Age Differences Among Different Sources of Stressor Related Negative Affect.

We examine age differences in the relationship between negative affect (NA) and different indicators of daily stress (interpersonal, health, and financial stressors and perceived stress). Participants completed 56 days of daily diary surveys from Wave 1 of the Notre Dame Study of Health & Well-being. Multi-level modeling allowed us to assess the within-person relationships between daily stress and NA and the cross-level interactions between these daily relationships and cross-sectional age. Each type of stress additively related to daily NA. Older age related to an exacerbated relationship between daily interpersonal stressors and NA, but a weaker relationship between daily perceived stress and NA. Interventions focused on enhancing daily well-being can encourage older adults to ensure they do not have overpacked schedules in regards to social relationships, and encourage midlife and younger adults to engage in activities that disrupt the link between perceived stress and NA.

Within-person changes in religiosity, control beliefs, and subjective well-being across middle and late adulthood.

Given the well-established link between control beliefs and well-being, researchers have turned their attention to characterizing mechanisms that help foster this relationship across the second half of life. Cross-sectional, empirical work has identified a mediating relationship among religiosity and spirituality (R/S), control beliefs, and subjective well-being, such that individuals with higher R/S show higher subjective well-being that is mediated by between-person differences in perceived control. Empirical tests of between-person differences, however, may not represent within-person associations. As such, the present study utilized longitudinal data from the Notre Dame Study of Health & Well-being (NDHWB; N = 1,017) to examine concurrent, within-person associations among three R/S dimensions (i.e., religious coping, religious practices, and spirituality), control beliefs, and subjective well-being. Results from our Bayesian multilevel mediation analyses showed significant within-person associations among these constructs, suggesting potential bidirectionality and circularity in these processes. Cross-sectional age differences and time significantly moderated these associations. In terms of age differences, younger, compared to older, individuals showed stronger positive associations among religious coping and spirituality, control beliefs, and subjective well-being and more negative associations among religious practices, control beliefs, and subjective well-being. Contrarily, the effect of time implied that the relationships among religious coping and spirituality, control beliefs, and subjective well-being became more positive across time. Given this disjunction and that the moderating effect of cross-sectional age by time was not significant, cross-sectional age differences in these relationships likely reflect generational differences in the associations among R/S, control beliefs, and subjective well-being. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Age Differences in Types and Perceptions of Daily Stress.

The present study explores differences in daily stress across individuals of varying ages. Specifically, we explore whether age group (young adult, midlife, late midlife, later life) relates to differences in types of stress (family, friends, partner, health, finances, work), total stress exposure, and perceptions of daily stress intensity. Participants from the Notre Dame Study of Health & Well-being (NDHWB; N = 891) completed daily questionnaires assessing negative small life events and perceived stress for 8 weeks. Findings indicated that young adults reported a higher average number of family, spouse, finance, and work-related stress. Additionally, total daily stress was highest among young adults, and perceived stress was lowest among later life adults. Because daily stress relates to long-term mental and physical stress, gaining a better understanding of how individuals at different points in the life span uniquely experience stress can inform intervention and preventative care techniques aimed at promoting optimal well-being.

Integrative Science Approach to Resilience: The Notre Dame Study of Health & Well-being (NDHWB).

Although many studies have unequivocally demonstrated the promise of understanding resilience to adversity and characterizing the consequences if stress is unabated, needed are dynamic theories and methods to enhance the rigor and interpretation of these assessments. From a dynamic systems perspective, the focus is not whether an individual possesses some fixed ability or unchangeable trait, but rather to understand the flexibility and responsiveness of stress regulation systems to daily hassles and adverse life events. A renewed interest in individual variability allows researchers to see trajectories of change over both short- and long-time scales to understand the developmental course. As a result, it is possible to answer questions, such as, how does the dysregulation in emotion caused by stress, to both within and between daily affect processes, relate to longitudinal trajectories (over time-scales of years) of dysfunction and disease? The overarching goal of the Notre Dame Study of Health & Well-being is to detail the types and qualities of contextual influences, in conjunction with dynamic psychobiological systems, to assess the precursors, concomitant influences and consequences of stress and resilience in the face of adversity on cognitive, health and well-being outcomes.

