Applying Sport and Exercise Research Week 1
Background and rationale
Session length and aim: Sessions are designed to be around 20–30 minutes, focusing on foundational aspects of research. The primary aim is to thoroughly cover the background and rationale for your chosen topic, delve into methodological considerations, explore various study designs, and understand how these elements collectively inform the specific focus of the module.
Focus areas for the presentation:
Background and rationale for the topic area: This involves establishing the current state of knowledge, identifying research gaps, and clearly articulating the clinical or practical significance of your study.
Study design considerations: Discussion on appropriate designs (e.g., experimental, quasi-experimental, observational) with justification based on the research question and practical constraints.
Methods: This section encompasses detailed aspects such as sample size determination (including power analysis), precise descriptions of procedures and intervention protocols, and the chosen statistical analysis plan. While the primary focus is quantitative, qualitative aspects are acknowledged for their complementary role.
Data handling and ethics: Critical considerations include secure data storage, principles of open access and data sharing, and comprehensive participant considerations (e.g., informed consent, anonymity, right to withdraw).
Timelines and personal development: A structured timeline of the entire project, alongside a reflective self-assessment of current research skills and a week-by-week plan for skill development and task completion.
Dissemination and implementation: Strategies for effectively communicating findings to relevant stakeholders, ensuring findings reach practice, and defining methods for monitoring their uptake and impact in real-world settings.
Emphasis on rigor:
Rigour means that data are visible and data-management is transparent, allowing for replicability and scrutiny. This includes detailed record-keeping and justification of all research decisions.
Consider potential barriers to successful completion early in the project lifecycle. Proactive identification allows for the development of mitigation strategies to prevent delays or failures.
Real-world relevance:
Much sports science research aims to directly influence coaching and practice. Therefore, robust dissemination and well-planned implementation strategies are crucial to determine whether research findings are actually adopted and used by practitioners, thereby maximizing practical impact.
Ethico-practical context:
Ethics submissions are a critical step and can be time-consuming, typically taking around 3 weeks for approval in this context. Planning this schedule in advance is vital to reduce bottlenecks that could delay data collection.
Principles of open data and secure data storage must be considered and integrated from the very outset of the project to avoid retrospective ethical issues and to ensure compliance with data governance policies.
Reading and engagement with literature:
A common observation is that many students read relatively few new articles per month (e.g., 0-4). While some report higher numbers (5-15+), the key point is not merely the accumulation of articles but the critical connection of reading with its implementation and practical application. Deep engagement, rather than superficial consumption, is encouraged.
Reflection prompt: When was the last time you read a study whose findings you actually implemented or directly applied in some way? If not, why do you think this was the case? This prompt encourages critical thinking about the utility of research.
Framing the background:
Provide a clear, detailed, and evidence-based background of the specific area you are studying. This should set the stage for your research question.
Do not assume prior knowledge on the part of your audience or supervisor. Explicitly explain the aims and objectives of your study, articulate the specific problem you are attempting to solve, and highlight its relevance and potential impact on practice or theory.
Presentation structure to guide discussion:
Background of topic area: Establish context, novelty, significance, and methodological rigor.
Sample size, procedures, and statistical analysis: Present the planned quantitative methodology, while acknowledging any qualitative considerations for completeness.
Ethics and data management: Detail protocols for data storage, access controls, and adherence to open science principles.
Timeline, personal research skills, and ethics submission planning: Outline project milestones and personal development, emphasizing the strategic timing of ethics applications.
Dissemination and implementation: Explain how findings will be communicated to reach practice and how their uptake will be monitored.
End with a question-and-answer session with your supervisor: This is a crucial opportunity to surface any overlooked issues, such as specific randomization strategies, participant recruitment challenges, or alternative analytical approaches.
What you will cover under Methods and design
Sample size
Document precisely how many participants you need, providing a clear justification (e.g., based on power analysis, previous literature, or practical constraints) and a detailed plan for how you will recruit them (e.g., inclusion/exclusion criteria, recruitment channels).
Sample size considerations are primarily framed from a quantitative standpoint, emphasizing statistical rigor and the ability to detect meaningful effects.
