Nursing - Course W - ASL LATINA FORMIA - GAETA

Activity type

Scienze propedeutiche

SSD

MED/01

Year

N/D

Semester

N/D

CFU

2

Hours distribution

24 classroom hours

Lecturers

ANDREA VERRILLO

Activity type

Scienze interdisciplinari

SSD

INF/01

Year

N/D

Semester

N/D

CFU

1

Hours distribution

12 classroom hours

Lecturers

ANDREA VERRILLO

Activity type

Scienze propedeutiche

SSD

MED/42

Year

N/D

Semester

N/D

CFU

3

Hours distribution

36 classroom hours

Lecturers

BENIAMINO CAPUTO

At the end of the course, the student:

Understands the fundamentals of general computer science, including the basic structure and functioning of hardware and software, with specific reference to the healthcare context. Is familiar with the main digital productivity tools (e.g., Word, Excel, PowerPoint, Google Workspace) and their application in clinical and administrative practice. Knows the fundamental concepts of descriptive and inferential statistics and their relevance in the analysis of healthcare data. Understands the principles of epidemiology and evidence-based medicine (EBM). Is aware of biomedical scientific information sources, the main study designs, and the metrics used to evaluate the effectiveness of healthcare interventions. Has learned to critically appraise scientific studies based on their methodology and to effectively search for scientific evidence through bibliographic search engines (e.g., PubMed), using appropriate strategies (e.g., PICOM, Boolean operators). Has acquired the ability to select and critically apply the most appropriate methodological tools to address clinical and healthcare questions.

To attend this course, the student is required to have:

· Preliminary notions of mathematics, particularly basic concepts of arithmetic and algebra.

· Fundamentals of biology and healthcare terminology, useful for understanding epidemiological and clinical content.

· Ability to read and comprehend scientific texts in the Italian language.

· Interest and motivation in using digital tools and quantitative methods for the analysis and management of information in the healthcare field.

Module: STATISTICS
POPULATION, SAMPLING AND MEASUREMENT
Population and sample
Types of sampling
Data and variables
Frequency distributions
Contingency tables

GRAPHIC REPRESENTATIONS AND DATA ANALYSIS
Data presentation: graphs
Central trend indices
Variability measures

PROBABILITY AND RANDOM VARIABLES
Basic notions of probability calculation
Random variables and probability curves
Normal and normal standardized distribution
Elements of statistical inference
Confidence intervals

MEANING TESTS
General notions on significance tests
Parametric and nonparametric tests (tests for both dependent and non-dependent samples
employees (paired data)
Chi-square test

CORRELATION MEASURES
The concept of correlation
The correlation coefficient for Spearman ranks



Module: COMPUTER SCIENCE
Computer architecture and application software
Von Neumann scheme
Components of a computer (processing, memory, input and output devices, storage)
Computer networks (classification, transmission media)
Client / server systems
Internet network
Software
Hardware-Software interaction
Operating systems
Computer language
Application software
Basic MS Windows Commands (Computer Power On / Off, Account Management, Privileges)
Main components of MS Windows (Desktop, Files and Folders, pop-up menus, system windows)
File and folder management (cut-copy-paste, multiple object selection)
Licenses for use and computer piracy

Email
Notes on the @email service
Folders for email management
Composing a message
Certified mail

Individual productivity software: word processors and spreadsheet
Word processors
Basic commands for creating, saving and writing a document
Display and printing commands
Formatting the document
Style management
Character and paragraph management
Footnotes
Index
Spreadsheet
Basic concepts of a spreadsheet
Selection of cells
Cell formatting
Data entry within the cells
Use of functions
The filters



