Time-use Surveys Research Articles

Who Has the Time? Community College Students’ Time-Use Response to Financial Incentives

We evaluate the effect of performance-based scholarship programs for postsecondary students on student time use and effort and whether these effects are different for students we hypothesize may be more or less responsive to incentives. To do so, we administered a time-use survey as part of a randomized experiment in which community college students in New York City were randomly assigned to be eligible for a performance-based scholarship or to a control group that was only eligible for the standard financial aid. This paper contributes to the literature by attempting to get inside the “black box” of how students respond to a monetary incentive to improve their educational attainment. We find that students eligible for a scholarship devoted more time to educational activities, increased the quality of effort toward and engagement with their studies, and allocated less time to leisure. Additional analyses suggest that students who were plausibly more myopic—place less weight on future benefits—were more responsive to the incentives, but we find no evidence that students who are arguably more time constrained were less responsive to the incentives.

Italian Families in the 21st Century: Gender Gaps in Time Use and their Evolution

We provide novel estimates of gender differences in the allocation of time by Italian adults and document their trends over the span 2002-2014, pooling three time-use surveys run by the Italian National Institute of Statistics (ISTAT). The positive gap (females-males) in time devoted to Household work and the negative gap in Market work and Leisure are found to have narrowed over the observed period, mainly due to changes in women’s time allocation, while the positive gap in time devoted to Child care remained substantially constant. In 2014, the sharing of family duties appears still heavily unbalanced even when we look at the sub-sample of full-time working parents. Full-time working mothers devote to Market work about 4 hours per week less than their partners, but they devote 14 hours per week more to Household work and 3 hours and a half more to Basic child care. This translates in 13 hours per week more total (paid and unpaid) work and 11 hours per week less Leisure. On the positive side, the gender gap in time devoted to Quality child care exhibits a reversed sign in 2014. The change is driven by weekend days, when partners of full-time working mothers become the main provider of this type of care.

A high-temporal resolution residential building occupancy model to generate high-temporal resolution heating load profiles of occupancy-integrated archetypes

A strong correlation exists between occupant behaviour and space heating energy use. In particular, the occupancy status (e.g., daytime absence) is known to have a significant influence on residential heating load profiles, as well as on cumulative heating energy consumption. In the literature, many occupancy models have been utilised to predict occupancy profiles of individual dwellings as part of the larger residential building stock. However, none of the existing models consider diversity associated with occupancy-integrated archetypes to generate high-temporal resolution heating load profiles. The current paper uses Time Use Survey (TUS) data to develop a high-temporal resolution residential building occupancy model. The key feature of the proposed model, implemented using MATLAB, is the ability to generate stochastic occupancy time-series data for national population subgroups characterised by specific occupancy profiles. It is shown that the results are capable of closely approximating data available from TUS. The developed model can be applied to improve the quality of modelled high-temporal resolution heating load profiles for generic building stock characterised by population subgroups represented by different occupancy-integrated archetypes. A case study is performed on a building stock sample located in London, UK. The developed occupancy model has been implemented in MATLAB and is available for download.

Room-level occupancy simulation model for private households

This work presents a novel occupancy simulation model for residential buildings. The main contribution is that occupancy is simulated at room level, as opposed to more course spatial resolutions in previous studies. The model is based on a time-use survey conducted in Denmark including several thousand households. It is formulated as an inhomogeneous hidden Markov model. The simulated occupancy profiles take into account the variables week day, time of day, occupant age and family type. Preliminary results show that they are in good agreement with the measurements.

Where You at? Using GPS Locations in an Electronic Time Use Diary Study to Derive Functional Locations

Smartphones enable passive collection of sensor data alongside survey participation. Location data add context to people’s reports about their time use. In addition, linking global positioning system data to self-reported time use surveys (TUSs) can be valuable for understanding how people spend their time. This article investigates whether and how passive collection of geographical locations (coordinates) proves useful for deriving respondents’ functional locations. Participants of the ongoing Children of Immigrants Longitudinal Survey in the Netherlands were invited to participate in a TUS administered with a smartphone app that also unobtrusively tracked respondents’ locations. Respondents reported their activities per 10-min interval in a smartphone diary app ( n = 1,339) and shared their geographical location data ( n = 1,264). The correspondence between the functional locations derived from the time use data and those derived from the geographical location data was assessed by calculating the percentage of intervals in which both measures are similar. Overall, results show that home locations can be automatically assigned reliably but that respondent information is required to reliably assign work or school locations. In addition, location tracking data contain many measurement errors, making it difficult to record valid locations. Multilevel models show that the variability in correct classifications is intrapersonal and largely predicted by phone type, which determines location measurement frequency.

