Using decision tree models and comprehensive statewide data to predict opioid overdoses following prison release.

PURPOSE: Identifying predictors of opioid overdose following release from prison is critical for opioid overdose prevention. METHODS: We leveraged an individually linked, state-wide database from 2015-2020 to predict the risk of opioid overdose within 90 days of release from Massachusetts state prisons. We developed two decision tree modeling schemes: a model fit on all individuals with a single weight for those that experienced an opioid overdose and models stratified by race/ethnicity. We compared the performance of each model using several performance measures and identified factors that were most predictive of opioid overdose within racial/ethnic groups and across models. RESULTS: We found that out of 44,246 prison releases in Massachusetts between 2015-2020, 2237 (5.1%) resulted in opioid overdose in the 90 days following release. The performance of the two predictive models varied. The single weight model had high sensitivity (79%) and low specificity (56%) for predicting opioid overdose and was more sensitive for White non-Hispanic individuals (sensitivity = 84%) than for racial/ethnic minority individuals. CONCLUSIONS: Stratified models had better balanced performance metrics for both White non-Hispanic and racial/ethnic minority groups and identified different predictors of overdose between racial/ethnic groups. Across racial/ethnic groups and models, involuntary commitment (involuntary treatment for alcohol/substance use disorder) was an important predictor of opioid overdose.

Identifying structural risk factors for overdose following incarceration: a concept mapping study.

BACKGROUND: Currently, there are more than two million people in prisons or jails, with nearly two-thirds meeting the criteria for a substance use disorder. Following these patterns, overdose is the leading cause of death following release from prison and the third leading cause of death during periods of incarceration in jails. Traditional quantitative methods analyzing the factors associated with overdose following incarceration may fail to capture structural and environmental factors present in specific communities. People with lived experiences in the criminal legal system and with substance use disorder hold unique perspectives and must be involved in the research process. OBJECTIVE: To identify perceived factors that impact overdose following release from incarceration among people with direct criminal legal involvement and experience with substance use. METHODS: Within a community-engaged approach to research, we used concept mapping to center the perspectives of people with personal experience with the carceral system. The following prompt guided our study: "What do you think are some of the main things that make people who have been in jail or prison more and less likely to overdose?" Individuals participated in three rounds of focus groups, which included brainstorming, sorting and rating, and community interpretation. We used the Concept Systems Inc. platform groupwisdom for our analyses and constructed cluster maps. RESULTS: Eight individuals (ages 33 to 53) from four states participated. The brainstorming process resulted in 83 unique factors that impact overdose. The concept mapping process resulted in five clusters: (1) Community-Based Prevention, (2) Drug Use and Incarceration, (3) Resources for Treatment for Substance Use, (4) Carceral Factors, and (5) Stigma and Structural Barriers. CONCLUSIONS: Our study provides critical insight into community-identified factors associated with overdose following incarceration. These factors should be accounted for during resource planning and decision-making.

Measurement of Health-Related Quality of Life from Conception to Postpartum Using the EQ-5D-5L Among a National Sample of US Pregnant and Postpartum Adults.

BACKGROUND: During pregnancy, physiological changes occur from conception to birth. We assessed the health-related quality of life (HRQoL) throughout pregnancy and postpartum using the EQ-5D-5L. METHODS: Between May and July 2021 (wave 1) and December 2021 and April 2022 (wave 2), we conducted a series of cross-sectional, national online surveys of 5250 pregnant and postpartum United States (US) adults. The survey included the EQ-5D-5L, EQ visual analog scale (EQ VAS), items measuring respondents' sociodemographic and health information, last menstrual period, estimated date of delivery, and date of pregnancy end (if postpartum). We examined monthly EQ-5D-5L items, utility values, and EQ VAS scores during pregnancy and postpartum. We used quantile regression adjusted for calendar month of last menstrual period to estimate changes in HRQoL at different time points of pregnancy and postpartum. RESULTS: There was a steady increase in the frequency of respondents reporting health-related problems and a decline in EQ-5D-5L utility values from early pregnancy until the ninth month of pregnancy (ß = - 0.21; standard error [SE] 0.02; P < 0.001), followed by a 0.10 (SE 0.02; P < 0.001) unit increase in values during the first postpartum month and a stabilization during the remainder of the postpartum period (ß = 0.02; SE 0.02; P = 0.214). The median EQ-5D-5L utility value was lowest during the ninth month of pregnancy (median 0.78 [interquartile range 0.30]). CONCLUSIONS: HRQoL as measured by EQ-5D-5L varies across pregnancy, indicating progressive declines throughout pregnancy and a return to first trimester values during the first month postpartum. Studies involving HRQoL measurement in pregnant people should account for the stage of pregnancy in their estimates.

COVID-19 vaccine coverage among college students following vaccine mandates.

OBJECTIVE: Colleges are potential hotspots for transmission of SARS-CoV-2 due to lower immunization rates and possible close contacts among young adults. Some universities have implemented policies mandating COVID-19 vaccination; however, their effects remain uncertain. We estimated COVID-19 vaccination rates with and without university-mandated vaccination policies. PARTICIPANTS: A university-wide survey was conducted among 2,011 students. METHODS: Students completed an online questionnaire on sociodemographics, COVID-19 vaccine status, and vaccine intention. RESULTS: Without university vaccine mandates, 76% of students would receive a COVID-19 vaccination, and with vaccine mandates, more than 82% of students would receive vaccination. Despite this improvement, we observed fewer changes in vaccine coverage for certain subgroups of students, indicating these policies could exacerbate ongoing disparities in COVID-19 vaccination rates. CONCLUSIONS: COVID-19 vaccine mandates on campuses are likely to increase vaccination rates modestly. However, interventions will likely be required to supplement vaccine mandates.