Surgical fear and sleep quality effect the postoperative quality of recovery in patients undergoing brain tumor surgery: cross sectional study

Abstract

Background

Patients with a brain tumor experience high levels of anxiety because of the fear of remaining functional and neuropsychological sequelae. This situation affects the postoperative quality of recovery. This study was conducted to determine the effect of surgical fear and sleep quality on the postoperative quality of recovery and pain.

Method

This cross-sectional study was completed with 101 patients who met the inclusion criteria and underwent craniotomy under general anesthesia for a brain tumor between October 2020 and August 2021 in a university hospital. The data were collected using the Patient Information Form, Surgical Fear Scale, Richard Champell Sleep Scale, Quality of Recovery Questionnaire, and Patient Follow-up Form. Hierarchical regression analysis was used to reveal the determinants of postoperative quality of recovery.

Results

The mean fear of surgery score of women was higher than men, and sleep quality and postoperative quality of recovery were lower than men (p = 0.045). A moderate negative correlation between fear of surgery and sleep quality was found (r = -0.377; p = 0.000). There was a weak negative correlation between fear of surgery and postoperative recovery quality (r = -0.252; p = 0.011), and a weak positive correlation between preoperative sleep quality and recovery quality (r = 0.297; p = 0.003). The variables of fear, sleep, duration of hospital stay, pain, and age were found to be statistically the best predictors of postoperative quality of recovery (R2 = 0.295; p = 0.000).

Conclusion

As a result, surgical fear, sleep deprivation, and pain during the perioperative period negatively impact recovery quality and prolong the healing process. Psychological preparation by starting from the pre-operative period, providing sleep and rest, evaluation, and management of postoperative pain would contribute to the early recovery and discharge of patients.

Introduction

The vast majority of brain tumors show invasive spread and malignant features and grow rapidly in a limited area, such as the skull. Brain tumors create many symptoms in individuals, rapidly reducing the quality of life and threatening life (Correia et al 2021). The most common symptoms include cognitive impairment, headache, memory loss, nausea, speech disorders, aphasia-dysphasia, motor disorders, and seizures (Kos et al 2016). Although treatment methods such as chemotherapy and immunotherapy are widely used in the treatment of brain tumors, surgery continues to be the first-line treatment in this patient group (De La Garze Ramos et al., 2016). Surgical procedures themselves can cause neurological sequelae and therefore have risks (Correia et al 2021).

Patients with brain tumors experience high levels of anxiety because of the fear of remaining functional and neuropsychological sequelae and experiencing neurological symptoms after tumor surgery (Valencia et al. 2022; Oteri et al. 2021). Studies conducted on neurosurgery patients indicate that patients who undergo surgery experience high levels of anxiety and worry about mental loss and the negative consequences of the surgery (Perks et al. 2009; Goebel & Mehdorn 2018). At the same time, it has been reported that preoperative anxiety is an important determinant of postoperative pain in patients undergoing neurosurgery (Valencia et al., 2022), negatively affecting the quality of life and general health of patients (Oteri et al. 2021).

Emotional factors, such as stress and fear experienced in the preoperative period also reduce the sleep quality of the individual. However, in this process, the individual also experiences a deterioration in sleep quality because of factors such as a new environment, noise, painful and uncomfortable diagnosis, treatment procedures associated with hospitalization, and medical devices (Yanık & Altun Uğraş, 2020; Mouch et al. 2020). In a study of patients undergoing elective surgery, 93% of patients had sleep problems compared to their home, and the disruption in sleep patterns was caused by the noise of roommates and nurses entering the room at night (Mouch et al. 2020).

Fear of surgery and deterioration in sleep quality negatively affect post-operative recovery (Kehlet 2018; Şara et al 2022). The stress response that develops due to fear causes more anesthetic substance use during the surgery, decreases the brink of pain, causes more analgesic use after the surgery, increases postoperative complications, and delays recovery (Stamenkovic et al. 2018; Michaelides and Zis 2019). In addition, the deterioration in sleep quality experienced with fear causes deterioration in the homeostatic functions of the individual, increased response to pain, weakened immune system, delayed recovery, and longer hospital stays (Su &Wang, 2018; Luo et al. 2019).

