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Objectives Sensorineural hearing loss (presbycusis) affects up to half of the adults, is associated with cognitive decline. Whether this association reflects the cause, the consequence, or parallel processes driven by other factors remains unclear. Both presbycusis and cognition are linked to elevated metabolic risk, which in turn raises with age. Method In a multioccasion longitudinal design, we used latent change score models with strong factorial invariance to assess the change in pure-tone threshold auditory function, fluid intelligence, metabolic risk, variability therein, and the dynamic relationships among the 3 domains. We examined, up to 4 times over more than 7 years, a sample of relatively healthy 687 adults (aged 18.17–83.25 years). Results We found that levels of auditory and cognitive functioning at time t-1 influence each other’s subsequent change between times t-1 and t, even when controlling for the reciprocal effects of metabolic risk on both. Thus, auditory and cognitive functioning do not only decline in parallel in healthy adults, but also affect each other’s trajectories. To the best of our knowledge, this is the first long-term study with such evidence. Discussion Our results are in accord with extant hypotheses about auditory-cognitive associations in old age (e.g., social isolation, cognitive load, increased inflammation, reduced gene expression, and other microvascular or neuropathological factors). They also echo previous reports underscoring the need for improving access to hearing aids and other rehabilitative services aimed at reducing hearing loss. If applied early in the aging process, such interventions may mitigate cognitive decline.

A key neuro-cognitive function that promotes autonomy and everyday functioning in old age is prospective memory (PM), defined as the capacity to remember to carry out intentions in the future. This study aimed at understanding if non-cognitive factors of metacognition and motivation are related to event-based and time-based laboratory PM, as well as to naturalistic PM in older adults, above and beyond the influences of neuropsychological determinants. We applied regression analyses predicting individual differences in classical PM tasks, in a sample of 99 healthy older participants (aged 64–88 years). Results indicated that metacognition, measured as memory self-efficacy and perceived competence in cognitive tasks, was related to laboratory time-based PM. Consistency of interests, a motivational factor, was associated with naturalistic PM. None of the non-cognitive factors related to event-based PM. Our study underlines the importance of considering non-cognitive characteristics when evaluating PM capacity, a key component of cognitive aging.

Contains fulltext : 248857.pdf (Publisher’s version ) (Open Access) Higher socio-economic status (SES) has been proposed to have facilitating and protective effects on brain and cognition. We ask whether relationships between SES, brain volumes and cognitive ability differ across cohorts, by age and national origin. European and US cohorts covering the lifespan were studied (4-97 years, N = 500 000; 54 000 w/brain imaging). There was substantial heterogeneity across cohorts for all associations. Education was positively related to intracranial (ICV) and total gray matter (GM) volume. Income was related to ICV, but not GM. We did not observe reliable differences in associations as a function of age. SES was more strongly related to brain and cognition in US than European cohorts. Sample representativity varies, and this study cannot identify mechanisms underlying differences in associations across cohorts. Differences in neuroanatomical volumes partially explained SES-cognition relationships. SES was more strongly related to ICV than to GM, implying that SES-cognition relations in adulthood are less likely grounded in neuroprotective effects on GM volume in aging. The relatively stronger SES-ICV associations rather are compatible with SES-brain volume relationships being established early in life, as ICV stabilizes in childhood. The findings underscore that SES has no uniform association with, or impact on, brain and cognition.

In many life-course research fields (e.g., sociology, psychology, economy, medicine, epidemiology) data often include repeated assessments of a variable and a dichotomous indicator of an event of interest. Such data naturally lend themselves to answering questions concerning the associations between individual trajectories and the occurrence and timing of discrete events. For instance, is one’s trajectory of health satisfaction spanning over dozens of years related to the risk of dying at a given age? Mixed-effect and survival models are well established to separately study such variables: mixed-effect models can conveniently be applied to characterize one’s trajectory, whereas survival models are ideally suited to study the risk of an event occurring. Joint longitudinal and survival models conveniently allow studying the associations between statistical characteristics of individual-based trajectories and individual survival features. In this chapter we first describe aspects of both longitudinal and survival models, to then discuss how the two can jointly be estimated, and thereby conditioned on each other, in joint models. We illustrate joint models on data from the publicly available Swiss Household Panel.

