R-2: Time Use Among People with Disabilities
Methods, Sample, Design, Measures, Intervention, Data Analysis
This project relies on data from the ATUS. Beginning in 2008, ATUS data was linked to the Current Population Survey (CPS), allowing investigations of respondents who report a disability on the CPS. In 2009, ATUS included 13,133 respondents of whom 1,577 identified themselves as disabled (12.0%). For this project, we will use data from the 2009 and 2010 datasets for an aggregated sample size of more than 3,000 people with disabilities. This size of sample will allow us to examine many subpopulations of people with disabilities and address the stated project hypotheses.
Data Collection and Measurement
This project uses data from the ATUS, a nationally representative survey that collects information for estimates of “how, where and with whom Americans spend their time” using a 24 hour recall of activities. Data collection methods are well developed in the time use field and studies of the 24-hour recall validity suggest a high degree of correspondence between recall and actual activity engagement. Disability, as measured by the CPS disability items, includes impairment type, self-care and community access limitations.
While it is possible to collect data on satisfaction with activity, this variable is not included in the ATUS dataset, which is an important study limitation. Therefore, we will be able to show important differences in time use, but not how individuals feel about those differences. These limitations notwithstanding, time use may be a reasonable metric for examining community living differences not only between people with and without disabilities but also between subpopulations of people with disabilities, as evidenced by one study that has examined the time use patterns of women with rheumatoid arthritis. The ATUS dataset includes where activities take place (e.g., home or yard, workplace, store/mall, place of worship, restaurant, bank, health club, etc.) and with whom the respondent participates (e.g., family, friends, etc.). Hence, we will compare sub-populations of people with disabilities to describe factors associated with time spent at home alone versus participating in community-based activities.
Independent variables will include employment status, availability of transportation and metropolitan/non-metropolitan. Dependent variables will include activity location (e.g., home, workplace, bar, bus, etc.), whether others are present (e.g., alone, household members, parents, friends, co-workers), time spent in community-based activities, time spent home alone.
To set the stage for our analysis, we use the population-based estimate of the proportions of people who have significant housing and transportation access problems, from R-1 of the RRTC/CL. This information will be helpful in interpreting differences in how people spend their time and the extent to which their activities involve community participation. The American Time Use data and dictionaries are publically available from the Bureau of Labor.
Data will be imported into and analyzed using SPSS 19.0. Descriptive statistics for all variables will be computed to examine the data for uni- and multivariate normality. When data approximate normality, parametric inferential statistics for detecting sub-population differences and associations will be used (e.g., t-tests, multiple regression) and where normality assumptions are clearly violated, we will use non-parametric statistics (e.g., Mann-Whitney).