Health sensitivity in the daily lives of younger and older adults: correlates and longer-term change in health.

OBJECTIVES: How susceptible older adults' affect is to fluctuations in health (i.e., health sensitivity) indicates how well they adapt to everyday health challenges. Theory and evidence are inconsistent as to whether older adults are more or less health sensitive than younger adults. The role of health burden as correlate and outcome of health sensitivity and age differences therein is also unclear. We thus move the study of health sensitivity ahead from longitudinal inquiry to examine age differences, the role of health burden, and long-term implications of daily life health sensitivitMethods: We use data from COGITO where 101 younger adults (Mage = 25; range = 20-31) and 103 older adults (Mage = 71; range = 65-80) gave daily reports of physical symptoms and positive and negative affect during a ∼100-day micro-longitudinal phase, as well as reports of trait-level health two years before and after. RESULTS: Extending earlier reports, older age and higher health burden were (independently) associated with lower health sensitivity in positive but not negative affect. Health sensitivity was unrelated to long-term changes in health burden. CONCLUSION: We take our findings to indicate successful aging (older adults are not more emotionally vulnerable to health issues) and discuss habituation as a process underlying how age and health burden may reduce health sensitivity.

Change in mental health symptoms during the COVID-19 pandemic: The role of appraisals and daily life experiences.

OBJECTIVE: When confronted with major threats, people often experience decline in well-being. The central purpose of this study was to identify mechanisms underlying change of well-being in times of threat, using the example of the COVID-19 pandemic, with a focus on appraisals of the pandemic and affective states, stress, as well as mindfulness in daily life. METHOD: We conducted a study across 3.5 weeks, including pretest, posttest, and a diary phase in-between. We worked with a sample of 460 adults, pre- and post-test information, as well as 7,189 observations from the diary phase. RESULTS: Results showed that deterioration in mental health symptoms across the duration of the study was associated with (a) change towards less fortunate appraisals of the pandemic and (b), more negative affect and less mindfulness in daily life. Furthermore, appraisals of the pandemic at pretest predicted experiences in daily life, with more negative appraisals of the pandemic predicting more negative affect and stressor occurrence as well as less mindfulness. CONCLUSIONS: These findings speak to the dynamic nature of well-being and appraisals in times of threat, and highlight the role of experiences in daily life in changes in well-being.

Improved Insight into and Prediction of Network Dynamics by Combining VAR and Dimension Reduction.

To understand within-person psychological processes, one may fit VAR(1) models (or continuous-time variants thereof) to multivariate time series and display the VAR(1) coefficients as a network. This approach has two major problems. First, the contemporaneous correlations between the variables will frequently be substantial, yielding multicollinearity issues. In addition, the shared effects of the variables are not included in the network. Consequently, VAR(1) networks can be hard to interpret. Second, crossvalidation results show that the highly parametrized VAR(1) model is prone to overfitting. In this article, we compare the pros and cons of two potential solutions to both problems. The first is to impose a lasso penalty on the VAR(1) coefficients, setting some of them to zero. The second, which has not yet been pursued in psychological network analysis, uses principal component VAR(1) (termed PC-VAR(1)). In this approach, the variables are first reduced to a few principal components, which are rotated toward simple structure; then VAR(1) analysis (or a continuous-time analog) is applied to the rotated components. Reanalyzing the data of a single participant of the COGITO study, we show that PC-VAR(1) has the better predictive performance and that networks based on PC-VAR(1) clearly represent both the lagged and the contemporaneous variable relations.

Long-Term Effects of an Extensive Cognitive Training on Personality Development.

Previous research found that cognitive training increases the Big Five personality trait Openness to Experience during and some weeks after the intervention. The present study investigated whether long-term changes happen in Openness to Experience and other personality traits after an extensive cognitive training of memory and perceptual speed. The intervention group consisted of 204 adults (20-31 years and 65-80 years; 50% female) who received daily 1-hour cognitive training sessions for about 100 days. The control group consisted of 86 adults (21-29 years and 65-82 years; 51% female) who received no cognitive training. All participants answered the NEO Five-Factor Inventory before and 2 years after the cognitive training. Latent change models were applied that controlled for age group (young vs. old) and gender. In the long run, the cognitive training did not affect changes in any facet of Openness to Experience. This was true for young and old participants as well as for men and women. Instead, the cognitive training lowered the general increase of Conscientiousness. Even an extensive cognitive training on memory and perceptual speed does not serve as a sufficient intervention for enduring changes in Openness to Experiences or one of its facets.

