Literature DB >> 33709943

Effort-Optimized Intervention Model: Framework for Building and Analyzing Digital Interventions That Require Minimal Effort for Health-Related Gains.

Amit Baumel1, Frederick J Muench2.   

Abstract

The majority of digital health interventions lean on the promise of bringing health and self-care into people's homes and hands. However, these interventions are delivered while people are in their triggering environments, which places competing demands on their attention. Individuals struggling to change or learn a new behavior have to work hard to achieve even a minor change because of the automatic forces propelling them back to their habitual behaviors. We posit that effort and burden should be explored at the outset and throughout the digital intervention development process as a core therapeutic mechanism, beyond the context of design or user experience testing. In effort-focused conceptualization, it is assumed that, even though goals are rational and people want to achieve them, they are overtaken by competing cognitive, emotional, and environmental processes. We offer the term effort-optimized intervention to describe interventions that focus on user engagement in the face of competing demands. We describe design components based on a 3-step process for planning an effort-optimized intervention: (1) nurturing effortless cognitive and environmental salience to help people keep effort-related goals prominent despite competition; (2) making it as effortless as possible to complete therapeutic activities to avoid ego depletion and self-efficacy reduction; and (3) turning the necessary effortful activities into sustainable assets. We conclude by presenting an example of designing a digital health intervention based on the effort-optimized intervention model. ©Amit Baumel, Frederick J Muench. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 12.03.2021.

Entities:  

Keywords:  addiction; behavior change; behavioral health; digital health; effort; intervention; mental health; persuasive design; salience

Year:  2021        PMID: 33709943      PMCID: PMC7998331          DOI: 10.2196/24905

Source DB:  PubMed          Journal:  J Med Internet Res        ISSN: 1438-8871            Impact factor:   5.428


  37 in total

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9.  Objective User Engagement With Mental Health Apps: Systematic Search and Panel-Based Usage Analysis.

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10.  Digital Micro Interventions for Behavioral and Mental Health Gains: Core Components and Conceptualization of Digital Micro Intervention Care.

Authors:  Amit Baumel; Theresa Fleming; Stephen M Schueller
Journal:  J Med Internet Res       Date:  2020-10-29       Impact factor: 5.428

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