Ecological risk and protective factors for food insufficiency in Los Angeles County during the COVID-19 pandemic.

OBJECTIVE: The COVID-19 pandemic increased food insufficiency: a severe form of food insecurity. Drawing on an ecological framework, we aimed to understand factors that contributed to changes in food insufficiency from April to December 2020, in a large urban population hard hit by the pandemic. DESIGN: We conducted internet surveys every 2 weeks in April-December 2020, including a subset of items from the Food Insecurity Experience Scale. Longitudinal analysis identified predictors of food insufficiency, using fixed effects models. SETTING: Los Angeles County, which has a diverse population of 10 million residents. PARTICIPANTS: A representative sample of 1535 adults in Los Angeles County who are participants in the Understanding Coronavirus in America tracking survey. RESULTS: Rates of food insufficiency spiked in the first year of the pandemic, especially among participants living in poverty, in middle adulthood and with larger households. Government food assistance from the Supplemental Nutrition Assistance Program was significantly associated with reduced food insufficiency over time, while other forms of assistance such as help from family and friends or stimulus funds were not. CONCLUSIONS: The findings highlight that during a crisis, there is value in rapidly monitoring food insufficiency and investing in government food benefits.

Effects of Excluding Those Who Report Having "Syndomitis" or "Chekalism" on Data Quality: Longitudinal Health Survey of a Sample From Amazon's Mechanical Turk.

BACKGROUND: Researchers have implemented multiple approaches to increase data quality from existing web-based panels such as Amazon's Mechanical Turk (MTurk). OBJECTIVE: This study extends prior work by examining improvements in data quality and effects on mean estimates of health status by excluding respondents who endorse 1 or both of 2 fake health conditions ("Syndomitis" and "Chekalism"). METHODS: Survey data were collected in 2021 at baseline and 3 months later from MTurk study participants, aged 18 years or older, with an internet protocol address in the United States, and who had completed a minimum of 500 previous MTurk "human intelligence tasks." We included questions about demographic characteristics, health conditions (including the 2 fake conditions), and the Patient Reported Outcomes Measurement Information System (PROMIS)-29+2 (version 2.1) preference-based score survey. The 3-month follow-up survey was only administered to those who reported having back pain and did not endorse a fake condition at baseline. RESULTS: In total, 15% (996/6832) of the sample endorsed at least 1 of the 2 fake conditions at baseline. Those who endorsed a fake condition at baseline were more likely to identify as male, non-White, younger, report more health conditions, and take longer to complete the survey than those who did not endorse a fake condition. They also had substantially lower internal consistency reliability on the PROMIS-29+2 scales than those who did not endorse a fake condition: physical function (0.69 vs 0.89), pain interference (0.80 vs 0.94), fatigue (0.80 vs 0.92), depression (0.78 vs 0.92), anxiety (0.78 vs 0.90), sleep disturbance (-0.27 vs 0.84), ability to participate in social roles and activities (0.77 vs 0.92), and cognitive function (0.65 vs 0.77). The lack of reliability of the sleep disturbance scale for those endorsing a fake condition was because it includes both positively and negatively worded items. Those who reported a fake condition reported significantly worse self-reported health scores (except for sleep disturbance) than those who did not endorse a fake condition. Excluding those who endorsed a fake condition improved the overall mean PROMIS-29+2 (version 2.1) T-scores by 1-2 points and the PROMIS preference-based score by 0.04. Although they did not endorse a fake condition at baseline, 6% (n=59) of them endorsed at least 1 of them on the 3-month survey and they had lower PROMIS-29+2 score internal consistency reliability and worse mean scores on the 3-month survey than those who did not report having a fake condition. Based on these results, we estimate that 25% (1708/6832) of the MTurk respondents provided careless or dishonest responses. CONCLUSIONS: This study provides evidence that asking about fake health conditions can help to screen out respondents who may be dishonest or careless. We recommend this approach be used routinely in samples of members of MTurk.