History-graded increases in older adults’ levels of cognitive performance are well documented, but little is known about historical shifts in within-person change: cognitive decline and onset of decline. We combined harmonized perceptual-motor speed data from independent samples recruited in 1990 and 2010 to obtain 2,008 age-matched longitudinal observations (M = 78 years, 50% women) from 228 participants in the Berlin Aging Study (BASE) and 583 participants in the Berlin Aging Study II (BASE-II). We used nonlinear growth models that orthogonalized within- and between-person age effects and controlled for retest effects. At age 78, the later-born BASE-II cohort substantially outperformed the earlier-born BASE cohort (d = 1.20; 25 years of age difference). Age trajectories, however, were parallel, and there was no evidence of cohort differences in the amount or rate of decline and the onset of decline. Cognitive functioning has shifted to higher levels, but cognitive decline in old age appears to proceed similarly as it did two decades ago. bundesministerium für bildung und forschung https://doi.org/10.13039/501100002347 bundesministerium für bildung und forschung https://doi.org/10.13039/501100002347 bundesministerium für familie, senioren, frauen und jugend https://doi.org/10.13039/501100016371 Berlin-Brandenburg Academy of Sciences’ Research Group on Aging and Societal Development bundesministerium für forschung und technologie https://doi.org/10.13039/501100004937

Previous studies report that monitoring the passing of time by checking a clock either frequently or strategically (immediately before a target time) improves the likelihood of remembering to perform a planned intention at a specific time (i.e., time-based prospective memory [TBPM]). Critically, strategicness of clock-checking is usually measured as the number of clock-checks during the last time interval before the target time-an operationalization where strategicness actually intertwines with absolute frequency of clock-checking and may not properly account for age effects in TBPM performance. To disentangle the respective contribution of frequent versus strategic clock-checking to the age-related decrease in TBPM performance, we propose a new, more fine-grained indicator of strategicness (i.e.

Abstract. Although personal goals give meaning to life and contribute to well-being, achieving goals can become difficult in older adults faced with age-related challenges. A group of 49 older adults aged 65 to 92 years completed a semistructured interview on personal goals, obstacles to goal achievement, and contributors to well-being. Using thematic analysis, we identified several types of goals contributing to well-being and general aspects of well-being. Results revealed that, although older people might say that they no longer have major goals in their lives, they end up mentioning many activities that theoretically are goals. Many of these activities are geared toward maintaining or increasing their general well-being. Of importance, they report few complaints regarding goal achievement, which they explained by (1) reducing the number and breadth of their goals, (2) adjusting and reevaluating these goals, and (3) overcoming difficulties and stabilizing current functioning, thereby maintaining a sense of continuity and satisfactory levels of well-being. This study illustrates the interactions between resources and stressors from the viewpoint of older adults. Taken together, the results advocate for the usefulness of the functional quality of life model and proactive approaches to successful aging, and they provide directions for individualized interventions in the elderly.

It has been shown that a mindfulness construct involving five component skills (observing, describing, acting with awareness, nonjudging of inner experience, and nonreactivity to inner experience) is related to well-being and lessens depression, anxiety, and stress symptoms. This study investigates the relationship between mindfulness, academic performance, and psychopathological symptoms in a sample of Swiss university students during preparation for examinations. A total sample of 150 university students from the psychology department at the University of Geneva were invited to report their mindfulness skills and academic performance, as well as anxiety, depression, and stress symptoms, through self-report measures. Results indicated that the total mindfulness score and the nonreactivity facet of mindfulness were associated with depression scores. Furthermore, mindfulness skills were positively correlated with students’ academic performance. Finally, certain demographic variables, such as gender, were linked to the presence of depression, anxiety, and stress symptoms in our sample. The clinical implications of these results are discussed.

