Abstract
Background
This study evaluated the effects of integrating evidence-based nursing (EBN) with proactive nursing on postoperative satisfaction and cognitive function in patients undergoing surgical anesthesia.
Methods
This quasi-experimental study enrolled 160 adults scheduled for elective surgery under general anesthesia. Participants were allocated to an intervention group receiving a structured protocol combining EBN and proactive nursing, or a control group receiving standard postoperative care. The primary outcome was postoperative patient satisfaction, measured by the Patient Satisfaction Questionnaire-18 (PSQ-18). Secondary outcomes included pain scores (Visual Analog Scale, VAS), cognitive function (Mini-Mental State Examination, MMSE), postoperative complications, length of hospital stay, early mobility, and emotional well-being.
Results
The intervention group had higher PSQ-18 total scores before discharge than the control group (78.6 ± 6.9 vs. 69.4 ± 8.1; mean difference, 9.2; 95% CI, 6.8–11.6; Bonferroni-adjusted p < 0.001). Repeated-measures analysis of VAS pain scores revealed significant time, group, and group × time interaction effects, indicating greater pain reduction over time in the intervention group. At 24 h postoperatively, VAS scores were 3.2 ± 2.1 in the intervention group and 5.6 ± 2.5 in the control group. The group × time interaction for MMSE scores was also significant: scores changed from 27.9 ± 1.4 preoperatively to 28.4 ± 1.2 at 72 h in the intervention group, and from 28.0 ± 1.5 to 27.3 ± 1.6 in the control group. Postoperative complications occurred in 9 patients (11.3%) in the intervention group and 33 patients (41.3%) in the control group (adjusted p = 0.031).
Conclusion
Integrating evidence-based and proactive nursing strategies was associated with improved postoperative satisfaction and selected recovery outcomes in surgical anesthesia patients. Given the quasi-experimental design, these findings should be interpreted cautiously and confirmed in future randomized controlled trials.
Clinical trial number
Not applicable.
Supplementary Information
The online version contains supplementary material available at https://doi.org/10.1186/s12912-026-04885-5.
Keywords: Evidence-based nursing, Proactive nursing, Postoperative satisfaction, Cognitive function, Surgical anesthesia
Background
The postoperative recovery phase is critically important for patients undergoing anesthesia. It significantly influences both short-term recovery outcomes—such as pain control, early mobilization, hospital stay, and immediate complications—and long-term outcomes, including sustained quality of life, functional independence, and survival [1]. Despite advances in surgical techniques and anesthesia management, postoperative experiences remain variable. This variability is often linked to the effectiveness of nursing care [2].
Effective nursing interventions can mitigate complications and enhance recovery, thereby improving overall patient satisfaction [3]. Inadequate postoperative care may lead to increased pain, anxiety, and cognitive deficits. Therefore, there is an urgent need to adopt more comprehensive nursing strategies that prioritize both evidence-based practices and proactive care.
Traditional nursing approaches have largely relied on reactive interventions, addressing complications only after they arise rather than anticipating patient needs [4]. Although studies have demonstrated the benefits of structured pain management and early mobilization, these strategies alone may not fully address the complex needs of postoperative patients [5]. The absence of a proactive framework can delay care delivery, resulting in suboptimal outcomes and diminished patient experiences [6].
In light of these challenges, this study proposes an integrated approach that combines evidence-based nursing (EBN) with proactive nursing strategies in the context of anesthesia care. EBN involves applying the best available research to inform clinical decision-making, ensuring that nursing interventions are both effective and grounded in current evidence [3]. Proactive nursing emphasizes anticipating patient needs and potential complications, thereby facilitating timely interventions that improve recovery outcomes [7].
Although both EBN and proactive nursing have been applied individually in perioperative care, limited evidence is available regarding their combined use in patients undergoing surgery under general anesthesia. In particular, it remains unclear whether an integrated nursing protocol can improve postoperative satisfaction while also supporting pain control, cognitive recovery, emotional well-being, and complication prevention. This knowledge gap limits the development of structured postoperative nursing protocols for surgical anesthesia patients.
The research question of this study was whether an integrated evidence-based and proactive nursing protocol would be associated with better postoperative outcomes than routine nursing care among patients undergoing general anesthesia. The primary objective was to evaluate the effect of this integrated protocol on postoperative patient satisfaction. Secondary objectives included assessing postoperative pain, cognitive function, complications, length of hospital stay, early mobility, and emotional well-being. Using a quasi-experimental design, we compared outcomes between patients receiving standard care and those receiving a structured protocol that incorporated both EBN and proactive nursing elements. Key variables included patient satisfaction scores, cognitive assessments, and the incidence of postoperative complications.
We hypothesized that patients receiving the integrated nursing approach would report higher postoperative satisfaction than those receiving routine nursing care. We further hypothesized that the integrated protocol would be associated with improved secondary outcomes, including lower pain scores, better cognitive recovery, fewer complications, shorter hospital stay, earlier mobility, and enhanced emotional well-being.
Methods
Study design
This study employed a quasi-experimental design to evaluate the association between an integrated nursing approach combining evidence-based nursing and proactive nursing strategies and postoperative outcomes in patients undergoing surgery under general anesthesia. The research was conducted in the surgical unit of Fushun People’s Hospital, Zigong, China, where patients were routinely monitored and cared for postoperatively.
Study population
The study population consisted of adult patients aged 18 years and older who were scheduled to undergo elective surgical procedures requiring general anesthesia. Participants were recruited from the surgical unit prior to their scheduled surgeries, and informed consent was obtained from all participants to ensure they understood the purpose of the study and their rights.
Inclusion and exclusion criteria
Individuals were eligible for inclusion in the study if they met the following criteria: (1) Aged 18 years and older. (2) Undergoing elective surgeries that required general anesthesia. (3) Able to provide informed consent and participate in the study, as assessed by the research team. (4) Expected to have a postoperative stay of at least 24 h for adequate monitoring of outcomes.
Individuals were excluded from the study if they met any of the following criteria: (1) Undergoing emergency surgical procedures. (2) Having a history of significant cognitive impairment or psychiatric disorders that may affect their ability to provide informed consent or participate in cognitive assessments. (3) Unable to communicate in the primary language of the research team. (4) Having severe comorbid conditions that could affect postoperative recovery or cognitive function. (5) Having a history of substance abuse that could interfere with cognitive assessments or recovery.
Grouping and blinding
Participants were allocated to the control or intervention group using a non-randomized, sequential allocation process. To reduce contamination between care models, eligible patients admitted during the first study period were assigned to the control group, whereas eligible patients admitted during the subsequent study period, after completion of nurse training on the integrated protocol, were assigned to the intervention group. No random sequence generation or allocation concealment was applied.
Because the study did not involve random sequence generation, allocation concealment, or full blinding, it was classified as a quasi-experimental study rather than a randomized controlled trial. This allocation approach was selected to facilitate implementation of the nursing protocol in routine clinical practice and to reduce contamination; however, it may have introduced selection bias, temporal bias, or unmeasured baseline imbalance. Therefore, the observed differences between groups should be interpreted as associations rather than definitive causal effects.
