Interpreting Change in Disorders of Consciousness Using the Coma Recovery Scale-Revised.

The purpose of this study was to differentiate clinically meaningful improvement or deterioration from normal fluctuations in patients with disorders of consciousness (DoC) following severe brain injury. We computed indices of responsiveness for the Coma Recovery Scale-Revised (CRS-R) using data from a clinical trial of 180 participants with DoC. We used CRS-R scores from baseline (enrollment in a clinical trial) and a 4-week follow-up assessment period for these calculations. To improve precision, we transformed ordinal CRS-R total scores (0-23 points) to equal-interval measures on a 0-100 unit scale using Rasch Measurement theory. Using the 0-100 unit total Rasch measures, we calculated distribution-based 0.5 standard deviation (SD) minimal clinically important difference, minimal detectable change using 95% confidence intervals, and conditional minimal detectable change using 95% confidence intervals. The distribution-based minimal clinically important difference evaluates group-level changes, whereas the minimal detectable change values evaluate individual-level changes. The minimal clinically important difference and minimal detectable change are derived using the overall variability across total measures at baseline and 4 weeks. The conditional minimal detectable change is generated for each possible pair of CRS-R Rasch person measures and accounts for variation in standard error across the scale. We applied these indices to determine the proportions of participants who made a change beyond measurement error within each of the two subgroups, based on treatment arm (amantadine hydrochloride or placebo) or categorization of baseline Rasch person measure to states of consciousness (i.e., unresponsive wakefulness syndrome and minimally conscious state). We compared the proportion of participants in each treatment arm who made a change according to the minimal detectable change and determined whether they also changed to another state of consciousness. CRS-R indices of responsiveness (using the 0-100 transformed scale) were as follows: 0.5SD minimal clinically important difference = 9 units, minimal detectable change = 11 units, and the conditional minimal detectable change ranged from 11 to 42 units. For the amantadine and placebo groups, 70% and 58% of participants showed change beyond measurement error using the minimal detectable change, respectively. For the unresponsive wakefulness syndrome and minimally conscious state groups, 54% and 69% of participants changed beyond measurement error using the minimal detectable change, respectively. Among 115 participants (64% of the total sample) who made a change beyond measurement error, 29 participants (25%) did not change state of consciousness. CRS-R indices of responsiveness can support clinicians and researchers in discerning when behavioral changes in patients with DoC exceed measurement error. Notably, the minimal detectable change can support the detection of patients who make a "true" change within or across states of consciousness. Our findings highlight that the continued use of ordinal scores may result in incorrect inferences about the degree and relevance of a change score.

Associations of social and cognitive-behavioral variables with disinhibited eating and anxiety: An ecological momentary assessment study.

OBJECTIVE: Among adolescents, disinhibited eating and anxiety commonly co-occur. Precision intervention approaches targeting unique mechanistic vulnerabilities that contribute to disinhibited eating and anxiety may therefore be helpful. However, the effectiveness of such interventions hinges on knowledge of between- and within-person associations related to disinhibited eating, anxiety, and related processes. METHOD: A sample of 39 adolescent females (12-17 years) with elevated anxiety and above-average weight (BMI %ile ≥ 75th) completed measures of theoretically driven social and cognitive-behavioral variables, disinhibited eating, and anxiety via ecological momentary assessment over 7 days. Data were analyzed using mixed-effects models. RESULTS: Between-person differences in social stressors were linked to emotional eating, eating in the absence of hunger, and anxiety, whereas between-person differences in negative thoughts were associated with all disinhibited eating variables and anxiety. Between-person differences in avoidance were not related to any outcome. Additionally, between-person differences in social stressors and negative thoughts-as well as within-person deviations (from person-average levels) of social stressors, negative thoughts, and avoidance-were associated with anxiety. In turn, between-person differences in anxiety predicted eating in the absence of hunger and emotional eating, and within-person deviations in anxiety were associated with emotional eating at any given time point. DISCUSSION: Findings support elements of both the interpersonal and cognitive-behavioral models of disinhibited eating. Differential trigger effects on anxiety, both at the between- and within-person levels, and significant associations between anxiety and all eating-related outcomes, highlight the potential utility of interventions targeting individual differences in sensitivity to anxiety triggers. PUBLIC SIGNIFICANCE: Findings provide support for the interpersonal and cognitive-behavioral models of disinhibited eating, highlighting anxiety as a salient vulnerability and potential mechanistic factor underlying disinhibited eating. Social, cognitive, and behavioral variables were differentially related to anxiety across participants, suggesting potential for future intervention tailoring and intervention selection based on adolescents' sensitivity to anxiety as a trigger for disinhibited eating behavior.