© The Author(s) 2022. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/pages/standard-publication-reuse-rights), Objectives: Previous studies have shown the importance of individual markers of cognitive reserve, such as education and occupation, for cognitive health in old age. However, there has been only little investigation so far on how this relationship varies across contexts. Methods: We analyzed data from the Survey of Health, Ageing, and Retirement in Europe, using second-order latent growth models, to assess the moderating role of welfare regimes on the relationship between education and occupation skill level in explaining overall cognitive functioning and decline in old age. Our sample includes 13 European countries using data from 5 regular waves of the survey (2004-2007 and 2011-2015) and 2 retrospective ones (2008-2009 and 2017). Cognitive functioning was modeled as a latent variable measured by immediate and delayed recall, verbal fluency, and numeracy. Results: 74,193 participants were included from the survey. Our analysis showed that the association of education with cognition was weaker overall in Scandinavian countries, but stronger in Southern European countries, relative to Bismarckian ones. However, educational differences in the decline of cognition were more pronounced only in Scandinavian compared to Bismarckian countries. Additionally, higher-skilled occupations in Scandinavian countries had better overall functioning compared to the same occupations in Bismarckian countries, but there was no difference in the decline in cognitive functioning. Discussion: Our findings indicate that the associations of cognitive functioning and its decline with individuals' cognitive reserve markers (education and occupational skill level) vary according to welfare regimes, showing the importance of contextual factors in cognitive aging processes., This article uses data from the SHARE Waves 1, 2, 3, 4, 5, 6, 7 (DOIs: 10.6103/SHARE.w1.710, 10.6103/SHARE.w2.710, 10.6103/SHARE.w3.710, 10.6103/SHARE.w4.710, 10.6103/ SHARE.w5.710, 10.6103/SHARE.w6.710, 10.6103/SHARE. w7.711). The SHARE data collection has been funded by the European Commission through FP5 (QLK6-CT-2001-00360), FP6 (SHARE-I3: RII-CT-2006-062193, COMPARE: CIT5-CT-2005-028857, SHARELIFE: CIT4-CT-2006-028812), FP7 (SHARE-PREP: GA N°211909, SHARE-LEAP: GA N°227822, SHARE M4: GA N°261982, DASISH: GA N°283646), and Horizon 2020 (SHARE-DEV3: GA N°676536, SHARE-COHESION: GA N°870628, SERISS: GA N°654221, SSHOC: GA N°823782) and by DG Employment, Social Affairs & Inclusion. Additional funding from the German Ministry of Education and Research, the Max Planck Society for the Advancement of Science, the U.S. National Institute on Aging (U01_AG09740- 13S2, P01_AG005842, P01_AG08291, P30_AG12815, R21_AG025169, Y1-AG-4553-01, IAG_BSR06-11, OGHA_04-064, HHSN271201300071C), and from various national funding sources is gratefully acknowledged (see www.share-project.org).

Contains fulltext : 292515.pdf (Publisher’s version ) (Open Access) It is well documented that some brain regions, such as association cortices, caudate, and hippocampus, are particularly prone to age-related atrophy, but it has been hypothesized that there are individual differences in atrophy profiles. Here, we document heterogeneity in regional-atrophy patterns using latent-profile analysis of 1,482 longitudinal magnetic resonance imaging observations. The results supported a 2-group solution reflecting differences in atrophy rates in cortical regions and hippocampus along with comparable caudate atrophy. The higher-atrophy group had the most marked atrophy in hippocampus and also lower episodic memory, and their normal caudate atrophy rate was accompanied by larger baseline volumes. Our findings support and refine models of heterogeneity in brain aging and suggest distinct mechanisms of atrophy in striatal versus hippocampal-cortical systems.

The question of how much sleep is best for the brain attracts scientific and public interest, and there is concern that insuficient sleep leads to poorer brain health. However, it is unknown how much sleep is sufficient and how much is too much. We analyzed 51,295 brain magnetic resonnance images from 47,039 participants, and calculated the self-reported sleep duration associated with the largest regional volumes and smallest ventricles relative to intracranial volume (ICV) and thickest cortex. 6.8 hours of sleep was associated with the most favorable brain outcome overall. Critical values, defined by 95% confidence intervals, were 5.7 and 7.9 hours. There was regional variation, with for instance the hippocampus showing largest volume at 6.3 hours. Moderately long sleep (> 8 hours) was more strongly associated with smaller relative volumes, thinner cortex and larger ventricles than even very short sleep (< 5 hours), but effect sizes were modest. People with larger ICV reported longer sleep (7.5 hours), so not correcting for ICV yielded longer durations associated with maximal volume. Controlling for socioeconomic status, body mass index and depression symptoms did not alter the associations. Genetic analyses showed that genes related to longer sleep in short sleepers were related to shorter sleep in long sleepers. This may indicate a genetically controlled homeostatic regulation of sleep duration. Mendelian randomization analyses did not suggest sleep duration to have a causal impact on brain structure in the analyzed datasets. The findings challenge the notion that habitual short sleep is negatively related to brain structure.Significance statementAccording to consensus recommendations, adults should sleep between 7 and 9 hours to optimize their health. We found that sleeping less than the recommended amount was associated with greater regional brain volumes relative to intracranial volume, and very short sleep was only weakly related to smaller volumes. Genetic analyses did not show causal effects of sleep duration on brain structure. Taken together, the results suggest that habitual short sleep is not an important contributor to lower brain volumes in adults on a group level, and that large individual dfferences in sleep need likely exist.

