Improving Self-management for Long COVID: Using Double Diamond Model to Design A mHealth App

Zhen Zhao, Lisha Yu, She Lyu, Hailiang Wang (Corresponding Author)

Research output: Journal article publicationConference articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

Due to physical isolation and shortages of medical resources caused by COVID-19, many patients with long-term symptoms cannot receive effective treatment and care after discharge from the hospital. In the present study, we proposed the design process of a mobile health (mHealth) app to improve the long COVID patients’ self-management. This study was mainly guided by the Double Diamond Model in four phases: discover, define, develop, and deliver. We interviewed twenty patients and used a user journey map to describe their experiences throughout their healthcare period. Four app themes were identified via thematic analysis in the develop phase, including self-monitoring, mental health improvement, health coaching, and health data visualization. Prototypes of the mHealth app were determined through user-centered design. The findings contributed to long COVID healthcare using mHealth and overcoming environmental barriers in existing healthcare services.

Original languageEnglish
Pages (from-to)2274-2280
Number of pages7
JournalProceedings of the Human Factors and Ergonomics Society
Volume67
Issue number1
DOIs
Publication statusPublished - 21 Oct 2023
Event67th International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2023 - Columbia, United States
Duration: 23 Oct 202327 Oct 2023

Keywords

  • double diamond model
  • long COVID
  • mHealth
  • self-management

ASJC Scopus subject areas

  • Human Factors and Ergonomics

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