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.

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.

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 This study sought to determine the validity and reliability of a novel, continuous, smartphone ecological momentary assessment (EMA)-based survey to measure delay discounting; to identify the fewest survey questions necessary to sufficiently capture delay discounting; and to determine the survey’s ability to reproduce established associations between delay discounting and substance use/cravings. 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 (i.e., 7-item time- 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. We examined correlations between our method and the traditional MCQ within and across Phases. For scale reduction, we iteratively selected a random number of items and assessed the correlation between the full and random scales. We then examined the association between our time- and monetary-selection scales assessed during Phase 2 and the percent of assessments that participants endorsed using or craving alcohol, tobacco, or cannabis. RESULTS Six of the seven individual time-selection items were highly correlated with the full scale (r>0.89). Both time- (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 implement real-time interventions to mitigate adverse health outcomes.

BACKGROUND The use of spatial methods to inform smartphone-based smoking cessation intervention delivery has been understudied. Such methods can facilitate person- and time-specific intervention delivery. OBJECTIVE This study aims to demonstrate an exploratory method of generating person-specific geofences around high-risk smoking areas for a smoking cessation intervention by presenting four case studies. METHODS Data came from an Ecological Momentary Assessment (EMA) study with young adult smokers conducted from 2016 to 2017 in the San Francisco Bay Area. Participants reported smoking and non-smoking events through a smartphone app for 30 days and GPS data we recorded by the app. We sampled four cases along EMA compliance quartiles and constructed person-specific geofences around locations with self-reported smoking events for each three-hour time interval around zones with normalized mean kernel density estimates exceeding 0.7. We assessed the percentage of smoking events captured within geofences constructed for three types of zones (Census blocks; 500 ft.2 and 1,000 ft.2 fishnet grids). RESULTS Geofences constructed for all three types of zones captured over 50% of smoking events for three of the four cases. Of the three types of zones, the 1,000 ft2 fishnet grid captured the highest percentage of smoking events across the four cases. Across three-hour time intervals, the average percentage of smoking events within geofences ranged from 36.4% – 100.0%. CONCLUSIONS This method can identify high-risk smoking situations by time and place and automatically generate individually-tailored geofences for smoking cessation intervention delivery. Our findings suggest that fishnet grid geofences may capture more smoking events compared to Census blocks. We plan to use fishnet grid geofences to inform delivery of a smartphone-based smoking cessation intervention.

Highlights: Weekly drinking before age 18 seems to impact alcohol progression over time. For females, extreme transitions from no problems to severe problems were impacted. For males, transitions from moderate to severe alcohol problems were impacted. Early, weekly drinking also predicted increased recovery for males.