Movement through motherhood: Exploring mood, wellbeing, and prenatal emotional availability (EA) through EA-based dance intervention.

Emotional availability (EA) is a construct that describes the observed emotional connection in parent-child relationships. During pregnancy, EA is assessed only using caregiver sensitivity and nonhostility. We used the nonverbal aspects of these qualities to create a new dance/movement intervention ("EA-Based Dance Intervention"). Given the scarcity of pregnancy interventions, we provided training to participants on how to be emotionally engaged with their unborn babies through dance/movement. The EA-Based Dance Intervention alone comprised the first intervention arm (n = 12). A second intervention arm involved the combination of EA-Based Dance Intervention with brief psychoeducation (n = 10). The third arm was a control group, which received only the assessments (n = 7). Measures of self-reported symptoms of depression and anxiety, emotional expressivity, flourishing, and the (newly developed) self-reported prenatal EA were used at pre- and posttest. The measure of observed prenatal EA was used to compare intervention versus control at posttest only. In this pilot study, we found that participants receiving the EA-Based Dance Intervention alone or combined with psychoeducation, self-reported improved anxiety symptoms and self-reported higher prenatal EA. When compared with the control group, those experiencing EA-Based Dance Intervention reported fewer depressive symptoms from pre- to posttest.

La disponibilidad emocional (EA) es una construcción que describe la observada conexión emocional en las relaciones entre progenitor y niño. Durante el embarazo, EA se evalúa solamente usando la sensibilidad y el nivel de no hostilidad de quien presta el cuidado. Usamos los aspectos no verbales de estas cualidades para crear una nueva intervención de baile/movimiento ("Intervención de Baile con Base en la Disponibilidad Emocional"). Dada la escasez de intervenciones de embarazo, les ofrecimos entrenamiento a las participantes en cuanto a cómo interactuar emocionalmente con sus bebés no nacidos por medio del baile/movimiento. La Intervención de Baile con Base en la Disponibilidad Emocional abarca por sí sola el primer grupo o brazo de la intervención (n = 12). Un segundo grupo o brazo de intervención incluyó la combinación de la Intervención de Baile con Base en la Disponibilidad Emocional con psicoeducación breve (n = 10). El tercer grupo o brazo de intervención fue un grupo de control, el cual sólo recibió las evaluaciones (n = 7). Anterior y posteriormente a la prueba, se usaron medidas de auto reportados síntomas de depresión y ansiedad, de expresividad emocional, de mejorar y salir adelante, y la (recién desarrollada) EA prenatal auto reportada. La medida de EA prenatal observada se usó para comparar los grupos de intervención vs. de control sólo con posterioridad a la prueba. En este estudio piloto, encontramos que las participantes que recibían la Intervención de Baile con Base en la Disponibilidad Emocional solamente o combinada con psicoeducación, auto reportaron mejoras en los síntomas de ansiedad y auto reportaron una EA prenatal más alta. Cuando se les comparó con el grupo de control, quienes experimentaban la Intervención de Baile con Base en la Disponibilidad Emocional reportaron menos síntomas depresivos desde antes hasta después de la prueba.

The Current and Retrospective Cognitive Reserve (2CR) survey and its relationship with cognitive and mood measures.

