Manual The Science of Real-Time Data Capture: Self-Reports in Health Research

Youth were informed about the study during group sessions or individually approached by research staff.

A high proportion of the youth in treatment were Latino, though eligibility criterion 3 was not a recruitment barrier. All youth we encountered in the treatment setting spoke English; many youth were bilingual, speaking both English and Spanish. For youth younger than 18 years, we obtained parental consent for their participation and youth assent.

Youth who were 18 years and older signed consent forms. In addition, youth who were compliant in responding to CEMA received additional cell phone minutes on a weekly basis. The use of a cell that was provided by the study during the study period and incentivized cell phone minutes generated a high degree of interest in study participation among youth at the treatment setting. There were only two reasons that interested youth were not enrolled in the study. Some parent s did not want their children to participate in the study.

Given a limited number of study cell phones and resources, we could only accommodate approximately 15 study participants at any one time. Eligible youth were administered a baseline assessment immediately following a screening interview that was conducted at the outpatient treatment setting in a private area. Afterwards, youth were assigned a mobile phone they would use to respond to a text message-based CEMA. During assignment, youth were trained and practiced filling out the CEMA with research staff.

Wording of the CEMA questions and response choices were informed by focus groups and key informant interviews conducted with youth currently and formerly in treatment. Daily reports have been commonly utilized in prior EMA studies, due in part to reliance on paper diaries that were most tenable for once-a-day reporting. Electronic data capture facilitates event-based and random assessment of events that vary in intensity throughout the day, e. AOD use Shiffman, Further details on the sampling strategies in this study follow:.

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• Compliance to cell phone-based EMA among Latino youth in outpatient treatment?

Over the course of the study, participants were rotated through the four CEMA strategies D, E, R, or C , with a month of participation in each rotation, followed by a month-long rest period in between rotations. During Rotations 3 and 4, we added the C strategy as a test case for another viable CEMA strategy in an adolescent treatment setting.

CEMA strategy assignment was not random and was done at the discretion of the research staff. For example, the E strategy was more likely to be assigned to youth who were newer to the treatment program, more likely to be using AOD, and in turn, more likely to have AOD-usage events to report on throughout the day. After Rotation 1, assignment was carried out to minimize repeating the same CEMA strategy in subsequent rotations.

The flow of study participants through the different EMA strategies is summarized in Figure 1. We allowed participants to enroll during any of the rotations. Eleven participants were enrolled in Rotation 1. Four of 11 participants who started in Rotation 1 completed all four possible rotations. Flow of study participants through four rotations by assigned assessment modality: An overview of the assessment is shown in Figure 2 , including the order of the questions and conditional branching of questions based on participant responses.

The R assessment questions covered time periods since the last assessment and events that were currently happening. The majority of the CEMA questions were multiple choice. For example, the final stem question in the D assessment was displayed in text-message format as follows: Some questions allowed for unique responses e. Outline of CEMA structure showing the order of the questions, conditional branching of questions based on study participant responses, and the number of questions in each branch n.

Question prompts were repeated if a text message response was not sent within three minutes of the prompt. Non-response to the second question prompt resulted in an incomplete assessment for the day if a response was not within 24 hours. Overall, response times were reasonable. Median completion times were 8 minutes for D assessment, 16 minutes for R assessment, and minutes for E assessment. As shown in Figure 2 , the E assessment was designed to be longer.

Initial questions to ascertain current AOD use were followed by a three-hour recovery period. Afterwards, more detailed questions were prompted. Participants also took more than three hours to complete nine percent of the D and R assessments, which was an unanticipated result of the flexible response times that were permitted.

The first item queried participants on AOD use during the past 12 months. TLFB was administered both at baseline and at the end of each rotation during the study period. Depending on the assessment strategy, the questions differed on how participants were instructed to recall last drug use, e.

