Sara Burgoa

This study uses the National Survey of Children’s Health to examine the nationwide prevalence and severity of US adolescent mental health issues in the 12–17 age group between the years 2022 and 2023 in relation to parental mental health and exposure to adverse childhood experiences (ACEs). We used the NSCH data collected for 12–17-year-old adolescents. Descriptive statistics were generated for the selected sample and binary logistics regressions were conducted to examine influential factors for the presence and severity of adolescent depression and anxiety for the selected year. Adolescents aged 12–17 who experienced neighborhood violence had higher odds of being diagnosed with anxiety (OR = 1.369, p = 0.009) and depression (OR = 1.508, p = 0.004). Those living with someone who was mentally ill, suicidal, or severely depressed showed increased odds of anxiety (OR = 1.642, p < 0.001) and depression (OR = 1.587, p < 0.001). Adolescents judged unfairly due to a health condition or disability had markedly higher odds of anxiety (OR = 3.056, p < 0.001) and depression (OR = 1.835, p < 0.001), including severe forms (severe anxiety OR = 2.569; severe depression OR = 2.238; both p < 0.001). Poorer parental emotional health was consistently associated with higher adolescent anxiety and depression, with “fair” parental emotional health showing the strongest association for depression (OR = 7.320, p < 0.001). These findings demonstrate the need for better tailored mental health efforts towards both adolescents and their caregivers highlighting the harm of long-term environmental and familial stressors, and the gaps in community approaches in this population.

Objectives: This scoping review aims to fill research gaps by exploring four guiding research questions. First, we aim to understand the major barriers encountered by U.S. menstruating college students in accessing menstrual health products at their educational institutions, households, and community. Second, we aim to identify social determinants of health (SDoH) that significantly influence and contribute to menstrual health inequities experienced by U.S. college students. Third, we aim to explore the measurement tools that have been used to assess menstrual health inequities experienced by U.S. menstruating college students. Lastly, we aim to determine the lessons learned and recommendations to improve overall menstrual health outcomes in U.S. menstruating college students. Study Design: This scoping review followed the Arksey and O’Malley framework (2005) and incorporated recommendations from the Joanna Briggs Institute (JBI) for the extraction, analysis, and presentation of results. Methods: The four databases searched were PubMed, Embase (Ovid), Web of Science, and Cochrane Library (Medline). Included articles were (1) published between 2000 and 2023, (2) focused on menstruating college students in the United States, (3) addressed menstrual health, menstrual equity, and period poverty in college campuses in the U.S., and/or (4) explored challenges encountered by menstruating college students in accessing menstrual health products. Results: A total of seven studies were retained for assessment. The most frequently cited Healthy People 2030 categories were economic stability (n = 5) and social and community context (n = 5). The most-cited barriers were sorted into the “Financial Constraints and Accessibility” (n = 13) theme category. Conclusions: Our study highlights practical applications and several recommendations for the future design, adoption, implementation, and evaluation of effective evidence-based interventions to address period poverty and subsequent barriers imposed by menstruating college students specific SDoH. More research is needed to further explore the health implications of menstrual health on mental, physical, and socioeconomic outcomes of menstruating individuals, particularly young adults experiencing different challenges as they venture into college and build their careers.

Background: The United States (US) continues to face a substantial burden of cervical cancer, which has been the focus of many policies and public health prevention agendas. Of the numerous risk factors associated with cervical cancer, human papillomavirus (HPV) infection remains the leading and most preventable cause of this chronic disease. Therefore, one major public health prevention strategy to decrease cervical cancer cases is HPV vaccination. Another screening tool that enables cervical cancer prevention and early intervention is the Pap smear, the primary method of screening for abnormal cervical cells. However, barriers such as social determinants of health and ineffective patient–provider communication hinder access to such critical preventive measures. The purpose of this study was to provide a comprehensive overview of the knowledge level of US female adults, aged 21–65 years, concerning HPV infection and cervical cancer prevention using the Health Information National Trends Survey (HINTS) database. Additionally, it assessed associations between patient–provider communication and the completion of Pap smear tests. Methods: Descriptive statistics were computed to explore the sociodemographic characteristics of female survey participants as well as to gather frequency and percentages of responses related to knowledge of HPV, awareness of the HPV vaccine, and history of Pap smear. Chi-squared tests were carried out to examine the associations between awareness of a cervical cancer vaccine or HPV shot and whether the participant has had a Pap smear, heard of the HPV vaccine, and knowledge of HPV’s association with cervical cancer. Next, binary logistic regression models were built to determine the size and direction of the association between patient–provider communication metrics and measures of (1) having had a Pap smear, (2) participant knowledge of HPV, (3) participant awareness of causality between HPV and cervical cancer, and (4) participant knowledge of HPV vaccine and cervical cancer prevention measures. Results: A substantial majority of participants (81.8%) reported having heard of HPV. Among them, 72.1% recognized that HPV could cause cervical cancer. Awareness of the HPV vaccine was reported by 88.1%, suggesting a relatively high reach of effective public health messaging. Regarding Pap tests, 43.3% of participants had undergone testing within the past year, but 12.6% had not been tested in over five years, and 3.6% have never been tested. Bivariate analysis using chi-squared tests revealed significant associations between participants’ history of Pap smears and their knowledge of HPV infection, its role in cervical cancer, and HPV vaccination as a prevention tool. Participants who had undergone a Pap test were more likely to have heard of HPV (p < 0.001), were knowledgeable of the HPV vaccine (p < 0.001), and were more aware of the HPV vaccine (p < 0.001). Participants reporting “never” for certain communication criteria significantly had an increased risk of having lower knowledge levels about the HPV vaccine and other cervical cancer prevention measures. They also had almost twice the risk of having lower knowledge levels about HPV prevention measures when reporting “never” (RR = 1.997, 95% CI (1.018–3.916) for “spending enough time with patients” compared to those selecting “always”. Additionally, participants responding “sometimes” (RR = 1.889, 95% CI (1.187–3.005) rather than “always” to feeling involved in healthcare decisions had a significantly higher risk of being unaware of the vaccine or other cervical cancer prevention measures. Conclusions: Strengthening provider communication and education skills not only encourages greater patient knowledge and adherence to preventative measures, such as HPV and cervical cancer screening, but also reduces disparities in healthcare stemming from limited health literacy.

