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.

Interviewer biases in medical survey data: The example of blood pressure measurements.

Health agencies rely upon survey-based physical measures to estimate the prevalence of key global health indicators such as hypertension. Such measures are usually collected by nonhealthcare worker personnel and are potentially subject to measurement error due to variations in interviewer technique and setting, termed "interviewer effects." In the context of physical measurements, particularly in low- and middle-income countries, interviewer-induced biases have not yet been examined. Using blood pressure as a case study, we aimed to determine the relative contribution of interviewer effects on the total variance of blood pressure measurements in three large nationally representative health surveys from the Global South. We utilized 169,681 observations between 2008 and 2019 from three health surveys (Indonesia Family Life Survey, National Income Dynamics Study of South Africa, and Longitudinal Aging Study in India). In a linear mixed model, we modeled systolic blood pressure as a continuous dependent variable and interviewer effects as random effects alongside individual factors as covariates. To quantify the interviewer effect-induced uncertainty in hypertension prevalence, we utilized a bootstrap approach comparing subsamples of observed blood pressure measurements to their adjusted counterparts. Our analysis revealed that the proportion of variation contributed by interviewers to blood pressure measurements was statistically significant but small: ∼0.24--2.2% depending on the cohort. Thus, hypertension prevalence estimates were not substantially impacted at national scales. However, individual extreme interviewers could account for measurement divergences as high as 12%. Thus, highly biased interviewers could have important impacts on hypertension estimates at the subdistrict level.

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.

Cross-national comparisons of later-life cognitive function using data from the Harmonized Cognitive Assessment Protocol (HCAP): Considerations and recommended best practices.

The Harmonized Cognitive Assessment Protocol (HCAP) is a major innovation that provides, for the first time, harmonized data for cross-national comparisons of later-life cognitive functions that are sensitive to linguistic, cultural, and educational differences across countries. However, cognitive function does not lend itself to direct comparison across diverse populations without careful consideration of the best practices for such comparisons. This perspective discusses theoretical and methodological considerations and offers a set of recommended best practices for conducting cross-national comparisons of risk factor associations using HCAP data. Because existing and planned HCAP studies provide cognition data representing an estimated 75% of the global population ≥65 years of age, these recommended best practices will support high-quality comparative analyses of cognitive aging around the world. The principles described in this perspective are applicable to any researcher aiming to integrate or compare harmonized data on cognitive outcomes and their risk and protective factors across diverse populations.

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.

Large-Scale Modeling of Sparse Protein Kinase Activity Data.

Protein kinases are a protein family that plays an important role in several complex diseases such as cancer and cardiovascular and immunological diseases. Protein kinases have conserved ATP binding sites, which when targeted can lead to similar activities of inhibitors against different kinases. This can be exploited to create multitarget drugs. On the other hand, selectivity (lack of similar activities) is desirable in order to avoid toxicity issues. There is a vast amount of protein kinase activity data in the public domain, which can be used in many different ways. Multitask machine learning models are expected to excel for these kinds of data sets because they can learn from implicit correlations between tasks (in this case activities against a variety of kinases). However, multitask modeling of sparse data poses two major challenges: (i) creating a balanced train-test split without data leakage and (ii) handling missing data. In this work, we construct a protein kinase benchmark set composed of two balanced splits without data leakage, using random and dissimilarity-driven cluster-based mechanisms, respectively. This data set can be used for benchmarking and developing protein kinase activity prediction models. Overall, the performance on the dissimilarity-driven cluster-based split is lower than on random split-based sets for all models, indicating poor generalizability of models. Nevertheless, we show that multitask deep learning models, on this very sparse data set, outperform single-task deep learning and tree-based models. Finally, we demonstrate that data imputation does not improve the performance of (multitask) models on this benchmark set.

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.

Deep phenotyping and genomic data from a nationally representative study on dementia in India.