Capturing Context-Related Change in Emotional Dynamics via Fixed Moderated Time Series Analysis.

Much of recent affect research relies on intensive longitudinal studies to assess daily emotional experiences. The resulting data are analyzed with dynamic models to capture regulatory processes involved in emotional functioning. Daily contexts, however, are commonly ignored. This may not only result in biased parameter estimates and wrong conclusions, but also ignores the opportunity to investigate contextual effects on emotional dynamics. With fixed moderated time series analysis, we present an approach that resolves this problem by estimating context-dependent change in dynamic parameters in single-subject time series models. The approach examines parameter changes of known shape and thus addresses the problem of observed intra-individual heterogeneity (e.g., changes in emotional dynamics due to observed changes in daily stress). In comparison to existing approaches to unobserved heterogeneity, model estimation is facilitated and different forms of change can readily be accommodated. We demonstrate the approach's viability given relatively short time series by means of a simulation study. In addition, we present an empirical application, targeting the joint dynamics of affect and stress and how these co-vary with daily events. We discuss potentials and limitations of the approach and close with an outlook on the broader implications for understanding emotional adaption and development.

Using Raw VAR Regression Coefficients to Build Networks can be Misleading.

Many questions in the behavioral sciences focus on the causal interplay of a number of variables across time. To reveal the dynamic relations between the variables, their (auto- or cross-) regressive effects across time may be inspected by fitting a lag-one vector autoregressive, or VAR(1), model and visualizing the resulting regression coefficients as the edges of a weighted directed network. Usually, the raw VAR(1) regression coefficients are drawn, but we argue that this may yield misleading network figures and characteristics because of two problems. First, the raw regression coefficients are sensitive to scale and variance differences among the variables and therefore may lack comparability, which is needed if one wants to calculate, for example, centrality measures. Second, they only represent the unique direct effects of the variables, which may give a distorted picture when variables correlate strongly. To deal with these problems, we propose to use other VAR(1)-based measures as edges. Specifically, to solve the comparability issue, the standardized VAR(1) regression coefficients can be displayed. Furthermore, relative importance metrics can be computed to include direct as well as shared and indirect effects into the network.

The Factor Structure, Predictors, and Percentile Norms of the Center for Epidemiologic Studies Depression (CES-D) Scale in the Dutch-speaking Adult Population of Belgium.

The Center of Epidemiologic Studies Depression Scale (CES-D) is a commonly used self-report scale to measure depressive symptoms in the general population. In the present study, the Dutch version of the CES-D was administered to a sample of 837 Dutch-speaking adults of Belgium to examine the factor structure of the scale. Using confirmatory factory analysis (CFA), four first-order models and two second-order models were tested, and the second-order factor model with three pairs of correlated error terms provided the best fit to the data. Second, five socio-demographic variables (age, gender, education level, relation status, and family history of depression) were included as covariates to the second-order factor model to explore the associations between background characteristics and the latent factor depression using a multiple indicators and multiple causes (MIMIC) approach. Age had a significantly negative effect on depression, but the effect was not substantial. Female gender, lower education level, being single or widowed, and having a family history of depression were found to be significant predictors of higher levels of depression symptomatology. Finally, percentile norms on the CES-D raw scores were provided for subgroups of gender by education level for the general Dutch-speaking adult population of Belgium.

Ambulatory Assessment in the Research on Aging: Contemporary and Future Applications.

