Times Have Changed: Using a Pictorial Smartphone App to Collect Time–Use Data in Rural Zambia

Abstract

One challenge of collecting socioeconomic data, such as data on time-use, is recall biases. While time-use researchers have continuously developed new methods to make data collection more accurate and easy, these methods are difficult to use in developing countries, where study participants may have low literacy levels and no clock-based concepts of time. To contribute to the closing of this research gap, we developed a picture-based smartphone app called Time-Tracker that allows data recording in real time to avoid recall biases. We pilot tested the app in rural Zambia, collecting 2,790 data days. In this article, we compare the data recorded with the app to data collected with 24-hours recall questions. The results confirm the literature on recall biases, suggesting that using the app leads to valid results. We conclude that smartphone apps using visual tools provide new opportunities for researchers collecting socioeconomic data in developing countries.

Of Trackers and Tractors. Using a Smartphone App and Compositional Data Analysis to Explore the Link Between Mechanization and Intra-Household Allocation of Time in Zambia

“…As outlined above, time-use is difficult to measure, especially in developing countries. To address this challenge, a smartphone application called Timetracker was used, which is based on visual tools and allows real-time recording of 88 time-use categories (see figure 1; Daum et al, 2019). The app allows to record up to three activities at a time but the focus here is on primary activities.…”

“…1 Notwithstanding some anecdotal evidence, the effects of mechanization on intra-household time allocation have not been examined, While the need to carefully monitor time-use effects of new technologies and policies is widely acknowledged, studying such effects empirically has been hampered by a lack of suitable data collection methods. Post-harvest questionnaires and 24-hour recall questions are prone to recall bias; time-use diaries require literacy and a familiarity with clock-based concepts of time; direct observations are expensive and associated with observer bias (Arthi et al, 2018;Daum et al, 2019). In this study, therefore, a smartphone application called Timetracker is used, which is based on visual tools.…”

Using smartphone app collected data to explore the link between mechanization and intra-household allocation of time in Zambia

“…This way of recording time use is an important feature of the app, as it enables continuous tracking of all activities that a household member carries out during the day (Daum et al 2018). As shown by Daum et al (2019) the Timetracker improves data quality as compared to conventional recall-based data collection. The Timetracker can, with a careful introduction, be used by very old, very young, and uneducated people as well as respondents without prior exposure to phones and low literacy (Daum et al 2019).…”

“…The collection of time-use data exemplifies the challenges faced by researchers. Typically used methods such as post-harvest questionnaires and 24-h recall questions are prone to recall bias; in contrast, time-use diaries are more accurate but require literacy and familiarity with clock-based concepts of time; and direct observations are expensive and associated with observer bias (Arthi et al 2018;Daum et al 2019).…”

“…For this, a smartphone application called Timetracker was developed that allows the self-recording of data by respondents. The Timetracker is based on visual tools to ensure that illiterate respondents and children can record data, and allows real-time recording of data to reduce recall bias (Daum et al 2019).…”