The linear mixed model (LMM) is a popular statistical model for the analysis of longitudinal data. However, the robust estimation of and inferential conclusions for the LMM in the presence of outliers (i.e., observations with very low probability of occurrence under Normality) is not part of mainstream longitudinal data analysis. In this work, we compared the coverage rates of confidence intervals (CIs) based on two bootstrap methods, applied to three robust estimation methods. We carried out a simulation experiment to compare CIs under three different conditions: data 1) without contamination, 2) contaminated by within-, or 3) between-participant outliers. Results showed that the semi-parametric bootstrap associated to the composite tau-estimator leads to valid inferential decisions with both uncontaminated and contaminated data. This being the most comprehensive study of CIs applied to robust estimators of the LMM, we provide fully commented R code for all methods applied to a popular example.

This study aimed to evaluate the effectiveness of a short mindfulness intervention on anxiety, stress and depression symptoms, as well as on inhibition of dominant responses and academic performance among university students. Fifty volunteers (M(age) = 23.8; SD = 5.3) with high levels of depression, anxiety or stress were randomly allocated to a mindfulness practice group or an active control group (listening to stories). Students who underwent the mindfulness practice had decreased levels of anxiety, stress and depression compared to the control group. The mindfulness program also had a beneficial impact on the students' academic performance. There was no change in the ability to inhibit dominant responses to neutral stimuli (letters); however, we observed a change in responses to neutral faces. Further research perspectives and the clinical implications of the study are discussed.

In linear mixed-effects models, several frequentist and Bayesian measures have been proposed to evaluate model adequacy or/and to perform model selection. First, a large set of these measures are selected, presented with comparable notations, discussed in their strengths, weaknesses, and applicability range, and finally commented upon regarding their limitations. Then, these measures are illustrated on the home radon levels data (Gelman & Pardoe, Technometrics, 241-251, 48, 2006). Next, an extensive simulation study is carried out, to evaluate their sensitivity in selecting the correct model from a series of simpler models containing fewer parameters. Finally, recommendations on the use of these different measures are provided. 1

Reflective functioning (RF) refers to the understanding of one's own and others' behaviors in terms of mental states, whereas empathy entails the abilities to understand (cognitive empathy) and to share (affective empathy) the emotions of others. Low RF and low empathy have been previously related to externalizing behaviors, such as aggression and rule breaking. However, few longitudinal studies have simultaneously examined the relationships between these variables during adolescence. The aim of the present study is to investigate the longitudinal effects of both RF and empathy on potential changes in externalizing behaviors over time, in a group of 103 adolescents and young adults from the general population assessed repeatedly up to four times. We conducted multilevel analysis in order to examine the effects of RF and empathy on the initial levels and the trajectories of externalizing behaviors over time, while accounting for other variables previously associated with externalizing behaviors, such as age, gender, internalizing problems, and cognitive abilities. The results suggest that the ability to reflect on behaviors in terms of mental states predicted a sharper decrease in externalizing behaviors over time. Moreover, externalizing behaviors at the first assessment were associated with RF impairments and low affective empathy. Age, gender, cognitive abilities, and cognitive empathy were not associated with externalizing behaviors. We discuss how our results, based on a typically developing population, might inform primary or indicated prevention strategies for externalizing behaviors by focusing on socio-cognitive processes such as RF and affective empathy.

First published online: January 2020 Growth models (GM) of the mixed-effects and latent curve varieties have become popular methodological tools in lifespan research. One of the major advantages of GM is their flexibility in studying individual differences in change. We scrutinized the change functions of GM used in five years of publications on cognitive aging. Of the 162 publications that we identified, 88% test linear or quadratic polynomials, and fewer than 5% apply functions that are nonlinear in their parameters, such as exponential decline. This apparent bias in favor of polynomial decomposition calls for exploring what conclusions about individual differences in change are likely to be drawn if one applies linear or quadratic GMs to data simulated under a conceptually and empirically plausible model of exponential cognitive decline from adulthood to old age. Hence, we set up a simulation that manipulated the rate of exponential decline, measurement reliability, number of occasions, interval width, and sample size. True rate of decline and interval width influenced results strongly, number of occasions and measurement reliability exerted a moderate effect, and the effects of sample size appeared relatively minor. Critically, our results show that fit statistics generally do not differentiate misspecified linear or quadratic models from the true exponential model. Moreover, power to detect variance in change for the linear and quadratic GMs is low, and estimates of individual differences in level and change can be highly biased by model misspecification. We encourage researchers to also consider plausible nonlinear change functions when studying behavioral development across the lifespan.