Older adults have surprisingly high levels of well-being, which has been referred to as a paradox in the past. Improved emotion regulation has been suggested to underlie these high levels of well-being. Later life is also a period with enhanced exposure to critical life events, and this comes with risks. During such times, and towards the end of life, emotional well-being may and eventually does decline. We suggest that ambulatory assessment (AA) is ideally suited for the investigation of the above phenomena and for intervention purposes. More precisely, AA can be used to thoroughly examine within-person processes of emotion regulation, including the multiple levels on which emotions occur (physiology, experience, behavior, context, and nonverbal expressions). It thereby provides a basis for understanding competent emotion regulation, the well-being paradox, and emotionally critical periods. Such insights can be utilized to detect person-specific critical periods and for designing immediate person-specific interventions. Although this is still a vision, the benefits of such an approach seem invaluable. The major part of this paper is organized around three general principles that we suggest to further tap the potential of AA in aging research, namely (1) identify within-subject processes and their relations to important life outcomes; (2) capitalize on the full scope of AA technology via multivariate assessments, and (3) combine real-time monitoring with real-time interventions.

Emotional inertia contributes to depressive symptoms beyond perseverative thinking.

The autocorrelation or inertia of negative affect reflects how much negative emotions carry over from moment to moment and has been associated with increased depressive symptoms. In this study, we posed three challenges to this association by examining: (1) whether emotional inertia is relevant for depressive symptoms when assessed on a longer timescale than usual; (2) whether inertia is uniquely related to depressive symptoms after controlling for perseverative thoughts; and (3) whether inertia is related to depressive symptoms over and above the within-person association between affect and perseverative thoughts. Participants (N = 101) provided ratings of affect and perseverative thoughts for 100 days; depressive symptoms were reported before and after the study, and again after 2.5 years. Day-to-day emotional inertia was related to depressive symptoms over and above trait and state perseverative thoughts. Moreover, inertia predicted depressive symptoms when adjusting for its association with perseverative thoughts. These findings establish the relevance of emotional inertia in depressive symptoms independent of perseverative thoughts.

Toward a Unified Framework for the Study of Between-Person and Within-Person Structures: Building a Bridge Between Two Research Paradigms.

The vast majority of empirical research in the behavioral sciences is based on the analysis of between-person variation. In contrast, much of applied psychology is concerned with the analysis of variation within individuals. Furthermore, the mechanisms specified by psychological theories generally operate within, rather than across, individuals. This disconnect between research practice, applied demands, and psychological theories constitutes a major threat to the conceptual integrity of the field. Following groundbreaking earlier work, we propose a conceptual framework that distinguishes within-person (WP) and between-person (BP) sources of variation in psychological constructs. By simultaneously considering both sources of variation, it is shown how to identify possible reasons for nonequivalence of BP and WP structures as well as establishing areas of convergence. For this purpose, we first introduce the concept of conditional equivalence as a way to study partial structural equivalence of BP and WP structures in the presence of unconditional nonequivalence. Second, we demonstrate the construction of likelihood planes to explore the causes of structural nonequivalence. Third, we examine 4 common causes for unconditional nonequivalence-autoregression, subgroup differences, linear trends, and cyclic trends-and demonstrate how to account for them. Fourth, we provide an empirical example on BP and WP differences in attentiveness.

Location-scale modeling as an integrative approach to symptom dynamics during psychotherapy: An illustration with depressive symptoms.

OBJECTIVE: Depressive symptom dynamics, including change trajectories and symptom variability, have been related to therapy outcomes. However, such dynamics have often been examined separately and related to outcomes of interest using two-step analyses, which are characterized by several limitations. Here, we show how to overcome these limitations using location-scale models in a dynamic structural equation modeling framework. METHOD: We introduce location-scale modeling in an accessible manner to pave the way for its use in research integrating within-person dynamics and intervention-related change in psychopathology, and we illustrate this modeling approach in a large-scale internet-based intervention for depression (N = 1,656). Using eight data points sampled across about 8 weeks, we predicted improvement across the intervention (50% symptom reduction) as a function of early change and symptom variability. RESULTS: Early symptom change was associated with a more likely improvement across therapy. Variability of symptoms beyond change trajectories during the intervention was associated with less likely improvement. CONCLUSIONS: Location-scale models, and dynamic structural equation modeling more generally, are well suited to modeling how patterns of symptom change during psychotherapy are related to important (e.g., therapy) outcomes. Our illustrative application of location-scale modeling showed that symptom variability was associated with less overall improvement in depressive symptoms. However, this finding requires replication with more intensive sampling of symptoms before final conclusions can be drawn on when and how to distinguish maladaptive from adaptive variability during psychotherapy. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

soulspace: Integrated youth mental health care in Berlin, Germany-An introduction to the program and a description of its users.