Module: EPIDEMIOLOGY
INTRODUCTION TO THE STUDY OF EPIDEMIOLOGY AND HISTORICAL OVERVIEW: Epidemiology and Human Diseases in the Last 100 Years. DEFINITION OF EPIDEMIOLOGY AND BASIC CONCEPTS: Differences between epidemiology and clinical medicine, The concept of primary and secondary "determinants" and that of "population." SPECIFIC TASKS AND PRACTICAL PURPOSES OF EPIDEMIOLOGY: Prevention, control, and eradication of diseases, Hypothesis evaluation, Overview of observational and experimental studies. FROM ASSOCIATION TO CAUSALITY: The logical process toward causality: Association and causality, Event association in epidemiology, Statistical significance and causality, Comparing two proportions or percentages: the Chi-square test, Comparing two means: Student's t-test, Tests of significance, Association and causality: types of association; General model of causal and non-causal associations; Examples of non-causal associations; Examples of confusion between cause and effect. MEASURES OF DISEASE FREQUENCY: Morbidity and mortality; Mortality rates; Survival and fatality; Prevalence and incidence: definitions; Prevalence, incidence, and the use of confidence intervals; Attack rate; Relationship between incidence and prevalence; Epidemic, endemic, sporadic disease; Other parameters of disease frequency; Standardization of measures.
2) EVIDENCE-BASED PREVENTIVE MEDICINE: Evidence-based Medicine, some methodological elements, the concept of evidence and evidence-based clinical practice, from the traditional paradigm to the evidence-based paradigm, history of the evidence-based movement, limits of evidence-based clinical practice, obstacles encountered in attempting high-quality scientific interventions, Pyramid of evidence and gold standard, Types of research. SEARCHING FOR EVIDENCE: Evidence-based nursing, Phases of EBN, Research question and its formulation, background and foreground questions, The PICO method, examples of narrative and reformulated questions with PICO, Searching the scientific literature online and search engines, research tools and Boolean operators, General information on using PubMed for bibliographic research, online search exercises.
3-4-5) RESEARCH AND EVALUATION OF TREATMENT STUDIES, Randomized Controlled Trial (RCT) Primary, secondary, and tertiary sources of biomedical information, research study designs, characteristics of primary studies, randomized and controlled studies, data organization in the 2x2 table, ethical considerations, non-controlled studies, Measures of associations: Relative and absolute risk, risk difference, interpreting relative risk and risk difference, validity of association measures: p-value and confidence intervals, properties of CIs, systematic error or bias, selection bias or improper randomization, ascertainment bias, protocol violation bias, critical appraisal of experimental studies (randomized controlled trials), examples of study results and calculation of association measures, online calculators (e.g., open epi).
6) RESEARCH AND EVALUATION OF ETIOLOGICAL AND PROGNOSTIC STUDIES. Observational Studies vs Experimental Studies (Prospective, Retrospective, Cross-sectional, or Prevalence), types of questions (prognostic vs etiological study), design of epidemiological studies.
7) COHORT STUDY: methodology, measuring associations, biases in cohort studies, information and selection biases, confounding factors, advantages and disadvantages of cohort studies.
8) CASE-CONTROL STUDIES methodology, measures of association: odds ratio, interpretation of OR, confidence intervals for OR, information errors (information bias), memory errors (recall bias), selection bias, confounding factors.
9) CROSS-SECTIONAL STUDIES, sampling, measure of association (prevalence ratio, odds ratio), biases in cross-sectional studies, evaluation sheet for etiological studies.
10) SCREENING TESTS AND DIAGNOSTIC TESTS: Evaluation of test performance, Gold standard, Predictive values of a test, Sensitivity and specificity: impact of the cut-off value, Relationship between predictive values and prevalence, ROC curve, Multiple tests: Validity of a test and agreement between tests, critical evaluation.
11) SYSTEMATIC REVIEWS traditional and systematic reviews, characteristics and methods of systematic reviews, question formulation, study search, study selection, research implementation, critical evaluation, data collection, study synthesis. META-ANALYSIS heterogeneity. Major databases of systematic reviews, critical evaluation of systematic reviews.
12) SUMMARY AND EXAM SIMULATIONS.

Module: STATISTICS
For the achievement of maximum profit in relation to the course topics, it is sufficient to study the material provided by the teacher consisting of the presentations used in the lectures, in-depth documents and practical exercises to be carried out independently and representative of the topics discussed.


Module: COMPUTER SCIENCE
For the achievement of maximum profit in relation to the course topics, it is sufficient to study the material provided by the teacher consisting of the presentations used in the lectures, in-depth documents and practical exercises to be carried out independently and representative of the topics discussed. However, for those wishing to further investigate the topics covered, I report below the texts from which the topics were taken, also used in similar courses in other universities:

Excel & statistica medica. Guida pratica per le professioni sanitarie. Villani Simona; Borrelli Paola

Fluency. Conoscere e usare l'informatica Lawrence Snyder Traduttore: S. Gaburri



Module: EPIDEMIOLOGY
EVIDENCE BASED CLINICAL PRACTICE 2/ED
2ed La pratica clinico-assistenziale basata su prove di efficacia
8838636737 · 9788838636738
di Paolo Chiari, Daniela Mosci, Enrico Naldi

Module: STATISTICS
The topics covered have been fully edited by the teacher and concern basic topics that are easily comparable to the most common bibliographies of Statistics and Probability Calculation.


Module: COMPUTER SCIENCE
The topics covered include basic notions for which it is not necessary for the teacher to refer to reference bibliographies


Module: EPIDEMIOLOGY
N/D

Traditional classroom teaching will take place at the premises designated by the University, unless otherwise communicated by the University.

The modules include:
- a 12-hour Computer Science course, divided into three 4-hour lessons. The lessons will include presentations of the planned topics, along with student interaction and practical exercises.
- a 24-hour Statistics course, divided into six 4-hour lessons. The lessons will include presentations of the planned topics, along with student interaction and practical exercises.
- a 24-hour Epidemiology course, divided into six 4-hour lessons. The lessons will include presentations of the planned topics, along with student interaction and practical exercises.

In order to be admitted to the final exam, a minimum attendance of 66% of the total hours in IT lessons is required.

The exam is passed by achieving a passing grade on the three tests, each covering the three course modules. Each test consists of open-ended and/or practical questions and multiple-choice questions.

- Specify and describe the types of data transmission networks based on the equipment used (transmission media), describing their characteristics and differences in terms of advantages/disadvantages (costs, data transmission speed).

- Contingency tables: To estimate the percentage of smokers in the Italian adult population, a sample of 16 women and 14 men was interviewed, obtaining the following responses:
Men 1 0 1 0 0 1 1 1 0 0 1 0 1 0
Women 0 0 0 1 1 0 1 1 1 1 0 1 0 1 0
where
1 = smoker and
0 = non-smoker
a) Derive a double distribution table
b) Determine the percentage of smokers among the respondents
c) Determine the percentage of male smokers among the respondents
d) What percentage of men smoke?
e) What percentage of women do not smoke among the respondents?

- The advantages of a cohort study are:
preservation of the temporal relationship between exposure and disease onset;
relatively low costs;
the ability to study very rare diseases;
cohort studies offer no advantage over other types of studies;
short implementation times.

Module: STATISTICS

• 2 university training credit, lessons from March to May 2026

• 1 university training credit, lessons from March to May 2026