A Stochastic Model for Residential User Activity Simulation

User activities is an important input to energy modelling, simulation and performance studies of residential buildings. However, it is often difficult to obtain detailed data on user activities and related energy consumption data. This paper presents a stochastic model based on Markov chain to simulate user activities of the households with one or more family members, and formalizes the simulation processes under different conditions. A data generator is implemented to create fine-grained activity sequences that require only a small sample of time-use survey data as a seed. This paper evaluates the data generator by comparing the generated synthetic data with real data, and comparing other related work. The results show the effectiveness of the proposed modelling approach and the efficiency of generating realistic residential user activities.

Unpaid Care Work in the Republic of Belarus: Structure Analysis and Methods of Macroeconomic Assessment

Achieving gender equality is important for sustainable socio-economic development of the country. The significance of this problem is also reflected in the Sustainable Development Goals, namely, achieve gender equality (Goal 5). While the Republic of Belarus pays great attention to solving gender problems, inequality in the labor market is persisting. In particular, gender differences in the distribution of paid and care-related work still exist. Therefore, it is important to study and identify the differences in the time budget of employed men and women in the Republic of Belarus, with assessing the unpaid household services and their recording in national accounts.
 The article is devoted to the analysis of the time use structure in the Republic of Belarus, with determining the differences in the distribution of paid and unpaid work between men and women and assessing the housework that is “invisible” for a market economy. The study is based on the methodological approaches of the System of National Accounts and the updated international standards on labor statistics. Data from time-use surveys and sample household surveys on employment issues are used as the information base of our study. 
 It is shown that the total daily working day of women lasts 68 minutes longer than the working day of men, which is explained by the fact that women spend twice longer time on housework than men. The unpaid work (services produced inside households) is valuated by the cost approach using the methods of full, specialized replacement and opportunity costs.
 The estimated scopes of the household work “invisible” for a market economy range from 12.6% to 20.5% of Gross Domestic Products in 2018. Future studies should focus on the assessment of the women’s contribution in the national economy, with inclusion of their housework and the household output for own final consumption in the traditional macroeconomic indicators.

Modelling household electricity load profiles based on Danish time-use survey data

The relationship among occupants’ presence, activities and appliance use is essential for households’ energy use. In the present work, we aimed to link occupants’ energy-related activities to electricity demand, in order to obtain a representative daily electricity load profile for Danish households using Danish time-use survey (DTUS) data. The approach was to combine appliance ownership and power ratings with occupant activities from the DTUS. Two modelling approaches were implemented: in the first approach, the occupant activities profiles from the DTUS were used directly to determine activities at 10-minute intervals. In the second approach, the probabilities of starting time and duration of the occupant activities were used to determine activities. In both approaches, appliance use was assigned to the energy-related activities. The set of appliances used in each activity was determined from a national database of appliance ownership, and the appliances’ power was calibrated using information from apartments in Copenhagen, Denmark. The modelled daily electricity load profile was compared with three measured datasets of varying sizes and from different parts of Denmark. Both approaches captured important qualitative characteristics of the measured load profiles. However, the first approach used a more simple method and resulted in smaller errors than the second approach.

Determinants of Intergenerational Family Solidarity during the Great Recession: the Spanish Case.

In the context of an economic crisis that has affected countries in Southern Europe especially and that has called into question the public pillar of the intergenerational contract, i.e. pensions, literature has shown an increasing interest in analyzing the other intergenerational pillar, which is largely based on family solidarity and which has been insufficiently explored for the Spanish case. Therefore, based on official data provided by the Time Use Survey (TUS) and the Household Budget Survey (HBS), an effort has been made to identify, through multivariate models, the individual factors that determined certain expressions of family solidarity and their participation and intensity of time and money transfers among family members in one of the most critical moments of this crisis in Spain (2009/2010). The results question the idea that the unemployed and the retired have been net recipients during the crisis, revealing that it is insufficient to consider only a single manifestation of solidarity, the financial one, when accounting for the wide range of support and transfers that circulate among family members.

