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Cited by 31Health Literacy and Information AccessibilityElectronic Health Records SystemsMobile Health and mHealth Applications

Transaction logfile analysis in health communication research: Challenges and opportunities

Han, Jeong Yeob·2011·Patient Education and Counseling
DOI 10.1016/j.pec.2010.12.018
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Abstract

Objective To investigate the individualized nature of eHealth communication, it is necessary for us to go beyond the conventional approach to explain the effect of eHealth initiatives. The current article proposes transaction logfile analysis as a unique method to probe the process by which individuals locate needed information and obtains benefits out of it.Methods This article discusses the background of logfile analysis along with practical and methodological issues related to the analysis of log data.Results This article recommends potential solutions to resolve issues discussed in the Section 2.Conclusions This article discusses how transaction logfile analysis could benefit eHealth researchers, along with its relevance and application in health communication research. Logfile analysis could provide rich knowledge on how eHealth applications and tools work if performed on a regular basis, incorporated with appropriate measurement techniques and research design, and interpreted carefully.Practice implications Logfile analysis can point toward important design implications for more effective eHealth applications. Further, interventions employing logfile analysis require not only well-designed research models but also interdisciplinary research team to handle the multifaceted work involved in the process.

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Crossref · 10.1016/j.pec.2010.12.018

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  • RCTs cannot provide insight into process outcomes or how use of different components of eHealth technology contributed to healthier living, improved well-being, or daily tasks.

    “Therefore, no insight can be obtained on process outcomes or how the use of the different components of the technology has contributed to healthier living, improved well-being, or a user’s ability to conduct daily tasks [7,9,10].”

    From Opening the Black Box of Electronic Health: Collecting, Analyzing, and Interpreting Log Data (2017) · cites this paper as [9]

  • Analyses of log data can provide continuous and objective insights into the actual usage of eHealth technology.

    “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.”

    From Opening the Black Box of Electronic Health: Collecting, Analyzing, and Interpreting Log Data (2017) · cites this paper as [9]

  • Longer and more frequent exposure to an eHealth technology might indicate how well the system fits users' needs, but can also signify unfocused and/or non-strategic use or an inefficient system.

    “For example, a longer and more frequent exposure to an eHealth technology might indicate how well the system fits the users’ needs, but it can also signify unfocused and/or non-strategic use or an inefficient system [9,21].”

    From Opening the Black Box of Electronic Health: Collecting, Analyzing, and Interpreting Log Data (2017) · cites this paper as [9]

  • eHealth research has limited insight into process outcomes or how technology use contributes to healthier living, improved well-being, or daily tasks.

    “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.”

    From Opening the Black Box of Electronic Health: Collecting, Analyzing, and Interpreting Log Data (2017) · cites this paper as [9]

  • The possibilities of log data in eHealth research have not been exploited to their fullest extent.

    “However, the possibilities of log data in eHealth research have not been exploited to their fullest extent.”

    From Opening the Black Box of Electronic Health: Collecting, Analyzing, and Interpreting Log Data (2017) · cites this paper as [9]

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Authors
Han, J. Y.
Affiliations
University of Georgia (US)
Corresponding author
Han, Jeong Yeob
ORCID
Han, Jeong Yeob
Venue
Patient Education and Counseling
Publisher
Elsevier BV
Published
2011-03
Volume
82
Issue
3
Pages
307-312
ISSN
0738-3991 (ISSN-L)
DOI
10.1016/j.pec.2010.12.018
OpenAlex
W2029246441
Cited by
31
References
39
Citations by year
2024: 1 · 2023: 2 · 2022: 1 · 2021: 2 · 2020: 1 · 2018: 3 · 2017: 5 · 2016: 1 · 2015: 3 · 2014: 5 · 2013: 3 · 2012: 2
FWCI
7.12
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
  • Patient Education and Counseling (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • University of Georgia
  • University of Georgia Research Foundation
Topics
  • Health Sciences › Health Professions › General Health Professions › Health Literacy and Information Accessibility
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
Keywords
health communication research, user behavior, information seeking, log analysis, user-centered design
MeSH terms
Comprehensive Health Care, Humans, Information Systems, Medical Informatics, Patient Education as Topic, Research Design, Transactional Analysis, Patient-Centered Care, Internet, Information Seeking Behavior, Health Communication

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