Wearable alcohol monitors for alcohol use data collection among college students: Feasibility and acceptability.

OBJECTIVE: We assessed the feasibility and acceptability of using BACtrack Skyn wearable alcohol monitors for alcohol research in a college student population. METHODS: We enrolled n = 5 (Sample 1) and n = 84 (Sample 2) Indiana University undergraduate students to wear BACtrack Skyn devices continuously over a 5-day to 7-day study period. We assessed feasibility in both samples by calculating compliance with study procedures, and by analyzing amount and distributions of device output [e.g., transdermal alcohol content (TAC), temperature, motion]. In Sample 1, we assessed feasibility and acceptability with the Feasibility of Intervention Measure (FIM) scale and the Acceptability of Intervention Measure (AIM) scale. RESULTS: All participants were able to successfully use the alcohol monitors, producing a total of 11,504 h of TAC data. TAC data were produced on 567 days of the 602 total possible days of data collection. The distribution of the TAC data showed between-person variation, as would be expected with between-person differences in drinking patterns. Temperature and motion data were also produced as expected. Sample 1 participants (n = 5) reported high feasibility and acceptability of the wearable alcohol monitors in survey responses with a mean FIM score of 4.3 (of 5.0 possible score) and mean AIM score of 4.3 (of 5.0 possible score). CONCLUSIONS: The high feasibility and acceptability we observed underscore the promise of using BACtrack Skyn wearable alcohol monitors to improve our understanding of alcohol consumption among college students, a population at particularly high risk for alcohol-related harms.

Development and validation of a model for measuring alcohol consumption from transdermal alcohol content data among college students.

BACKGROUND AND AIMS: Transdermal alcohol content (TAC) data collected by wearable alcohol monitors could potentially contribute to alcohol research, but raw data from the devices are challenging to interpret. We aimed to develop and validate a model using TAC data to detect alcohol drinking. DESIGN: We used a model development and validation study design. SETTING: Indiana, USA PARTICIPANTS: In March to April 2021, we enrolled 84 college students who reported drinking at least once a week (median age = 20 years, 73% white, 70% female). We observed participants' alcohol drinking behavior for 1 week. MEASUREMENTS: Participants wore BACtrack Skyn monitors (TAC data), provided self-reported drinking start times in real time (smartphone app) and completed daily surveys about their prior day of drinking. We developed a model using signal filtering, peak detection algorithm, regression and hyperparameter optimization. The input was TAC and outputs were alcohol drinking frequency, start time and magnitude. We validated the model using daily surveys (internal validation) and data collected from college students in 2019 (external validation). FINDINGS: Participants (N = 84) self-reported 213 drinking events. Monitors collected 10 915 hours of TAC. In internal validation, the model had a sensitivity of 70.9% (95% CI = 64.1%-77.0%) and a specificity of 73.9% (68.9%-78.5%) in detecting drinking events. The median absolute time difference between self-reported and model-detected drinking start times was 59 min. Mean absolute error (MAE) for the reported and detected number of drinks was 2.8 drinks. In an exploratory external validation among five participants, number of drinking events, sensitivity, specificity, median time difference and MAE were 15%, 67%, 100%, 45 minutes and 0.9 drinks, respectively. Our model's output was correlated with breath alcohol concentration data (Spearman's correlation [95% CI] = 0.88 [0.77, 0.94]). CONCLUSION: This study, the largest of its kind to date, developed and validated a model for detecting alcohol drinking using transdermal alcohol content data collected with a new generation of alcohol monitors. The model and its source code are available as Supporting Information (https://osf.io/xngbk).

A Per-Protocol Analysis Using Inverse-Probability-of-Censoring Weights in a Randomized Trial of Initial Protease Inhibitor Versus Nonnucleoside Reverse Transcriptase Inhibitor Regimens in Children.

