Learning objectives
The primary outcome of this educational module is to provide knowledge, cultivate virtues and develop the necessary skills to actively implement the ethical, professional and legal standards that underpin research integrity. This module values critical thinking and fosters an open dialogue on the quality of research.
Upon completion of the module each student will be able to:
Distinguish “normal” clinical practice from good clinical practice in research.
Understand and apply the principles and norms set forth in the new “Costituzione Etica” for Orthoptists and Assistants in Ophthalmology published in June 2021.
Be aware of the principles and norms set forth in the Belmont Report, Declaration of Helsinki, Guideline for Good Clinical Practice, European Code of Conduct for Research Integrity (ECoC, 2023).
Correctly apply principles and norms to research activities.
Recognise conflicts of interest (financial, personal, intellectual, etc.) and how they can affect our evaluations, judgment, decisions and behaviour.
Recognise cases of research misconduct and detrimental research practices: identify the violated principles/norms and decide the “best” course of action.
Recognise virtues (e.g. intellectual honesty, responsibility for one’s actions, etc.) and virtuous conduct in research.
Cultivate virtues in practice by seeking the “golden mean” (Aristotle) in each specific context.
Identify the different types of “goodness” (Von Wright, 1963) in research and in the European Code of Conduct for Research Integrity (ECoC, 2023).
Recognise the importance of communication in the clinician-patient/investigator-patient relationship and of the application of the FREDA (Fairness-Respect-Equality-Dignity-Autonomy) principles in the context of patient care and clinical research practice.
Prerequisites
Course unit content
- Bases of statistics and computer science
The first part of the course will introduce the basics of statistical planning and experimental design.
Principles of probability and combinatorial analysis needed later in the course will be introduced, as well as the major probability distributions.
This includes the binomial distribution, the Poisson distribution, the Normal and standard Normal distribution.
The second part of the course will address the methods of descriptive statistics. It will be shown how to recognize the type of data and how to
summarize them in appropriate indicators. The student will learn how to calculate measures of location (mean,
median, mode), variability (variance, standard deviation), the coefficient
of variation (CV), quantiles and their use.
Overview of special charts (mosaic plot, box-percentile plot, parallelviolin
plot, etc).
In the final part of the course the general principles of statistical
inference will be introduced.
The student will face the concepts of sampling distribution, type I and II error, power of a statistical test and operating curve.
The following methods will then be explained:
parametric tests - Student's t test, ANOVA 1 and 2 classification criteria.
non-parametric tests: - Wilcoxon test, Mann-Whitney, Kruskal-Wallis,
Friedman test, median test, chi-square test, Fisher's exact test.
Elements of correlation and linear regression.
The course will conclude with an introduction to Machine Learning and related examples of application in the scientific field.
- Integrity of Research and Good Clinical Practice
It is essential to distinguish “normal” clinical practice from good clinical practice in research.
The Orthoptist/Assistant in Ophthalmology must be familiar with the principles and norms included in the new “Costituzione Etica”, which represents a professional ethical standard.
As regards research, in this module, two complementary approaches to Research Integrity will be developed:
1) The “principle-based” approach
2) The “virtue-based” approach
During the course we will perform a further exercise to stimulate reflection and discussion on Research Integrity. The starting point will be the question: “What is goodness?”.
The philosopher George Henrik von Wright thought that “goodness” could be divided into categories.
We will identify the different types of goodness in the context of research and in the content of the European Code of Conduct for Research Integrity (ECoC).
-Information processing systems
Short account of historical evolution from the first inventions in the 1600s to the present Introduction to computer science and the use of computers General concepts on the operating principles Functional analysis of the structure of a processor Hardware: CPU Memory I/O devices Binary system and Boolean operators Information (text, numbers, images, sounds) and its digital representation
Software
Basic software and operating systems
Application software
Notes on programs and algorithms
Full programme
Bibliography
• Costituzione Etica. Federazione nazionale Ordini dei Tecnici sanitari di radiologia medica, delle professioni sanitarie tecniche, della riabilitazione e della prevenzione. Edizione Giugno 2021.
• ALLEA (All European Academies). The European Code of Conduct for Research Integrity – Revised Edition 2023 (https://allea.org/code-of-conduct/)
• Buona Pratica nella Ricerca e nella Pubblicazione e Disseminazione dei Risultati. Linee Guida. Università degli Studi di Parma. 3 Agosto 2020.
(https://www.unipr.it/node/21810)
• The Virt2UE program. The Embassy of Good Science.
(https://www.embassy.science/wiki/Main_Page)
• Commissione per l’Etica della Ricerca e la Bioetica del CNR. Linee Guida per l’integrità nella ricerca. Revisione dell’11-4-2019.
(https://www.cnr.it/sites/default/files/public/media/doc_istituzionali/linee-guida-integrita-nella-ricerca-cnr-commissione_etica.pdf?v=1)
• Belmont Report; 1979.
(www.hhs.gov/ohrp/regulations-and-policy/belmont-report/index.html)
• WMA Declaration of Helsinki; 2013.
(www.wma.net/en/30publications/10policies/b3/index.html)
• ICH (International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use) Harmonised Guideline. Integrated Addendum to ICH E6(R1): Guideline for Good Clinical Practice E6(R2); November 9, 2016.
(https://database.ich.org/sites/default/files/E6_R2_Addendum.pdf)
• EQUATOR (Enhancing the Quality and Transparency of Health Research) Network.
(https://www.equator-network.org/)
• George Henrik von Wright. The Varieties of Goodness. 1963
(https://www.giffordlectures.org/lectures/varieties-goodness)
Teaching methods
The course will be conducted face-to-face, to allow and enhance the interaction between students, “facilitated” by the instructor, using materials and exercises developed within the VIRT²UE Program, a European Project on Research Integrity. Concrete examples of research integrity violations will be used to stimulate and develop dialogue and critical thinking: the students will identify the violated principles and norms establishing a strict connection between theory and practice.
In the event of an emergency the lessons will be held in synchronous streaming on the Teams platform.
The lessons will be supported by PowerPoint presentations that will be available to students on the Elly platform.
Assessment methods and criteria
In an oral examination the student must demonstrate that he/she has acquired the predefined learning outcomes of the course.
The student will be questioned on the content of the course to ascertain his/her knowledge and understanding.
The student’s ability to apply knowledge and understanding will be verified by evaluating his/her ability to apply principles, norms and strategies in good research practice and to concrete cases of research integrity violations.
Finally the student will demonstrate his/her ability to make judgements (make a decision) on the “best” course of action to follow in concrete cases of research integrity violations.
Other information