Each group consisted of 80 participants, with one group designated as the intervention group and the other as the control group. The Intervention Group received a structured nursing protocol that integrated evidence-based practices and proactive nursing strategies, which included preoperative education, standardized pain management, cognitive assessments, emotional support, and encouragement of early mobilization. In contrast, the Control Group received standard postoperative care, which involved routine nursing practices without the additional structured interventions.
Due to the nature of the nursing intervention, participants and nursing staff could not be fully blinded to group allocation. Participants were informed that they would receive perioperative nursing care as part of the study, but they were not explicitly informed of the specific study hypothesis or expected direction of benefit. Standardized outcome assessment procedures were used to reduce response and assessment bias, in accordance with recommended transparent reporting of allocation and blinding procedures [8]. Nursing staff providing care were not blinded to group allocation because the intervention required active participation. Outcome assessors were not involved in the delivery of the nursing intervention and collected data using standardized questionnaires and predefined assessment forms. If complete assessor blinding was not feasible, this was acknowledged as a methodological limitation. The lack of full blinding of participants, nursing staff, and potentially outcome assessors was considered a source of possible performance and detection bias [8]. To mitigate any potential bias in care delivery, all nursing staff underwent training on the study protocols and were instructed to maintain consistent care standards for both groups. This approach was intended to reduce potential performance and assessment bias, although residual bias could not be completely excluded.
Measures to minimize contamination between groups
Several measures were implemented to minimize potential contamination between the intervention and control groups. First, different nursing staff were assigned to provide care for patients in the intervention and control groups whenever feasible. Nurses responsible for the intervention group received separate training on the integrated evidence-based and proactive nursing protocol, whereas nurses caring for the control group continued to provide routine nursing care according to standard departmental procedures. Second, intervention-related materials, including structured education content, proactive assessment checklists, and nursing protocol documents, were not provided to the control group. Third, data collectors were not involved in the direct delivery of the nursing intervention, which helped reduce the risk that intervention procedures would be unintentionally transferred to the control group. Fourth, patients were not encouraged to discuss the specific content of their nursing care with patients in the other group during hospitalization. Finally, nursing staff were reminded throughout the study period to maintain the distinction between routine care and the integrated intervention protocol. Despite these measures, contamination between groups could not be completely excluded because both groups were treated within the same hospital setting; this was therefore considered a limitation of the study [8].
Sample size
The sample size calculation was exploratory and was performed using G*Power software, which is commonly used for statistical power analysis across t tests, F tests, χ² tests, z tests, and exact tests [9]. The calculation was based on the primary outcome, postoperative patient satisfaction assessed using the PSQ-18. Because limited prior evidence was available for the combined use of evidence-based and proactive nursing in this specific population, an expected medium effect size of Cohen’s d = 0.5 was assumed, consistent with Cohen’s conventional definition of a medium standardized effect size [10, 11]. The power analysis was based on a two-sided independent-samples t-test comparing postoperative satisfaction scores between the intervention and control groups, with α = 0.05 and statistical power = 0.80. To account for potential participant attrition or incomplete outcome data, an anticipated dropout rate of 10% was incorporated into the sample size estimation.
Using these parameters, the power analysis indicated that a minimum of 64 participants per group would be required to achieve the desired power and effect size. To accommodate the anticipated dropout rate, the total required sample size was adjusted to 144 participants (72 per group). Therefore, the final target sample size was set at 160 participants, with 80 allocated to each group. This sample size was used consistently across the Abstract, Methods, Results, and tables.
Interventions
The intervention protocol was developed based on evidence-based nursing principles and proactive nursing strategies and was delivered according to a structured perioperative checklist. The protocol covered four stages: preoperative assessment and education, intraoperative risk prevention, early postoperative monitoring, and discharge-oriented recovery support. Before implementation, all intervention nurses received standardized training, including protocol explanation, checklist use, pain assessment, MMSE assessment procedures, communication skills, early mobilization guidance, and complication-prevention strategies. Protocol adherence was reviewed daily by the head nurse.
Evidence-based nursing emphasizes the integration of best available research evidence, clinical expertise, and patient needs into nursing decision-making, whereas proactive nursing focuses on anticipating patient needs, identifying potential risks early, and providing timely preventive care [3, 7]. The major components of routine nursing, evidence-based nursing, proactive nursing, and the combined intervention are summarized in Supplementary Table 1.
(1) Preoperative Preparations: a). Comprehensive preoperative assessments were conducted, ensuring all necessary examinations were completed. B). Relevant medications were prepared in advance, and the surgical instruments were calibrated for the procedure. (2) Surgical Environment Preparation: a). The operating room was thoroughly disinfected to maintain a sterile environment. b). Appropriate temperature and humidity levels were adjusted in the surgical area to optimize conditions for the procedure. (3) Venous Access: a). Establishment of venous access was performed to facilitate the administration of medications and fluids. b). Support was provided to the anesthesiologist during the anesthesia induction process. (4) Intraoperative Support: a). During surgery, the nursing staff actively collaborated with the surgical team, adhering to departmental protocols and the specific requirements of the surgeon. B). Continuous monitoring of the patient’s vital signs was maintained throughout the procedure to ensure immediate detection of any abnormalities.
Intervention group: the intervention group received an integrated model of evidence-based and proactive nursing throughout the perioperative period (Fig. 1). The intervention was implemented by trained nurses according to the structured protocol described in Supplementary Table 1.
Fig. 1.
An overview of evidence-based nursing + proactive nursing processes
I. Evidence-based nursing: A. Formation of the Evidence-Based Nursing Team. (1) An evidence-based nursing team was established, consisting of the head nurse and seven experienced surgical nurses (≥ 5 years). 2). Training sessions were conducted focusing on the concepts and methods of evidence-based nursing, including evidence retrieval, identification of patient-specific nursing problems, translation of evidence into clinical care plans, and evaluation of nursing outcomes [3]. Following the training, assessments were administered to ensure that all nurses fully mastered the evidence-based nursing techniques before being assigned nursing responsibilities. B. Identification of Evidence-Based Issues. 1) A comprehensive analysis of each patient’s specific condition, surgical treatment plan, physical status, and psychological state was performed, summarizing past clinical experiences to identify evidence-based nursing issues. (2) The primary nursing concerns identified for patients undergoing anesthesia in the surgical unit included unstable vital signs post-anesthesia, inadequate venous access, postoperative pain, and management of drainage tubes. (3) Based on these issues, relevant nursing research literature was reviewed, and previous clinical experiences were summarized to develop targeted evidence-based nursing intervention protocols. C. Evidence-Based Nursing Interventions. (1) Vital Signs Monitoring: Continuous monitoring of blood pressure, temperature, and other physiological indicators was conducted after anesthesia. Observations included pupil changes, consciousness, mental status, and emotional state, with immediate reporting of any abnormalities to the surgical team for timely intervention. Bleeding volume, color, and quality were also monitored to prevent emergencies. (2) Venous Access Management: Continuous monitoring of venous access was implemented to ensure patency for medication, blood, and fluid administration. Dual venous access was established to facilitate treatment and emergency procedures. (3) Postoperative Pain Management: Postoperative pain was assessed every 3 h during the first 24 h after surgery and then at least twice daily until 72 h postoperatively using the Visual Analog Scale (VAS), allowing patients to indicate their pain intensity on a 0 to 10 cm scale. When VAS scores were ≥ 4, nurses promptly informed the physician and implemented individualized pain-relief measures, including prescribed analgesics, position adjustment, relaxation guidance, music therapy, and reassessment after intervention. Pain relief was tailored based on self-reported assessments, combining pharmacological pain relief with music therapy and meditation techniques. (4) Postoperative Care: Nasogastric tubes were secured with adhesive tape, and continuous monitoring of drainage tubes was implemented to ensure patency. Patients were guided on gentle and slow movements to avoid dislodgment or blockage of nasogastric and drainage tubes. Daily skin care was provided to prevent infections and other factors that could lead to catheter blockage. Follow-up care was conducted to guide patients in self-care.