Protocol adherence may influence measured treatment effectiveness in randomized controlled trials. Using data from a multicenter trial (Europe and the Americas, 2002-2009) of children with human immunodeficiency virus type 1 who had been randomized to receive initial protease inhibitor (PI) versus nonnucleoside reverse transcriptase inhibitor (NNRTI) antiretroviral therapy regimens, we generated time-to-event intention-to-treat (ITT) estimates of treatment effectiveness, applied inverse-probability-of-censoring weights to generate per-protocol efficacy estimates, and compared shifts from ITT to per-protocol estimates across and within treatment arms. In ITT analyses, 263 participants experienced 4-year treatment failure probabilities of 41.3% for PIs and 39.5% for NNRTIs (risk difference = 1.8% (95% confidence interval (CI): -10.1, 13.7); hazard ratio = 1.09 (95% CI: 0.74, 1.60)). In per-protocol analyses, failure probabilities were 35.6% for PIs and 29.2% for NNRTIs (risk difference = 6.4% (95% CI: -6.7, 19.4); hazard ratio = 1.30 (95% CI: 0.80, 2.12)). Within-arm shifts in failure probabilities from ITT to per-protocol analyses were 5.7% for PIs and 10.3% for NNRTIs. Protocol nonadherence was nondifferential across arms, suggesting that possibly better NNRTI efficacy may have been masked by differences in within-arm shifts deriving from differential regimen forgiveness, residual confounding, or chance. A per-protocol approach using inverse-probability-of-censoring weights facilitated evaluation of relationships among adherence, efficacy, and forgiveness applicable to pediatric oral antiretroviral regimens.

Target Trial Emulation: A Design Tool for Cancer Clinical Trials.

PURPOSE: To apply target trial emulation to explore the potential impact of eligibility criteria on the primary outcome of a randomized controlled trial. METHODS: Simulations of a real-world explanatory trial of transarterial radioembolization for advanced unresectable hepatocellular carcinoma with portal vein invasion were performed to examine the effects of cohort specification on survival outcomes and patient sample size. Simulations comprised 24 different permutations of the trial varied on three disease nonspecific eligibility parameters. Treatment and control arms for these emulated trials were drawn from the National Cancer Database and matched by treatment propensity. Target trial emulation served as the causal framework for this analysis, allowing the architecture of a true controlled experiment to address forms of bias routinely encountered in comparative effectiveness studies involving real-world observational data. RESULTS: Twenty-four propensity score-matched cohorts comprising a wider clinical spectrum of patients than specified by the original target trial were successfully generated using the National Cancer Database. The arms for each of the emulated trials demonstrated exchangeability across all eligibility criteria and other clinical covariates. Significant treatment benefits were associated with only a narrow range of eligibility criteria, indicating that the original target trial was well specified. CONCLUSION: The impact of patient selection on treatment outcomes can be studied using target trial emulation. This analytical framework can furthermore serve to leverage existing real-world data to inform the task of cohort specification for a randomized controlled trial, facilitating a more data-driven approach for this important step in clinical trial design.

The association between social factors and COVID-19 protective behaviors and depression and stress among midwestern US college students.

PURPOSE: The aim of this cross-sectional study was to examine the relationship between social factors and COVID-19 protective behaviors and two outcomes: depressive and perceived stress symptoms. METHODS: In September 2020, 1,064 randomly selected undergraduate students from a large midwestern university completed an online survey and provided information on demographics, social activities, COVID-19 protective behaviors (i.e., avoiding social events and staying home from work and school), and mental health symptoms. Mental health symptoms were measured using the Center for Epidemiological Studies Depression-10 questionnaire for depression and the Perceived Stress Scale-10 for stress symptoms. RESULTS: The results showed respondents who were males and also the respondents who were "hanging out" with more people while drinking alcohol reported significantly lower depressive symptoms and lower stress symptoms. On the contrary, staying home from work or school "very often" was associated with higher stress symptoms, compared with "never/rarely" staying home from work/school. Similarly, having a job with in-person interaction was also associated with increased stress. CONCLUSIONS: These findings suggest that lack of social engagement was associated with depression and stress symptoms among college students during the COVID-19 pandemic. Planning social activities that align with recommended safety precautions, as well as meet students' social needs, should be an important priority for higher education institutions.

