583
Views
0
CrossRef citations to date
0
Altmetric
Highlights from Interact 2019

The design of persuasive prompts to induce behavioural change through an mHealth application for people with depression

, &
Pages 2497-2513 | Received 27 Nov 2020, Accepted 10 Nov 2021, Published online: 04 Dec 2021
 

ABSTRACT

The alteration of an individual's lifestyle and the adoption of healthy behaviours have been shown to be effective in combating a majority of the major symptoms of depression. While there are several mHealth applications that use behaviour change to reduce depressive symptoms, they are often not grounded in behaviour change theory and display a lack of understanding regarding the specific factors that lead to behaviour change. Therefore, there is a need to test innovative strategies to tackle the issue. One such strategy is the use of behaviour change theories to design mHealth applications that use persuasive prompts to assist in ‘prompting’ the user to adopt healthier behaviours. In this paper, we present the design of persuasive prompts and an mHealth application to induce behavioural change, followed by the results of two studies: (i) an acceptability study that tested the acceptability of the persuasive prompts and (ii) a usability study of the mHealth application. The results show that there is a significant difference in which behaviour change theories users prefer based on their level of depression and that overall, users have a positive perception of the application.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 333.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.