Intimate partner violence (IPV), inclusive of all forms of abuse, is an ongoing public health and criminal-legal issue that transcends social boundaries. However, there is a lack of equitable representation of diverse populations who experience IPV in the literature. To garner a holistic knowledge of diverse IPV survivor populations\' experiences with seeking help from the police, the current review utilized a qualitative research synthesis methodology to explore police interactions among six IPV survivor populations that are underrepresented in the current literature: women with substance use issues, immigrant women, women in rural localities, heterosexual men, racially/ethnically minoritized women, and sexual minority women. Seven electronic databases were searched to identify peer-reviewed articles on IPV survivors\' narrative descriptions (qualitative or mixed-methods) of their encounters with law enforcement. The final analysis included 28 studies that were then coded with an iterative coding strategy. The analysis uncovered the following themes: (a) revictimization by the police, (b) police negligence, (c) discrimination, (d) cultural differences, and (e) positive experiences. These themes demonstrated that while some experiences with law enforcement were shared between under-researched survivor groups, some experiences were explicitly tied to some aspects of survivors\' identities. Recognizing the potential law enforcement has to support survivors, the findings of the current review reiterate the need for ongoing efforts to improve law enforcement knowledge and overall response to IPV, especially for diverse populations of IPV survivors.

OBJECTIVE: To modify an existing questionnaire Brief Infant Sleep Questionnaire - Revised (BISQ-R) to ensure that it is suitable to measure nocturnal sleep health in a diverse sample of young children from Aotearoa New Zealand whānau (families), and to develop a \"Perception of Infant and Toddler Sleep Scale\" (PoITSS) to use as a primary outcome measurement in an upcoming trial.
METHODS: Items from the BISQ-R were adapted for use among ethnically diverse whānau, and tested online with caregivers of 0-2 year old children. A PoITSS score was generated by scaling the responses from three of the questionnaire items to create a value between 0 (very poor) and 10 (very good). Caregivers provided qualitative feedback about the ease of interpreting and answering questionnaire items.
RESULTS: Caregivers of 957 children (35% Māori, 12% Pacific) completed the questionnaire. Few differences in children\'s nocturnal sleep were observed by demographic characteristics. The mean PoITSS score was 6.9 (SD 2.3) and was slightly higher among Māori children (mean difference 0.4, 95% CI 0.1, 0.7). Test-retest indicated good reliability (ICC=0.81). While the majority (86%) of caregivers did not find it difficult to answer any of the items which formed the PoITSS, qualitative feedback indicated that simple modifications to some items would help ensure that they would be well understood by most caregivers.
CONCLUSIONS: Items from the BISQ-R were successfully adapted, and the PoITSS scale was shown to be appropriate, for use in ethnically diverse Aotearoa New Zealand whānau with young children.

Addressing systemic injustices and racism in training and clinical service provision are key next steps in clinical science. While the APA Multicultural Guidelines and accreditation standards have long emphasized this need, most graduate programs offer a single course on diversity, equity, and inclusion topics, which is inadequate to train and sustain culturally humble providers and redress systemic injustices and racism within psychology. Few \"real-world\" examples exist to guide the development of training models. We provide background on the development and components of a specialty clinic, the University of New Mexico\'s Cultural Counseling Center, whose mission is providing culturally informed clinical services to diverse clientele, and to infuse multicultural training throughout the graduate program. Informed by the racial-spatial framework for psychology and critical race theory, we describe our approach intended to: 1) offer applications for the operationalization and delivery of multicultural and antiracist training; 2) enhance supervisory models; and 3) increase awareness of structural competence. Our clinic, developed collaboratively among students and faculty, serves as a safe forum for dialogue around structural injustices and seeks to improve treatment for diverse clients and those underserved in mental health care. We discuss issues of student and faculty engagement and offer the perspectives of faculty and students of color, case examples illustrating our services, and current efforts to expand and formalize community collaborations. We offer a model that integrates coursework, informal activities, and multicultural supervision for comprehensive student training and that promotes a departmental culture of dialogue and support around equity, diversity, and justice.

