Effect of pain-relief nursing on activities of daily living in patients following hip arthroplasty: a systematic review and meta-analysis
Bibliographic record
Abstract
Background: Discomfort and reduced physical function can often be significant after hip arthroplasty procedures, especially in older adults. This can lead to delays in rehabilitation and affect the person's capability to participate in self-care activities. Nursing care directed toward pain relief may be another meaningful step toward advancement in early mobility and functional independence. Purpose: To conduct a systematic review and meta-analysis to examine the effects of nursing care interventions focused on pain relief on activities of daily living outcomes for participants undergoing hip arthroplasty. Methods: Articles published from January 2010 to December 2023 were identified as a result of searches of the PubMed, Web of Science, and Scopus databases. The inclusion criteria consisted of randomized controlled trials and cohort studies in which nursing care interventions directed toward pain relief were examined against standard care. Random effects models were used to calculate pooled standardized mean differences and 95 percent confidence intervals. The risk of bias assessment was conducted using the Newcastle-Ottawa Scale to evaluate each article included in the study. Results: Five articles were reviewed and analyzed with a total of 539 patients. Pain relief-focused nursing care interventions, such as individualized patient education, multimodal analgesia, or guided early ambulation, resulted in improved activities of daily living outcomes when compared to standard care. Overall, the pooled effect size was statistically significant, with an indication of overall greater improvement and minimal variability between studies. Conclusion: Structured planning through nursing care directed toward pain relief is an effective nursing intervention to achieve and sustain improved functional independence and daily activity outcomes, while also decreasing the experience of pain. Implementing evidence-based nursing interventions can enhance recovery and improve patient satisfaction when used as part of postoperative protocols. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD420251164478, identifier PROSPERO (CRD420251164478).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.022 | 0.043 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".