Incentives and limitations of Greek blood donors: Application of the Health Belief Model in the design of recruiting strategies.

BACKGROUND: Studies of the behavior of blood donors suggest that the examination of their incentives and reported barriers could be utilized in designing targeted recruiting strategies and awareness-raising campaigns. METHODOLOGY: Data was collected via a questionnaire based on the Health Belief Model (HBM), aimed to examine reported incentives, limitations, benefits, and self-efficacy of 261 blood donors at Thriasio General Hospital from January 1 to March 1, 2020, after required permission provided. The analysis was performed by the use of the SPSS statistical software. In addition, a Greek translation of the K6+ distress scale was provided. RESULTS: Our sample consisted of 261 blood donors, the majority of which were men (88.5%), 40-50 years old (36.4%), high school graduates (49.4%), and married (53.3%). Heightened awareness of increased blood needs and blood shortages was mentioned. 92.8% of respondents believe that blood donation is an act of contribution to society or beneficial for their health (86.6%). The limited working hours of blood donation services are the main obstacle mentioned by the participants (32.8%), while 80.7% emphasized the need for public information campaigns. Based on the K6 scale answers score, most participants are classified in the intermediate-risk category for Serious Mental Illness (SMI). CONCLUSION: The study of beliefs and incentives of blood donors is a critical factor in developing an effective recruiting strategy in a volunteering frame. Public information campaigns regarding the blood donation process and reminders aiming at the return of blood donors after the necessary time interval could facilitate this effort.

Options and Limitations in Clinical Investigation of Bacterial Biofilms.

Bacteria can form single- and multispecies biofilms exhibiting diverse features based upon the microbial composition of their community and microenvironment. The study of bacterial biofilm development has received great interest in the past 20 years and is motivated by the elegant complexity characteristic of these multicellular communities and their role in infectious diseases. Biofilms can thrive on virtually any surface and can be beneficial or detrimental based upon the community's interplay and the surface. Advances in the understanding of structural and functional variations and the roles that biofilms play in disease and host-pathogen interactions have been addressed through comprehensive literature searches. In this review article, a synopsis of the methodological landscape of biofilm analysis is provided, including an evaluation of the current trends in methodological research. We deem this worthwhile because a keyword-oriented bibliographical search reveals that less than 5% of the biofilm literature is devoted to methodology. In this report, we (i) summarize current methodologies for biofilm characterization, monitoring, and quantification; (ii) discuss advances in the discovery of effective imaging and sensing tools and modalities; (iii) provide an overview of tailored animal models that assess features of biofilm infections; and (iv) make recommendations defining the most appropriate methodological tools for clinical settings.

Preventing Data Ambiguity in Infectious Diseases with Four-Dimensional and Personalized Evaluations.

BACKGROUND: Diagnostic errors can occur, in infectious diseases, when anti-microbial immune responses involve several temporal scales. When responses span from nanosecond to week and larger temporal scales, any pre-selected temporal scale is likely to miss some (faster or slower) responses. Hoping to prevent diagnostic errors, a pilot study was conducted to evaluate a four-dimensional (4D) method that captures the complexity and dynamics of infectious diseases. METHODS: Leukocyte-microbial-temporal data were explored in canine and human (bacterial and/or viral) infections, with: (i) a non-structured approach, which measures leukocytes or microbes in isolation; and (ii) a structured method that assesses numerous combinations of interacting variables. Four alternatives of the structured method were tested: (i) a noise-reduction oriented version, which generates a single (one data point-wide) line of observations; (ii) a version that measures complex, three-dimensional (3D) data interactions; (iii) a non-numerical version that displays temporal data directionality (arrows that connect pairs of consecutive observations); and (iv) a full 4D (single line-, complexity-, directionality-based) version. RESULTS: In all studies, the non-structured approach revealed non-interpretable (ambiguous) data: observations numerically similar expressed different biological conditions, such as recovery and lack of recovery from infections. Ambiguity was also found when the data were structured as single lines. In contrast, two or more data subsets were distinguished and ambiguity was avoided when the data were structured as complex, 3D, single lines and, in addition, temporal data directionality was determined. The 4D method detected, even within one day, changes in immune profiles that occurred after antibiotics were prescribed. CONCLUSIONS: Infectious disease data may be ambiguous. Four-dimensional methods may prevent ambiguity, providing earlier, in vivo, dynamic, complex, and personalized information that facilitates both diagnostics and selection or evaluation of anti-microbial therapies.