The Law of Attrition in eHealth Trials
Author Information
Author(s): Gunther Eysenbach, Helen Christensen
Primary Institution: Centre for Global eHealth Innovation, University of Toronto & University Health Network
Hypothesis
What factors contribute to high dropout rates in eHealth trials?
Conclusion
High dropout rates in eHealth trials are a common phenomenon that should be analyzed and reported as they provide insights into the effectiveness and usability of eHealth applications.
Supporting Evidence
- Only 12 out of 1161 users completed a 12-week panic disorder program.
- Only 97 out of 19607 participants completed all modules of a depression program.
- 26 out of 58 users continued to use a disease management platform after 3 months.
Takeaway
Many people stop using health apps before finishing them, and understanding why can help make these apps better.
Methodology
The paper discusses the need for a science of attrition and suggests using survival analysis methods to analyze dropout rates.
Potential Biases
There may be a publication bias against studies with high dropout rates, leading to underreporting of attrition data.
Limitations
The study does not provide specific empirical data but rather discusses theoretical models and observations from existing literature.
Digital Object Identifier (DOI)
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