Does receiving a SARS-CoV-2 antibody test result change COVID-19 protective behaviors? Testing risk compensation in undergraduate students with a randomized controlled trial.

BACKGROUND: Risk compensation, or matching behavior to a perceived level of acceptable risk, can blunt the effectiveness of public health interventions. One area of possible risk compensation during the SARS-CoV-2 pandemic is antibody testing. While antibody tests are imperfect measures of immunity, results may influence risk perception and individual preventive actions. We conducted a randomized control trial to assess whether receiving antibody test results changed SARS-CoV-2 protective behaviors. PURPOSE: Assess whether objective information about antibody status, particularly for those who are antibody negative and likely still susceptible to SARS-CoV-2 infection, increases protective behaviors. Secondarily, assess whether a positive antibody test results in decreased protective behaviors. METHODS: In September 2020, we enrolled 1076 undergraduate students, used fingerstick tests for SARS-CoV-2 antibodies, and randomized participants to receive their results immediately or delayed by 4 weeks. Two weeks later, participants completed a survey about their engagement in 4 protective behaviors (mask use, social event avoidance, staying home from work/school, ensuring physical distancing). We estimated differences between conditions for each of these behaviors, stratified by antibody status. For negative participants at baseline, we also estimated the difference between conditions for seroconversion over 8 weeks of follow-up. RESULTS: For the antibody negative participants (n = 1029) and antibody positive participants (n = 47), we observed no significant differences in protective behavior engagement between those who were randomized to receive test results immediately or after 4 weeks. For the baseline antibody negative participants, we also observed no difference in seroconversion outcomes between conditions. CONCLUSIONS: We found that receiving antibody test results did not lead to significant behavior change in undergraduate students whether the SARS-CoV-2 antibody result was positive or negative.

The relationship between acquaintance with a SARS-CoV-2 death, positive SARS-CoV-2 test results, and sleep duration among college students in fall 2020.

Background: The aim of this study was to test whether two SARS-CoV-2 experiences, knowing someone who had died of SARS-CoV-2 infection and having received a positive SARS-CoV-2 test result, were associated with shorter sleep duration among undergraduate students. Methods: An online cross-sectional study was conducted at a large public Midwestern university in September 2020 (fall semester). Self-reported average sleep duration and the exposures of interest, knowing someone who died from a SARS-CoV-2 infection and their own SARS-CoV-2 test result, were collected from 1,058 undergraduate study participants. Results: Respondents who knew someone who had died of a SARS-CoV-2 infection were more likely to report having a short sleep duration, compared to respondents who did not know someone who had died of a SARS-CoV-2 infection (aOR = 1.80, 95% CI: 1.14, 2.79). However, those with a positive SARS-CoV-2 test result were less likely to report a short sleep duration, compared to respondents without a positive test history (aOR = 0.47, 95% CI: 0.21, 0.91). Conclusions: These findings suggest that college students' knowing someone who had died of SARS-CoV-2 infection and having received a positive SARS-CoV-2 test result are associated with sleep duration. However, different experiences may impact sleep differently, so further research is warranted to better understand how unusual events impact the sleep of college students.

SARS-CoV-2 reinfections in a US university setting, Fall 2020 to Spring 2021.

BACKGROUND: SARS-CoV-2 reinfections are a public health concern because of the potential for transmission and clinical disease, and because of our limited understanding of whether and how well an infection confers protection against subsequent infections. Despite the public health importance, few studies have reported rigorous estimates of reinfection risk. METHODS: Leveraging Indiana University's comprehensive testing program to identify both asymptomatic and symptomatic SARS-CoV-2 cases, we estimated the incidence of SARS-CoV-2 reinfection among students, faculty, and staff across the 2020-2021 academic year. We contextualized the reinfection data with information on key covariates: age, sex, Greek organization membership, student vs faculty/staff affiliation, and testing type. RESULTS: Among 12,272 people with primary infections, we found a low level of SARS-CoV-2 reinfections (0.6%; 0.4 per 10,000 person-days). We observed higher risk for SARS-CoV-2 reinfections in Greek-affiliated students. CONCLUSIONS: We found evidence for low levels of SARS-CoV-2 reinfection in a large multi-campus university population during a time-period prior to widespread COVID-19 vaccination.

