Sport research/Research design

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Think about and carefully plan your study to get the best results

Your research question will largely determine how you will go about conducting the research. The broad methodology you adopt to answer the question you have is often referred to your research design. Initially you need to determine if you want to answer a question relating to a single case (a case study) or if you want to know what happens in general (i.e. you study a sample which relates to a larger popultion). Most reported research in exercise and sport is in the form of a sample and that's what will be considered here.

The type of research you conduct can be grouped into

Hopkin's[1] refers to this as modes of enquiry. Descriptive and experimental research are the two most common types of research that we deal with.

As part of your research design, it will also be important to consider the validity and reliability of data that you are collecting. This may have implications on parts of your research design. Your research design will also determine what kind of data analysis you can do. You should know what data analysis you are going to do before you collect your data.

Descriptive research

Descriptive research occurs when data is collected in a natural setting (i.e. the researcher has not manipulated the environment in any way). The natural setting doesn't mean a green forest, it just means the researcher does not interfere. So videoing and coding a game of rugby, then going on and describing what happens would be referred to as a descriptive, or observational, study. Although the data description is factual, accurate and systematic, the research cannot describe what caused a situation. Thus, descriptive research cannot be used to create a causal relationship, where one variable affects another. Qualitative research often has the aim of description and researchers may follow-up with examinations of why the observations exist and what the implications of the findings are.

Descriptive, or observational research can be used to describe a single point in time, or changes over time (longitudinal - e.g. changes in strength over weeks, changes in blood glucose during a single exercise bout, the evolving role of a sports manager over the decades). Observational research also often incorporates correlations, where different observations are correlated against each other to see if they are associated.

Hopkin's[1] describes the types of observational study with a sample, weak to strong:

Experimental and Quasi experimental

In an experimental research design, you almost always gather information before and after an intervention (where you, the experimenter, do something to effect the natural world) and then look for changes. The ways in which interventions can be incorporated into a study have been described by Hopkin's[1], from weak to strong (in terms of study design):

You need up to 4x as many subjects as in a crossover.

In experimental research, it is also important to limit the bias associated with your measures. Bias[1] is less likely if…

In other words, you want treatment groups to be similar.
Single blind = subjects don't know which is which.
Double blind = the researchers administering the treatments and doing the measurements and analysis don't know either.

If you have a controlled trial, then here is a useful decision tree[2] for Controlled Trials

Meta analyses

A meta-analysis combines the results of several studies that address a set of related research hypotheses. In its simplest form, this is normally by identification of a common measure of effect size, for which a weighted average might be the output of a meta-analyses. Here the weighting might be related to sample sizes within the individual studies. More generally there are other differences between the studies that need to be allowed for, but the general aim of a meta-analysis is to more powerfully estimate the true "effect size" as opposed to a smaller "effect size" derived in a single study under a given single set of assumptions and conditions.

Meta-analyses are often, but not always, important components of a systematic review procedure. Here it is convenient to follow the terminology used by the Cochrane Collaboration, and use "meta-analysis" to refer to statistical methods of combining evidence, leaving other aspects of 'research synthesis' or 'evidence synthesis', such as combining information from qualitative studies, for the more general context of systematic reviews.

Hopkin's also has an introduction to meta-analysis[3] worth reading.

Things you (may) need to think about

Power and subject numbers

http://www.sportsci.org/resource/stats/relyappl.html#samplesize

Hopkins WG (2006) Estimating Sample Size for Magnitude-Based Inferences Sportscience 10, 63-70.

Online effect size calculator from University of Colorado academic.

Random allocation of subjects

Hopkins WG (2010) Assigning Subjects to Groups in a Controlled Trial. Sportscience 14, 7-12.

Activity

Activities are mini-tasks that will give you some practice with the concepts of each section. Activities should appear here soon, if not, feel free to add some open access ones yourself.

Task

  1. What type of research are you conducting?
  2. Explain why you have answered as you have to Q1.
  3. Could you do a different type of research on the same thing? What would you need to change?
  4. Explain how the type of research you are conducting limits you or allows you to make inferences about causality

Resources

In "research designs" Will Hopkin's provides a powerpoint overview of different research designs often used in sports research. This is an excellent resource.[4]

For quantitive research design, Hopkins has another useful resource[5] that will help you thinak about all apects of your research design.

See Also

Meta analysis on Wikipedia.
Experiment on Wikipedia.
Descriptive research on Wikipedia.

National Statistical Service website offers a series of chapters intending to provide an understanding of the issues involved in survey design. It provides the key issues to be considered when designing surveys and potential survey designs and covers the advantages and disadvantages of the various methods. The site can be accessed from http://www.nss.gov.au/nss/home.nsf/2c4c8bd01df32224ca257134001ea79a/e4e968fc83fb1217ca2571ab00247b3e?OpenDocument

References

  1. ↑ Hopkins WG (2002). What is research? [Slideshow]. Sportscience 6, http://sportsci.org/jour/0201/What_is_research.ppt page 12.
  2. ↑ Batterham AM and Hopkins WG (2005). A decision tree for controlled trials. Sportscience 9, 33-39. http://sportsci.org/jour/05/wghamb.htm
  3. ↑ Hopkins WG (2004). An Introduction to Meta-analysis Sportscience 8, 20-24. http://sportsci.org/jour/04/wghmeta.htm
  4. ↑ Hopkins WG (2008). Research Designs: Choosing and Fine-tuning a Design for Your Study. Sportscience 12, 12-21 (http://sportsci.org/2008/wghdesign.htm)
  5. ↑ Hopkins WG (2000) Quantitative Research Design. Sportscience 4(1) http://sportsci.org/jour/0001/wghdesign.html
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