Designing and Validating a Novel Method for Assessing Delay Discounting Associated With Health Behaviors: Ecological Momentary Assessment Study.

BACKGROUND: Delay discounting quantifies an individual's preference for smaller, short-term rewards over larger, long-term rewards and represents a transdiagnostic factor associated with numerous adverse health outcomes. Rather than a fixed trait, delay discounting may vary over time and place, influenced by individual and contextual factors. Continuous, real-time measurement could inform adaptive interventions for various health conditions. OBJECTIVE: The goals of this paper are 2-fold. First, we present and validate a novel, short, ecological momentary assessment (EMA)-based delay discounting scale we developed. Second, we assess this tool's ability to reproduce known associations between delay discounting and health behaviors (ie, substance use and craving) using a convenience-based sample. METHODS: Participants (N=97) were adults (age range 18-71 years), recruited on social media. In phase 1, data were collected on participant sociodemographic characteristics, and delay discounting was evaluated via the traditional Monetary Choice Questionnaire (MCQ) and our novel method (ie, 7-item time-selection and 7-item monetary-selection scales). During phase 2 (approximately 6 months later), participants completed the MCQ, our novel delay discounting measures, and health outcomes questions. The correlations between our method and the traditional MCQ within and across phases were examined. For scale reduction, a random number of items were iteratively selected, and the correlation between the full and random scales was assessed. We then examined the association between our time- and monetary-selection scales assessed during phase 2 and the percentage of assessments that participants endorsed using or craving alcohol, tobacco, or cannabis. RESULTS: In total, 6 of the 7 individual time-selection items were highly correlated with the full scale (r>0.89). Both time-selection (r=0.71; P<.001) and monetary-selection (r=0.66; P<.001) delay discounting rates had high test-retest reliability across phases 1 and 2. Phase 1 MCQ delay discounting function highly correlated with phase 1 (r=0.76; P<.001) and phase 2 (r=0.45; P<.001) time-selection delay discounting scales. One or more randomly chosen time-selection items were highly correlated with the full scale (r>0.94). Greater delay discounting measured via the time-selection measure (adjusted mean difference=5.89, 95% CI 1.99-9.79), but not the monetary-selection scale (adjusted mean difference=-0.62, 95% CI -3.57 to 2.32), was associated with more past-hour tobacco use endorsement in follow-up surveys. CONCLUSIONS: This study evaluated a novel EMA-based scale's ability to validly and reliably assess delay discounting. By measuring delay discounting with fewer items and in situ via EMA in natural environments, researchers may be better able to identify individuals at risk for poor health outcomes.

Using Smartphone Survey and GPS Data to Inform Smoking Cessation Intervention Delivery: Case Study.

BACKGROUND: Interest in quitting smoking is common among young adults who smoke, but it can prove challenging. Although evidence-based smoking cessation interventions exist and are effective, a lack of access to these interventions specifically designed for young adults remains a major barrier for this population to successfully quit smoking. Therefore, researchers have begun to develop modern, smartphone-based interventions to deliver smoking cessation messages at the appropriate place and time for an individual. A promising approach is the delivery of interventions using geofences-spatial buffers around high-risk locations for smoking that trigger intervention messages when an individual's phone enters the perimeter. Despite growth in personalized and ubiquitous smoking cessation interventions, few studies have incorporated spatial methods to optimize intervention delivery using place and time information. OBJECTIVE: This study demonstrates an exploratory method of generating person-specific geofences around high-risk areas for smoking by presenting 4 case studies using a combination of self-reported smartphone-based surveys and passively tracked location data. The study also examines which geofence construction method could inform a subsequent study design that will automate the process of deploying coping messages when young adults enter geofence boundaries. METHODS: Data came from an ecological momentary assessment study with young adult smokers conducted from 2016 to 2017 in the San Francisco Bay area. Participants reported smoking and nonsmoking events through a smartphone app for 30 days, and GPS data was recorded by the app. We sampled 4 cases along ecological momentary assessment compliance quartiles and constructed person-specific geofences around locations with self-reported smoking events for each 3-hour time interval using zones with normalized mean kernel density estimates exceeding 0.7. We assessed the percentage of smoking events captured within geofences constructed for 3 types of zones (census blocks, 500 ft2 fishnet grids, and 1000 ft2 fishnet grids). Descriptive comparisons were made across the 4 cases to better understand the strengths and limitations of each geofence construction method. RESULTS: The number of reported past 30-day smoking events ranged from 12 to 177 for the 4 cases. Each 3-hour geofence for 3 of the 4 cases captured over 50% of smoking events. The 1000 ft2 fishnet grid captured the highest percentage of smoking events compared to census blocks across the 4 cases. Across 3-hour periods except for 3:00 AM-5:59 AM for 1 case, geofences contained an average of 36.4%-100% of smoking events. Findings showed that fishnet grid geofences may capture more smoking events compared to census blocks. CONCLUSIONS: Our findings suggest that this geofence construction method can identify high-risk smoking situations by time and place and has potential for generating individually tailored geofences for smoking cessation intervention delivery. In a subsequent smartphone-based smoking cessation intervention study, we plan to use fishnet grid geofences to inform the delivery of intervention messages.

