This article describes the process evaluation of two interventions (tailored or general information) to encourage people to behave in a manner conducive to the early detection of cancer. A total of 1040 Dutch adults participated in the study. Tailored information is adapted to the characteristics, needs and interests of the individual, and hence has more personal relevance and contains less redundant information. It was therefore hypothesized that tailored information would be evaluated better than general information, does not increase worries, influences attitude and behavior change, and that no differences in subgroups would be found in the reactions to the tailored information. The results showed that both kinds of information were read by a large majority of the participants. Recipients of the tailored information saved and discussed the information with others more often, and they were more appreciative of its format and content. Tailored information resulted significantly more often in changes in attitudes and behavior after the intervention. It is concluded that information adapted to individuals' characteristics is an accepted method of health education in early detection of cancer.
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http://dx.doi.org/10.1093/her/17.2.239 | DOI Listing |
Scand J Urol
January 2025
Department of Urology, Odense University Hospital, Odense, Denmark; Academy of Geriatric Cancer Research (AgeCare), Odense University Hospital, Odense, Denmark; Department of Clinical Research, University of Southern Denmark, Odense, Denmark.
Objective: Early and accurate diagnosis of prostate cancer (PC) is crucial for effective treatment. Diagnosing clinically insignificant cancers can lead to overdiagnosis and overtreatment, highlighting the importance of accurately selecting patients for further evaluation based on improved risk prediction tools. Novel biomarkers offer promise for enhancing this diagnostic process.
View Article and Find Full Text PDFAdv Clin Exp Med
January 2025
Luddy School of Informatics, Computing and Engineering, Indiana University, Bloomington, USA.
Background: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma (RCC). Due to the lack of symptoms until advanced stages, early diagnosis of ccRCC is challenging. Therefore, the identification of novel secreted biomarkers for the early detection of ccRCC is urgently needed.
View Article and Find Full Text PDFEmergencias
December 2024
Servicio de Urgencias, Hospital Clínic, IDIBAPS, Universitat de Barcelona, Barcelona, España.
Hidden infections and late diagnoses are currently the main challenges of the HIV pandemic. Emergency departments (EDs) are one of the health care system's key resources addressing these challenges. In 2020, the Spanish Society of Emergency Medicine (SEMES) published recommendations for ordering HIV serology testing for patients with certain health conditions, and in 2021 SEMES launched the "Leave Your Mark" (Deja tu Huella - DTH) program to facilitate implementing the recommendations during emergency care.
View Article and Find Full Text PDFAnal Chem
January 2025
State Key Laboratory of Integrated Optoelectronics, College of Electronics Science and Engineering, Jilin University, No. 2699 Qianjin Street, Changchun, Jilin 130012, P. R. China.
Hepatitis D virus (HDV) significantly influences the progression of liver diseases. Through clinical observations and database analyses, it has been established that patients coinfected with HDV and hepatitis B virus (HBV) experience accelerated progression toward cirrhosis, hepatocellular carcinoma (HCC), and liver failure compared to those infected solely with HBV. A higher viral load correlates with increased replicative activity, enhanced infectivity, and more severe disease manifestations.
View Article and Find Full Text PDFHeliyon
January 2025
Cancer Early Detection Advanced Research Center (CEDAR), Knight Cancer Institute, Oregon Health and Science University, Portland, OR, USA.
Neurosignaling is increasingly recognized as a critical factor in cancer progression, where neuronal innervation of primary tumors contributes to the disease's advancement. This study focuses on segmenting individual axons within the prostate tumor microenvironment, which have been challenging to detect and analyze due to their irregular morphologies. We present a novel deep learning-based approach for the automated segmentation of axons, AxonFinder, leveraging a U-Net model with a ResNet-101 encoder, based on a multiplexed imaging approach.
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