AIM: A substantial gap between young people's need for mental health care services and their actual access to such services led worldwide organizations (e.g., the WHO) to recommend the implementation of early intervention programs and youth mental health services. Some countries around the world have established structures to meet this recommendation. In this paper, we describe soulspace as the first integrated youth mental health service for young people aged between 15 and 35 years in Berlin, Germany. METHODS: We introduce soulspace as easily accessible mental health care for young people, and we characterize soulspace along the lines of the internationally established eight key principles of integrated youth mental health services (Killackey, et al., 2020, World Economic Forum). Soulspace is a cooperation between clinical outpatient units of psychiatric clinics for adolescents and young adults as well as a community-based counselling service. It provides initial contact, counselling, diagnostics, and treatment. RESULTS: Our analyses of the pathways to soulspace and the characteristics of the soulspace users suggest that the low threshold is a facilitator to help finding for young people in comparison to more conventional early intervention models. That is, having transferred the early intervention center in a youth-facing counselling service as was done in soulspace seems to have reduced the threshold to seek help for families and for young people in need for support. CONCLUSIONS: In summary, with soulspace, an easily accessible mental health care service was established that integrates counselling and specialized psychiatric treatment if needed.

Addressing measurement issues in affect dynamic research: Modeling emotional inertia's reliability to improve its predictive validity of depressive symptoms.

Methodical developments facilitated research on the time-dynamic nature of emotions, introducing novel emotion dynamic measures such as emotional inertia that initially showed significant associations with well-being outcomes like depressive symptoms. However, recent research has challenged this notion by demonstrating that negative emotion inertia's explanatory power in predicting depressive symptoms vanished once mean negative emotion was controlled for. Emotional inertia is often modeled by a two-step approach that first derives estimates of emotional inertia and then uses those to predict depressive symptoms. In the present research, we reanalyzed five experience sampling data sets (N = 875 participants) and demonstrate that this two-step approach leads to low reliability of negative emotion inertia, r¯sb = .52; thereby, attenuating its association with depressive symptoms, as reflected by only 1.3% added explained variance in depressive symptoms above mean negative emotion. As an alternative, we propose a novel one-step approach that adjusts for unreliability of inertia estimates: We introduce a latent inertia factor that is defined by the autocorrelation of various emotion items. Using dynamic structural equation models, this latent factor is simultaneously used to predict depressive symptoms. Here, negative emotion inertia showed good reliability, ω¯ = .81, and explained an additional 4.5% of the total variance in depressive symptoms. Thus, our results demonstrate that emotion dynamic measures can be an important feature of individual well-being if their lower reliability compared with mean negative emotion is modeled and corrected for in dynamic structural equation models. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Stress buffering after physical activity engagement: An experience sampling study.

OBJECTIVES: While encountering daily hassles is a normative experience, it poses a threat to individuals' daily affective well-being. However, physical activity engagement may help to reduce the current stress-related impact on affective well-being (i.e. stress buffering), which we investigate in this study. Furthermore, we examined the possible moderating role of people's global stress context (i.e. exposure to major life events and chronic stress) on this within-person stress-buffering effect. DESIGN: We approached these ideas using six-times-a-day experience sampling assessments over a period of 22 days. METHODS: Drawing on a broad national sample of 156 middle-aged adults from the EE-SOEP-IS study, we aimed to elucidate the naturally occurring within-person dynamics of current stress, physical activity engagement, and momentary affect within individuals' everyday lives. Major life events and chronic stress were measured as between-person variables. RESULTS: Multilevel analyses revealed significant within-person associations of current stress and physical activity engagement with momentary affect. Stress-related negative affect was lower when individuals engaged in physical activity, in accordance with the idea of a within-person stress-buffering effect of physical activity engagement. For individuals exposed to more severe major life events, the stress-buffering effect of physical activity engagement for negative affect was lower. Chronic stress did not moderate the within-person stress-buffering effect. CONCLUSIONS: Overall, results add to the existing literature that links physical activity to increased stress resilience and emphasizes the need for taking the global between-person stress context into account.

