Unit RESEARCH METHODOLOGY

Course
Midwifery
Study-unit Code
A000964
Curriculum
In all curricula
Teacher
Francesco Santini
CFU
7
Course Regulation
Coorte 2021
Offered
2021/22
Type of study-unit
Obbligatorio (Required)
Type of learning activities
Attività formativa integrata

GENERAL AND APPLIED HYGIENE

Code GP003132
CFU 2
Teacher Chiara De Waure
Teachers
  • Chiara De Waure
Hours
  • 30 ore - Chiara De Waure
Learning activities Base
Area Scienze propedeutiche
Academic discipline MED/42
Type of study-unit Obbligatorio (Required)
Language of instruction Italian
Contents Definition of health and public health, definition and classification of
health determinants and preventive interventions. The role of
epidemiology in public health. Epidemiology and prevention of
communicable and non communicable diseases. Health systems and
organization.
Reference texts Ricciardi W et al. [Editor]. Igiene per le lauree triennali e magistrali.
Idelson Gnocchi 2019
Educational objectives The aim of the course is to provide students with the knowledge and skills
to analyse population health and needs and to properly use preventive
interventions.
Prerequisites Knowledge of secondary school mathematics and biology
Teaching methods Lectures
Learning verification modality Written test
Extended program Definition of health and public health, definition and classification of
health determinants. Natural history of disease. Prevention: definition,
aims, levels (primary, secondary and tertiary) and methods. The role of
the epidemiology in the health planning: epidemiological measures and
approaches to the study of health. Epidemiology and prevention of
communicable diseases: direct (disinfection, sterilization, notification,
contingency measures, diagnostic assessment, vaccines) and indirect
methods. Epidemiology and prevention of non-communicable diseases:
health education and promotion and screening. History and
development of the Italian national health service. Organization of the
Italian health system.

COMPUTER SCIENCE

Code GP003880
CFU 2
Teacher Francesco Santini
Teachers
  • Francesco Santini
Hours
  • 30 ore - Francesco Santini
Learning activities Caratterizzante
Area Scienze interdisciplinari
Academic discipline INF/01
Type of study-unit Obbligatorio (Required)
Language of instruction Italian
Contents HTML and CSS programming, visualization of content through a Webpage.
Databases and search engines in Life Sciences and Biomedical topics (PubMed).
Introduction to Word.
Introduction to Powerpoint.
Introduction to Excel. R language.
Reference texts Handouts.
Educational objectives Students will learn how the basics of computer programming in HTML/CSS and R languages. Moreover, they will be introduced to Word, Powerpoint and Excel, and how to search for information in PubMed.
Prerequisites No specific requirement.
Teaching methods Frontal lessons with slides and laboratory exercises.
Other information Website: www.unistudium.unipg.it

For the exam schedule, see:
www.informatica.unipg.it
Learning verification modality The exam project consists in choosing a scientific article through PubMed, and present it with a Website, a report in Word, a presentation in Powerpoint, and finally to represent data with an Excel sheet. Moreover, it will be required prepare a short R script to analyse the Excel data. The assignment will be prepared in group and individually discussed during the oral exam.

For information on support services for students with disabilities and / or DSA visit the page http://www.unipg.it/disabilita-e-dsa
Extended program HTML.
CSS language.
Life Sciences and Biomedical databases (PubMed, etc.).
Search for information in PubMed.
Introduction to Word and how to prepare a scientific report.
Introduction to Powerpoint and hot to prepare a presentation.
Introduction to Excel and statistical functions.
Introduction to R language.