Participants were asked if they used drugs in parallel time frames to alcohol consumption. Participants indicating marijuana use were also asked two additional questions: Participants indicating sexual activity were then asked three additional questions: Participants were asked when they used e. Analyses on a three-category indicator of compliance would have been impractical. For the E assessment strategy, non-compliance 0 could only result from partially completed CEMA, since E assessments were initiated by study participants. Given the different definition of compliance, E assessments were not included in statistical analyses on compliance.

Bestselling Series

For the C assessment strategy, analyses grouped daily assessments with assessments that originated from the D assessment strategy; E assessments were grouped similarly. This seemed reasonable, since levels of compliance did not significantly differ for daily assessments that were collected during the D and C strategies. A key study design feature was the rotation of study participants through different sampling strategies. This within-subjects study design potentially reduced variability on comparisons between sampling strategies relative to a study design that would have compared sampling strategies between separate groups of individuals.

In turn, within-subjects comparisons offer greater statistical power relative to comparisons on independent groups. All regression models included random-effects RE at the participant-level to properly model correlations between repeated compliance data points on the same participant over time. RE multinomial logistic regression was used to estimate the probability of assignment to CEMA assessment strategy in order to check for imbalances across background characteristics that may have resulted from non-random assessment strategy assignment.

F-statistics, degrees of freedom, and p-values are presented for omnibus tests of differences between at least two assessment strategies. We present t-tests, degrees of freedom, and p-values for regression coefficients. The predictive margin is estimated as the average difference in the probability of compliance between different response values for a given covariate in x , e.

All analyses were conducted in SAS software Version 9. No one reported using barbiturates, sedatives, heroin, or injecting drugs. Half of the 12 participants reporting the use of other drugs also reported using multiple drugs. On average, participants endorsed 5. Table 1 summarizes baseline characteristics across CEMA assessment strategies as a visual check for imbalances that may have resulted from non-random assignment.

No obvious differences were observed. There were a total of CEMA prompts that were received during daily D and random R assessment strategies or initiated during event-based assessment strategies E by the 28 participants over the study. The number of prompts closely matched the total number of days that study participants were in the study roughly 30 days for each rotation in Figure 1 , except for days where multiple event-based assessments were initiated or a daily and event-based assessment were filled out by participants assigned to the combination C assessment strategy.

Prompts excluded from the analysis data resulted from glitches in the preprogrammed algorithm for administering the text-message CEMA and nonsensical response patterns that made compliance difficult to calculate, e. Table 2 shows the median and maximum number of days of AOD use and percentage out of the total number of reporting days that was reported by each participant. Regardless of the reporting mechanism, reports of use were fairly low.

Half of the participants reporting using alcohol or marijuana for three or fewer days and did not report any use of other drugs during the study period. As indicated in Table 2 , reports of use were quite low across most substances, making meaningful comparisons difficult. Table 3 summarizes the observed compliance data and shows high compliance across assessment days by CEMA strategy D, E, and R and rotation. Compliance was regressed on the following covariates in separate models: Other drugs were not included, due to low rates of reporting Table 2.

None of the demographic and baseline characteristics were significantly associated with compliance. Two-way interactions between remaining covariates were also tested in the model; none were significant. Results of the final model are shown in Table 4. The ratio between the generalized Chi-square statistic and its degrees of freedom for the final model is 0. A value greater than one would indicate over-dispersion in the data or model misspecification. Regression coefficient effects were in the same direction as they were in single-predictor models.

Therefore, interpretation is the same. In terms of predicted probabilities, significant differences were relatively small. Compliance was estimated to be 4. Similarly, compliance was estimated to be 5.

Two aspects of our study highlight the potential of CEMA as a tool for use in outpatient treatment with adolescents. Higher CEMA compliance rates in treatment settings may benefit from the self-selection of motivated individuals who participate in treatment programs. Given the paucity of CEMA studies that have been conducted in treatment settings, further study is needed before conclusions can be drawn.

