Utility Scores for Risk-Reducing Mastectomy and Risk-Reducing Salpingo-Oophorectomy: Mapping to EQ-5D.

BACKGROUND: Risk-reducing mastectomy (RRM) and risk-reducing salpingo-oophorectomy (RRSO) are the most effective breast and ovarian cancer preventive interventions. EQ-5D is the recommended tool to assess the quality of life and determine health-related utility scores (HRUSs), yet there are no published EQ-5D HRUSs after these procedures. These are essential for clinicians counselling patients and for health-economic evaluations. METHODS: We used aggregate data from our published systematic review and converted SF-36/SF-12 summary scores to EQ-5D HRUSs using a published mapping algorithm. Study control arm or age-matched country-specific reference values provided comparison. Random-effects meta-analysis provided adjusted disutilities and utility scores. Subgroup analyses included long-term vs. short-term follow-up. RESULTS: Four studies (209 patients) reported RRM outcomes using SF-36, and five studies (742 patients) reported RRSO outcomes using SF-12/SF-36. RRM is associated with a long-term (>2 years) disutility of -0.08 (95% CI -0.11, -0.04) (I2 31.4%) and a utility of 0.92 (95% CI 0.88, 0.95) (I2 31.4%). RRSO is associated with a long-term (>1 year) disutility of -0.03 (95% CI -0.05, 0.00) (I2 17.2%) and a utility of 0.97 (95% CI 0.94, 0.99) (I2 34.0%). CONCLUSIONS: We present the first HRUSs sourced from patients following RRM and RRSO. There is a need for high-quality prospective studies to characterise quality of life at different timepoints.

Can you tell people's cognitive ability level from their response patterns in questionnaires?

Questionnaires are ever present in survey research. In this study, we examined whether an indirect indicator of general cognitive ability could be developed based on response patterns in questionnaires. We drew on two established phenomena characterizing connections between cognitive ability and people's performance on basic cognitive tasks, and examined whether they apply to questionnaires responses. (1) The worst performance rule (WPR) states that people's worst performance on multiple sequential tasks is more indicative of their cognitive ability than their average or best performance. (2) The task complexity hypothesis (TCH) suggests that relationships between cognitive ability and performance increase with task complexity. We conceptualized items of a questionnaire as a series of cognitively demanding tasks. A graded response model was used to estimate respondents' performance for each item based on the difference between the observed and model-predicted response ("response error" scores). Analyzing data from 102 items (21 questionnaires) collected from a large-scale nationally representative sample of people aged 50+ years, we found robust associations of cognitive ability with a person's largest but not with their smallest response error scores (supporting the WPR), and stronger associations of cognitive ability with response errors for more complex than for less complex questions (supporting the TCH). Results replicated across two independent samples and six assessment waves. A latent variable of response errors estimated for the most complex items correlated .50 with a latent cognitive ability factor, suggesting that response patterns can be utilized to extract a rough indicator of general cognitive ability in survey research.

Cognitive Functioning and the Quality of Survey Responses: An Individual Participant Data Meta-Analysis of 10 Epidemiological Studies of Aging.

OBJECTIVES: Self-reported survey data are essential for monitoring the health and well-being of the population as it ages. For studies of aging to provide precise and unbiased results, it is necessary that the self-reported information meets high psychometric standards. In this study, we examined whether the quality of survey responses in panel studies of aging depends on respondents' cognitive abilities. METHODS: Over 17 million survey responses from 157,844 participants aged 50 years and older in 10 epidemiological studies of aging were analyzed. We derived 6 common statistical indicators of response quality from each participant's data and estimated the correlations with participants' cognitive test scores at each study wave. Effect sizes (correlations) were synthesized across studies, cognitive tests, and waves using individual participant data meta-analysis methods. RESULTS: Respondents with lower cognitive scores showed significantly more missing item responses (overall effect size ρ^ = -0.144), random measurement error (ρ^ = -0.192), Guttman errors (ρ^ = -0.233), multivariate outliers (ρ^ = -0.254), and acquiescent responses (ρ^ = -0.078); the overall effect for extreme responses (ρ^ = -0.045) was not significant. Effect sizes were consistent across studies, modes of survey administsration, and different cognitive functioning domains, although some cognitive domain specificity was also observed. DISCUSSION: Lower-quality responses among respondents with lower cognitive abilities add random and systematic errors to survey measures, reducing the reliability, validity, and reproducibility of survey study results in aging research.

