Introduction – Obesity is a contributing factor to many diseases and is becoming a growing problem worldwide. Many apps have been developed to assist users in improving their weight management. However, given the speed at which apps are created, it is crucial to assess their quality regularly.
Objectives – This study aimed to evaluate the quality of weight management apps using comprehensive quality assessment criteria. By doing so, the information quality (RQ1) and system quality (RQ2) were determined, and relationships between these elements, user ratings, and app downloads (RQ3) were examined.
Methods – A systematic search in the US App Store using search terms related to weight management was performed. System quality was assessed using the Mobile App Rating Scale (MARS) and rated on a 5-point scale. The Taxonomy of Behavior Change Techniques (BCTs) was used to determine their presence or absence. A second reviewer coded 50% of the apps to account for interrater reliability. The descriptive and inferential statistical data analyses were carried out with SPSS.
Results – A sample of N = 38 apps was deemed eligible for this review. On average, 9.6 BCTs were identified per app (range: 3–19). The most frequently used BCTs were Provide instructions (87%) and Prompt self-monitoring (87%). The MARS overall quality scores indicated moderate system quality (M = 3.48; SD .61). Functionality was the highest-scoring MARS domain (M = 3.52; SD .68), while Aesthetics (M = 3.40; SD .84) scored the lowest. Significant positive correlations were identified between the overall MARS score, the number of BCTs, and app downloads.
Conclusion – Establishing a standardized framework for quality evaluation would increase the comparability of assessments and the significance for users. Based on the present findings, future app development should involve more health professionals, integrate more evidence- based content, and incorporate more effective BCTs for weight management.
Table of Contents
1 Introduction
2 Research Topic
2.1 Relevance of the Topic
2.2 Description of the Research Subject
3 State of Research and Theory
3.1 State of Research
3.1.1 Quality Assessments of mHealth Apps
3.1.2 Behavior Change Technique Incorporation
3.2 Theoretical Background
3.2.1 Social Cognitive Theory
3.2.2 Theory of Reasoned Action / Planned Behavior
3.3.3 Information–Motivation–Behavioral Skills Model
3.3.4 Operant Conditioning
3.3.5 Control Theory
4 Research Problem
4.1 Conceptual Framework
4.2 Research Questions
5 Methods
5.1 Study Design
5.2 Operationalization and Instruments
5.2.1 Information Quality
5.2.2 System Quality
5.3 Sampling
5.4 Data Collection
5.5 Data Analysis
5.6 Research Ethics
6 Results
6.1 App Selection
6.2 App Characteristics
6.3 Information Quality - (RQ1)
6.4 System Quality - (RQ2)
6.5 Relationships - (RQ3)
6.6 Qualitative Examples
6.6.1 App Fastyle
6.6.2 App Fresh Tri
6.6.3 App GPlans
6.6.4 App YAZIO
6.6.5 App Zero
7 Discussion
7.1 Summary and Interpretation of Main Results
7.1.1 Information Quality - (RQ1)
7.1.2 System Quality - (RQ2)
7.1.3 Relationships - (RQ3)
7.2 Limitations of the Study
7.3 Discussion of Future Research and Applications
Research Objectives and Themes
This study aims to evaluate the quality of mobile weight management applications by analyzing the presence of behavior change techniques (BCTs) and overall system quality using the Mobile App Rating Scale (MARS), while examining the correlations between these technical factors, user ratings, and download counts.
- Systematic evaluation of commercial weight management apps on the iOS platform.
- Assessment of information quality through the integration of BCTs based on the Abraham & Michie taxonomy.
- Measurement of technical system quality using the validated Mobile App Rating Scale (MARS).
- Analysis of the relationship between app features, user engagement, and store performance metrics.
- Investigation into the role of evidence-based strategies in digital weight management tools.
Excerpt from the Book
3.3.4 Operant Conditioning
Operant Conditioning (OC) is a type of learning that uses rewards and punishments to influence behavior. Through OC, a link is established between a behavior and its associated outcome (whether positive or negative) (Staddon & Certrutti, 2003). The operant is the behavior. The link between the discriminative stimulus, response, and reinforcer impacts the possibility of a behavior occurring again in the future. A reinforcer is a positive reinforcement or, in the case of negative outcomes, a punishment. OC emphasizes deliberate behaviors above unconscious and automatic ones and the role of rewards and punishments in the formation of behaviors. When pleasant consequences follow a behavior, it is more likely to be repeated, and when unpleasant consequences follow a behavior, it is less likely to be repeated.
Summary of Chapters
1 Introduction: Provides background on global obesity trends and the rising importance of mobile health apps for weight management.
2 Research Topic: Outlines the clinical and economic relevance of shifting toward cost-effective digital weight loss interventions.
3 State of Research and Theory: Reviews existing literature on mHealth quality assessments and explains fundamental behavioral theories used to guide interventions.
4 Research Problem: Introduces the adapted Information Systems (IS) Success Model and specifies the core research questions driving the evaluation.
5 Methods: Details the systematic search, app inclusion criteria, and the use of the MARS and BCT taxonomy for the quantitative content analysis.
6 Results: Presents statistical findings regarding the BCT implementation, MARS quality scores, and correlations with App Store metrics.
7 Discussion: Interprets the findings in the context of previous research, acknowledges study limitations, and proposes directions for future app development and research.
Keywords
mHealth, Weight Management, Mobile Apps, Behavior Change Techniques, MARS, Information Quality, System Quality, Obesity, Digital Interventions, App Evaluation, Health Promotion, User Engagement, Behavior Modification, Dietary Habits, Mobile Technology
Frequently Asked Questions
What is the core focus of this research?
The research focuses on evaluating the technical quality and the inclusion of behavior change techniques in popular mobile weight management apps.
Which thematic fields are addressed?
The study intersects the fields of media psychology, health promotion, and information systems, specifically looking at how software design impacts health-related behavior change.
What is the primary research goal?
The primary goal is to determine how well commercial weight management apps integrate evidence-based behavioral strategies and how these features relate to app quality, user ratings, and popularity.
Which scientific methodology is employed?
The study performs a quantitative content analysis using the Mobile App Rating Scale (MARS) and the BCT taxonomy developed by Abraham & Michie to code app content.
What is covered in the main body of the work?
The work provides a thorough literature review, a theoretical framework based on behavioral science, a detailed methodology section, a results chapter with statistical correlations, and a qualitative discussion of top-rated apps.
What are the characterizing keywords?
The study is characterized by concepts such as mHealth, Behavior Change Techniques, mobile app quality evaluation, and weight management interventions.
Why are BCTs important for weight management apps?
BCTs are considered the 'active ingredients' of interventions that help users transition from passive information consumption to active habit modification and long-term behavioral change.
How does the study define 'success' for these apps?
The study uses the adapted IS Success Model, looking at information and system quality alongside objective measures like download counts and average user star ratings from the App Store.
What did the qualitative analysis of the top apps reveal?
The analysis showed that top-rated apps like Fastyle and YAZIO distinguish themselves by combining high aesthetic appeal with a wide range of integrated BCTs that cater to user self-monitoring and engagement.
Why are consumer education and developer guidelines recommended?
The study suggests that because many apps lack clinical validation, standardizing assessment frameworks is essential to help users choose effective tools and to encourage developers to incorporate more evidence-based content.
- Quote paper
- Max Amelang (Author), 2021, Quality Evaluation of Weight Management Apps, Munich, GRIN Verlag, https://www.grin.com/document/1223353
