Exploring daily time-use patterns: ATUS-X data extractor and online diary visualization tool.

Time-use data can often be perceived as inaccessible by non-specialists due to their unique format. This article introduces the ATUS-X diary visualization tool that aims to address the accessibility issue and expand the user base of time-use data by providing users with opportunity to quickly visualize their own subsamples of the American Time Use Survey Data Extractor (ATUS-X). Complementing the ATUS-X, the online tool provides an easy point-and-click interface, making data exploration readily accessible in a visual form. The tool can benefit a wider academic audience, policy-makers, non-academic researchers, and journalists by removing accessibility barriers to time use diaries.

Demographic, health, and economic transitions and the future care burden.

The COVID-19 pandemic has caused millions of infections and deaths worldwide, forced schools to suspend classes, workers to work from home, many to lose their livelihoods, and countless businesses to close. Throughout this crisis, families have had to protect, comfort and care for their children, their elderly and other members. While the pandemic has greatly intensified family care responsibilities for families, unpaid care work has been a primary activity of families even in normal times. This paper estimates the future global need for caregiving, and the burden of that need that typically falls on families, especially women. It takes into account projected demographic shifts, health transitions, and economic changes in order to obtain an aggregate picture of the care need relative to the potential supply of caregiving in low-, middle- and high-income countries. This extensive margin of the future care burden, however, does not capture the weight of that burden unless the quantity and quality of care time per caregiver are taken into account. Adjusting for care time given per caregiver, the paper incorporates data from time-use surveys, illustrating this intensive margin of the care burden in three countries that have very different family and economic contexts-Ghana, Mongolia, and South Korea. Time-use surveys typically do not provide time data for paid care services, so the estimates depend only on the time intensity of family care. With this caveat, the paper estimates that the care need in 2030 would require the equivalent of one-fifth to two-fifths of the paid labor force, assuming 40 weekly workhours. Using the projected 2030 mean wage for care and social service workers to estimate the hypothetical wage bill for these unpaid caregivers if they were paid, we obtain a value equivalent to 16 to 32 percent of GDP in the three countries.

Measuring the "Sandwich": Care for Children and Adults in the American Time Use Survey 2003-2012.

While the economic burden of simultaneously caring for young and old family members is widely recognized, it has yet to be accurately measured. Yet, such assessments are relevant both to public policies providing support to family caregivers and to private insurance markets for long-term care. This descriptive study presents a new method to address this problem: the construction of a crosswalk between time-use diaries and other types of surveys using lists of activities of daily living (ADLs) and instrumental activities of daily living (IADLs) for which assistance is required. Analysis of pooled data from American time use survey 2003-2012 provides some quantitative indicators, but understates the temporal burden of care and fails to distinguish types of care that involve personal interaction from those that do not. A crosswalk of time-use survey categories with the list-based approach typically applied in public health surveys clearly demonstrates the importance of clear definitions and also offers more precise measures. Depending on how sandwich caregiving was defined, the temporal burden for caregiving ranged from 11.2 to 60 h per week, clustering at around 20 h per week for most cases. This result demonstrates the magnitude of sandwich care demands and also underscores the need for improved care survey design. As shown in this study, such efforts should take into account the implications of disaggregating data by gender and age, and definitional variations that characterize existing datasets.