary on sleep.

CONCLUSIONS

Results suggest that, on average, nighttime sleep is a stronger predictor of subsequent sedentary behavior (compared with the reverse), and this is the case for the majority of toddlers. Findings highlight the importance of interindividual associations between sleep and sedentary activity. The present study is an example of how DSEM methods can be used to ask questions about Granger-causal cross-lagged relations between variables, both within and between individuals.

Annual Research Review: Ecological momentary assessment studies in child psychology and psychiatry

BACKGROUND

Enhancements in mobile phone technology allow the study of children and adolescents' everyday lives like never before. Ecological momentary assessment (EMA) uses these advancements to allow in-depth measurements of links between context, behavior, and physiology in youths' everyday lives.

FINDINGS

A large and diverse literature now exists on using EMA to study mental and behavioral health among youth. Modern EMA methods are built on a rich tradition of idiographic inquiry focused on the intensive study of individuals. Studies of child and adolescent mental and behavioral health have used EMA to characterize lived experience, document naturalistic within-person processes and individual differences in these processes, measure familiar constructs in novel ways, and examine temporal order and dynamics in youths' everyday lives.

CONCLUSIONS

Ecological momentary assessment is feasible and reliable for studying the daily lives of youth. EMA can inform the development and augmentation of traditional and momentary intervention. Continued research and technological development in mobile intervention design and implementation, EMA-sensor integration, and complex real-time data analysis are needed to realize the potential of just-in-time adaptive intervention, which may allow researchers to reach high-risk youth with intervention content when and where it is needed most.