Objectives: With aging populations worldwide, there is growing interest in links between cognitive decline and elevated mortality risk—and, by extension, analytic approaches to further clarify these associations. Toward this end, some researchers have compared cognitive trajectories of survivors vs. decedents while others have examined longitudinal changes in cognition as predictive of mortality risk. A two-stage modeling framework is typically used in this latter approach; however, several recent studies have used joint longitudinal-survival modeling (i.e., estimating longitudinal change in cognition conditionally on mortality risk, and vice versa). Methodological differences inherent to these approaches may influence estimates of cognitive decline and cognition-mortality associations. These effects may vary across cognitive domains insofar as changes in broad fluid and crystallized abilities are differentially sensitive to aging and mortality risk. Methods: We applied each of the above analytic approaches to data from a large-sample repeated-measures study of older adults (N = 5,954, of whom 4,453 deceased; ages 50–87 years at assessment). Results: Cognitive trajectories indicated worse performance in decedents and when estimated jointly with mortality risk, but this was attenuated after adjustment for health-related covariates. Better cognitive performance predicted lower mortality risk, and, importantly, cognition-mortality associations were stronger when estimated in joint models. Associations between mortality risk and crystallized abilities only emerged under joint estimation, confirming the greater power of this statistical approach. Discussion: These results suggest that joint estimation of cognition-mortality associations may be beneficial for research in cognitive epidemiology and cognitive reserve in adult development.

Introduction University students’ psychological health is linked to their academic satisfaction. This study aimed to investigate students’ psychological health and academic satisfaction in the context of COVID-19 and academic year-end stress. Materials and methods Standardized self-filled scales for anxiety, depression, stress, psychological well-being, academic satisfaction (subjective assessment of students’ quality of life in their educational setting), and an ad-hoc scale for stress on the learning experience due to COVID-19 were used in this cross-sectional study. Participants were first- to third-year students of eight different health-related tracks in Geneva, Switzerland. Descriptive statistics and hierarchical regression analyses were applied. Results In June 2020, out of 2835 invited students, 433 (15%) completed the survey. Academic satisfaction was a stronger mental health predictor than COVID-19 stress on the learning experience, which mainly predicted stress and anxiety. Lower academic satisfaction scores were significantly associated with stress (β = −0.53, p < 0.001), depression (β = −0.26, p < 0.001), anxiety (β = −0.20, p < 0.001), while higher scores with psychological well-being (β = 0.48, p < 0.001). Identifying as female was strongly associated with anxiety and stress but not with depression or psychological well-being. Lower age was associated with stress only. The nature of the academic training had a lesser impact on mental health and the academic year had no impact. Conclusions Academic satisfaction plays a more substantial role than COVID-19 stress on the learning experience in predicting students’ overall mental health status. Training institutions should address the underlying factors that can enhance students’ academic satisfaction, especially during the COVID-19 period, in addition to ensuring that they have a continuous and adequate learning experience, as well as access to psychosocial services that help them cope with mental distress and enhance their psychological well-being.

In biostatistics and medical research, longitudinal data are often composed of repeated assessments of a variable (e.g., blood pressure or other biomarkers) and dichotomous indicators to mark an event of interest (e.g., recovery from disease, or death). Consequently, joint modeling of longitudinal and time-to-event data has generated much interest in these disciplines over the previous decade. In psychology, too, often we are interested in relating individual trajectories (e.g., cognitive performance or well-being across many years) and discrete events (e.g., death, diagnosis of dementia, or of depression). Yet, joint modeling are rarely applied in psychology and social sciences more generally. This tutorial presents an overview and general framework for joint modeling of longitudinal and time-to-event data, and fully illustrates its application in the context of a behavioral (cognitive aging) study. We discuss practical topics, such as model selection and comparison for both longitudinal and time-to-event data, choice of joint modeling parameterization, and interpretation of model parameters. To do so, we examined seven frequently used packages for joint modeling in the R language and environment. We concluded that of these, JMbayes is especially attractive due to its flexibility, its various parameterizations of the association structure, and for its powerful and fully Bayesian implementation. We make available the R syntax to apply the JMbayes package within our example.

