Identification of Child Survivors of Sex Trafficking From Electronic Health Records: An Artificial Intelligence Guided Approach.

Survivors of child sex trafficking (SCST) experience high rates of adverse health outcomes. Amidst the duration of their victimization, survivors regularly seek healthcare yet fail to be identified. This study sought to utilize artificial intelligence (AI) to identify SCST and describe the elements of their healthcare presentation. An AI-supported keyword search was conducted to identify SCST within the electronic medical records (EMR) of ∼1.5 million patients at a large midwestern pediatric hospital. Descriptive analyses were used to evaluate associated diagnoses and clinical presentation. A sex trafficking-related keyword was identified in .18% of patient charts. Among this cohort, the most common associated diagnostic codes were for Confirmed Sexual/Physical Assault; Trauma and Stress-Related Disorders; Depressive Disorders; Anxiety Disorders; and Suicidal Ideation. Our findings are consistent with the myriad of known adverse physical and psychological outcomes among SCST and illuminate the future potential of AI technology to improve screening and research efforts surrounding all aspects of this vulnerable population.

Assessment of US Federal Funding of Incarceration-Related Research, 1985 to 2022.

Importance: The US leads the world in the raw number of incarcerated persons as well as the rate of incarceration, with detrimental effects on individual-, family-, community-, and population-level health; as such, federal research has a critical role in documenting and addressing the health-related impacts of the US criminal legal system. How often incarceration-related research is funded at the National Institutes of Health (NIH), National Science Foundation (NSF), and US Department of Justice (DOJ) levels has a direct association with the public attention given to mass incarceration as well as the efficacy of strategies to mitigate negative effects and poor health related to incarceration. Objective: To understand how many incarceration-related projects have been funded at the NIH, NSF, and DOJ. Design, Setting, and Participants: This cross-sectional study used public historical project archives to search for relevant incarceration-related keywords (eg, incarceration, prison, parole) since January 1, 1985 (NIH and NSF), and since January 1, 2008 (DOJ). Quotations and Boolean operator logic were used. All searches and counts were conducted and double verified by 2 coauthors between December 12 and 17, 2022. Main Outcomes and Measures: Number and prevalence of funded projects related to incarceration and prison keywords. Results: The term incarceration resulted in 3540 of 3 234 159 total project awards (0.11%) and prisoner-related terms resulted in 11 455 total project awards (0.35%) across the 3 federal agencies since 1985. Nearly a tenth of all projects funded at NIH since 1985 related to education (256 584 [9.62%]) compared with only 3373 projects (0.13%) that related to criminal legal or criminal justice or correctional system and 18 projects (0.0007%) that related to incarcerated parents. Only 1857 (0.07%) of all NIH-funded projects have been funded related to racism since 1985. Conclusions and Relevance: This cross-sectional study found that a very low number of projects about incarceration have historically been funded at the NIH, DOJ, and NSF. These findings reflect a dearth of federally funded studies investigating the effects of mass incarceration or intervention strategies to mitigate adverse effects. Given the consequences of the criminal legal system, it is undoubtedly time for researchers, and our nation, to invest more resources into studying whether this system should be maintained, the intergenerational effects of mass incarceration, and strategies to best mitigate its impact on public health.

Exploration of Differences between Women Who Do and Do Not Disclose Their Marijuana Use during Pregnancy.

OBJECTIVE: This study aimed to explore demographic and health-related factors that may differentiate women who do and do not disclose their marijuana use during pregnancy. STUDY DESIGN: The current study is a secondary analysis of data from a prospective cohort of pregnant women identified as using marijuana during pregnancy via a variety of assessment tools including self-report, urine screen, and obstetrics record abstraction. The cohort included a convenience sample of women recruited from several antenatal clinics at The Ohio State University Wexner Medical Center (OSUWMC). To be eligible, women needed to be within the first or second trimester of their pregnancy, 16 to 50 years of age, able to communicate in English, and intended to deliver at OSUWMC. Chi-square, independent samples t-tests, and logistic regression analyses were used to explore differences between those who did and did not disclose their use in relation to physical and mental health diagnoses, adverse experiences, use of other substances, and demographics. RESULTS: Women who used marijuana during their pregnancy and had mental/physical health data available comprised the current sample (n = 109). Women who attended college were more likely to disclose their marijuana use compared with women who did not attend college (p < 0.001). Women who experienced homelessness (p < 0.01) or self-reported alcohol use during pregnancy (p < 0.001) were significantly more likely to disclose their marijuana use. CONCLUSION: Findings, suggesting disclosure of other substance use and adverse experiences, such as homelessness, may increase the likelihood that pregnant women will voluntarily disclose their marijuana use to providers. Findings did not reflect racial differences nor significant differences in mental/physical health status among women based on their disclosure. Future research with larger datasets is needed to build on these findings by confirming results, as well as exploring additional factors, that may more effectively differentiate women who are unlikely to disclose their prenatal marijuana use from those who do disclose their use. KEY POINTS: · Women with higher education were more likely to self-disclose their prenatal marijuana use.. · Women who experienced homelessness were more likely to self-disclose their prenatal marijuana use.. · Self-disclosure of prenatal alcohol use was related to self-disclosure of prenatal marijuana use.