The positive and negative affect relation in the context of stress and age.

Research suggests that the within-person inverse relationship between negative affect (NA) and positive affect (PA) indicates poorer emotional well-being, and this interaffect correlation fluctuates in relation to the context of the individual. Specifically, age, stress, and global PA all relate to changes in the interaffect correlation. The current study used comprehensive data from the Notre Dame Study of Health and Well-Being, which allowed us to uniquely examine between-person differences in within-person change and variability in the interaffect correlation, thereby examining these constructs from a process-oriented perspective. Midlife and later-life participants (N = 965) completed daily questionnaires assessing stress, NA, and PA. Three-level multilevel models illustrated that the interaffect correlation becomes more negative during times of stress, adults with greater global PA experience a stronger inverse interaffect correlation during times of stress, and days of higher stress relate to a stronger inverse interaffect correlation for older adults compared to midlife adults. The findings illustrate the idiographic nature of these relationships and suggest that later-life adults and adults with high levels of global PA undergoing higher than typical stressful situations experience stronger inverse interaffect correlations. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Daily Religious Coping Buffers the Stress-Affect Relationship and Benefits Overall Metabolic Health in Older Adults.

This study focuses on how daily religious coping mitigates daily stress, regulates emotional responses, and ultimately produces more optimal health outcomes. Participants were 267 community-dwelling older adults from the Later Life Cohort of the Notre Dame Study of Health & Well-being (mean age=72; 63% female). Daily diary data (56 days) were used to assess the effects of daily perceived stress, daily religious coping, and their interaction on daily negative affect. Multi-level modeling (MLM) results suggested that religious coping regulated the effects of stress on negative affect (ß=0.02; p<.01). The intraindividual variability in these day-level effects represent specific dynamic aspects of the individual, referred to as dynamic characteristics. These person-level dynamic characteristics derived from the MLM were correlated with indicators of metabolic health, and predicted healthier values. Most significantly, the stress buffering effects of Religious Coping predicted better metabolic health, as indicated by negative correlations with glucose tolerance (A1c; r = -0.32, p < .001) and the Obesity composite variable (r = -0.23, p = .01). Results demonstrate that the ability to use religious coping to regulate the effects of stress on negative affect may delay the onset of disorders associated with obesity and dysregulation in the metabolic system.

Daily Stress Reactivity Across the Life span: Longitudinal and Cross-Sectional Effects of Age.

OBJECTIVE: Exploration of development requires the use of research designs and process-oriented methodologies that can capture daily fluctuations within individuals, systematic changes within individuals, and differences between individuals. We examine the stress-affect relationship in this way to assess how the relationship between daily stress and negative affect (NA) as well as the relationship between daily stress and positive affect (PA) differs between individuals and changes over time depending on age and stress differences. METHOD: Participants (N = 966) completed daily "burst" assessments of stress, NA, and PA. Three-level multilevel models depicted how cross-sectional age, within-person age changes, and global stress differences impact the daily stress-affect relationship. RESULTS: Findings illustrate that cross-sectional age and the aging process uniquely buffer the stress-NA relationship whereas global stress exacerbates it. Furthermore, older adults as well as adults with low global stress experience a weaker relationship between daily stress and PA as they age, but midlife adults and adults with high global stress experience a stronger relationship. DISCUSSION: These results depict differences in aging trajectories for both midlife and older adults and thus inform intervention and preventative care strategies aimed toward promoting stress regulation.

On Standardizing Within-Person Effects: Potential Problems of Global Standardization.

Person-mean centering has been recommended for disaggregating between-person and within-person effects when modeling time-varying predictors. Multilevel modeling textbooks recommended global standardization for standardizing fixed effects. An aim of this study is to evaluate whether and when person-mean centering followed by global standardization can accurately estimate fixed-effects within-person relations (the estimand of interest in this study) in multilevel modeling. We analytically derived that global standardization generally yields inconsistent (asymptotically biased) estimates for the estimand when between-person differences in within-person standard deviations exist and the average within-person relation is nonzero. Alternatively, a person-mean-SD standardization (P-S) approach yields consistent estimates. Our simulation results further revealed (1) how misleading the results from global standardization were under various circumstances and (2) the P-S approach had accurate estimates and satisfactory coverage rates of fixed-effects within-person relations when the number of occasions is 30 or more (in many conditions, performance was satisfactory with 10 or 20 occasions). A daily diary data example, focused on emotional complexity, was used to empirically illustrate the approaches. Researchers should choose standardization approaches based on theoretical considerations and should clearly describe the purpose and procedure of standardization in research articles.

