Supplementary data for the manuscript entitled “Reliable data collection in participatory trials to assess digital healthcare applications”

Citation Author(s):
Junseok
Park
KAIST
Seongkuk
Park
KAIST
Gwangmin
Kim
KAIST
Kwangmin
Kim
KAIST
Jaegyun
Jung
KAIST
Sunyong
Yoo
Chonnam National University
Gwan-su
Yi
KAIST
Doheon
Lee
KAIST
Submitted by:
Junseok Park
Last updated:
Wed, 03/11/2020 - 06:02
DOI:
10.21227/at9y-6657
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Abstract 

The dataset comprises raw data to validate methods for reliable data collection. We proposed the data collection methods in a path to assess digital healthcare apps. To validate the methods, we conducted experiments in Amazon Mechanical Turk (MTurk), and then we showed that the methods have a significant meaning based on statistical tests. The methods and tests are as follows: (1) comparison with the simplicity of protocol creation during the data preparation stage; (2) validation of data reliability weight compared with manually collected data during the data storage stage; and (3) the future reward distribution effect of observation during the data sharing stage. Each data set contains test information and raw data. The total number of participants was 718, and we excluded their worker ID, following by a policy by Amazon. All participants signed an informed consent document for the tests. 

Instructions: 

Download each data set, and extract the files. You will get PDF files for the test description per group for the experiment. CSV files consist of raw data and processed results, which calculate the results from MTurk.

 

If there is any question about this dataset, please send an e-mail to dhlee@kaist.ac.kr, who is a corresponding author of the original manuscript.