The physiological mechanisms of age-related cognitive decline remain unclear, in no small part due to the lack of longitudinal studies. Extant longitudinal studies focused on gross neuroanatomy and diffusion properties of the brain. We present herein a longitudinal analysis of changes in arterial pulsatility – a proxy for arterial stiffness – in two major cerebral arteries, middle cerebral and vertebral. We found that pulsatility increased in some participants over a relatively short period and these increases were associated with hippocampal shrinkage. Higher baseline pulsatility was associated with lower scores on a test of fluid intelligence at follow-up. This is the first longitudinal evidence of an association between increase in cerebral arterial stiffness over time and regional shrinkage.

Background University students’ psychological health is linked to their academic satisfaction. This study aimed to investigate students’ psychological health and academic satisfaction in the context of COVID-19 and academic year-end stress. Methods Standardized self-filled scales for anxiety, depression, stress, psychological well-being, and an ad-hoc COVID-19 stress scale were used in this cross-sectional study. Participants were first- to third-year students of eight different health-related tracks in Geneva, Switzerland. Descriptive statistics and hierarchical regression analyses were applied. Results In June 2020, out of 2835 invited students, 433 (15%) completed the survey. Academic satisfaction was a stronger mental health predictor than COVID-19, which mainly predicted stress and anxiety. Lower academic satisfaction scores were significantly associated with stress (β = -.53, p < .001), depression (β = -.26, p < .001), anxiety (β = -.20, p < .001), while higher scores with psychological well-being (β = .48, p < .001). Being female was strongly associated with anxiety and stress but not with depression or psychological well-being. Lower age was associated with stress only. The nature of the academic training had a lesser impact on mental health and the academic year none. Compared to students starting the academic year, year-end students reported significantly lower academic satisfaction, higher depression, and particularly higher anxiety and stress. There was, however, no difference in psychological well-being. Conclusion Students suffer more from anxiety, stress, depression, and lower satisfaction with studies at the end of the academic year than at the beginning. Academic satisfaction plays a more substantial role than COVID-19 in predicting students’ overall mental health status. Training institutions should address the underlying factors that can enhance students’ academic satisfaction, especially during the COVID-19 period, in addition to ensuring that they have a continuous and adequate learning experience, as well as access to psychosocial services that help them cope with mental distress and enhance their psychological well-being.

Background: Research on the mental health of students in health disciplines mainly focuses on psychological distress and nursing and medical students. This study aimed to investigate the psychological well-being and distress and related factors among undergraduate students training in eight different health-related tracks in Geneva, Switzerland. Methods: This cross-sectional study used established self-filled scales for anxiety, depression, stress, psychological well-being, and study satisfaction. Descriptive statistics and hierarchical regression analyses were applied. Results: In October 2019, out of 2835 invited students, 915 (32%) completed the survey. Lower academic satisfaction scores were strongly associated with depression (β = −0.26, p &lt, 0.001), anxiety (β = −0.27, p &lt, 0.001), and stress (β = −0.70, p &lt, 0.001), while higher scores were associated with psychological well-being (β = 0.70, p &lt, 0.001). Being female was strongly associated with anxiety and stress but not with depression or psychological well-being. Increased age was associated with enhanced psychological well-being. The nature of the academic training had a lesser impact on mental health and the academic year had none. Conclusion: Academic satisfaction strongly predicts depression, anxiety, stress, and psychological well-being. Training institutions should address the underlying factors that can improve students’ satisfaction with their studies while ensuring that they have access to psychosocial services that help them cope with mental distress and enhance their psychological well-being.

Contains fulltext : 228447.pdf (Publisher’s version ) (Open Access) We examined whether sleep quality and quantity are associated with cortical and memory changes in cognitively healthy participants across the adult lifespan. Associations between self-reported sleep parameters (Pittsburgh Sleep Quality Index, PSQI) and longitudinal cortical change were tested using five samples from the Lifebrain consortium (n = 2205, 4363 MRIs, 18-92 years). In additional analyses, we tested coherence with cell-specific gene expression maps from the Allen Human Brain Atlas, and relations to changes in memory performance. "PSQI # 1 Subjective sleep quality" and "PSQI #5 Sleep disturbances" were related to thinning of the right lateral temporal cortex, with lower quality and more disturbances being associated with faster thinning. The association with "PSQI #5 Sleep disturbances" emerged after 60 years, especially in regions with high expression of genes related to oligodendrocytes and S1 pyramidal neurons. None of the sleep scales were related to a longitudinal change in episodic memory function, suggesting that sleep-related cortical changes were independent of cognitive decline. The relationship to cortical brain change suggests that self-reported sleep parameters are relevant in lifespan studies, but small effect sizes indicate that self-reported sleep is not a good biomarker of general cortical degeneration in healthy older adults. 17 p.