BACKGROUND: Disparities in cervical cancer screening rates among marginalized groups is a driver of inequalities in cervical cancer. Self-sampling for human papillomavirus (HPV) testing is a newly emerging alternative to clinician-performed testing to screen for cervical cancer, and has high potential to reduce screening barriers in under-screened and marginalized groups. We study the acceptability in of HPV self-sampling and informational materials among Black/African American, Hispanic/Spanish speaking, American Indian/Alaska Native and transgender/nonbinary populations.
METHODS: We conducted qualitative interviews with patients, ages 30-65, who were Black/African American, Hispanic, American Indian, and/or transgender/nonbinary individuals assigned female at birth. Telephone interviews were conducted in English or Spanish. Patients did not complete the test, rather were asked about the attractiveness, comprehensibility, and acceptability of the HPV self-test, instructions, and messaging.
RESULTS: Among 23 completed interviews (5 American Indian/Alaska Native, 7 Hispanic [2 bilingual, 5 Spanish-speaking], 5 Black/African American, and 6 transgender/nonbinary), patients from all groups thought the test was straightforward and convenient, and they would complete the test at home or in clinic. The transgender/nonbinary patients preferred at-home testing. American Indian and transgender/nonbinary patients liked that the test might avoid pain, discomfort, and invasiveness. All patients liked the letter and instructions. All groups had specific suggestions for making the materials more culturally acceptable.
CONCLUSIONS: The HPV self-test and the instructions and materials for use were acceptable for a diverse group of patients. Tailored outreach and messaging should be considered to reduce screening disparities among groups that have been historically underserved by the medical system.

Recent advancement in genome-wide association studies (GWAS) comes from not only increasingly larger sample sizes but also the shift in focus towards underrepresented populations. Multipopulation GWAS increase power to detect novel risk variants and improve fine-mapping resolution by leveraging evidence and differences in linkage disequilibrium (LD) from diverse populations. Here, we expand upon our previous approach for single-population fine-mapping through Joint Analysis of Marginal SNP Effects (JAM) to a multipopulation analysis (mJAM). Under the assumption that true causal variants are common across studies, we implement a hierarchical model framework that conditions on multiple SNPs while explicitly incorporating the different LD structures across populations. The mJAM framework can be used to first select index variants using the mJAM likelihood with different feature selection approaches. In addition, we present a novel approach leveraging the ideas of mediation to construct credible sets for these index variants. Construction of such credible sets can be performed given any existing index variants. We illustrate the implementation of the mJAM likelihood through two implementations: mJAM-SuSiE (a Bayesian approach) and mJAM-Forward selection. Through simulation studies based on realistic effect sizes and levels of LD, we demonstrated that mJAM performs well for constructing concise credible sets that include the underlying causal variants. In real data examples taken from the most recent multipopulation prostate cancer GWAS, we showed several practical advantages of mJAM over other existing multipopulation methods.

Genome-wide association studies (GWAS) have identified loci associated with Alzheimer\'s disease (AD) but did not identify specific causal genes or variants within those loci. Analysis of whole genome sequence (WGS) data, which interrogates the entire genome and captures rare variations, may identify causal variants within GWAS loci.
We performed single common variant association analysis and rare variant aggregate analyses in the pooled population (N cases = 2184, N controls = 2383) and targeted analyses in subpopulations using WGS data from the Alzheimer\'s Disease Sequencing Project (ADSP). The analyses were restricted to variants within 100 kb of 83 previously identified GWAS lead variants.
Seventeen variants were significantly associated with AD within five genomic regions implicating the genes OARD1/NFYA/TREML1, JAZF1, FERMT2, and SLC24A4. KAT8 was implicated by both single variant and rare variant aggregate analyses.
This study demonstrates the utility of leveraging WGS to gain insights into AD loci identified via GWAS.

