Study Overview
A recent study published in the British Journal of Health Psychology has highlighted the adverse behavioral and psychological effects associated with popular commercial fitness apps, as reported by users on social media. These negative impacts could potentially diminish the apps’ effectiveness in promoting health and wellbeing.
Research Methodology
Researchers employed artificial intelligence (AI) through a technique known as Machine-Assisted Topic Analysis (MATA). This method integrates AI-driven topic modeling with human qualitative analysis to examine 58,881 posts on X (formerly Twitter) related to the five most profitable fitness apps. The analysis revealed several concerning themes:
- Challenges in quantifying diet and physical activity
- Complexity in tracking calories and exercise due to oversimplified algorithms
- Technical issues and malfunctions
- Negative emotional responses to app notifications
User Reactions
Many users expressed feelings of shame, disappointment, and demotivation, leading to disengagement from both the apps and healthy behaviors.
Implications for App Design
The findings underscore the necessity for a more user-centered and psychologically informed approach to app design. This should prioritize wellbeing and intrinsic motivation rather than rigid, quantitative targets.
Expert Insights
According to Paulina Bondaronek, PhD, the study’s corresponding author from University College London, “Fitness apps are among the most profitable and widely downloaded health tools worldwide. While they can offer health benefits, their potential downsides have received insufficient attention. Reducing health to mere calorie counts and step goals can lead to feelings of demotivation and disconnection from genuine wellbeing.” The study utilized AI alongside human analysis to highlight these often-overlooked impacts by focusing on the experiences of real users.
For further reading, refer to the study: Sheen F, Porter L, Papakonstantinou T, Ceka M, Bondaronek P. Living well? The unintended consequences of highly popular commercial fitness apps through social listening using Machine-Assisted Topic Analysis: Evidence from X. Br J Health Psychol. 2025 Nov;30(4):e70026. doi: 10.1111/bjhp.70026