Grip Type Alters Maximal Pinch Forces in Syringe Use
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to determine maximum forces during syringe use for different grips found in the field. BACKGROUND: Prolonged syringe use in chemotherapy drug delivery is associated with pain and injury in nurses and technicians. METHOD: Twenty healthy female hospital workers generated isometric maximum voluntary force using a 30 cc syringe with four pinch grips (chuck, chuck variation, thenar, two-handed). Both dominant and nondominant hands were used with the syringe plunger fixed in wide (8.3 cm) and narrow (2.5 cm) grip spans. Participants were encouraged to position the apparatus in the most comfortable position and exert a maximal effort for 5 seconds. RESULTS: Significant interaction effects were found: Grip Span × Pinch Type, Hand × Pinch Type, and Grip Span × Hand × Pinch Type ( p < .05). The results demonstrated that the thenar (103.6 ± 22.9 N) and two-handed (104.7 ± 17.1 N) pinches produced the highest forces. CONCLUSION: Thenar and two-handed pinch grips may be the preferred pinch type to lower the relative efforts required to use a syringe and may be one strategy to assist with reduction of musculoskeletal disorder risk associated with syringe use. APPLICATION: Determining maximal syringe press forces allows workers and ergonomists to develop better strategies for managing the cumulative loads during drug delivery and mixing.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".