Postoperative Arm Massage
Bibliographic record
Abstract
PURPOSE/OBJECTIVE: To evaluate the usefulness of arm massage from a significant other following lymph node dissection surgery. DESIGN: Randomized clinical trial with a pretest-posttest design. Data were collected prior to surgery, within 24 hours post surgery, within 10 to 14 days post surgery, and 4 months post surgery. SAMPLE: 59 women, aged 21 to 78 undergoing lymph node dissection surgery and who had a significant other with them during the postoperative period. METHODS: Subjects were randomly assigned to intervention and control groups. Subjects' significant others in the intervention group were first taught, then performed arm massage as a postoperative support measure. RESEARCH MAIN VARIABLES: Variables included postoperative pain, family strengths and stressors, range of motion, and health related costs. FINDINGS: Participants reported a reduction in pain in the immediate postoperative period and better shoulder function. CONCLUSION: Arm massage decreased pain and discomfort related to surgery, and promoted a sense of closeness and support amongst subjects and their significant other. IMPLICATION FOR NURSING PRACTICE: Postoperative massage therapy for women with lymph node dissection provided therapeutic benefits for patients and their significant other. Nurses can offer effective alternative interventions along with standard procedures in promoting optimal health.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".