Social and Solitary Exercise among the Unemployed and Out of the Labor Force in the United States: Estimates by Gender and Partnership Status

Abstract Introduction: The negative effects of unemployment are significant, and the potential for increased morbidity and mortality is a major public health challenge. Negative effects may be partially attributable to health behavior change and loss of social ties. Exercise has positive physical and mental health benefits and could help buffer such negative effects. This study examines whether time in social and solitary exercise varies by unemployment and out of the labor force (OOLF) status because exercise, especially social exercise, provides health benefits. Methods: Gender-stratified ordinary least squares models are estimated using data from the nationally representative 2003-2016 American Time Use Surveys to test how own and partner employment status are associated with total time in exercise, exercise alone, with children, with a partner, and with others. Results: Unemployed and OOLF men spend significantly more time in exercise alone (3-9 minutes, p<.05) and with others (about 13 minutes, p<.001) compared to employed men. Unemployed women spend significantly more time in exercise with others (6 minutes, p<.05), and OOLF women in all types of social exercise (1-9 minutes, p<.05), compared to employed women. Conclusions: Unemployed and OOLF individuals engage in more social exercise, which could be leveraged to help buffer loss of social ties and improve health. Exercise-related interventions may help reduce negative health consequences of unemployment. Keywords: physical activity, employment, American Time Use Survey

Time Matters: The Carbon Footprint of Everyday Activities in Austria

Mitigating climate change to achieve the goal of staying below 2 °C of warming requires urgent reductions of emissions. Demand-side measures mostly focus on the footprints of consumption. Analysing time use can add to understand the carbon implications of everyday life and the potentials and limitations for decarbonising consumption better.We investigate the carbon footprints of everyday activities in Austria. We linked data from the Austrian Time-use Survey and the Austrian Household Budget Survey with the Eora-MRIO for 2009–2010 in order to estimate the household carbon footprints of all time-use activities. We introduce a functional time-use perspective differentiating personal, committed, contracted and free time to investigate the average carbon intensity of activities per hour, for an average day and for the average woman and man. We find that personal time is relatively low-carbon, while household as well as leisure activities show large variation in terms of CO2e footprint/h. The traditional gendered division of labour shapes the time-use patterns of women and men, with implications for their carbon footprints.Further research analysing differences in household size, income, location and availability of infrastructure in their relation to time use is crucial to be able to assess possible pathways towards low carbon everyday life.

The Effects of Working While in School: Evidence from Uruguayan Lotteries

We provide the first estimates of the effects of working while in school that use controlled random variation in job offers. We leverage a Uruguayan program offering 9-to-12-month part-time employment in state-owned companies by lottery to enrolled students. Using social security data matched to the universe of over 120,000 applicants, we estimate a 9% increase in earnings over the four post-program years for youth completing a program job. We find large positive effects on school enrollment during the program year, consistent with the conditionality of the program and smaller effects in the post-program years. Our time-use survey indicates that students substitute leisure and household chores with work, without significant reductions in studying time. Finally, a decomposition of the earnings effect shows that accumulation of work experience can explain the majority of the increase in earnings.

Activity travel of population segments grouped by daily time-use: GPS tracking in Halifax, Canada

This paper examines the weekday activity patterns and associated travel behaviour of urban residents grouped by similarity of their daily time-use profiles. We analyze the two-day in-home and out-of-home activity of respondents to the large STAR time-use and travel survey. The efficient Fuzzy C-Means (FCM) clustering algorithm yields 12 clusters of activity days grouped by homogeneous activity patterns. Six clusters are characterized as out-of-home workers, five as non-workers, and one as students. Time-stamped GPS-tracking of activity is employed to map out-of-home locations of individuals at key times in the day, which reveals considerable variation between the groups in their locational and temporal preferences. Worker groups cluster in employment areas, with 9-5 workers focused downtown and earlier-shift workers in suburban business parks. Non-workers are more dispersed, and more clustered in retail/service areas. Time-diary data also show clear variations in typical trip-tour behaviour, relating both to trip purposes and to tour complexity: non-worker groups take more tours, on average, but fewer complex tours.

Doing a Time Use Survey on Smartphones Only: What Factors Predict Nonresponse at Different Stages of the Survey Process?