Does cigarette or E-cigarette use increase the risk for SARS-CoV-2 seroconversion among Midwestern college students?

OBJECTIVE: This longitudinal study tested the relationship between cigarette and e-cigarette use and SARS-CoV-2 seroconversion among US college students. PARTICIPANTS: Undergraduate students (n = 764), drawn from a randomly selected invitation-only pool from a large Midwestern university, that were initially negative for SARS-CoV-2 antibodies and were re-tested in November were included in this study conducted in Fall 2020. METHODS: Demographics and cigarette and e-cigarette use behaviors (nicotine use) were collected in a baseline survey. SARS-CoV-2 antibody tests were administered in September (baseline) and November (endline) of 2020. Log-binomial regression analyses were conducted to test the association between nicotine use and SARS-CoV-2 seroconversion. RESULTS: SARS-CoV-2 seroconversion was 5.2%. No statistically significant associations were found between nicotine use and SARS-CoV-2 seroconversion. CONCLUSIONS: Contrary to prior results, we found no association between nicotine use and SARS-CoV-2 seroconversion. Nicotine use may not be a key risk factor for COVID-19 acquisition in predominantly healthy college-aged populations.

Relationship between high-risk alcohol consumption and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroconversion: a prospective sero-epidemiological cohort study among American college students.

AIMS: To estimate the associations between high-risk alcohol consumption and (1) severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroconversion, (2) self-reported new SARS-CoV-2 infection and (3) symptomatic COVID-19. DESIGN: Prospective cohort study. SETTING: Indiana University Bloomington (IUB), IN, USA. PARTICIPANTS: A total of 1027 IUB undergraduate students (64% female), aged 18 years or older, residing in Monroe County, Indiana, seronegative for SARS-CoV-2 at study baseline. MEASUREMENTS: Primary exposure was high-risk alcohol consumption measured with an Alcohol Use Disorders Identification Test (AUDIT) questionnaire score of 8 or more. Primary outcome was SARS-CoV-2 seroconversion since baseline, assessed with two SARS-CoV-2 antibody tests, at baseline (September 2020) and end-line (November 2020). Secondary outcomes were (a) self-reported new SARS-CoV-2 infection at the study end-line and (b) self-reported symptomatic COVID-19 at baseline. FINDINGS: Prevalence of high-risk alcohol consumption was 32 %. In models adjusted for demographics, students with high-risk alcohol consumption status had 2.44 [95% confidence interval (CI) = 1.35, 4.25] times the risk of SARS-CoV-2 seroconversion and 1.84 (95% CI = 1.04, 3.28) times the risk of self-reporting a positive SARS-CoV-2 infection, compared with students with no such risk. We did not identify any association between high-risk alcohol consumption and symptomatic COVID-19 (prevalence ratio = 1.17, 95% CI = 0.93, 1.47). Findings from sensitivity analyses corroborated these results and suggested potential for a dose-response relationship. CONCLUSIONS: Among American college students, high-risk alcohol consumption appears to be associated with higher risk for severe acute respiratory syndrome coronavirus 2 seroconversion/infection.

Use of research electronic data capture (REDCap) in a COVID-19 randomized controlled trial: a practical example.