Attrition from longitudinal ageing studies and performance across domains of cognitive functioning: an individual participant data meta-analysis.

OBJECTIVES: This paper examined the magnitude of differences in performance across domains of cognitive functioning between participants who attrited from studies and those who did not, using data from longitudinal ageing studies where multiple cognitive tests were administered. DESIGN: Individual participant data meta-analysis. PARTICIPANTS: Data are from 10 epidemiological longitudinal studies on ageing (total n=209 518) from several Western countries (UK, USA, Mexico, etc). Each study had multiple waves of data (range of 2-17 waves), with multiple cognitive tests administered at each wave (range of 4-17 tests). Only waves with cognitive tests and information on participant dropout at the immediate next wave for adults aged 50 years or older were used in the meta-analysis. MEASURES: For each pair of consecutive study waves, we compared the difference in cognitive scores (Cohen's d) between participants who dropped out at the next study wave and those who remained. Note that our operationalisation of dropout was inclusive of all causes (eg, mortality). The proportion of participant dropout at each wave was also computed. RESULTS: The average proportion of dropouts between consecutive study waves was 0.26 (0.18 to 0.34). People who attrited were found to have significantly lower levels of cognitive functioning in all domains (at the wave 2-3 years before attrition) compared with those who did not attrit, with small-to-medium effect sizes (overall d=0.37 (0.30 to 0.43)). CONCLUSIONS: Older adults who attrited from longitudinal ageing studies had lower cognitive functioning (assessed at the timepoint before attrition) across all domains as compared with individuals who remained. Cognitive functioning differences may contribute to selection bias in longitudinal ageing studies, impeding accurate conclusions in developmental research. In addition, examining the functional capabilities of attriters may be valuable for determining whether attriters experience functional limitations requiring healthcare attention.

Prevalence of DSM-5 mild and major neurocognitive disorder in India: Results from the LASI-DAD.

INTRODUCTION: India, with its rapidly aging population, faces an alarming burden of dementia. We implemented DSM-5 criteria in large-scale, nationally representative survey data in India to characterize the prevalence of mild and major Neurocognitive disorder. METHODS: The Harmonized Diagnostic Assessment of Dementia for the Longitudinal Aging Study in India (LASI-DAD) (N = 4,096) is a nationally representative cohort study in India using multistage area probability sampling methods. Using neuropsychological testing and informant reports, we defined DSM-5 mild and major neurocognitive disorder, reported its prevalence, and evaluated criterion and construct validity of the algorithm using clinician-adjudicated Clinical Dementia Ratings (CDR)®. RESULTS: The prevalence of mild and major neurocognitive disorder, weighted to the population, is 17.6% and 7.2%. Demographic gradients with respect to age and education conform to hypothesized patterns. Among N = 2,390 participants with a clinician-adjudicated CDR, CDR ratings and DSM-5 classification agreed for N = 2,139 (89.5%) participants. DISCUSSION: The prevalence of dementia in India is higher than previously recognized. These findings, coupled with a growing number of older adults in the coming decades in India, have important implications for society, public health, and families. We are aware of no previous Indian population-representative estimates of mild cognitive impairment, a group which will be increasingly important in coming years to identify for potential therapeutic treatment.

Perception of Whole Day Workload as a Mediator Between Activity Engagement and Stress in Workers with Type 1 Diabetes.