Studies indicate that patients who undergo cranial surgery experience high levels of anxiety (Goebel & Mehdorn 2018) and that patients are worried about the negative consequences of the surgery, such as possible physical or mental loss in the postoperative period (Perks et al. 2009; Valencia et al. 2022). In the literature review, no study was found that examined the effects of surgical fear, sleep quality, post-operative recovery quality, and pain in patients who underwent brain tumor surgery. For this reason, this study intended to detect the effect of surgical fear and sleep quality on postoperative quality of recovery and pain in patients undergoing brain tumor surgery.

Research hypotheses were:

• Preoperative surgical fear and sleep quality affect postoperative pain and postoperative recovery quality

• Preoperative surgical fear, sleep quality, and postoperative pain are the determinants of postoperative recovery quality

Methods

Design

This study was conducted as a descriptive and cross-sectional study. The Strengthening the Reporting Observation Studies in Epidemiology (STROBE) checklist was used in reporting the study (Supplementary File).

Participants

The population of the study consisted of 148 patients in the neurosurgery clinic of a university hospital between October 2020 and August 2021 who underwent brain tumor surgery. This study ended with 101 patients who met the inclusion criteria and volunteered to participate in the study (Fig. 1). The sufficiency of the sample was determined according to the Post-Hoc power analyses. The effect size was obtained as 0.54 by using the correlation coefficient between the Richard Champell Sleep Scale and the Recovery Quality Questionnaire. When the Type I error was 5% and the sample size was 101, the post hoc power was 99% (Kang 2021).

Fig. 1

The universe and sample of the study

The population of the study consists of individuals who meet the inclusion criteria: (1) Those who are over 18 years old and have no communication problems; (2) preoperative and postoperative Glasgow coma score of 14 and above; (3) no psychiatric disease and no psychiatric drugs; (4) voluntarily agreeing to participate in the study; (5) patients undergoing elective surgery. (6) patients who were in the preoperative period and had spent 24 h postoperatively; (7) patients with scores I and II in the American Society of Anesthesiologists (ASA) scoring were included (Li et al 2021).

The study ending criteria are as follows; (1) patients who were included in the preoperative sampling and did not undergo surgery; (2) patients who were included in the preoperative sampling and who developed postoperative exitus; (3) when complications affecting communication such as aphasia develop after surgery.

Surgery and anesthesia

All patients underwent surgery under general anesthesia. Fentanyl, rocuronium bromide, and propofol were used to provide anesthesia. 8 patients underwent craniotomy (tumor excision with neuronavigation and duraplasty) due to meningioma, 84 patients underwent craniotomy (tumor excision with neuronavigation and duraplasty) due to brain tumor, and 10 patients underwent transsphenoidal mass excision with neuronavigation due to pituitary adenoma.

Data collection instruments

Data were obtained using the Patient Information Form, the Surgical Fear Questionnaire, the Richard Champell Sleep Scale, the Quality of Recovery Questionnaire (QOR-40), and the Numerical Pain Scale.

Patient information form

The questionnaire form, which was created by scanning the literature (Kaya & Özlü, 2019; Bağdiğen & Özlü, 2018), consists of 16 questions including the socio-demographic characteristics of the patients (age, gender, place of residence, etc.), the duration of the surgery, the duration of the intensive care unit, the ASA score, the Glasgow Coma Scale (GCS) score, and the surgical experience.

Surgical Fear Questionnaire (SFQ)

Theunissen et al. created the questionnaire in 2014 to reveal the level of surgical fear in patients undergoing elective surgery (Theunissen et al. 2014). The reliability and validity of its Turkish version were made by Bağdigen and Özlü in 2018 (Bağdigen & Özlü, 2018). The questionnaire, which is designed as an 11-point Likert scale, consists of eight items, and is scored between 0 and 10 (0 not afraid at all; 10 very afraid). The scale consists of two sub-dimensions regarding the source of fear, each consisting of four items. Items 1–4 in the questionnaire measure the fear of the short-term results of surgery (SFQ-S), while items 5–8 measure the fear of the long-term results of surgery (SFQ-L). The questionnaire total score is 0 at the lowest and 80 at the highest. A higher score indicates a higher level of fear. The Cronbach's alpha value of the adapted scale was found to be 0.93 (Bağdıgen & Özlü, 2018). In our study, Cronbach's alpha value was found to be 0.98.