Time and Other Considerations in Mediation Design.

This article serves as a practical guide to mediation design and analysis by evaluating the ability of mediation models to detect a significant mediation effect using limited data. The cross-sectional mediation model, which has been shown to be biased when the mediation is happening over time, is compared with longitudinal mediation models: sequential, dynamic, and cross-lagged panel. These longitudinal mediation models take time into account but bring many problems of their own, such as choosing measurement intervals and number of measurement occasions. Furthermore, researchers with limited resources often cannot collect enough data to fit an appropriate longitudinal mediation model. These issues were addressed using simulations comparing four mediation models each using the same amount of data but with differing numbers of people and time points. The data were generated using multilevel mediation models, with varying data characteristics that may be incorrectly specified in the analysis models. Models were evaluated using power and Type I error rates in detecting a significant indirect path. Multilevel longitudinal mediation analysis performed well in every condition, even in the misspecified conditions. Of the analyses that used limited data, sequential mediation had the best performance; therefore, it offers a viable second choice when resources are limited. Finally, each of these models were demonstrated in an empirical analysis.

Multilevel autoregressive mediation models: Specification, estimation, and applications.

In the current study, extending from the cross-lagged panel models (CLPMs) in Cole and Maxwell (2003), we proposed the multilevel autoregressive mediation models (MAMMs) by allowing the coefficients to differ across individuals. In addition, Level-2 covariates can be included to explain the interindividual differences of mediation effects. Given the complexity of the proposed models, Bayesian estimation was used. Both a CLPM and an unconditional MAMM were fitted to daily diary data. The 2 models yielded different statistical conclusions regarding the average mediation effect. A simulation study was conducted to examine the estimation accuracy of Bayesian estimation for MAMMs and consequences of model mis-specifications. Factors considered included the sample size (N), number of time points (T), fixed indirect and direct effect sizes, and Level-2 variances and covariances. Results indicated that the fixed effect estimates for the indirect effect components (a and b) and the fixed effects of Level-2 covariates were accurate when N ≥ 50 and T ≥ 5. For estimating Level-2 variances and covariances, they were accurate provided a sufficiently large N and T (e.g., N ≥ 500 and T ≥ 50). Estimates of the average mediation effect were generally accurate when N ≥ 100 and T ≥ 10, or N ≥ 50 and T ≥ 20. Furthermore, we found that when Level-2 variances were zero, MAMMs yielded valid inferences about the fixed effects, whereas when random effects existed, CLPMs had low coverage rates for fixed effects. DIC can be used for model selection. Limitations and future directions were discussed. (PsycINFO Database Record

On the Use of Mixed Markov Models for Intensive Longitudinal Data.

Markov modeling presents an attractive analytical framework for researchers who are interested in state-switching processes occurring within a person, dyad, family, group, or other system over time. Markov modeling is flexible and can be used with various types of data to study observed or latent state-switching processes, and can include subject-specific random effects to account for heterogeneity. We focus on the application of mixed Markov models to intensive longitudinal data sets in psychology, which are becoming ever more common and provide a rich description of each subject's process. We examine how specifications of a Markov model change when continuous random effect distributions are included, and how mixed Markov models can be used in the intensive longitudinal research context. Advantages of Bayesian estimation are discussed and the approach is illustrated by two empirical applications.

A process-oriented perspective examining the relationships among daily coping, stress, and affect.

