Collecting Data from a Vulnerable Population during the COVID-19 Pandemic

Harcey, Sela R.; Gauthier, G. Robin; Markowski, Kelly L.; Smith, Jeffrey A.

doi:10.31235/osf.io/af2sr

Cited by 3 publications

(2 citation statements)

References 13 publications

(15 reference statements)

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“…In our case, we contacted participants midway through the study (eg, at the end of the first week) to alert them of the number of questions answered and compensation earned. More involved interactions were not possible because COVID-19 protocols limited the number of face-to-face interactions between participants and field staff [ 26 ]. We expect that more extensive check-ins and compensation opportunities may reinvigorate study commitment and engagement [ 33 ].…”

Section: Discussionmentioning

confidence: 99%

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Patterns of Missing Data With Ecological Momentary Assessment Among People Who Use Drugs: Feasibility Study Using Pilot Study Data

Markowski¹,

Smith²,

Gauthier³

et al. 2021

JMIR Form Res

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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.

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Section: Discussionmentioning

confidence: 99%

“…The study also tested the feasibility of using a smartphone-based EMA app, called the Open Dynamic Interaction Network (ODIN) [ 24 , 25 ], among this population. As our data were collected during the COVID-19 pandemic, extensive health and safety protocols were followed to maximize safety and minimize transmission risk [ 26 ].…”

Section: Methodsmentioning

confidence: 99%

Patterns of Missing Data With Ecological Momentary Assessment Among People Who Use Drugs: Feasibility Study Using Pilot Study Data

Markowski¹,

Smith²,

Gauthier³

et al. 2021

JMIR Form Res

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View full text Add to dashboard Cite

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Practical problems and positive experiences with ecological momentary assessment: reflections from people who use drugs

Markowski

Smith

Gauthier

et al. 2021

The American Journal of Drug and Alcohol Abuse

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Patterns of Missing Data With Ecological Momentary Assessment Among People Who Use Drugs: Feasibility Study Using Pilot Study Data (Preprint)

Markowski¹,

Smith²,

Gauthier³

et al. 2021

Preprint

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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. CLINICALTRIAL

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Collecting Data from a Vulnerable Population during the COVID-19 Pandemic

Cited by 3 publications

References 13 publications

Patterns of Missing Data With Ecological Momentary Assessment Among People Who Use Drugs: Feasibility Study Using Pilot Study Data

Patterns of Missing Data With Ecological Momentary Assessment Among People Who Use Drugs: Feasibility Study Using Pilot Study Data

Practical problems and positive experiences with ecological momentary assessment: reflections from people who use drugs

Patterns of Missing Data With Ecological Momentary Assessment Among People Who Use Drugs: Feasibility Study Using Pilot Study Data (Preprint)

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