Associations between various forms of activity engagement (e.g. work, leisure) and the experience of stress in workers have been widely documented. The mechanisms underlying these effects, however, are not fully understood. Our goal was to investigate if perceived whole day workload accounted for the relationships between daily frequencies of activities (i.e. work hours and leisure/rest) and daily stress. We analyzed data from 56 workers with type 1 diabetes (T1D) who completed approximately two weeks of intensive longitudinal assessments. Daily whole day workload was measured with an adapted version of the National Aeronautics and Space Administration Task Load Index (NASA-TLX). A variety of occupations were reported including lawyer, housekeeper, and teacher. In multilevel path analyses, day-to-day changes in whole day workload mediated 67% (p<.001), 61% (p<.001), 38% (p<.001), and 55% (p<.001) of the within-person relationships between stress and work hours, rest frequency, active leisure frequency, and day of week, respectively. Our results provided evidence that whole day workload perception may contribute to the processes linking daily activities with daily stress in workers with T1D. Perceived whole day workload may deserve greater attention as a possible stress intervention target, ones that perhaps ergonomists would be especially suited to address.

Using Attributes of Survey Items to Predict Response Times May Benefit Survey Research.

Researchers have become increasingly interested in response times to survey items as a measure of cognitive effort. We used machine learning to develop a prediction model of response times based on 41 attributes of survey items (e.g., question length, response format, linguistic features) collected in a large, general population sample. The developed algorithm can be used to derive reference values for expected response times for most commonly used survey items.

Within-person relationships of sleep duration with next-day stress and affect in the daily life of adults with Type-1 diabetes.

OBJECTIVE: The objective of this study is to examine the within-person relationships between sleep duration and next-day stress and affect in the daily life of individuals with T1D. METHODS: Study participants were recruited in the Function and Emotion in Everyday Life with Type 1 Diabetes (FEEL-T1D) study. Sleep duration was derived by synthesizing objective (actigraphy) and self-report measures. General and diabetes-specific stress and positive and negative affect were measured using ecological momentary assessment. Multilevel regression was used to examine the within-person relationships between sleep duration and next-day stress and affect. Cross-level interactions were used to explore whether gender and baseline depression and anxiety moderated these within-person relationships. RESULTS: Adults with T1D (n = 166) completed measurements for 14 days. The average age was 41.0 years, and 91 participants (54.8%) were female. The average sleep duration was 7.3 h (SD = 1.2 h). Longer sleep was significantly associated with lower general stress (p < 0.001) but not diabetes-specific stress (p = 0.18) on the next day. There were significant within-person associations of longer sleep with lower levels on next-day negative affect (overall, p = 0.002, disappoint, p = 0.05; sad, p = 0.05; tense, p < 0.001; upset, p = 0.008; anxious, p = 0.04). There were no significant associations with positive affect. Examination of the interaction effects did not reveal significant differential relationships for men and women and for individuals with and without depression or anxiety at baseline. CONCLUSION: Findings from this study suggest optimizing sleep duration as an important interventional target for better managing general stress and improving daily emotional wellbeing of individuals with T1D.

Workers' whole day workload and next day cognitive performance.

Workload experienced over the whole day, not just work periods, may impact worker cognitive performance. We hypothesized that experiencing greater than typical whole day workload would be associated with lower visual processing speed and lower sustained attention ability, on the next day. To test this, we used dynamic structural equation modeling to analyze data from 56 workers with type 1 diabetes. For a two-week period, on smartphones they answered questions about whole day workload at the end of each day, and completed cognitive tests 5 or 6 times throughout each day. Repeated smartphone cognitive tests were used, instead of traditional one- time cognitive assessment in the laboratory, to increase the ecological validity of the cognitive tests. Examples of reported occupations in our sample included housekeeper, teacher, physician, and cashier. On workdays, the mean number of work hours reported was 6.58 (SD 3.5). At the within-person level, greater whole day workload predicted decreased mean processing speed the next day (standardized estimate=-0.10, 95% CI -0.18 to -0.01) using a random intercept model; the relationship was not significant and only demonstrated a tendency toward the expected effect (standardized estimate= -0.07, 95% CI -0.15 to 0.01) in a model with a random intercept and a random regression slope. Whole day workload was not found to be associated with next-day mean sustained attention ability. Study results suggested that just one day of greater than average workload could impact next day processing speed, but future studies with larger sample sizes are needed to corroborate this finding.

