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This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (5513) Mobile Health (mhealth) (5358) Electronic/Mobile Data Capture, Internet-based Survey & Research Methodology (1788) mHealth for Data Collection and Research (1811) Wearable Devices and Sensors (1686) Fitness Trackers and Smart Pedometers/Accelerometers (821) Innovations and Technology for Physical Activity Education (1094)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/39211, first published .
Woman running along the oceanfront promenade on a sunny day.

Comparing Self-Reported Running Distance and Pace With a Commercial Fitness Watch Data: Reliability Study

Comparing Self-Reported Running Distance and Pace With a Commercial Fitness Watch Data: Reliability Study

Authors of this article:

Garrett Bullock1 Author Orcid Image ;   Joanne Stocks2 Author Orcid Image ;   Benjamin Feakins3 Author Orcid Image ;   Zahra Alizadeh4 Author Orcid Image ;   Amelia Arundale5 Author Orcid Image ;   Stefan Kluzek2 Author Orcid Image
Article Authors Cited by (2) Tweetations (5) Metrics

Journals

  1. West S, Ward P, Plisky P, Beiting J, Martin C, Losciale J, Stitzel J, Marshall S, Butler R, Morrison S, Bullock G. Getting the Most From Your Data: Using Statistical Process Controls for Data Quality Assurance in Sport Science Data. Journal of Strength & Conditioning Research 2026;40(2):e202 View
  2. Rande J, Naga J, Ebardo R. Running-app engagement and perceived training gains: sequential indirect associations through motivational affordances and runner motivation. Frontiers in Psychology 2026;17 View