BACKGROUND: Randomized controlled trials (RCT) are considered the ideal design for evaluating the efficacy of interventions. However, conducting a successful RCT has technological and logistical challenges. Defects in randomization processes (e.g., allocation sequence concealment) and flawed masking could bias an RCT's findings. Moreover, investigators need to address other logistics common to all study designs, such as study invitations, eligibility screening, consenting procedure, and data confidentiality protocols. Research Electronic Data Capture (REDCap) is a secure, browser-based web application widely used by researchers for survey data collection. REDCap offers unique features that can be used to conduct rigorous RCTs. METHODS: In September and November 2020, we conducted a parallel group RCT among Indiana University Bloomington (IUB) undergraduate students to understand if receiving the results of a SARS-CoV-2 antibody test changed the students' self-reported protective behavior against coronavirus disease 2019 (COVID-19). In the current report, we discuss how we used REDCap to conduct the different components of this RCT. We further share our REDCap project XML file and instructional videos that investigators can use when designing and conducting their RCTs. RESULTS: We reported on the different features that REDCap offers to complete various parts of a large RCT, including sending study invitations and recruitment, eligibility screening, consenting procedures, lab visit appointment and reminders, data collection and confidentiality, randomization, blinding of treatment arm assignment, returning test results, and follow-up surveys. CONCLUSIONS: REDCap offers powerful tools for longitudinal data collection and conduct of rigorous and successful RCTs. Investigators can make use of this electronic data capturing system to successfully complete their RCTs. TRIAL REGISTRATION: The RCT was prospectively (before completing data collection) registered at ClinicalTrials.gov; registration number: NCT04620798 , date of registration: November 9, 2020.

If you build it, will they come? Social, economic, and psychological determinants of COVID-19 testing decisions.

BACKGROUND: The efficacy of testing and tracing programs to reduce COVID-19 transmission hinges not only on widespread access to testing, but also on the public's willingness to participate in them. To the extent that testing intentions are patterned by social determinants of health, this constitutes an understudied mechanism of disparities in COVID-19 morbidity and mortality. DESIGN: Using data from a representative household probability sample, the Person to Person Health Interview Study (n = 935), sociodemographic, economic, and psychological determinants of testing considerations were evaluated across six domains: treatment affordability, ability to work if positive, hospital effectiveness, symptom severity, proximity to infected, and risk of transmitting to others. RESULTS: Findings demonstrated significant differences in testing motivations across race/ethnicity, education level, socioeconomic status, and worry about self and loved ones. Notably, Black (p<0.01) and Latino (p<0.05) respondents and those experiencing financial strain (p<0.001) were disproportionately likely to indicate that resource factors would influence their decision to get tested. Desire to reduce transmission and concern about proximity to the infected were reported among those who expressed COVID-19 worries (p<0.001). CONCLUSION: Public health efforts to combat the COVID-19 pandemic must address social, economic, and psychological factors that enable and constrain individual behavior. Increasing access to preventative interventions and technologies, including vaccines, is unlikely to markedly reduce morbidity and mortality without effective messaging and economic support to improve uptake in vulnerable populations.

A Cross-Sectional Analysis of Demographic and Behavioral Risk Factors of Severe Acute Respiratory Syndrome Coronavirus 2 Seropositivity Among a Sample of U.S. College Students.

PURPOSE: Colleges and universities across the United States are developing and implementing data-driven prevention and containment measures against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Identifying risk factors for SARS-CoV-2 seropositivity could help to direct these efforts. This study aimed to estimate the associations between demographic factors and social behaviors and SARS-CoV-2 seropositivity and self-reported positive SARS-CoV-2 diagnostic test. METHODS: In September 2020, we randomly sampled Indiana University Bloomington undergraduate students. Participants completed a cross-sectional online survey about demographics, SARS-CoV-2 testing history, relationship status, and risk behaviors. Additionally, during a subsequent appointment, participants were tested for SARS-CoV-2 antibodies using a fingerstick procedure and SARS-CoV-2 IgM/IgG rapid assay kit. We used unadjusted modified Poisson regression models to evaluate the associations between predictors of both SARS-CoV-2 seropositivity and self-reported positive SARS-CoV-2 infection history. RESULTS: Overall, 1,076 students were included in the serological testing analysis, and 1,239 students were included in the SARS-CoV-2 infection history analysis. Current seroprevalence of SARS-CoV-2 was 4.6% (95% confidence interval: 3.3%, 5.8%). Prevalence of self-reported SARS-CoV-2 infection history was 10.3% (95% confidence interval: 8.6%, 12.0%). Greek membership, having multiple romantic partners, knowing someone in one's immediate environment with SARS-CoV-2 infection, drinking alcohol more than 1 day a week, and hanging out with more than five people when drinking alcohol increased both the likelihood of seropositivity and SARS-CoV-2 infection history. CONCLUSION: Our findings have implications for American colleges and universities and could be used to inform SARS-CoV-2 prevention and control strategies on such campuses.

