Exploring Changes in Caregiver Burden and Caregiving Intensity due to COVID-19

This study explored self-reported changes in caregiving intensity (CI) and caregiver burden (CB) among informal caregivers due to the COVID-19 pandemic overall and by gender. Informal caregivers for someone age 50+ completed a survey via Amazon’s MTurk in June 2020. Participants reported changes in CI and CB due to COVID-19 and provided demographic information. Multinomial logistic regression models assessed changes in CI and CB attributed to the COVID-19 pandemic overall and by gender. The sample (n = 835) was 68.5% male and had an average age of 34 years (SD 9.8); 55.7% had increased CI, and 53.1% had increased CB attributed to the pandemic. Increased CB due to COVID-19 was associated with increased CI (OR 5.67, 95% CI 3.92–8.00). Male caregivers with decreased CI due to COVID-19 were nearly seven times as likely as those with no change in CI to have reduced CB due to COVID-19 (OR 6.91, 95% CI 3.29–14.52). Women with decreased CI due to COVID-19 were over eight times as likely to have reduced CB due to COVID (OR 8.30, 95% CI 2.66–25.91). Results indicate that many caregivers experienced increases in CI and CB since the start of the COVID-19 pandemic, and that these changes are complex and vary by gender

Rural-Urban Differences in Caregiver Burden Due to the COVID-19 Pandemic among a National Sample of Informal Caregivers

The objective of this exploratory study was to explore potential associations between changes to caregiver burden (CB) due to the COVID-19 pandemic and rural-urban status using a nationally representative sample of 761 informal caregivers. Tertiles of two measures of rural-urban status were used: Rural-Urban Commuting Areas (RUCAs) and population density. Bivariate and multivariable binary and ordinal logistic regression were used to asses study objectives. Using RUCAs, rural informal caregivers were more than twice as likely as urban informal caregivers to report a substantial increase in CB due to COVID-19 (OR 2.27, 95% CI [1.28–4.02]). Similar results were observed for population density tertiles (OR 2.20, 95% CI [1.22–3.96]). Having a COVID-19 diagnosis was also significantly associated with increased CB. Understanding and addressing the root causes of rural-urban disparities in CB among informal caregivers is critical to improving caregiver health and maintaining this critical component of the healthcare system

Self-reported changes in physical activity, sedentary behavior, and screen time among informal caregivers during the COVID-19 pandemic

Background: Informal caregivers providing unpaid assistance may be vulnerable to changes in health behaviors due to modifications in caregiving during the COVID-19 pandemic. Therefore, this cross-sectional study explored self-reported changes in physical activity (PA), sedentary behavior, and screen time among informal caregivers providing care for older adults aged 50+ during the pandemic. Methods: Study participants were recruited via Amazon’s Mechanical Turk and reported their perceived changes (increased a lot, increased a little, remained the same, decreased a little, decreased a lot) in moderate-intensity PA (MPA), vigorous-intensity PA (VPA), sedentary behavior, and screen time (weekday and weekend) during the pandemic. For analytic purposes, response categories were categorized into three-level ordinal variables—increased (increased a lot, increased a little), no change (remained the same), decreased (decreased a little, decreased a lot). Multinomial logistic regression models assessed the likelihood of changes (vs. no change) in MPA, VPA, sedentary behavior, and screen time (weekday, weekend) based on caregiving and demographic characteristics. Results: In total, 2574 individuals accessed the study link, 464 of whom did not meet eligibility requirements. In addition, people who completed 80% or less of the survey (n = 1171) and/or duplicate IP addresse (n = 104) were excluded, resulting in an analytic sample of n = 835. The sample was 69% male, had a mean age of 34 (SD = 9.7), and 48% reported increased VPA, while 55% reported increased MPA. The majority also reported increased sedentary behavior, as well as increased screen time. Respondents living with their care recipient were more likely to report increased weekday screen time (Odds Ratio [OR] = 1.55, 95% CI 1.11–2.16) and sedentary behavior (OR = 1.80, 95% CI 1.28–2.53) than respondents not living with the care recipient. Those living with their care recipient were also more likely to reported increased MPA (OR = 1.64, 95% CI 1.16–2.32), and VPA (OR = 1.53, 95% CI 1.09–2.15), but also more likely to report a decrease in VPA (OR = 1.75, 95% CI 1.14–2.70). Conclusion: The majority of respondents reported that their MPA, VPA PA, sedentary behavior, and screen time had changed during the pandemic. Living with the care recipient was associated with both positive and negative changes in behavior. Future research can explore factors associated with these reported changes in behavior

