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Understanding the Medical Education Experiences of Low-Income Students Through a Maslow's Hierarchy of Needs Lens: An Exploratory Qualitative Study.
J Gen Intern Med
January 2025
MD/PhD Program, Yale School of Medicine, New Haven, CT, USA.
Background: Diversity in the physician workforce is critical for quality patient care. Students from low-income backgrounds represent an increasing proportion of medical school matriculants, yet little research has addressed their medical school experiences.
Objective: To explore the medical school experiences of students from low-income backgrounds using a modified version of Maslow's Hierarchy of Needs (physiologic, safety, love/belonging, esteem, and self-actualization) as a theoretical framework.
Psychometric evaluation of the Yale-Brown Obsessive-Compulsive Scale in pregnant women.
Arch Womens Ment Health
January 2025
Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, 77030, USA.
Purpose: Although many women experience obsessive-compulsive symptoms during the perinatal period, the Yale-Brown Obsessive Compulsive Scale (YBOCS) has not yet been psychometrically evaluated in this population. This study examined the internal consistency, convergent and divergent validity, and factor structure of the YBOCS among pregnant women.
Methods: 256 Women who were 20 to 24 weeks pregnant completed the clinician-administered YBOCS and Mini International Neuropsychiatric Interview (MINI) along with a series of self-report questionnaires including the Edinburgh Postnatal Depression Scale (EPDS), Perinatal Anxiety Screening Scale (PASS) and Obsessive-Compulsive Inventory-Revised (OCI-R).
Education moderates the association between motor involvement and executive status in ALS.
Eur J Neurol
January 2025
Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Milan, Italy.
Background: This study aimed to determine whether educational attainment-a common proxy of cognitive reserve (CR)-influences the association between motor and cognitive/behavioural outcomes in a large cohort of ALS patients without dementia.
Methods: N = 726 ALS patients without FTD were assessed for motor (ALSFRS-R), cognitive (Edinburgh Cognitive and Behavioural ALS Screen, ECAS) and behavioural outcomes (ECAS-Carer Interview, ECAS-CI). CR was operationalized via educational attainment (in years).
Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations.
Lancet Digit Health
January 2025
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK; National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre, Birmingham, UK; Centre for Patient Reported Outcomes Research, School of Health Sciences, College of Medical and Dental Sciences, Birmingham, UK; University of Birmingham, Birmingham, UK. Electronic address:
Article Synopsis
- There is a significant risk of reinforcing existing health inequalities in AI health technologies due to biases, primarily stemming from the datasets used.
- The STANDING Together recommendations focus on transparency in health datasets and proactive evaluation of their impacts on different population groups, informed by a comprehensive research process with over 350 global contributors.
- The 29 recommendations are divided into guidance for documenting health datasets and strategies for using them, aiming to identify and reduce algorithmic biases while promoting awareness of the inherent limitations in all datasets.
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