Estimation of the incubation period of COVID-19 using viral load data.

The incubation period, or the time from infection to symptom onset, of COVID-19 has usually been estimated by using data collected through interviews with cases and their contacts. However, this estimation is influenced by uncertainty in the cases' recall of exposure time. We propose a novel method that uses viral load data collected over time since hospitalization, hindcasting the timing of infection with a mathematical model for viral dynamics. As an example, we used reported data on viral load for 30 hospitalized patients from multiple countries (Singapore, China, Germany, and Korea) and estimated the incubation period. The median, 2.5, and 97.5 percentiles of the incubation period were 5.85 days (95 % CI: 5.05, 6.77), 2.65 days (2.04, 3.41), and 12.99 days (9.98, 16.79), respectively, which are comparable to the values estimated in previous studies. Using viral load to estimate the incubation period might be a useful approach, especially when it is impractical to directly observe the infection event.

HIV Testing by Public Health Centers and Municipalities and New HIV Cases During the COVID-19 Pandemic in Japan.

BACKGROUND: During the COVID-19 outbreak, facility capacity for HIV testing has been limited. Furthermore, people may have opted against HIV testing during this period to avoid COVID-19 exposure. We investigated the influence of the COVID-19 pandemic on HIV testing and the number of reported HIV cases in Japan. METHODS: We analyzed quarterly HIV/AIDS-related data from 2015 to the second quarter of 2020 using an anomaly detection approach. The data included the number of consultations, the number of HIV tests performed by public health centers or municipalities, and the number of newly reported HIV cases with and without an AIDS diagnosis. We further performed the same analysis for 2 subgroups: men who have sex with men (MSM) and non-Japanese persons. RESULTS: The number of HIV tests (9,584 vs. 35,908 in the year-before period) and consultations (11,689 vs. 32,565) performed by public health centers significantly declined in the second quarter of 2020, whereas the proportion of new HIV cases with an AIDS diagnosis (36.2% vs. 26.4%) significantly increased after removing the trend and seasonality effects. HIV cases without an AIDS diagnosis decreased (166 vs. 217), but the reduction was not significant. We confirmed similar trends for the men who have sex with men and non-Japanese subgroups. CONCLUSIONS: During the COVID-19 pandemic, the current HIV testing system in Japan seems to have missed more cases of HIV before developing AIDS. Continuously monitoring the situation and securing sufficient test resources by use of self-testing is essential to understand the clear epidemiological picture of HIV incidence during the COVID-19 pandemic.

Food insecurity, gestational weight gain and gestational diabetes in the National Children's Study, 2009-2014.

BACKGROUND: Household food insecurity (HFI) and gestational diabetes mellitus (GDM) are both common during pregnancy, yet it is unknown if these two factors are related. We aimed to determine the independent and joint associations between HFI, gestational weight gain (GWG) and GDM among pregnant women in the USA. METHODS: We used data from 592 women in the National Children's Study, Initial Vanguard Study from 2009 to 2014. HFI was assessed using the Household Food Security Survey Module at the first study visit; GDM was assessed through questionnaires and medical chart review. Logistic regression models were used to investigate the exposures of HFI, GWG and their joint effect on GDM. RESULTS: Among participants, 20.1% were marginally food secure or food insecure and 7.4% were diagnosed with GDM. The elevated unadjusted association between HFI and GDM was attenuated after adjustment (aOR: 1.12; 95%CI: 0.47, 2.66). There was an elevated risk of GDM associated with inadequate GWG, (aOR: 2.42; 95%CI: 0.97, 6.00), but results were imprecise. There were no statistically significant associations in the joint exposure analysis. CONCLUSION: The relationship between HFI and GDM is mostly explained by other covariates, but there is some evidence that inadequate GWG is a possible risk factor for GDM.