Reliability and Validity of Noncognitive Ecological Momentary Assessment Survey Response Times as an Indicator of Cognitive Processing Speed in People's Natural Environment: Intensive Longitudinal Study.

BACKGROUND: Various populations with chronic conditions are at risk for decreased cognitive performance, making assessment of their cognition important. Formal mobile cognitive assessments measure cognitive performance with greater ecological validity than traditional laboratory-based testing but add to participant task demands. Given that responding to a survey is considered a cognitively demanding task itself, information that is passively collected as a by-product of ecological momentary assessment (EMA) may be a means through which people's cognitive performance in their natural environment can be estimated when formal ambulatory cognitive assessment is not feasible. We specifically examined whether the item response times (RTs) to EMA questions (eg, mood) can serve as approximations of cognitive processing speed. OBJECTIVE: This study aims to investigate whether the RTs from noncognitive EMA surveys can serve as approximate indicators of between-person (BP) differences and momentary within-person (WP) variability in cognitive processing speed. METHODS: Data from a 2-week EMA study investigating the relationships among glucose, emotion, and functioning in adults with type 1 diabetes were analyzed. Validated mobile cognitive tests assessing processing speed (Symbol Search task) and sustained attention (Go-No Go task) were administered together with noncognitive EMA surveys 5 to 6 times per day via smartphones. Multilevel modeling was used to examine the reliability of EMA RTs, their convergent validity with the Symbol Search task, and their divergent validity with the Go-No Go task. Other tests of the validity of EMA RTs included the examination of their associations with age, depression, fatigue, and the time of day. RESULTS: Overall, in BP analyses, evidence was found supporting the reliability and convergent validity of EMA question RTs from even a single repeatedly administered EMA item as a measure of average processing speed. BP correlations between the Symbol Search task and EMA RTs ranged from 0.43 to 0.58 (P<.001). EMA RTs had significant BP associations with age (P<.001), as expected, but not with depression (P=.20) or average fatigue (P=.18). In WP analyses, the RTs to 16 slider items and all 22 EMA items (including the 16 slider items) had acceptable (>0.70) WP reliability. After correcting for unreliability in multilevel models, EMA RTs from most combinations of items showed moderate WP correlations with the Symbol Search task (ranged from 0.29 to 0.58; P<.001) and demonstrated theoretically expected relationships with momentary fatigue and the time of day. The associations between EMA RTs and the Symbol Search task were greater than those between EMA RTs and the Go-No Go task at both the BP and WP levels, providing evidence of divergent validity. CONCLUSIONS: Assessing the RTs to EMA items (eg, mood) may be a method of approximating people's average levels of and momentary fluctuations in processing speed without adding tasks beyond the survey questions.

Using Item Response Times in Online Questionnaires to Detect Mild Cognitive Impairment.

OBJECTIVES: With the increase in web-based data collection, response times (RTs) for survey items have become a readily available byproduct in most online studies. We examined whether RTs in online questionnaires can prospectively discriminate between cognitively normal respondents and those with cognitive impairment, no dementia (CIND). METHOD: Participants were 943 members of a nationally representative internet panel, aged 50 and older. We analyzed RTs that were passively recorded as paradata for 37 surveys (1,053 items) administered online over 6.5 years. A multilevel location-scale model derived 3 RT parameters for each survey: (1) a respondent's average RT and 2 components of intraindividual RT variability addressing (2) systematic RT adjustments and (3) unsystematic RT fluctuations. CIND status was determined at the end of the 6.5-year period. RESULTS: All 3 RT parameters were significantly associated with CIND, with a combined predictive accuracy of area under the receiver-operating characteristic curve = 0.74. Slower average RTs, smaller systematic RT adjustments, and greater unsystematic RT fluctuations prospectively predicted a greater likelihood of CIND over periods of up to 6.5, 4.5, and 1.5 years, respectively. DISCUSSION: RTs for survey items are a potential early indicator of CIND, which may enhance analyses of predictors, correlates, and consequences of cognitive impairment in online survey research.

