Explore innovative methodologies in medical research applied to sport and expand your opportunities in the healthcare and sports sectors”

Sports Medical Research plays a crucial role in the evolution of training practices, injury prevention, and performance optimization.  In an environment where physical demands and competitiveness reach ever-higher levels, having knowledge based on scientific evidence is essential. Biomedical analysis, exercise physiology, and the application of advanced technologies have enabled the development of more effective strategies for athlete health and performance, consolidating the importance of this field within sports sciences.

This program offers a unique opportunity to acquire specialized skills in an area with growing demand in the sports sector. Delving into the evaluation of physiological parameters, applied biomechanics, and sports nutrition can boost your professional career and extend your impact in the field.  The combination of scientific knowledge and technological tools provides competitive advantages in both research and clinical and sports interventions, facilitating access to new job opportunities in high-performance centers, academic institutions, and professional teams.

Thanks to its 100% online methodology, this program adapts to the current needs of the sector, allowing access to cutting-edge content without geographical or scheduling restrictions.  The flexibility of this model facilitates balancing work and personal life, ensuring effective learning through multimedia resources, practical cases, and guidance from specialists in the field. Moreover, the use of interactive technologies and state-of-the-art virtual environments enhances the academic experience, offering a dynamic and innovative approach.

TECH has designed this qualification with a comprehensive and updated approach, responding to the demands of the sports market and applied medical research.

Master the analysis of biomedical data with advanced technological tools and optimize athlete performance and recovery”

This Master's Degree in Sports Medical Research contains the most complete and up-to-date university program on the market. Its most notable features are:

• The development of practical case studies presented by experts in Sport Medicine
• The graphic, schematic, and practical contents with which they are created, provide scientific and practical information on the disciplines that are essential for professional practice
• Practical exercises where the self-assessment process can be carried out to improve learning
• Special emphasis on innovative methodologies in Sports Medicine
• Theoretical lessons, questions to the expert, debate forums on controversial topics, and individual reflection assignments
• Content that is accessible from any fixed or portable device with an internet connection

Access cutting-edge technological tools to assess, prevent, and improve physical performance at different levels of competition”

The faculty includes professionals from the field of Sports Medicine, who bring their practical experience to this program, as well as renowned specialists from leading societies and prestigious universities.

The multimedia content, developed with the latest educational technology, will provide the professional with situated and contextual learning, i.e., a simulated environment that will provide an immersive learning experience designed to prepare for real-life situations.

This program is designed around Problem-Based Learning, whereby the student must try to solve the different professional practice situations that arise throughout the program. For this purpose, the professional will be assisted by an innovative interactive video system created by renowned and experienced experts.

Drive innovation in sports medicine through evidence-based strategies and contribute to the development of new therapies"

Connect with international experts in health research and expand your network within health and sports institutions"

Sport and Medicine have evolved together, giving rise to a discipline where research is key to developing innovative strategies in health and performance. From genetic analysis to applied artificial intelligence, new scientific approaches allow for a better understanding of the body's response to exertion and the design of more effective interventions.
 
As technology redefines the limits of human performance, the need for specialists in this field becomes indispensable. In this context, TECH Global University drives an academic program that combines scientific rigor and advanced technological tools, preparing professionals to face the challenges of the future of Sports Medicine.

Lead high-impact projects in health centers, biomedical laboratories, and sports institutions with a science-based approach”

Module 1. The Scientific Method Applied to Health Research. Bibliographic Positioning of Research

1.1. Definition of the Question or Problem to be Solved
1.2. Bibliographic Positioning of the Question or Problem to be Solved

1.2.1. Information Search

1.2.1.1. Strategies and Keywords
1.2.2.2    Pubmed and Other Repositories of Scientific Articles

1.3. Treatment of Bibliographic Sources
1.4. Treatment of Documentary Sources
1.5. Advanced Bibliography Search
1.6. Generation of Reference Databases for Multiple Use
1.7. Bibliography Management Tools
1.8. Extraction of Metadata in Bibliographic Searches
1.9. Definition of the Scientific Methodology to be Followed

1.9.1. Selection of the Necessary Tools
1.9.2. Design of Positive and Negative Controls in Research

1.10. Translational Projects and Clinical Trials: Similarities and Differences

Module 2. Generation of Work Groups: Collaborative Research

2.1. Definition of Work Groups
2.2. Formation of Multidisciplinary Teams
2.3. Optimal Distribution of Responsibilities
2.4. Leadership
2.5. Control of Activity Achievement
2.6. Hospital Research Teams
2.6.1. Clinical Research
2.6.2. Basic Research
2.6.3. Translational Research

