scholarly journals Patient-Generated Health Data: Dimensions, Challenges, and Open Questions

2020 ◽  
Vol 13 (3) ◽  
pp. 165-297
Author(s):  
Mayara Costa Figueiredo ◽  
Yunan Chen
Keyword(s):  
Health Data ◽  
Open Questions

scholarly journals To What Extent Does the EU General Data Protection Regulation (GDPR) Apply to Citizen Scientist-Led Health Research with Mobile Devices?

2020 ◽  
Vol 48 (S1) ◽  
pp. 187-195
Author(s):  
Edward S. Dove ◽  
Jiahong Chen
Keyword(s):  
Mobile Devices ◽  
Data Protection ◽  
Health Research ◽  
Health Data ◽  
Specific Context ◽  
General Data Protection Regulation ◽  
Citizen Scientist ◽  
Open Questions ◽  
General Data ◽  
The Eu

In this article, we consider the possible application of the European General Data Protection Regulation (GDPR) to “citizen scientist”-led health research with mobile devices. We argue that the GDPR likely does cover this activity, depending on the specific context and the territorial scope. Remaining open questions that result from our analysis lead us to call for lex specialis that would provide greater clarity and certainty regarding the processing of health data by for research purposes, including these non-traditional researchers.

scholarly journals Task-Data Taxonomy for Health Data Visualizations: Web-Based Survey With Experts and Older Adults (Preprint)

2017 ◽  
Author(s):  
Sabine Theis ◽  
Peter Wilhelm Victor Rasche ◽  
Christina Bröhl ◽  
Matthias Wille ◽  
Alexander Mertens
Keyword(s):  
Older Adults ◽  
Online Survey ◽  
Empirical Evaluation ◽  
Health Data ◽  
Control Group ◽  
Data Types ◽  
Open Questions ◽  
User Groups ◽  
Health Situation ◽  
Data Visualizations

BACKGROUND Increasingly, eHealth involves health data visualizations to enable users to better understand their health situation. Selecting efficient and ergonomic visualizations requires knowledge about the task that the user wants to carry out and the type of data to be displayed. Taxonomies of abstract tasks and data types bundle this knowledge in a general manner. Task-data taxonomies exist for visualization tasks and data. They also exist for eHealth tasks. However, there is currently no joint task taxonomy available for health data visualizations incorporating the perspective of the prospective users. One of the most prominent prospective user groups of eHealth are older adults, but their perspective is rarely considered when constructing tasks lists. OBJECTIVE The aim of this study was to construct a task-data taxonomy for health data visualizations based on the opinion of older adults as prospective users of eHealth systems. eHealth experts served as a control group against the bias of lacking background knowledge. The resulting taxonomy would then be used as an orientation in system requirement analysis and empirical evaluation and to facilitate a common understanding and language in eHealth data visualization. METHODS Answers from 98 participants (51 older adults and 47 eHealth experts) given in an online survey were quantitatively analyzed, compared between groups, and synthesized into a task-data taxonomy for health data visualizations. RESULTS Consultation, diagnosis, mentoring, and monitoring were confirmed as relevant abstract tasks in eHealth. Experts and older adults disagreed on the importance of mentoring (χ24=14.1, P=.002) and monitoring (χ24=22.1, P<.001). The answers to the open questions validated the findings from the closed questions and added therapy, communication, cooperation, and quality management to the aforementioned tasks. Here, group differences in normalized code counts were identified for “monitoring” between the expert group (mean 0.18, SD 0.23) and the group of older adults (mean 0.08, SD 0.15; t96=2431, P=.02). Time-dependent data was most relevant across all eHealth tasks. Finally, visualization tasks and data types were assigned to eHealth tasks by both experimental groups. CONCLUSIONS We empirically developed a task-data taxonomy for health data visualizations with prospective users. This provides a general framework for theoretical concession and for the prioritization of user-centered system design and evaluation. At the same time, the functionality dimension of the taxonomy for telemedicine—chosen as the basis for the construction of present taxonomy—was confirmed.

What’s Next?

2011 ◽  
Vol 23 (1) ◽  
pp. 60-63 ◽  
Author(s):  
Peter Vorderer
Keyword(s):  
Cultural Differences ◽  
Factor Model ◽  
New Developments ◽  
Theoretical Concepts ◽  
Open Questions ◽  
Entertainment Products ◽  
Entertainment Theory

This paper points to new developments in the context of entertainment theory. Starting from a background of well-established theories that have been proposed and elaborated mainly by Zillmann and his collaborators since the 1980s, a new two-factor model of entertainment is introduced. This model encompasses “enjoyment” and “appreciation” as two independent factors. In addition, several open questions regarding cultural differences in humans’ responses to entertainment products or the usefulness of various theoretical concepts like “presence,” “identification,” or “transportation” are also discussed. Finally, the question of why media users are seeking entertainment is brought to the forefront, and a possibly relevant need such as the “search for meaningfulness” is mentioned as a possible major candidate for such an explanation.

Sign in / Sign up

Export Citation Format

Share Document