Impact of Overnight Glucose on Next-Day Functioning in Adults With Type 1 Diabetes: An Exploratory Intensive Longitudinal Study.

OBJECTIVE: While there is evidence that functioning, or ability to perform daily life activities, can be adversely influenced by type 1 diabetes, the impact of acute fluctuations in glucose levels on functioning is poorly understood. RESEARCH DESIGN AND METHODS: Using dynamic structural equation modeling, we examined whether overnight glucose (coefficient of variation[CV], percent time <70 mg/dL, percent time >250 mg/dL) predicted seven next-day functioning outcomes (mobile cognitive tasks, accelerometry-derived physical activity, self-reported activity participation) in adults with type 1 diabetes. We examined mediation, moderation, and whether short-term relationships were predictive of global patient-reported outcomes. RESULTS: Overall next-day functioning was significantly predicted from overnight CV (P = 0.017) and percent time >250 mg/dL (P = 0.037). Pairwise tests indicate that higher CV is associated with poorer sustained attention (P = 0.028) and lower engagement in demanding activities (P = 0.028), time <70 mg/dL is associated with poorer sustained attention (P = 0.007), and time >250 mg/dL is associated with more sedentary time (P = 0.024). The impact of CV on sustained attention is partially mediated by sleep fragmentation. Individual differences in the effect of overnight time <70 mg/dL on sustained attention predict global illness intrusiveness (P = 0.016) and diabetes-related quality of life (P = 0.036). CONCLUSIONS: Overnight glucose predicts problems with objective and self-reported next-day functioning and can adversely impact global patient-reported outcomes. These findings across diverse outcomes highlight the wide-ranging effects of glucose fluctuations on functioning in adults with type 1 diabetes.

Health Information-Seeking Behavior of Latino Caregivers of People Living with Dementia: A Mixed-Methods Study.

This mixed-methods study examined the health information-seeking behavior of Latino caregivers of people living with dementia. A structured survey and semi-structured interviews were conducted with 21 Latino caregivers in Los Angeles, California. For triangulation, semi-structured interviews were also conducted with six healthcare and social service providers. The interview transcripts were coded and analyzed via thematic analysis, while the survey data were summarized using descriptive statistics. The results show that caregivers sought information on what changes to expect as dementia progresses. Some desired detailed (limited) information to be better prepared (to worry less). The most common action to address their information needs was searching the Internet. However, those who did this tended to be concerned about the quality of information. Overall, this study sheds light on how much detail Latino caregivers desire in the information they need and the actions they take to obtain this information.

Within-person Relationships of Sleep Duration with Next-Day Stress and Affect in the Daily Life of Adults with Type-1 Diabetes.

Objective: The objective of this study is to examine the within-person relationships between sleep duration and next-day stress and affect in the daily life of individuals with T1D. Methods: Study participants were recruited in the Function and Emotion in Everyday Life with Type 1 Diabetes (FEEL-T1D) study. Sleep duration was derived by synthesizing objective (actigraphy) and self-report measures. General and diabetes-specific stress and positive and negative affect were measured using ecological momentary assessment. Multilevel regression was used to examine the within-person relationships between sleep duration and next-day stress and affect. Cross-level interactions were used to explore whether gender and baseline depression and anxiety moderated these within-person relationships. Results: Adults with T1D (n=166) completed measurements for 14 days. The average age was 40.99 years, and 91 participants (54.82%) were female. The average sleep duration was 7.29 hours (SD=1.18 hours). Longer sleep was significantly associated with lower general stress (p<0.001) but not diabetes-specific stress (p=0.18) on the next day. There were significant within-person associations of longer sleep with lower levels on next-day negative affect (overall, p=0.002, disappoint, p=0.05; sad, p=0.05; tense, p<0.001; upset, p=0.008; anxious, p=0.04). There were no significant associations with positive affect. Examination of the interaction effects did not reveal significant differential relationships for men and women and for individuals with and without depression or anxiety at baseline. Conclusion: Findings from this study suggest optimizing sleep duration as an important interventional target for better managing general stress and improving daily emotional wellbeing of individuals with T1D.

