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Accepted for/Published in: JMIR Research Protocols

Date Submitted: Apr 18, 2022
Open Peer Review Period: Apr 18, 2022 - Jun 13, 2022
Date Accepted: Nov 13, 2022
(closed for review but you can still tweet)

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

Personalization of Mobile Apps for Health Behavior Change: Protocol for a Cross-sectional Study

Gosetto L, Pittavino M, Falquet G, Ehrler F

Personalization of Mobile Apps for Health Behavior Change: Protocol for a Cross-sectional Study

JMIR Res Protoc 2023;12:e38603

DOI: 10.2196/38603

PMID: 36602850

PMCID: 9853334

Warning: This is an author submission that is not peer-reviewed or edited.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.

Validation of a Conceptual framework to Personalize a Mobile Application for Behavioral Change in the Health Domain: protocol for a cross-sectional study

  • Laetitia Gosetto; 
  • Marta Pittavino; 
  • Gilles Falquet; 
  • Frédéric Ehrler

ABSTRACT

Background:

Although mobile health apps (mHealth) has the potential to motivate people to adopt healthier behaviors, many of them fail to maintain these behavior over time. This long-term adherence can be improved by personalizing the proposed interventions. Based on the literature, we have created a conceptual framework guiding the selection of appropriate functionalities according to the user's profile.

Objective:

This cross-sectional study aims to check if the relationships linking functionalities and profiles proposed in our conceptual framework are confirmed by the preferences of users collected through questionnaires.

Methods:

An online questionnaire lead participants to discover several functionalities of a mobile app aiming to foster healthier behavior. The participants must select the 5 functionalities they consider as the most relevant to motivate a healthier behavior and evaluate them on a score ranging from 0 to 100.

Results:

Data collection was conducted between July 2021 and December 2021.

Conclusions:

This protocol will allow us to define the functionalities that are preferred by users according to their profile according to our conceptual framework.


 Citation

Please cite as:

Gosetto L, Pittavino M, Falquet G, Ehrler F

Personalization of Mobile Apps for Health Behavior Change: Protocol for a Cross-sectional Study

JMIR Res Protoc 2023;12:e38603

DOI: 10.2196/38603

PMID: 36602850

PMCID: 9853334

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