Detecting Gamification in Breast Cancer Apps: an automatic methodology for screening purposes

Minna Isomursu; Guido Giunti; Diego Giunta; Santiago Hors-Fraile; Diana  Karosevičiūtė

doi:10.1109/CBMS.2017.21

Detecting Gamification in Breast Cancer Apps: an automatic methodology for screening purposes

Minna Isomursu, Guido Giunti, Diego Giunta, Santiago Hors-Fraile, Diana Karosevičiūtė

Publikation: Konference artikel i Proceeding eller bog/rapport kapitel › Konferencebidrag i proceedings › Forskning › peer review

Abstract

Breast cancer is the most common cancer in women both in developed and developing countries. More than half of all cancer mobile application concern breast cancer. Gamification is widely used in mobile software applications created for health-related services. Current prevalence of gamification in breast cancer apps is unknown and detection must be manually performed. The purpose of this study is to describe and produce a tool allowing automatic detection of apps which contain gamification elements and thus empowering researchers to study gamification using large data samples. Predictive logistic regression model was designed on data extracted from breast cancer apps’ title and description text available in app stores. Model was validated comparing
estimated and benchmark values, observed by gamification specialists. Study’s outcome can be applied as a screening tool to efficiently identify gamification presence in breast cancer
apps for further research.

Originalsprog	Engelsk
Titel	30th IEEE International Symposium on Computer-Based Medical Systems - IEEE CBMS 2017, Proceedings
Antal sider	6
Forlag	IEEE
Publikationsdato	2017
ISBN (Elektronisk)	2372-9198
DOI	https://doi.org/10.1109/CBMS.2017.21
Status	Udgivet - 2017
Udgivet eksternt	Ja
Begivenhed	30th IEEE International Symposium on Computer-Based Medical Systems - Thessaloniki Varighed: 20 jun. 2017 → 24 jun. 2017 Konferencens nummer: 30

Konference

Konference	30th IEEE International Symposium on Computer-Based Medical Systems
Nummer	30
Lokation	Thessaloniki
Periode	20/06/2017 → 24/06/2017

Adgang til dokumentet

10.1109/CBMS.2017.21

1705.03228Accepteret manuskript, 677 KB

https://arxiv.org/pdf/1705.03228.pdf

Citationsformater

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title = "Detecting Gamification in Breast Cancer Apps: an automatic methodology for screening purposes",

abstract = "Breast cancer is the most common cancer in women both in developed and developing countries. More than half of all cancer mobile application concern breast cancer. Gamification is widely used in mobile software applications created for health-related services. Current prevalence of gamification in breast cancer apps is unknown and detection must be manually performed. The purpose of this study is to describe and produce a tool allowing automatic detection of apps which contain gamification elements and thus empowering researchers to study gamification using large data samples. Predictive logistic regression model was designed on data extracted from breast cancer apps{\textquoteright} title and description text available in app stores. Model was validated comparingestimated and benchmark values, observed by gamification specialists. Study{\textquoteright}s outcome can be applied as a screening tool to efficiently identify gamification presence in breast cancerapps for further research. ",

keywords = "Breast Cancer, Mobile Applications, Gamification, Health Informatics, Predictive Model",

author = "Minna Isomursu and Guido Giunti and Diego Giunta and Santiago Hors-Fraile and Diana Karosevi{\v c}iūtė",

year = "2017",

doi = "10.1109/CBMS.2017.21",

language = "English",

booktitle = "30th IEEE International Symposium on Computer-Based Medical Systems - IEEE CBMS 2017, Proceedings",

publisher = "IEEE",

address = "United States",

note = "30th IEEE International Symposium on Computer-Based Medical Systems ; Conference date: 20-06-2017 Through 24-06-2017",

}

Isomursu, M, Giunti, G, Giunta, D, Hors-Fraile, S & Karosevičiūtė , D 2017, Detecting Gamification in Breast Cancer Apps: an automatic methodology for screening purposes. i 30th IEEE International Symposium on Computer-Based Medical Systems - IEEE CBMS 2017, Proceedings. IEEE, 30th IEEE International Symposium on Computer-Based Medical Systems, 20/06/2017. https://doi.org/10.1109/CBMS.2017.21

Detecting Gamification in Breast Cancer Apps: an automatic methodology for screening purposes. / Isomursu, Minna; Giunti, Guido; Giunta, Diego et al.
30th IEEE International Symposium on Computer-Based Medical Systems - IEEE CBMS 2017, Proceedings. IEEE, 2017.

Publikation: Konference artikel i Proceeding eller bog/rapport kapitel › Konferencebidrag i proceedings › Forskning › peer review

TY - GEN

T1 - Detecting Gamification in Breast Cancer Apps: an automatic methodology for screening purposes

AU - Isomursu, Minna

AU - Giunti, Guido

AU - Giunta, Diego

AU - Hors-Fraile, Santiago

AU - Karosevičiūtė , Diana

N1 - Conference code: 30

PY - 2017

Y1 - 2017

N2 - Breast cancer is the most common cancer in women both in developed and developing countries. More than half of all cancer mobile application concern breast cancer. Gamification is widely used in mobile software applications created for health-related services. Current prevalence of gamification in breast cancer apps is unknown and detection must be manually performed. The purpose of this study is to describe and produce a tool allowing automatic detection of apps which contain gamification elements and thus empowering researchers to study gamification using large data samples. Predictive logistic regression model was designed on data extracted from breast cancer apps’ title and description text available in app stores. Model was validated comparingestimated and benchmark values, observed by gamification specialists. Study’s outcome can be applied as a screening tool to efficiently identify gamification presence in breast cancerapps for further research.

AB - Breast cancer is the most common cancer in women both in developed and developing countries. More than half of all cancer mobile application concern breast cancer. Gamification is widely used in mobile software applications created for health-related services. Current prevalence of gamification in breast cancer apps is unknown and detection must be manually performed. The purpose of this study is to describe and produce a tool allowing automatic detection of apps which contain gamification elements and thus empowering researchers to study gamification using large data samples. Predictive logistic regression model was designed on data extracted from breast cancer apps’ title and description text available in app stores. Model was validated comparingestimated and benchmark values, observed by gamification specialists. Study’s outcome can be applied as a screening tool to efficiently identify gamification presence in breast cancerapps for further research.

KW - Breast Cancer

KW - Mobile Applications

KW - Gamification

KW - Health Informatics

KW - Predictive Model

U2 - 10.1109/CBMS.2017.21

DO - 10.1109/CBMS.2017.21

M3 - Article in proceedings

BT - 30th IEEE International Symposium on Computer-Based Medical Systems - IEEE CBMS 2017, Proceedings

PB - IEEE

T2 - 30th IEEE International Symposium on Computer-Based Medical Systems

Y2 - 20 June 2017 through 24 June 2017

ER -

Detecting Gamification in Breast Cancer Apps: an automatic methodology for screening purposes

Abstract

Konference

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