Cognitive Reserve (CR) is often assessed with surveys spanning demographic, lifestyle, and socio-behavioral variables. The role of both past and current life experiences on CR has, however, rarely been examined. We developed the Current and Retrospective Cognitive Reserve (2CR) survey to assess classical CR proxies (socio-economic status, engagement in leisure and social activities) and other dimensions of potential importance (family engagement, religious/spiritual activity) both currently (CRc; in later adulthood) and retrospectively (CRr; as recalled from younger adulthood). We administered the 2CR, measures of general cognitive functioning, working memory (WM), crystallized-vocabulary- and fluid-reasoning-intelligence, and depressive symptoms (DS) to 235 community-dwelling Italian adults (ages 55-90 years). We used exploratory and confirmatory factor analyses to examine the 2CR latent structure, and we estimated correlations of its dimensions with cognitive abilities and DS. Analyses confirmed a three-level factor structure with two global CR factors (CRc and CRr) at the top level, dimensional CR factors (socio-economic status, family engagement, leisure activity, social engagement, and religious/spiritual activity) at mid-level and observed items at the lowest level. Item-factor representations partially differed across CRc and CRr. Both CRc and CRr were positively correlated with measures of intelligence, WM and DS, but associations of measures of intelligence were stronger for CRr, whereas associations of WM and DS were slightly stronger for CRc. The 2CR can be considered a reliable survey for assessing CR proxies within a multidimensional, "life stage-dependent" framework insofar as CRc are CRr closely related but also differently associated with intelligence, WM, and DS.

Mother-Child and Father-Child Emotional Availability during the COVID-19 Pandemic.

While the body of literature on COVID-19's impacts on family life is rapidly expanding, most studies are based entirely on self-report data, leaving a critical gap in observational studies of parent-child interactions. The goal of this study was to evaluate parent-child relationships during the COVID-19 pandemic using the observational emotional availability (EA) construct. Parents (n = 43) were assessed using the Epidemic-Pandemic Impacts Inventory (EPII), the Flourishing Scale (FLS), and the adverse childhood experiences (ACEs) questionnaires. The subcategories of the EPII were used to develop an EPII negative and an EPII positive for each parent. EA (sensitivity, structuring, nonhostility, nonintrusiveness, child responsiveness, and child involvement) was coded from filmed parent-child interactions. Separate hierarchical multiple regressions (HMRs) were run to evaluate each of the variables of interest (EPII and FLS) as predictive of EA. Child age (M = 6, SD = 4.68) and ACEs were added in subsequent steps for EPII negative and positive if the initial step was significant. For mothers (n = 25), results demonstrated EPII negative as a significant predictor of EA with child age and ACEs adding only small amount of variance to the prediction. The same HMR process was repeated for flourishing, with the covariate child age alone. For fathers (n = 18), flourishing was a significant predictor of EA and child age added only a small amount of variance to the prediction. Results indicate that experiencing high COVID-19-related stressors is associated with lower EA for mothers, but not fathers. Having high levels of flourishing during the pandemic was predictive of higher EA for fathers, but not mothers.

Age-Related Trajectories of General Fluid Cognition and Functional Decline in the Health and Retirement Study: A Bivariate Latent Growth Analysis.

There have been few studies on associations between age-related declines in fluid cognition and functional ability in population-representative samples of middle-aged and older adults. We used a two-stage process (longitudinal factor analysis followed by structural growth modeling) to estimate bivariate trajectories of age-related changes in general fluid cognition (numeracy, category fluency, executive functioning, and recall memory) and functional limitation (difficulties in daily activities, instrumental activities, and mobility). Data came from the Health and Retirement Study (Waves 2010-2016; N = 14,489; ages 50-85 years). Cognitive ability declined on average by -0.05 SD between ages 50-70 years, then -0.28 SD from 70-85 years. Functional limitation increased on average by +0.22 SD between ages 50-70 years, then +0.68 SD from 70-85 years. Significant individual variation in cognitive and functional changes was observed across age windows. Importantly, cognitive decline in middle age (pre-age 70 years) was strongly correlated with increasing functional limitation (r = -.49, p < .001). After middle age, cognition declined independently of change in functional limitation. To our knowledge, this is the first study to estimate age-related changes in fluid cognitive measures introduced in the HRS between 2010-2016.

