1,721,117 research outputs found
Translational Researchers, Nurses, and Other Health Professionals with Evidence-Based Medicine Terms and Resources
No full textEvidence-based medicine (EBM) is a central theme
in health practice and training. The understanding of EBM
technical terms and the familiarity with EBM resources were
surveyed in four different health professional categories. A
self-administered questionnaire on the familiarity with EBM
terminology and resources was proposed to 218 health professionals
(physicians, translational researchers, nurses, and
others) working in the oncology field. Relationships between
variable and familiarity were examined: Pearson χ2 or exact
Fisher test was used for the categorical variables and one-way
ANOVA for the continuous ones. The odds of familiarity for
subjects, who had followed or not at least one EBM course,
were estimated fitting a multiple logistic regression model
adjusted for age, gender, and profession. All subjects completed
the questionnaire. The majority of health personnel
seemed to lack a sound knowledge of key EBM terms and
sources. Physicians showed the highest knowledge of terms,
nurses the lowest. Physicians also declared the largestfamiliarity with the widest variety of resources, followed by
others and the researchers. The most popular resource was
PLNG, the Italian Guideline System. People who attended at
least one EBMcourse showed consistently higher percentages
of knowledge, but the association was irrelevant for nurses.
Themain perceived barrier to implement EBMin practicewas
a lack of personal time. Familiarity of health professionals
with EBM terminology and resources is still limited to the
medical field and needs to be improved. Increasing education
may be pivotal, even if different approaches should be developed
for different professional categories
Comment on “Safety of systemic hormone replacement therapy in breast cancer survivors: a systematic review and meta‐analysis”
No full text
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Studio sulla mortalità dei lavoratori del Ramo Industriale e della Compagnia Carenanti del Porto di Genova negli ultimi venti anni in rapporto anche al tempo di esposizione.
No full textmortalità - lavoratori porto - studio coorte- tempo di esposizion
Analysis of mortality and hospitalization in patients with dementia.
No full textmortality and hospitalization in patients with dementi
Geografical variation and temporal changes in mortality rates in Liguria.
No full textGeografical variation and temporal changes in mortality rate
The mortality rate of the province of birth as a risk indicator for lung and stomach cancer mortality among Genoa residents born in other italian provinces
No full textprovince of birth - risk indicator - lung cancer mortality - stomach cancer mortality - born in other province
Comparison bias and dilution effect in occupational cohort studies
No full textHealth effects of occupational exposures are frequently evaluated by comparing the mortality of a whole cohort of workers with that of the general population. This study design may be affected by two major biases: a dilution effect (DE), due to the inclusion of unexposed subjects in the study cohort, and a comparison bias (CB), due to the different distribution of risk factors in the reference population. A theoretical model of the joint effect of DE and CB is proposed. Their impact was evaluated in two actual cohorts, selecting specific causes of death based on a priori hypotheses of an association. A linear relationship between the risk estimates and the two biases was found after applying either direct or indirect standardization to adjust for confounding. In the two cohorts, higher risks in exposed workers emerged only after adjusting for DE and CB. Cohort studies without an internal referent group may provide unreliable results
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