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Opening the Black Box of Electronic Health: Collecting, Analyzing, and Interpreting Log Data
In electronic health (eHealth) research, limited insight has been obtained on process outcomes or how the use of technology has contributed to the users’ ability to have a healthier life, improved well-being, or activate new attitudes in their daily tasks. As a result, eHealth is often perceived as...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5565791/ https://www.ncbi.nlm.nih.gov/pubmed/28784592 http://dx.doi.org/10.2196/resprot.6452 |
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author | Sieverink, Floor Kelders, Saskia Poel, Mannes van Gemert-Pijnen, Lisette |
author_facet | Sieverink, Floor Kelders, Saskia Poel, Mannes van Gemert-Pijnen, Lisette |
author_sort | Sieverink, Floor |
collection | PubMed |
description | In electronic health (eHealth) research, limited insight has been obtained on process outcomes or how the use of technology has contributed to the users’ ability to have a healthier life, improved well-being, or activate new attitudes in their daily tasks. As a result, eHealth is often perceived as a black box. To open this black box of eHealth, methodologies must extend beyond the classic effect evaluations. The analyses of log data (anonymous records of real-time actions performed by each user) can provide continuous and objective insights into the actual usage of the technology. However, the possibilities of log data in eHealth research have not been exploited to their fullest extent. The aim of this paper is to describe how log data can be used to improve the evaluation and understand the use of eHealth technology with a broader approach than only descriptive statistics. This paper serves as a starting point for using log data analysis in eHealth research. Here, we describe what log data is and provide an overview of research questions to evaluate the system, the context, the users of a technology, as well as the underpinning theoretical constructs. We also explain the requirements for log data, the starting points for the data preparation, and methods for data collection. Finally, we describe methods for data analysis and draw a conclusion regarding the importance of the results for both scientific and practical applications. The analysis of log data can be of great value for opening the black box of eHealth. A deliberate log data analysis can give new insights into how the usage of the technology contributes to found effects and can thereby help to improve the persuasiveness and effectiveness of eHealth technology and the underpinning behavioral models. |
format | Online Article Text |
id | pubmed-5565791 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-55657912017-09-07 Opening the Black Box of Electronic Health: Collecting, Analyzing, and Interpreting Log Data Sieverink, Floor Kelders, Saskia Poel, Mannes van Gemert-Pijnen, Lisette JMIR Res Protoc Tutorial In electronic health (eHealth) research, limited insight has been obtained on process outcomes or how the use of technology has contributed to the users’ ability to have a healthier life, improved well-being, or activate new attitudes in their daily tasks. As a result, eHealth is often perceived as a black box. To open this black box of eHealth, methodologies must extend beyond the classic effect evaluations. The analyses of log data (anonymous records of real-time actions performed by each user) can provide continuous and objective insights into the actual usage of the technology. However, the possibilities of log data in eHealth research have not been exploited to their fullest extent. The aim of this paper is to describe how log data can be used to improve the evaluation and understand the use of eHealth technology with a broader approach than only descriptive statistics. This paper serves as a starting point for using log data analysis in eHealth research. Here, we describe what log data is and provide an overview of research questions to evaluate the system, the context, the users of a technology, as well as the underpinning theoretical constructs. We also explain the requirements for log data, the starting points for the data preparation, and methods for data collection. Finally, we describe methods for data analysis and draw a conclusion regarding the importance of the results for both scientific and practical applications. The analysis of log data can be of great value for opening the black box of eHealth. A deliberate log data analysis can give new insights into how the usage of the technology contributes to found effects and can thereby help to improve the persuasiveness and effectiveness of eHealth technology and the underpinning behavioral models. JMIR Publications 2017-08-07 /pmc/articles/PMC5565791/ /pubmed/28784592 http://dx.doi.org/10.2196/resprot.6452 Text en ©Floor Sieverink, Saskia Kelders, Mannes Poel, Lisette van Gemert-Pijnen. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 07.08.2017. 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 JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on http://www.researchprotocols.org, as well as this copyright and license information must be included. |
spellingShingle | Tutorial Sieverink, Floor Kelders, Saskia Poel, Mannes van Gemert-Pijnen, Lisette Opening the Black Box of Electronic Health: Collecting, Analyzing, and Interpreting Log Data |
title | Opening the Black Box of Electronic Health: Collecting, Analyzing, and Interpreting Log Data |
title_full | Opening the Black Box of Electronic Health: Collecting, Analyzing, and Interpreting Log Data |
title_fullStr | Opening the Black Box of Electronic Health: Collecting, Analyzing, and Interpreting Log Data |
title_full_unstemmed | Opening the Black Box of Electronic Health: Collecting, Analyzing, and Interpreting Log Data |
title_short | Opening the Black Box of Electronic Health: Collecting, Analyzing, and Interpreting Log Data |
title_sort | opening the black box of electronic health: collecting, analyzing, and interpreting log data |
topic | Tutorial |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5565791/ https://www.ncbi.nlm.nih.gov/pubmed/28784592 http://dx.doi.org/10.2196/resprot.6452 |
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