A new perspective to aid in MMed research report completion: The effort-time trajectory model
DOI:
https://doi.org/10.7196/Keywords:
Master of Medicine (MMed), MMed research, Cognitive load theoryAbstract
Background. Since 2011, the Health Professions Council of South Africa has required all specialist trainees to complete a Master of Medicine (MMed) research report, a requirement intended to strengthen the production of relevant local research. However, evidence shows that this expectation substantially increases trainee workload, contributes to delays in specialist registration and may impede clinical skills development. SA studies report that registrars frequently lack the time and support needed to complete research tasks, with many exceeding the nominal training period. These challenges mirror international experiences where integrating research into busy clinical programmes remains difficult.
Objective. To introduce and describe the effort-time trajectory model as an innovative conceptual framework to support MMed trainees in planning and completing their research reports.
Methods. We describe the effort-time trajectory model, originally developed by Nel, which complements existing scheduling-based research support models by explicitly incorporating anticipated cognitive effort. Drawing on educational theory, particularly cognitive load theory, the model conceptualises research progression as a dynamic trajectory of both practical and cognitive effort over time.
Results. The model highlights predictable peaks – such as protocol development, data analysis and final writing – and lulls, such as routine data collection. Mapping these fluctuations enables early identification of periods where trainees are most vulnerable to overload and where targeted supervisory or institutional support may have the greatest impact.
Conclusion. The effort-time trajectory model provides a more holistic lens for supporting MMed research training by accounting for both temporal and cognitive demands. Its application may reduce last-minute workload surges, improve research completion timelines and support more sustainable integration of research within specialist training programmes.
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