The Harmonized Diagnostic Assessment of Dementia for the Longitudinal Aging Study in India (LASI-DAD) is a nationally representative in-depth study of cognitive aging and dementia. We present a publicly available dataset of harmonized cognitive measures of 4,096 adults 60 years of age and older in India, collected across 18 states and union territories. Blood samples were obtained to carry out whole blood and serum-based assays. Results are included in a venous blood specimen datafile that can be linked to the Harmonized LASI-DAD dataset. A global screening array of 960 LASI-DAD respondents is also publicly available for download, in addition to neuroimaging data on 137 LASI-DAD participants. Altogether, these datasets provide comprehensive information on older adults in India that allow researchers to further understand risk factors associated with cognitive impairment and dementia.

Prevalence of dementia in India: National and state estimates from a nationwide study.

INTRODUCTION: Prior estimates of dementia prevalence in India were based on samples from selected communities, inadequately representing the national and state populations. METHODS: From the Longitudinal Aging Study in India (LASI) we recruited a sample of adults ages 60+ and administered a rich battery of neuropsychological tests and an informant interview in 2018 through 2020. We obtained a clinical consensus rating of dementia status for a subsample (N = 2528), fitted a logistic model for dementia status on this subsample, and then imputed dementia status for all other LASI respondents aged 60+ (N = 28,949). RESULTS: The estimated dementia prevalence for adults ages 60+ in India is 7.4%, with significant age and education gradients, sex and urban/rural differences, and cross-state variation. DISCUSSION: An estimated 8.8 million Indians older than 60 years have dementia. The burden of dementia cases is unevenly distributed across states and subpopulations and may therefore require different levels of local planning and support. HIGHLIGHTS: The estimated dementia prevalence for adults ages 60+ in India is 7.4%. About 8.8 million Indians older than 60 years live with dementia. Dementia is more prevalent among females than males and in rural than urban areas. Significant cross-state variation exists in dementia prevalence.

Identifying Cognitive Impairment Among Older Participants in a Nationally Representative Internet Panel.

OBJECTIVES: The Health and Retirement Study Telephone Interview for Cognitive Status (HRS TICS) score and its associated Langa-Weir cutoffs are widely used as indicators of cognitive status for research purposes in population-based studies. The classification is based on in-person and phone interviews of older individuals. Our purpose was to develop a corresponding classification for web-based self-administered assessments. METHODS: Participants were 925 members of a nationally representative internet panel, all aged 50 and older. We conducted (a) a phone interview comprised of cognitive items used to construct the HRS TICS score, and (b) a web counterpart with self-administered cognitive items, while also considering (c) other already administered web-based cognitive tests and instrumental activities of daily living survey questions, all from the same respondents. RESULTS: The web-administered HRS TICS items have only modest correlations with the same phone items, although neither mode showed universally higher scores than the other. Using latent variable modeling, we created a probability of cognitive impairment score for the web-based battery that achieved good correspondence to the phone Langa-Weir classification. DISCUSSION: The results permit analyses of predictors, correlates, and consequences of cognitive impairment in web surveys where relevant cognitive test and functional abilities items are available. We discuss challenges and caveats that may affect the findings.

Economic costs of dementia in 11 countries in Europe: Estimates from nationally representative cohorts of a panel study.

