"Learning from those who know the system inside and out": Experiences of physician mothers who are informal caregivers.

Background: For physicians, the added responsibility of being an informal caregiver (IC, providing regular care for seriously ill loved ones) can create challenges such as increased rates of burnout that have received little attention. In this study, we explored physician mothers' informal caregiving experiences and probed their perspectives on how health systems can better support their needs.

Method: From September 14, 2021, to October 31, 2021, we distributed an online survey to a national sample of physician mothers who self-identified as ICs; survey questions examined their caregiving responsibilities and perspectives on workplace changes needed to support them.

Mental health care needs of caregivers of people with Alzheimer's disease from online forum analysis.

Informal caregivers of people with Alzheimer's disease and related dementias (ADRD) are at risk of poor mental health. This study aimed to investigate the feasibility and validity of studying caregivers' mental stressors using online caregiving forum data (March 2018-February 2022) and natural language processing and machine learning (NLP/ML). NLP/ML topic modeling generated eight prominent topics, which we compared with qualitatively defined themes and the existing caregiving framework to assess validity.

Skin Cancer and Other Dermatologic Conditions Among US Veterans.

Importance: US veterans may be at an increased risk of developing various dermatologic conditions compared with nonveterans.

Objectives: To compare the prevalence and the odds of dermatologic conditions (eg, skin cancers, dermatitis/eczema/rash, psoriasis) between veterans and nonveterans.

Design, Setting, And Participants: This population-based cross-sectional study leveraged nationally representative data from the National Health and Nutrition Examination Survey (NHANES).

Large language models outperform mental and medical health care professionals in identifying obsessive-compulsive disorder.

Despite the promising capacity of large language model (LLM)-powered chatbots to diagnose diseases, they have not been tested for obsessive-compulsive disorder (OCD). We assessed the diagnostic accuracy of LLMs in OCD using vignettes and found that LLMs outperformed medical and mental health professionals. This highlights the potential benefit of LLMs in assisting in the timely and accurate diagnosis of OCD, which usually entails a long delay in diagnosis and treatment.

Online, home-based dystrophic epidermolysis bullosa registry.

Genetic testing is the gold standard for diagnosing different epidermolysis bullosa (EB) subtypes; however, testing rates are low. We conducted a pilot study to test feasibility of a novel, home-based registry that involved patients with EB submitting self-reported clinical symptoms using secure, online surveys (REDCap) and submitting buccal swabs for exome sequencing of EB-related genes (GeneDx). In total, 50 EB participants were enrolled, with an average age of 17 years and an average distance of 198 miles from EB specialty centers.

Telehealth Utilization and Associations in the United States During the Third Year of the COVID-19 Pandemic: Population-Based Survey Study in 2022.

Background: The COVID-19 pandemic rapidly changed the landscape of clinical practice in the United States; telehealth became an essential mode of health care delivery, yet many components of telehealth use remain unknown years after the disease's emergence.

Objective: We aim to comprehensively assess telehealth use and its associated factors in the United States.

Methods: This cross-sectional study used a nationally representative survey (Health Information National Trends Survey) administered to US adults (≥18 years) from March 2022 through November 2022.

Impact of COVID-19, cancer survivorship and patient-provider communication on mental health in the US Difference-In-Difference.

Poor mental health has been found to be more prevalent among those with cancer and is considered a public health crisis since COVID-19. This study assessed the impact of COVID-19 and cancer survivorship on mental health and investigated factors, including online patient-provider communications (OPPC; email/internet/tablet/smartphone), associated with poor mental health prior to and during the early COVID-19. Nationally representative Health Information National Trends Survey data during 2017-2020 (n = 15,871) was used.

Human-AI interaction in skin cancer diagnosis: a systematic review and meta-analysis.

The development of diagnostic tools for skin cancer based on artificial intelligence (AI) is increasing rapidly and will likely soon be widely implemented in clinical use. Even though the performance of these algorithms is promising in theory, there is limited evidence on the impact of AI assistance on human diagnostic decisions. Therefore, the aim of this systematic review and meta-analysis was to study the effect of AI assistance on the accuracy of skin cancer diagnosis.

Incidence of Nonkeratinocyte Skin Cancer After Breast Cancer Radiation Therapy.

Importance: Previous studies have suggested that radiation therapy may contribute to an increased risk of subsequent nonkeratinocyte (ie, not squamous and basal cell) skin cancers.

Objective: To test the hypothesis that radiation therapy for breast cancer increases the risk of subsequent nonkeratinocyte skin cancers, particularly when these cancers are localized to the skin of the breast or trunk.

Design, Setting, And Participants: This population-based cohort study used longitudinal data from the Surveillance, Epidemiology, and End Results (SEER) Program for January 1, 2000, to December 31, 2019.

A Comparison of ChatGPT and Fine-Tuned Open Pre-Trained Transformers (OPT) Against Widely Used Sentiment Analysis Tools: Sentiment Analysis of COVID-19 Survey Data.

Background: Health care providers and health-related researchers face significant challenges when applying sentiment analysis tools to health-related free-text survey data. Most state-of-the-art applications were developed in domains such as social media, and their performance in the health care context remains relatively unknown. Moreover, existing studies indicate that these tools often lack accuracy and produce inconsistent results.

Prevalence and associations of poor mental health in the third year of COVID-19: U.S. population-based analysis from 2020 to 2022.

Background: Poorer mental health was found early in the COVID-19 pandemic, yet mental health in the third year of COVID-19 has not been assessed on a general adult population level in the United States.

Methods: We used a nationally representative cross-sectional survey (Health Information National Trends Survey, HINTS 5 2020 n = 3,865 and HINTS 6 2022 n = 6,252). The prevalence of poor mental health was examined using a Patient Health Questionnaire-4 scale in 2020 and 2022.

Longitudinal remote monitoring of hidradenitis suppurativa: a pilot study.

We sought to investigate the feasibility of longitudinal monitoring of disease activity from home in people with hidradenitis suppurativa (HS). Over 6 months, our novel digital tool collected 421 photos of HS-affected skin from 27 participants and captured trends in pain and quality of life scores. We found that participants with mild disease were more likely to share their progress than those with more severe disease, which is favourable as it may suggest a role for remote monitoring in tracking disease progression.

Development of a digital tool for home-based monitoring of skin disease for older adults.

We developed a digital tool for home-based monitoring of skin disease, our digital tool. In the current observational pilot study, we found that DORA is feasible to use in practice, as it has a high patient compliance, retention and satisfaction. Clinicans rated the photos generally good quality or perfect quality.

Estimating remaining life expectancy in veterans with basal cell carcinoma using an automated electronic health record scoring system: A retrospective cohort study.

Background: Active surveillance may be considered for low-risk basal cell carcinomas (BCCs) in patients with limited life expectancy; however, estimates of life expectancy are not readily available. Veterans Health Administration's Care Assessment Need (CAN) score may address this problem.

Objective: We examined the CAN score's performance in predicting 1-, 3-, and 5-year mortality in US veterans with BCC.