Developing Early Markers of Cognitive Decline and Dementia Derived From Survey Response Behaviors: Protocol for Analyses of Preexisting Large-scale Longitudinal Data.

BACKGROUND: Accumulating evidence shows that subtle alterations in daily functioning are among the earliest and strongest signals that predict cognitive decline and dementia. A survey is a small slice of everyday functioning; nevertheless, completing a survey is a complex and cognitively demanding task that requires attention, working memory, executive functioning, and short- and long-term memory. Examining older people's survey response behaviors, which focus on how respondents complete surveys irrespective of the content being sought by the questions, may represent a valuable but often neglected resource that can be leveraged to develop behavior-based early markers of cognitive decline and dementia that are cost-effective, unobtrusive, and scalable for use in large population samples. OBJECTIVE: This paper describes the protocol of a multiyear research project funded by the US National Institute on Aging to develop early markers of cognitive decline and dementia derived from survey response behaviors at older ages. METHODS: Two types of indices summarizing different aspects of older adults' survey response behaviors are created. Indices of subtle reporting mistakes are derived from questionnaire answer patterns in a number of population-based longitudinal aging studies. In parallel, para-data indices are generated from computer use behaviors recorded on the backend server of a large web-based panel study known as the Understanding America Study (UAS). In-depth examinations of the properties of the created questionnaire answer pattern and para-data indices will be conducted for the purpose of evaluating their concurrent validity, sensitivity to change, and predictive validity. We will synthesize the indices using individual participant data meta-analysis and conduct feature selection to identify the optimal combination of indices for predicting cognitive decline and dementia. RESULTS: As of October 2022, we have identified 15 longitudinal ageing studies as eligible data sources for creating questionnaire answer pattern indices and obtained para-data from 15 UAS surveys that were fielded from mid-2014 to 2015. A total of 20 questionnaire answer pattern indices and 20 para-data indices have also been identified. We have conducted a preliminary investigation to test the utility of the questionnaire answer patterns and para-data indices for the prediction of cognitive decline and dementia. These early results are based on only a subset of indices but are suggestive of the findings that we anticipate will emerge from the planned analyses of multiple behavioral indices derived from many diverse studies. CONCLUSIONS: Survey response behaviors are a relatively inexpensive data source, but they are seldom used directly for epidemiological research on cognitive impairment at older ages. This study is anticipated to develop an innovative yet unconventional approach that may complement existing approaches aimed at the early detection of cognitive decline and dementia. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/44627.

Regular Cannabis Use During the First Year of the Pandemic: Studying Trajectories Rather Than Prevalence.

INTRODUCTION: Cannabis use in the U.S. rose early in the COVID-19 pandemic, but it is unclear whether that rise was temporary or permanent. This study estimated the nature and sociodemographic correlates of U.S. adult subpopulations regularly using cannabis by examining weekly trajectories of use during the first year of the pandemic. METHODS: Data came from the Understanding America Study, a nationally representative panel of U.S. adults (N=8,397; March 10, 2020-March 29, 2021). A growth mixture model was deployed to identify subgroups with similar regular cannabis use. Sociodemographic correlates of subgroups were examined using multinomial logistic regression. RESULTS: Four cannabis-use groups were identified. Most participants did not regularly use cannabis (no regular use; 81.7%). The other groups increased regular use until April 2020 but then diverged. Some (7.1%) decreased thereafter, whereas others (3.4%) maintained their elevated use until October 26, 2020 before decreasing. The last group (7.7%) sustained their elevated use throughout. Individuals aged between 18 and 39 years, unmarried, living in poverty, without a college degree, and with longer unemployment or underemployment spells had higher odds of being in the other groups with more weekly use than in the no-regular-use group. CONCLUSIONS: The analyses revealed population subgroups with prolonged regular cannabis use and a disproportionate concentration of socioeconomically vulnerable members of society in these subgroups. These findings elucidate important heterogeneity in the subpopulations using cannabis, highlighting the urgent need to tailor public health programs for subgroups that may have unique service needs.

