1. Physical Activity in the Context of Major Social Challenges: Analysis of sedentary behavior as a public health problem; physical activity in
   active and healthy aging; equity in access to sport and physical activity.
2. Environmental Sustainability and Sport: The ecological footprint of sport and sporting events; strategies for promoting sustainable sports
   practices and facilities; the “One Health” concept applied to Physical Activity and Well-Being.
3. Public Policies and Strategic Framework: Critical analysis of national, European and international policies for the promotion of physical
   activity and sport (e.g., National Health Plan, EU Sport Strategy) and their alignment with the SDGs.
4. From Theory to Action – Designing Projects with Impact: Methodologies for the design of action-research and community intervention
   projects focused on measurable social impact and sustainability. Impact-oriented funding sources

1. Fundamentals of Ethics: principles (autonomy, beneficence, non-maleficence, justice). National Data Protection Law, Declaration of Helsinki, ALLEA Code.
2. Ethics Applied to Physical Activity: vulnerable populations (children, elderly, disabled, ill). Ethical issues in community studies, wearables, big data, competitive contexts.
3. Submission & Evaluation: structure, writing, criteria for ethics committee proposals. Monitoring, modification, post-approval communication.
4. Scientific Integrity & Data Governance: good practices in authorship, peer review, publication. Preventing misconduct (plagiarism, data fabrication). Data Management Plan (DMP) aligned with FAIR (Findable, Accessible, Interoperable, Reusable).

1. Epistemological Foundations: positivism, interpretivism, critical theory. Implications for research questions, researcher-participant relationship, and validation in Physical Activity;
2. Qualitative Strategies: case study, phenomenology, grounded theory, ethnography. Techniques: interview, participant observation, focus groups. Criteria: credibility, transferability.
3. Quantitative Strategies: experimental, quasi-experimental, cross-sectional, longitudinal designs. Variables, hypotheses, internal/external validity, and reliability.
4. Mixed Methods: foundations, designs (sequential explanatory, sequential exploratory, convergent). Challenges of integration and interpretation.
5. Instrument Design: construction of questionnaires/scales (content validity, construct validity). Interview guides, observation protocols. Pretests and pilot studies.
6. Research Protocol Writing: structure of a scientific proposal: introduction, questions, literature review, methodology, ethics, work plan.

This course has 8 scientific seminars, aligned with CIDESD’s research lines (ELITE and HEART groups). Themes:

1. Physical Activity, Health and Chronic Disease: mechanisms, interventions, policies (HEART).
2. Sport, Inclusion and Equity: gender, disability, minorities, access (ELITE).
3. Sedentary Behavior and Public Health: measurement, determinants, intervention (HEART).
4. Exercise/Sport Psychology and Motor Behavior: adherence, motivation, well-being (ELITE).
5. Active Aging: exercise prescription, quality of life, assistive technologies, AI (HEART).
6. Technology and Innovation: wearables, big data, AI, VR/AR (ELITE).
7. Public Policies: analysis, implementation, evaluation (HEART).
8. Sustainability and Sport Management: governance, environmental impact (ELITE).

HEART I – Fundamentals of Exercise in Health Promotion and Chronic Disease

1. Exercise Physiology Applied to Chronic Disease: Mechanisms of action of exercise on cardiac function, vascular health, muscle and bone
   metabolism, immunity and tumor biology.
2. Evidence-Based Exercise Prescription: Principles of prescription (FITT) for specific conditions (e.g., chronic kidney disease, post-heart
   attack, during and after cancer treatments, frailty). Safety monitoring.
3. Clinical and Economic Outcomes: Analysis of the impact of exercise on hard outcomes (mortality, hospital admissions) and soft
   outcomes (quality of life, function), and on the reduction of healthcare costs.
4. Methodological Approaches in Clinical Research: Study designs (RCTs, cohort studies, pilot studies) and methodological challenges in
   research with clinical populations.

ELITE I – Fundamentals of Sports Performance Sciences and Emerging Technologies

1. Theoretical Foundations of Elite Performance: Non-linear pedagogy and differential learning. Principles of complexity science and
   dynamical systems applied to sport.
2. Innovative Training Methodologies for Excellence: Approaches to developing creativity and decision-making in the game context. Models
   of periodization and adaptive load.
3. Technologies for Performance Analysis: Introduction to wearable sensors, computer vision systems and AI tools for capturing and
   analyzing individual and collective behaviors.
4. From Theory to Practice – Case Studies: Analysis of emblematic research from the ELITE group and other centers, focusing on the
   integration between theory, training methodology and technology.

1. Advanced Statistical Analysis: review of concepts. ANOVA for complex designs (repeated measures, factorial). Multiple linear and logistic regression. Introduction to SEM and path analysis. Power and effect size.
2. Advanced Qualitative Analysis: deductive vs. inductive coding. Advanced thematic analysis, categorical/conceptual content analysis. IPA. Validation: triangulation, peer review.
3. Mixed Data Integration: strategies to integrate quantitative and qualitative results (construction, validation, complementarity). Meta-inferences.
4. Software: R, SPSS, AMOS, Mplus for statistical analyses; NVivo, MAXQDA for qualitative data.
5. Results Communication: writing results and discussion sections. Tables, figures, narratives. From p-values to practical significance.

Tutorial and individualized course, with an initial theoretical-practical component to frame the doctoral project (objectives, requirements, structure, guidelines). Contents organized in stages:

1. Consolidation of the Individual Work Plan: refinement of the research problem, questions and plan with supervisors.
2. Literature Review: search, critical synthesis and organization of the theoretical framework.
3. Methodology Development: design, population, instruments, data collection and analysis plan.
4. Ethical, Feasibility and Dissemination Considerations: proposal for ethics committee, logistical planning and timeline.
5. Writing and Revision of the Final Document: incorporating feedback.
6. Preparation for Public Defense: oral presentation, anticipation of questions and argumentation training.

HEART II – Technologies and Personalization of Exercise Interventions for Health

1. Responsive Technologies for Home and Community-Based Exercise: Overview of wearables, ambient assisted living (AAL) sensors,
   mobile applications and telerehabilitation platforms. Usability and accessibility criteria.
2. Artificial Intelligence for Personalization: Introduction to recommender systems for exercise prescription, models for predicting adherence
   and adverse events, and reinforcement learning systems for program adaptation.
3. Data Integration and Augmented Clinical Decision-Making: Fusion of physiological (HR, activity), behavioral (adherence, self-report) and
   contextual (environment) data to create personalized profiles and generate actionable insights.
4. Implementation, Equity and Ethics: Challenges in implementing technologies in real-world contexts (digital literacy, cost). Equity in access
   to digital health solutions. Ethics in the use of sensitive data and in the automation of decisions

ELITE II – Advanced Modeling and Optimization of Sports Performance

1. Modeling and Optimization in Sport: Principles of mathematical and computational modeling. Introduction to the optimization of
   parameters and processes in training and competition.
2. Machine Learning Applied to Performance: Learning techniques (regression, classification, clustering, dimensionality reduction) applied
   to sports data.
3. Model Building and Validation: Model development pipeline (pre-processing, feature selection, training, validation). Evaluation metrics
   and interpretability.
4. Advanced Cases and Ethical Limitations: Analysis of case studies of predictive injury models, tactical optimization or talent identification.
   Discussion on bias, generalization and ethical implications of automation in sport

This curricular unit embodies the tutorial research component. Its “contents” are the stages of research execution, supervised by an advisor
and governed by the Study Cycle Regulations