MIDWIFERY, NURSING GYNAECOLOGICAL SCIENCES

Code 50518804
CFU 2
Teacher Eleonora Brillo
Teachers
  • Eleonora Brillo
Hours
  • 30 ore - Eleonora Brillo
Learning activities Caratterizzante
Area Scienze ostetriche
Academic discipline MED/47
Type of study-unit Obbligatorio (Required)
Language of instruction Italian
Contents The course introduces students to the main issues in evidence based medicine (EBM), literature research and review, databases (Cochrane Library and Medline/PubMed), methodology for drawing up protocols and final reports of systematic reviews, key features of meta-analyses and forest plots, research designs of primary studies, reading and assessment of scientific texts, methodology for writing protocols for clinical trials.
Reference texts -Fain JA. La ricerca infermieristica. Leggerla, comprenderla e applicarla. Milano: Mc Graw-Hill; 2004.
-Polit DF, Beck CT. Fondamenti di Ricerca infermieristica. Milano: Mc Graw-Hill; 2014.
-Vellone E, Piredda M. La ricerca bibliografica; strumenti e metodi per trovare e utilizzare la letteratura sanitaria. Milano: Mc Graw-Hill; 2009.
-Jefferson T. Come leggere uno studio controllato randomizzato. 2nd ed. Roma: Il Pensiero Scientifico Editore; 2012.
-Guidelines for Obstetrics and Gynecology.
-Selected scientific papers.
Educational objectives By the end of the course students should be able to:
-describe evidences meaning and importance for clinical decision-making;
-analyze critically and employ some support tools for decision making (procedures, protocols, guidelines, consensus conferences documents);
-formulate foreground questions using a structured framework (e.g. PICO);
-carry out a searching strategy to find information on a topic in different search engines (MedLine/PubMed and Cochrane Library);
-distinguish a systematic review from other types of reviews;
-describe the importance of systematic reviews/meta-analyses for clinical decision-making;
-describe the components of a search protocol for a systematic review;
-interpret a forest plot;
-describe the main distinctive features of different study types (in primary research);
-assess methodological quality of some study types (in primary research);
-plan a simple design of primary research, identifying the main elements and steps.
Teaching methods The course consists of 30 hours of class teaching during which a combination of lectures, discussions, small group works, in-class and computer-based exercises, and computer demonstrations.
Learning verification modality The examination includes an optional written exam (test) and a compulsory oral exam.
The test, which covers module I, lasts 12 minutes and consists of ten multiple-choice questions, each with four answers and only one correct. Correct answers gain one point, blank answers score zero points, and incorrect answers lose one-quarter point. The lowest passing grade is seven. No grades are assigned (only approved/not approved). If a student chooses not to take the exam or he does not pass the test, the final oral exam cover all three modules. If student pass the test, the oral exam cover modules II and III.
Students are required to register in advance for the final oral exam through SOL Servizi On Line according to the general rules of the University of Perugia.
The grades for the final exam are measured in thirtieths (0-30 scale), the minimum grade is 18/30 and the maximum grade is 30/30. The maximum grade can be enhanced with "cum laude" (30 cum laude).
Extended program MODULE I - EVIDENCE BASED MEDICINE (EBM)
-Concept of effectiveness, efficiency, appropriateness;
-Traditional medicine paradigm;
-Birth history, development, meaning and paradigm of EBM;
-Evidence Based Public Health (EBPH);
-Clinical Governance;
-Evidence Based Health Care (EBHC);
-Evidence Based Practice (EBP);
-Evidence Based Midwifery:
-History of Evidence Based Midwifery:
-Healthcare professional EBP core-curriculum;
-Process clinical decision making: a comparison of models;
-Responsibilities of the midwife in the clinical decision-making;
-Methods and tools to support process clinical decision making: procedures, protocols, guidelines, consensus conferences documents;
-Guidelines: features and quality;
-Guidelines International Network (GIN);
-National Guidelines System (SNLG);
-Systems for grading the quality of evidence and the strength of recommendations.
MODULE II - SCIENTIFIC LITERATURE, LITERATURE RESEARCH AND REVIEW, DATABASES
-Introduction and approach to scientific literature;
-White and grey/gray literature;
-Scientific literature search methodology;
-Literature review: scanning and searching methods;
-Literature searching techniques;
-Clinical queries;
-Background questions;
-Foreground questions;
-PICO/PECO and EPICOT models;
-Concept of population, sample and outcome;
-Primary and secondary sources, primary and secondary databases;
-Cochrane Collaboration;
-Cochrane Library database;
-Medline database;
-MeSH thesaurus;
-The use of PubMed (basic search; searching for a phrase, searching by a specific field; searching by author and journal title; combining searches using History; combining search terms with Boolean operators; using filters and limits);
-Traditional and systematic reviews;
-Methodology for drawing up protocols of systematic reviews;
-Methodology for writing a final report of a systematic review;
-Meta-analyses and forest plot.
MODULE III - PRIMARY RESEARCH: TYPES OF STUDY DESIGN
-Introduction to quantitative and qualitative research methods;
-Analytic and non-analytic studies;
-Non-analytic (or descriptive) studies: case reports, case-series, qualitative and surveys (cross-sectional) studies;
-Analytic observational studies: case-control and nested case-control studies, cohort studies and analytic cross-sectional studies;
-Ethical issues in observational studies;
-Experimental studies (randomized controlled trials);
-Non-experimental designs;
-Quasi-esperimental designs;
-Experimental designs;
-Ethical issues in experimental studies;
-Type of biases;
-Reading, interpretation, understanding and assessment of scientific texts;
-Methodology to develop projects of scientific research.

MEDICAL STATISTICS

Code 50A00030
CFU 1
Teacher Fabrizio Stracci
Teachers
  • Fabrizio Stracci
Hours
  • 37.5 ore - Fabrizio Stracci
Learning activities Base
Area Scienze propedeutiche
Academic discipline MED/01
Type of study-unit Obbligatorio (Required)
Language of instruction Italian
Contents The basis of scientific investigation
The role of statistic methods in biomedical research
Descriptive statistics
Inferential statistics
Regression models to analyze relationships between variables
Reference texts Primer of biostatistics by Stanton A. Glantz

or

Principles of Biostatistics by Marcello Pagano, Kimberlee Gauvreau

or

Statistical Methods in Medical Research di Peter Armitage, Geoffrey Berry, J. N. S. Matthews
Educational objectives Basic data analysis
Understanding of the role of statistics in medicine
Critical reading of methods and results in published biomedical research
Prerequisites none
Teaching methods Lesson
Practical exercises
Other information -
Learning verification modality Oral test
Extended program 1. Introduction
1.1 Statistics definitions and scope
1.2 Statistical methods in medical research

2. Data
2.1 Types of variables
2.2 Tabulation and processing of data
2.3 Diagrams
2.4 Descriptive statistics
2.5 Measures of central tendency
2.6 Measures of variability

3. Probability
3.1 Frequentist definition of probability
3.2 Probability distributions
3.3 The normal or Gaussian distribution
3.4 Probability distributions and applications

4. Populations and samples
4.1 Parameters and their estimation
4.2 Sampling

5. Statistical inference
5.1 Point and interval estimation
5.2 Confidence interval for the sample mean
5.3 Significance testing
5.4 Parametric Hypothesis Tests: Student’s t test and Analysis of Variance
5.5 Confidence interval for the difference between two means
5.6 Non-Parametric Hypothesis Tests: chi-squared test
5.7 rank test
6. Regression and correlation
6.1 Regression models
6.2 Linear regression
6.2.1 Linear regression equation: parameters estimation using the ordinary least squares method
6.2.2 Tests of significance in regression
6.2.3 Confidence interval for the linear regression coefficient b
6.3 Correlation
6.4 Critical reading of results from multivariable regression models
6.5 Multivariable modeling, an introduction (regrression models, goodness of fit, model selection, missing data)
Condividi su