Estimating the Prevalence of Dementia in India Using a Semi-Supervised Machine Learning Approach.

INTRODUCTION: Accurate estimation of dementia prevalence is essential for making effective public and social care policy to support individuals and families suffering from the disease. The purpose of this paper is to estimate the prevalence of dementia in India using a semi-supervised machine learning approach based on a large nationally representative sample. METHODS: The sample of this study is adults 60 years or older in the wave 1 (2017-2019) of the Longitudinal Aging Study in India (LASI). A subsample in LASI received extensive cognitive assessment and clinical consensus ratings and therefore has diagnoses of dementia. A semi-supervised machine learning model was developed to predict the status of dementia for LASI participants without diagnoses. After obtaining the predictions, sampling weights and age standardization to the World Health Organization (WHO) standard population were applied to generate the estimate for prevalence of dementia in India. RESULTS: The prevalence of dementia for those aged 60 years and older in India was 8.44% (95% CI: 7.89%-9.01%). The age-standardized prevalence was estimated to be 8.94% (95% CI: 8.36%-9.55%). The prevalence of dementia was greater for those who were older, were females, received no education, and lived in rural areas. DISCUSSION: The prevalence of dementia in India may be higher than prior estimates derived from local studies. These prevalence estimates provide the information necessary for making long-term planning of public and social care policy. The semi-supervised machine learning approach adopted in this paper may also be useful for other large population aging studies that have a similar data structure.

Quality of Survey Responses at Older Ages Predicts Cognitive Decline and Mortality Risk.

Background and Objectives: It is widely recognized that survey satisficing, inattentive, or careless responding in questionnaires reduce the quality of self-report data. In this study, we propose that such low-quality responding (LQR) can carry substantive meaning at older ages. Completing questionnaires is a cognitively demanding task and LQR among older adults may reflect early signals of cognitive deficits and pathological aging. We hypothesized that older people displaying greater LQR would show faster cognitive decline and greater mortality risk. Research Design and Methods: We analyzed data from 9, 288 adults 65 years or older in the Health and Retirement Study. Indicators of LQR were derived from participants' response patterns in 102 psychosocial questionnaire items administered in 2006-2008. Latent growth models examined whether LQR predicted initial status and change in cognitive functioning, assessed with the modified Telephone Interview for Cognitive Status, over the subsequent 10 years. Discrete-time survival models examined whether LQR was associated with mortality risk over the 10 years. We also examined evidence for indirect (mediated) effects in which LQR predicts mortality via cognitive trajectories. Results: After adjusting for age, gender, race, marital status, education, health conditions, smoking status, physical activity, and depressive symptoms, greater LQR was cross-sectionally associated with poorer cognitive functioning, and prospectively associated with faster cognitive decline over the follow-up period. Furthermore, greater LQR was associated with increased mortality risk during follow-up, and this effect was partially accounted for by the associations between LQR and cognitive functioning. Discussion and Implications: Self-report questionnaires are not formally designed as cognitive tasks, but this study shows that LQR indicators derived from self-report measures provide objective, performance-based information about individuals' cognitive functioning and survival. Self-report surveys are ubiquitous in social science, and indicators of LQR may be of broad relevance as predictors of cognitive and health trajectories in older people.

Alcohol use trajectories among U.S. adults during the first 42 weeks of the COVID-19 pandemic.

