Well-being and quality of life in people with disabilities practicing sports, athletes with disabilities, and para-athletes: Insights from a critical review of the literature
Bibliographic record
Abstract
Global well-being (GWB) is a complex, multi-dimensional, and multi-faceted construct that can be explored from two different, but often overlapping, complementary perspectives: the subjective and the objective ones. The subjective perspective, in turn, is comprised of two dimensions: namely, the hedonic and the eudaimonic standpoints. Within the former dimension, researchers have developed the concept of subjective hedonic well-being (SHWB), whereas, within the latter, they have built the framework of psychological and social well-being (PSWB). Disabled people have poorer well-being due to their pathology and may more frequently suffer from anxiety and depressive disorders than their able-bodied counterparts. Sports participation is an essential way to cope with disability. On the other hand, compared with their able-bodied peers, athletes with disabilities and para-athletes undergo a unique series of stressors. Little is known in terms of hedonic and eudaimonic well-being and quality of life in this specific population. Here, we review the literature, with an emphasis on the current state-of-art and gaps in knowledge that need to be addressed by future research. High-quality, large-scale investigations are needed to have a better understanding of the self-perceived (hedonic) and objective (eudaimonic) well-being and quality of life of disabled people practicing sports, athletes with disabilities, and para-athletes.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".