Procedures
Clearly describe what specific test(s) or measurements you will use (e.g., questionnaires, physiological assessments, performance tests), including any equipment, protocols, and standardized instructions.
Provide a clear, step-by-step description of procedures and data collection methods, ensuring enough detail for replicability. This may include details on blinding, order of tests, and familiarization sessions.
Statistical analysis
You will outline the planned statistical analyses (e.g., specific tests like ANOVA, regression, t-tests; what software will be used).
Expect to justify your choice of analysis beyond merely naming software. For instance, explain why a particular test is appropriate for your data type and research question. JASP is recommended as it's user-friendly, free, available online, and provides transparent statistical output, making it an excellent alternative to proprietary software like SPSS.
Software choices
A strong preference exists for JASP over SPSS, with a clear rationale provided: its ease of use, cost-effectiveness (being free and open-source), and broad accessibility significantly reduce barriers for students and researchers.
Qualitative vs quantitative balance
While acknowledging the importance of qualitative design and analysis for rich, in-depth understanding, this module emphasizes a quantitative focus. Any qualitative aspect is noted, typically for future complementary work or a broader understanding, but not as the primary methodological emphasis of this particular module.
Open data and storage
Specify the secure data storage location (e.g., university-approved cloud storage like OneDrive, institutional servers) and elaborate on data access controls to ensure confidentiality and integrity.
Outline open-access considerations, including potential data sharing policies, and detail how participant confidentiality will be maintained if data are to be made openly available (e.g., anonymization strategies).
Barriers to study completion
Proactively anticipate and discuss potential practical challenges, such as difficulties with participant recruitment (e.g., low turnout, specific populations), issues with participant compliance during interventions or data collection, and threats to data completeness (e.g., missing data, dropouts).
Ethical considerations in the methods
Clearly articulate what ethical approvals will cover. This includes detailed plans for participant recruitment (e.g., advertisements, initial contact), procedures for data handling (e.g., anonymization, security), the informed consent process (e.g., consent forms, debriefing), and any considerations for vulnerable populations.
Timeline and personal research skills
Timeline planning
You’ll present a detailed timeline slide that breaks down the project into manageable phases, with key milestones and deadlines.
The broader schedule often covers several weeks, for instance, dedicating weeks 9-10 specifically for considerations of dissemination and implementation, and week 11 for a dedicated personal research skills assessment and reflection.
Ethical submission window: This is a critical period, typically requiring about 3 weeks for review and approval. The timing of your ethics submission is paramount as it can significantly affect when you can commence data collection.
Dissertation hand-in date: The final dissertation is typically due in April of the following year. This means that data collection can potentially start earlier (e.g., February–March), especially if an expedited data collection window can be secured and planned for.
Week 13: This week often marks the data collection deadline within the module’s schedule; however, specific hand-in dates may be publicized differently depending on the overarching module and institutional academic calendar.
Personal research skills reflection (Week 11 activity)
Engage in self-assessment using online tools or structured prompts to identify both strengths and gaps in your current research skills portfolio.
Examples of essential skills include: efficient literature searching, effective keyword selection, critical synthesis of research, robust data management practices, proficient statistical analysis, and clear scientific communication.
Mock datasets
The practice of creating mock datasets is highly beneficial for planning analyses, allowing you to test statistical approaches and software before real data are collected. This helps refine your analytical strategy and identify potential issues.
A future module will specifically cover advanced techniques for using generative AI tools (e.g., ChatGPT) to create and manipulate realistic mock data for practice and simulation.
Presentation preparation activity
This involves an exercise where you pair up with a peer, taking on rotating roles as an 'examiner' and a 'researcher'. This structured practice helps in honing your ability to articulate and defend your project’s background, methods, and anticipate potential barriers.
In each pair, the examiner asks one comprehensive background question followed by two specific follow-up questions. Roles then rotate, providing exposure to both questioning and defending viewpoints.
Dissemination and implementation: why they matter
Dissemination
This refers to the strategic process of how to effectively get research information out to the target audience. This can involve a variety of channels, including academic journals, professional conferences, social media platforms, direct engagement with coaches and practitioners, and targeted workshops.
