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The present study examines the extent to which a two-factor model of affect explains how caregiving appraisals experienced by caregivers influence their own well-being. We used data from three waves of Nation Study of Caregiving (NSOC) to conduct latent growth curve models with the time-varying predictors to investigate the effect of between-person (BP) and within-person (WP) caregiving appraisals on positive and negative affect. Furthermore, we simultaneously modeled WP differences in activity participation and affective experience with multilevel modeling. Then, we tested the moderating effect of activity participation in the association between WP caregiving appraisals and emotional valence. We found that BP and WP caregiving negative appraisal also contribute to caregiver positive affect similar to that of negative affect. Time-varying effects of negative appraisals and emotional valence are consistent with the two-factor model. Future longitudinal investigations could target WP and BP activity participation to alleviate caregiving cognitive appraisal among caregivers.
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Introduction: The aging population in South Korea faces numerous health challenges, one of which is the decline in Activities of Daily Living (ADL) and Instrumental Activities of Daily Living (IADL). This study aims to investigate the patterns of change in ADL and IADL among older adults and examines how these patterns vary between individuals with and without dementia. Methods: We conducted an analysis of data collected from the Korea Longitudinal Study of Ageing (KLoSA) between 2006 and 2022. Our cohort consisted of individuals aged 45 and older with non-dementia conditions, including mild cognitive impairment (N=6042), and a smaller group with dementia (N=91). Using Latent Growth Curve Models, we explored the developmental trajectories of ADL and IADL among our sample. Results: Our findings indicate a linear decline in both ADL and IADL scores as individuals age. The decline in IADL was more pronounced in the dementia group, suggesting a greater sensitivity to sociocultural factors within this domain. The data revealed that individuals with dementia had consistently lower ADL and IADL scores. Notably, the variance in scores within the dementia group increased with age, signifying a worsening in daily living performance and an increase in individual variation (F=226.630, p<.001). Discussion: The results of this study underscore the impact of dementia on both the self-regulation function and the social and cultural aspects of daily living performance, particularly reflected in IADL scores. These findings point to the necessity for comprehensive care strategies that address the multifaceted needs of older adults with dementia, including support for complex daily activities that are influenced by sociocultural factors.
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Competency-based teasing has been identified as a risk factor for children's depressive symptoms. However, the specific psychological mechanisms mediating this relationship are not well understood, especially in the context of Chinese culture. This study examined the relationship between competency-based teasing, subsequent depressive symptoms, and the possible mediating role of positivity in Chinese children by using parallel process latent growth curve modelling. Gender differences were also explored. A sample of 4376 Chinese children (55.1% boys; age: M = 9.98 years, SD = 0.88) completed measurements of the relevant constructs on five occasions across 2 years, using half-year intervals. The findings revealed that competency-based teasing was significantly positively associated with subsequent depressive symptoms in Chinese children. Furthermore, positivity mediated this relationship in girls, but not in boys. The results suggest that positivity-cultivating and gender-specific interventions may be effective to reduce the risk of depressive symptoms in Chinese children.
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Parallel process latent growth curve mediation models (PP-LGCMMs) are frequently used to longitudinally investigate the mediation effects of treatment on the level and change of outcome through the level and change of mediator. An important but often violated assumption in empirical PP-LGCMM analysis is the absence of omitted confounders of the relationships among treatment, mediator, and outcome. In this study, we analytically examined how omitting pretreatment confounders impacts the inference of mediation from the PP-LGCMM. Using the analytical results, we developed three sensitivity analysis approaches for the PP-LGCMM, including the frequentist, Bayesian, and Monte Carlo approaches. The three approaches help investigate different questions regarding the robustness of mediation results from the PP-LGCMM, and handle the uncertainty in the sensitivity parameters differently. Applications of the three sensitivity analyses are illustrated using a real-data example. A user-friendly Shiny web application is developed to conduct the sensitivity analyses.
