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Feasibility of digital footprint data for health analytics and services: an explorative pilot study

Overview of attention for article published in BMC Medical Informatics and Decision Making, November 2016
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Title
Feasibility of digital footprint data for health analytics and services: an explorative pilot study
Published in
BMC Medical Informatics and Decision Making, November 2016
DOI 10.1186/s12911-016-0378-0
Pubmed ID
Authors

Marja Harjumaa, Saila Saraniemi, Saara Pekkarinen, Minna Lappi, Heidi Similä, Minna Isomursu

Abstract

As a result of digitalization, data is available about almost every aspect of our lives. Personal data collected by individuals themselves or stored by organizations interacting with people is known as a digital footprint. The purpose of this study was to identify prerequisites for collecting and using digital data that could be valuable for health data analytics and new health services. Researchers and their contacts involved in a nationwide research project focusing on digital health in Finland were asked to participate in a pilot study on collecting their own personal data from various organizations of their own choice, such as retail chains, banks, insurance companies, and healthcare providers. After the pilot, a qualitative inquiry was adopted to collect semi-structured interview data from twelve active participants in the pilot. Interviews comprised themes such as the experiences of collecting personal data, as well as the usefulness of the data in general and for the participants themselves. Interview data was then analyzed thematically. Even if the participants had an academic background and were highly motivated to collect and use their data, they faced many challenges, such as quite long delays in the provision of the data, and the unresponsiveness of some organizations. Regarding the usefulness of the acquired personal data, our results show that participants had high expectations, but they were disappointed with the small amount of data and its irrelevant content. For the most part, the data was not in a format that would be useful for health data analytics and new health services. Participants also found that there were actual mistakes in their health data reports. The study revealed that collecting and using digital footprint data, even by knowledgeable individuals, is not an easy task. As the usefulness of the acquired personal health data mainly depended on its form and usability for services or solutions relevant to an individual, rather than on the data being valuable as such, more emphasis should be placed on providing the data in a reusable form.

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Finland 1 1%
Unknown 75 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 17%
Researcher 10 13%
Student > Master 7 9%
Student > Bachelor 6 8%
Librarian 4 5%
Other 15 20%
Unknown 21 28%
Readers by discipline Count As %
Business, Management and Accounting 8 11%
Social Sciences 8 11%
Computer Science 8 11%
Nursing and Health Professions 7 9%
Engineering 5 7%
Other 15 20%
Unknown 25 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 August 2020.
All research outputs
#13,373,196
of 23,577,654 outputs
Outputs from BMC Medical Informatics and Decision Making
#895
of 2,025 outputs
Outputs of similar age
#158,912
of 314,839 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#14
of 24 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,025 research outputs from this source. They receive a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 54% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 314,839 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.