We assess the daily relationships between age, three functional coping strategies, and positive and negative affect while accounting for the individual's cognitive appraisal of the severity and controllability of their encountered stressor. We collected 56 days of daily data from participants in the Notre Dame Study of Healthy & Well-Being assessing affect, the most bothersome event experienced each day, and coping strategies used to deal with that event (N = 371; Age 44-87; M = 67.41; SD = 8.87). Multi-level modeling allowed us to explore and compare the between- and within-person effects. The main effects revealed that coping strategies relate to affect differently. The interaction terms revealed that the effectiveness of each coping strategy depended on characteristics of the encountered stressor and/or characteristics of the individual. Average values of stress severity, Altering the Meaning, and Dispelling the Effects more strongly related to PA or NA than daily fluctuations on these constructs. Findings illustrate that certain coping strategies target affect differently. Approaching research questions regarding stress and coping with a process-oriented perspective, through the use of daily data, allows for a more thorough understanding of the real-time, lived relationships among the individual, stress, and coping.

Extending multivariate distance matrix regression with an effect size measure and the asymptotic null distribution of the test statistic.

Person-centered methods are useful for studying individual differences in terms of (dis)similarities between response profiles on multivariate outcomes. Multivariate distance matrix regression (MDMR) tests the significance of associations of response profile (dis)similarities and a set of predictors using permutation tests. This paper extends MDMR by deriving and empirically validating the asymptotic null distribution of its test statistic, and by proposing an effect size for individual outcome variables, which is shown to recover true associations. These extensions alleviate the computational burden of permutation tests currently used in MDMR and render more informative results, thus making MDMR accessible to new research domains.

Finding structure in data using multivariate tree boosting.

Technology and collaboration enable dramatic increases in the size of psychological and psychiatric data collections, but finding structure in these large data sets with many collected variables is challenging. Decision tree ensembles such as random forests (Strobl, Malley, & Tutz, 2009) are a useful tool for finding structure, but are difficult to interpret with multiple outcome variables which are often of interest in psychology. To find and interpret structure in data sets with multiple outcomes and many predictors (possibly exceeding the sample size), we introduce a multivariate extension to a decision tree ensemble method called gradient boosted regression trees (Friedman, 2001). Our extension, multivariate tree boosting, is a method for nonparametric regression that is useful for identifying important predictors, detecting predictors with nonlinear effects and interactions without specification of such effects, and for identifying predictors that cause 2 or more outcome variables to covary. We provide the R package "mvtboost" to estimate, tune, and interpret the resulting model, which extends the implementation of univariate boosting in the R package "gbm" (Ridgeway, 2015) to continuous, multivariate outcomes. To illustrate the approach, we analyze predictors of psychological well-being (Ryff & Keyes, 1995). Simulations verify that our approach identifies predictors with nonlinear effects and achieves high prediction accuracy, exceeding or matching the performance of (penalized) multivariate multiple regression and multivariate decision trees over a wide range of conditions. (PsycINFO Database Record

Affective health bias in older adults: Considering positive and negative affect in a general health context.

RATIONALE: Because subjective health reports are a primary source of health information in a number of medical and research-based contexts, much research has been devoted to establishing the extent to which these self-reports of health correspond to health information from more objective sources. One of the key factors considered in this area is trait affect, with most studies emphasizing the impact of negative affect (negative emotions) over positive affect (positive emotions), and focusing on high-arousal affect (e.g., anger, excitement) over moderate- or low-arousal affect (e.g., relaxed, depressed). OBJECTIVES: The present study examines the impact of both Positive and Negative Affect (PA/NA)-measured by items of both high and low arousal-on the correspondence between objective health information and subjective health reports. Another limitation of existing literature in the area is the focus on samples suffering from a particular diagnosis or on specific symptom reports; here, these effects are investigated in a sample of community-dwelling older adults representing a broader spectrum of health. METHOD: 153 older adults (Mage = 71.2) took surveys assessing Perceived Health and Affect and underwent an objective physical health assessment. Structural equation modeling was used to investigate the extent to which the relationship between Objective Health and Perceived Health was moderated by PA or NA, which would indicate the presence of affective health bias. RESULTS: Results reveal a significant moderation effect for NA, but not for PA; PA appeared to serve a more mediational function, indicating that NA and PA operate on health perceptions in distinct ways. CONCLUSIONS: These findings provide evidence that in our high-functioning, community-dwelling sample of older adults, a) affective health bias is present within a general health context, and not only within specific symptom or diagnostic categories; and b) that both PA and NA play important roles in the process.

Aging and the HPA axis: Stress and resilience in older adults.

