Interplay of motivation and self-regulation throughout the development of elite athletes
Bibliographic record
Abstract
Recent development in the understanding of human motivation has highlighted the crucial and reciprocal role of motivation on cognitive processes. In elite sport settings, athletes are subject to external forces that do not necessarily correspond with their inherent drives. However, they seem to develop cognitive competencies to cope with external forces, when planning, monitoring, and reflecting on their high-level achievements. The current study aims to explore likely interactions between motivation and cognitive processes as athletes develop from novice to elite levels. Five female Olympic and World Championship medallists were interviewed. A thematic analysis revealed how motivation and self-regulation competencies interchangeably influenced athletes’ career trajectories asynchronously. Chronologically, four themes emerged: 1) Motivational shifts evoked planning and self-control competencies, 2) The external control constrained athletes’ self-regulation, 3) Self-control and reflection in extrinsically driven athletes, and 4) Elite athletes’ multidimensional motivation and self-regulation profile. Initially, intrinsic motivation prompted athletes’ participation, but the competitive nature of sport activities led to a shift toward more external forms of motivation. This motivational shift was accompanied by changes in self-regulation competencies, particularly planning and self-control, rather than self-reflection. Over time, athletes’ increased sport-specific self-confidence contributed to further refinement of self-regulation competencies and integrated motivational regulations. Rather than exploring motivation and cognitive competencies individually, current study findings highlight dynamic interactions between these concepts that influences athletes’ ongoing development to elite level performances.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".