Trajectories of Mental Distress Among U.S. Adults During the COVID-19 Pandemic.

BACKGROUND: Cross-sectional studies have found that the coronavirus disease 2019 (COVID-19) pandemic has negatively affected population-level mental health. Longitudinal studies are necessary to examine trajectories of change in mental health over time and identify sociodemographic groups at risk for persistent distress. PURPOSE: To examine the trajectories of mental distress between March 10 and August 4, 2020, a key period during the COVID-19 pandemic. METHODS: Participants included 6,901 adults from the nationally representative Understanding America Study, surveyed at baseline between March 10 and 31, 2020, with nine follow-up assessments between April 1 and August 4, 2020. Mixed-effects logistic regression was used to examine the association between date and self-reported mental distress (measured with the four-item Patient Health Questionnaire) among U.S. adults overall and among sociodemographic subgroups defined by sex, age, race/ethnicity, household structure, federal poverty line, and census region. RESULTS: Compared to March 11, the odds of mental distress among U.S. adults overall were 1.84 (95% confidence interval [CI] = 1.65-2.07) times higher on April 1 and 1.92 (95% CI = 1.62-2.28) times higher on May 1; by August 1, the odds of mental distress had returned to levels comparable to March 11 (odds ratio [OR] = 0.80, 95% CI = 0.66-0.96). Females experienced a sharper increase in mental distress between March and May compared to males (females: OR = 2.29, 95% CI = 1.85-2.82; males: OR = 1.53, 95% CI = 1.15-2.02). CONCLUSIONS: These findings highlight the trajectory of mental health symptoms during an unprecedented pandemic, including the identification of populations at risk for sustained mental distress.

The role of trust in the likelihood of receiving a COVID-19 vaccine: Results from a national survey.

High acceptance of coronavirus disease 2019 (COVID-19) vaccines is instrumental to ending the pandemic. Vaccine acceptance by subgroups of the population depends on their trust in COVID-19 vaccines. We surveyed a probability-based internet panel of 7832 adults from December 23, 2020-January 19, 2021 about their likelihood of getting a COVID-19 vaccine and the following domains of trust: an individual's generalized trust, trust in COVID-19 vaccine's efficacy and safety, trust in the governmental approval process and general vaccine development process for COVID-19 vaccines, trust in their physician about COVID-19, and trust in other sources about COVID-19. We included identified at-risk subgroups: healthcare workers, older adults (65-74-year-olds and ≥ 75-year-olds), frontline essential workers, other essential workers, and individuals with high-risk chronic conditions. Of 5979 respondents, only 57.4% said they were very likely or somewhat likely to get a COVID-19 vaccine. More hesitant respondents (p < 0.05) included: women, young adults (18-49 years), Blacks, individuals with lower education, those with lower income, and individuals without high-risk chronic conditions. Lack of trust in the vaccine approval and development processes explained most of the demographic variation in stated vaccination likelihood, while other domains of trust explained less variation. We conclude that hesitancy for COVID-19 vaccines is high overall and among at-risk subgroups, and hesitancy is strongly tied to trust in the vaccine approval and development processes. Building trust is critical to ending the pandemic.

Mental Distress in the United States at the Beginning of the COVID-19 Pandemic.

Objectives. To assess the impact of the COVID-19 pandemic on mental distress in US adults.Methods. Participants were 5065 adults from the Understanding America Study, a probability-based Internet panel representative of the US adult population. The main exposure was survey completion date (March 10-16, 2020). The outcome was mental distress measured via the 4-item version of the Patient Health Questionnaire.Results. Among states with 50 or more COVID-19 cases as of March 10, each additional day was significantly associated with an 11% increase in the odds of moving up a category of distress (odds ratio = 1.11; 95% confidence interval = 1.01, 1.21; P = .02). Perceptions about the likelihood of getting infected, death from the virus, and steps taken to avoid infecting others were associated with increased mental distress in the model that included all states. Individuals with higher consumption of alcohol or cannabis or with history of depressive symptoms were at significantly higher risk for mental distress.Conclusions. These data suggest that as the COVID-19 pandemic continues, mental distress may continue to increase and should be regularly monitored. Specific populations are at high risk for mental distress, particularly those with preexisting depressive symptoms.

