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Using New Technologies for Time Diary Data Collection: Instrument Design and Data Quality Findings from a Mixed-Mode Pilot Survey

Author

Listed:
  • Stella Chatzitheochari

    (University of Warwick)

  • Kimberly Fisher

    (University of Oxford)

  • Emily Gilbert

    (UCL Institute of Education)

  • Lisa Calderwood

    (UCL Institute of Education)

  • Tom Huskinson

    (Ipsos MORI)

  • Andrew Cleary

    (Ipsos MORI)

  • Jonathan Gershuny

    (University of Oxford)

Abstract

Recent years have witnessed a steady growth of time-use research, driven by the increased research and policy interest in population activity patterns and their associations with long-term outcomes. There is recent interest in moving beyond traditional paper-administered time diaries to use new technologies for data collection in order to reduce respondent burden and administration costs, and to improve data quality. This paper presents two novel diary instruments that were employed by a large-scale multi-disciplinary cohort study in order to obtain information on the time allocation of adolescents in the United Kingdom. A web-administered diary and a smartphone app were created, and a mixed-mode data collection approach was followed: cohort members were asked to choose between these two modes, and those who were unable or refused to use the web/app modes were offered a paper diary. Using data from a pilot survey of 86 participants, we examine diary data quality indicators across the three modes. Results suggest that the web and app modes yield an overall better time diary data quality than the paper mode, with a higher proportion of diaries with complete activity and contextual information. Results also show that the web and app modes yield a comparable number of activity episodes to the paper mode. These results suggest that the use of new technologies can improve diary data quality. Future research using larger samples should systematically investigate selection and measurement effects in mixed-mode time-use survey designs.

Suggested Citation

  • Stella Chatzitheochari & Kimberly Fisher & Emily Gilbert & Lisa Calderwood & Tom Huskinson & Andrew Cleary & Jonathan Gershuny, 2018. "Using New Technologies for Time Diary Data Collection: Instrument Design and Data Quality Findings from a Mixed-Mode Pilot Survey," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 137(1), pages 379-390, May.
    • Handle: RePEc:spr:soinre:v:137:y:2018:i:1:d:10.1007_s11205-017-1569-5
    DOI: 10.1007/s11205-017-1569-5
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    1. Martijn Hendriks & Kai Ludwigs & Ruut Veenhoven, 2016. "Why are Locals Happier than Internal Migrants? The Role of Daily Life," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 125(2), pages 481-508, January.
    2. Joeri Minnen, 2014. "Modular Online Time Use Survey (MOTUS) – Translating an existing method in the 21st century," electronic International Journal of Time Use Research, Research Institute on Professions (Forschungsinstitut Freie Berufe (FFB)) and The International Association for Time Use Research (IATUR), vol. 11(1), pages 73-93, December.
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    5. Ignace Glorieux & Joeri Minnen, 2009. "How many days? A comparison of the quality of time-use data from 2-day and 7-day diaries," electronic International Journal of Time Use Research, Research Institute on Professions (Forschungsinstitut Freie Berufe (FFB)) and The International Association for Time Use Research (IATUR), vol. 6(2), pages 314-327, September.
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    2. Marcin Hitczenko, 2022. "Improved Estimation of Poisson Rate Distributions Through a Multimode Survey Design," Sociological Methods & Research, , vol. 51(2), pages 699-727, May.
    3. Andronis, Lazaros & Maredza, Mandy & Petrou, Stavros, 2019. "Measuring, valuing and including forgone childhood education and leisure time costs in economic evaluation: Methods, challenges and the way forward," Social Science & Medicine, Elsevier, vol. 237(C), pages 1-1.
    4. Marcin Hitczenko, 2021. "Improved Estimation of Poisson Rate Distributions through a Multi-Mode Survey Design," FRB Atlanta Working Paper 2021-10, Federal Reserve Bank of Atlanta.
    5. Zeni Mattia & Bison Ivano & Giunchiglia Fausto & Reis Fernando & Gauckler Britta, 2021. "Improving Time Use Measurement with Personal Big Data Collection – The Experience of the European Big Data Hackathon 2019," Journal of Official Statistics, Sciendo, vol. 37(2), pages 341-365, June.
    6. Alesia Ferguson & Ashok Dwivedi & Foluke Adelabu & Esther Ehindero & Mehdi Lamssali & Emmanuel Obeng-Gyasi & Kristina Mena & Helena Solo-Gabriele, 2021. "Quantified Activity Patterns for Young Children in Beach Environments Relevant for Exposure to Contaminants," IJERPH, MDPI, vol. 18(6), pages 1-19, March.
    7. Annalisa Guarini & Alessandra Sansavini & Chiara Suttora & Stefania Bortolotti & Margherita Fort & Daniela Iorio & Chiara Monfardini & Maria Bigoni, 2022. "Mindful Parenting Intervention MinUTo App for Parents of Preschool Children: Study Protocol of a Randomised Controlled Trial," IJERPH, MDPI, vol. 19(13), pages 1-16, June.
    8. Piotrowski Krzysztof & Krukowska Renata, 2021. "Time Budget of Inhabitants of Large Cities in Poland During the Covid-19 Pandemic," Polish Journal of Sport and Tourism, Sciendo, vol. 28(4), pages 32-39, December.

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