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Background: Social behavioral research studies have increasingly shifted to remote recruitment and enrollment procedures. This shifting landscape necessitates evolving best practices to help mitigate the negative impacts of deceptive attempts (eg, fake profiles and bots) at enrolling in behavioral research., Objective: This study aimed to develop and implement robust deception detection procedures during the enrollment period of a remotely conducted randomized controlled trial., Methods: A 32-group (2×2×2×2×2) factorial design study was conducted from November 2021 to September 2022 to identify mobile health (mHealth) survey design features associated with the highest completion rates of smartphone-based ecological momentary assessments (n=485). Participants were required to be at least 18 years old, live in the United States, and own an Android smartphone that was compatible with the Insight app that was used in the study. Recruitment was conducted remotely through Facebook advertisements, a 5-minute REDCap (Research Electronic Data Capture) prescreener, and a screening and enrollment phone call. The research team created and implemented a 12-step checklist (eg, address verification and texting a copy of picture identification) to identify and prevent potentially deceptive attempts to enroll in the study. Descriptive statistics were calculated to understand the prevalence of various types of deceptive attempts at study enrollment., Results: Facebook advertisements resulted in 5236 initiations of the REDCap prescreener. A digital deception detection procedure was implemented for those who were deemed pre-eligible (n=1928). This procedure resulted in 26% (501/1928) of prescreeners being flagged as potentially deceptive. Completing multiple prescreeners (301/501, 60.1%) and providing invalid addresses (156/501, 31.1%) were the most common reasons prescreeners were flagged. An additional 1% (18/1928) of prescreeners were flagged as potentially deceptive during the subsequent study screening and enrollment phone call. Reasons for exclusion at the screening and enrollment phone call level included having an invalid phone type (6/18, 33.3%), completing multiple prescreeners (6/18, 33.3%), and providing an invalid address (5/18, 27.7%). This resulted in 1409 individuals being eligible after all deception checks were completed. Postenrollment social security number checks revealed that 3 (0.6%) fully enrolled participants out of 485 provided erroneous social security numbers during the screening process., Conclusions: Implementation of a deception detection procedure in a remotely conducted randomized controlled trial resulted in a substantial proportion of cases being flagged as potentially engaging in deceptive attempts at study enrollment. The results of the deception detection procedures in this study confirmed the need for vigilance in conducting remote behavioral research in order to maintain data integrity. Implementing systematic deception detection procedures may support study administration, data quality, and participant safety in remotely conducted behavioral research., Trial Registration: ClinicalTrials.gov NCT05194228; https://clinicaltrials.gov/study/NCT05194228., (©Krista M Kezbers, Michael C Robertson, Emily T Hébert, Audrey Montgomery, Michael S Businelle. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 28.01.2025.)

Objective: Cannabis use has increased in the United States as states have legalized/decriminalized recreational and/or medicinal use. The primary aim of this study was to examine daily associations between cannabis use and health (physical activity [PA]) and substance use (alcohol consumption, cigarette use) behaviors., Method: Data from a 28-day nationwide study that prompted daily ecological momentary assessments (EMAs) were used to assess daily cannabis use, moderate-to-vigorous PA (MVPA), alcohol containing drinks consumed, and cigarettes smoked. Only participants who reported cannabis use on at least one day during the study period were included in the analysis (N = 98). Generalized linear mixed models were used to examine associations between cannabis use and same-day health and substance use behaviors while adjusting for race, biological sex, and age., Results: Daily cannabis use was positively associated with daily PA (p = 0.04, 3.31-minute higher PA duration on use vs. non-use days), number of alcohol containing drinks consumed (p = 0.01, 0.45 more drinks on use vs. non-use days), and number of cigarettes smoked (p = 0.01, 0.63 more cigarettes on use vs. non-use days)., Conclusions: This study was among the first to use EMAs to examine associations between daily cannabis use and same-day PA, alcohol consumption, and cigarette use. Overall, findings indicated that daily cannabis use is associated with higher engagement in these daily health and substance use behaviors. Further research is needed to understand mechanisms linking cannabis use with these and other behaviors., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: [Dr. Michael S. Businelle is the primary inventor of the Insight(TM) mHealth Platform, which was used to develop the Exemplar app. Businelle receives royalties related to the Insight(TM) Platform, but he did not receive royalties in this case because he was the study PI. All other authors declare that they have no conflicts of interest]., (Copyright © 2024. Published by Elsevier Ltd.)

Black persons who smoke are recognized as a smoking health disparity group and face higher rates of tobacco-related disease and morbidity. These disparities result from, in part, exposure to minority-related stress, which results in lower rates of quit success. Anxiety sensitivity (AS), which refers to the fear of stress, is associated with lower rates of cessation and impedes quit success among Black adults who smoke. The current study evaluated the feasibility, utilization, acceptability, and initial efficacy of a smoking cessation and AS reduction smartphone application for Black adults with elevated AS who smoke (The Mobile Anxiety Sensitivity Program for Smoking [MASP]). Participants ( N  = 24; 62.50% female; M age  = 47.83 years, SD  = 9.32) participated in a 6-week trial of MASP. Retention was 83.33% at the 6-week follow-up and MASP utilization was high, with all features used by most participants. Participants reported that MASP was acceptable and 25% of participants reported 7-day point-prevalence abstinence, demonstrating strong utility and impact potential. Results also indicated a statistically significant reduction in AS from baseline to follow-up ( p  = .003, Cohen's d =.76). Black persons who smoke with AS may benefit from an accessible, adaptive app with culturally tailored treatment that addressed AS in the context of smoking cessation.

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., (©Michael S Businelle, Emily T Hébert, Dingjing Shi, Lizbeth Benson, Krista M Kezbers, Sarah Tonkin, Megan E Piper, Tianchen Qian. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 12.08.2024.)

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., Competing Interests: Declaration of Competing Interest MSB, DEK, and DV are inventors of the Insight™ mHealth Platform, which was used to develop the app described in this study. The inventors only receive royalties related to the use of the Insight™ platform by investigators affiliated with institutions external to the University of Oklahoma Health Sciences Center, and thus, did not receive royalties for this study., (Copyright © 2024. Published by Elsevier B.V.)

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., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Darla Kendzor reports financial support was provided by National Cancer Institute. Karen Cropsey reports financial support was provided by National Institutes of Health. Jason Oliver reports financial support was provided by National Institute on Drug Abuse. Michael Businelle reports financial support was provided by Oklahoma Tobacco Settlement Endowment Trust. Michael Businelle reports equipment, drugs, or supplies were provided by Bedfont Scientific Ltd. Dr. Karen Cropsey serves as an associate editor for Drug and Alcohol Dependence., (Copyright © 2023 Elsevier B.V. All rights reserved.)