東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Enhancing Public Health Communicatio...

Kantartjis, Michalis,

Linked to FindBook

Google Book

Amazon

博客來

Enhancing Public Health Communication and Decision-Making: Evaluating the Efficacy of Bivariate Choropleth Mapping Using Eye Tracking /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Enhancing Public Health Communication and Decision-Making: Evaluating the Efficacy of Bivariate Choropleth Mapping Using Eye Tracking // Michalis Kantartjis.
Author:	Kantartjis, Michalis,
Description:	1 electronic resource (276 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-03, Section: B.
Contained By:	Dissertations Abstracts International86-03B.
Subject:	Information science. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31485206
ISBN:	9798384031222

Enhancing Public Health Communication and Decision-Making: Evaluating the Efficacy of Bivariate Choropleth Mapping Using Eye Tracking /
Kantartjis, Michalis,

Enhancing Public Health Communication and Decision-Making: Evaluating the Efficacy of Bivariate Choropleth Mapping Using Eye Tracking /Michalis Kantartjis. - 1 electronic resource (276 pages)

Source: Dissertations Abstracts International, Volume: 86-03, Section: B.

The prevalent use of choropleth maps for visualizing spatial data often falls short in conveying complex, multivariate information. The onset of COVID-19 highlighted the need for effective visualization tools for public health data, such as vaccination rates and mortality. Early work in this dissertation involved developing an information visualization application allowing users to navigate COVID-19 nursing home data. A substantial portion of the literature review focused on designing user-friendly multivariate interfaces to make public health data more accessible and on understanding how users navigate these information interfaces, such as geovisualizations. Building on this foundation, this dissertation examines the use of bivariate maps. It investigates the efficacy of bivariate choropleth maps compared to juxtaposed univariate choropleth maps and explores the impact of bidirectional interactive highlighting on user performance and cognitive load.In the first study, a between-subjects eye-tracking experiment divided participants into two groups: one using bivariate choropleth maps (n=25) and the other using juxtaposed univariate choropleth maps (n=23). Results indicated that for tasks requiring region searches based on specified values and anomaly detection, bivariate map users had significantly faster response times (p<0.001) and more linear visual search patterns with fewer transitions between map elements. However, tasks requiring decoding of map regions showed comparable response times between the two groups.The second study further explored the complexity of bivariate maps through a between-subjects eye-tracking experiment with 52 participants, comparing static (n=25) and interactive (n=27) map interfaces. Interactive highlighting improved accuracy (p<0.01) in anomaly detection tasks and refined visual search strategies without compromising efficiency. Both static and interactive map users demonstrated high overall accuracy, with significant decreases in response times across tasks by the third block (p<0.05).These studies collectively demonstrate that bivariate choropleth maps enhance efficiency and streamline information extraction, while bidirectional interactive highlighting further improves user accuracy and search strategies. The findings contribute to the broader understanding of multivariate data visualization, highlighting the potential benefits and usability of bivariate maps in representing complex geospatial data.

English

ISBN: 9798384031222Subjects--Topical Terms:

554358
Information science.
Subjects--Index Terms:

Bivariate choropleth maps

Enhancing Public Health Communication and Decision-Making: Evaluating the Efficacy of Bivariate Choropleth Mapping Using Eye Tracking /
LDR:04042nmm a22004453i 4500 001 2429045
005 20250428055552.5
006 m o d
007 cr|nu||||||||
008 261011s2024 miu||||||m |||||||eng d
020 $a 9798384031222
035 $a (MiAaPQD)AAI31485206
035 $a AAI31485206
040 $a MiAaPQD $b eng $c MiAaPQD $e rda
100 1 $a Kantartjis, Michalis, $e author. $3 3816656
245 1 0 $a Enhancing Public Health Communication and Decision-Making: Evaluating the Efficacy of Bivariate Choropleth Mapping Using Eye Tracking / $c Michalis Kantartjis.
264 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2024
300 $a 1 electronic resource (276 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 86-03, Section: B.
500 $a Advisors: Hourcade, Juan Pablo Committee members: Shaw, Clarissa; Daack-Hirsch, Sandra; Koylu, Caglar; Papke, Todd.
502 $b Ph.D. $c The University of Iowa $d 2024.
520 $a The prevalent use of choropleth maps for visualizing spatial data often falls short in conveying complex, multivariate information. The onset of COVID-19 highlighted the need for effective visualization tools for public health data, such as vaccination rates and mortality. Early work in this dissertation involved developing an information visualization application allowing users to navigate COVID-19 nursing home data. A substantial portion of the literature review focused on designing user-friendly multivariate interfaces to make public health data more accessible and on understanding how users navigate these information interfaces, such as geovisualizations. Building on this foundation, this dissertation examines the use of bivariate maps. It investigates the efficacy of bivariate choropleth maps compared to juxtaposed univariate choropleth maps and explores the impact of bidirectional interactive highlighting on user performance and cognitive load.In the first study, a between-subjects eye-tracking experiment divided participants into two groups: one using bivariate choropleth maps (n=25) and the other using juxtaposed univariate choropleth maps (n=23). Results indicated that for tasks requiring region searches based on specified values and anomaly detection, bivariate map users had significantly faster response times (p<0.001) and more linear visual search patterns with fewer transitions between map elements. However, tasks requiring decoding of map regions showed comparable response times between the two groups.The second study further explored the complexity of bivariate maps through a between-subjects eye-tracking experiment with 52 participants, comparing static (n=25) and interactive (n=27) map interfaces. Interactive highlighting improved accuracy (p<0.01) in anomaly detection tasks and refined visual search strategies without compromising efficiency. Both static and interactive map users demonstrated high overall accuracy, with significant decreases in response times across tasks by the third block (p<0.05).These studies collectively demonstrate that bivariate choropleth maps enhance efficiency and streamline information extraction, while bidirectional interactive highlighting further improves user accuracy and search strategies. The findings contribute to the broader understanding of multivariate data visualization, highlighting the potential benefits and usability of bivariate maps in representing complex geospatial data.
546 $a English
590 $a School code: 0096
650 4 $a Information science. $3 554358
650 4 $a Public health education. $3 2144801
650 4 $a Geographic information science. $3 3432445
650 4 $a Epidemiology. $3 568544
653 $a Bivariate choropleth maps
653 $a Comparative usability study
653 $a Nursing home
653 $a Eye tracking
653 $a Geospatial data
690 $a 0723
690 $a 0370
690 $a 0500
690 $a 0766
710 2 $a The University of Iowa. $b Computer Science. $e degree granting institution. $3 3816657
720 1 $a Hourcade, Juan Pablo $e degree supervisor.
773 0 $t Dissertations Abstracts International $g 86-03B.
790 $a 0096
791 $a Ph.D.
792 $a 2024
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31485206