Subject

Biostatistics 1

  • code 08587
  • course 3
  • term Semester 2
  • type OB
  • credits 4

Matter: Dessign tools and projects Physiotherapy Evidence based

Main language of instruction: Catalan

Other languages of instruction: Spanish

Timetable
 Sem.2  MO 10:00 15:00 
 Sem.2  WE 10:00 12:00 

Teaching staff

Head instructor

MsU Jordi OLLE - jolle@uic.es

Office hours

To speak with the professor personally, appointments should be made by e-mail to Montserrat Girabent, PhD (girabent@uic.es)

 

Introduction

 

The practice of the physiotherapist often implies "value" and as a result, we have data, both of the evaluations, and the characteristics of the individual. These are the factors we think are associated with the diagnosis we are looking for. Our interest is, therefore, to extract information from these records in order to use them and to find connections between the characteristics and what we are assessing. This way, we can look for more evidence and continually improve in our practice as physiotherapists. This is why knowing the bases of Biostatistics is a must in order to analyze clinical data, and to make a comprehensive report of scientific evidence about our profession.


Pre-course requirements

Not specified

Objectives

The main objective of this course is to provide the knowledge necessary to understand the statistics as a tool to be use in the field of health sciences; and specifically in physiotherapy.

 More specifically, it is intended that students are able to understand and apply the statistical concepts and methods, as well as to interpret and present the results from the use of this discipline. This will also allow them to address any scientific publication of their area of expertise using critical thinking, contributing to the promotion of professional practice based on scientific evidence.

 As a complementary objective, it is intended that students acquire basic skills that allow them to make efficient use of statistical software 

Competences / Learning outcomes of the degree programme

  • 09 - Demonstrate critical thinking skills.
  • 10 - Develop autonomous learning skills.
  • 14 - Demonstrate initiative and an entrepreneurial spirit.
  • 15 - Demonstrate a concern for quality.
  • 28.1 - Capacity for oral and written communication in the native language.
  • 28.2 - Demonstrate Interpersonal skills.
  • 37 - Knowledge of ethics, legal and professional issues in physiotherapy practice.
  • 44 - Knowledge of research and assessment methodology that integrates theory and research in the design and implementation of effective physiotherapy.
  • 45 - Knowledge of problem-solving and critical thinking theories.
  • 55 - Capacity to incorporate scientific research and an evidence-based practice within the professional culture.
  • 01 - The ability to analysis and synthesis.
  • 02 - The ability to organise and synthesize
  • 04 - To have computing skills within the field of study.
  • 05 - The ability to manage information.
  • 06 - To have comprehensive problem-solving skills.
  • 07 - Demonstrate decision-making skills.

Learning outcomes of the subject

After completing the course the student will be able to:

  •                                 Understand the basic concepts related to Evidence Based Physiotherapy.
  •                                 Understand and interpret the fundamental concepts of biostatistics related to physiotherapy. Complete in depth assignments using specific physiotherapeutic bibliographical sources.
  •                                 Having respectful behaviors and attitudes regarding the professional code of ethics.
  •                                 Use specific informatic tools.

Syllabus

Unit 1. Introductión. Definition of Statistics. Statistics in the Health Sciences.
Definition of:

a. Population, sample, representative sample, sample selection.

b. Random variables and measurement scales.

Unit 2. Descriptive statistics:

a. Frequency measures, contingency tables and epidemiological and diagnostic measures.

b. Graphic representation I

c. Measures of central tendency and dispersion

d. Position and dispersion rates.

e. Symmetry and form rates

f. Graphic representation II


Unit 3. Inferential statistics

a. Hypothesis test concept. Types of errors and statistical power. P-value concept. Concept of unilateral and bilateral test. Confidence intervals. Statistical significance and clinical relevance.

b. Confidence intervals and statistical tests for a sample

c. Parametric and nonparametric test for comparing two samples

d. Parametric and nonparametric test for comparison of more than two samples

e. Correlation and Linear Regression

Teaching and learning activities

In person

TRAINING ACTIVITYMETHODOLOGYCOMPETENCESECTS CREDITS
lectures
learning based upon problema-solving
oral presentation / master class
29 29.1 37 55 0.48
self-learning activities
apprenticeship contract
problem-solving exercises
01 02 05 06 07 10 14 15 29 29.1 0.2
practical
cooperative learning
case method
problem-solving exercises
01 02 05 06 07 10 14 15 29 29.1 55 0.32
student's independant work-study
02 10 14 15 29 29.1 2.40
theoretical and practical workshops
learning based upon problema-solving
case method
problem-solving exercises
02 10 14 15 28 28.1 28.2 29 29.1 30 30.1 37 55 0.4
tutorials
learning based upon problema-solving
cooperative learning
01 02 05 06 07 09 14 15 28 28.1 29 29.1 30.1 0.2

Evaluation systems and criteria

In person

Evaluation of the subject will be through the activities undertaken in practical classes. Attendance to 80% of classes is necessary to be evaluated. 

 

The grade of the practical part will mean 30% of the final grade. In addition, there will be a multiple-choice test at the end of the semester, if the student has achieved the proposed learning results, this exam will mean 70% of the final grade.

 

In order to pass the subject, students must obtain a minimum of 5 in each of the parts, otherwise the subject will be failed and they will be able to choose to do a resit.

 

The resit of the course consists of a final exam that will represent 100% of the final grade. This will have the same characteristics as the previous final exam

Bibliography and resources

 

  • Martínez-González M.A, Faulín Fajardo, F.J., Sánchez Villegas, A., Biostadística amigable, 2ª Ed. Madrid: Díaz de Santos, 2006. ISBN: 8479787910.
  • Cobo Valeri, E., Muñoz, P., & González, J. A. (2007). Bioestadística para no estadísticos: Principios para interpretar un estudio científico. Barcelona: Masson.
  • Martín A, Luna del Castillo, J.D., Bioestadística para las ciencias de la salud Madrid: Norma-Capitel Ediciones S.L., 2004
  • Dawson-Saunders E. Bioestadística médica. 4a ed. [México D.F.]: El Manual Moderno; 2005.
  • BOPAL, R. (2002). Concepts of Epidemiology - An integrated introduction to the ideas, theories, principles and methods of epidemiology.
  • SZKLO, M., NIETO, J. (2003). Epidemiologia intermedia: conceptos y aplicaciones. Madrid: Díez de Santos.
  • Forthofer,R., Eun Lee, E., Hernandez, M. Biostatistics - A Guide to Design, Analysis and Discovery. (2nd edition). Academic press February 2007
  • Dawson, B., Trapp, R.G. , Basic & Clinical Biostatistics, 4ed., Mcgraw-Hill/Interamericana, 2004
  • Wassesrteheil-Smoller, S. Biostatistics and Epidemiology - A Primer for Health and Biomedical Professionals. 3rd Edition, springer, 2004. ISBN 10: 0387402926
  • Rosner, B. Fundamentals Of Biostatistics, ED Hardcover, 2005 ISBN-10: 0534418201
  • Armitage P, Berry G. Estadística para la investigación biomédica. 3a ed. Madrid [etc.]: Harcourt Brace de España; 1997.
  • Sentís Vilalta J, Ascaso Terrén C, Vallés A, Canela i Soler J. Bioestadística Barcelona: Ediciones Científicas y Técnicas; 1992.

 

Evaluation period

E: exam date | R: revision date | 1: first session | 2: second session:

  • E1 22/05/2019 10:00h
  • E2 03/07/2019 10:00h I2
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