II. Proactive Nursing Measures: Proactive nursing was designed to identify patient needs and potential perioperative risks in advance, rather than responding only after complications or discomfort occurred [7]. A. Preoperative Proactive Care. (1) One day prior to surgery, targeted health education was provided, detailing the surgical procedure and important precautions. The necessity and benefits of preventive nursing measures were emphasized, allowing patients to understand potential adverse events and complications. (2) A comprehensive assessment of the patient’s physiological, nutritional, and psychological status was conducted to predict potential adverse events and complications, implementing targeted preventive measures. For patients with suboptimal physiological indicators (e.g., blood pressure, blood sugar), specific improvement measures were taken. Nutritional support was provided for those with poor nutritional status, and psychological well-being was addressed through companionship, reassurance, and encouragement. B. Intraoperative Proactive Care. (1) Continuous presence during surgery helped reassure patients through gentle touch and physical presence, enhancing their sense of safety. Privacy was maintained, and the surgical area was minimally exposed. (2) Communication among medical staff was kept at a low volume to avoid using distressing terminology (e.g., “cut,” “bleeding”) that might provoke anxiety in patients. Nursing staff were informed about the surgical process and the operating habits of the surgical team to enhance coordination. (3) A warming device was utilized for infusions, and continuous monitoring of the patient’s temperature was conducted to prevent intraoperative hypothermia. The intravenous access was monitored to ensure fluid administration remained unobstructed, with detailed records kept of intraoperative procedures to ensure accountability. C. Postoperative Proactive Care. (1) Continuous follow-up was conducted after anesthesia recovery, with immediate communication of the surgical outcomes to the patient, alongside encouragement. (2) Assessment of the patient’s postoperative recovery was carried out, providing targeted nursing guidance. Patients were encouraged to mobilize early according to their postoperative condition, vital signs, pain level, drainage-tube status, and physician instructions. Nurses assessed mobilization readiness within 6 h after surgery and provided stepwise guidance, including turning in bed, sitting at the bedside, standing, and walking with assistance. Mobilization was postponed when patients had dizziness, unstable vital signs, excessive pain, or high drainage risk. (3) To prevent complications, patients were repositioned every 2 h to reduce the risk of pressure injuries. Infection indicators were monitored to provide appropriate antimicrobial treatment, and bleeding was closely observed and managed. (4) Targeted dietary plans and nutritional support were developed to improve the patient’s nutritional status, with ongoing follow-up to encourage active prevention of complications.
Outcome measures
Primary outcome — Patient satisfaction
Patient satisfaction was assessed using the Patient Satisfaction Questionnaire-18, which evaluates various dimensions of care, including communication with healthcare providers, pain management, and overall quality of care. Patients complete the PSQ-18 before discharge, rating their satisfaction on a Likert scale ranging from 1 (very dissatisfied) to 5 (very satisfied). Each item is scored, and the total score provides insight into specific areas that may require improvement, helping to enhance overall patient experience.
Secondary outcome — Pain levels
Pain intensity was quantified using the Visual Analog Scale, where patients indicated their pain level on a 10-cm line, with 0 representing “no pain” and 10 indicating “worst pain imaginable.” Pain assessments are conducted every 3 h postoperatively, allowing for timely adjustments to pain management strategies based on the recorded levels. This method provides a straightforward way for patients to communicate their pain, ensuring that nursing staff can respond promptly to any pain management needs.
Secondary outcome — Cognitive function
The Mini-Mental State Examination was used to evaluate cognitive function in patients. This assessment consists of 30 questions that cover various cognitive domains, including orientation, attention, memory, and language skills. The MMSE is administered preoperatively and again at 24 and 72 h postoperatively to monitor any changes in cognitive status. This evaluation was used to monitor short-term changes in global cognitive performance after surgery and anesthesia. However, because MMSE scores may be affected by repeated testing, short follow-up duration, patient fatigue, pain, sleep disturbance, and emotional state, the MMSE results were interpreted as short-term cognitive screening outcomes rather than definitive evidence of postoperative cognitive protection. However, repeated administration of the MMSE at 24 and 72 h postoperatively may introduce a learning effect, whereby patients could perform better on subsequent assessments due to familiarity with the test items rather than true cognitive recovery. To minimize this bias, the research team used alternate test versions where available and instructed assessors to follow standardized scripts; nonetheless, residual practice effects could not be completely eliminated.
Secondary outcome — Incidence of postoperative complications
A custom complication tracking form was used to document specific postoperative complications, such as nausea, vomiting, and surgical site infections. Nursing staff systematically record any complications observed during the hospital stay, including the timing and severity of each event. This data is collected daily until discharge, enabling comprehensive tracking of complications and facilitating better postoperative care management through the identification of trends and patterns.
Secondary outcomes — Recovery outcomes
Recovery outcomes were assessed using length of hospital stay, early mobility, emotional well-being, and quality of life. Length of hospital stay was determined by reviewing hospital records to calculate the total duration from admission to discharge. Early mobility was documented using a mobility assessment checklist, where nursing staff recorded the time from surgery to the first successful achievement of sitting up, standing, or walking with or without assistance. A shorter time indicated earlier mobilization. Emotional well-being was evaluated using the Hospital Anxiety and Depression Scale (HADS), which includes two subscales: HADS-Anxiety and HADS-Depression. Each subscale ranges from 0 to 21, with higher scores indicating greater anxiety or depression symptoms. HADS-Anxiety and HADS-Depression were reported separately rather than as a combined total score. Quality of life was assessed using the 36-item Short Form Health Survey (SF-36), with scores transformed to a 0–100 scale; higher scores indicated better quality of life. A score of 70 was used descriptively to indicate relatively favorable quality of life rather than as a diagnostic threshold.
Statistical analysis
All statistical analyses were performed using SPSS version 23.0. Continuous variables were summarized as mean ± standard deviation for normally distributed data or median and interquartile range for non-normally distributed data. Categorical variables were summarized as frequencies and percentages. The Shapiro-Wilk test was used to assess normality. Between-group comparisons of baseline characteristics were performed using independent-samples t-tests or Mann-Whitney U tests for continuous variables and χ² tests or Fisher’s exact tests for categorical variables, as appropriate.
