Cited by 793Impact of Technology on AdolescentsChild Development and Digital TechnologyMedia and Digital Communication

A systematic review and meta-analysis of discrepancies between logged and self-reported digital media use

Open access
Parry, Douglas A., Davidson, Brittany I., Sewall, Craig J. R., Fisher, Jacob T., Mieczkowski, Hannah, Quintana, Daniel S.·2021·Nature Human Behaviour

Published version of a preprint

Abstract

There is widespread public and academic interest in understanding the uses and effects of digital media. Scholars primarily use self-report measures of the quantity or duration of media use as proxies for more objective measures, but the validity of these self-reports remains unclear. Advancements in data collection techniques have produced a collection of studies indexing both self-reported and log-based measures. To assess the alignment between these measures, we conducted a pre-registered meta-analysis of this research. Based on 106 effect sizes, we found that self-reported media use correlates only moderately with logged measurements, that self-reports were rarely an accurate reflection of logged media use and that measures of problematic media use show an even weaker association with usage logs. These findings raise concerns about the validity of findings relying solely on self-reported measures of media use.

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Crossref · 10.1038/s41562-021-01117-5

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  • Log-based measures have their own validity threats, such as technical errors and erroneous tracing of SM apps running in the background when the screen is turned off.

    “However, although log-based measures are often seen as the gold standard, they have their own validity threats, such as technical errors and the erroneous tracing of SM apps running in the background when the screen is turned off [42,43].”

    From Social media use and its impact on adolescent mental health: An umbrella review of the evidence. (2022) · cites this paper as [42]

    The Discussion (page not available in our copy) identifies technical errors as a threat to log-based measures and says tracking may mistakenly count background activity as active use. It does not specify social-media apps running while the screen is off. (LLM, conf=0.86)

    Experimental — accuracy not yet measured
  • The uMARS is a self-report measure that may not be a reliable indicator of actual usage.

    “Despite these encouraging findings, the uMARS is a self-report measure, which according to a recent meta-analysis (Parry et al., 2021) may not be a reliable indicator of actual usage.”

    From Pilot study of a well-being app to support New Zealand young people during the COVID-19 pandemic (2021) · cites this paper as Parry et al., 2021

    The Discussion says self-reported media use may not be a valid stand-in for usage logs and cautions against treating self-reports as accurate indicators of actual behaviour. It does not assess uMARS specifically, so it supports the general caution but not a finding about that measure. (LLM, conf=0.82)

    Experimental — accuracy not yet measured
  • Device-based measures can provide a more accurate assessment of social media use than self-reported tools.

    “It was recently suggested that that device-based measures can provide a more accurate assessment of social media use than self-reported tools (Parry et al., 2021;Sewall et al., 2022).”
  • Self-report measures of time spent with SM correlate only moderately with similar log-based measures.

    “Indeed, self-report measures of time spent with SM correlate only moderately with similar log-based measures [42,43].”
  • The correspondence between self-reported and logged social media use is far from perfect.

    “a recent systematic review has evidenced that the correspondence between self-reported and logged social media use is far from perfect (Parry et al., 2021).”

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Cites

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Research works printed but not linked: 7

  1. [42]42. Parry, D., Davidson, B. I., Sewall, C., Fisher, J. T., Mieczkowski, H., & Quintana, D. S. Associations Between Log-Based and Self-Reported Digital Media Use: A Systematic Review and Meta- analysis Protocol. Preprint at OSF Preprints https://osf.io/xrg5c (2020).
  2. [43]43. *Ahn, H., Nguyen, G. T., Lee, H., Jo, S. J., Kim, E. J., & Yim, H. W. Data collection and analysis of smartphone use and sleep of secondary school children. In 2017 IEEE International Conference on Big Data and Smart Computing (BigComp) (pp. 410-413). (2017).
  3. [60]60. *Newell, C. A. Smartphone and Social Media use and its Health Associations (Masters dissertation). The University of Texas at Arlington. (2018).
  4. [62]62. *Oeldorf-Hirsch, A., & Chen, Y. Who Cares about Screen Time? Predicting the use of Mobile Phone Tracking Features. Paper presented at The 70th annual conference of the International Communication Association (ICA), Gold Coast, Australia (Virtual Conference). (2020)
  5. [71]71. *Shin, M., & Lee, K. Measuring smartphone usage time is not sufficient to predict smartphone addiction. Journal of Theoretical and Applied Information Technology, 95(19), (2017).
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  7. [89]89. Salganik, M. J. Bit by bit: Social research in the digital age (Princeton University Press, 2019).

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Authors
Parry, D. A., Davidson, B. I., Sewall, C. J. R., Fisher, J. T., Mieczkowski, H., & Quintana, D. S.
Affiliations
  • Stellenbosch University (ZA)
  • University of Bristol (GB)
  • University of Pittsburgh (US)
  • University of Illinois Urbana-Champaign (US)
  • Stanford University (US)
  • Oslo University Hospital (NO)
Corresponding author
Parry, Douglas A.
Venue
Nature Human Behaviour
Published
2021-05-17
Volume
5
Issue
11
Pages
1535-1547
ISSN
2397-3374 (ISSN-L)
OpenAlex
W3162414724
Cited by
793
References
108
Citations by year
2026: 152 · 2025: 150 · 2024: 145 · 2023: 165 · 2022: 117 · 2021: 56 · 2020: 6 · 2014: 1
FWCI
23.13
Type
journal article
Language
en
Open access
Locations
  • Nature Human Behaviour (publishedVersion)
  • PubMed (publishedVersion)
  • VU Research Portal (publishedVersion)
  • Pure (University of Bath) (submittedVersion, other-oa)
  • RePEc: Research Papers in Economics (submittedVersion)
  • PsyArXiv (OSF Preprints) (submittedVersion, cc-by)
  • PsyArXiv (OSF Preprints) (submittedVersion)
Topics
  • Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
  • Social Sciences › Education › Child Development and Digital Technology
  • Physical Sciences › Computer Science › Computer Networks and Communications › Media and Digital Communication
Keywords
digital media use, usage logs, measurement validity, self-report accuracy, problematic media use, self-assessment bias
MeSH terms
Screen Time, Humans, Reproducibility of Results, Self Report, Social Media

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