High Prevalence of Sexual Assault Victimization Experiences Among University Fraternity Men.

Limited research has examined sexual victimization among U.S. college men, and particularly fraternity men. We report the prevalence of sexual assault (SA) victimization among a sample of college fraternity members and the sociodemographic variables associated with this victimization. In April 2018, we conducted a web-based survey study among a random sample of fraternity members (n = 102) from a list of all fraternity members at a large Midwestern university. We used Fisher's exact tests, Student's t-tests, and log-binomial regression models to assess associations between sociodemographic variables and any SA victimization (attempted or completed penetrative sexual assault). Over a quarter (27.5%) of respondents reported experiencing any SA victimization-penetrative sexual assault (13.7%) or attempted penetrative sexual assault (25.5%)-since entering college. Age, school year, and being on a varsity sports team were significantly associated with any SA victimization (p-values: <.01, <.01, and .02, respectively). Regression analyses showed older fraternity men had experienced significantly greater prevalence of any SA victimization compared to younger fraternity men (prevalence ratio [PR]: 2.78, 95% confidence interval (CI): 1.35-5.73). Furthermore, any SA victimization was also more common among varsity sports team members (3%) compared to nonmembers (0%). These findings indicate that college men, particularly fraternity members, may experience sexual assault victimization at high rates. Our more inclusive survey language may have captured sexually violent experiences that traditional measures have not, such as "made to penetrate" experiences. We encourage the use of queries that are sensitive to the specific characteristics of male sexual violence victimization, including experiences of nonconsensual sexual activity where the victim is either the penetrated or the penetrator. Furthermore, prevention efforts and supportive services for survivors should be expanded to better address male SA victimization on college campuses.

A population-based study of concurrent prescriptions of opioid analgesic and selective serotonin reuptake inhibitor medications during pregnancy and risk for adverse birth outcomes.

BACKGROUND: Pregnant women with painful conditions often have mental health problems, including depression and anxiety. Co-morbid conditions may cause pregnant women to use multiple medications, although safety of such practice is poorly understood. OBJECTIVES: We investigated the influence of combined prescriptions of opioid analgesics and selective serotonin reuptake inhibitors (SSRIs) during pregnancy on two adverse birth outcomes. METHODS: We analysed Swedish population-based births (n = 688 914) between 2007 and 2013. Using national registers, we obtained data on filled medication prescriptions, birth outcomes, and a wide range of parental characteristics. We estimated preterm birth and small-for-gestational-age risk following independent or combined prescriptions of the two medications compared with no filled prescriptions for either medication. We adjusted for confounders using inverse probability of treatment weights. RESULTS: After adjusting for confounders, preterm birth risk was higher among women with opioid analgesic prescriptions only (5.9%; risk ratio [RR] 1.27, 95% confidence interval [CI] 1.22, 1.33), SSRIs only (6.2%; RR 1.34, 95% CI 1.27, 1.42), and both medications (7.8%; RR 1.70, 95% CI 1.47, 1.96) compared with unexposed women (4.6%). The interaction between the medications on preterm birth was small (risk difference [RD] 0.4%, 95% CI -0.8%, 1.6%); relative excess risk due to interaction [RERI] 0.09, 95% CI -0.17, 0.34; RR 1.00, 95% CI 0.85, 1.17). For small for gestational age, risk was approximately 2% across all groups, and there was no interaction between the medications (RD 0.3%, 95% CI -0.4%, 1.1%); RERI 0.15, 95% CI -0.16, 0.47; RR 1.15, 95% CI 0.87, 1.52). CONCLUSIONS: Compared with unexposed pregnancies, those with either medication alone had a small increased risk for preterm birth but no increased risk for small for gestational age. The magnitude of associations with combined exposure to both medications were not greater than the sum of the associations with each medication considered individually.

