“Adequate” EMA Compliance
EMA
What level of EMA compliance should we strive for in long-term studies of health behavior and at what level is the validity of EMA seriously threatened? Certainly, when there are long periods of 0% compliance in the majority of the sample [Ultimately, “acceptable” compliance depends in large part on the particular questions being asked and analyses being performed. Greater temporal precision and representativeness of momentary changes is needed to test complex within-day mediational analyses involving changes in multiple processes (eg, affect, self-efficacy, and momentary changes in health behavior) than to examine week-to-week changes in health behavior and related processes. However, even for complex mediational analyses, statistical approaches to address missing data (eg, imputation strategies and full-information estimation) can mitigate bias even at high levels of missingness [These results may be useful in optimizing approaches to deal with missing EMA data and addressing issues of noncompliance. Our findings suggest adding variables associated with compliance including assessment type, age, employment status, and race into statistical models can help to reduce bias from missing data. Additional quantitative and qualitative work is also needed to better understand the mediating mechanisms that cause these groups to have reduced compliance (eg, increased demands, lowered research engagement, and stress). Such information can help inform EMA protocols to better meet the needs of participants and increase compliance.