In sports science, there is a substantial body of literature specifically on how coaches and practitioners perceive research evidence and what characteristics they value most in research findings, highlighting the need for tailored communication.
Implementation
Beyond simply sharing findings, implementation focuses on how to monitor and systematically apply those findings in practice over an extended period. It addresses the practical integration and sustainment of research-informed strategies.
The key question for implementation is: does anyone actually use the findings once they have been published or disseminated, and if so, how effectively?
Practical implication
Even well-designed projects can exist perfectly in theory but ultimately fail to translate into tangible practice due to various real-world constraints. Therefore, it is imperative to design projects with a clear focus on practical implementation from the very beginning.
Real-world workflow example
If you are studying a sports intervention, a critical first step is to consider stakeholder buy-in (e.g., from coaches, athletes, club directors). You must also anticipate practical constraints (e.g., fitting interventions into existing training schedules, limited facility access) and identify potential barriers to the adoption of the intervention (e.g., resistance to change, lack of resources).
The practitioner vs. academic lens: understanding stakeholder perspectives
A common exercise compares practitioner and academic viewpoints on barriers
Examples of barriers frequently cited by practitioners: insufficient funding, lack of organizational buy-in from leadership, resistance from senior management, use of academic jargon that is inaccessible, perceived inferior knowledge in comparison to academics, negative prior experiences with research, severe time constraints, concerns about data-sharing privacy and security, and the perceived risks to competitive advantage.
Academics may view funding and publishability as primary motivators. In contrast, practitioners typically prioritize immediate applicability, practicality, and the direct benefits of research to their day-to-day work.
Key tensions
The use of overly academic jargon can alienate practitioners and hinder understanding. Therefore, clear, plain-language communication is absolutely crucial for effective engagement.
Gaining buy-in is essential not only for successful participant recruitment but also for sustained participation and the ultimate adoption of findings. It is highly beneficial to involve stakeholders early in the research process.
Prior experiences, both positive and negative, and the level of trust established significantly influence practitioners' willingness to participate in or adopt research. Building rapport and fostering strong relationships are foundational.
Differences in priorities (academics often seek novelty and theoretical contributions, while practitioners focus on immediate application) can create significant barriers to effective collaboration and knowledge translation.
The path to alignment
Horizon scanning: Systematically gather input anonymously (e.g., using collaborative online tools like Padlet or anonymous surveys) to identify the most pressing problems, challenges, and recurring themes that affect stakeholders.
Transform top-down ideas into bottom-up problems: This involves actively engaging stakeholders in the process of problem definition and prioritization, ensuring that research addresses their genuine needs and concerns.
Engage decision-makers (e.g., directors of sport, club managers) early in the process to secure their endorsement, ensure resource allocation, and facilitate the implementation of research findings.
Practical negotiation for projects
Frame research proposals in a way that clearly demonstrates how the findings will be used to improve existing practices and how stakeholders will directly benefit from the project’s outcomes.
Provide a clear, actionable implementation plan that outlines specific steps, realistic timelines, and strategies for addressing anticipated barriers to adoption.
A note on participatory approaches
Actively involving end-users (e.g., athletes, coaches, support staff) as collaborative partners throughout the research process can significantly improve the relevance, applicability, and ultimate uptake of research findings.
Simple, ongoing interactions, such as regular conversations and informal feedback loops, may often be more effective in fostering engagement and trust than infrequent, formal one-off presentations.
Example from practice (illustrative)
A project requiring buy-in from a sports club for an intervention or data collection initiative is more likely to succeed if senior leadership is engaged from the outset. Crucially, researchers should demonstrate how any testing or intervention can occur with minimal disruption to ongoing training schedules and competition calendars, emphasizing practical integration.
Clearly demonstrating practical relevance (e.g., through potential risk reduction, quantifiable performance gains, or injury prevention) helps to align the goals of researchers and practitioners, fostering a collaborative environment.
Models of research design in sport science
David Bishop’s Applied Research Model for Sports Science (ARMS) - 2008
Core sequence: The model outlines a logical flow: first, define the specific problem → then, formulate clear hypotheses and select appropriate measures → subsequently, conduct the study meticulously → and finally, implement the findings effectively.
