Dataset

Datasets: Eye tracking to explore attendance in health-state descriptions

Selivanova, A. (Creator), Krabbe, P. (Creator), University of Groningen, 28-Nov-2017

Dataset

Description

A crucial assumption in health valuation methods is that respondents pay equal attention to all information components presented in the response task. So far, there is no solid evidence that respondents are fulfilling this condition. The aim of our study is to explore the attendance to various information cues presented in the discrete choice (DC) response tasks.
Eye tracking was used to study the eye movements and fixations on specific information areas. This was done for seven DC response tasks comprising health-state descriptions. A sample of 10 respondents participated in the study. Videos of their eye movements were recorded and are presented graphically. Frequencies were computed for length of fixation and number of fixations, so differences in attendance were demonstrated for particular attributes in the tasks.
The data is produced by the software Gazepoint and stored in the Gazepoint format. The relevant data underlying the graphs can be provided as simple Excel file, or SigmaPlot Graph.
For full reproducibility the data of participants’ eye-movements, the data being held in Gazepoint format is required. However, due to anonymity of participants the videos are not provided. The eye-movements of the respondents were recorded using specific software Gazepoint. Therefore, for getting the full data, it will be needed to install the Gazepoint Analysis software and access the underlying data from the authors
Date made available28-Nov-2017
PublisherUniversity of Groningen
Temporal coverageMay-2016 - Jun-2016
Geographical coverageThe Netherlands
Access to the dataset Restricted
Contact researchdata@rug.nl

    Keywords on Datasets

  • Medicine and Health Sciences, Eye Movement, Eyes, Fatigue, Cognition, Decision making, Attention
Related Publications
  1. Eye tracking to explore attendance in health-state descriptions

    Selivanova, A. & Krabbe, P. F. M., 5-Jan-2018, In : PLoS ONE. 13, 1, 14 p., 0190111.

    Research output: Contribution to journalArticleAcademicpeer-review

View all (1) »

View graph of relations

ID: 79896760