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Assessing Physicians’ Recall Bias of Work Hours With a Mobile App: Interview and App-Recorded Data Comparison
BACKGROUND: Previous studies have shown inconsistencies in the accuracy of self-reported work hours. However, accurate documentation of work hours is fundamental for the formation of labor policies. Strict work-hour policies decrease medical errors, improve patient safety, and promote physicians’ we...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8742215/ https://www.ncbi.nlm.nih.gov/pubmed/34951600 http://dx.doi.org/10.2196/26763 |
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author | Wang, Hsiao-Han Lin, Yu-Hsuan |
author_facet | Wang, Hsiao-Han Lin, Yu-Hsuan |
author_sort | Wang, Hsiao-Han |
collection | PubMed |
description | BACKGROUND: Previous studies have shown inconsistencies in the accuracy of self-reported work hours. However, accurate documentation of work hours is fundamental for the formation of labor policies. Strict work-hour policies decrease medical errors, improve patient safety, and promote physicians’ well-being. OBJECTIVE: The aim of this study was to estimate physicians’ recall bias of work hours with a mobile app, and to examine the association between the recall bias and physicians’ work hours. METHODS: We quantified recall bias by calculating the differences between the app-recorded and self-reported work hours of the previous week and the penultimate week. We recruited 18 physicians to install the “Staff Hours” app, which automatically recorded GPS-defined work hours for 2 months, contributing 1068 person-days. We examined the association between work hours and two recall bias indicators: (1) the difference between self-reported and app-recorded work hours and (2) the percentage of days for which work hours were not precisely recalled during interviews. RESULTS: App-recorded work hours highly correlated with self-reported counterparts (r=0.86-0.88, P<.001). Self-reported work hours were consistently significantly lower than app-recorded hours by –8.97 (SD 8.60) hours and –6.48 (SD 8.29) hours for the previous week and the penultimate week, respectively (both P<.001). The difference for the previous week was significantly correlated with work hours in the previous week (r=–0.410, P=.01), whereas the correlation of the difference with the hours in the penultimate week was not significant (r=–0.119, P=.48). The percentage of hours not recalled (38.6%) was significantly higher for the penultimate week (38.6%) than for the first week (16.0%), and the former was significantly correlated with work hours of the penultimate week (r=0.489, P=.002) CONCLUSIONS: Our study identified the existence of recall bias of work hours, the extent to which the recall was biased, and the influence of work hours on recall bias. |
format | Online Article Text |
id | pubmed-8742215 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-87422152022-01-21 Assessing Physicians’ Recall Bias of Work Hours With a Mobile App: Interview and App-Recorded Data Comparison Wang, Hsiao-Han Lin, Yu-Hsuan J Med Internet Res Original Paper BACKGROUND: Previous studies have shown inconsistencies in the accuracy of self-reported work hours. However, accurate documentation of work hours is fundamental for the formation of labor policies. Strict work-hour policies decrease medical errors, improve patient safety, and promote physicians’ well-being. OBJECTIVE: The aim of this study was to estimate physicians’ recall bias of work hours with a mobile app, and to examine the association between the recall bias and physicians’ work hours. METHODS: We quantified recall bias by calculating the differences between the app-recorded and self-reported work hours of the previous week and the penultimate week. We recruited 18 physicians to install the “Staff Hours” app, which automatically recorded GPS-defined work hours for 2 months, contributing 1068 person-days. We examined the association between work hours and two recall bias indicators: (1) the difference between self-reported and app-recorded work hours and (2) the percentage of days for which work hours were not precisely recalled during interviews. RESULTS: App-recorded work hours highly correlated with self-reported counterparts (r=0.86-0.88, P<.001). Self-reported work hours were consistently significantly lower than app-recorded hours by –8.97 (SD 8.60) hours and –6.48 (SD 8.29) hours for the previous week and the penultimate week, respectively (both P<.001). The difference for the previous week was significantly correlated with work hours in the previous week (r=–0.410, P=.01), whereas the correlation of the difference with the hours in the penultimate week was not significant (r=–0.119, P=.48). The percentage of hours not recalled (38.6%) was significantly higher for the penultimate week (38.6%) than for the first week (16.0%), and the former was significantly correlated with work hours of the penultimate week (r=0.489, P=.002) CONCLUSIONS: Our study identified the existence of recall bias of work hours, the extent to which the recall was biased, and the influence of work hours on recall bias. JMIR Publications 2021-12-24 /pmc/articles/PMC8742215/ /pubmed/34951600 http://dx.doi.org/10.2196/26763 Text en ©Hsiao-Han Wang, Yu-Hsuan Lin. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 24.12.2021. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Wang, Hsiao-Han Lin, Yu-Hsuan Assessing Physicians’ Recall Bias of Work Hours With a Mobile App: Interview and App-Recorded Data Comparison |
title | Assessing Physicians’ Recall Bias of Work Hours With a Mobile App: Interview and App-Recorded Data Comparison |
title_full | Assessing Physicians’ Recall Bias of Work Hours With a Mobile App: Interview and App-Recorded Data Comparison |
title_fullStr | Assessing Physicians’ Recall Bias of Work Hours With a Mobile App: Interview and App-Recorded Data Comparison |
title_full_unstemmed | Assessing Physicians’ Recall Bias of Work Hours With a Mobile App: Interview and App-Recorded Data Comparison |
title_short | Assessing Physicians’ Recall Bias of Work Hours With a Mobile App: Interview and App-Recorded Data Comparison |
title_sort | assessing physicians’ recall bias of work hours with a mobile app: interview and app-recorded data comparison |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8742215/ https://www.ncbi.nlm.nih.gov/pubmed/34951600 http://dx.doi.org/10.2196/26763 |
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