Richard champell sleep scale

Developed by Richards et al., the scale consists of 6 items (Richards et al. 2000). Özlü and Özer performed the Turkish reliability and validity study in 2015 (Özlü & Özer 2015). In the scale, patients are asked to evaluate between 0 and 100 points for each item. The 6th item, which evaluates the noise level in the environment, is not included in the total score evaluation. The result is obtained by dividing the total point obtained from the scale by the number of questions, “0–25” points demonstrate “very bad sleep", and "76–100" points demonstrate "very good sleep". A minimum of zero and a maximum of 100 points can be collected from the scale. An increase in the score demonstrates an increase in sleep quality. The Cronbach’s alpha value of the scale is 0.91 (Özlü & Özer 2015). In our study, Cronbach's alpha value was found to be 0.93.

Quality of Recovery Questionnaire (QOR-40)

The questionnaire consisting of 40 items was developed by Myles in 2000, and its validity and reliability were determined by Karaman et al. in 2014 (Myles et al. 2000; Karaman et al. 2014). The questionnaire has five sub-dimensions: comfort (12 items), emotions (9 items), physical dependence (5 items), patient support (7 items), and pain (7 items). Each item is evaluated from one to five (never, sometimes, usually, often, and always). Negative statements on the scale are scored by reversing (Myles, 2000). The score obtained from the scale varies between 40 and 200. As the score increases, the quality of recovery increases (Karaman et al. 2014). While Cronbach's alpha coefficient was 0.936 in the original study, it was 0.908 in our study..

Numerical pain scale

Patients are asked to choose the number that best describes their pain intensity. While zero indicates no pain, 10 represents the worst pain imaginable (Yeşilyurt & Beneficial, 2020).

Data collection

Data were obtained by the face-to-face interview method. On the morning of the surgery day, the Patient Information Form, SFQ, and Richard Champell Sleep Scale were filled in. The patient's hospitalization date, surgery date, ASA, and GCS score were recorded from the patient's file by the researcher. 24 h after the operation, the duration of the operation, the duration of the intensive care unit stay, the GCS score, and the pain score were recorded. After discharge planning, the patient was asked to fill out the quality of recovery questionnaire.

Ethical statements

Ethics Committee Permission from XXX University Clinical Research Ethics Committee (Decision No: 2020/438) and institutional permission from XXX University Health Application and Research Center Directorate was obtained. Besides, verbal and written consent was obtained from the individuals participating in the research. The information was given to the patients verbally by the researcher (ÖÇ), who is also a neurosurgery nurse. The data is stored in a computer environment by the same researcher. The ethical principles specified in the Declaration of Helsinki were followed throughout the research.

Data analysis

Data were analyzed with SPSS 24.0 (IBM Corp., Armonk, United States). The suitability of the data to the normal dispersion was determined by the Shapiro–Wilk test, Q-Q graph, and Skewness-Kurtosis values. Student's t-test was used to compare two groups and a one-way analysis of variance was performed to compare more than two groups for normally distributed data. Mann–Whitney U test was performed to compare two groups, and Kruskal Wallis analysis was performed to compare two or more groups for data not normally distributed. In the evaluation of the relationship between the scales, Pearson correlation and Spearman correlation analysis were used. The correlation coefficient was interpreted as 0.00–0.10 insignificant correlation, 0.10–0.39 weak correlation, 0.40–0.69 moderate correlation, 0.70–0.89 strong correlation, 0.90–1.00 very strong correlation. (Schober et al 2018). Hierarchical regression analysis was done to reveal the determinants of postoperative quality of recovery. In all results, p < 0.05 was considered statistically significant. Consultation was received from the university's statistics unit.

Results

It was found that 66.3% of the patients were 41–63 years old, and the mean age was 50.95 ± 14.21. 54.5% of the individuals are women, 81.2% are married, and 58.4% live in the city. 34.7% of the patients have chronic diseases and 51.4% have hypertension. 72.3% of the patients were hospitalized at least once and 67.3% had surgery. 21.8% of the patients had a previous neurosurgery experience (Table 1).