Marijuana use and sleep quality during pregnancy.

OBJECTIVE: Marijuana use among pregnant women is on the rise in part due to the perception that marijuana may improve problems related to pregnancy such as poor sleep. This study's objective was to examine associations between marijuana use and sleep quality among a sample of women during pregnancy. MATERIAL AND METHODS: The sample included women seeking prenatal care at The Ohio State University Wexner Medical Center (2010-2015). Intake assessments included medical, demographic, and socioeconomic domains, as well as the Pittsburgh Sleep Quality Index. Marijuana use during pregnancy was determined using urine screens, chart abstraction, and self-report. Women completed standardized questionnaires regarding sleep quality, depressive symptoms, anxiety, stress, and discrimination at enrollment and each subsequent trimester. A linear mixed-effect model was used to assess the relationship between sleep variables and marijuana use adjusted for maternal race, education, household income, age, marital status, depressive symptoms, anxiety, stress, discrimination, and use of tobacco and other substances during pregnancy. Women completed the sleep quality assessments for a total of 294 pregnancies, which comprise the study population. RESULTS: Among the study sample (n = 294), 93 women used marijuana and 201 women did not use marijuana during their pregnancies. Women who used marijuana (n = 93) were more likely to identify as African-American (73% vs 58%; p = .01), report government health insurance (98% vs 89%; p = .001), use tobacco during pregnancy (66% vs 33%; p < .001), report less household income (70% vs 43% < 10,000 annual household income; p < .001), and be unmarried (69% vs 49%; p < .001) compared to women who did not. Mean sleep quality was similar among women who did (µ = 7.6; SD = 4.0) and did not use marijuana during pregnancy (µ = 7.7; SD = 4.0), and both groups had a mean score worse than the conventional cutoff for poor sleep quality (>5). In fact, both groups reported worse sleep than is typically observed among cohorts reporting poor sleep, which have ranged from 5.3 to 6.3. CONCLUSIONS: Current findings did not suggest differences in sleep quality between women who used and did not use marijuana during pregnancy. Findings are contrary to the perception that marijuana use alleviates sleep-related problems during pregnancy. Given well-documented adverse outcomes associated with prenatal marijuana exposure for children and the increase in women using marijuana during pregnancy, providers should be prepared to discuss possible harms associated with marijuana use during pregnancy as well as provide psychoeducational information and service referrals to those interested. Future studies could improve upon this design by assessing objective measures of sleep, such as actigraphy, as well as marijuana use repeatedly throughout pregnancy, which may be a more optimal strategy for illuminating potential relationships between marijuana use and sleep during pregnancy.

Behavioral and Cognitive Differences in Early Childhood related to Prenatal Marijuana Exposure.

Prenatal marijuana exposure (PME) negatively impacts child development and behavior; however, few studies have examined these associations at early ages among children exposed to today's highly potent marijuana. Using a prospective prenatal cohort (Columbus, Ohio, USA), PME was determined from maternal self-report, medical chart abstraction, and urine toxicology from prenatal visits and delivery. At age 3.5 years, 63 offspring children completed tasks assessing executive function (EF), visual spatial ability, emotion regulation, and aggressive behavior. Caregivers reported on children's EF and problem behaviors. Logistic regressions and analyses of covariance controlling for key variables were used to examine associations between PME and child outcomes. Compared to non-exposed children, children with PME had more sleep-related problems, withdrawal symptoms, and externalizing problems, including aggressive behaviors and oppositional defiant behaviors. Children with and without PME did not differ in terms of executive functioning. Findings suggest behavioral problems associated with PME may manifest by age 3.5.