Background: With population aging, the economic burden of dementia is growing in Europe. Understanding the economic costs of dementia provides an important basis for prioritization in public health policy and resource allocation. Methods: We calculate the economic costs of dementia, including both direct medical and social care costs and indirect costs of informal care, for 11 countries in Europe. Costs are estimated using population-representative data from the Survey of Health, Ageing, and Retirement in Europe from 2004 to 2017, supplemented with external information about wages of care workers, dementia prevalence, and fraction of direct costs paid by other sources. We report overall costs for persons, both living and deceased with dementia and also isolate the costs attributable to dementia by estimating regression models that relate a given cost component to dementia while controlling for coexisting conditions and demographics. We make the monetary data comparable by adjusting for inflation and Purchasing Power Parity to 2018 euros. Findings: Average annual direct out of pocket costs that can be attributed to dementia vary between EUR 253(95% CI: -17 to 522) and EUR 859 (95% CI: -587 to 2306) across countries, but are not statistically significant after adjustment for multiple testing. Average annual hours of informal care that can be attributed to dementia vary between 163 (95% CI: 27-299) and 1051 (95% CI: 15-2086) annual hours across countries, and are statistically significant in all countries before adjustment for multiple testing, and in seven out of 11 countries after this adjustment. Combining these estimates with external wage information in each country implies a burden between EUR 2687.4 (95% CI: 704.5 to 4670.3) and EUR 15,468 (95% CI: 8088.1 to 22,847.9) per individual with dementia per year depending on the country. When combined with external estimates of the fraction of direct costs covered by other payment sources (insurance, government) and numbers of individuals with dementia, estimates of the total costs of dementia at the country level vary from EUR 162.9 million (95% CI: 56.3 to 269.5) in Estonia to EUR 32,606.9 (95% CI: 13,893.9 to 51,319.9) in Germany. Informal care costs account for the largest proportion of costs attributable to dementia in all European countries, varying between about 50% and about 90%. Interpretation: The economic burden of dementia on families in terms of direct out-of-pocket and informal care costs varies greatly by country, depending on the health and social care systems. Informal care costs accounts for the largest proportion of costs, requiring policy attention to dementia care provision and costs. Funding: This project is funded by the National Institute on Aging, National Institutes of Health, USA (R01 AG030153).

Performance of the Informant Questionnaire on Cognitive Decline for the Elderly (IQCODE) in a nationally representative study in India: the LASI-DAD study.

BACKGROUND: Low and middle-income countries like India anticipate rapid population aging and increases in dementia burden. In India, dementia screening scales originally developed in other contexts need to be assessed for feasibility and validity, given the number of different languages and varying levels of literacy and education. METHOD: Using data from the Longitudinal Aging Study in India-Diagnostic Assessment of Dementia (N = 4,028), we characterize the performance of the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE). We described patterns and correlates of missingness, evaluated the psychometric properties of the scale, and assessed criterion validity against the Hindi Mental State Examination (HMSE) using linear regression. RESULTS: Several IQCODE items had high levels of missingness, which was associated with urbanicity, respondent's gender, and informant's generation (same vs. younger generation). Full IQCODE scores showed strong criterion validity against the HMSE; each 1-point increase in IQCODE score was associated with a 3.03-point lower score on the HMSE, controlling for age, gender, and urbanicity. The statistically significant association between IQCODE and HMSE was stronger in urban than rural settings (p-value for interaction = 0.04). Associations between IQCODE and HMSE remained unchanged after removing the three items with the highest levels of differential missingness (remembering addresses and telephone numbers, ability to work with familiar machines, ability to learn to use new gadget or machine). CONCLUSION: Findings raise questions about the value of including items with high proportions of missingness, which may signal cultural irrelevance, while removing them did not affect criterion validity.

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.

Self-administered Web-Based Tests of Executive Functioning and Perceptual Speed: Measurement Development Study With a Large Probability-Based Survey Panel.

