The Academic, Psychological, and Physical Impact of Motor Skills Difficulties on College Students: A Scoping Review
Bibliographic record
Abstract
Abstract Purpose of Review This scoping review examines the extent and quality of research literature to determine the impact of motor skills difficulties on college or university students. It assesses the adequacy of current institutional supports and identifies opportunities for more inclusive educational practices. Recent Findings Four databases (PubMed, SCOPUS, PsycINFO, and Web of Science) were searched for English-language studies published since 1970. Eighteen studies met inclusion criteria: 12 empirical, 4 descriptive, and 2 program evaluations. Six papers from the UK addressed support, social isolation, and academic confidence; six Israeli studies focused on handwriting, dysgraphia, and accommodations; three US studies examined physical activity; and single studies from Canada, Sweden, and Italy explored social impact, assessment practices, and self-efficacy. Study selection followed PRISMA-ScR and Arksey and O’Malley’s five-stage framework. Findings were qualitatively synthesized. Summary Students with motor difficulties face challenges in executive functioning, communication, confidence, and daily living. While support is inconsistent, physical activity and person-centred approaches show promise. Early identification and inclusive practices are essential, with future research needed to centre the student voice and adopt longitudinal, strengths-based approaches.
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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 | 0.006 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".