Health insurance and AIDS Drug Assistance Program (ADAP) increases retention in care among women living with HIV in the United States.

Our objective was to examine the association between healthcare payer type and missed HIV care visits among 1,366 US women living with HIV (WLWH) enrolled in the prospective Women's Interagency HIV Study (WIHS). We collected secondary patient-level data (October 1, 2017-September 30, 2018) from WLWH at nine WIHS sites. We used bivariate and multivariable binary logistic regression to examine the relationship between healthcare payer type (cross-classification of patients' ADAP and health insurance enrollment) and missed visits-based retention in care, defined as no-show appointments for which patients did not reschedule. Our sample included all WLWH who self-reported having received HIV care at least once during the two consecutive biannual WIHS visits a year prior to October 1, 2017-September 30, 2018. In the bivariate model, compared to uninsured WLWH without ADAP, WLWH with private insurance + ADAP were more likely to be retained in care, as were WLWH with Medicaid only and private insurance only. In the adjusted model, WLWH with private insurance only were more likely to be retained in care compared to uninsured WLWH without ADAP. Private health insurance and ADAP are associated with increased odds of retention in care among WLWH.

Time to treatment disruption in children with HIV-1 randomized to initial antiretroviral therapy with protease inhibitors versus non-nucleoside reverse transcriptase inhibitors.

BACKGROUND: Choice of initial antiretroviral therapy regimen may help children with HIV maintain optimal, continuous therapy. We assessed treatment-naïve children for differences in time to treatment disruption across randomly-assigned protease inhibitor versus non-nucleoside reverse transcriptase inhibitor-based initial antiretroviral therapy. METHODS: We performed a secondary analysis of a multicenter phase 2/3, randomized, open-label trial in Europe, North and South America from 2002 to 2009. Children aged 31 days to <18 years, who were living with HIV-1 and treatment-naive, were randomized to antiretroviral therapy with two nucleoside reverse transcriptase inhibitors plus a protease inhibitor or non-nucleoside reverse transcriptase inhibitor. Time to first documented treatment disruption to any component of antiretroviral therapy, derived from treatment records and adherence questionnaires, was analyzed using Kaplan-Meier estimators and Cox proportional hazards models. RESULTS: The modified intention-to-treat analysis included 263 participants. Seventy-two percent (n = 190) of participants experienced at least one treatment disruption during study. At 4 years, treatment disruption probabilities were 70% (protease inhibitor) vs. 63% (non-nucleoside reverse transcriptase inhibitor). The unadjusted hazard ratio (HR) for treatment disruptions comparing protease inhibitor vs. non-nucleoside reverse transcriptase inhibitor-based regimens was 1.19, 95% confidence interval [CI] 0.88-1.61 (adjusted HR 1.24, 95% CI 0.91-1.68). By study end, treatment disruption probabilities converged (protease inhibitor 81%, non-nucleoside reverse transcriptase inhibitor 84%) with unadjusted HR 1.11, 95% CI 0.84-1.48 (adjusted HR 1.13, 95% CI 0.84-1.50). Reported reasons for treatment disruptions suggested that participants on protease inhibitors experienced greater tolerability problems. CONCLUSIONS: Children had similar time to treatment disruption for initial protease inhibitor and non-nucleoside reverse transcriptase inhibitor-based antiretroviral therapy, despite greater reported tolerability problems with protease inhibitor regimens. Initial pediatric antiretroviral therapy with either a protease inhibitor or non-nucleoside reverse transcriptase inhibitor may be acceptable for maintaining optimal, continuous therapy.