Long-term Compliance Habits: What Early Data Tells Us
This research addresses data loss issues for researchers designing long-term health studies, but it is incremental as it applies existing methods to new data.
The study tackled the problem of compliance attrition in long-term health studies by analyzing early data from 392 students, finding that compliance data from as early as one month correlated with dropout likelihood and long-term compliance (p < .001).
The rise in popularity of physical activity trackers provides extensive opportunities for research on personal health, however, barriers such as compliance attrition can lead to substantial losses in data. As such, insights into student's compliance habits could support researcher's decisions when designing long-term studies. In this paper, we examined 392 students on a college campus currently two and a half years into an ongoing study. We find that compliance data from as early as one month correlated with student's likelihood of dropping out of the study (p < .001) and compliance long-term (p < .001). The findings in this paper identify long-term compliance habits and the viability of their early detection.