Effects of income supplementation on health of the poor elderly: the case of Mexico.

We use an income supplementation experiment we designed in the state of Yucatan in Mexico for residents 70 y and older to evaluate health impacts of additional income. Two cities in the State of Yucatan, Valladolid (treatment) and Motul (control), were selected for the income supplementation experiment. Elderly residents of Valladolid were provided the equivalent of an additional $67 per month, a 44% increase in average household income. We designed a survey given to residents of both cities before and 6 mo after the income supplement about their health and other aspects of overall well-being. Both baseline and follow-up surveys collect self-reported data on health, physical functioning, and biomarkers. Anthropometric measurements for every age-eligible respondent, including height, weight, and waist circumference, were collected. We also collected lung capacity, grip strength, a series of balance tests, and a timed walk. Our results show significant health benefits associated with the additional income. Relative to the control site, there was a statistically significant improvement in lung function and an improvement in memory. These improvements are equivalent to a reduction in age of 5-10 y. Residents used their extra income to go to the doctor, buy their medications, and alleviate their hunger. The fear that this extra income could be undone by reduced transfers from other family members or unwise expenditures by the poor elderly appears to be unfounded.

Preparedness of Americans for the Affordable Care Act.

This paper investigates whether individuals are sufficiently informed to make reasonable choices in the health insurance exchanges established by the Affordable Care Act (ACA). We document knowledge of health reform, health insurance literacy, and expected changes in healthcare using a nationally representative survey of the US population in the 5 wk before the introduction of the exchanges, with special attention to subgroups most likely to be affected by the ACA. Results suggest that a substantial share of the population is unprepared to navigate the new exchanges. One-half of the respondents did not know about the exchanges, and 42% could not correctly describe a deductible. Those earning 100-250% of federal poverty level (FPL) correctly answered, on average, 4 out of 11 questions about health reform and 4.6 out of 7 questions about health insurance. This compares with 6.1 and 5.9 correct answers, respectively, for those in the top income category (400% of FPL or more). Even after controlling for potential confounders, a low-income person is 31% less likely to score above the median on ACA knowledge questions, and 54% less likely to score above the median on health insurance knowledge than a person in the top income category. Uninsured respondents scored lower on health insurance knowledge, but their knowledge of ACA is similar to the overall population. We propose that simplified options, decision aids, and health insurance product design to address the limited understanding of health insurance contracts will be crucial for ACA's success.

Use of Internet panels to conduct surveys.

The use of Internet panels to collect survey data is increasing because it is cost-effective, enables access to large and diverse samples quickly, takes less time than traditional methods to obtain data for analysis, and the standardization of the data collection process makes studies easy to replicate. A variety of probability-based panels have been created, including Telepanel/CentERpanel, Knowledge Networks (now GFK KnowledgePanel), the American Life Panel, the Longitudinal Internet Studies for the Social Sciences panel, and the Understanding America Study panel. Despite the advantage of having a known denominator (sampling frame), the probability-based Internet panels often have low recruitment participation rates, and some have argued that there is little practical difference between opting out of a probability sample and opting into a nonprobability (convenience) Internet panel. This article provides an overview of both probability-based and convenience panels, discussing potential benefits and cautions for each method, and summarizing the approaches used to weight panel respondents in order to better represent the underlying population. Challenges of using Internet panel data are discussed, including false answers, careless responses, giving the same answer repeatedly, getting multiple surveys from the same respondent, and panelists being members of multiple panels. More is to be learned about Internet panels generally and about Web-based data collection, as well as how to evaluate data collected using mobile devices and social-media platforms.

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.

A health production model with endogenous retirement.

