Psychological stress in nurses assisting Amyotrophic Lateral Sclerosis patients: a statistical analysis based on Non-Parametric Combination test

We aimed to evaluate the psychological, emotional and relational burden of nurses who provide assistance to patients affected by Amyotrophic Lateral Sclerosis (ALS). A survey was conducted by administering a questionnaire, the “Health Professions Stress and Coping Scale”, which proposes some potentially stressful work situations. The questionnaire was administered to 105 nurses working in hospitals where there is a ward for patients suffering from ALS. We used the "Non-Parametric Combination Test", a multivariate methodology based on permutation solution, widely applicable in various research contexts. Firstly, we investigated the areas of stress; then, the attention was focused on the different coping strategies adopted by respondent nurses within each stress area. The analyses were stratified according to different confounding factors, in order to control their potential effect. The results show the presence of an average level of stress, regardless of gender and educational status. Furthermore, there are significant differences in stress levels in subjects classified according to the ward in which they operate and a positive correlation between higher stress levels and the number of service years was found. In the future this study could also be of interest to nurses working in wards with potentially stressful situations

analysis of the propensity to fruit consumption among young people through the cumulative proportional odds model

After in-depth studies, the World Health Organization (WHO), asserts and suggests that in order to improve human health and well-being it is necessary to eat 400 grams of fruit and vegetables on a daily basis, as well as to consume potatoes and other starchy tubers such as manioc. In Europe, recommendations vary from country to country. Generally, these suggestions are in line with those of the WHO. However, some countries recommend a greater amount: For example, Denmark suggests more than 600 grams each day. The main goal of the present work is to analyse the fruit-consumption behaviour among young people, particularly university students and to identify the target of young people who frequently consume fruit. The present survey, therefore, has the aim of establishing a scientific reference framework regarding the propensity to "fruit" consumption in the diet of the students attending the University of Messina. In order to identify the existence of possible variables that may influence the frequency of fruit consumption, it was deemed appropriate to estimate an adequate regression model. Since the response variable was one of ordinal type on 4 levels (0 = never; 1 = once or twice a week; 2 = 3-5 times a week; 3 = each day) the Cumulative Proportional Odds Model, an extension of the general linear model to ordinal categorical data, was used

egg consumption among young people a study through the application of the logistic regression model

The purpose of the present survey is to study and to investigate the proper eating style, focusing the attention on the propensity to "egg" consumption, in the diet of young people, with reference to the students attending the University of Messina. The data collection technique that was used consisted of the administration of a distributed anonymous ad hoc questionnaire by directly interviewing a sample of university students. In order to individualize the possible variables which may influence the frequency of egg consumption, a logistic regression model was used. It is a particular case of generalized linear model whose link function is the log it function. It is frequently applied when the dependent variable y is, dichotomous. The research results indicate that the only two statistically significant variables are the eating style and the reading of the product label. Moreover, the Hosmer and Leme show test for model's adequacy guaranteed that the estimates provided by the model are not significantly different from the observations

I modello lineari generalizzati per lo studio della dipendenza della bagnatura fogliare da variabili atmosferiche.

The duration of leaf wetness is a very significant parameter for the development of many fungal diseases in plants. In order to make agriculture more competitive, it's important knowledge resulting from good information on the use of models and by application of remote sensing of leaf wetness and other agro-meteorological variables. So it’s possible to reduce risk and uncertainty in decisions and increase profits. In this study we aim to estimate a statistical model formalizing the dependence of leaf wetness from atmospheric variables. In particular we have applied some specific regression models in three different agro-eteorological stations, located at different altitudes (Cesarò Vignazza, Pettineo and Patti) in Messina’s province. The examined agro-meteorological variables are: air temperature, barometric pressure, precipitation, relative humidity, solar radiation and wind speed at 2 meters. The first approach was the Poisson regression, applied to the count of minutes of leaf wetness; later, we estimated an ordinal logistic regression model for classes of leaf wetness duration; after dichotomization of the response variable, we estimated a binary logistic regression model. Finally, we perform a comparison of the results obtained by the estimated generalized linear models. In our analysis, temperature, wind speed, pressure and humidity significantly influence the leaf wetness. Although the three estimated regression models provided similar information, specific criteria suggest that the Poisson regression is the best model