Background: The current study explores the genetic underpinnings of cardiac arrhythmia phenotypes within Middle Eastern populations, which are under-represented in genomic medicine research. Methods: Whole-genome sequencing data from 14,259 individuals from the Qatar Biobank were used and contained 47.8% of Arab ancestry, 18.4% of South Asian ancestry, and 4.6% of African ancestry. The frequency of rare functional variants within a set of 410 candidate genes for cardiac arrhythmias was assessed. Polygenic risk score (PRS) performance for atrial fibrillation (AF) prediction was evaluated. Results: This study identified 1196 rare functional variants, including 162 previously linked to arrhythmia phenotypes, with varying frequencies across Arab, South Asian, and African ancestries. Of these, 137 variants met the pathogenic or likely pathogenic (P/LP) criteria according to ACMG guidelines. Of these, 91 were in ACMG actionable genes and were present in 1030 individuals (~7%). Ten P/LP variants showed significant associations with atrial fibrillation p < 2.4 × 10-10. Five out of ten existing PRSs were significantly associated with AF (e.g., PGS000727, p = 0.03, OR = 1.43 [1.03, 1.97]). Conclusions: Our study is the largest to study the genetic predisposition to arrhythmia phenotypes in the Middle East using whole-genome sequence data. It underscores the importance of including diverse populations in genomic investigations to elucidate the genetic landscape of cardiac arrhythmias and mitigate health disparities in genomic medicine.

Population screening for risk of type 1 diabetes (T1D) has been proposed to identify those with islet autoimmunity (presence of islet autoantibodies). As islet autoantibodies can be transient, screening with a genetic risk score has been proposed as an entry into autoantibody testing.
Children were recruited from eight general pediatric and specialty clinics across Virginia with diverse community settings. Recruiters in each clinic obtained informed consent/assent, a medical history, and a saliva sample for DNA extraction in children with and without a history of T1D. A custom genotyping panel was used to define T1D genetic risk based upon associated SNPs in European- and African-genetic ancestry. Subjects at \"high genetic risk\" were offered a separate blood collection for screening four islet autoantibodies. A follow-up contact (email, mail, and telephone) in one half of the participants determined interest and occurrence of subsequent T1D.
A total of 3818 children aged 2-16 years were recruited, with 14.2% (n = 542) having a \"high genetic risk.\" Of children with \"high genetic risk\" and without pre-existing T1D (n = 494), 7.0% (34/494) consented for autoantibody screening; 82.4% (28/34) who consented also completed the blood collection, and 7.1% (2/28) of them tested positive for multiple autoantibodies. Among children with pre-existing T1D (n = 91), 52% (n = 48) had a \"high genetic risk.\" In the sample of children with existing T1D, there was no relationship between genetic risk and age at T1D onset. A major factor in obtaining islet autoantibody testing was concern over SARS-CoV-2 exposure.
Minimally invasive saliva sampling implemented using a genetic risk score can identify children at genetic risk of T1D. Consent for autoantibody screening, however, was limited largely due to the SARS-CoV-2 pandemic and need for blood collection.

BACKGROUND: Resting electrocardiogram (ECG) is a valuable non-invasive diagnostic tool used in clinical medicine to assess the electrical activity of the heart while the patient is resting. Abnormalities in ECG may be associated with clinical biomarkers and can predict early stages of diseases. In this study, we evaluated the association between ECG traits, clinical biomarkers, and diseases and developed risk scores to predict the risk of developing coronary artery disease (CAD) in the Qatar Biobank.
METHODS: This study used 12-lead ECG data from 13,827 participants. The ECG traits used for association analysis were RR, PR, QRS, QTc, PW, and JT. Association analysis using regression models was conducted between ECG variables and serum electrolytes, sugars, lipids, blood pressure (BP), blood and inflammatory biomarkers, and diseases (e.g., type 2 diabetes, CAD, and stroke). ECG-based and clinical risk scores were developed, and their performance was assessed to predict CAD. Classical regression and machine-learning models were used for risk score development.
RESULTS: Significant associations were observed with ECG traits. RR showed the largest number of associations: e.g., positive associations with bicarbonate, chloride, HDL-C, and monocytes, and negative associations with glucose, insulin, neutrophil, calcium, and risk of T2D. QRS was positively associated with phosphorus, bicarbonate, and risk of CAD. Elevated QTc was observed in CAD patients, whereas decreased QTc was correlated with decreased levels of calcium and potassium. Risk scores developed using regression models were outperformed by machine-learning models. The area under the receiver operating curve reached 0.84 using a machine-learning model that contains ECG traits, sugars, lipids, serum electrolytes, and cardiovascular disease risk factors. The odds ratio for the top decile of CAD risk score compared to the remaining deciles was 13.99.
CONCLUSIONS: ECG abnormalities were associated with serum electrolytes, sugars, lipids, and blood and inflammatory biomarkers. These abnormalities were also observed in T2D and CAD patients. Risk scores showed great predictive performance in predicting CAD.

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