Identifying Data 2019/20
Subject (*) Research in Health Sciences II Code 653862236
Study programme
Mestrado Universitario en Asistencia e Investigación Sanitaria (plan 2012)
Descriptors Cycle Period Year Type Credits
Official Master's Degree 2nd four-month period
 First Obligatory 6
Language
Spanish
Teaching method Face-to-face
Prerequisites
Department Ciencias da Saúde
Matemáticas
Coordinador
Jacome Pumar, Maria Amalia
 E-mail
maria.amalia.jacome@udc.es
Lecturers
Jacome Pumar, Maria Amalia
Lopez de Ullibarri Galparsoro, Ignacio
Sobrido Prieto, María
 E-mail
maria.amalia.jacome@udc.es
ignacio.lopezdeullibarri@udc.es
maria.sobrido@udc.es
Web http://www.mastermais.udc.es/?page_id=197#Materia02
General description

Study programme competencies
Code Study programme competences
A1 Capacidade para elixir e aplicar as metodoloxías de investigación mais adecuadas á investigación proposta.
A2 Capacidade para o deseño experimental e o completo desenvolvemento de proxectos de investigación no ámbito sanitario, desde a formulación da hipótese de investigación ata a comunicación dos resultados.
A3 Adquirir un sentido ético da investigación sanitaria.
A4 Obter un substrato teórico suficiente para comprender o entorno clínico de aplicación das técnicas de investigación.
A5 Adquirir o coñecemento da realidade investigadora nun ámbito concreto das ciencias da saúde.
B1 Capacidade para aplicar o método científico na planificación e o desenvolvemento da investigación sanitaria.
B2 Fluidez e propiedade na comunicación científica oral e escrita.
B3 Compromiso pola calidade do desenvolvemento da actividade investigadora.
B4 Capacidade de análise e de síntese.
B5 Habilidade para manexar distintas fontes de información.
B6 Capacidade para traballar de forma colaborativa en equipos multi e interdisciplinar.
B7 Capacidade de establecer unha relación de empatía cos suxeitos implicados no desenvolvemento da actividade investigadora.
C1 Expresarse correctamente, tanto de forma oral coma escrita, nas linguas oficiais da comunidade autónoma.
C2 Dominar a expresión e a comprensión de forma oral e escrita dun idioma estranxeiro.
C3 Utilizar as ferramentas básicas das tecnoloxías da información e as comunicacións (TIC) necesarias para o exercicio da súa profesión e para a aprendizaxe ao longo da súa vida.
C4 Desenvolverse para o exercicio dunha cidadanía aberta, culta, crítica, comprometida, democrática e solidaria, capaz de analizar a realidade, diagnosticar problemas, formular e implantar solucións baseadas no coñecemento e orientadas ao ben común.
C5 Entender a importancia da cultura emprendedora e coñecer os medios ao alcance das persoas emprendedoras.
C6 Valorar criticamente o coñecemento, a tecnoloxía e a información dispoñible para resolver os problemas cos que deben enfrontarse.
C7 Asumir como profesional e cidadán a importancia da aprendizaxe ao longo da vida.
C8 Valorar a importancia que ten a investigación, a innovación e o desenvolvemento tecnolóxico no avance socioeconómico e cultural da sociedade.

Learning aims
Learning outcomes Study programme competences
Data analysis: Introduction to the advanced statistical tools required for multivariate analysis and modelling of relationships among variables. AR1
AR2
AR4
 BC1
BC4
 CC3
CC6
CC7
CC8
Evidence-based clinical practice AR1
AR3
AR4
 BC1
BC3
BC4
BC5
BC6
BC7
 CC1
CC2
CC3
CC7
To know the basic principles of meta-analysis. AR4
AR5
 BC2
BC4
BC5
 CC1
CC4
CC5
CC6

Contents
Topic Sub-topic
1. Association between two categorical variables Basic concepts.
Chi-squared and McNemar tests.
2. Simple linear regression Simple linear correlation
Fitting a simple linear regression
Measures of goodness of fit
Model diagnostics
3. Multiple linear regression Variables selection
Interaction
Multicollinearity
Comparison of models
4. Analysis of covariance Introduction
Fit of regression lines with different slopes
Fit of regression lines with equal slopes
5. Logistic regression Introduction
Examples
Goodness of fit
Model selection
6. Survival analysis Introduction to censored data
Survival function: Kaplan-Meier estimator
Comparison of survival functions: log-rank test
7.1. Evidence Based Practice Introduction.
Research implications.
Evidence levels
7.2. Reviews Narrative Reviews
Systematic Reviews
7.3. Systematic reviews: Guidelines for its preparation Introduction
Methodology
Results
Discussion and conclussions
Other elementes
8. Meta-analysis Overview.
Effect size.
Statistical models.
Quantification of heterogeneity.
Publication bias.
Meta-regression.

