BackgroundEcological momentary assessment (EMA) assesses individuals’ current experiences, behaviors, and moods as they occur in real time and in their natural environment. EMA studies, particularly those of longer duration, are complex and require an infrastructure to support the data flow and monitoring of EMA completion.ObjectiveOur objective is to provide a practical guide to developing and implementing an EMA study, with a focus on the methods and logistics of conducting such a study.MethodsThe EMPOWER study was a 12-month study that used EMA to examine the triggers of lapses and relapse following intentional weight loss. We report on several studies that informed the implementation of the EMPOWER study: (1) a series of pilot studies, (2) the EMPOWER study’s infrastructure, (3) training of study participants in use of smartphones and the EMA protocol and, (4) strategies used to enhance adherence to completing EMA surveys.ResultsThe study enrolled 151 adults and had 87.4% (132/151) retention rate at 12 months. Our learning experiences in the development of the infrastructure to support EMA assessments for the 12-month study spanned several topic areas. Included were the optimal frequency of EMA prompts to maximize data collection without overburdening participants; the timing and scheduling of EMA prompts; technological lessons to support a longitudinal study, such as proper communication between the Android smartphone, the Web server, and the database server; and use of a phone that provided access to the system’s functionality for EMA data collection to avoid loss of data and minimize the impact of loss of network connectivity. These were especially important in a 1-year study with participants who might travel. It also protected the data collection from any server-side failure. Regular monitoring of participants’ response to EMA prompts was critical, so we built in incentives to enhance completion of EMA surveys. During the first 6 months of the 12-month study interval, adherence to completing EMA surveys was high, with 88.3% (66,978/75,888) completion of random assessments and around 90% (23,411/25,929 and 23,343/26,010) completion of time-contingent assessments, despite the duration of EMA data collection and challenges with implementation.ConclusionsThis work informed us of the necessary preliminary steps to plan and prepare a longitudinal study using smartphone technology and the critical elements to ensure participant engagement in the potentially burdensome protocol, which spanned 12 months. While this was a technology-supported and -programmed study, it required close oversight to ensure all elements were functioning correctly, particularly once human participants became involved.
Writing Committee for the REMAP-CAP Investigators IMPORTANCE The evidence for benefit of convalescent plasma for critically ill patients with COVID-19 is inconclusive.OBJECTIVE To determine whether convalescent plasma would improve outcomes for critically ill adults with COVID-19. DESIGN, SETTING, AND PARTICIPANTSThe ongoing Randomized, Embedded, Multifactorial, Adaptive Platform Trial for Community-Acquired Pneumonia (REMAP-CAP) enrolled and randomized 4763 adults with suspected or confirmed COVID-19 between March 9, 2020, and January 18, 2021, within at least 1 domain; 2011 critically ill adults were randomized to open-label interventions in the immunoglobulin domain at 129 sites in 4 countries. Follow-up ended on April 19, 2021. INTERVENTIONSThe immunoglobulin domain randomized participants to receive 2 units of high-titer, ABO-compatible convalescent plasma (total volume of 550 mL ± 150 mL) within 48 hours of randomization (n = 1084) or no convalescent plasma (n = 916). MAIN OUTCOMES AND MEASURESThe primary ordinal end point was organ support-free days (days alive and free of intensive care unit-based organ support) up to day 21 (range, −1 to 21 days; patients who died were assigned -1 day). The primary analysis was an adjusted bayesian cumulative logistic model. Superiority was defined as the posterior probability of an odds ratio (OR) greater than 1 (threshold for trial conclusion of superiority >99%). Futility was defined as the posterior probability of an OR less than 1.2 (threshold for trial conclusion of futility >95%). An OR greater than 1 represented improved survival, more organ support-free days, or both. The prespecified secondary outcomes included in-hospital survival; 28-day survival; 90-day survival; respiratory support-free days; cardiovascular support-free days; progression to invasive mechanical ventilation, extracorporeal mechanical oxygenation, or death; intensive care unit length of stay; hospital length of stay; World Health Organization ordinal scale score at day 14; venous thromboembolic events at 90 days; and serious adverse events. RESULTS Among the 2011 participants who were randomized (median age, 61 [IQR, 52 to 70] years and 645/1998 [32.3%] women), 1990 (99%) completed the trial. The convalescent plasma intervention was stopped after the prespecified criterion for futility was met. The median number of organ support-free days was 0 (IQR, -1 to 16) in the convalescent plasma group and 3 (IQR, -1 to 16) in the no convalescent plasma group. The in-hospital mortality rate was 37.3% (401/1075) for the convalescent plasma group and 38.4% (347/904) for the no convalescent plasma group and the median number of days alive and free of organ support was 14 (IQR, 3 to 18) and 14 (IQR, 7 to 18), respectively. The median-adjusted OR was 0.97 (95% credible interval, 0.83 to 1.15) and the posterior probability of futility (OR <1.2) was 99.4% for the convalescent plasma group compared with the no convalescent plasma group. The treatment effects were consistent across the primary outcome and the 11...
Findings from studies examining self-efficacy and its relationship to weight loss have been inconsistent. We examined self-efficacy specific to changing eating behaviors in the PREFER trial, an 18-month behavioral weight-loss study, to determine if self-efficacy and dietary adherence were associated with weight change, and what impact self-efficacy had on weight change after controlling for adherence. Measurements included the weight efficacy lifestyle (WEL) questionnaire, body weight, self-reported fat gram intake, kilocalorie intake, and adherence to kilocalorie and fat gram goals at baseline, 6, 12, and 18 months. The sample (N = 170) was 88.2% female and 70.0% Caucasian; the mean age was 44.1 years (SD = 8.8). Mean weight loss at 18 months was 4.64% (SD = 6.24) of baseline body weight and the mean increase in self-efficacy was 11.70% (SD = 38.61). Self-efficacy improved significantly over time (p = 0.04) and was associated with weight loss (p = 0.02). Adherence to the fat gram goal was associated with weight loss (p = 0.0003), and self-efficacy remained associated with weight loss after controlling for fat gram adherence (p = 0.0001). Consistent with self-efficacy theory, improvement in self-efficacy over time supported greater weight loss. Adherence to the fat gram goal also influenced weight loss.
Background-The primary form of treatment for obesity today is behavioral therapy. Selfmonitoring diet and physical activity plays an important role in interventions targeting behavior and weight change. The SMART weight loss trial examined the impact of replacing the standard paper record used for self-monitoring with a personal digital assistant (PDA). This paper describes the design, methods, intervention, and baseline sample characteristics of the SMART trial.Methods-The SMART trial used a 3-group design to determine the effects of different modes of self-monitoring on short-and long-term weight loss and on adherence to self-monitoring in a 24-month intervention. Participants were randomized to one of three conditions (1) use of a standard paper record (PR); (2) use of a PDA with dietary and physical activity software (PDA); or (3), use of a PDA with the same software plus a customized feedback program (PDA + FB).Results-We screened 704 individuals and randomized 210. There were statistically but not clinically significant differences among the three cohorts in age, education, HDL cholesterol, blood glucose and systolic blood pressure. At 24 months, retention rate for the first of three cohorts was 90%.Conclusions-To the best of our knowledge, the SMART trial is the first large study to compare different methods of self-monitoring in a behavioral weight loss intervention and to compare the use of PDAs to conventional paper records. This study has the potential to reveal significant details about self-monitoring patterns and whether technology can improve adherence to this vital intervention component.
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