1,720,973 research outputs found
The Impact of Socio-Economic Conditions on Individuals’ Health: Development of an Index and Examination of its Association with Three of the Most Frequently Registered Diseases in Lazio Region of Italy
Full text linkThis study examines spatial disparities and associations between the social deprivation
index (SDI) and Type 2 Diabetes, Dementia, and Heart Failure in Italy’s Lazio Region.
The primary goal is to assess how social deprivation impacts health inequalities by analys-
ing SDI-disease correlations. This retrospective study uses 2020 socioeconomic data and
2021 epidemiological indicators in Lazio Region, Italy. The SDI, constructed following
established guidelines, measures social deprivation. Statistical tools, including regression
models, Moran’s I test, and LISA techniques, are used to analyse spatial patterns. Uti-
lizing a retrospective approach, we merge 2020 socioeconomic and 2021 epidemiologi-
cal data for analysis. The SDI is computed using established methods. Spatial disparities
are explored through regression models, Moran’s I test, and LISA techniques. The study
reveals significant disparities in disease incidence. District V in Rome exhibits high Type 2
Diabetes (113.75/1000) and Heart Failure (37.98/1000) rates, while Marcetelli has elevated
Dementia incidence (19.74). Southern municipalities face high unemployment (up to 25%),
whereas bordering areas have higher education levels (30–60%). Disease hotspots emerge
in Rome and centre-north municipalities, aligning with social deprivation patterns. Regres-
sion models confirm the link between disease incidence and socioeconomic indicators. SDI
ranges from − 1.31 to + 10.01. This study underscores a correlation between social depriva-
tion and disease incidence. Further national-level research is essential to deepen our under-
standing of how social deprivation influences health outcomes, with potential implications
for addressing health disparities both regionally and nationally
Community-based participatory research to engage disadvantaged communities: Levels of engagement reached and how to increase it. A systematic review
No full textCommunity-based participatory research (CBPR) is one of the most used community engagement frameworks to promote health changes in vulnerable populations. The more a community is engaged, the more a program can impact the social determinants of health. The present study aims to measure the level of engagement reached in randomized controlled trials (RCTs) using CBPR in disadvantaged populations, and to find out the CBPR components that better correlate with a higher level of engagement. A systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Embase, Web of Science, MEDLINE, Cochrane and Scopus databases were queried. Engagement level was assessed using the revised version of IAP2 spectrum, ranging from "inform" to "shared leadership" . Fifty-one RCTs were included, belonging to 36 engagement programs. Fourteen CBPR reached the highest level of engagement. According to the multivariate logistic regression, a pre-existing community intervention was associated with a higher engagement level (OR = 10.08; p<0.05).The variable "institutional funding" was perfectly correlated with a higher level of engagement. No correlation was found with income status or type of preventive programs. A history of collaboration seems to influence the effectiveness in involving communities burdened with social inequities, so starting new partnerships remains a public health priority to invest on. A strong potentiality of CBPR was described in engaging disadvantaged communities, addressing social determinants of health.The key findings described above should be taken into account when planning a community engagement intervention, to build up an effective collaborative field between researchers and population
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
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Cost-effectiveness analysis of Next generation sequencing tests in critically ill pediatric patients
Full text linkRare genetic diseases in the pediatric population constitute an urgent global public health issue; overall, more than 300 million people are affected worldwide. Next Generation Sequencing techniques, as Whole genome sequencing (WGS) and Whole exome sequencing (WES), have proven to be significantly supportive in diagnosing these complex conditions. The aim is to evaluate the cost-effectiveness of WGS versus WES in pediatric patients with suspected genetic disorders. A Bayesian Markov model was calibrated among this target population, comparing WGS to WES. Model parameters were retrieved from the scientific literature. Costs and benefits were discounted at a rate of 3%. A lifetime time horizon and the National Health Service perspective was chosen. The Eurozone threshold, ranging from €30,000 to €50,000, was adopted. Markov Chain Monte Carlo was used as the simulation method for Bayesian inference. Uncertainty was explored through a probabilistic sensitivity analysis (PSA) and a value of information analysis (VOI), illustrated through Cost-Effectiveness Acceptability Curve (CEAC) and Expected Value of Perfect Information (EVPI). Results were reported as Incremental Cost-Effectiveness Ratio (ICER), expressed as euros per additional diagnosis. The base case findings highlighted that WGS was cost-effective with an ICER of €31,973. The CEAC showed that for all thresholds over the ICER, WGS had the highest probability of being cost-effective. The EVPI per patient was estimated to be €6,535 on a threshold of €50,000/diagnosis. In addition to being cost-effective, WGS could allow early genetic diagnosis shortening the diagnostic odyssey. The use of WGS in the diagnostic workup has the potential to revolutionise personalised medicine and to play a significant role in achieving SDG 3 by providing personalised healthcare, identifying genetic risk factors for diseases, and informing public health policies for a target population that represents the human capital of the future
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