Cognitive-behavioral therapy and exercise training in adolescent females with elevated depression symptoms and at-risk for type 2 diabetes: Protocol for a randomized controlled trial.

BACKGROUND: Adolescent-onset type 2 diabetes (T2D) is a major public health concern of growing proportions. Prevention, therefore, is critical. Unfortunately, standard-of-care treatment for T2D prevention (e.g., exercise training) show insufficient effectiveness and do not address key modifiable barriers (e.g., depression symptoms) to exercise engagement. Depression symptoms are associated with both poorer physical fitness and greater insulin resistance, the key risk factor in adolescent-onset T2D. Thus, a targeted prevention approach that addresses depression symptoms in combination with exercise training may offer a novel approach to mitigating T2D risk. METHODS: This manuscript describes the design and study protocol for a multi-site, four-arm randomized controlled trial comparing the efficacy of group cognitive-behavioral therapy, group exercise training, and their combinations for the targeted prevention of worsening insulin resistance in N = 300 adolescent females at-risk for T2D with BMI ≥85th percentile and elevated depression symptoms. All four intervention arms will run in parallel and meet weekly for 1 h per week for 6-week to 6-week segments (12 weeks total). Outcomes are assessed at baseline, 6-week mid-treatment, 12-week follow-up, and 1-year follow-up. RESULTS: The primary outcome is insulin resistance. Key secondary outcomes include insulin sensitivity, cardiorespiratory fitness, physical activity, depression symptoms, and body measurements. CONCLUSION: Study findings will guide the ideal sequencing of two brief T2D prevention interventions for ameliorating the course of insulin resistance and lessening T2D risk in vulnerable adolescents. These interventions will likely be cost-effective and scalable for dissemination, having the potential for significant public health impact on communities at risk for T2D.

Predictors of depression among middle-aged and older men and women in Europe: A machine learning approach.

Background: The high prevalence of depression in a growing aging population represents a critical public health issue. It is unclear how social, health, cognitive, and functional variables rank as risk/protective factors for depression among older adults and whether there are conspicuous differences among men and women. Methods: We used random forest analysis (RFA), a machine learning method, to compare 56 risk/protective factors for depression in a large representative sample of European older adults (N = 67,603; ages 45-105y; 56.1% women; 18 countries) from the Survey of Health, Ageing and Retirement in Europe (SHARE Wave 6). Depressive symptoms were assessed using the EURO-D questionnaire: Scores ≥ 4 indicated depression. Predictors included a broad array of sociodemographic, relational, health, lifestyle, and cognitive variables. Findings: Self-rated social isolation and self-rated poor health were the strongest risk factors, accounting for 22.0% (in men) and 22.3% (in women) of variability in depression. Odds ratios (OR) per +1SD in social isolation were 1.99x, 95% CI [1.90,2.08] in men; 1.93x, 95% CI [1.85,2.02] in women. OR for self-rated poor health were 1.93x, 95% CI [1.81,2.05] in men; 1.98x, 95% CI [1.87,2.10] in women. Difficulties in mobility (in both sexes), difficulties in instrumental activities of daily living (in men), and higher self-rated family burden (in women) accounted for an additional but small percentage of variance in depression risk (2.2% in men, 1.5% in women). Interpretation: Among 56 predictors, self-perceived social isolation and self-rated poor health were the most salient risk factors for depression in middle-aged and older men and women. Difficulties in instrumental activities of daily living (in men) and increased family burden (in women) appear to differentially influence depression risk across sexes. Funding: This study was internally funded by Colorado State University through research start-up monies provided to Stephen Aichele, Ph.D.

