# 6. Discussion

This study reports on a large-scale survey experiment that was implemented for the first time in a lowincome country to provide a comparative assessment of real-time, smartphone-based self-administered time use diaries versus recall-based, interviewer-assisted approaches to time use measurement. The experimental study design, repeated measurements of smartphone- and recall-based data, and the scope of the smartphone app functionality unlock several empirical insights regarding the practical field experience with smartphone-based data collection and the quality of reporting across smartphone and recall-based approaches. The analysis shows that compared to real-time time use data collection using a pictorial smartphone app, the reliance on a recall-based 24-hour diary leads to underestimation of participation in employment and unpaid work; mischaracterizes intra-day variation in time use with policyrelevant implications; fails to capture the true extent of multitasking, particularly among women; and yet, results in overestimation of time devoted to a wide range of activities. The latter is <mark>due to the minimum 15 minute-duration that was used for recording activities the 24-hour recall diary – while over one-third of activities lasted less than 15 minutes in the smartphone arm. The design of the 24-hour recall diary also results in “rounding” of estimated time, which is not a concern in the use of the open-ended smartphone time use diary. The analysis also demonstrates that compared to the smartphone time use diary, the reliance on stylized time use questions with a 7-day recall (as opposed to a 24-hour recall diary) results in an even greater overestimation of time devoted to employment and unpaid work. Ultimately, recall-based time use measurement methods provide an incomplete and misleading representation of men’s and women’s time use outcomes in this study population.</mark> Looking forward, survey practitioners can consider using the existing _TimeTracker_ app and training materials for deployment in alternative contexts. The app illustrations and translations can be updated with ease, and the fixed costs of smartphone procurement can be managed by procuring a limited pool of smartphones that can redeployed throughout the fieldwork. The app pop-ups can also be tailored to collect additional policy-relevant contextual information regarding reported activities, including passive childcare provision, as demonstrated in this study. At the same time, there are key issues that need to be addressed prior to proposing concrete recommendations for scaling up real-time time use data collection in low- and middle-income countries. First, it would be essential to replicate our study in alternative contexts, including with additional recall variants that have emerged in recent literature (Field et al., 2023; McCullough et al., 2023), to verify the external validity of our findings and strengthen the evidence base regarding the utility and requirements of improved approaches to time use measurement. Second, future research should provide guidance on whether the duration of smartphone data collection can be reduced, for example from nine to three full days of reporting, to save on costs without losing the analytical utility of the resulting data. Finally, survey practitioners could benefit from guidance on whether real-time, smartphone-based data collection can be limited to a sub-sample with the idea of relying on model-based within-survey imputation of time use measures – again as a cost saving mechanism while improving the quality of time use data collected in large-scale surveys.

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