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Growth curve models are popular tools for studying the development of a response variable within subjects over time. Heterogeneity between subjects is common in such models, and researchers are typically interested in explaining or predicting this heterogeneity. We show how generalized linear mixed-effects model (GLMM) trees can be used to identify subgroups with different trajectories in linear growth curve models. Originally developed for clustered cross-sectional data, GLMM trees are extended here to longitudinal data. The resulting extended GLMM trees are directly applicable to growth curve models as an important special case. In simulated and real-world data, we assess performance of the extensions and compare against other partitioning methods for growth curve models. Extended GLMM trees perform more accurately than the original algorithm and LongCART, and similarly accurate compared to structural equation model (SEM) trees. In addition, GLMM trees allow for modeling both discrete and continuous time series, are less sensitive to (mis-)specification of the random-effects structure and are much faster to compute.
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BACKGROUND: The bidirectional relationship between physical health (PH) and depressive symptoms (DS) remains unclear. METHODS: Data were extracted from the Health and Retirement Study in the United States. PH was measured with a composite of chronic diseases, functional limitations and difficulties in basic and instrumental activities of daily living, and DS with a modified Center for Epidemiological Studies of Depression. Latent growth curve models (LGCM) were employed to examine how the change in PH or DS affected their mutual trajectories in later life. In addition, multilevel models were utilized. RESULTS: There were 6144 participants included, with an average age of 69.82 ± 6.85 years at baseline, of whom 3686 (59.99 %) were women. PH scores increased from 5.65 in 2010 to 7.72 in 2018, while depression scores increased from 1.14 to 1.31. LGCM results showed that the initial levels of PH and DS were associated (ß = 0.558, P < .001), and the initial level of PH could predict the trajectory of DS (ß = 0.089, P < .001). Likewise, the initial level of DS was also related to initial PH (ß = -0.563, P < .001) but couldn't predict the trajectory of PH. Furthermore, the slopes of PH and DS were predicted bidirectionally by each other. Two-level logistic models further demonstrated the bidirectional association between PH and DS. CONCLUSION: There was a bidirectional association between physical health and depressive symptoms, which highlights the necessity of comprehensive health management for older adults with poor physical health or depression symptoms.
Subject(s)
Activities of Daily Living , Depression , Health Status , Humans , Female , Male , Aged , Depression/epidemiology , Longitudinal Studies , United States/epidemiology , Middle Aged , Retirement/statistics & numerical data , Retirement/psychology , Chronic Disease/epidemiologyABSTRACT
BACKGROUND AND OBJECTIVES: Social isolation has been recognized as a social problem with negative health consequences. Using data from 3 waves of the Health and Retirement Study, this study aimed to examine the long-term impact of social isolation on loneliness and depressive symptoms and to explore the moderating effect of resilience. RESEARCH DESIGN AND METHODS: This study comprised 3,681 U.S. adults aged 60 and older at the baseline wave. Social isolation index was constructed using 5 indicators, including not married or cohabitating with a partner, no social participation, and less than monthly contacts with children, family members, or friends. Loneliness was measured by the University of California Los Angeles (UCLA) Loneliness Scale and depressive symptoms were measured by the Center for Epidemiological Studies-Depression scale. The moderator of resilience was assessed by the simplified resilience score. Latent growth curve models with robust standard errors were estimated. RESULTS: The results of latent growth curve models showed that social isolation was significantly associated with more initial loneliness and depressive symptoms. However, social isolation was associated with a slower increasing rate of loneliness, but no significant relationship with the change rate of depressive symptoms. Furthermore, resilience significantly buffered the negative effect of social isolation on the initial level of depressive symptoms. DISCUSSION AND IMPLICATIONS: The findings underscore the importance of enacting strategies and interventions targeting resilience to address social isolation and its negative consequences among older adults.
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Depression , Loneliness , Resilience, Psychological , Social Isolation , Humans , Loneliness/psychology , Social Isolation/psychology , Aged , Male , Female , Depression/psychology , Depression/epidemiology , Middle Aged , Aged, 80 and over , United States , Longitudinal StudiesABSTRACT
Objectives: This study examined the association between self-reported visual difficulty and age-related cognitive declines among older Chinese adults and how the timing of visual difficulty onset plays a role in cognitive trajectories. Methods: Data were drawn from the 2011-2018 wave of the China Health and Retirement Longitudinal Study, involving 9974 respondents aged 60 years or older (mean age 65.44 years, range 60-101 years). Results: At baseline, 14.16% respondents had self-reported visual difficulty. Growth curve models showed that Chinese older adults with visual difficulty experienced a faster decline in cognitive function compared to those without visual difficulty (ß = -0.02, p < .01). Older adults who began experiencing visual difficulty between 61 and 75 years of age had steeper cognitive declines compared to those with earlier or later onset (ß = -0.05, p < .01). Discussion: Older adults with self-reported visual difficulty experience faster rates of cognitive decline. Future research should explore potential factors that underlie the association between onset timing of visual difficulty and cognitive function.