Cognition-Mortality Associations Are More Pronounced When Estimated Jointly in Longitudinal and Time-to-Event Models.

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. We compared these analytic approaches as applied to data from a large-sample, repeated-measures study of older adults (N = 5,954; ages 50-87 years at assessment; 4,453 deceased at last census). 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 more pronounced when estimated in joint models. Associations between mortality risk and crystallized abilities only emerged under joint estimation. This may have important implications for cognitive reserve, which posits that knowledge and skills considered well-preserved in later life (i.e., crystallized abilities) may compensate for declines in abilities more prone to neurodegeneration, such as recall memory and problem solving. Joint longitudinal-survival models thus appear to be important (and currently underutilized) for research in cognitive epidemiology.

Dementia Incidence, Burden and Cost of Care: A Filipino Community-Based Study.

Background: In the midst of competing priorities and limited resources in low-middle-income countries (LMIC), convincing epidemiological evidence is critical for urging governments to develop national dementia plans. The majority of primary epidemiological studies on dementia are from high income countries (HIC). Implications for developing countries are typically extrapolated from these outcomes through modeling, meta-analyses, and systematic reviews. In this study, we directly assessed the incidence of dementia, disability adjusted life years (DALYs), and cost of care among community-dwelling Filipino elderly. Methods: This was a follow-up study of the prospective cohort Marikina Memory Ageing Project (MMAP). Baseline assessment was performed in 2011-2012, and follow-up was done in 2015-2016 (N = 748 at follow-up). Incident dementia was determined. Disease burden was computed using the incidence rates and DALYs. Both indirect and direct (medical and non-medical) costs of dementia care were computed. Results: The crude incidence rate was 16 (CI: 13-20) cases per 1,000 person-years (pyr) with 17 (CI: 12-21) per 1,000 pyr for females and 14 (CI: 9-21) per 1,000 pyr for males. Based on this incidence, we project an estimation of 220,632 new cases in 2030, 295,066 in 2040, and 378,461 in 2050. Disease burden was at 2,876 DALYsper 100,000 persons. The economic burden per patient was around Php 196,000 annually (i.e., ~4,070 USD, or 36.7% of average family annual income in the Philippines). The majority (86.29%) of this care expense was indirect cost attributed to estimated lost potential earning of unpaid family caregivers whereas direct medical cost accounted for only 13.48%. Conclusions: We provide the first Filipino community-based data on the incidence of dementia, DALYs, and cost of care to reflect the epidemiologic and economic impact of disease. The findings of this study serve to guide the development of a national dementia plan.

Predicting Cognitive Impairment and Dementia: A Machine Learning Approach.

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.

Illness and intelligence are comparatively strong predictors of individual differences in depressive symptoms following middle age.

OBJECTIVE: We compared the importance of socio-demographic, lifestyle, health, and multiple cognitive measures for predicting individual differences in depressive symptoms in later adulthood. METHOD: Data came from 6203 community-dwelling older adults (age 41-93 years at study entry) from the United Kingdom. Predictors (36 in total) were assessed up to four times across a period of approximately 12 years. Depressive symptoms were measured with the Geriatric Depression Scale. Statistical methods included multiple imputation (for missing data), random forest analysis (a machine learning approach), and multivariate regression. RESULTS: On average, depressive symptoms increased gradually following middle age and appeared to accelerate in later life. Individual differences in depressive symptoms were most strongly associated with differences in combined symptoms of physical illness (positive relation) and fluid intelligence (negative relation). The strength of association between depressive symptoms and fluid intelligence was unaffected by differences in health status within a subsample of chronically depressed individuals. CONCLUSION: Joint consideration of general health status and fluid intelligence may facilitate prediction of depressive symptoms severity during later life and may also serve to identify sub-populations of community-dwelling elders at risk for chronic depression.

Memory Deficits Precede Increases in Depressive Symptoms in Later Adulthood.