Hypothalamic-pituitary-adrenal (HPA) axis function may change over the course of aging, and altered diurnal or stress-induced secretion of the hormone cortisol could predispose older adults to negative health outcomes. We propose that psychological resilience may interact with diurnal cortisol to affect health outcomes later in life. Emotion regulation and social support are two constructs that contribute to resilience and exhibit age-specific patterns in older adults. Determining how the use of resilience resources interacts with age-related diurnal cortisol will improve our understanding of the pathways between stress, resilience, and well-being. In this review, we assess published studies evaluating diurnal cortisol in older adults to better understand differences in their HPA axis functioning. Evidence thus far suggests that diurnal cortisol may increase with age, although cross-sectional studies limit the conclusions that can be drawn. We also review extant evidence connecting age-specific signatures of emotion regulation and social support with diurnal cortisol. Conclusions are used to propose a preliminary model demonstrating how resilience resources may modulate the effects of cortisol on health in aging.

FINANCIAL STRESS, NEIGHBORHOOD STRESS, AND WELL-BEING: MEDIATIONAL AND MODERATIONAL MODELS.

This study explores whether high quality neighborhoods or social integration have protective effects on psychological well-being, especially in the face of financial challenges. Previous research suggests that low levels of financial stress, lower neighborhood stress, and social integration are each associated with greater levels of well-being; few studies, however, investigate these contextual variables in confluence. Data from the Notre Dame Study of Health and Well-Being were used to investigate whether (a) neighborhood stress mediates the relationship between financial stress and psychological well-being and (b) social integration moderates the relationship between neighborhood stress and psychological well-being. Results were consistent with both hypotheses and were replicated in data from Successful Aging in Context. These results suggest that proximal contextual variables, such as social integration and neighborhood stress can arbitrate the effect that less proximal contextual variables, such as economic conditions, have on individuals' psychological well-being.

Trajectories of social support and well-being across the first two years of widowhood.

The death of a spouse can be one of the most challenging events an older adult can face, yet many exhibit resilience. The present study examined the trajectories of structural and functional social support components, depression, and life satisfaction across the first two years of widowhood. The majority of structural and functional support trajectories exhibited stability across the first two years postloss. However, emotional support and support provided by family members did display a slight decline across time. Depression showed a linear pattern across time (e.g., decline in depressive symptomology) and life satisfaction demonstrated evidence of a one-year anniversary effect.

Synchrony in affect among stressed adults: the Notre Dame Widowhood Study.

OBJECTIVES: This study examined 3 types of synchrony (i.e., asynchrony, synchrony, and desynchrony) between positive and negative affect in a sample of adult widows and assessed whether individual differences in synchrony type predicted adjustment over time. METHODS: Participants included 34 widows from the Notre Dame Widowhood Study, who reported on their positive and negative affect across a 98-day period following conjugal loss and responded to follow-up questionnaires every 4 months for 1 year. RESULTS: Multilevel models revealed that although the nomothetic average of the synchrony scores indicated a negative or desynchronous relationship between positive and negative affect, an ideographic view identified evidence of individual differences. Furthermore, patterns of change in the relationship between positive and negative affect suggested that, over time, desynchrony in affect generally abates for widows but individual differences were predictive of adjustment over time. Furthermore, distinct trajectories that the women follow from the time of their husband's death include patterns of resilience and delayed negative reaction, each of which predicted present levels of grief. DISCUSSION: Discussion focuses on (a) individual differences in the within-person structure in affect, (b) the dynamic processes involving negative and positive affect, and (c) the predictive power of synchrony scores.

Trait Stress Resistance and Dynamic Stress Dissipation on Health and Well-Being: The Reservoir Model.

Daily data from the NDHWB (n = 783; age range 37-90) were analyzed to produce 'dynamic characteristic' estimates of stress input and dissipation. These were used in multi-level modeling (with age and trait stress resistance) to predict depression and health trajectories. Main effects suggest that dissipation and stress resistance predict lower depression and better health, but lower stress input was only related to lower depression. Interactions revealed that subjects with above average stress resistance had lower depression irrespective of their ability to dissipate stress, but for individuals low in trait resistance those with better stress dissipation show lower depression and better health.