Best practice for deltoid intramuscular injections in older adults: Study in cadavers
Bibliographic record
Abstract
Most injectable vaccines are administered via deltoid intramuscular injection (IMI). Nursing students are taught to perform deltoid IMI in their entry-to-practice education program. However, best practice evidence is lacking regarding specific techniques of deltoid IMI, and students are often taught what their instructor was taught in his/her own entry-to-practice (ETP) program. Nursing textbooks provide instructions and diagrams for how to perform deltoid IMI, but rarely cite underpinning empirical evidence. This study tested the injection techniques of bunching (squeezing) or flattening (stretching) the deltoid muscle before administering IMI using medical school donated cadavers. Flattening technique resulted in over-penetration of deltoid injections more than 85% of the time in these older adults, whereas nearly 80% of deltoid IMI are successful using bunching technique. Body mass index (BMI) and needle length are also crucial considerations when administering deltoid IMI. Nurses, and other health professionals who use deltoid IMI to administer vaccines to older adults, should determine the client’s body mass index to select the appropriate needle length. Based on these results, bunching technique is recommended. Flattening technique is not recommended for older adults with a BMI < 30.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".