The primary outcome was the PSQ-18 total satisfaction score before discharge. Between-group differences in PSQ-18 scores were analyzed using an independent-samples t-test, and the mean difference with 95% confidence interval was reported. For repeated-measures outcomes, including VAS pain scores, MMSE scores, and HADS-Anxiety and HADS-Depression scores, repeated-measures ANOVA was used to evaluate the time effect, group effect, and group × time interaction effect. When the sphericity assumption was violated, Greenhouse-Geisser correction was applied. If repeated-measures data were not normally distributed, sensitivity analyses were performed using non-parametric comparisons of change scores between time points.
Because multiple secondary outcomes were analyzed, Bonferroni correction was applied to key secondary outcome comparisons. Secondary outcomes were interpreted as exploratory, and adjusted p-values were reported where appropriate. Logistic regression was used to evaluate the association between the nursing intervention and postoperative complications after adjustment for age, sex, type of surgical procedure, anesthesia duration, preoperative anxiety score, and comorbidities. Statistical significance was assessed using two-sided tests, with p < 0.05 considered statistically significant for the primary outcome. For secondary outcomes, findings were interpreted cautiously in light of multiple comparisons.
Results
Baseline profiles
The baseline characteristics of the participants in both the intervention and control groups are summarized in Table 1. A total of 160 adult patients participated in the study, with 80 allocated to the intervention group and 80 to the control group. Baseline variables included age, sex, body mass index, type of surgery, anesthesia duration, anesthetic agents, preoperative medication use, preoperative HADS-Anxiety and HADS-Depression scores, and baseline SF-36 quality-of-life scores. The groups were generally comparable in measured demographic and clinical characteristics. However, given the quasi-experimental design, unmeasured baseline differences could not be excluded, and differences in postoperative outcomes should be interpreted as associations rather than definitive causal effects.
Table 1.
Baseline characteristics of participants
| Variable | Intervention group (n = 80) | Control group (n = 80) | p value |
|---|---|---|---|
| Age, years | 52.4 ± 10.8 | 53.1 ± 11.2 | 0.69 |
| Age ≥ 60 years, n (%) | 40 (50.0) | 42 (52.5) | 0.75 |
| Male sex, n (%) | 39 (48.8) | 41 (51.3) | 0.75 |
| BMI, kg/m² | 23.8 ± 3.2 | 24.1 ± 3.4 | 0.56 |
| Surgical procedure type, n (%) | |||
| General surgery | 31 (38.8) | 33 (41.3) | 0.75 |
| Orthopedic surgery | 24 (30.0) | 22 (27.5) | 0.73 |
| Gynecological surgery | 15 (18.8) | 16 (20.0) | 0.84 |
| Urological surgery | 10 (12.5) | 9 (11.3) | 0.81 |
| Comorbidities, n (%) | |||
| Hypertension | 25 (31.3) | 24 (30.0) | 0.87 |
| Diabetes mellitus | 15 (18.8) | 17 (21.3) | 0.69 |
| Cardiovascular disease | 10 (12.5) | 9 (11.3) | 0.81 |
| Respiratory disease | 8 (10.0) | 7 (8.8) | 0.79 |
| Renal disease | 5 (6.3) | 6 (7.5) | 0.76 |
| ASA physical status, n (%) | |||
| ASA I | 30 (37.5) | 28 (35.0) | 0.74 |
| ASA II | 40 (50.0) | 42 (52.5) | 0.75 |
| ASA III | 10 (12.5) | 10 (12.5) | 1 |
| Smoker, n (%) | 15 (18.8) | 18 (22.5) | 0.56 |
| Anesthesia duration, min | 112.6 ± 28.4 | 115.3 ± 30.1 | 0.56 |
| Propofol-based anesthesia, n (%) | 72 (90.0) | 70 (87.5) | 0.62 |
| Sevoflurane use, n (%) | 58 (72.5) | 61 (76.3) | 0.59 |
| Opioid analgesic use, n (%) | 76 (95.0) | 77 (96.3) | 0.7 |
| Preoperative sedative use, n (%) | 18 (22.5) | 20 (25.0) | 0.71 |
| Preoperative pain score | 4.0 ± 1.2 | 4.1 ± 1.1 | 0.6 |
| Preoperative HADS-Anxiety score | 7.6 ± 2.3 | 7.8 ± 2.4 | 0.59 |
| Preoperative HADS-Depression score | 6.7 ± 2.1 | 6.8 ± 2.2 | 0.77 |
| Baseline SF-36 score | 68.5 ± 9.6 | 67.9 ± 10.1 | 0.7 |
Note: Data are presented as mean ± standard deviation or number (percentage). p values were derived from independent-samples t-tests for continuous variables and chi-square or Fisher’s exact tests for categorical variables, as appropriate. ASA, American Society of Anesthesiologists; BMI, body mass index; HADS, Hospital Anxiety and Depression Scale; SF-36, 36-item Short Form Health Survey
Patient satisfaction
As shown in Fig. 2, patient satisfaction was assessed using the PSQ-18 questionnaire before discharge. The intervention group had a higher PSQ-18 total score than the control group (78.6 ± 6.9 vs. 69.4 ± 8.1; mean difference, 9.2; 95% CI, 6.8–11.6; Bonferroni-adjusted p < 0.001). Subscale analyses showed higher scores in the intervention group for communication with healthcare providers (4.5 ± 0.5 vs. 3.9 ± 0.7), pain management satisfaction (4.4 ± 0.6 vs. 3.6 ± 0.8), and overall quality of care (4.6 ± 0.5 vs. 3.8 ± 0.7). These findings suggest that the integrated nursing protocol was associated with higher patient-reported satisfaction.
Fig. 2.
Comparison of patient satisfaction between the two groups before discharge. Selected PSQ-18 domain scores were higher in the intervention group than in the control group. PSQ-18 total scores are reported in the Results section. **** p < 0.0001 vs. control group
Pain severity
VAS pain scores were analyzed using repeated-measures ANOVA across postoperative 6, 24, 48, and 72 h. Pain scores decreased over time in both groups, but the reduction was greater in the intervention group. The repeated-measures analysis showed a significant time effect (F = 186.4, p < 0.001), group effect (F = 34.7, p < 0.001), and group × time interaction effect (F = 11.8, p < 0.001), indicating that the pattern of pain reduction differed between groups over time. VAS scores in the intervention group were 5.1 ± 1.7 at 6 h, 3.2 ± 2.1 at 24 h, 2.1 ± 1.4 at 48 h, and 1.3 ± 0.9 at 72 h. Corresponding scores in the control group were 6.0 ± 1.8, 5.6 ± 2.5, 3.9 ± 1.8, and 2.5 ± 1.3, respectively. These results suggest that the integrated nursing intervention was associated with greater improvement in postoperative pain over time (Fig. 3).
Fig. 3.