Planning
Methodologies / tests Competencies Ordinary class hours Student’s personal work hours Total hours
Document analysis A4 A5 B4 B5 C3 C6 20 50 70
Introductory activities B6 B7 C3 12 30 42
Seminar A1 4 12 16
Collaborative learning B6 B7 C4 C5 C7 C8 4 12 16
Supervised projects A1 A2 A3 A4 A5 B1 B2 B3 B4 B5 C1 C2 C6 2 4 6
 
Personalized attention 0 0 0
 
(*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students.

Methodologies
Methodologies Description
Document analysis Learning through online material: recorded keynote speeches, videos, presentations and complementary pdf files.
Introductory activities Online monitoring and personalized attention tools: forums and debates.
Seminar Face to face seminars where students will be able to solve questions and problems.
Collaborative learning Continuous evaluation through some of the following tools: exams, exercises, involvement with the virtual classroom, etc.
Supervised projects Final academic work where students must demonstrate their theoretical and methodological knowledge of the contents. Works will be requested in virtual format and computer support.

Personalized attention
Methodologies
Introductory activities
Supervised projects
Seminar
Description
Personalized attention is inherent in the methodologies used'

Assessment
Methodologies Competencies Description Qualification
Supervised projects A1 A2 A3 A4 A5 B1 B2 B3 B4 B5 C1 C2 C6 Final academic work where the students should show their theoretical and methodological knowledge of the contents. 50
Collaborative learning B6 B7 C4 C5 C7 C8 Exams, delivered exercises, involvement with the virtual classroom.
 50
 
Assessment comments

The subject is formed by 3 blocks: Block A, Data analysis (units 1-6), Block B, Systematic reviews (units 7.1-7.3), and Block C, Meta-analysis (unit 8). The weight of each block in the final mark is: Block A,
50%; Block B, 25%; and Block C, 25%.

If the student has not been assessed in any of the three blocks, the final mark will be "ABSENT".

The student will not pass the subject if the mark of any of the blocks is lower than 3 (in a 0-10 scale). Otherwise, the final mark of the subject will be the sum of the weighted marks of the corresponding blocks.

The three blocks are independent, that is, the mark of one block is not affected by the mark/s of the other block/s.

The assessment of each block is based on the delivery of exercises and/or essays. The instructions regarding the delivery of exercises and/or essays will be published on moodle.udc.es before the beginning of each block. Regarding supervised projects, following the "Normativa académica de evaluaciones, de calificaciones y reclamaciones" Article 14, plagiarism and the use of non-original material, including that obtained online, without implicit indication of the source and, if it is the case, the author, will result in a failing grade (numerical score 0) in the corresponding block. All of this without prejudice of the disciplinary responsibilities derived from the corresponding procedure.

Concerning repeating students, the different marks of previous academic years will not be kept.

Early opportunity:

The criteria are those considered in the Article 19 of the "Normas de avaliación, revisión e reclamación das
cualificacións dos estudos de grao e mestrado universitario".

D) Qualification with honors:

The students with a final score greater than 9 might be granted with a qualification with honors. The teachers might consider aditional criteria in the scores, based on any of the methodologies included in the teaching guide.

Sources of information
Basic

Topics 1-6

Topics7.1 -7.4

  • Casal Acción B, Ríos Neira M, Sobrido Prieto M. Guía de uso de CRD Databases. Plan de Calidad el Sistema Nacional de Salud del Ministerio de Sanidad y Política Social. Axencia de Avaliación de Tecnoloxías Sanitarias deGalicia; 2012. Guías de Recursos deInformación: nº 1. Disponible en: http://www.sergas.es/docs/Avalia-t/guia-uso-CRD.pdf
Complementary


Recommendations
Subjects that it is recommended to have taken before
Preparing a Research Project II: Development/653862202
Statistics Applied to Health Sciences/653862206
Clinical Research I/653862232

Subjects that are recommended to be taken simultaneously

Subjects that continue the syllabus

Other comments

Programa Green Campus FCS

Para axudar a conseguir un entorno inmediato sustentable e cumprir cos obxectivos estratéxicos 1 e 2 do "III Plan de Acción do Programa Green Campus FCS (2018-2020)", os traballos documentais que se realicen nesta materia:

a. Solicitaranse maioritariamente en formato virtual e soporte informático. 

b. De realizarse en papel: 

- Non se empregarán plásticos. 

- Realizaranse impresións a dobre cara. 

- Empregarase papel reciclado. 

- Evitarase a realización de borradores.

PLAxio

A detección de fraude, copia ou plaxio na redacción do traballo da materia implicará un suspenso na oportunidade de avaliación afectada (0,0) e a remisión directa á oportunidade seguinte.

Dita circunstancia comunicarase á Comisión Académica e ao resto de profesores do título. En caso de que se reitere a irregularidade nunha 2ª avaliación, a Comisión poderá solicitar ao Reitor a expulsión temporal ou definitiva do/a estudante do título cursado.


(*)The teaching guide is the document in which the URV publishes the information about all its courses. It is a public document and cannot be modified. Only in exceptional cases can it be revised by the competent agent or duly revised so that it is in line with current legislation.