Table 2.

Study design principles for middle-distance running populations.

Example Research Question: “The effect of high intensity training interventions at or beyond VO2max on middle-distance race performance”
	Traditional approach	Issues with approach	Emerging approaches	Rationale
I. Participant description	“18 middle-distance runners,” height, weight, age, international ranking level, VO2max, middle-distance performance times	Does not provide enough information to distinguish what type of middle-distance athlete the participants since MSS is not assessed	MSS measured over 50 m used to complement the aerobic characterization of vVO2max. Elite Athletes presented across the middle distance continuum, n = 400–800, n = 800, and n = 800–1,500 and categorized using the SRR (MSS/vVO2max) (Sandford et al., 2019a) Performance times provided across multiple distances (400, 800, 1,500) Training volume, time in zones quantified to understand training history	Allows for sub-group characterization even in underpowered studies that can have closer application and relevance for coaches and support staff frontline or for future study hypothesis generation
II. Exercise prescription	%vVO2max (>VO2max) %HRmax (>VO2max) Event personal best running speeds (e.g., intervals at 800 or 1,500 m race pace)	Human locomotor performance (i.e., time to exhaustion) at intensities beyond vVO2max can be surprisingly “predicted” using only 2 locomotor entities: vVO2max and MSS (Bundle et al., 2003; Alexander, 2006; Bundle and Weyand, 2012) Therefore, without acknowledgment of the MSS differences, the intervention will have athletes working at different relative intensities of a given workload. For example, the lower the use of the ASR, the greater the exercise tolerance (Blondel et al., 2001; Buchheit et al., 2012; Buchheit and Laursen, 2013) and thus a big confounder often overlooked in these types of studies	% ASR (or exercise prescription decisions set relative to both %vVO2max and %MSS)	Accounts for mechanical differences between athletes and allows the same relative physiological stimulus to be applied (Buchheit and Laursen, 2013)
Ill. Analysis	(1) All runners grouped together for analysis (despite some studies having 800 m (1.5–2 min) to marathon (130–160 min) specialists. (2) Periodically a sub-group responders vs. non responders	Misrepresentation of athletes ability to “respond.” Should we expect all athletes to respond equally to the same stimulus despite having very different event specialty or diverse profile to approach the same event?	Analyze data as a single group, BUT also display individual and sub-group response and differences between subgroups	Further understanding the appropriateness of a stimulus for a given sub-group profile