Repeated-measures comparison of postoperative pain severity between the two groups using VAS scores at 6, 24, 48, and 72 h after surgery. Repeated-measures ANOVA showed significant time, group, and group × time interaction effects. **** p < 0.0001 vs. control group. vs. control group
Cognitive function
MMSE scores were analyzed using repeated-measures ANOVA at three time points: preoperatively, 24 h postoperatively, and 72 h postoperatively. The analysis showed a significant time effect (F = 42.6, p < 0.001), group effect (F = 9.4, p = 0.003), and group × time interaction effect (F = 8.7, p < 0.001). In the intervention group, MMSE scores were 27.9 ± 1.4 preoperatively, 27.1 ± 1.6 at 24 h, and 28.4 ± 1.2 at 72 h. In the control group, MMSE scores were 28.0 ± 1.5 preoperatively, 26.3 ± 1.9 at 24 h, and 27.3 ± 1.6 at 72 h. As shown in Fig. 4, the intervention group showed slightly higher MMSE scores over time than the control group. The absolute between-group difference at 72 h was modest, and the follow-up period was short. Therefore, although the MMSE trajectory favored the intervention group, this finding should be interpreted cautiously as a short-term association rather than definitive evidence that the intervention directly improved cognitive function. However, repeated MMSE administration at 24 and 72 h postoperatively may introduce a learning effect. Such practice effects could lead to artificially higher scores over time even in the absence of genuine cognitive recovery. Therefore, the observed between-group difference in MMSE trajectories should be interpreted with caution; it reflects an association with the nursing intervention but does not prove a direct cognitive protective effect. The possibility that part of the improvement was due to test repetition cannot be excluded.
Fig. 4.
Short-term MMSE score trajectories in the intervention and control groups preoperatively and at 24 and 72 h postoperatively. Repeated-measures ANOVA showed significant time, group, and group × time interaction effects
Postoperative complication rates between the two groups
The intervention group had a lower overall postoperative complication rate than the control group. In the intervention group, nausea occurred in 5 patients (6.3%), vomiting in 3 patients (3.8%), and surgical site infection in 1 patient (1.3%). In the control group, nausea occurred in 16 patients (20.0%), vomiting in 10 patients (12.5%), and surgical site infection in 7 patients (8.8%). Overall, postoperative complications occurred in 9 patients in the intervention group and 33 patients in the control group (11.3% vs. 41.3%; Bonferroni-adjusted p = 0.031). All complications were mild to moderate and were managed during hospitalization (Table 2).
Table 2.
Comparison of postoperative complication rates between the two groups
| Complication | Intervention group (n = 80) | Control group (n = 80) | χ² value | p value |
|---|---|---|---|---|
| Nausea, n (%) | 5 (6.3) | 16 (20.0) | 6.54 | 0.011 |
| Vomiting, n (%) | 3 (3.8) | 10 (12.5) | 4.1 | 0.043 |
| Surgical site infection, n (%) | 1 (1.3) | 7 (8.8) | 4.74 | 0.03 |
| Other complications, n (%) | 0 (0.0) | 0 (0.0) | — | — |
| Any postoperative complication, n (%) | 9 (11.3) | 33 (41.3) | 18.62 | 0.031* |
Note: Data are presented as number (percentage). χ² tests or Fisher’s exact tests were used, as appropriate. “Any postoperative complication” refers to the number of patients who experienced at least one postoperative complication. Because secondary outcomes were interpreted as exploratory, p values for individual complication categories should be interpreted cautiously in the context of multiple comparisons. * Bonferroni-adjusted p value
Recovery results
Recovery outcomes were assessed by length of hospital stay, early mobility, and emotional well-being (HADS). The mean length of hospital stay in the treatment group was 4.2 ± 1.1 days, which was significantly shorter than 5.7 ± 1.4 days in the control group (p < 0.001, Fig. 5A). In terms of early mobility, the mean time to first successful sitting, standing, or walking was longer in the intervention group than in the control group (16.4 ± 4.2 h vs. 12.3 ± 3.5 h; p = 0.02; Fig. 5B). Because a shorter time indicates earlier mobilization, this finding did not support an improvement in early mobility in the intervention group. This result was therefore interpreted cautiously and discussed as an inconsistent finding. HADS-Anxiety and HADS-Depression scores were analyzed separately using repeated-measures ANOVA. For HADS-Anxiety, the intervention group scores were 7.6 ± 2.3 preoperatively, 5.8 ± 2.1 at 24 h, and 5.0 ± 1.8 at 72 h, whereas the control group scores were 7.8 ± 2.4, 7.1 ± 2.2, and 6.6 ± 2.1, respectively. The group × time interaction was significant (F = 6.9, p = 0.002). For HADS-Depression, the intervention group scores were 6.7 ± 2.1 preoperatively, 4.7 ± 1.9 at 24 h, and 4.2 ± 1.7 at 72 h, whereas the control group scores were 6.8 ± 2.2, 6.3 ± 2.0, and 5.8 ± 1.9, respectively. The group × time interaction was also significant (F = 5.8, p = 0.004). These findings suggest that the intervention was associated with more favorable emotional well-being trajectories over time (Fig. 5C). The repeated-measures outcomes for VAS pain scores, MMSE scores, HADS-Anxiety scores, and HADS-Depression scores are summarized in Table 3.
Fig. 5.
Comparison of recovery-related outcomes between the two groups. (A) Length of hospital stay. (B) Time to first mobilization; a shorter time indicates earlier mobilization. (C) HADS-Anxiety and HADS-Depression scores. * p < 0.05, ** p < 0.01, *** p < 0.001 vs. control group
Table 3.
Repeated-measures outcomes
| Outcome | Time point | Intervention group (n = 80) | Control group (n = 80) | Group × time p |
|---|---|---|---|---|
| VAS pain score | 6 h | 5.1 ± 1.7 | 6.0 ± 1.8 | < 0.001 |
| VAS pain score | 24 h | 3.2 ± 2.1 | 5.6 ± 2.5 | |
| VAS pain score | 48 h | 2.1 ± 1.4 | 3.9 ± 1.8 | |
| VAS pain score | 72 h | 1.3 ± 0.9 | 2.5 ± 1.3 | |
| MMSE score | Preoperative | 27.9 ± 1.4 | 28.0 ± 1.5 | < 0.001 |
| MMSE score | 24 h | 27.1 ± 1.6 | 26.3 ± 1.9 | |
| MMSE score | 72 h | 28.4 ± 1.2 | 27.3 ± 1.6 | |
| HADS-Anxiety | Preoperative | 7.6 ± 2.3 | 7.8 ± 2.4 | 0.002 |
| HADS-Anxiety | 24 h | 5.8 ± 2.1 | 7.1 ± 2.2 | |
| HADS-Anxiety | 72 h | 5.0 ± 1.8 | 6.6 ± 2.1 | |
| HADS-Depression | Preoperative | 6.7 ± 2.1 | 6.8 ± 2.2 | 0.004 |
| HADS-Depression | 24 h | 4.7 ± 1.9 | 6.3 ± 2.0 | |
| HADS-Depression | 72 h | 4.2 ± 1.7 | 5.8 ± 1.9 |
Note: Values are presented as mean ± standard deviation. Repeated-measures ANOVA was used to evaluate time, group, and group × time effects. The group × time p value indicates whether the outcome trajectory differed between the intervention and control groups over time. VAS, Visual Analog Scale; MMSE, Mini-Mental State Examination; HADS, Hospital Anxiety and Depression Scale
Quality of life was assessed using the SF-36 score before discharge. The intervention group had a higher SF-36 total score than the control group (76.8 ± 8.7 vs. 69.5 ± 9.4; mean difference, 7.3; 95% CI, 4.5–10.1; adjusted p < 0.001). The proportion of patients with an SF-36 score ≥ 70 was also higher in the intervention group than in the control group (59/80, 73.8% vs. 43/80, 53.8%; p = 0.009). Because the cut-off value of 70 was used descriptively rather than diagnostically, the raw SF-36 scores were used for the main between-group comparison.