BACKGROUND: Cognitive testing in large population surveys is frequently used to describe cognitive aging and determine the incidence rates, risk factors, and long-term trajectories of the development of cognitive impairment. As these surveys are increasingly administered on internet-based platforms, web-based and self-administered cognitive testing calls for close investigation. OBJECTIVE: Web-based, self-administered versions of 2 age-sensitive cognitive tests, the Stop and Go Switching Task for executive functioning and the Figure Identification test for perceptual speed, were developed and administered to adult participants in the Understanding America Study. We examined differences in cognitive test scores across internet device types and the extent to which the scores were associated with self-reported distractions in everyday environments in which the participants took the tests. In addition, national norms were provided for the US population. METHODS: Data were collected from a probability-based internet panel representative of the US adult population-the Understanding America Study. Participants with access to both a keyboard- and mouse-based device and a touch screen-based device were asked to complete the cognitive tests twice in a randomized order across device types, whereas participants with access to only 1 type of device were asked to complete the tests twice on the same device. At the end of each test, the participants answered questions about interruptions and potential distractions that occurred during the test. RESULTS: Of the 7410 (Stop and Go) and 7216 (Figure Identification) participants who completed the device ownership survey, 6129 (82.71% for Stop and Go) and 6717 (93.08% for Figure Identification) participants completed the first session and correctly responded to at least 70% of the trials. On average, the standardized differences across device types were small, with the absolute value of Cohen d ranging from 0.05 (for the switch score in Stop and Go and the Figure Identification score) to 0.13 (for the nonswitch score in Stop and Go). Poorer cognitive performance was moderately associated with older age (the absolute value of r ranged from 0.32 to 0.61), and this relationship was comparable across device types (the absolute value of Cohen q ranged from 0.01 to 0.17). Approximately 12.72% (779/6123 for Stop and Go) and 12.32% (828/6721 for Figure Identification) of participants were interrupted during the test. Interruptions predicted poorer cognitive performance (P<.01 for all scores). Specific distractions (eg, watching television and listening to music) were inconsistently related to cognitive performance. National norms, calculated as weighted average scores using sampling weights, suggested poorer cognitive performance as age increased. CONCLUSIONS: Cognitive scores assessed by self-administered web-based tests were sensitive to age differences in cognitive performance and were comparable across the keyboard- and touch screen-based internet devices. Distraction in everyday environments, especially when interrupted during the test, may result in a nontrivial bias in cognitive testing.

Hypertension awareness, treatment, and control and their association with healthcare access in the middle-aged and older Indian population: A nationwide cohort study.

BACKGROUND: Hypertension is the most important cardiovascular risk factor in India, and representative studies of middle-aged and older Indian adults have been lacking. Our objectives were to estimate the proportions of hypertensive adults who had been diagnosed, took antihypertensive medication, and achieved control in the middle-aged and older Indian population and to investigate the association between access to healthcare and hypertension management. METHODS AND FINDINGS: We designed a nationally representative cohort study of the middle-aged and older Indian population, the Longitudinal Aging Study in India (LASI), and analyzed data from the 2017-2019 baseline wave (N = 72,262) and the 2010 pilot wave (N = 1,683). Hypertension was defined as self-reported physician diagnosis or elevated blood pressure (BP) on measurement, defined as systolic BP ≥ 140 mm Hg or diastolic BP ≥ 90 mm Hg. Among hypertensive individuals, awareness, treatment, and control were defined based on self-reports of having been diagnosed, taking antihypertensive medication, and not having elevated BP, respectively. The estimated prevalence of hypertension for the Indian population aged 45 years and older was 45.9% (95% CI 45.4%-46.5%). Among hypertensive individuals, 55.7% (95% CI 54.9%-56.5%) had been diagnosed, 38.9% (95% CI 38.1%-39.6%) took antihypertensive medication, and 31.7% (95% CI 31.0%-32.4%) achieved BP control. In multivariable logistic regression models, access to public healthcare was a key predictor of hypertension treatment (odds ratio [OR] = 1.35, 95% CI 1.14-1.60, p = 0.001), especially in the most economically disadvantaged group (OR of the interaction for middle economic status = 0.76, 95% CI 0.61-0.94, p = 0.013; OR of the interaction for high economic status = 0.84, 95% CI 0.68-1.05, p = 0.124). Having health insurance was not associated with improved hypertension awareness among those with low economic status (OR = 0.96, 95% CI 0.86-1.07, p = 0.437) and those with middle economic status (OR of the interaction = 1.15, 95% CI 1.00-1.33, p = 0.051), but it was among those with high economic status (OR of the interaction = 1.28, 95% CI 1.10-1.48, p = 0.001). Comparing hypertension awareness, treatment, and control rates in the 4 pilot states, we found statistically significant (p < 0.001) improvement in hypertension management from 2010 to 2017-2019. The limitations of this study include the pilot sample being relatively small and that it recruited from only 4 states. CONCLUSIONS: Although considerable variations in hypertension diagnosis, treatment, and control exist across different sociodemographic groups and geographic areas, reducing uncontrolled hypertension remains a public health priority in India. Access to healthcare is closely tied to both hypertension diagnosis and treatment.

