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

  • Minna Isomursu
    ,
  • Guido Giunti
    ,
  • Diego Giunta
    ,
  • Santiago Hors-Fraile
    ,
  • Diana Karosevičiūtė
  • University of Oulu
Publikation:
Konference artikel i Proceeding eller bog/rapport kapitel
Konferencebidrag i proceedings
Peer-review

Open Access

Resume

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.

Publikation information

Produktionstype

Publikation:
Konference artikel i Proceeding eller bog/rapport kapitel
Konferencebidrag i proceedings
Peer-review

Originalsprog

Engelsk

Publikationsmilepæle

  • Udgivet - 2017

Publikationsstatus

Udgivet - 2017

Forlag

IEEE, USA

ISBN (Elektronisk)

2372-9198

Publication IDs

  • Scopus: 85040358045

Titel på værtspublikation

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

Metrikker

PlumX, åbner i en ny fane

Hentninger
53
Antal citationer
5

Relateret event

Titel

30th IEEE International Symposium on Computer-Based Medical Systems

Begivenhedstype

Konference

Dato

20/06/2017 - 24/06/2017

Lokation

Thessaloniki