Understanding the negative outcomes of sport participation – a motivational model
Bibliographic record
Abstract
Sport psychology research, using the Self-Determination Theory (SDT) framework, has extensively examined athletes and the factors that lead to their success and continued participation in sport. In reality, athletes can also experience a number of negative outcomes such as burnout that undermine the positive outcomes. The relationship between the environment, psychological needs, goal content, motivation, and negative outcomes in sport is somewhat ambiguous. The purpose of the present review is to examine existing research that has looked at SDT and negative affective, behavioural, and cognitive outcomes in sport and to organize this literature into a coherent model for understanding negative outcomes. The proposed model suggests that a non-supportive environment will directly influence need-dissatisfaction, low quality motivation, and negative outcomes for athletes. When it comes to need dissatisfaction specifically, athletes can either engage in compensatory behaviours to satisfy their needs, or they can become chronically dissatisfied which also leads to extrinsic goals, lower quality motivation and negative outcomes. Negative affective, behavioural, and cognitive outcomes serve as ends in and of themselves; however, cognitive outcomes also serve as a mediator between psychological needs and motivation with affective and behavioural outcomes. In these instances, the athletes' cognitive experience serves to either enable or prevent other negative outcomes. Implications and directions for future research are discussed. Acknowledgments: This research was conducted while the first author was supported by a doctoral scholarship from the Social Sciences and Humanities Research Council of Canada (SSHRC).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".