The increasing use of smartphones opens up opportunities for novel ways of survey data collection, but also poses new challenges. Collecting more and different types of data means that studies can become increasingly intrusive. We risk over-asking participants, leading to nonresponse. This study documents nonresponse and nonresponse bias in a smartphone-only version of the Dutch Time Use Survey (TUS). Respondents from the Dutch LISS panel were asked to perform five sets of tasks to complete the whole TUS: 1) accept an invitation to participate in the study and install an app, 2) fill out a questionnaire on the web, 3) participate in the smartphone time use diary on their smartphone, 4) answer pop-up questions and 5) give permission to record sensor data (GPS locations and call data). Results show that 42.9% of invited panel members responded positively to the invitation to participate in a smartphone survey. However, only 28.9% of these willing panel members completed all stages of the study. Predictors of nonresponse are somewhat different at every stage. In addition, respondents who complete all smartphone tasks are different from groups who do not participate at some or any stage of the study. By using data collected in previous waves we show that nonresponse leads to nonresponse bias in estimates of time use. We conclude by discussing implications for using smartphone apps in survey research.

Estimating age-mixing patterns relevant for the transmission of airborne infections

IntroductionAge-mixing patterns can have substantial effects on infectious disease dynamics and intervention effects. Data on close contacts (people spoken to and/or touched) are often used to estimate age-mixing. These are not the only relevant contacts for airborne infections such as tuberculosis, where transmission can occur between anybody ‘sharing air’ indoors. Directly collecting data on age-mixing patterns between casual contacts (shared indoor space, but not ‘close’) is difficult however. We demonstrate a method for indirectly estimating age-mixing patterns between casual indoor contacts from social contact data. MethodsWe estimated age-mixing patterns between close, casual, and all contacts using data from a social contact survey in South Africa. The age distribution of casual contacts in different types of location was estimated from the reported time spent in the location type by respondents in each age group. ResultsPatterns of age-mixing calculated from contact numbers were similar between close and all contacts, however patterns of age-mixing calculated from contact time were more age-assortative in all contacts than in close contacts. There was also more variation by age group in total numbers of casual and all contacts, than in total numbers of close contacts. Estimates were robust to sensitivity analyses. ConclusionsPatterns of age-mixing can be estimated for all contacts using data that can be easily collected as part of social contact surveys or time-use surveys, and may differ from patterns between close contacts.

Abstract P322: Physical Activity Patterns Among Indian Adolescents: Independent and Joint Associations of Gender and Socio-Economic Status

Introduction: The increasing global burden of CVD mortality is primarily attributable to the rising number of deaths in developing countries; India alone accounted for 15% of global CVD deaths in 2016. Little is known about patterns and predictors of physical activity (PA), a key modifiable risk factor for CVD, among Indian adolescents. Existing research has focused on play- and travel-related PA, which do not fully capture adolescent activity, and socio-demographic differences in PA are not well understood. We examined independent and joint associations of gender and socio-economic status (SES) with PA across multiple activity domains. Hypothesis: We assessed the hypotheses that 1) the types of PA in which adolescents engage will differ by gender and SES, and 2) gender differences in PA will vary by SES. Methods: We recruited 395 adolescents, ages 13-16, from six schools in Vijayapura, India. We classified public school students as low SES and private school students as high SES. We measured PA using adolescent-reported 24-hour time-use surveys. Activities were categorized into three domains: chores, errands, and jobs; play; and travel. We assigned each activity a metabolic equivalent (MET) value to assess moderate-to-vigorous PA (MVPA). Negative binomial regression modeled the adjusted count of PA minutes per day in each domain, and logistic regression modeled the probability of engaging in ≥60 minutes of MVPA in the prior 24 hours (WHO recommended level for ages 5-17). We assessed additive interaction between gender and SES with the relative excess risk due to interaction (RERI). Results: The proportion of adolescents engaging in ≥60 minutes of MVPA was higher among low SES (79.8% boys, 76.8% girls) than high SES (50.0% boys, 32.3% girls) adolescents. In adjusted models, there were no gender differences in the likelihood of engaging in ≥60 minutes of MVPA. However, girls had twice the PA minutes in chores, errands, and jobs (e(β)=1.98, 95% CI:1.32-2.98), while boys had twice the PA minutes in play (e(β)=2.11, 95% CI:1.23-3.62). Low versus high SES adolescents had higher PA across domains. Additive interaction between gender and SES was present in chores, errands, and jobs: while girls were more active in this domain across SES, gender differences were greater among low SES adolescents (RERI=2.53, 95% CI: 0.31-4.76). Conclusions: A far greater proportion of low SES adolescents engaged in recommended levels of MVPA. While there were no gender differences in the likelihood of engaging in ≥60 minutes of MVPA, girls and boys may accrue different advantages as a result of engaging in substantively different types of PA. Interaction in the chores, errands, and jobs domain suggests that gender hierarchies may emerge in the presence of socio-economic constraints, and lose salience as available resources increase. PA interventions must consider the role of gender- and SES-based facilitators and barriers.

