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RESEARCH PAPER

User Experiences of Behavioral and Psychological Change Techniques in a Walking-Based Mobile Exergame: Cross-Sectional Qualitative Study.

PMID
41894590
Journal
JMIR serious games
Publication Date
2026-03-27
Grade
E

AI Summary

Small qualitative study (n=14, ages 67–92, including some participants with Parkinson disease) found a walking-based mobile exergame increased motivation, goal-setting, feedback, self-monitoring, and routine integration but had limited social feature uptake and varied digital literacy.

Why It Matters

This work is useful for designing interventions to increase physical activity and adherence in people with Parkinson's (symptomatic/supportive care and trial engagement), but it has minimal direct relevance to therapeutic discovery because it provides no mechanistic, biomarker, or disease-modifying…

Abstract

BACKGROUND: Physical activity plays a central role in the course and progression of chronic conditions in older adults. However, individuals within this population tend to have an inactive lifestyle. Exergaming, which is defined as the integration of physical activity with game-based elements, offers a promising approach to promote physical activity in individuals with chronic conditions. Despite its potential, limited evidence exists on how specific game elements influence behavioral and psychological outcomes in this population. OBJECTIVE: The aim of this study is to explore the behavioral and psychological change techniques experienced by individuals with chronic conditions using a walking-based mobile exergame, called Heart Farming. METHODS: A cross-sectional qualitative design was used based on a gamification framework, using data from semistructured interviews with 14 participants aged 67 to 92 years who used the Heart Farming exergame for 3 months. Participants with chronic conditions, including heart failure, Parkinson disease, type 2 diabetes, stroke, or rheumatic disease, were recruited from 2 ongoing studies. Data were analyzed using deductive content analysis and presented based on the gamification framework. RESULTS: The data analysis revealed increased motivation to walk, which was facilitated by game elements such as goals, rewards, feedback, and planning. Participants valued not only the sense of progression and achievement within the game but also the real-world benefits, such as spending time in nature or feeling a sense of community with others. Exergaming was integrated into daily routines by supporting the planning and structuring of daily activities. It was also perceived as enjoyable, especially due to its farming theme and visual design. Behavioral change techniques such as goal setting, feedback, and social support were commonly experienced, whereas focus on past success (as described in the gamification framework) was not used as a technique by the exergame. Psychological techniques, including self-monitoring and stress management, were mentioned. A feeling of discomfort due to playing in public was reported, and participants varied in terms of the levels of digital literacy. Social interaction features were not adequately used, even though some participants created informal support groups to exergame. CONCLUSIONS: This study contributes to the exergaming literature by examining behavioral and psychological change techniques from the perspective of individuals with chronic conditions. Exergaming incorporates a variety of behavioral and psychological change techniques, which were experienced by the participants in various ways. Individuals' previous knowledge of exergaming, interests, and illness progression were mentioned as factors that can influence their experiences of exergaming. By increasing the understanding of how game elements are experienced and how they influence health-related behavior, the findings of this study may inform the development of exergames that are better tailored to users' needs. Further research is needed to refine behavioral change techniques and assess condition-specific adaptations to maximize engagement and health outcomes.

Score Breakdown

AI Score
12.0
Base Score
23.4
Rank Score
22.9
Narrative Velocity
-
AI Confidence
-
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