We formulate a stylized structural model of health, wealth accumulation and retirement decisions building on the human capital framework of health and derive analytic solutions for the time paths of consumption, health, health investment, savings and retirement. We argue that the literature has been unnecessarily restrictive in assuming that health is always at the 'optimal' health level. Exploring the properties of corner solutions, we find that advances in population health decrease the retirement age, whereas at the same time, individuals retire when their health has deteriorated. This potentially explains why retirees point to deteriorating health as an important reason for early retirement, whereas retirement ages have continued to fall in the developed world, despite continued improvements in population health and mortality. In our model, workers with higher human capital invest more in health and, because they stay healthier, retire later than those with lower human capital whose health deteriorates faster.

Role of Parents' Perceived Risk and Responsibility in Deciding on Children's COVID-19 Vaccination.

OBJECTIVES: We examined associations between parents' reports for whether their children had been vaccinated against coronavirus disease 2019 (COVID-19) and parents' perceptions of the vaccine's long-term risk, as well as their own sense of responsibility on deciding to vaccinate or not vaccinate their children. METHODS: During the period when the Omicron variant was dominant (February-March 2022), we surveyed parents from a nationally representative, probability-based Internet panel about vaccination of their school-aged children, perceptions that the vaccine's long-term risk exceeds risks without vaccination (henceforth: comparative long-term risk), their tendency to feel more responsible if their child became sick from vaccination than when unvaccinated (henceforth: anticipated responsibility), and their own vaccination status. We used multivariate analyses to assess associations of children's COVID-19 vaccination with parental comparative long-term risk perceptions, anticipated responsibility, parents' vaccination status, and demographics. RESULTS: Among 1715 parent respondents (71% of eligible), 45% perceived vaccine-related comparative long-term risk and 18% perceived greater anticipated responsibility from vaccination than no vaccination. After accounting for parental vaccination, parents who were more concerned about comparative long-term risk and who reported greater anticipated responsibility were 6% (95% confidence interval, -0.09 to -0.03; P < .001) and 15% (95% confidence interval, -0.19 to -0.11; P < .001) less likely to have vaccinated their children, respectively. Findings were driven by vaccinated parents. CONCLUSIONS: Parents' perceptions of the COVID-19 vaccine's long-term comparative risk and their greater anticipated responsibility for children getting sick if vaccinated (versus not) were associated with lower vaccine uptake among children of vaccinated parents.

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.

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.

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.

Behind closed doors: Protective social behavior during the COVID-19 pandemic.

The success of personal non-pharmaceutical interventions as a public health strategy requires a high level of compliance from individuals in private social settings. Strategies to increase compliance in these hard-to-reach settings depend upon a comprehensive understanding of the patterns and predictors of protective social behavior. Social cognitive models of protective behavior emphasize the contribution of individual-level factors while social-ecological models emphasize the contribution of environmental factors. This study draws on 28 waves of survey data from the Understanding Coronavirus in America survey to measure patterns of adherence to two protective social behaviors-private social-distancing behavior and private masking behavior-during the COVID-19 pandemic and to assess the role individual and environmental factors play in predicting adherence. Results show that patterns of adherence fall into three categories marked by high, moderate, and low levels of adherence, with just under half of respondents exhibiting a high level of adherence. Health beliefs emerge as the single strongest predictor of adherence. All other environmental and individual-level predictors have relatively poor predictive power or primarily indirect effects.

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.

Born to be wild: Second-to-fourth digit length ratio and risk preferences.

The second-to-fourth digit length ratio of an individual's hand (digit ratio) is a putative biomarker for prenatal exposure to testosterone. We examine the hypothesized negative association between the digit ratio and the preference for risk taking within a large U.S. population survey. Our statistical framework provides a cardinal proxy for the true digit ratio based on ordinal digit ratio measurements and accounts for measurement error under the assumptions of Gaussianity and time-invariant true digit ratios. Our empirical findings support the hypothesis and suggest a meaningful biological basis for risk preferences.