A person-centred investigation of the associations between actual and perceived physical fitness among youth with intellectual disabilities
Bibliographic record
Abstract
The main objective of this person-centred study was to identify profiles of actual and perceived physical fitness among a sample of youth with intellectual disabilities (ID). Participants were 377 youth (60.4% boys) with mild (49.6%) to moderate (50.4%) ID recruited in Australia and Canada. Latent profile analyses revealed five profiles: (1) Underestimation of Average Physical Fitness (5.5% of the sample); (2) Moderate Overestimation of Low Physical Fitness (17.7%), (3) Moderate Underestimation of Average Physical Fitness (31.3%); (4) High Overestimation of Average Physical Fitness (28.3%); and (5) Moderate Underestimation of High Physical Fitness with an Accurate Estimation of Average Flexibility (17.2%). Profiles 1, 2, and 3 relatives to Profiles 4 and 5 included younger participants, more participants with moderate levels of ID, and participants with a higher body mass index. Additionally, profiles 1 and 3 also included a higher proportion of youth pursuing externally-driven motives and less frequently involved in sports outside of the school. In sum, our findings showed that the tendency of youth with ID to rely on upward or downward-lateral social comparisons may have resulted in a depreciation or overestimation of their low levels of physical fitness.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".