Key emphasis: Crucially, implementation should be considered and planned very early in the research process. The model explicitly advises against conducting research that results in data you cannot practically apply or translate to the real world.
Practical note: While ARMS provides a robust overarching framework for research flow, it may not specify the exact, detailed design steps (e.g., specific experimental protocols). Therefore, close collaboration with coaches and other stakeholders is indispensable to accurately identify and address real-world problems.
Benefit: The model helps maintain practitioner buy-in in the field by directly linking day-to-day testing protocols and research activities to practical use and ongoing monitoring of interventions or performance.
Tension: A potential tension arises if implementation is only designed for later stages, which might lead to overlooking front-end feasibility issues. To counteract this, planning for iterative feedback loops throughout the project life cycle is recommended.
National/institutional performance research framework (as discussed in the session)
Concept: This framework posits that performance-oriented research demands careful and explicit consideration of how results will be applied and utilized in practice, extending beyond mere academic publication.
Quadrants to help frame research goals and application potential:
New knowledge + application: This represents the ideal situation, where research generates novel scientific findings that also possess high practical applicability and direct relevance.
New knowledge but limited application: This quadrant includes novel theoretical or fundamental findings that, while contributing to scientific understanding, are not immediately or easily translated to practical application in the field.
Application with existing knowledge: This refers to research that focuses on applying, validating, or optimizing existing scientific knowledge in practical settings, without necessarily contributing new theoretical insights.
Low novelty + low applicability: Research falling into this quadrant typically offers limited value for either advancing theoretical understanding or providing practical utility, and should generally be avoided.
Purpose: The framework’s purpose is to help researchers balance the pursuit of scientific novelty with the imperative of practical applicability. It also serves to proactively anticipate and address potential barriers to the uptake and utilization of research findings.
Practical takeaway from the models
Always begin your research project by clearly defining the problem within its real-world context and concurrently plan for the implementation of findings right from the outset.
Proactively build in stakeholder engagement strategies and detailed dissemination plans early in your project’s development.
Thoroughly consider horizon-scanning techniques and solicit multi-stakeholder inputs to effectively identify potential practical barriers and emerging opportunities for your research.
Barriers, ethics, and practical considerations in sport-science research
Common barriers to starting and completing projects
Time constraints: This frequently involves challenges in aligning data collection schedules with demanding training and competition calendars of athletes and teams.
Recruitment and participant compliance: Difficulties in attracting the required number of participants and ensuring their consistent adherence to study protocols.
Getting buy-in: Securing the active support and cooperation from key stakeholders, including coaches, athletes, and club management, is critical.
Jargon and communication gaps: The use of highly specialized academic terminology can create significant barriers to effective communication between researchers and practitioners.
Fear of losing competitive edge and data sensitivity: Concerns among teams or individuals about sharing sensitive performance data that could be exploited by competitors.
Funding and resource limitations: Insufficient financial resources, access to equipment, or personnel to conduct the research effectively.
Multidisciplinary coordination (MDT) challenges: Difficulties in effectively coordinating efforts and communication across various specialists, such as coaches, athletes, sport scientists, medical staff, and administrators.
Managing ethical considerations
Ethics submissions can take around 3 weeks to process; therefore, planning ahead is absolutely essential to avoid delays that could impact data collection commencement.
Expectations for undergraduate vs. Masters by Research (MRES) students differ significantly. MRES projects often require work of publishable quality and necessitate stricter adherence to ethical guidelines and detailed documentation.
Data handling: This involves ensuring robust privacy protocols, secure storage solutions (e.g., encrypted servers, password protection), and obtaining clear, unequivocal consent for specific data use and potential sharing, adhering to GDPR or similar regulations.
Timing of ethics approvals: This must be carefully considered in relation to your proposed data collection timeline and subsequent publication plans, as approval must be in place before any data are gathered.
Practical strategies to reduce barriers
Implement horizon scanning to systematically identify the top barriers and align proposed solutions with the genuine needs and preferences of stakeholders.
Engage with key decision-makers (e.g., directors of sport, head coaches) early in the process to secure crucial support, resources, and institutional endorsement.
Use plain, accessible language and tailor communications specifically to practitioners to significantly improve buy-in and understanding.