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Using the Consequences of COVID-19 (COCO) dataset (quota sample of the adult Italian population, surveyed seven times by email), we analysed the trend of trust in political (political parties, parliament and local administrations), super partes (president of the Republic, judiciary and police) and international (the European Union and the United Nations) institutions from June 2019 to October 2022. Three latent growth curve models showed that trust in political institutions increased between June 2019 and April 2020 and subsequently decreased below the pre-pandemic level. Trust in super partes institutions decreased slightly between June 2019 and April 2020, decreased from April 2020 to April 2022 and increased in the subsequent months. Trust in international institutions declined between June 2019 and April 2020 and then returned to pre-pandemic levels. Three piecewise decompositions showed different trends in trust for non-populist voters, populist voters and non-voters. Strengths, weaknesses and possible developments of the study are discussed.
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Trust , Voting , Adult , Humans , PoliceABSTRACT
OBJECTIVE: Body mass index (BMI) trajectories are associated with night-time sleep, but it is not clear how they relate to daytime sleepiness in population data. This study aimed to examine longitudinal associations between levels and changes in daytime sleepiness and BMI trajectories among men and women. METHODS: We estimated growth curve models among 827 participants in the Wisconsin Sleep Cohort Study (mean [sd] age = 55.2 [8.0] years at baseline). The outcome variable was BMI (kg/m2) and the key predictor was daytime sleepiness measured by Multiple Sleep Latency Test (MSLT) scores. Covariates included demographics, health behaviors, retirement status, stimulant use, and depressive symptoms. In sensitivity analyses, we evaluated the potential effects of cardiovascular disease, shift work status, and sleep apnea on the robustness of sleepiness and BMI associations. RESULTS: At the between-person level, men who were sleepier had higher BMI levels. At the within-person level, age moderated the positive association between sleepiness and BMI among women. Specifically, young women who became sleepier over time gained more BMI than older women with comparable increases in sleepiness. Furthermore, while BMI tended to increase with age among women, BMI trajectories were steeper among sleepy women than among well-rested women, who experienced less increase in BMI over time. CONCLUSION: The study suggested that levels and changes in daytime sleepiness as objectively measured by MSLT scores are associated with body mass among adults.
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Body Mass Index , Humans , Male , Female , Middle Aged , Wisconsin/epidemiology , Cohort Studies , Sleepiness , Adult , Longitudinal StudiesABSTRACT
Proximate determinants theory considers infertility rates a risk factor for lower fertility rates, but the assumption that people who perceive infertility will have fewer children has not been tested. This study investigates the association of self-perceived infertility with the number of children people have had after 11 years. Infertility implies reduced chances of conception (rather than sterility), but people do not always consistently perceive infertility over time. If people who think they are infertile at one time can later report no infertility, then does self-perceived infertility necessarily lead to having fewer children? We answer this question by analyzing 11 waves of the German family panel (pairfam) data using negative binomial growth curve models for eight core demographic subgroups created by combinations of gender (men/women), parity (0/1+children), and initial age groups (25-27 and 35-37). Those who repeatedly perceived themselves to be infertile (three times or more) had fewer children than those who perceived themselves to be infertile once or twice in only four of eight gender by initial parity by age groups. Only in four groups did people who perceived themselves to be infertile once or twice have fewer children than those who never perceived themselves to be infertile in both the unadjusted and adjusted models. Thus, self-perceived infertility does not necessarily result in fewer children. Rather, the association depends upon life course context and gender.