Contains fulltext : 235420.pdf (Publisher’s version ) (Open Access) Education has been related to various advantageous lifetime outcomes. Here, using longitudinal structural MRI data (4,422 observations), we tested the influential hypothesis that higher education translates into slower rates of brain aging. Cross-sectionally, education was modestly associated with regional cortical volume. However, despite marked mean atrophy in the cortex and hippocampus, education did not influence rates of change. The results were replicated across two independent samples. Our findings challenge the view that higher education slows brain aging.

Objectives: From a longitudinal perspective, the direction of the relationship between cognitive functioning and well-being in old age, both conceptually and empirically, is still under debate. Therefore, we aimed to disentangle the different longitudinal relationship patterns proposed and whether those differed between young-old and old-old adults. Methods: We used latent change score modeling based on longitudinal data from 1,040 older adults ( M = 74.54 years at Time 1 [T1], median = 73 years) to analyze reciprocal lead–lag relationships over 6 years in executive functioning (trail making test [TMT] completion time) and well-being (life satisfaction), taking into account chronological age, sex, education, leisure activities, and chronic diseases. Results: In young-old adults (Discussion: Lower executive functioning may predict a subsequent decline in well-being in young-old adults only. Wider implications in a context of promotion of healthy aging are discussed.

Objectives We aimed at examining between-person and within-person associations across age trajectories of perceptual speed and loneliness in old age. Method We applied multilevel models to 4 waves of data collected over 6 years from 1,491 participants of the Berlin Aging Study II (60–88 years at baseline, 50% women) to disentangle between-person and within-person associations across age trajectories of perceptual speed and both emotional and social loneliness. Sex and education were considered as relevant individual characteristics and included as covariates in the model. Results Analyses revealed that on average perceptual speed exhibited moderate within-person age-related declines, whereas facets of loneliness were rather stable. Perceptual speed did not predict age trajectories of emotional or social loneliness, at either the between- or within-person level. In contrast, loneliness discriminated individuals at the between-person level, such that those feeling emotionally or socially more lonely showed lower cognitive performance than those feeling emotionally or socially less lonely. Predictive effects of social loneliness were stronger for relatively young people (i.e., in their mid to late 60s) than for relatively older participants (i.e., in their 80s). In addition, predictive effects of social loneliness for perceptual speed at the within-person level were modest and deviated in direction and size from between-person social loneliness effects among those in their mid- to late 60s, whereas they did not among those in their 80s. Discussion We conclude that loneliness may serve as a precursor for basic cognitive functioning in old age and suggest routes for further inquiry.

BackgroundOlder persons with poor sleep are more likely to develop neurodegenerative disease, but the causality underlying this association is unclear. To move towards explanation, we examine whether sleep quality and quantity are similarly associated with brain changes across the adult lifespan.MethodsAssociations between self-reported sleep parameters (Pittsburgh Sleep Quality Index;PSQI) and longitudinal cortical change were tested using five samples from theLifebrainconsortium (n=2205, 4363 MRIs, 18-92 years). Analyses were augmented by considering episodic memory change, gene expression from the Allen Human Brain Atlas, and amyloid-beta (Aβ) accumulation (n=1980).ResultsPSQI components sleep problems and low sleep quality were related to thinning of the right lateral temporal cortex. The association with sleep problems emerged after 60 years, especially in regions with high expression of genes related to oligodendrocytes and S1 pyramidal neurons. BMI and symptoms of depression had negligible effects. Sleep problems were neither related to longitudinal change in episodic memory function nor to Aβ accumulation, suggesting that sleep-related cortical changes were independent of AD neuropathology and cognitive decline.ConclusionWorse self-reported sleep in later adulthood was associated with more cortical thinning in regions of high expression of genes related to oligodendrocytes and S1 pyramidal neurons, but not to Aβ accumulation or memory decline. The relationship to cortical brain change suggests that self-reported sleep parameters are relevant in lifespan studies, but small effect sizes, except for a few restricted regions, indicate that self-reported sleep is not a good biomarker of general cortical degeneration in healthy older adults.