Higher CEMA compliance rates we found in our study relative to non-CEMA assessment strategies in other non-patient Latino populations may also partly be due to the self-selection of motivated individuals in our sample. Second, text message-based assessment that was utilized in our studyis easily scaled to treatment programs where patients use their own cell phones; smartphone features were not required.

The ability to tailor text messages and CEMA, in general, is another important feature of cell phone delivery that opens the door for CEMA across treatment populations of different cultural and ethnic origins. Text messages in our study were written in English in line with the English-speaking population in the study clinic. Text messages can easily accommodate Spanish and other languages, as well as cultural nuances in the wording of questions.

Text message-based assessment can handle fairly complex skip patterns as we demonstrated in our study to address differing levels of engagement in AOD use and sexual encounters. Similarly, Rodgers et al. As hypothesized, we found decreases in compliance over the study period and on days when alcohol use was reported. A ten percent decrease in the probability of compliance was predicted for days when alcohol use was reported. Unfortunately, use of other substances was too low to adequately test for similar associations between use and non-compliance.

Lower levels of compliance in the random R strategy compared to the daily D strategy was unexpected. Non-random assignment to the assessment strategies makes the impact of strategy on compliance difficult to interpret. As a potentially related issue, the median assessment completion time was twice as long for the R versus the D assessment strategy.

We do not have an explanation for this. The median R assessment completion time does not decrease if we exclude participants who indicated using AOD now, which could have partly explained the longer median completion time. R assessment generally resulted in a larger number of questions than D assessment for comparable AOD and sexual behavioral patterns, but not enough to reasonably explain the difference in median completion times between R and D assessment. For example, a participant in the R strategy who indicating drinking beer, using marijuana, and engaging in sex since their last survey, but not using alcohol or drugs now was prompted to answer 26 questions.

A comparable participant in the D strategy was prompted to answer 20 questions. It is also important to acknowledge that the R strategy only prompted participants once a day, done in part because participants were likely to be in school at earlier times of the day. We cannot tell how a multiple-times-per-day R strategy would perform against a D strategy in terms of compliance.

More intensive assessment offers more opportunities to respond but may be offset by introducing additional burden. Of course, a once-a-day assessment may not give a reliable picture of behaviors throughout the day. Clinicians are left with a delicate balancing act between the ability to minimize participant burden and potentially obtain better information. This points to the importance of considering synergistic effects between the timing of CEMA prompts throughout the day and the time frame over which the CEMA is conducted when designing a plan to support a treatment program.

Questions around information utility for treatment providers and patient self-management support are high priorities for future research. A number of study limitations need to be acknowledged. Our study sample was small and use of AOD was relatively low. Examining potential biases that were introduced by non-random assignment to CEMA assessment strategies was difficult as statistical comparisons of baseline characteristics and AOD use between assessment strategies was underpowered.

As noted by Shiffman , EMA needs to be tested on the spectrum of drug users. This is certainly needed in a larger sample of Latino youth in outpatient treatment before conclusions can really be drawn on the impact AOD use and other factors on compliance. Despite these limitations, our study provided an important proof-of-concept for the administration of text message-based CEMA in adolescent outpatient settings.

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Participants were rotated through daily, random, and event-based CEMA strategies for 1-month periods. The snippet could not be located in the article text. This may be because the snippet appears in a figure legend, contains special characters or spans different sections of the article. J Ethn Subst Abuse. Author manuscript; available in PMC Jul 1.

Scott Comulada , Dr. See other articles in PMC that cite the published article. Abstract Outpatient treatment practices for adolescent substance users utilize retrospective self-report to monitor drug use. Log in via OpenAthens. Log in using your username and password For personal accounts OR managers of institutional accounts. Forgot your log in details? Register a new account? Forgot your user name or password? Search for this keyword. Latest content Current issue Archive Authors About. Log in via Institution. A dictionary of public health. Edited by John M Last.

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