Breast cancer and cervical cancer are the most common female cancers in Spain and in many developed countries. The main goal of this paper is to identify the determinants of individual decisions on breast screening and smear testing, that is to say, the decision to take a test for the first time and the decision to test with suitable regularity. To that end, we have combined analyses of micro and macro data (the Spanish National Health Survey and Spanish Regional Social Indicators) and employed multilevel estimation models. Among the main results, we highlight the fact that regional public screening programmes improve individual decisions on screening (more women testing for the first time and more women testing regularly) and, furthermore, they generate positive synergies; for example, regional public programmes for smear testing improve individual decisions on both cervical and breast cancer screening. In addition, we conclude that it is not only important to know if the numbers of women undergoing breast screening and smear testing are increasing, it is also important to know if they are testing regularly.
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http://dx.doi.org/10.1016/j.healthpol.2014.04.012 | DOI Listing |
J Am Coll Cardiol
December 2024
UCL MRC Unit for Lifelong Health and Ageing, University College London, London, United Kingdom; UCL Institute of Cardiovascular Science, University College London, London, United Kingdom; Centre for Inherited Heart Muscle Conditions, Cardiology Department, Royal Free Hospital, London, United Kingdom. Electronic address:
Background: Aircraft noise is a growing concern for communities living near airports.
Objectives: This study aimed to explore the impact of aircraft noise on heart structure and function.
Methods: Nighttime aircraft noise levels (L) and weighted 24-hour day-evening-night aircraft noise levels (L) were provided by the UK Civil Aviation Authority for 2011.
J Am Coll Cardiol
December 2024
Department of Medicine, University of Colorado School of Medicine, Aurora, Colorado, USA; Adult and Child Center for Outcomes Research and Delivery Science, University of Colorado School of Medicine, Aurora, Colorado, USA.
As expensive therapeutics rise to the fore of heart failure management, out-of-pocket (OOP) medication costs have become increasingly relevant to patient care. Prescription medication costs influence medical decision-making and affect adherence. Yet, individualized cost estimates are seldom available during clinical encounters when prescription decisions are made.
View Article and Find Full Text PDFJ Am Coll Cardiol
December 2024
Barts Heart Centre, Barts Health NHS Trust, West Smithfield, London, United Kingdom; Institute of Cardiovascular Science, University College London, London, United Kingdom.
Background: Hypertrophic cardiomyopathy (HCM) is a leading cause of sudden cardiac death. Current diagnosis emphasizes the detection of left ventricular hypertrophy (LVH) using a fixed threshold of ≥15-mm maximum wall thickness (MWT). This study proposes a method that considers individual demographics to adjust LVH thresholds as an alternative to a 1-size-fits-all approach.
View Article and Find Full Text PDFJ Thorac Oncol
January 2025
Department of Cardiothoracic Surgery, New York University Langone Health, New York, New York. Electronic address:
Introduction: The phase 3 randomized controlled trial of extended pleurectomy decortication and chemotherapy versus chemotherapy alone for pleural mesothelioma (PM) (MARS2) reported "extended pleurectomy decortication was associated with worse survival to 2 years, and more serious adverse events for individuals with resectable PM, compared with chemotherapy alone." These results have led to considerable discourse regarding the future role of surgery for PM, and there has not been unanimity in the mesothelioma surgical community regarding the trial interpretation. This "perspective" evaluates MARS2 using internationally renowned PM experts who either agreed with the trial interpretation or who found issues with its conduct which may have influenced the results.
View Article and Find Full Text PDFViruses
November 2024
Faculty of Medical and Health Sciences, Tel Aviv University, Tel Aviv 6997801, Israel.
In this study, we introduce a novel approach that integrates interpretability techniques from both traditional machine learning (ML) and deep neural networks (DNN) to quantify feature importance using global and local interpretation methods. Our method bridges the gap between interpretable ML models and powerful deep learning (DL) architectures, providing comprehensive insights into the key drivers behind model predictions, especially in detecting outliers within medical data. We applied this method to analyze COVID-19 pandemic data from 2020, yielding intriguing insights.
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