Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Accepted for/Published in: JMIR mHealth and uHealth

Date Submitted: Aug 1, 2019
Open Peer Review Period: Aug 6, 2019 - Oct 1, 2019
Date Accepted: Feb 20, 2022
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

The Quality of Indian Obesity-Related mHealth Apps: PRECEDE-PROCEED Model–Based Content Analysis

S SN, S A

The Quality of Indian Obesity-Related mHealth Apps: PRECEDE-PROCEED Model–Based Content Analysis

JMIR Mhealth Uhealth 2022;10(5):e15719

DOI: 10.2196/15719

PMID: 35544318

PMCID: 9133986

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

A theory-based content analysis on mhealth applications for obesity

  • Shanmuga Nathan S; 
  • Arulchelvan S

ABSTRACT

Background:

With the availability of handy mobile devices and high-speed internet, much information in the field of health, wellness and fitness is now more accessible to the public. People of almost all age groups use mhealth apps (Mobile health applications) to know about common diseases and their symptoms, medicine uses and side effects, diet plans and calculates BMI to keep them fit, etc. Obesity is considered as a growing threat to our society, especially for kids. Mobile apps related to obesity are available in large numbers. The potentials of such obesity-related mobile apps have to be investigated for better understanding of these apps, for using them in an effective way and for their influencing behavioural change on the users. There are prevalent studies on health & fitness apps in general but studies rarely focused on a particular health issue related apps.

Objective:

Thus the aim of the study is to explore the potentials of obesity-related apps.

Methods:

The content analysis method was adopted to analyze the contents of the top 35 obesity-related mhealth apps. A framework based on Precede-Proceed Model (PPM) was used to explore the chosen apps. The three factors of PPM model are a pre-disposing factor, enabling factor and reinforcing factor.

Results:

The analysis resulted that 26% of the apps satisfied all the variables of pre-disposing factor, only 3% of the apps satisfied all the variables of enabling factor and 6% of the apps satisfied all the variables of reinforcing factor.

Conclusions:

Entirely only 9% of the apps taken for the study satisfied the maximum variables of PPM to influence the health behavioural change of the app users. The researchers strongly recommend health professionals to involve in the development of obesity-related mhealth apps rather than some third-party developers. Lastly, a few suggestions regarding how users can adapt an obesity-related mhealth app were provided.


 Citation

Please cite as:

S SN, S A

The Quality of Indian Obesity-Related mHealth Apps: PRECEDE-PROCEED Model–Based Content Analysis

JMIR Mhealth Uhealth 2022;10(5):e15719

DOI: 10.2196/15719

PMID: 35544318

PMCID: 9133986

Download PDF


Request queued. Please wait while the file is being generated. It may take some time.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.