OBJECTIVES: We examined bidirectional, time-ordered associations between age-related changes in depressive symptoms and memory. METHOD: Data 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. RESULTS: Depressive 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. CONCLUSION: In later adulthood, lower memory performance at a given age predicts subsequent 2-year increases in depressive symptoms.

Fluid Intelligence Predicts Change in Depressive Symptoms in Later Life: The Lothian Birth Cohort 1936.

We examined reciprocal, time-ordered associations between age-related changes in fluid intelligence and depressive symptoms. Participants were 1,091 community-dwelling older adults from the Lothian Birth Cohort 1936 study who were assessed repeatedly at 3-year intervals between the ages of 70 and 79 years. On average, fluid intelligence and depressive symptoms worsened with age. There was also a dynamic-coupling effect, in which low fluid intelligence at a given age predicted increasing depressive symptoms across the following 3-year interval, whereas the converse did not hold. Model comparisons showed that this coupling parameter significantly improved overall fit and had a correspondingly moderately strong effect size, accounting on average for an accumulated 0.9 standard-deviation increase in depressive symptoms, following lower cognitive performance, across the observed age range. Adjustment for sociodemographic and health-related covariates did not significantly attenuate this association. This implies that monitoring for cognitive decrements in later life may expedite interventions to reduce related increases in depression risk.

Cardiovascular symptoms and longitudinal declines in processing speed differentially predict cerebral white matter lesions in older adults.

It is well established that cerebral white matter lesions (WML), present in the majority of older adults, are associated with cardiovascular and cerebrovascular diseases and also with cognitive decline. However, much less is known about how WML are related to other important individual characteristics and about the generality vs. brain region-specificity of WML. In a longitudinal study of 112 community-dwelling adults (age 50-71 years at study entry), we used a machine learning approach to evaluate the relative strength of 52 variables in association with WML burden. Variables included socio-demographic, lifestyle, and health indices-as well as multiple cognitive abilities (modeled as latent constructs using factor analysis)-repeatedly measured at three- to six-year intervals. Greater chronological age, symptoms of cardiovascular disease, and processing speed declines were most strongly linked to elevated WML burden (accounting for ∼49% of variability in WML). Whereas frontal lobe WML burden was associated both with elevated cardiovascular symptoms and declines in processing speed, temporal lobe WML burden was only significantly associated with declines in processing speed. These latter outcomes suggest that age-related WML-cognition associations may be etiologically heterogeneous across fronto-temporal cerebral regions.

Age Differences in Day-To-Day Speed-Accuracy Tradeoffs: Results from the COGITO Study.

We examined adult age differences in day-to-day adjustments in speed-accuracy tradeoffs (SAT) on a figural comparison task. Data came from the COGITO study, with over 100 younger and 100 older adults, assessed for over 100 days. Participants were given explicit feedback about their completion time and accuracy each day after task completion. We applied a multivariate vector auto-regressive model of order 1 to the daily mean reaction time (RT) and daily accuracy scores together, within each age group. We expected that participants adjusted their SAT if the two cross-regressive parameters from RT (or accuracy) on day t-1 of accuracy (or RT) on day t were sizable and negative. We found that: (a) the temporal dependencies of both accuracy and RT were quite strong in both age groups; (b) younger adults showed an effect of their accuracy on day t-1 on their RT on day t, a pattern that was in accordance with adjustments of their SAT; (c) older adults did not appear to adjust their SAT; (d) these effects were partly associated with reliable individual differences within each age group. We discuss possible explanations for older adults' reluctance to recalibrate speed and accuracy on a day-to-day basis.

Quantitative Methods in Psychological Aging Research: A Mini-Review.