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Background: This systematic review has the following aims: (1) to identify measurement tools used globally by healthcare providers to diagnose PCOS in women at elevated risk; (2) to assess the comprehensiveness of these tools regarding mental health and chronic pain; (3) to list strategies for validating, disseminating, and implementing these tools; and (4) to provide future recommendations for experts in healthcare settings. Methods: This review utilized the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) and the Arksey and O’Malley York methodology. Studies were sourced from the PubMed, Embase, and Cochrane Library databases, with inclusion criteria focusing on peer-reviewed articles addressing PCOS diagnosis and associated comorbidities. Data extraction and analysis followed the Joanna Briggs Institute (JBI) recommendations. Results: A total of 63 studies met the inclusion criteria. Findings indicate that current screening tools for PCOS often lack comprehensive integration of mental health and chronic pain assessments. Tools like the PCOSQ and its updated version, PCOSQ-50, inadequately address pain-related symptoms, highlighting a gap in holistic patient evaluation. This review identified significant associations between PCOS and mental health disorders, including anxiety and depression, emphasizing the need for mental health screenings as part of PCOS management. Conclusions: There is a critical need for validated PCOS screening tools that encompass both physical and psychological aspects of the condition. Educating healthcare providers on the cultural and social determinants influencing PCOS can improve diagnosis and patient outcomes. Future research should focus on developing holistic screening tools and culturally relevant educational resources, aiming to enhance the overall quality of life for women with PCOS.

Background: Artificial intelligence (AI) algorithms can be applied in breast cancer risk prediction and prevention by using patient history, scans, imaging information, and analysis of specific genes for cancer classification to reduce overdiagnosis and overtreatment. This scoping review aimed to identify the barriers encountered in applying innovative AI techniques and models in developing breast cancer risk prediction scores and promoting screening behaviors among adult females. Findings may inform and guide future global recommendations for AI application in breast cancer prevention and care for female populations. Methods: The PRISMA-SCR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) was used as a reference checklist throughout this study. The Arksey and O’Malley methodology was used as a framework to guide this review. The framework methodology consisted of five steps: (1) Identify research questions; (2) Search for relevant studies; (3) Selection of studies relevant to the research questions; (4) Chart the data; (5) Collate, summarize, and report the results. Results: In the field of breast cancer risk detection and prevention, the following AI techniques and models have been applied: Machine and Deep Learning Model (ML-DL model) (n = 1), Academic Algorithms (n = 2), Breast Cancer Surveillance Consortium (BCSC), Clinical 5-Year Risk Prediction Model (n = 2), deep-learning computer vision AI algorithms (n = 2), AI-based thermal imaging solution (Thermalytix) (n = 1), RealRisks (n = 2), Breast Cancer Risk NAVIgation (n = 1), MammoRisk (ML-Based Tool) (n = 1), Various MLModels (n = 1), and various machine/deep learning, decision aids, and commercial algorithms (n = 7). In the 11 included studies, a total of 39 barriers to AI applications in breast cancer risk prediction and screening efforts were identified. The most common barriers in the application of innovative AI tools for breast cancer prediction and improved screening rates included lack of external validity and limited generalizability (n = 6), as AI was used in studies with either a small sample size or datasets with missing data. Many studies (n = 5) also encountered selection bias due to exclusion of certain populations based on characteristics such as race/ethnicity, family history, or past medical history. Several recommendations for future research should be considered. AI models need to include a broader spectrum and more complete predictive variables for risk assessment. Investigating long-term outcomes with improved follow-up periods is critical to assess the impacts of AI on clinical decisions beyond just the immediate outcomes. Utilizing AI to improve communication strategies at both a local and organizational level can assist in informed decision-making and compliance, especially in populations with limited literacy levels. Conclusions: The use of AI in patient education and as an adjunctive tool for providers is still early in its incorporation, and future research should explore the implementation of AI-driven resources to enhance understanding and decision-making regarding breast cancer screening, especially in vulnerable populations with limited literacy.