Revisiting the Effect of Retirement on Cognition: Heterogeneity and Endowment.

Since the seminal paper of Rohwedder and Willis (2010), the effect of retirement on cognition has drawn significant research interest from economists. Especially with ongoing policy discussions about public pension reforms and the increasing burden of dementia, it is indisputably an important research question with significant policy implications. Building on this growing literature, our paper makes two important contributions. First, we explicitly consider cognitive demands of jobs in studying hetereogeneity of the retirement effect. As the primary explanation for the potential adverse effect of retirement is that cognition is better maintained through mental exercise (Salthouse, 2006), by investigating the cognitive demands of the job one retires from we can directly test the hypothesized relationship. Second, we avoid biases associated with omitted variables, particularly by controlling for endowed cognitive ability. While endowed, genetic differences in cognitive ability is an important omitted variable that can explain individual differences in cognitive performance as well as selection into a particular type of job, this inherited characteristic has not been controlled for in the prior literature. Taking advantage of the polygenic risk score of cognition (Davies et al., 2015), we control for individual differences in genetic endowments in estimating the effect of retirement on cognition. We find supporting evidence for differential effects of retirement by cognitive demands of jobs after controlling for innate differences in cognition and educational attainment.

Inferring Cognitive Abilities from Response Times to Web-Administered Survey Items in a Population-Representative Sample.

Monitoring of cognitive abilities in large-scale survey research is receiving increasing attention. Conventional cognitive testing, however, is often impractical on a population level highlighting the need for alternative means of cognitive assessment. We evaluated whether response times (RTs) to online survey items could be useful to infer cognitive abilities. We analyzed >5 million survey item RTs from >6000 individuals administered over 6.5 years in an internet panel together with cognitive tests (numerical reasoning, verbal reasoning, task switching/inhibitory control). We derived measures of mean RT and intraindividual RT variability from a multilevel location-scale model as well as an expanded version that separated intraindividual RT variability into systematic RT adjustments (variation of RTs with item time intensities) and residual intraindividual RT variability (residual error in RTs). RT measures from the location-scale model showed weak associations with cognitive test scores. However, RT measures from the expanded model explained 22−26% of the variance in cognitive scores and had prospective associations with cognitive assessments over lag-periods of at least 6.5 years (mean RTs), 4.5 years (systematic RT adjustments) and 1 year (residual RT variability). Our findings suggest that RTs in online surveys may be useful for gaining information about cognitive abilities in large-scale survey research.

Subtle mistakes in self-report surveys predict future transition to dementia.

INTRODUCTION: We investigate whether indices of subtle reporting mistakes derived from responses in self-report surveys are associated with dementia risk. METHODS: We examined 13,831 participants without dementia from the prospective, population-based Health and Retirement Study (mean age 69 ± 10 years, 59% women). Participants' response patterns in 21 questionnaires were analyzed to identify implausible responses (multivariate outliers), incompatible responses (Guttman errors), acquiescent responses, random errors, and the proportion of skipped questions. Subsequent incident dementia was determined over up to 10 years of follow-up. RESULTS: During follow-up, 2074 participants developed dementia and 3717 died. Each of the survey response indices was associated with future dementia risk controlling for confounders and accounting for death as a competing risk. Stronger associations were evident for participants who were younger and cognitively normal at baseline. DISCUSSION: Mistakes in the completion of self-report surveys in longitudinal studies may be early indicators of dementia among middle-aged and older adults.