Effectiveness of a volunteer befriending programme for patients with schizophrenia: randomised controlled trial.

Befriending by volunteers has the potential to reduce the frequent social isolation of patients with schizophrenia and thus improve health outcomes. However, trial-based evidence for its effectiveness is limited. To conduct a randomised controlled trial of befriending for patients with schizophrenia or related disorders. Patients were randomised to a befriending programme for 1 year or to receive information about social activities only (trial registration: ISRCTN14021839). Outcomes were assessed masked to allocation at the end of the programme; at 12 months and at a 6-month follow-up. The primary outcome was daily time spent in activities (using the Time Use Survey (TUS)) with intention-to-treat analysis. A total of 124 patients were randomised (63 intervention, 61 active control) and 92 (74%) were followed up at 1 year. In the intervention group, 49 (78%) met a volunteer at least once and 31 (49%) had more than 12 meetings. At 1 year, mean TUS scores were more than three times higher in both groups with no significant difference between them (adjusted difference 8.9, 95% CI -40.7 to 58.5, P = 0.72). There were no significant differences in quality of life, symptoms or self-esteem. However, patients in the intervention group had significantly more social contacts than those in the control group at the end of the 12-month period. This difference held true at the follow-up 6 months later. Although no difference was found on the primary outcome, the findings suggest that befriending may have a lasting effect on increasing social contacts. It may be used more widely to reduce the social isolation of patients with schizophrenia.

More at home, more alone? Youth, digital media and the everyday use of time and space

From a joint temporal and socio-spatial perspective, we examine how young people’s everyday lives integrate with the use of digital media. Conceptually, we complement a standard displacement approach by advancing the role of time-space priorities, time elasticities, and online/offline intersections. We use micro-level data concerning youth aged 15–24 years from the Swedish Time-Use Survey, 2010–2011. Using covariate analysis, we compare heavy, medium, and light digital media users on weekdays and weekends. The results contradict expectations of a homogenous group of ‘digital natives’, also showing that heavy use is still gendered. Heavy users generally spend more time at home, perform more activities alone, and travel less. Heavy use is associated with less time spent on outdoor activity and sports, socializing offline, and watching TV, and more time sleeping at night. Digital media use is highly elastic to available free time on weekdays, but is very differently prioritized on weekends.

Revealing household characteristics using connected home products

Recent technological advances have helped make our homes more intelligent and responsive to our needs. In this context, analyzing data from smart home products to gain insights is becoming increasingly important. This paper proposes an analytical framework to reveal the characteristics of households using event logs from smart door lock systems. The analytical framework uses constraint satisfaction problems to enable streaming event log analysis to solve the problems of overlapping classes and a lack of information concerning the truth class. The proposed method was applied to two datasets: one consisting of door-lock log data from 40 households and the other of time-use survey data from more than 10,000 households in South Korea. The results verify its effectiveness in terms of estimating the number of occupants in a household. The performance of the proposed method was compared with that of a naïve clustering approach in terms of mean squared error.

Time Use, Unemployment, and Well-Being: An Empirical Analysis Using British Time-Use Data

We use nationally representative data from the UK Time-Use Survey 2014/2015 to investigate how a person’s employment status is related to time use and cognitive and affective dimensions of subjective well-being. We find that unemployed persons report substantially lower levels of life satisfaction than employed persons. When looking at specific types of activities, the unemployed enjoy most of the activities they engage in less than the employed. However, the employed consider working to be one of the least enjoyable activities. They also spend a large share of their time at work and with work-related activities, while the unemployed spend more time on leisure and more enjoyable activities instead. When looking at duration-weighted average affective well-being over the entire waking time of the day, our results suggest that the benefit of having to spend less time at work outweighs the negative emotional effect of unemployment during leisure episodes, such that the unemployed experience, on average, more enjoyment during the day than the employed.