Flynnmoore3859

timates of prevalence in the present sample.

The prevalence of the 5 PGAD criteria in 2 large non-clinical samples ranged from similar to higher than rates reported in previous research. However, distress ratings associated with each of the 5 criteria varied, with most respondents describing them primarily as neutral or non-distressing. Jackowich RA, Pukall CF. Prevalence of Persistent Genital Arousal Disorder in 2 North American Samples. J Sex Med 2020;172408-2416.

The prevalence of the 5 PGAD criteria in 2 large non-clinical samples ranged from similar to higher than rates reported in previous research. However, distress ratings associated with each of the 5 criteria varied, with most respondents describing them primarily as neutral or non-distressing. Jackowich RA, Pukall CF. Prevalence of Persistent Genital Arousal Disorder in 2 North American Samples. J Sex Med 2020;172408-2416.

Numerous U.S. state legislatures have proposed bills to ban gender-affirming medical interventions for minors. Parents and caregivers play a critical role in advocating for and supporting their transgender and gender-diverse youth (TGDY). We aimed to understand parent and caregiver perspectives about this potential legislation and perceived effects on their TGDY's mental health.

We developed and launched a social-media based, anonymous online survey in February 2020 to assess parent and caregiver perspectives on proposed laws to ban gender-affirming medical interventions for minors. Participants were asked to respond to two open-ended questions about these laws; responses were coded to identify key themes.

We analyzed responses from 273 participants from 43 states. Most identified as white (86.4%) female (90.0%) mothers (93.8%), and 83.6% of their TGDY had received gender-affirming medical interventions before age 18years. The most salient theme, which appeared in the majority of responses, described paeir medical providers.

To analyze the potential association between social support, experiences of violence, and sociodemographic characteristics of adolescents and the likelihood of acceptance of violence and machismo in different European countries.

Cross-sectional design. We recruited 1,555 participants ages 13-16 from secondary schools in Alicante (Spain), Rome (Italy), Iasi (Romania), Matosinhos (Portugal), Poznan (Poland), and Cardiff (UK). We used linear regression models to identify how social support from teachers and parents, experiences of violence-dating violence, bullying, cyberbullying, abuse in childhood-and sociodemographic characteristics were associated with violent thinking, specifically machismo and acceptance of violence. The analysis was stratified by sex.

Acceptance of violence was higher for those who had lower perceived social support from parents (β

=-154, p < .001; β

=-.114, p= .019) for both sexes. Perpetration of bullying and/or cyberbullying was associated with higher scores for machismo andonal violence, including bullying and dating violence.

To determine the incidence and outcomes of firearm injuries in adolescents and the effect of trauma center (TC) designation on their mortality.

The National Trauma Data Bank (2010-2016) was queried for all encounters involving adolescents aged 13-16years with firearm injuries. Multivariable logistic regression was employed to determine the association of covariates with mortality (α= .05). Propensity score matching was also used to explore the relationship between TC designation and mortality.

A total of 9,029 adolescents met inclusion criteria. Patients aged 15 and 16 years compromised 77.8% of the cohort and were more often male (87.9% vs. 80.6%, p < .001), black (63.8% vs. 56.1%, p < .001), injured in the abdomen (25.4% vs. 22.4%, p= .007) or extremities (62.3% vs. 56.7%, p < .001), and incurred severe injuries (54.5% vs. 50.9%, p= .004) versus 13- and 14-year-old patients. Younger patients were more often injured in the head/neck (23.8% vs. 20.5%, p= .001). Multivariable logistic regressionthe closest available TC.

To evaluate the frequency of nonmelanoma skin cancer (NMSC), NMSC precursors, and melanoma on a store-and-forward dermatology model featuring the pharmacist as the patient's point-of-contact. The secondary objective was to define lesion changes and symptoms perceived by patients (clinical prediction rules by nonexpert observers) that can be predictive of malignity.

A cross-sectional study of teledermatology consultation was performed. All patients who underwent a teledermatology consultation between September 2018 and March 2020 were included. A patient could have more than 1 lesion per consultation. The object of the study was a defined dermatologic lesion. The differences between the variables were analyzed using a univariate model based on the chi-square test for independent qualitative variables and Fisher exact test in cases when the expected values in any of the cells of a contingency table were less than 5. Selonsertib solubility dmso Statistical significance was set at P < 0.05 (2-tailed).

A total of 225 lesions in 218 anoma, NMSC, and NMSC precursors when backed by a robust dermatology service.

The Coronary Artery Risk Detection in Appalachian Communities (CARDIAC) Project is a state-wide risk factor screening program that operated in West Virginia for 19years and screened more than 100,000 5th graders for obesity, hypertension, and dyslipidemia.

We investigated siblings in the CARDIAC Project to assess whether cardiometabolic risk factors (CMRFs) correlate in siblings.

We identified 12,053 children from 5752 families with lipid panel, blood pressure, and anthropometric data. A linkage application (LinkPlus from the U.S. Centers for Disease Control and Prevention) matched siblings based on parent names, addresses, telephone numbers, and school to generate a linkage probability curve. Graphical and statistical analyses demonstrate the relationships between CMRFs in siblings.

Siblings showed moderate intraclass correlation coefficient of 0.375 for low-density lipoprotein cholesterol (LDL-C), 0.34 for high-density lipoprotein cholesterol (HDL-C), and 0.22 for triglyceride levels. The body mass index (BMI) intraclass correlation coefficient (0.