Proposed

Variability in domain-based exercise-intensity prescription: a structured expert judgement study

When researchers receive the same detailed physiological information, do they prescribe the same exercise intensity?

Plain-language summary

Testing agreement before assuming consensus

Researchers can use several physiological anchors and analytical methods to define exercise-intensity domains. The proposed study asks what happens when independent researchers make a prescription from exactly the same evidence.

Participants would receive one richly characterised synthetic physiological dataset. They would independently prescribe standardised moderate-, heavy-, and severe-intensity cycling sessions. The session structures would be fixed so that the main decision is the selected work rate and the method used to derive it.

The study would compare prescribed work rates and record the selected physiological anchors, threshold or critical-power methods, confidence, and brief methodological rationale. This would help distinguish agreement, disagreement, and genuine methodological pluralism.

Standardised task

Three intended intensity domains

Participants would not alter the session structure. Their task would be to specify the target work rate or rates and explain the basis for the prescription.

Moderate

50 minutes

Continuous, constant-power cycling

Heavy

30 minutes

Continuous, constant-power cycling

Severe

4 × 4 minutes

Work intervals with 3 minutes of active recovery

What the study would examine

Variation in decisions and their methodological basis

The proposal emphasises estimation and description. It does not presume that researchers have already been shown to disagree.

Prescribed work rates

Quantify between-participant variation for each intended intensity domain.

Selected anchors and methods

Record the physiological information and analytical approach used for each prescription.

Reasons for agreement or disagreement

Examine rationales including validity, reliability, practicality, familiarity, and other methodological considerations.

Dataset and study boundaries

Synthetic data, no physiological testing

The proposed dataset represents a comprehensively assessed trained cyclist and includes incremental, constant-work-rate, and all-out test information. It is synthetic, was designed to be physiologically plausible, and does not derive from or correspond to a real person.

Participants would contribute professional judgements through an online task. The proposed study would not conduct physiological testing of a real participant and would not collect participant health data.

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Relevant methodological expertise?

Early-career researchers can describe how their skills and interests may support this or another developing Consortium project.

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