Investigating Best Practices for Ecological Momentary Assessment: Nationwide Factorial Experiment.

BACKGROUND: Ecological momentary assessment (EMA) is a measurement methodology that involves the repeated collection of real-time data on participants' behavior and experience in their natural environment. While EMA allows researchers to gain valuable insights into dynamic behavioral processes, the need for frequent self-reporting can be burdensome and disruptive. Compliance with EMA protocols is important for accurate, unbiased sampling; yet, there is no "gold standard" for EMA study design to promote compliance. OBJECTIVE: The purpose of this study was to use a factorial design to identify optimal study design factors, or combinations of factors, for achieving the highest completion rates for smartphone-based EMAs. METHODS: Participants recruited from across the United States were randomized to 1 of 2 levels on each of 5 design factors in a 2×2×2×2×2 design (32 conditions): factor 1-number of questions per EMA survey (15 vs 25); factor 2-number of EMAs per day (2 vs 4); factor 3-EMA prompting schedule (random vs fixed times); factor 4-payment type (US $1 paid per EMA vs payment based on the percentage of EMAs completed); and factor 5-EMA response scale type (ie, slider-type response scale vs Likert-type response scale; this is the only within-person factor; each participant was randomized to complete slider- or Likert-type questions for the first 14 days or second 14 days of the study period). All participants were asked to complete prompted EMAs for 28 days. The effect of each factor on EMA completion was examined, as well as the effects of factor interactions on EMA completion. Finally, relations between demographic and socioenvironmental factors and EMA completion were examined. RESULTS: Participants (N=411) were aged 48.4 (SD 12.1) years; 75.7% (311/411) were female, 72.5% (298/411) were White, 18.0% (74/411) were Black or African American, 2.7% (11/411) were Asian, 1.5% (6/411) were American Indian or Alaska Native, 5.4% (22/411) belonged to more than one race, and 9.6% (38/396) were Hispanic/Latino. On average, participants completed 83.8% (28,948/34,552) of scheduled EMAs, and 96.6% (397/411) of participants completed the follow-up survey. Results indicated that there were no significant main effects of the design factors on compliance and no significant interactions. Analyses also indicated that older adults, those without a history of substance use problems, and those without current depression tended to complete more EMAs than their counterparts. No other demographic or socioenvironmental factors were related to EMA completion rates. Finally, the app was well liked (ie, system usability scale score=82.7), and there was a statistically significant positive association between liking the app and EMA compliance. CONCLUSIONS: Study results have broad implications for developing best practices guidelines for future studies that use EMA methodologies. TRIAL REGISTRATION: ClinicalTrials.gov number NCT05194228; https://clinicaltrials.gov/study/NCT05194228.

Project phoenix: Pilot randomized controlled trial of a smartphone-delivered intervention for people who are not ready to quit smoking.

BACKGROUND: Most people who smoke cigarettes report they want to quit in the future, but only 20 % are ready to quit within the next 30 days. This 3-arm pilot randomized controlled trial examined the feasibility and initial efficacy of a novel smartphone-based intervention that aimed to induce smoking cessation attempts among adults not initially ready to quit. METHODS: Participants randomized into the two intervention groups (Group 1: Phoenix App Only; Group 2: Phoenix App + Nicotine Replacement Therapy) received daily smoking cessation messages via smartphone application that were tailored to their current readiness to quit, while the attention control group (i.e., Factoid) received messages not related to smoking cessation. All participants completed a weekly survey for 26 weeks and used the app to set quit dates when/if desired. RESULTS: Participants (N=152) were female (67.8 %), White (75.7 %), 50.0 years old (SD=12.5), and smoked 20.4 cigarettes per day (SD=10.5). Results indicated that the Phoenix interventions were feasible (e.g., participants viewed ~185 messages over 26 weeks; 74.8 % of weekly surveys were completed; 85.5 % completed the 26-week follow-up assessment). Phoenix participants set more quit dates, set quit dates sooner, were abstinent for more days, and used smoking cessation medications on more days than those assigned to the Factoid group. CONCLUSIONS: This low-burden, smartphone-based smoking cessation induction intervention may increase smoking cessation attempts, and may reduce barriers that are encountered with traditional in-person or call-based interventions. TRIAL REGISTRATION: Clinicaltrials.gov number: NCT03405129; https://clinicaltrials.gov/ct2/show/NCT03405129.

Comparison of the Bluetooth iCOquit, piCO, and Vitalograph for the assessment of breath carbon monoxide among adults initiating smoking cessation and standardized canisters.

BACKGROUND: The Bluetooth iCOquit enables remote biochemical verification of smoking status, but its validity among adults attempting to quit smoking is unclear. This study 1) compared the iCOquit, piCO, and Vitalograph sensors to identify device-specific bias, 2) assessed the diagnostic accuracy of the iCOquit for the overall sample and within specific subgroups (sex, race, smoking rate, menthol use), and 3) assessed the validity of iCOquit readings against standardized CO canisters. METHODS: iCOquit devices were tested with human breath samples from individuals seeking treatment for combustible tobacco use (N = 93) attending an in-person clinic visit. Participants provided breath samples via the iCOquit, piCO, and Vitalograph (order randomized). iCOquit devices were also tested using 5 and 10 parts per million (ppm) canisters. RESULTS: The iCOquit underestimated CO and categorized more participants as abstinent relative to the other CO sensors with human breath samples. The results suggested the iCOquit could not be used interchangeably with the other CO devices. Using a cut-off of < 6 ppm, the diagnostic accuracy of the iCOquit (specificity = 94%; sensitivity = 85%) did not vary across demographic/smoking subgroups. Canister tests with the iCOquit suggested good precision (< 1 ppm). CONCLUSIONS: The iCOquit is an affordable option for the remote measurement of CO that provides a reasonably accurate assessment of smoking status of those attempting to quit smoking using abstinence cut-off criteria of < 6 ppm. However, compared to other CO monitors, the iCOquit may underestimate CO, thereby increasing error in assessing abstinence.