All time references are in CEST
Data Collection Using Wearable Devices: Challenges and Opportunities |
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| Session Organisers | Dr Heidi Guyer (RTI International) Professor Florian Keusch (University of Mannheim) Professor Bella Struminskaya (Utrecht University) |
| Time | Tuesday 18 July, 09:00 - 10:30 |
| Room | |
The use of wearable devices, such as fitness trackers, to track human behavior as well as external environmental factors has increased dramatically over the past 20 years. A recent Google Scholar search showed a 10-fold increase in research article citations for “wearables AND adults” between 2005 and 2024. The use of wearable devices for data collection has expanded from use with adults to adolescent and youth populations, and specific at-risk subgroups of the population such as caregivers, clinical populations, military populations, and others. While the field was initially dominated by expensive research-grade devices, the augmented capabilities of consumer-grade devices, accompanied by the lower cost and data accessibility, has allowed for the integration into data collection plans for an expanding field of researchers. Wearables are used to measure physical activity, biorhythms such as pulse, heart rate variability and temperature, sleep and other external factors about the environment. The increase in consumer usage may translate to increased consent and compliance rates for research participation. However, the field continues to grapple with several methodological challenges related to data quality and representation of the data collected. For this session, we invite methodological contributions dealing with various challenges of collecting data from wearable devices, including differences in consent and participation rates by subgroups, scalability of research designs, the integration of additional touch points such as EMAs, accessing data from user- owned devices (BYOD) versus distributed study devices, usability and design features, data harmonization across device makes and models, and measurement differences related to sociodemographic characteristics. With the rapid expansion of wearable devices in survey research, this session will allow researchers to share their findings and lessons learned to date.
Keywords: data collection, wearables, sensors, measurement
Mr Wai Tak Tung (University of Mannheim) - Presenting Author
Measuring the level of physical activity (PA) of the general population accurately is important to guide public health policies. Instead of relying on self-reported measures which are prone to social desirability and recall biases, studies increasingly provide accelerometers to study participants for passively measuring PA. After the raw accelerometer data are collected, researchers have to go through a series of processing steps, such as removing extreme values and aggregating the data into fixed time intervals. A concern in accelerometer studies is identifying non-adherence, i.e., participants taking off the device, resulting in non-wear time. The accurate processing and calculation of non-wear time in the accelerometer data is important to ensure data quality. Although prior research has identified how a subset of processing decisions affect the measurement of non-wear time, there is currently only limited research about how decisions across the entire processing pipeline can affect the estimation of non-wear time in tri-axial accelerometer studies of the general population.
In this paper, I address this research gap by using data from the 2013-2014 accelerometer study conducted in the National Health and Nutrition Examination Survey (NHANES), a probability survey of the United States population aged 3 years or above. Recruited participants were asked to wear an accelerometer device for seven consecutive days on their non-dominant hand. The device recorded acceleration in three dimensions with 80 Hz. I will first compare the estimation of non-wear time based on multiple processing decisions, including choices for outlier detection and lengths of time intervals. Second, I will analyze whether individual-level predictors of non-wear time differ across the different processing decisions, which will shed more light on how potential processing error can impact the understanding of non-adherence in an accelerometer study.
Professor Arie Kapteyn (Center for Economic and Social Research, University of Southern California ) - Presenting Author
Mr Htay-Wah Saw (Michigan Program in Survey and Data Science, University of Michigan-Ann Arbor )
Mr Bas Weerman (Center for Economic and Social Research, University of Southern California )
Publicly available pollution data are mostly regional-level data such as those collected by EPA’s weather stations. Such data are likely to miss substantial differences in individual exposures to pollution, both inside the home, at work, or elsewhere. To address this lack of granularity, we have asked some 900 respondents (balanced across education, race & ethnicity, household income) to the Understanding America Study (UAS) to wear an air quality monitor (Atmotube) continuously for at least one year. The air quality monitor collects pollution and weather data at 1-minute intervals and is Bluetooth enabled so that it communicates with a smartphone app.
In addition, we have conducted monthly surveys of the respondents’ home characteristics (heating and cooling types; cooking stoves, proximity of busy roads) and of their whereabouts in 30-minute episodes during the previous 24 hours (home, work, motor vehicle, other). More recently, we have also asked for consent to link the GPS coordinates recorded by the Atmotube to their survey and air quality data.
By merging in modelled pollution data at the 1km2 level, we are able to disentangle the effects of local air quality and micro-climates such as inside one’s home, at work, or when traveling with a motor vehicle. We presented the premilitary results from pilot data at ESRA 2023. In the presentation we provide descriptive results of how air quality varies by respondents’ location, socio-economic, and housing characteristics. Furthermore, to gain insight into individual exposure to air quality, we will decompose individual pollution exposure into its various components: regional air quality and variation by individuals’ location during the day. We have rich background information on our respondents, including their health and cognitive outcomes, which allows us to analyze how exposure to pollution is associated with these substantive outcomes.
Ms Alena Klenke (University of Oldenburg)
Professor Bettina Langfeldt (University of Kassel)
Ms Maximiliane Reifenscheid (University of Kassel) - Presenting Author
Professor Sebastian Schnettler (University of Oldenburg)
Time use studies traditionally rely on survey-based time diaries. These have consistently shown significant gender disparities in household tasks between parents (Schulz, 2021). However, self-administered time diaries face inherent limitations, including measurement error. Issues such as gendered over- and under-reporting of work and household activities (Bonke, 2005) and difficulties in capturing simultaneous activities (Giménez-Nadal & Molina, 2022), are notable challenges.
Technological advances, such as wearables, provide opportunities to collect more accurate data on task division, daily routines, and household interactions. These devices automatically record activities, offering valuable insights as demonstrated by research in other fields (Fischbach et al., 2010; Shinmoto Torres et al., 2017; Vanhems et al., 2013). Despite this potential, little is known about the acceptance of wearables for studying family life.
Our study investigates the feasibility and acceptance of using wearables in households with young children using a mixed methods approach. The feasibility of measuring time use with wearables in the home environment is evaluated in a laboratory flat used as a practical testing ground. To explore parents' perspectives on using wearables for time use studies, including preferences for device types, acceptable study durations, and concerns about equipping all family members with such devices, we employ focus groups. We then use experimental surveys to assess the prevalence of these aspects in the general population.
Preliminary findings suggest that parents with young children are generally open to participating in research using wearables in the home. However, challenges arise in specific everyday situations where the devices are perceived as intrusive. Furthermore, the willingness to use these devices is influenced by the range of their technical capabilities. The use of wearables in a laboratory flat demonstrated that the use of these devices requires a thorough understanding of the optimal placement of household items.