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Researchers are often interested in examining between-individual differences in within-individual processes. If the process under investigation is tracked for a long time, its trajectory may show a certain degree of nonlinearity, so that the rate of change is not constant. A fundamental goal of modeling such nonlinear processes is to estimate model parameters that reflect meaningful aspects of change, including the parameters related to change and other parameters that shed light on substantive hypotheses. However, if the measurement occasion is unstructured, existing models cannot simultaneously estimate these two types of parameters. This article has three goals. First, we view the change over time as the area under the curve (AUC) of the rate of change versus time ( r - t ) graph. Second, using the instantaneous rate of change midway through a time interval to approximate the average rate of change during that interval, we propose a new specification to describe longitudinal processes. In addition to obtaining the individual change-related parameters and other parameters related to specific research questions, the new specification allows for unequally spaced study waves and individual measurement occasions around each wave. Third, we derive the model-based interval-specific change and change from baseline, two common measures to evaluate change over time. We evaluate the proposed specification through a simulation study and a real-world data analysis. We also provide OpenMx and Mplus 8 code for each model with the novel specification.
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Individuality , Models, Statistical , Humans , Computer SimulationABSTRACT
Much of the literature on fertility intentions has shown that they are broadly predictive of fertility behaviour. Fertility intentions tend to change over a person's life. How religiosity affects these changes over time has rarely been the subject of investigation. In this paper, we focus on whether and how religiosity affects trajectories of lifetime fertility intentions. Specifically, we examine whether highly religious people start with higher fertility intentions and are more likely to sustain them during their life course compared to their less religious counterparts. We apply random and fixed effects growth curve models to data from the German family panel pairfam, using a sample of 6214 women and 5802 men aged 14-46. We find that religiosity mainly contributes to explain the starting level at teenage years but not the trajectories of lifetime fertility intentions as people get older. Highly religious people start with higher intentions than less religious people. However, similarly to less religious people they experience a decline in their fertility intentions with age. This study demonstrates that religiosity is an important variable in research on fertility intentions but with changing relevance over the life course.
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Fertility , Intention , Male , Adolescent , Female , HumansABSTRACT
OBJECTIVES: (1) To characterize the average trajectories of frailty over time in Chinese community-dwelling older adults; (2) To assess the effects of neighborhood structural and individual characteristics on frailty progression. DESIGN: A nationally representative prospective cohort study. SETTING: Communities in 28 provinces, China. PARTICIPANTS: 6238 respondents aged 60 and above in 447 communities from four waves of the China Health and Retirement Longitudinal Study. MEASUREMENTS: Frailty was measured using the 61-item Frailty Index (FI). RESULTS: The trajectory of FI was nonlinear, with an average growth rate of 0.025 that significantly slows down at the rate of 0.002 per year. Older, male, and uninsured respondents showed faster rates of growth in FI over time than younger, female, and insured counterparts. Respondents living in neighborhoods with a higher percentage of the older population and rural villages showed slower rates of growth in FI over time. CONCLUSION: Expanding health insurance coverage and keeping a high clustering of the elderly in neighborhoods may be the potential strategies for population-level frailty prevention and interventions.
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Frailty , Retirement , Aged , Humans , Male , Female , Frailty/epidemiology , Longitudinal Studies , Frail Elderly , Prospective Studies , China/epidemiologyABSTRACT
There is substantial rank-order stability in children's mathematical skills throughout development. Research has shown that children who enter school with relatively low math skills are unlikely to catch up to peers who begin kindergarten with more developed math skills. Emerging evidence suggests that children's executive function skills might play an important role in shaping the rate and stability of mathematical skill development during early development. Therefore in the present study, we used data from the Early Childhood Longitudinal Study-Kindergarten Cohort 2010-11-a prospective sample of over 18,000 children in the United States-to examine executive function as an antecedent to characteristics of growth in math skills and to test whether executive function moderates the longitudinal stability of math achievement from kindergarten through second grade. Latent growth curve models reveal that executive function is related to not only the level of math skills at school entry but also to the rate of growth in early elementary years. Moreover, we found that executive function moderated the stability of math achievement from kindergarten to second grade, suggesting that early executive function skills can serve as a compensatory mechanism for children who enter school with lower levels of mathematical skills. These findings might have important implications for narrowing gaps in math achievement during early elementary school.
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The Flynn effect refers to increases over time in measured (particularly fluid) intelligence of approximately 3 IQ points per decade. We define the Flynn effect at the family level, using longitudinal data and two new family-level cohort definitions. Multilevel growth curve analyses of the National Longitudinal Survey of Youth 1979 data showed that children in families with later-born mothers had higher average PIAT math scores, and lower average reading comprehension scores and growth, in young and middle childhood. Children in families where the first child was born later had higher average PIAT math, reading recognition, and reading comprehension scores, as well as larger developmental growth. The latter family-level Flynn effects were of higher magnitudes than the usual individual-level Flynn effect found in previous studies. Our results, showing family level-intercept and slope Flynn effects for both maternal birthyear and first child birthyear, have implications for research aiming to explain the Flynn effect.