2.7. Creation of Collaborative Networks for Health Research
2.8. New Spaces for Health Research
2.8.1. Thematic Networks

2.9. Biomedical Research Centers in Network
2.10. Biobanks of Samples: International Collaborative Research

Module 3. Generation of Research Projects

3.1. General Structure of a Project
3.2. Presentation of Background and Preliminary Data
3.3. Definition of the Hypothesis
3.4. Definition of General and Specific Objectives
3.5. Definition of the Type of Sample, Number and Variables to be Measured
3.6. Establishment of the Scientific Methodology
3.7. Exclusion/Inclusion Criteria in Projects with Human Samples
3.8. Establishment of the Specific Team: Balance and Expertise
3.9. Expectations: An Important Element Often Overlooked
3.10. Generation of the Budget: Fine-Tuning Between Needs and the Realities of the Call for Proposals

Module 4. Clinical Trials in Health Research

4.1. Types of Clinical Trials (CT)

4.1.1. Clinical Trials Promoted by the Pharmaceutical Industry
4.1.2. Independent Clinical Trials
4.1.3. Drug Replacement Trials

4.2. Phases of Clinical Trials
4.3. Key Figures Involved in Clinical Trials
4.4. Generation of Protocols

4.4.1. Randomization and Blinding
4.4.2. Non-Inferiority Studies

4.5. Patient Information Sheet
4.6. Good Clinical Practice Criteria
4.7. Funding for Clinical Trials

4.7.1. Public Funding. Key European, Latin American and U.S. Agencies.
4.7.2. Private Funding. Major Pharmaceutical Companies

Module 5. Project Funding

5.1. Searching for Funding Opportunities
5.2. How to Adjust a Project to the Format of a Call for Proposals?

5.2.1. Keys to Achieving Success
5.2.2. Positioning, Preparation, and Writing

5.3. Public Calls for Proposals. Key European and American Agencies
5.4. Specific European Calls for Proposals

5.4.1. Horizon 2020 Projects
5.4.2. Human Resources Mobility
5.4.3. Madame Curie Program

5.5. Intercontinental Collaboration Calls, Opportunities for International Interaction
5.6. Collaborative Calls for Proposals with the United States
5.7. Strategy for Participation in International Projects

5.7.1. How to Define a Strategy for Participation in International Consortia
5.7.2. Support and Assistance Structures

5.8. International Scientific Lobbies

5.8.1. Access and Networking

5.9. Private Calls for Proposals

5.9.1. Foundations and Organizations Funding Health Research in Europe and America
5.9.2. Private Funding Calls from U.S. Organizations

5.10. Securing a Funding Source: Keys to Sustaining Long-Term Financial Support

Module 6. Statistics and R in Health Research

6.1. Biostatistics

6.1.1. Introduction to The Scientific Method
6.1.2. Population and Sample. Sampling Measures of Centralization
6.1.3. Discrete and Continuous Distributions
6.1.4. General Scheme of Statistical Inference. Inference about a Normal Population Mean. Inference about a General Population Mean
6.1.5. Introduction to Non-Parametric Inference

6.2. Introduction to R

6.2.1. Basic Features of the Program
6.2.2. Main Types of Objects
6.2.3. Simple Examples of Simulation and Statistical Inference
6.2.4. Graphics
6.2.5. Introduction to Programming in R

6.3. Regression Methods with R

6.3.1. Regression Models
6.3.2. Variable Selection
6.3.3. Model Diagnosis
6.3.4. Handling Outliers
6.3.5. Regression Analysis

6.4. Multivariate Analysis with R

6.4.1. Description of Multivariate Data
6.4.2. Multivariate Distributions
6.4.3. Dimensionality Reduction
6.4.4. Unsupervised Classification: Cluster Analysis
6.4.5. Supervised Classification: Discriminant Analysis

6.5. Regression Methods for Research with R

6.5.1. Generalized Linear Models (GLM): Poisson Regression and Negative Binomial Regression
6.5.2. Generalized Linear Models (GLM): Logistic and Binomial Regressions
6.5.3. Zero-Inflated Poisson and Negative Binomial Regression
6.5.4. Local Adjustments and Generalized Additive Models (GAM)
6.5.5. Generalized Linear Mixed Models (GLMM) and Generalized Additive Mixed Models (GAMM)

6.6. Applied Statistics in Biomedical Research with R I

6.6.1. Basic Concepts in R: Variables, Objects, and Data Management. Files. Graphics
6.6.2. Descriptive Statistics and Probability Functions
6.6.3. Programming and Functions in R
6.6.4. Analysis of Contingency Tables
6.6.5. Basic Inference with Continuous Variables