Bonferroni-Holm and Permutation tests to compare medical data: methodological and applicative issues

BACKGROUND Statistical methodology is a powerful tool in the health research; however, there is wide accord that statistical methodologies are not usually used properly. In particular when multiple comparisons are needed, it is necessary to check the rate of false positive results and the potential inflation of type I errors. In this case, permutation testing methods are useful to check the simultaneous significance level and identify the most significant factors. METHODS In this paper an application of permutation tests, in the medical context of Inflammatory Bowel Diseases, is performed. The main goal is to assess the existence of significant differences between Crohn's Disease (CD) and Ulcerative Colitis (UC). The Sequentially Rejective Multiple Test (Bonferroni-Holm procedure) is used to find which of the partial tests are effectively significant and solve the problem of the multiplicity control. RESULTS Applying Non-Parametric Combination (NPC) Test for partial and combined tests we conclude that Crohn's Disease patients and Ulcerative Colitis patients differ between them for most examined variables. UC patients compared with the CD patients, have a higher diagnosis age, not show smoking status, proportion of patients treated with immunosuppressants or with biological drugs is lower than the CD patients, even if the duration of such therapies is longer. CD patients have a higher rate of re-hospitalization. Diabetes is more present in the sub-population of UC patients. Analyzing the Charlson score we can highlight that UC patients have a more severe clinical situation than CD patients. Finally, CD patients are more frequently subject to surgery compared to UC. Appling of the Bonferroni Holm procedure, which provided adjusted p-values, we note that only nine of the examined variables are statistically significant: Smoking habit, Immunosuppressive therapy, Surgery, Biological Drug, Diabetes, Adverse Events, Re-hospitalization, Gender and Duration of Immunosoppressive Therapy. Therefore, we can conclude that these are the specific variables that can discriminate effectively the Crohn’s Disease and Ulcerative Colitis groups. CONCLUSIONS We identified significant variables that discriminate the two groups, satisfying the multiplicity problem, in fact we can affirm that Smoking habit, Immunosuppressive therapy, Surgery, Biological Drug, Diabetes, Adverse Events, Hospitalization, Gender and Duration of Immunosoppressive Therapy are the effectively significant variables

Bonferroni-Holm and permutation tests to compare health data: methodological and applicative issues

Abstract Background Statistical methodology is a powerful tool in the health research; however, there is wide accord that statistical methodologies are not usually used properly. In particular when multiple comparisons are needed, it is necessary to check the rate of false positive results and the potential inflation of type I errors. In this case, permutation testing methods are useful to check the simultaneous significance level and identify the most significant factors. Methods In this paper an application of permutation tests, in the medical context of Inflammatory Bowel Diseases, is performed. The main goal is to assess the existence of significant differences between Crohn’s Disease (CD) and Ulcerative Colitis (UC). The Sequentially Rejective Multiple Test (Bonferroni-Holm procedure) is used to find which of the partial tests are effectively significant and solve the problem of the multiplicity control. Results Applying Non-Parametric Combination (NPC) Test for partial and combined tests we conclude that Crohn’s Disease patients and Ulcerative Colitis patients differ between them for most examined variables. UC patients compared with the CD patients, have a higher diagnosis age, not show smoking status, proportion of patients treated with immunosuppressants or with biological drugs is lower than the CD patients, even if the duration of such therapies is longer. CD patients have a higher rate of re-hospitalization. Diabetes is more present in the sub-population of UC patients. Analyzing the Charlson score we can highlight that UC patients have a more severe clinical situation than CD patients. Finally, CD patients are more frequently subject to surgery compared to UC. Appling of the Bonferroni Holm procedure, which provided adjusted p-values, we note that only nine of the examined variables are statistically significant: Smoking habit, Immunosuppressive therapy, Surgery, Biological Drug, Diabetes, Adverse Events, Re-hospitalization, Gender and Duration of Immunosoppressive Therapy. Therefore, we can conclude that these are the specific variables that can discriminate effectively the Crohn’s Disease and Ulcerative Colitis groups. Conclusions We identified significant variables that discriminate the two groups, satisfying the multiplicity problem, in fact we can affirm that Smoking habit, Immunosuppressive therapy, Surgery, Biological Drug, Diabetes, Adverse Events, Hospitalization, Gender and Duration of Immunosoppressive Therapy are the effectively significant variables