Univariate and multivariate analysis of factors associated with overall outcomes
Univariate and multivariate logistic regression analyses were performed to evaluate factors associated with postoperative complications. After adjustment for age, sex, BMI, type of surgical procedure, anesthesia duration, anesthetic agents, preoperative sedative use, comorbidities, preoperative HADS-Anxiety and HADS-Depression scores, and baseline SF-36 score, the integrated evidence-based and proactive nursing intervention was associated with lower odds of postoperative complications compared with routine nursing care (adjusted OR = 0.28; 95% CI, 0.12–0.65; p = 0.003; Table 4). Longer anesthesia duration was also associated with higher odds of postoperative complications. No undefined symbols or question marks were retained in the table, and all reference categories were specified.
Table 4.
Univariate and multivariate logistic regression analysis of factors associated with postoperative complications
| Variable | Univariate OR (95% CI) | p value | Multivariate OR (95% CI) | p value |
|---|---|---|---|---|
| Age, per 1-year increase | 1.03 (1.00–1.06) | 0.061 | 1.02 (0.99–1.06) | 0.138 |
| Male sex | 1.12 (0.58–2.16) | 0.736 | 1.08 (0.52–2.23) | 0.837 |
| BMI, per 1 kg/m² increase | 1.04 (0.94–1.15) | 0.438 | 1.03 (0.92–1.15) | 0.624 |
| Anesthesia duration, per 10-min increase | 1.15 (1.02–1.29) | 0.021 | 1.13 (1.00–1.28) | 0.049 |
| Surgical procedure type | ||||
| General surgery | Reference | — | Reference | — |
| Orthopedic surgery | 1.18 (0.54–2.59) | 0.679 | 1.11 (0.48–2.56) | 0.812 |
| Gynecological surgery | 0.94 (0.38–2.32) | 0.897 | 0.91 (0.34–2.42) | 0.849 |
| Urological surgery | 1.21 (0.41–3.57) | 0.728 | 1.16 (0.36–3.75) | 0.804 |
| Propofol-based anesthesia | 0.82 (0.27–2.47) | 0.724 | 0.88 (0.27–2.87) | 0.831 |
| Sevoflurane use | 1.19 (0.56–2.53) | 0.654 | 1.14 (0.50–2.60) | 0.755 |
| Opioid analgesic use | 1.28 (0.25–6.51) | 0.766 | 1.21 (0.21–6.91) | 0.83 |
| Preoperative sedative use | 1.34 (0.61–2.96) | 0.466 | 1.29 (0.54–3.07) | 0.567 |
| Any comorbidity | 1.86 (0.96–3.61) | 0.066 | 1.64 (0.79–3.41) | 0.185 |
| Preoperative HADS-Anxiety score, per 1-point increase | 1.18 (1.03–1.36) | 0.019 | 1.14 (0.98–1.33) | 0.091 |
| Preoperative HADS-Depression score, per 1-point increase | 1.11 (0.96–1.29) | 0.151 | 1.05 (0.89–1.25) | 0.557 |
| Baseline SF-36 score, per 1-point increase | 0.96 (0.93–0.99) | 0.012 | 0.97 (0.94–1.01) | 0.123 |
| Integrated evidence-based and proactive nursing | 0.27 (0.12–0.59) | 0.001 | 0.28 (0.12–0.65) | 0.003 |
Note: The outcome variable was the occurrence of any postoperative complication. Values are presented as odds ratios and 95% confidence intervals. The multivariate model included age, sex, BMI, type of surgical procedure, anesthesia duration, anesthetic agents, preoperative sedative use, comorbidities, preoperative HADS-Anxiety score, preoperative HADS-Depression score, baseline SF-36 score, and group allocation. General surgery and routine nursing care were used as reference categories where applicable. OR, odds ratio; CI, confidence interval; BMI, body mass index; HADS, Hospital Anxiety and Depression Scale; SF-36, 36-item Short Form Health Survey
Discussion
This quasi-experimental study compared the intervention and control groups across several postoperative outcomes, including patient satisfaction, complication rates, pain management, and cognitive function recovery. The results indicated that the intervention group experienced more favorable outcomes in terms of satisfaction, pain relief, and complication control. The trajectory of MMSE scores also appeared better in the intervention group. However, the absolute differences were small, and the follow-up period was limited to the short-term postoperative phase. Therefore, these cognitive findings should be considered exploratory rather than definitive evidence of a direct protective effect on cognitive function. Notably, the intervention group showed more favorable trends over time in both pain scores and MMSE scores. Nevertheless, given the quasi-experimental design, all findings should be interpreted as associations rather than causal effects. The incidence of complications—particularly nausea, vomiting, and surgical site infection—was lower in the intervention group. This association remained significant after adjustment for selected baseline and clinical variables, although residual confounding cannot be entirely ruled out. Overall, the integrated nursing intervention may be associated with improved postoperative recovery and could serve as a useful structured care strategy for patients undergoing surgical anesthesia. However, because this was not a randomized controlled trial, the observed differences must be interpreted with caution and should not be taken as definitive proof of causality.
The significant reduction in pain scores within the intervention group may be attributable to more effective pain management measures. Postoperative pain control typically involves multiple mechanisms, including pharmacological analgesia, physical therapy, and psychological interventions [12]. The intervention group may have achieved enhanced analgesic effects through a comprehensive regimen, such as precise dose titration, use of patient-controlled analgesia pumps, and application of local anesthetics. Existing studies have shown that the timeliness and accuracy of postoperative pain management are key determinants of recovery speed [13]. Furthermore, the intervention group adopted a more personalized pain management protocol, which may have contributed to faster pain relief. For example, nurses assessed individual pain thresholds and adjusted drug types and dosages accordingly to ensure timely and effective control [14]. In contrast, the control group received standard care protocols that were not tailored to individual patient needs, which may explain its less favorable pain outcomes.
Cognitive function recovery is an important postoperative indicator. Research suggests that cognitive decline occurring within 24 to 72 h after surgery is strongly associated with anesthetic drug effects, postoperative inflammatory responses, and individual patient characteristics [15]. The gradual improvement in cognitive function scores observed in the intervention group may be related to a more refined anesthesia management strategy and earlier postoperative interventions. Specifically, the intervention group implemented early cognitive function monitoring and adjusted nursing plans in real time based on patients’ cognitive status. Studies have shown that the incidence of postoperative cognitive dysfunction is closely linked to preoperative and postoperative care quality, anesthetic dosage, and patients’ baseline cognitive function [16]. The intervention group adopted a more meticulous and individualized approach to anesthetic selection and dosing, thereby potentially reducing the risk of cognitive decline. In addition, the group strengthened early postoperative cognitive training through timely environmental stimulation and communication with patients, which may have promoted brain function recovery. This finding aligns with existing literature suggesting that early postoperative cognitive activation helps reduce the extent of cognitive impairment [17].