BACKGROUND: Efforts to identify important risk factors for cognitive impairment and dementia have to date mostly relied on meta-analytic strategies. A comprehensive empirical evaluation of these risk factors within a single study is currently lacking. OBJECTIVE: We used a combined methodology of machine learning and semi-parametric survival analysis to estimate the relative importance of 52 predictors in forecasting cognitive impairment and dementia in a large, population-representative sample of older adults. METHODS: Participants from the Health and Retirement Study (N = 9,979; aged 50-98 years) were followed for up to 10 years (M = 6.85 for cognitive impairment; M = 7.67 for dementia). Using a split-sample methodology, we first estimated the relative importance of predictors using machine learning (random forest survival analysis), and we then used semi-parametric survival analysis (Cox proportional hazards) to estimate effect sizes for the most important variables. RESULTS: African Americans and individuals who scored high on emotional distress were at relatively highest risk for developing cognitive impairment and dementia. Sociodemographic (lower education, Hispanic ethnicity) and health variables (worse subjective health, increasing BMI) were comparatively strong predictors for cognitive impairment. Cardiovascular factors (e.g., smoking, physical inactivity) and polygenic scores (with and without APOEɛ4) appeared less important than expected. Post-hoc sensitivity analyses underscored the robustness of these results. CONCLUSIONS: Higher-order factors (e.g., emotional distress, subjective health), which reflect complex interactions between various aspects of an individual, were more important than narrowly defined factors (e.g., clinical and behavioral indicators) when evaluated concurrently to predict cognitive impairment and dementia.

There is a debate on possible alterations of self-identity following deep brain stimulation for neurological disorders including Parkinson&rsquo, s disease. Among the psychological variables likely to undergo changes throughout such a medical procedure, illness representations and coping strategies have not been the target of much research to this day. In order to remedy this, we investigated the dynamics of illness representations and coping strategies in an 18-month longitudinal study involving 45 patients undergoing deep brain stimulation for idiopathic Parkinson&rsquo, s disease. Two research hypotheses were formulated and investigated through repeated measures of ANOVAs and structural equation modelling with full information maximum likelihood and Bayesian estimations. Representations of Parkinson&rsquo, s disease as a cyclical condition and perception of control over the disease diminished after surgery. Use of instrumental coping strategies was not modified after deep brain stimulation. These changes were identified by SEM but not ANOVAs, their magnitude was nevertheless relatively small, implying general stability in representations. These findings suggest that psychological variables do not undergo major changes after deep brain stimulation for Parkinson&rsquo, s disease.

Longitudinal data collection is a time-consuming and cost-intensive part of developmental research. Wu et al. (2016) discussed planned missing (PM) designs that are similar in efficiency to complete designs but require fewer observations per person. The authors reported optimal PM designs for linear latent growth curve models based on extensive Monte Carlo simulations. They called for further formal investigation of the question as to how much the proposed PM mechanisms influence study design efficiency to arrive at a better understanding of PM designs. Here, we propose an approximate solution to the design problem by comparing the asymptotic effective errors of PM designs. Effective error was previously used to find optimal longitudinal study designs for complete data designs; here, we extend the approach to planned missing designs. We show how effective error is a metric for comparing the efficiency of study designs with both planned and unplanned missing data, and how earlier simulation-based results for PM designs can be explained by an asymptotic solution. Our approach is computationally more efficient than Wu et al.’s approach and leads to a better understanding of how various design factors, such as the number of measurement occasions, their temporal arrangement, attrition rates, and PM design patterns interact and how they conjointly determine design efficiency. We provide R scripts to calculate effective errors in various scenarios of PM designs.

ObjectivesWe examined bidirectional, time-ordered associations between age-related changes in depressive symptoms and memory.MethodData came from 107,599 community-dwelling adults, aged 49–90 years, who participated in the Survey of Health, Ageing, and Retirement in Europe (SHARE). Depressive symptoms were measured with the EURO-D inventory, and memory was evaluated as delayed recall of a 10-word list. Participants were assessed up to five times at 2-year intervals. Dynamic structural equation models were used to estimate longitudinal and time-ordered (lead-lag) relations between depressive symptoms and memory performance.ResultsDepressive symptoms increased and memory scores decreased across the observed age range, with worsening mostly evident after age 62 years. These long-term changes were moderately negatively correlated (r = −.53, p < .001). A time-ordered effect emerged such that age-specific memory deficits preceded shorter-term increases in depression symptoms. This effect can be translated such that each 1-point decrement on a 10-point memory scale at a given age predicted a 14.5% increased risk for depression two years later. Statistical adjustment for covariates (sex, education, re-test, smoking, and body mass index) had little influence on these associations.ConclusionIn later adulthood, lower memory performance at a given age predicts subsequent 2-year increases in depressive symptoms.