BACKGROUND: This study characterized the prevalence, drinking patterns, and sociodemographic characteristics of U.S. adult subpopulations with distinct drinking trajectories during the COVID-19 pandemic's first 42 weeks. METHODS: Adult respondents (n = 8130) in a nationally representative prospective longitudinal study completed 21 biweekly web surveys (March 2020 to January 2021). Past-week alcohol drinking frequency (drinking days [range: 0 to 7]) and intensity (binge drinking on usual past-week drinking day [yes/no]) were assessed at each timepoint. Growth mixture models identified multiple subpopulations with homogenous drinking trajectories based on mean drinking days or binge drinking proportional probabilities across time. RESULTS: Four drinking frequency trajectories were identified: Minimal/stable (72.8% [95% CI = 71.8 to 73.8]) with <1 mean past-week drinking days throughout; Moderate/late decreasing (6.7% [95% CI = 6.2 to 7.3) with 3.13 mean March drinking days and reductions during summer, reaching 2.12 days by January 2021; Moderate/early increasing (12.9% [95% CI = 12.2 to 13.6) with 2.13 mean March drinking days that increased in April and then plateaued, ending with 3.20 mean days in January 2021; and Near daily/early increasing (7.6% [95% CI = 7.0 to 8.2]) with 5.58 mean March drinking days that continued increasing without returning to baseline. Four drinking intensity trajectories were identified: Minimal/stable (85.8% [95% CI = 85.0% to 86.5%]) with <0.01 binge drinking probabilities throughout; Low-to-moderate/fluctuating (7.4% [95% CI = 6.8% to 8%]) with varying binge probabilities across timepoints (range:0.12 to 0.26); Moderate/mid increasing (4.2% [95% CI = 3.7% to 4.6%]) with 0.39 April binge drinking probability rising to 0.65 during August-September without returning to baseline; High/early increasing trajectory (2.7% [95% CI = 2.3% to 3%]) with 0.84 binge drinking probability rising to 0.96 by June without returning to baseline. Males, Whites, middle-aged/older adults, college degree recipients, those consistently working, and those above the poverty limit were overrepresented in various increasing (vs. minimal/stable) frequency trajectories. Males, Whites, nonmarried, those without college degree, 18 to 39-year-olds, and middle aged were overrepresented in increasing (vs. minimal/stable) intensity trajectories. CONCLUSIONS: Several distinct U.S. adult sociodemographic subpopulations appear to have acquired new drinking patterns during the pandemic's first 42 weeks. Frequent alcohol use assessment in the COVID-19 era could improve personalized medicine and population health efforts to reduce drinking.

Validation of the National Aeronautics and Space Administration Task Load Index (NASA-TLX) adapted for the whole day repeated measures context.

Our objective was to investigate the validity of four-item and six-item versions of the National Aeronautics and Space Administration Task Load Index (NASA-TLX, or TLX for short) for measuring workload over a whole day in the repeated measures context. We analysed data on 51 people with type 1 diabetes from whom we collected ecological momentary assessment and daily diary data over 14 days. The TLX was administered at the last survey of every day. Confirmatory factor analysis fit statistics indicated that neither the TLX-6 nor TLX-4 were a unidimensional representation of whole day workload. In exploratory analyses, another set of TLX items we refer to as TLX-4v2 was sufficiently unidimensional. Raw sum scores from the TLX-6 and TLX-4v2 had plausible relationships with other measures, as evidenced by intra-person correlations and mixed-effects models. TLX-6 appears to capture multiple factors contributing to workload, while TLX-4v2 assesses the single factor of 'mental strain'. Practitioner Summary: Using within-person longitudinal data, we found evidence supporting the validity of a measure evaluating whole-day workload (i.e. workload derived from all sources, not only paid employment) derived from the NASA-TLX. This measure may be useful to assess how day-to-day variations in workload impact quality of life among adults.Abbreviations: NASA-TLX or TLX: National Aeronautics and Space Administration Task Load Index; TLX-6: six item version of the NASA-TLX; TLX-4: four item version of the NASA-TLX, TLX-4v2: four item NASA-TLX version two; NIOSH: National Institute for Occupational Safety and Health; CFA: confirmatory factor analysis; T1D: type 1 diabetes; EMA: ecological momentary assessment; BG: blood glucose; SD: standard deviation; CV: coefficient of variation; RMSEA: root mean square error of approximation; CFI: comparative fit index; TLI: Tucker-Lewis Index; SRMR: standardized root mean square residual; AIC: Akaike information criterion; BIC: Bayesian information criterion; χ2: Chi-square statistic.