The incidence of postoperative complications was significantly lower in the intervention group, especially for nausea, vomiting, and surgical site infection. Complication control involves multiple factors, including effective antibiotic use, postoperative nursing interventions, and nutritional support. In terms of infection control, the intervention group may have implemented stricter aseptic techniques and wound care measures, thereby reducing infection rates. Research indicates that postoperative infection control is closely associated with nursing staff’s operational standards, surgical incision cleanliness, and patients’ postoperative immune responses [18]. Moreover, the intervention group may have reduced complications through earlier mobilization and breathing exercises. For instance, deep breathing and coughing training soon after surgery can help prevent pulmonary infections [19]. For nausea and vomiting, the intervention group may have used more effective antiemetic agents, such as 5-HT3 receptor antagonists, which have proven efficacy in reducing postoperative nausea and vomiting [20]. The control group, by contrast, may have relied solely on standard drug therapy without individualizing treatment, leading to higher complication rates.
The present findings are consistent with existing literature showing that refined postoperative care and pain management can significantly enhance patient recovery. Multiple studies have demonstrated that effective postoperative pain control not only reduces patient discomfort but also promotes early recovery and reduces complications [21]. For example, Fang et al. reported that personalized pain management programs significantly lowered postoperative pain scores and improved quality of life [22]. Regarding cognitive recovery, the literature indicates that anesthetic drug selection, early postoperative cognitive training, and psychological interventions have meaningful impacts [23]. In this study, the intervention group showed higher MMSE scores over time, which may be attributed to more structured postoperative assessments, emotional support, and early cognitive engagement. However, repeated MMSE administration at 24 and 72 h postoperatively may have introduced practice effects; therefore, these MMSE findings should be interpreted cautiously. They indicate an association between the intervention and MMSE trajectories, not definitive evidence of directly improved cognitive function. Regarding complication control, our results are also highly consistent with other studies, which have shown that the occurrence of postoperative complications is closely related to early intervention, care quality, and medication use [24]. The intervention group’s strict nursing measures—particularly in infection control and nausea/vomiting management—substantially reduced complication rates, aligning with the conclusions of prior research.
Contamination between groups is a major concern in nursing intervention studies, especially when patients are treated in the same hospital setting and nursing staff may exchange information about care procedures. In this study, several strategies were employed to minimize contamination, including assigning different nursing staff to each group whenever possible, providing separate training for intervention nurses, restricting intervention materials to the intervention group, and separating data collection from intervention delivery. Nevertheless, contamination could not be completely eliminated due to the shared institutional environment. Any residual contamination may have diluted the true difference between groups or introduced bias into patient-reported outcomes.
One inconsistent finding emerged regarding early mobility. The intervention group had a longer mean time to first sitting, standing, or walking compared with the control group. Because a shorter time indicates earlier mobilization, this result does not support a beneficial effect of the intervention on early mobility. Several explanations are possible. First, nurses in the intervention group may have applied more cautious, individualized assessments before mobilizing patients, particularly those with pain, dizziness, or drainage tubes. Second, differences in surgical complexity, anesthesia duration, or postoperative physical condition may have influenced mobilization timing. Third, as this was a quasi-experimental study, unmeasured baseline differences may have affected this outcome. Therefore, the early mobility finding should be interpreted with caution and should not be presented as uniformly favorable to the intervention.
This study has several limitations. First, the quasi-experimental design limits causal inference; all findings should be interpreted as associations rather than definitive evidence of intervention effectiveness. Second, the absence of random sequence generation and allocation concealment—participants were assigned via a non-randomized sequential process—may have introduced selection bias, temporal bias, or unmeasured baseline imbalance, despite the apparent comparability of measured characteristics. Although multivariable adjustment was performed for selected covariates, residual confounding cannot be excluded. Third, full blinding of participants and nursing staff was not feasible due to the nature of the intervention, which may have led to performance bias, response bias, or detection bias. Fourth, despite measures to reduce contamination, it could not be completely ruled out because both groups were treated in the same hospital. Fifth, patients underwent different types of surgical procedures; heterogeneity in surgical complexity, anesthesia exposure, and postoperative recovery trajectories may have influenced outcomes. Sixth, repeated MMSE assessments at 24 and 72 h postoperatively may have introduced practice effects. Such effects are well documented: patients who take the same or similar tests multiple times often show improved scores due to familiarity with test items, reduced test anxiety, or recall of previous responses, rather than genuine cognitive recovery. Both groups were exposed to repeated testing, so practice effects likely affected both to some degree. However, if the intervention group received more frequent cognitive engagement or emotional support, they might have benefited more from practice effects, potentially exaggerating the apparent between-group difference in MMSE trajectories. Consequently, the higher MMSE scores observed in the intervention group should not be interpreted as definitive evidence of superior cognitive recovery. Future randomized trials should consider using alternate cognitive test versions, longer washout periods, or objective biomarkers of cognitive function to separate intervention effects from practice effects. Seventh, multiple outcomes were assessed; although Bonferroni correction was applied to key secondary outcome comparisons, these analyses should still be considered exploratory, and statistically significant findings should not be overinterpreted as confirmatory. Eighth, the single-center design may limit generalizability to other hospitals or patient populations. Finally, the study did not evaluate long-term recovery outcomes, so the durability of the observed associations remains uncertain. Future research should therefore adopt larger, multicenter randomized designs with rigorous sequence generation, allocation concealment, blinded outcome assessment where feasible, predefined primary outcomes, appropriate adjustment for multiple comparisons, and longer follow-up to confirm these findings.
Future research should also focus on tailoring postoperative care and treatment plans to individual patient characteristics—such as age and baseline health status—thereby further personalizing postoperative nursing and providing more targeted guidance for clinical practice.
Conclusion
The integrated evidence-based and proactive nursing protocol was associated with higher postoperative satisfaction, lower pain scores, and fewer complications than routine nursing. The intervention group also showed a more favorable short-term MMSE trajectory, but this finding is tentative due to modest differences, 72-hour follow-up, and potential practice effects. While these results suggest potential value for postoperative management, cautious interpretation is required given the quasi-experimental design, incomplete blinding, potential contamination, surgical heterogeneity, multiple outcomes, and inconsistent mobility results. Future randomized trials with rigorous methods and longer follow-up are needed to confirm effectiveness and generalizability.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
We are particularly grateful to all the people who have given us help on our article.
Abbreviations
- EBN
Evidence-based nursing
- MMSE
Mini-mental state examination
- VAS
Visual analog scale
- PSQ-18
Patient satisfaction questionnaire
- HADS
Hospital anxiety and depression scale
Author contributions
Li Weng: guarantor of integrity of the entire study, study concepts, study design, manuscript preparation, editing and review. Xue-Feng Zhang: definition of intellectual content, experimental studies, data acquisition. Guo-Lan Yi: literature research, clinical studies. Hua-Yong Xie: data analysis, statistical analysis. All authors read and approved the final draft.
Funding
No external funding received to conduct this study.
Data availability
All data generated or analysed during this study are included in this article. Further enquiries can be directed to the corresponding author.
Declarations
Ethics approval and consent to participate
The study was conducted in accordance with the Declaration of Helsinki (as was revised in 2013). The study was approved by Ethics Committee of Fushun People’s Hospital (Approval Number: WYZ2023-KY-058-02). Written informed consent was obtained from all participants.