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With the advent of Complex dynamic systems theory (CDST) in the field of second language question (SLA), the need for suitable CDST compatible methods for the investigation of temporal change in L2 affective variables has been felt more than before. One of the innovative methods for this purpose is latent growth curve modeling (LGCM), which has recently drawn the attention of SLA scholars. However, the application of this method is still a burgeoning demand in SLA. In response to this demand, the present study provides a review of the conceptualization, significance, and technical features of the implementation of LGCM. In doing so, this review suggests a number of practices via which LGCM has been introduced in SLA. Additionally, some practical implications are provided for SLA researchers to enhance their literacy of LGCM. Finally, future research suggestions for the progress of the use of this method in SLA are discussed.
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This study aims to understand the direct and indirect effects of poverty trajectories on maternal depression trajectories mediated by material hardship trajectories. A latent growth mediation model was tested using a predominantly low-income and mostly unmarried sample of mothers from the Fragile Families and Child Wellbeing Study, a national birth cohort of racially diverse mothers (N = 3999). Measures included family poverty, material hardship, and maternal depression from 5 waves of data which tracked mothers starting 1 year after childbirth until the child reached 15 years of age. The results revealed that (1) family poverty was associated with material hardship and maternal depression, and material hardship was related to maternal depression at the trajectory level and the rate of change, with the exception of the relationships between the rate of change in family poverty and the rate of change in maternal depression; (2) material hardship mediated the relationship between family poverty and maternal depression at the initial trajectory levels, and the rate of change in material hardship fully mediated the relationship between the rate of change in poverty and the rate of change in maternal depression. This study provides further evidence that alleviating material hardship might be a promising avenue to reducing maternal depression.
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Depression , Poverty , Depression/epidemiology , Female , Humans , Mothers , United States/epidemiologyABSTRACT
OBJECTIVES: We draw from the life course and stress process frameworks to examine how experiencing disability in early life influences mental health in adulthood. METHODS: Data come from the Health and Retirement Study Cross-Wave Childhood Health and Family Aggregated Data file (2008-2018, n = 15,289). Childhood disability status is a retrospective self-report of whether respondents were disabled for six months or more because of a health problem before the age of 16 (n = 581). We used age-based growth curve models to construct trajectories of depressive symptoms by childhood disability status. RESULTS: Respondents who experienced childhood disability exhibit more depressive symptoms at age 50 compared to those who did not experience this stressor. However, there is no difference in the growth of depressive symptoms with age between these groups, suggesting maintained inequality over the late adulthood life course. DISCUSSION: Findings suggest that childhood disability has long-term implications for life course mental health.
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Disabled Persons , Mental Health , Adult , Depression/psychology , Humans , Longitudinal Studies , Retirement/psychology , Retrospective StudiesABSTRACT
OBJECTIVE: Effortful control (EC) has been conceptualized as a higher-order construct defined by a class of self-regulatory mechanisms. However, the developmental higher-order structure of EC has seldom been investigated with a thorough psychometric analysis. To begin to fill this gap in the literature, data were obtained from parents and teachers of 185 children (age at T1: M = 9.43 y/o, SD = 1.17) every 2 years for 8 years. METHOD: We used a structural equation modeling approach for assessing if EC develops as a higher-order factor superordinate to three commonly studied self-regulatory mechanisms, namely inhibitory control (IC), attention focusing (AF), and attention shifting (AS). RESULTS: Results showed that (a) IC, AF, and AS followed a similar pattern of growth, (b) EC displayed an acceptable degree of scalar longitudinal invariance when operationalized as a latent variable indicated by IC, AF, and AS, (c) a higher-order structure explained the co-development of IC, AF, and AS, and (d) stability and change in EC negatively predicted externalizing symptoms, much better than the stability and change of IC, AF, and AS, but only for parents' reports. CONCLUSION: Overall, the higher-order structure of EC was supported, but our results also indicated that there is a certain degree of uniqueness in its facets.