Keep Your Stats in the Cloud! Evaluating the Use of Google Sheets to Teach Quantitative Methods

Teaching quantitative methods at the undergraduate level is a difficult yet rewarding endeavor due to the challenges instructors face in presenting the material. One way to bolster student learning is through the use of statistical software packages. Google Sheets is a cloud-based spreadsheet program capable of many basic statistical procedures, which has yet to be evaluated for use in quantitative methods courses. This article contains pros and cons to using Google Sheets in the classroom and provides an evaluation of student attitudes toward using Google Sheets in an introductory quantitative methods class. The results suggest favorable student attitudes toward Google Sheets and which attitudes toward Google Sheets show a positive relationship with quantitative self-efficacy. Thus, based on the positive student attitudes and the unique features of Google Sheets, it is a viable program to use in introductory methods classes. However, due to limited functionality, Google Sheets may not be useful for more advanced courses. Future research may want to evaluate the use of third-party Google Sheets applications, which can increase functionality, and the use of Google Sheets in online classes

Optical Coherence Tomography (OCT) for examination of artworks

Chapter in the book: Bastidas D., Cano E. (eds) Advanced Characterization Techniques, Diagnostic Tools and Evaluation Methods in Heritage Science. Springer, Cham, 2018, pp 49-59 , doi: 10.1007/978-3-319-75316-4, Authors’version after embargo periodOptical coherence tomography is a fast, non-invasive technique of structural analysis utilising near-infrared radiation. Examples of using OCT, for obtaining cross-sectional images of objects of craftsmanship and an easel painting have been shown. Issues regarding the technique of execution and destruction phenomena were resolved non-invasively. In some cases, the secondary alterations can be identified and localised within the object’s structure which helps in authentication of the artwork

Validating the Psychosocial Functioning during COVID-19 Questionnaire among a Sample of Informal Caregivers

The COVID-19 pandemic has had a dramatic impact on global economies and societies. Although social distancing policies are needed to contain the spread and impact of COVID-19, they also impose a psychological and economic burden on people who are already experiencing increased distress such as caregivers. Yet, few measures have been developed and validated to measure the psychosocial impact of COVID-19. Utilizing item response theory (IRT), the purpose of this study was to develop and psychometrically validate a measure of psychosocial functioning—the Psychosocial Functioning during COVID-19 (PFC-19) Questionnaire—to assess changes in social interaction, mental health, health behavior, and global functioning among a sample of informal caregivers during the COVID-19 pandemic. The analytic sample (n = 733) was recruited from Amazon Mechanic Turk (MTurk) (69% male, 55% white). Results suggest a two-factor measure, assessing global functioning (14 items) and affective response (8 items), with strong evidence for reliability, validity, and dimensionality. Future research should replicate this factor structure in other samples

Paternal occupation and delirium risk in older adults: a potential marker of early-life exposures

BACKGROUND AND OBJECTIVES: Delirium is a common disorder among older adults following hospitalization or major surgery. Whereas many studies examine the risk of proximate exposures and comorbidities, little is known about pathways linking childhood exposures to later-life delirium. In this study, we explored the association between paternal occupation and delirium risk. RESEARCH DESIGN AND METHODS: A prospective observational cohort study of 528 older adults undergoing elective surgery at two academic medical centers. Paternal occupation group (white collar vs. blue collar) served as our independent variable. Delirium incidence was assessed using the Confusion Assessment Method (CAM) supplemented by medical chart review. Delirium severity was measured using the peak CAM-Severity score (CAM-S Peak), the highest value of CAM-S observed throughout the hospital stay. RESULTS: Blue-collar paternal occupation was significantly associated with a higher rate of incident delirium (91/234, 39%) compared with white-collar paternal occupation (84/294, 29%), adjusted odds ratio OR (95% confidence interval [CI]) = 1.6 (1.1, 2.3). All analyses were adjusted for participant age, race, gender, and Charlson Comorbidity Index. Blue-collar paternal occupation was also associated with greater delirium severity, with a mean score (SD) of 4.4 (3.3), compared with white-collar paternal occupation with a mean score (SD) of 3.5 (2.8). Among participants reporting blue-collar paternal occupation, we observed an adjusted mean difference of 0.86 (95% CI = 0.4, 1.4) additional severity units. DISCUSSION AND IMPLICATIONS: Blue-collar paternal occupation is associated with greater delirium incidence and severity, after adjustment for covariates. These findings support the application of a life-course framework to evaluate the risk of later-life delirium and delirium severity. Our results also demonstrate the importance of considering childhood exposures, which may be consequential even decades later.2019-AARFD-644816 - Alzheimer’s AssociationPublished versio