A Cumulative Proportional Odds Model to Analyze the Influence of Mass Media on Teenagers in Messina

The media are constantly evolving at a breakneck pace and mainly young people, with their flexibility of mind and their continuous curiosity, can better understand the characteristics and potential of such advances. The aim of this paper is to analyze the relationship between teenagers and media, in order to try to better understand the habits and to conduct analysis on social interactions with young people. In order to evaluate the influence of mass media in the life of the young people, the Statisticians of Messina University decided to perform a statistical survey to evaluate the influence of the media in the life of Messina’s teenagers. A questionnaire entitled "Perceptions of the influence exerted by mass media" was administered in some schools. From the methodological point of view, three statistical models were estimated in order to formalize the dependence of the mass media influence by the kind of TV programs, the time spent on TV viewing and computer use and the kind of most used social networks. Since the mass media influence is an ordinal variable expressed by four ordered categories (1 = nothing; 2 = low; 3 = average; 4 = high) we used the Cumulative Proportional Odds Model to formalize the dependence by the potential predictors

Risk Factors Regarding Dog Euthanasia and Causes of Death at a Veterinary Teaching Hospital in Italy: Preliminary Results

The decision to request and proceed with euthanasia in a dog is complex and predictors of such decisions are important. This study investigates the risk factors (demographic and clinical) associated with the main clinical causes and methods of death (euthanasia or unassisted death) in a population of dogs. By comparing euthanasia to unassisted deaths, the authors assess causes of death to evaluate their relative impacts on decision-making to choose euthanasia compared with an unassisted death. For this, goal data from electronic medical records of dogs who had died (unassisted death and euthanasia), obtained from an Italian referral veterinary teaching hospital from 2010 to 2020, were analyzed. The causes of death were categorized by pathophysiological process and the organ system. Univariate and multivariable logistic regression analyses were performed to identify the factors that significantly affect the probability of undergoing euthanasia and to individuate independent significant predictors of euthanasia and unassisted death, respectively. Death rate by euthanasia was 40.7% (125/307), by died unassisted 50.8% (156/307), whilst only 8.5% of dogs (26/307) died accidentally. The main causes of death for euthanasia were due to neoplastic (75.6%), degenerative (64.3%), and congenital (60%) diseases. Furthermore, the findings reveal that in deaths by euthanasia, the significant risk predictors were female gender, age, and neoplastic and degenerative processes; while in unassisted deaths, the significant risk predictors were male gender, age, and infection/inflammatory conditions. These preliminary outcomes highlight the information of this study which may be used to evaluate strategic interventions and health promotion strategies to be implemented, with consequent welfare gains for the canine population

Non-Motherhood between Obligation and Choice: Statistical Analysis Based on Permutation Tests of Spontaneous and Induced Abortion Rates in the Italian Context

(1) Background: This paper aims to examine two relevant phenomena in the context of public health: spontaneous abortion (SA) and induced abortion (IA). SA is one of the most common complications of pregnancies; IA is a conscious choice that is made by the mother/couple. (2) Methods: Permutation tests were applied to SA and IA standardized rates detected by ISTAT (2016–2020). The NPC test, chosen for its optimal properties, was applied to compare different Italian territorial divisions (stratifying for year and age classes of women) and analyze the trend of years by stochastic ordering. (3) Results: Only for SA, there are significant differences among the three territorial divisions: the South records higher SA standardized rates than the North and the Center; the rates of IA are similar. Relating to distinct women age classes, the SA standardized rates do not show significant differences among the three analyzed geographical areas; different results are highlighted for IA. Stochastic ordering shows that only the IA standardized rates are characterized by a significant monotonous decreasing trend over the years. (4) Conclusion: The SA phenomenon has shown a decreasing trend that could be justified by the progress of science. For IA, we can certainly say that the general decrease in the phenomenon is due to the greater use of contraceptive methods that help to prevent unwanted pregnancies