The Costs and Benefits of Mindfulness and Reappraisal in Daily Life.

Reappraisal and mindfulness represent two fundamentally different but interconnected ways of dealing with one's emotions: whereas reappraisal is aimed at changing one's thoughts and emotions, mindfulness is aimed at not immediately changing, but appreciating them. Despite this difference, prior research has shown that both are beneficial for one's affective well-being. However, research on the spontaneous use of reappraisal and mindfulness in daily life found that they might be differentially associated with positive and negative affect, with reappraisal and mindful attention being more strongly associated with increased positive affect and mindful acceptance with decreased negative affect. Moreover, the spontaneous use of reappraisal may be less effective than mindfulness in daily life given that it is more cognitively taxing. To compare these possibly different benefits (i.e., change in positive and negative affect) and costs (i.e., feeling depleted), we re-analyzed two experience sampling studies (N = 125 and N = 179). Regarding benefits, endorsing reappraisal and mindful attention was significantly associated with increases in positive affect, whereas endorsing mindful acceptance was significantly associated with decreases in negative affect. Regarding costs, we found that endorsing reappraisal led to more depletion and that reappraisal was selected less often than mindfulness in daily life. Our results demonstrate the importance of assessing not only the different benefits but also the costs of emotion regulation in daily life. Supplementary Information: The online version contains supplementary material available at 10.1007/s42761-022-00178-7.

How within-person effects shape between-person differences: A multilevel structural equation modeling perspective.

Various theoretical accounts suggest that within-person effects relating to everyday experiences (assessed, e.g., via experience sampling studies or daily diary studies) are a central element for understanding between-person differences in future outcomes. In this regard, it is often assumed that the within-person effect of a time-varying predictor X on a time-varying mediator M contributes to the long-term development in an outcome variable Y. In the present work, we demonstrate that traditional multilevel mediation approaches fall short in capturing the proposed mechanism, however. We suggest that a model in which between-person differences in the strength of within-person effects predict the outcome Y mediated via mean levels in M more adequately aligns with the presumed theoretical account that within-person effects shape between-person differences. Using simulated data, we show that the central parameters of this multilevel structural equation model can be recovered well in most of the investigated scenarios. Our approach has important implications for whether or not to control for mean levels in models with within-person effects as predictors. We illustrate the model using empirical data targeting the question if the within-person association of occurrence of daily stressors (X) with daily experiences of negative affect (M) longitudinally predicts between-person differences in change in depressive symptoms (Y). Implications for other multilevel designs and intervention studies are discussed. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Perspectives on resilience: Trait resilience, correlates of resilience in daily life, and longer-term change in affective distress.

Resilience describes successful adaptation in the face of adversity, commonly inferred from trajectories of well-being following major life events. Alternatively, resilience was conceptualised as a psychological trait, facilitating adaptation through stable individual characteristics. Both perspectives may relate to individual differences in how stress is regulated in daily life. In the present study, we combined these perspectives on resilience. Our sample consisted of N = 132 middle-aged adults, who experienced major life events in between two waves of a longitudinal study. We implemented latent change regression models to predict change in affective distress. As predictors, we investigated trait resilience and correlates of resilience in daily life (stressor occurrence, stress reactivity, positive reappraisal, mindful attention, and acceptance), measured using experience sampling (T = 70 occasions). Unexpectedly, trait resilience was not associated with change in distress. In contrast, resilience correlates in daily life, most notably lower stress reactivity, were associated with more favourable change. Higher trait resilience related to higher average mindfulness, higher reappraisal, and lower negative affect. Overall, while trait resilience translated into everyday correlates of resilience, it was not predictive of changes in affective distress. Instead, precursors of changes in well-being may be found in correlates of resilience in daily life.

