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Identifying Behavior Change Techniques in an Artificial Intelligence-Based Fitness App

A Content Analysis

Bibliographic Data

ID21650996
AuthorsHakan Kuru (0000-0002-6477-1782, İstanbul Rumeli University, İstanbul, Turkey, corresponding author)
Year2024
Volume51
Issue4
Pages636-647
Publication date2024-08-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueHealth Education & Behavior (JOURNAL)
Journal identifiersISSN: 1090-1981 • E-ISSN: 1552-6127
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/10901981231213586
PMID38054236
OpenAlexW4389392453
LanguageEN
References cited55

In the field of artificial intelligence-based fitness apps, the effective integration of behavior change techniques (BCTs) is critical for promoting physical activity and improving health outcomes. However, the specific BCTs employed by apps and their impact on user engagement and behavior change are not explored sufficiently. This study investigates the Freeletics fitness app through a mixed-methods approach to evaluate the use of BCTs. In the quantitative analysis, fifteen unique BCTs were identified based on the Behavior Change Technique Taxonomy (V1). In the qualitative analysis, user reviews ( n =400) were examined to understand perspectives on the app’s effectiveness in promoting behavior change. Goal setting, action planning, self-monitoring of behavior, and social support were among the most prevalent BCTs identified in the Freeletics app, and their effectiveness in enhancing user engagement and promoting behavior change was also highlighted by user reviews. Among the areas of improvement identified in the study were the need for simplifying personalization options and addressing user concerns regarding the specificity of feedback. The study underscores the importance of integrating BCTs effectively within AI-based fitness apps to drive user engagement and facilitate behavior change. It contributes valuable insights into the design and implementation of BCTs in fitness apps and offers recommendations for developers, emphasizing the significance of goal setting, feedback mechanisms, self-monitoring, and social support. By understanding the impact of specific BCTs on user behavior and addressing user concerns, developers can create more effective fitness apps, ultimately promoting healthier lifestyles and positive behavior change

Behavior change · Behavior change methods · Behaviour change · Goal setting · Personalization · World Wide Web · Applied Psychology · Behavioral Health and Interventions · Computer Science · Mobile Health and mHealth Applications · Physical Activity and Health · Psychology · Social Psychology

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