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Background Effective gender-based violence (GBV) interventions depend on precise tools to assess healthcare providers' knowledge, attitudes, and practices (KAP). This study aimed to develop and validate a culturally appropriate GBV questionnaire on the KAP of healthcare workers in India using a modified e-Delphi method. Methodology The study used a modified e-Delphi approach, conducted online, to validate a GBV questionnaire. The process included the following three rounds: content validation, quantitative validation, and finalization. It began with a literature review and questionnaire drafting in May 2022, followed by validation from September 2022 to December 2023. The expert panel included healthcare professionals, public health experts, and researchers. The questionnaire included the following four sections: demographic information, knowledge of GBV, attitudes toward GBV, and GBV-related practices. Results In Round 1, significant revisions were made to enhance relevance and clarity, including the addition of a "Don't Know" option and revisions to questions on gender roles and societal expectations. The quantitative validation of Round 2 revealed high scores for Importance (4.980), Usefulness (4.965), Relevance (4.965), Clarity (4.955), Simplicity (4.980), and Ambiguity (4.815), with all items retained and no significant modifications. In Round 3, consensus was achieved, finalizing the questionnaire with expert validation certificates, demonstrating strong reliability and contextual appropriateness. Conclusions The validated KAP questionnaire is a reliable tool for assessing healthcare providers' capacity to manage GBV. It can be used to inform and enhance interventions aimed at improving GBV management in healthcare settings., Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. Institutional Ethics Committee, KLE Jagadguru Gangadhar Mahaswamigalu Moorsavirmath Medical College issued approval JGMMMCIEC/058/2023. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: The study “Catalyzing Change: Enhancing the Capacity of Healthcare Workers to Address Violence Against Women - An Interventional Study in the Field Practice Area of KLE’s JGMM Medical College, Hubballi, Karnataka” was funded by the Research and Development Cell, KAHER, Belagavi, Karnataka, India. Financial relationships: Dr. Namratha Kulkarni Dr. Rizwana B Shaikh declare(s) a grant from Research Cell, KLE Academy of Higher Education and Research. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Kulkarni et al.)

Systemic sclerosis (SSc) is a complex, autoimmune connective tissue disease that affects multiple organs in the body, culminating in a variance of severity and a reduced quality of life. Breast cancer (BC) also affects patients with SSc, and these two conditions affect a similar demographic. With this systematic review, we aim to characterize the links between SSc and BC. Characterizing possible links between SSc and breast malignancies is important for advancing the understanding of SSc management and comorbidities. In this systematic meta-analysis, a comprehensive literature search was conducted in PubMed using relevant keywords and MeSH terms. The inclusion criteria included an English-language retrospective analysis that characterized patients with SSc with or without BC. Two independent reviewers assessed the study's eligibility based on predetermined criteria. Data extraction included patient antibody measurements, demographics (age and gender), family history, social behaviors (alcohol use and smoking history), concurrent condition treatments, and adverse effects following treatment. Thirteen articles were identified in the literature with relevant data on SSc and BC patients. Studies encompassed research about SSc patients with or without BC and relevant risk factors being measured. SSc was found to have a link to antibodies widely associated with cancer. Adverse treatment outcomes and concurrent conditions of BC were found when patients had a family history of SSc, BC, or an alcohol or smoking history. Our results suggest that the presence of antinuclear antibodies, anti-centromere antibodies, or anti-topoisomerase antibodies in SSc patients is correlated with BC. Out of the three antibodies, ATA seemed to be found more commonly in patients with SSc and malignancy across the studies. This systematic review discusses the link between SSc and BC through patients with relevant clinical markers, medical histories, and treatments. However, further research is necessary to advance the linkage between SSc and BC and determine whether management of one condition may prevent or alleviate the other., Competing Interests: Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Dutt et al.)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel coronavirus discovered in late 2019 in Wuhan, Hubei Province, China. The virus has now developed into a full-scale global pandemic affecting hundreds of millions of people to date. A majority of cases present with nonspecific acute upper respiratory symptoms. A wide range of systemic symptoms has been reported, with some patients presenting with nonspecific extrapulmonary symptoms. Recently, there has been an increased association of COVID-19-positive patients presenting with ocular symptoms. As an increasing number of patients present with ophthalmic manifestations, recognizing these visual symptoms is of utmost importance. Some patients may present with ocular symptoms as the first indication of COVID-19 infection; quickly isolating and starting treatment can aid in stopping the spread of this novel coronavirus. This review will describe the current epidemiology and pathophysiology of SARS-CoV-2, emphasizing the ophthalmic manifestations and their clinical course progression. Further, we will be reporting on the growing number of rare ocular manifestations that have occurred in some COVID-19-positive patients, along with the route of transmission, specific manifestations, and the treatment methods for both these pulmonary and extrapulmonary symptoms, specifically the ocular manifestations., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2024, Patel et al.)

A systematic search was conducted on the PubMed database using the keywords "education," "melanoma," and "African Americans." The results were filtered to include studies published within the last decade that focused on melanoma diagnosis, risk, or outcomes. These selected studies included African Americans, non-Hispanic Black individuals, or those with darker skin tones and compared them with educational interventions or non-Hispanic White groups. The studies showed an overall positive impact of targeted educational initiatives on using sun-protective behaviors, health education, and self-efficacy related to melanoma. Notably, interventions proven to be effective for non-Hispanic White populations also demonstrated efficacy in other racial groups, including non-Hispanic Blacks. It was observed that non-Hispanic Blacks exhibited an overall reduced level of concern regarding melanoma, partly due to its lower incidence within this demographic. Furthermore, these studies focussed on the disparities in melanoma incidence and survival rates among different racial groups. Non-Hispanic Black individuals were found to have a higher incidence of melanoma and lower survival rates compared to non-Hispanic White individuals. Collectively, the studies evaluating melanoma educational interventions for darker skin tones yield promising results for improving melanoma prognosis in Black communities. They underscore the importance of addressing racial disparities in melanoma awareness, diagnosis, and treatments. These studies also highlighted the barriers to sun protection behaviors, such as cost, limited awareness, and misconceptions, particularly prevalent among ethnic communities and youth. The use of melanoma photographs specifically tailored to darker skin tones in outreach efforts to enhance identification, self-examination, and early detection should be considered to improve melanoma prognosis similar to the non-White population., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2023, Shaikh et al.)

Diagnoses of autism spectrum disorders (ASD) are typically made after toddlerhood by examining behavioural patterns. Earlier identification of ASD enables earlier intervention and better outcomes. Machine learning provides a data-driven approach of diagnosing autism at an earlier age. This review aims to summarize recent studies and technologies utilizing machine learning based strategies to screen infants and children under the age of 18 months for ASD, and identify gaps that can be addressed in the future. We reviewed nine studies based on our search criteria, which includes primary studies and technologies conducted within the last 10 years that examine children with ASD or at high risk of ASD with a mean age of less than 18 months old. The studies must use machine learning analysis of behavioural features of ASD as major methodology. A total of nine studies were reviewed, of which the sensitivity ranges from 60.7% to 95.6%, the specificity ranges from 50% to 100%, and the accuracy ranges from 60.9% to 97.7%. Factors that contribute to the inconsistent findings include the varied presentation of ASD among patients and study design differences. Previous studies have shown moderate accuracy, sensitivity and specificity in the differentiation of ASD and non-ASD individuals under the age of 18 months. The application of machine learning and artificial intelligence in the screening of ASD in infants is still in its infancy, as observed by the granularity of data available for review. As such, much work needs to be done before the aforementioned technologies can be applied into clinical practice to facilitate early screening of ASD., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2021, Siddiqui et al.)