The impact of affective information on working memory: A psychometric approach.

It has been debated whether working memory (WM) performance is modulated by the valence of the stimuli that are being processed. A recent meta-analysis revealed that at the behavioral level and in individuals without mental health problems, mean-level performance differences in WM tasks with neutral versus affective conditions are small to negligible. We took this finding an important step further by employing a psychometric approach. This is an important refinement of previous work because even in the absence of mean-level differences, differential processing of affective versus nonaffective information may still be occurring. We examined whether at the construct level, 2 latent WM factors could be distinguished in capturing the processing of neutral and affective stimuli, respectively. Applying confirmatory factor analyses (N = 183 university students) to a battery of 18 tasks (3 n-back paradigms crossed with 3 stimulus types and neutral vs. affective valence), the 2 factors correlated perfectly. This result was replicated when neutral stimuli were analyzed together with either positive or negative stimuli. Based on individual differences, the processing of affective versus nonaffective stimuli in WM therefore cannot be distinguished, at least not in a student sample of younger adults. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Sequencing effects of behavioral activation and cognitive restructuring in an Internet-based intervention for depressed adults are negligible: Results from a randomized controlled trial.

OBJECTIVE: Applying elements of cognitive behavioral therapy (CBT) in internet-based interventions (IBIs) is effective in treating depression. However, CBT-based IBIs differ in which kind of components are applied and the order of their application. Furthermore, it is as yet unknown whether such sequencing matters. Using an IBI for depression, we examined whether the sequence of two major CBT components, behavioral activation (BA) and cognitive restructuring (CR), affect patterns of symptom changes and dropout rates. METHOD: Individuals with moderate to mild depressive symptoms (N = 2,304, 59% female) were randomly assigned to two groups: one group that received BA in Modules 2 and 3 and CR in Modules 4 and 5, and another group with the opposite sequence. The component contents were identical. We investigated group differences in dropout rates, symptom changes, and change trajectories across the intervention. RESULTS: The groups had similar dropout rates and showed similar changes pre- to postassessment, and from pre- to 3-, 6-, and 12-month follow-up assessments. Between-group differences were small enough to be considered equivalent. Three classes of change trajectories emerged in both groups, but they did not differ in shape or size and did not show diverging associations with person-level characteristics. CONCLUSIONS: Results suggest that the sequence of the CBT components BA and CR in IBIs for depression does, on average, not systematically impact how individuals change during and after participation, which provides flexibility in designing CBT-based interventions. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

When and How to Regulate: Everyday Emotion-Regulation Strategy Use and Stressor Intensity.

Contextual factors shape emotion regulation (ER). The intensity of emotional stimuli may be such a contextual factor that influences the selection and moderates the effectiveness of ER strategies in reducing negative affect (NA). Prior research has shown that, on average, when emotional stimuli were more intense, distraction was selected over reappraisal (and vice versa). This pattern was previously shown to be adaptive as the preferred strategies were more efficient in the respective contexts. Here, we investigated whether stressor intensity predicted strategy use and effectiveness in similar ways in daily life. We examined five ER strategies (reappraisal, reflection, acceptance, distraction, and rumination) in relation to the intensity of everyday stressors, using two waves of experience-sampling data (N = 156). In accordance with our hypotheses, reappraisal, reflection, and acceptance were used less, and rumination was used more, when stressors were more intense. Moreover, results suggested that distraction was more effective, and rumination more detrimental the higher the stressor intensity. Against our hypotheses, distraction did not covary with stressor intensity, and there was no evidence that reappraisal, reflection, and acceptance were more effective at lower levels of stressor intensity. Instead, when examined individually, reflection and reappraisal (like distraction) were more effective at higher levels of stressor intensity. In sum, stressor intensity predicted ER selection and moderated strategy effectiveness, but the results also point to a more complex ER strategy use in daily life than in the laboratory. Supplementary Information: The online version contains supplementary material available at 10.1007/s42761-021-00087-1.