Effects of doctor-nurse-patient collaborative nursing on self-care ability and psychological resilience in trifacial neuralgia patients after surgery
Bibliographic record
Abstract
Objective To explore the effects of doctor-nurse-patient collaborative nursing on self-care ability and psychological resilience in trifacial neuralgia (TN) patients after surgery so as to establish the effective nursing intervention model for TN patients after surgery. Methods From January 2016 to October 2018, this study selected 56 TN patients with doctor-nurse-patient collaborative nursing after surgery at the People's Hospital Anyang City of Henan Province in observation group. From January 2013 to December 2015, this study recruited 45 TN patients with routine nursing after surgery in control group. Differences of patients between two groups were compared with the Exercise of Self-Care Agency Scale (ESCA) , Connor-Davidson Resilience Scale (CD-RISC) and the McGill pain questionnaire (MPQ) before and after intervention. Results Three months after intervention, the subscale scores of self-care skill and self-care responsibility of ESCA, toughness, self-reliance and optimist of CD-RISC of patients in observation group were (36.22±5.47) , (27.23±3.47) , (34.12±4.36) , (26.15±3.69) and (16.02±1.76) respectively higher than those in control group with statistical differences (t=7.394, 4.982, 7.792, 6.965, 6.864; P<0.05) . Three months after intervention, the score of present pain intensity of MPQ of patients in observation group was (1.02±0.34) lower than that (1.69±0.22) in control group with a statistical difference (t=11.429, P<0.01) . Conclusions Doctor-nurse-patient collaborative nursing can improve self-care ability, social support and quality of life of TN patients after surgery, reduce the pain intensity and increase patients' psychological resilience. Key words: Trigeminal neuralgia; Quality of life; Pain; Collaborative nursing; Resilience, psychological; Self-care
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".