University of Oulu

Niels van Berkel, Jorge Goncalves, Peter Koval, Simo Hosio, Tilman Dingler, Denzil Ferreira, and Vassilis Kostakos. 2019. Context-Informed Scheduling and Analysis: Improving Accuracy of Mobile Self-Reports. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI '19). ACM, New York, NY, USA, Paper 51, 12 pages. DOI: https://doi.org/10.1145/3290605.3300281

Context-informed scheduling and analysis : improving accuracy of mobile self-reports

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Author: van Berkel, Niels1; Goncalves, Jorge1; Koval, Peter1;
Organizations: 1The University of Melbourne, Australia
2University of Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.9 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2019050614365
Language: English
Published: Association for Computing Machinery, 2019
Publish Date: 2019-05-06
Description:

Abstract

Mobile self-reports are a popular technique to collect participant labelled data in the wild. While literature has focused on increasing participant compliance to self-report questionnaires, relatively little work has assessed response accuracy. In this paper, we investigate how participant context can affect response accuracy and help identify strategies to improve the accuracy of mobile self-report data. In a 3-week study we collect over 2,500 questionnaires containing both verifiable and non-verifiable questions. We find that response accuracy is higher for questionnaires that arrive when the phone is not in ongoing or very recent use. Furthermore, our results show that long completion times are an indicator of a lower accuracy. Using contextual mechanisms readily available on smartphones, we are able to explain up to 13% of the variance in participant accuracy. We offer actionable recommendations to assist researchers in their future deployments of mobile self-report studies.

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ISBN Print: 978-1-4503-5970-2
Pages: 1 - 12
Article number: 51
DOI: 10.1145/3290605.3300281
OADOI: https://oadoi.org/10.1145/3290605.3300281
Host publication: CHI Conference on Human Factors in Computing Systems Proceedings (CHI 2019), May 4–9, 2019, Glasgow, Scotland UK
Conference: ACM SIGCHI annual conference on human factors in computing systems
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
Subjects:
EMA
ESM
Copyright information: © 2019 Copyright held by the owner/author(s). Publication rights licensed to ACM. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in CHI Conference on Human Factors in Computing Systems Proceedings (CHI 2019), May 4–9, 2019, Glasgow, Scotland UK, http://dx.doi.org/10.1145/3290605.3300281.