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Background : Ecological momentary assessment (EMA) is an increasingly popular and feasible form of data collection, but it can be intensive and intrusive. Especially for at-risk, vulnerable populations like people who use drugs (PWUD), poor experiences with EMA may exacerbate existing chronic struggles while decreasing response rates. However, little research queries participants' experiences with EMA studies. Objectives : We explore participants' positive and negative experiences with EMA, identifying what they liked about the study, the problems they experienced, and suggested solutions to these problems. Methods : Results come from semi-structured interviews from 26 PWUD (6 women; 20 men) in Nebraska who participated in a two-week EMA pilot study on drug use with a study-provided smartphone. Participant responses were recorded by interviewers into open-text fields in Qualtrics. Data were analyzed with an iterative open coding procedure. Results : We found that many participants enjoyed the study and seamlessly incorporated the phone into their daily lives. There were a number of negative study aspects identified, however, as many participants experienced functional issues (e.g., running out of high-speed data, trouble keeping the phone charged, not able to answer questions within the two-hour timeframe) that detracted from their experience, especially if they were homeless. Conclusion : Our findings provide methodological considerations for studies with EMA components among at-risk, vulnerable populations, like PWUD. These suggestions are targeted toward the continued ethical collection of high-quality data in clinical and non-clinical settings.

Background: Ecological momentary assessment (EMA) is a set of research methods that capture events, feelings, and behaviors as they unfold in their real-world setting. Capturing data in the moment reduces important sources of measurement error but also generates challenges for noncompliance (ie, missing data). To date, EMA research has only examined the overall rates of noncompliance. Objective: In this study, we identify four types of noncompliance among people who use drugs and aim to examine the factors associated with the most common types. Methods: Data were obtained from a recent pilot study of 28 Nebraskan people who use drugs who answered EMA questions for 2 weeks. We examined questions that were not answered because they were skipped, they expired, the phone was switched off, or the phone died after receiving them. Results: We found that the phone being switched off and questions expiring comprised 93.34% (1739/1863 missing question-instances) of our missing data. Generalized structural equation model results show that participant-level factors, including age (relative risk ratio [RRR]=0.93; P=.005), gender (RRR=0.08; P=.006), homelessness (RRR=3.80; P=.04), personal device ownership (RRR=0.14; P=.008), and network size (RRR=0.57; P=.001), are important for predicting off missingness, whereas only question-level factors, including time of day (ie, morning compared with afternoon, RRR=0.55; P<.001) and day of week (ie, Tuesday-Saturday compared with Sunday, RRR=0.70, P=.02; RRR=0.64, P=.005; RRR=0.58, P=.001; RRR=0.55, P<.001; and RRR=0.66, P=.008, respectively) are important for predicting expired missingness. The week of study is important for both (ie, week 2 compared with week 1, RRR=1.21, P=.03, for off missingness and RRR=1.98, P<.001, for expired missingness). Conclusions: We suggest a three-pronged strategy to preempt missing EMA data with high-risk populations: first, provide additional resources for participants likely to experience phone charging problems (eg, people experiencing homelessness); second, ask questions when participants are not likely to experience competing demands (eg, morning); and third, incentivize continued compliance as the study progresses. Attending to these issues can help researchers ensure maximal data quality. [ABSTRACT FROM AUTHOR]