Early Identification of Cognitive Impairment in Community Environments Through Modeling Subtle Inconsistencies in Questionnaire Responses: Machine Learning Model Development and Validation.

Background: The underdiagnosis of cognitive impairment hinders timely intervention of dementia. Health professionals working in the community play a critical role in the early detection of cognitive impairment, yet still face several challenges such as a lack of suitable tools, necessary training, and potential stigmatization.

Objective: This study explored a novel application integrating psychometric methods with data science techniques to model subtle inconsistencies in questionnaire response data for early identification of cognitive impairment in community environments.

Within-person relationship between employment insecurity and mental health: a longitudinal analysis of the Understanding America Study.

Background: Employment insecurity is a socioeconomic factor influencing mental health, yet the empirical evidence supporting this claim has important limitations. The fluctuations in employment insecurity throughout the COVID-19 pandemic offered a distinctive opportunity to delve deeper into this issue. By viewing employment as a dynamic process, this study explores the within-person relationship between shifts in employment status and corresponding changes in mental health.

Whole Day Workload: Evaluation of a New Outcome Measure in Occupational Therapy for Adults With Type 1 Diabetes.

Importance: Typical whole day workload is a metric with potential relevance to the occupational balance and well-being of individuals with chronic conditions.

Objective: To examine the reliability and validity of using multiple daily NASA Task Load Index measures (whole day TLX) as an indicator of typical whole day workload experienced by adults with Type 1 diabetes (T1D).

Design: Participants with T1D completed cross-sectional measures and 2 wk of ecological momentary assessments (EMA) and daily diaries.

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.

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.

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.

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).

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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).

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.

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.

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 in the 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.

Understanding Worker Well-Being Relative to High-Workload and Recovery Activities across a Whole Day: Pilot Testing an Ecological Momentary Assessment Technique.

Occupational health and safety is experiencing a paradigm shift from focusing only on health at the workplace toward a holistic approach and worker well-being framework that considers both work and non-work factors. Aligned with this shift, the purpose of this pilot study was to examine how, within a person, frequencies of high-workload and recovery activities from both work and non-work periods were associated with same day well-being measures. We analyzed data on 45 workers with type 1 diabetes from whom we collected activity data 5-6 times daily over 14 days.