Publications by authors named "E Linos"
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.
Article Synopsis
- Cutaneous melanoma (CM) and non-melanoma skin cancer (NMSC) rates are increasing in postmenopausal women, but the impact of vitamin A on their risk remains unclear.
- A study of 52,877 White women found no link between total vitamin A intake and melanoma risk; however, higher dietary vitamin A and beta-cryptoxanthin were correlated with an increased risk of NMSC.
- The findings suggest that while vitamin A does not lower CM or NMSC risk, higher dietary intakes may actually increase NMSC risk in this demographic.
Article Synopsis
- Digital health innovations are crucial for tackling healthcare challenges, especially in low-resource areas, and the COVID-19 pandemic highlighted their significance for public health.
- In South and Southeast Asia, diverse cultural contexts create both challenges and opportunities for implementing these digital health solutions.
- Ongoing research and local partnerships are essential for developing effective digital health infrastructures, which can inform global strategies in low- and middle-income countries.
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.
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