Impact of early, weekly drinking on latent classes of alcohol involvement progression and recovery: Evidence from the NESARC Waves 1 and 2.

INTRODUCTION: Early drinkers have been found to have higher risk of developing alcohol use disorder; however, the association of early drinking with progression to problematic alcohol involvement that does not meet disorder criteria (i.e., subclinical problems) or to severe stages of alcohol involvement, sex-specific associations, and relationship of early drinking with alcohol recovery have rarely been investigated. METHODS: Using data from Waves 1 and 2 of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), we applied latent transition analyses to investigate the impact of weekly drinking before age 18 on alcohol progression and recovery operationalized as three classes of alcohol involvement using abuse and dependence indicators. We analyzed data separately for male (n = 12,276) and female (n = 14,750) drinkers and applied propensity score methods to address confounding. RESULTS: We observed significant associations between early, weekly drinking and alcohol involvement class membership at Wave 1 for both males and females. For males, early, weekly drinking was also associated with greater odds of transitioning from moderate to severe alcohol problems (aOR = 3.19, 95% CI = 1.72, 5.35). For females, early, weekly drinking predicted the transition from no to severe problems (aOR = 2.98, 95% CI = 1.11-8.00). Contrary to our hypothesis, early, weekly drinking was associated with greater likelihood of transition from severe to no problems for males (aOR = 3.23, 95% CI = 1.26, 8.26). DISCUSSION: Frequent, early drinking seems to be an important indicator of drinking progression with differential associations by sex. This information is useful to identify those at greater risk of progressing to severe drinking problems to intervene appropriately.

Electronic cigarette and cannabis use: results from the 2018 Maryland Youth Risk Behavior Survey.

OBJECTIVE: To determine the relationship between lifetime e-cigarette use and current cannabis use among youth. Our analyses accounted for county variability, in addition to student-level covariates. METHODS: This study examined responses from high school students on a state-level population survey, the 2018 Maryland Youth Risk Behavior Survey/Youth Tobacco Survey, a cross-sectional, complex survey sample. Of participating students, final analyses included an unweighted sample of 41,091 9th to 12th grade students who provided complete reports for measured variables. Analyses with survey weights were conducted between August 2019 and May 2020. A multivariable logistic regression was conducted to investigate the association between lifetime e-cigarette use and current (past 30-day) cannabis use, after controlling for county, lifetime cigarette use, current (past 30-day) alcohol use, emotional distress, and demographics. RESULTS: Lifetime e-cigarette use significantly increased the odds of current cannabis use among Maryland high school students (aOR = 6.04; 95% CI 5.27, 6.93). Other significant risk factors for current cannabis use included lifetime cigarette use (aOR 2.23, 95% CI 1.86, 2.68) and current alcohol use (aOR 5.21, 95% CI 4.42, 6.14). Significantly higher odds of current cannabis use were also found among older high school students, males, non-Hispanic Blacks and students identifying as other race, and those reporting emotional distress. CONCLUSIONS: Lifetime e-cigarette use among Maryland high school students is strongly associated with current cannabis use when including counties as a covariate. Non-significant county differences, however, suggest smaller geographical units may be required to control for variability. Efforts should focus on reducing youth e-cigarette use to decrease cannabis use. Maryland's recent implementation of Tobacco 21 and a ban on flavored e-cigarettes will be of interest for future evaluations.

On Racial Disparities in Child Abuse Reports: Exploratory Mapping the 2018 NCANDS.

Research suggests children from non-White and Hispanic/Latinx communities are at higher risk for child maltreatment. This study identified in which states children from specific non-White communities were overrepresented in child protective services reports for child physical, sexual, and emotional/psychological abuse through exploratory mapping. Reports on child maltreatment originated from the 2018 National Child Abuse and Neglect Data System and state-level population estimates from the U.S. Census Bureau. Racial disparities were identified in states with unequal proportions of reported child maltreatment among a non-White child population compared to the proportion among the White child population. We found disparities for children from non-White communities in many states, especially for Black communities (Disparity Ratio [DR]: 15.10 for child physical abuse, DR: 12.77 for child sexual abuse in Washington DC, and DR: 5.25 for child emotional/psychological abuse in California). The ability to identify high disparities among Pacific Islanders highlights one of the study's strengths, given we separately examined Asian Americans, Pacific Islanders and multiracial communities. Results from our exploratory mapping provide insight into how preventive resources might be differentially allocated to non-White communities with higher child protective services reporting compared with White communities, and manifest states with multiple non-White communities overrepresented across maltreatment types.