Consent to publish
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Bowyer A, Royse C. The importance of postoperative quality of recovery: influences, assessment, and clinical and prognostic implications. Can J Anaesth. 2016;63(2):176–83. 10.1007/s12630-015-0508-7. [DOI] [PubMed] [Google Scholar]
- 2.Ramirez MF, Cata JP. Anesthetic care influences long-term outcomes: What is the evidence? Best Pract Res Clin Anaesthesiol. 2021;35(4):491–505. 10.1016/j.bpa.2021.01.004. [DOI] [PubMed] [Google Scholar]
- 3.Connor L, Dean J, McNett M, et al. Evidence-based practice improves patient outcomes and healthcare system return on investment: Findings from a scoping review. Worldviews Evid Based Nurs. 2023;20(1):6–15. 10.1111/wvn.12621 [DOI] [PubMed] [Google Scholar]
- 4.Younas A, Quennell S. Usefulness of nursing theory-guided practice: an integrative review. Scand J Caring Sci. 2019;33(3):540–55. 10.1111/scs.12670. [DOI] [PubMed] [Google Scholar]
- 5.Tazreean R, Nelson G, Twomey R. Early mobilization in enhanced recovery after surgery pathways: current evidence and recent advancements. J Comp Eff Res. 2022;11(2):121–9. 10.2217/cer-2021-0258. [DOI] [PubMed] [Google Scholar]
- 6.Yeoh EK, Wong MCS, Wong ELY, et al. Benefits and limitations of implementing Chronic Care Model (CCM) in primary care programs: A systematic review. Int J Cardiol. 2018;258:279–88. 10.1016/j.ijcard.2017.11.057. [DOI] [PubMed] [Google Scholar]
- 7.Al Danaf J, Chang BH, Shaear M, et al. Surfacing and addressing hospitalized patients’ needs: Proactive nurse rounding as a tool. J Nurs Manag. 2018;26(5):540–7. 10.1111/jonm.12580. [DOI] [PubMed] [Google Scholar]
- 8.Schulz KF, Altman DG, Moher D. CONSORT 2010 statement: Updated guidelines for reporting parallel group randomised trials. J Pharmacol Pharmacother. 2010;1(2):100–7. PMID: 21350618; PMCID: PMC3043330. 10.4103/0976-500X.72352. PMID: 21350618; PMCID: PMC3043330. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Faul F, Erdfelder E, Lang AG, Buchner A. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007;39(2):175 – 91. 10.3758/bf03193146. PMID: 17695343. [DOI] [PubMed]
- 10.Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Hillsdale, NJ: Lawrence Erlbaum Associates; 1988. [Google Scholar]
- 11.Marshall GN, Hays RD. The patient satisfaction questionnaire short-form (PSQ-18). Santa Monica, CA: Rand; 1994. [Google Scholar]
- 12.Sampognaro G, Harrell R. Multimodal postoperative pain control after orthopaedic surgery. StatPearls. Treasure Island (FL). StatPearls Publishing. 2023:29. [PubMed]
- 13.Jaensson M, Nilsson U, Dahlberg K. Methods and timing in the assessment of postoperative recovery: a scoping review. Br J Anaesth. 2022;129(1):92–103. 10.1016/j.bja.2022.04.015. [DOI] [PubMed] [Google Scholar]
- 14.Guzmán Pavón MJ, Cavero Redondo I, Martínez Vizcaíno V, Ferri Morales A, Lorenzo García P, Álvarez Bueno C. Comparative Effectiveness of Manual Therapy Interventions on Pain and Pressure Pain Threshold in Patients With Myofascial Trigger Points: A Network Meta-analysis. Clin J Pain. 2022;38(12):749–60. 10.1097/AJP.0000000000001079. Published 2022 Dec 1. [DOI] [PubMed] [Google Scholar]
- 15.Li X, Lai H, Wang P, et al. Risk Factors for Postoperative Cognitive Decline After Orthopedic Surgery in Elderly Chinese Patients: A Retrospective Cohort Study. Clin Interv Aging. 2024;19:491–502. 10.2147/CIA.S436349. Published 2024 Mar 19. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Xu X, Chen Z, Gao F. The relationship between postoperative cognitive dysfunction and cerebral small vessel disease: a comprehensive review. J Alzheimers Dis Published online November. 2024;29. 10.1177/13872877241298974. [DOI] [PubMed]
- 17.O’Gara BP, Mueller A, Gasangwa DVI, et al. Prevention of Early Postoperative Decline: A Randomized, Controlled Feasibility Trial of Perioperative Cognitive Training. Anesth Analg. 2020;130(3):586–95. 10.1213/ANE.0000000000004469. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Wen B, Lu Y, Huang X, et al. Influence and risk factors of postoperative infection after surgery for ischemic cardiomyopathy. Front Cardiovasc Med. 2023;10:1231556. 10.3389/fcvm.2023.1231556. Published 2023 Aug 24. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Miskovic A, Lumb AB. Postoperative pulmonary complications. Br J Anaesth. 2017;118(3):317–34. 10.1093/bja/aex002. [DOI] [PubMed] [Google Scholar]
- 20.Heckroth M, Luckett RT, Moser C, Parajuli D, Abell TL. Nausea and Vomiting in 2021: A Comprehensive Update. J Clin Gastroenterol. 2021;55(4):279–99. 10.1097/MCG.0000000000001485. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Chou R, Gordon DB, de Leon-Casasola OA, et al. Management of Postoperative Pain: A Clinical Practice Guideline From the American Pain Society, the American Society of Regional Anesthesia and Pain Medicine, and the American Society of Anesthesiologists’ Committee on Regional Anesthesia, Executive Committee, and Administrative Council [published correction appears in J Pain. 2016;17(4):508 – 10. https://doi.org/10.1016/j.jpain.2016.02.002. Dosage error in article text]. J Pain. 2016;17(2):131–157. 10.1016/j.jpain.2015.12.008. [DOI] [PubMed]
- 22.Fang L, Chen L, Sun H, Xu Y, Jin J. The Effectiveness of Using a Nurse-Led Pain Relief Model for Pain Management among Abdominal Surgical Patients: A Single-Center, Controlled before-after Study in China. Pain Manag Nurs. 2021;22(2):198–204. 10.1016/j.pmn.2020.08.004. [DOI] [PubMed] [Google Scholar]
- 23.Dong Q, Yang Y, Tang Q, et al. Effects of early cognitive rehabilitation training on cognitive function and quality of life in critically ill patients with cognitive impairment: A randomised controlled trial. Aust Crit Care. 2023;36(5):708–15. 10.1016/j.aucc.2022.10.015. [DOI] [PubMed] [Google Scholar]
- 24.Staiger RD, Gerns E, Castrejón Subirà M, Domenghino A, Puhan MA, Clavien PA. Can Early Postoperative Complications Predict High Morbidity and Decrease Failure to Rescue Following Major Abdominal Surgery? Ann Surg. 2020;272(5):834–9. 10.1097/SLA.0000000000004254. [DOI] [PubMed] [Google Scholar]
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Supplementary Materials
Data Availability Statement
All data generated or analysed during this study are included in this article. Further enquiries can be directed to the corresponding author.