Unit NURSING BASED ON EFFICACY TRIALS

BIOENGINEERING AND MEDICAL INFORMATICS

Code	50696901
Location	FOLIGNO
CFU	1
Teachers	Daniela Fruttini
Hours	15 ore - Daniela Fruttini
Learning activities	Altro
Area	Altre attività quali l'informatica, attività seminariali ecc.
Academic discipline	INF/01
Type of study-unit	Obbligatorio (Required)

EPIDEMIOLOGY

Code	50696902
Location	FOLIGNO
CFU	2
Teacher	Annunziata Di Marco
Teachers	Annunziata Di Marco
Hours	30 ore - Annunziata Di Marco
Learning activities	Base
Area	Scienze propedeutiche
Academic discipline	MED/42
Type of study-unit	Obbligatorio (Required)

SCIENTIFIC EVIDENCES FOR NURSING

Code	50696801
Location	FOLIGNO
CFU	1
Teacher	Gianluigi Bellani
Teachers	Gianluigi Bellani
Hours	15 ore - Gianluigi Bellani
Learning activities	Caratterizzante
Area	Scienze infermieristiche
Academic discipline	MED/45
Type of study-unit	Obbligatorio (Required)
Language of instruction	Italian
Contents	The nurses in clinical practice is to employ the best scientific evidence for your patient and his profession. The task of the nurse is to know to acquire, read, interpret and use the scientific evidence, the research sources, literature and databases to provide the best and latest treatments.
Reference texts	Chiari P., Mosci D., Naldi E., L'infermieristica basata su prove di efficacia, guida operativa per l'evidence based nursing. McGraw Hill Editore, Milano, 2006, ISBN: 9788838616686 - Articles provided by the teacher
Educational objectives	The student, at the end of the course, will be able to: Search, read and analyze a scientific article.
Prerequisites	not provided
Teaching methods	face-to-face
Other information	Attendance: Compulsory. At least 75% of lessons Venue: Via Oberdan n.123 - Foligno Start and end dates of teaching activities as per calendar published on the Degree Course website See web site http://www.med.unipg.it/infermieristica/Foligno/
Learning verification modality	Oral exam with discussion on research article.
Extended program	Nursing Evidence-Based The Evidence Based Practice 1. The clinical care decision: the positivist paradigm and post-positivist paradigm. 2. Background. 3. Definition and characteristics. 4. Benefits, obstacles and limitations of evidence-based practice. EBN methodology 1. Convert the need for clinical question information. 2. Seek the best information: a) The stages of the literature search process; b) Multimedia sources in research. 3. Read and interpret the evidence. 4. The tools for evidence-based practice: a) Systematic reviews; b) Meta-analysis; c) Guidelines. Research Methodology 1. The relationship between theory and nursing research. 2. The phases of the research process.

HEALTH STATISTICS

Code	50696701
Location	FOLIGNO
CFU	1
Teacher	Donatella Siepi
Teachers	Donatella Siepi
Hours	15 ore - Donatella Siepi
Learning activities	Base
Area	Scienze propedeutiche
Academic discipline	MED/01
Type of study-unit	Obbligatorio (Required)
Language of instruction	Italian
Contents	General information on statistics and its use in medicine. Aims and methods of statistical analysis, statistical characteristics and classification. Descriptive Statistics: principli indices descriptive statistics, their use and their representation Epidemiology and Clinical Trials Probability. Inferential statistics. Evaluation of data usage and processing Correlation. Linear regression. Survival curves
Reference texts	Fowler J., Jarvis P., Chevannes M.: STATISTICA PER LE PROFESSIONI SANITARIE. Edizioni EdiSES.
Educational objectives	The main objective of the course is to provide students with adequate knowledge in order to understand the use of the elements of statistical research. At the end of the course the student will acquire the knowledge needed to understand the elements of descriptive and inferential statistics found in the scientific literature, organize, process, interpret and communicate scientific data appropriately summary information obtained.
Prerequisites	In order to understand and use the concepts described in the teaching it requires knowledge of basic elements of Mathematics, Computer and English.
Teaching methods	Frontal Lessons: Classroom lessons on all the topics of the module and practical exercises
Learning verification modality	The exam includes an oral exam consisting in a collegial discussion, with the presence of the teachers of the various modules, of 25-30 minutes aimed at ascertaining the level of knowledge and understanding reached by the student on the topics presented in class and listed in the program. The student must demonstrate the ability to know the epidemiological characteristics of various diseases, what is a literature search and what tools to use to effectively implement and finally the notions statistics to be able to read and understand a paper. The oral test will also verify the communication skills of the student, his command of the language, the ability to apply the acquired skills and develop solutions in independent judgment.
Extended program	General information on statistics and its use in medicine. Aims and methods of statistical analysis, statistical characteristics and classification. Decrittive Statistics : Measurements and sampling in health studies. Data analysis and presentation. Presentation of the results of tables. Main graphic representation (histograms, etc.). Absolute frequencies, relative, cumulative. Distribution of frequencies. Measures of central tendency. Measurement variability. Symmetric and asymmetric frequency curves. Epidemiology Measures of disease frequency: prevalence and frequency. Types of studies. Confounding. Clinical Trials: History, nature of clinical trials. Types of clinical trials. Ethical aspects. Probability. Definition and theories of probability. Event and event space. The measure of probability. Basic principles of probability. Bayes' theorem and applications. Specificity and Sensitivity. Positive predictive value, negative predictive values. Relative risk and odds-ratio. ROC-curves and their interpretation. Empirical law of the case. Theoretical probability distributions: Gaussian and Binomial and Poisson. Applications. Inferential statistics. Outline of the central limit theorem. Standard error. Significance levels. Confidence intervals. Standardized normal distribution and distribution of T-student. Hypothesis testing: the concept of hypothesis, error I ° species and II species. Power of the test. Tests based on a sample. Z-test for the mean. One-tailed test and two-tailed. Comparison between means for paired samples and independent samples. Parametric and non-parametric statistics. Analysis of variance. Test for multiple comparisons. ¿2 test: meaning, properties and applications. Correlation for the association between qualitative variables, the Pearson coefficient, Spearman coefficient. Linear regression. Tables and survival curves.