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ScreenLife Capture: An open-source and user-friendly framework for collecting screenomes from Android smartphones

As our interactions with each other become increasingly digitally mediated, there is growing interest in the study of people’s digital experiences. To better understand digital experiences, some researchers have proposed the use of screenomes. This involves the collection of sequential high-frequenc...

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Detalles Bibliográficos
Autores principales: Yee, Andrew Z. H., Yu, Ryan, Lim, Sun Sun, Lim, Kwan Hui, Dinh, Tien Tuan Anh, Loh, Lionell, Hadianto, Andre, Quizon, Miguel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9607811/
https://www.ncbi.nlm.nih.gov/pubmed/36289177
http://dx.doi.org/10.3758/s13428-022-02006-z
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author Yee, Andrew Z. H.
Yu, Ryan
Lim, Sun Sun
Lim, Kwan Hui
Dinh, Tien Tuan Anh
Loh, Lionell
Hadianto, Andre
Quizon, Miguel
author_facet Yee, Andrew Z. H.
Yu, Ryan
Lim, Sun Sun
Lim, Kwan Hui
Dinh, Tien Tuan Anh
Loh, Lionell
Hadianto, Andre
Quizon, Miguel
author_sort Yee, Andrew Z. H.
collection PubMed
description As our interactions with each other become increasingly digitally mediated, there is growing interest in the study of people’s digital experiences. To better understand digital experiences, some researchers have proposed the use of screenomes. This involves the collection of sequential high-frequency screenshots which provide detailed objective records of individuals’ interaction with screen devices over time. Despite its usefulness, there remains no readily available tool that researchers can use to run their own screenome studies. To fill this gap, we introduce ScreenLife Capture, a user-friendly and open-source software to collect screenomes from smartphones. Using this tool, researchers can set up smartphone screenome studies even with limited programming knowledge and resources. We piloted the tool in an exploratory mixed-method study of 20 college students, collecting over 740,000 screenshots over a 2-week period. We found that smartphone use is highly heterogeneous, characterized by threads of experiences. Using in-depth interviews, we also explored the impact that constant background surveillance of smartphone use had on participants. Participants generally had slight psychological discomfort which fades after a few days, would suspend screen recording for activity perceived to be extremely private, and recounted slight changes in behavior. Implications for future research is discussed.
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spelling pubmed-96078112022-10-28 ScreenLife Capture: An open-source and user-friendly framework for collecting screenomes from Android smartphones Yee, Andrew Z. H. Yu, Ryan Lim, Sun Sun Lim, Kwan Hui Dinh, Tien Tuan Anh Loh, Lionell Hadianto, Andre Quizon, Miguel Behav Res Methods Article As our interactions with each other become increasingly digitally mediated, there is growing interest in the study of people’s digital experiences. To better understand digital experiences, some researchers have proposed the use of screenomes. This involves the collection of sequential high-frequency screenshots which provide detailed objective records of individuals’ interaction with screen devices over time. Despite its usefulness, there remains no readily available tool that researchers can use to run their own screenome studies. To fill this gap, we introduce ScreenLife Capture, a user-friendly and open-source software to collect screenomes from smartphones. Using this tool, researchers can set up smartphone screenome studies even with limited programming knowledge and resources. We piloted the tool in an exploratory mixed-method study of 20 college students, collecting over 740,000 screenshots over a 2-week period. We found that smartphone use is highly heterogeneous, characterized by threads of experiences. Using in-depth interviews, we also explored the impact that constant background surveillance of smartphone use had on participants. Participants generally had slight psychological discomfort which fades after a few days, would suspend screen recording for activity perceived to be extremely private, and recounted slight changes in behavior. Implications for future research is discussed. Springer US 2022-10-26 /pmc/articles/PMC9607811/ /pubmed/36289177 http://dx.doi.org/10.3758/s13428-022-02006-z Text en © The Psychonomic Society, Inc. 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Yee, Andrew Z. H.
Yu, Ryan
Lim, Sun Sun
Lim, Kwan Hui
Dinh, Tien Tuan Anh
Loh, Lionell
Hadianto, Andre
Quizon, Miguel
ScreenLife Capture: An open-source and user-friendly framework for collecting screenomes from Android smartphones
title ScreenLife Capture: An open-source and user-friendly framework for collecting screenomes from Android smartphones
title_full ScreenLife Capture: An open-source and user-friendly framework for collecting screenomes from Android smartphones
title_fullStr ScreenLife Capture: An open-source and user-friendly framework for collecting screenomes from Android smartphones
title_full_unstemmed ScreenLife Capture: An open-source and user-friendly framework for collecting screenomes from Android smartphones
title_short ScreenLife Capture: An open-source and user-friendly framework for collecting screenomes from Android smartphones
title_sort screenlife capture: an open-source and user-friendly framework for collecting screenomes from android smartphones
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9607811/
https://www.ncbi.nlm.nih.gov/pubmed/36289177
http://dx.doi.org/10.3758/s13428-022-02006-z
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