Plan for flexible research designs, such as mixed-methods or adaptive designs, that can accommodate the dynamic and often unpredictable realities of real-world settings.
Create a detailed stakeholder map, clearly defining roles, responsibilities, and communication channels to prevent misunderstandings and potential bottlenecks.
What to consider for dissemination and implementation in practice
How to present research findings in a highly actionable format that is directly useful for coaches and practitioners (e.g., infographics, brief reports, workshops).
How to develop robust mechanisms to monitor the uptake of interventions or new practices and adjust strategies as needed, ensuring sustained impact.
How to align your research outcomes and implementation plans with the broader strategic goals of the club or organization to maximize relevance, secure long-term support, and ensure sustainability.
Quick activities and recall prompts used in the module
Two-minute examiner/researcher probing exercise
This activity involves taking turns in the roles of an 'examiner' and a 'researcher' within a two-minute timeframe, fostering rapid critical thinking.
The examiner is tasked with asking one broad background question and two subsequent follow-up questions, designed to probe deeper.
The focus of these discussions is on the project's background, ethical considerations, anticipated barriers, chosen methods, and practical implications, deliberately saving detailed dissemination for a later, more focused discussion.
Participants rotate partners to practice articulating their project clearly, concisely, and with adaptability when faced with challenging questions, enhancing their presentation and defense skills.
Reflection on personal research skills (example prompts)
What are your current strengths within the research process? (e.g., adept literature searching, precise keyword selection, effective pattern recognition in existing literature, strong theoretical understanding).
What do you identify as your weaknesses or areas for development? (e.g., struggles with identifying appropriate search terms for systematic reviews; challenges in recruiting participants; difficulties with efficient data management; complex statistical analysis).
How can you strategically leverage your identified strengths to mitigate or overcome your weaknesses throughout the duration of the project?
Mock dataset planning
Consider the proactive creation of a mock dataset specifically to practice various analyses and to gain confidence in interpreting results well in advance of collecting real data. This preparatory step is invaluable for refining analytical strategies.
A future module will explicitly demonstrate how to effectively use advanced tools, such as chat-based AI assistants (e.g., ChatGPT), to generate and manipulate realistic mock data for comprehensive practice and simulation.
Practical implications and takeaways for exam preparation
Always define the problem and rationale clearly and comprehensively at the start of your project. Explicitly explain how your project's findings could realistically be implemented and utilized in practical settings.
Be explicit and highly detailed about your methods: specify the rationale behind your sample size, outline your precise recruitment approach, describe all procedures meticulously, and detail your planned statistical analyses (making sure to justify all choices thoroughly).
Plan for ethics approval very early in the project timeline. Understand the typical timeline and specific requirements for approvals, and critically assess how potential delays in this process could significantly affect your data collection schedule.
Develop a strong implementation mindset: constantly think about who will ultimately benefit from your research, what specific changes or adaptations will be needed for its adoption, and how you will effectively monitor its uptake and impact over time.
Utilize horizon-scanning techniques and engage actively with stakeholders to anticipate potential barriers and opportunities, allowing you to tailor your project design and communication strategies accordingly.
Clearly differentiate between dissemination (spreading the word) and implementation (putting it into practice). Develop a realistic and actionable plan for both aspects.
Practice communicating your project clearly and concisely to non-specialists. Actively avoid academic jargon and ensure that your background section effectively explains why your work matters and its broader significance.
When working in sports science, always remember and account for the significant practical constraints faced by athletes, teams, and clubs (e.g., demanding training schedules, tight competition calendars, and variable participant availability).
Keep in mind the essential integration of quantitative rigor with practical relevance. Be fully prepared to discuss and demonstrate how your research findings could be effectively translated into actionable practice within a real-world setting, bridging the gap between theory and application.
Final notes for the upcoming session
We will introduce stakeholder-focused content next week, expecting a detailed discussion on who stakeholders are, how to accurately identify them, and effective strategies for engaging them throughout the research process.
You will cover a small journal activity and receive a brief but comprehensive overview of key stakeholder considerations.
There will be a detailed follow-up session on various models of research design and how to practically apply them to your own specific project, effectively tying together theoretical frameworks and real-world practical application.