6.7. Applied Statistics in Biomedical Research with R II

6.7.1. Analysis of Variance
6.7.2. Correlation Analysis
6.7.3. Simple Linear Regression
6.7.4. Multiple Linear Regression
6.7.5. Logistic Regression

6.8. Applied Statistics in Biomedical Research with R III

6.8.1. Confounding Variables and Interactions
6.8.2. Building a Logistic Regression Model
6.8.3. Survival Analysis
6.8.4. Cox Regression
6.8.5. Predictive Models. ROC Curve Analysis

6.9. Statistical Techniques for Data Mining with R I

6.9.1. Introduction. Data Mining. Supervised and Unsupervised Learning. Predictive Models. Classification and Regression
6.9.2. Descriptive Analysis. Data Pre-Processing
6.9.3. Principal Component Analysis (PCA)
6.9.4. Principal Component Analysis (PCA)
6.9.5. Cluster Analysis. Hierarchical Methods. K-Means

6.10. Statistical Techniques for Data Mining with R II

6.10.1. Model Evaluation Metrics. Predictive Capacity. ROC Curves
6.10.2. Model Evaluation Techniques. Cross-Validation. Bootstrap Sampling
6.10.3. Tree-Based Methods (CART)
6.10.4. Support Vector Machines (SVM)
6.10.5. Random Forest (RF) and Neural Networks (NN)

Module 7. Graphical Representations of Data in Health Research and Other Advanced Analyses

7.1. Types of Graphs
7.2. Survival Analysis
7.3. ROC Curves
7.4. Multivariate Analysis (Types of Multiple Regression)
7.5. Binary Regression Models
7.6. Analysis of Big Data
7.7. Methods for Dimensionality Reduction
7.8. Comparison of Methods: PCA, PPCA and KPCA
7.9. T-SNE (T-Distributed Stochastic Neighbor Embedding)
7.10. UMAP (Uniform Manifold Approximation and Projection)

Module 8. Dissemination of Results I: Reports, Theses, and Scientific Articles

8.1. Generation of a Scientific Report or Thesis for a Project

8.1.1. Optimal Approach to the Discussion
8.1.2. Presentation of Limitations

8.2. Generation of a Scientific Article: How to Write a Paper from the Data Collected?

8.2.1. General Structure
8.2.2. Where Should the Paper Be Submitted?

8.3. Where to Start?

8.3.1. Appropriate Representation of Results

8.4. The Introduction: The Mistake of Starting with this Section.
8.5. The Discussion: The Pivotal Moment
8.6. The Description of Materials and Methods: Ensuring Reproducibility
8.7. Choosing the Journal to Submit the Paper

8.7.1. Selection Strategy
8.7.2. Priority List

8.8. Adapting the Manuscript to Different Formats
8.9. The Cover Letter: A Concise Presentation of the Study to the Editor
8.10. How to Respond to Reviewers' Questions? The Rebuttal Letter

Module 9. Dissemination of Results II: Symposia, Conferences, and Outreach to Society

9.1. Presenting Results at Conferences and Symposia

9.1.1. How to Create a Poster?
9.1.2. Representation of Data
9.1.3. Focusing the Message

9.2. Short Presentations

9.2.1. Data Representation for Short Presentations
9.2.2. Focusing the Message

9.3. Plenary Lectures: Tips for Keeping the Specialized Audience’s Attention for More Than 20 Minutes
9.4. Outreach to the General Public

9.4.1. Need vs. Opportunity
9.4.2. Use of References

9.5. Use of Social Media for Dissemination of Results
9.6. How to Adapt Scientific Data to Popular Language?
9.7. Tips for Summarizing a Scientific Paper in a Few Characters

9.7.1. Instant Dissemination via Twitter

9.8. How to Turn a Scientific Paper into Outreach Material

9.8.1. Podcast
9.8.2. YouTube Videos
9.8.3. TikTok
9.8.4. Comics

9.9. Popular Science Literature

9.9.1. Columns
9.9.2. Books

Module 10. Protection and Transfer of Results

10.1. Protection of Results: General Aspects
10.2. Valuation of Research Project Results
10.3. Patents: Pros and Cons
10.4. Other Forms of Protection of Results
10.5. Transfer of Results to Clinical Practice
10.6. Transfer of Results to Industry
10.7. Technology Transfer Agreements
10.8. Industrial Secrets
10.9. Generation of Spin-Off Companies from a Research Project
10.10. Searching for Investment Opportunities in Spin-Off Companies

Study in a 100% online format with access to updated content and no restrictions on schedule or geographic location”