As research on psychological aging moves forward, it is increasingly important to accurately assess longitudinal changes in psychological processes and to account for their (often complex) associations with sociodemographic, lifestyle, and health-related variables. Traditional statistical methods, though time tested and well documented, are not always satisfactory for meeting these aims. In this mini-review, we therefore focus the discussion on recent statistical advances that may be of benefit to researchers in psychological aging but that remain novel in our area of study. We first compare two methods for the treatment of incomplete data, a common problem in longitudinal research. We then discuss robust statistics, which address the question of what to do when critical assumptions of a standard statistical test are not met. Next, we discuss two approaches that are promising for accurately describing phenomena that do not unfold linearly over time: nonlinear mixed-effects models and (generalized) additive models. We conclude by discussing recursive partitioning methods, as these are particularly well suited for exploring complex relations among large sets of variables.

Think Fast, Feel Fine, Live Long: A 29-Year Study of Cognition, Health, and Survival in Middle-Aged and Older Adults.

In a 29-year study of 6,203 individuals ranging in age from 41 to 96 years at initial assessment, we evaluated the relative and combined influence of 65 mortality risk factors, which included sociodemographic variables, lifestyle attributes, medical indices, and multiple cognitive abilities. Reductions in mortality risk were most associated with higher self-rated health, female gender, fewer years as a smoker, and smaller decrements in processing speed with age. Thus, two psychological variables-subjective health status and processing speed-were among the top predictors of survival. We suggest that these psychological attributes, unlike risk factors that are more narrowly defined, reflect (and are influenced by) a broad range of health-related behaviors and characteristics. Information about these attributes can be obtained with relatively little effort or cost and-given the tractability of these measures in different cultural contexts-may prove expedient for prevention, diagnosis, and treatment of conditions related to increased mortality risk in diverse human populations.

Life span decrements in fluid intelligence and processing speed predict mortality risk.

We examined life span changes in 5 domains of cognitive performance as predictive of mortality risk. Data came from the Manchester Longitudinal Study of Cognition, a 20-plus-year investigation of 6,203 individuals ages 42-97 years. Cognitive domains were general crystallized intelligence, general fluid intelligence, verbal memory, visuospatial memory, and processing speed. Life span decrements were evident across these domains, controlling for baseline performance at age 70 and adjusting for retest effects. Survival analyses stratified by sex and conducted independently by cognitive domain showed that lower baseline performance levels in all domains-and larger life span decrements in general fluid intelligence and processing speed-were predictive of increased mortality risk for both women and men. Critically, analyses of the combined predictive power of cognitive performance variables showed that baseline levels of processing speed (in women) and general fluid intelligence (in men), and decrements in processing speed (in women and in men) and general fluid intelligence (in women), accounted for most of the explained variation in mortality risk. In light of recent evidence from brain-imaging studies, we speculate that cognitive abilities closely linked to cerebral white matter integrity (such as processing speed and general fluid intelligence) may represent particularly sensitive markers of mortality risk. In addition, we presume that greater complexity in cognition-survival associations observed in women (in analyses incorporating all cognitive predictors) may be a consequence of longer and more variable cognitive declines in women relative to men.

Intensive meditation training influences emotional responses to suffering.

Meditation practices purportedly help people develop focused and sustained attention, cultivate feelings of compassionate concern for self and others, and strengthen motivation to help others who are in need. We examined the impact of 3 months of intensive meditative training on emotional responses to scenes of human suffering. Sixty participants were assigned randomly to either a 3-month intensive meditation retreat or a wait-list control group. Training consisted of daily practice in techniques designed to improve attention and enhance compassionate regard for others. Participants viewed film scenes depicting human suffering at pre- and posttraining laboratory assessments, during which both facial and subjective measures of emotion were collected. At post-assessment, training group participants were more likely than controls to show facial displays of sadness. Trainees also showed fewer facial displays of rejection emotions (anger, contempt, disgust). The groups did not differ on the likelihood or frequency of showing these emotions prior to training. Self-reported sympathy--but not sadness or distress--predicted sad behavior and inversely predicted displays of rejection emotions in trainees only. These results suggest that intensive meditation training encourages emotional responses to suffering characterized by enhanced sympathetic concern for, and reduced aversion to, the suffering of others.