Application of staged nursing based on Snyder's theory of hope in preoperative nursing of patients with primary liver cancer
Bibliographic record
Abstract
ObjectiveTo observe the effect of staged nursing based on Snyder's theory of hope on the preoperative frailty and despair levels of primary liver cancer patients.MethodsA total of 140 patients with primary liver cancer who underwent surgical treatment in our hospital from December 2022 to December 2023 were selected,and were randomly divided into a control group and a hope group,with 70 cases in each group.Both groups received routine perioperative care.The patients in control group received conventional psychological intervention.The patients in hope group adopted staged care based on Snyder's theory of hope.The scores of the Chinese version of Edmonton Frail Scale(EFS),Mini⁃Mental State Examination(MMSE) and Beck Hopelessness Scale(BHS) of two groups of patients before and after the operation were compared.ResultsThe EFS scores of the patients in the hope group on the day of surgery and the third day after surgery were all lower than those in the control group(P<0.05),the MMSE scores were higher than those in the control group(P<0.05).Three days after the operation,the total score of BHS and the scores of all dimension in the hope group were lower than those at admission.And the perception of the future,expectations for the future and the total score in the hope group were all lower than those in the control group(P<0.05).The incidence of postoperative complications in the hope group was lower than that in the control group(P<0.05).ConclusionsStaged nursing based on Snyder's theory of hope for patients undergoing primary liver cancer surgery could improve the frailty,cognitive function and postoperative despair level,and reduce the risk of postoperative complications.
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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".