Black-Box Testing of the Interactive Prostate Cancer Information, Communication, and Support Program to Ensure Reliability for Patients and Caregivers

Fei Yu, Daria Neidre, Nibras Ar Rakib, Marcus Lambert, Chunxuan Ma, Amy C. Vondenberger, Lixin Song

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This study evaluates the iPICS (Interactive Prostate Cancer Information, Communication, and Support) Program, a digital health psychoeducational platform designed to support prostate cancer survivorship. Utilizing black-box testing, we assessed the system's reliability, including functionality and multimedia engagement. Results indicate that the system largely adheres to its design requirements, with users efficiently searching, bookmarking, and sharing content. However, there were search result precision disparities when integrating MedlinePlus content. Notably, users actively engaged with multimedia content, highlighting its importance in digital health platforms. Areas like search algorithms and usability for older users need refinement. This research emphasizes the need for continuous evaluation in developing digital health systems.

Original languageEnglish (US)
Title of host publicationProceedings - 2024 IEEE 12th International Conference on Healthcare Informatics, ICHI 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages461-465
Number of pages5
ISBN (Electronic)9798350383737
DOIs
StatePublished - 2024
Event12th IEEE International Conference on Healthcare Informatics, ICHI 2024 - Orlando, United States
Duration: Jun 3 2024Jun 6 2024

Publication series

NameProceedings - 2024 IEEE 12th International Conference on Healthcare Informatics, ICHI 2024

Conference

Conference12th IEEE International Conference on Healthcare Informatics, ICHI 2024
Country/TerritoryUnited States
CityOrlando
Period6/3/246/6/24

Keywords

  • black-box testing
  • digital health
  • prostate cancer

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Information Systems and Management
  • Statistics, Probability and Uncertainty
  • Health Informatics

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