Although vaccination uptake is high in most countries, pockets of suboptimal coverage remain, such as those observed among ultra-orthodox Jews in Israel and elsewhere, posing a threat to both individual and public immunity. Drawing on the Precaution Adoption Process Model (PAPM), this study proposes a Non-Vaccination Stage Model (NVSM) to analyze the decision-making process among Non-Vaccinating Parents (NVPs), focusing on the ultra-orthodox Jewish population of Israel. In-depth interviews were conducted with 10 Israeli ultra-orthodox Jewish NVPs (mothers). The interviews revealed five stages in the participants' decision-making process: Being good mothers who vaccinate their children; Emergence of doubts regarding the risks of vaccination; Personal vaccination policy-hesitancy concerning vaccination; Decision not to vaccinate; Confirmation signs of what participants perceive as a wise decision. NVSM can help understand parents who consider non-vaccination to be healthier behavior and explore the various stages of their decision-making process. Differentiating among the various stages of NVPs' decision-making processes enables application of different intervention approaches by policymakers and healthcare practitioners.
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http://dx.doi.org/10.1177/1363459320988884 | DOI Listing |
Sci Rep
December 2024
Department of Architecture, Rafsanjan Branch, Islamic Azad University, Rafsanjan, Iran.
The advent of smart cities has brought about a paradigm shift in urban management and citizen engagement. By leveraging technological advancements, cities are now able to collect and analyze extensive data to optimize service delivery, allocate resources efficiently, and enhance the overall well-being of residents. However, as cities become increasingly interconnected and data-dependent, concerns related to data privacy and security, as well as citizen participation and representation, have surfaced.
View Article and Find Full Text PDFOpen Vet J
November 2024
Pasteur Institute of Tunis, Tunis, Tunisia.
Background: Since 2012, the northeast region of Tunisia has witnessed an increase in dog rabies cases, indicating a concerning emergence of the disease. Previous studies have indicated the widespread nature of rabies in northern Tunisia. However, there remains a lack of comprehensive understanding regarding the associated risk factors.
View Article and Find Full Text PDFFront Hum Neurosci
December 2024
Department of Information Medicine, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan.
Accurate interoceptive processing in decision-making is essential to maintain homeostasis and overall health. Disruptions in this process have been associated with various psychiatric conditions, including depression. Recent studies have focused on nutrient homeostatic dysregulation in depression for effective subtype classification and treatment.
View Article and Find Full Text PDFBMC Med Imaging
December 2024
Department of MRI, Xinxiang Central Hospital (The Fourth Clinical College of Xinxiang Medical University), 56 Jinsui Road, Xinxiang, Henan, 453000, China.
Background: To develop and validate an interpretable machine learning model based on intratumoral and peritumoral radiomics combined with clinicoradiological features and metabolic information from magnetic resonance spectroscopy (MRS), to predict clinically significant prostate cancer (csPCa, Gleason score ≥ 3 + 4) and avoid unnecessary biopsies.
Methods: This study retrospectively analyzed 350 patients with suspicious prostate lesions from our institution who underwent 3.0 Tesla multiparametric magnetic resonance imaging (mpMRI) prior to biopsy (training set, n = 191, testing set, n = 83, and a temporal validation set, n = 76).
BMC Public Health
December 2024
Bengbu Medical University, School of Health Management, Bengbu, China.
Objective: To explore the health information avoidance behaviors and influencing factors of cancer patients, and to construct a structural equation model to analyze the mediating roles of self-efficacy and negative emotions in the process of generating health information avoidance behaviors of cancer patients.
Methods: A face-to-face electronic questionnaire was used to collect data. Applying a chi-square test and multivariate logistic regression model to analyze the role of different socio-demographic factors in influencing health information avoidance behavior of cancer patients; applying structural equation modeling to analyze the role mechanism of health information avoidance behavior of cancer patients.
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