Table 1 Descriptive characteristics of the patients (n = 101)

The sleep scale mean score of the patients was 50.63 ± 25.00 and 59.4% of them slept well. The mean SFQ score of the patients was 38.45 ± 26.17. Patients' mean postoperative QoR-40 score was 103.03 ± 16.07 (Table 2).

Table 2 Surgical fear, sleep and quality of recovery scales total score and subscale scores

While there was no difference between the SFQ and sleep scale mean scores and the age groups, the QoR-40 mean score was higher in patients who were 64 years old and over (p = 0.044). The preoperative SFQ mean scores of the women were higher (p = 0.045) and the QoR-40 and sleep scale mean scores were lower than the men (p = 0.035) (Table 3).

Table 3 The mean score of the SFQ, sleep scale and QOR-40 according to the descriptive characteristics of the patients (n = 101)

A weak negative correlation was detected between preoperative SFQ and postoperative QoR-40 scores (r = −0.252; p = 0.011). As the fear of surgery increases, the quality of recovery decreases. A moderate negative correlation was found between preoperative SFQ and sleep scale scores (r = −0.377; p = 0.000). As the SFQ scores increase, sleep scale scores decrease. There was a weak positive correlation between preoperative sleep scale scores and postoperative QoR-40 scores (r = 0.297; p = 0.003). As the sleep scale scores and sleep quality increase, the postoperative QoR-40 scores increase (Table 4).

Table 4 The relationship between SFQ, the QOR-40, sleep scale mean score of patients and some surgical process parameters

A moderate negative correlation was detected between postoperative QoR-40 score and pain level (r = −0.460; p = 0.000). As the level of pain increases, the QoR-40 score decreases. A moderate and negative relationship was determined between preoperative sleep scale scores and postoperative pain (r = −0.367; p = 0.000). As sleep scale scores increase, pain level decreases (Table 4).

A moderate positive correlation was found between the duration of postoperative hospital stay and the QoR-40 scores (r = −0.460; p = 0.000), and a moderate positive correlation between the duration of postoperative hospital stay and the duration of intensive care unit stay (r = 0.464; p = 0.000). As the duration of postoperative hospital stay increases, the QoR-40 scores decrease, and as the duration of intensive care unit stay increases, the duration of postoperative hospital stay increases. In addition, as the duration of surgery increases, the duration of intensive care unit stays increases (r = 0.364; p = 0.000) (Table 4).

In Table 5, the determinants of post-operative QoR-40 were analyzed using the hierarchical regression model. It was explained by the 5th model that the statistically best predictors of postoperative QoR-40 were the variables of SFQ, sleep, duration of hospital stay, pain, and age (R2 = 0.295; p = 0.000). The variables of SFQ, sleep, duration of hospital stay, pain and age explain 29.5% of the postoperative QoR-40. In addition, postoperative pain is the strongest predictor of QoR-40 (β = −0.421, p = 0.000).

Table 5 Determinants of postoperative QOR-40

Discussion

In this study, the preoperative SFQ mean score of women was higher than men. Similarly, in the study of Çelik and Edipoğlu, the anxiety experienced by women in the preoperative period was higher than men, and in the study of Eberhart et al., female gender was a risk factor for preoperative anxiety (Çelik & Edipoğlu 2018; Eberhart et al., 2020). In a study, it was stated that stress-induced anxiety creates different levels and opposite activities in the brain lobes of the two genders, therefore, men and women experience different levels of anxiety due to different use of their neural resources (Seo et al. 2017). In addition, it has been reported that there are differences in regulating neuronal mechanisms involving corticotropin-releasing factors in the two sexes in the stress response (Bangasser & Wierselis, 2018). Besides, women’s emotionality due to fluctuations in estrogen and progesterone hormones may explain the difference in results (Kundakoviç & Rocks, 2022).

In this study, it was found that women's sleep quality was lower. In a study, poor sleep quality and sleep disorders were more common in women than in men, and this was due to sex hormone differences between men and women (Kische et al. 2016). The results of the study are in line with the literature.

In this study, it was found that the post-operative quality of recovery of women was lower than men. There are conflicting results in the literature. Although some studies supporting this study show that the post-operative quality of recovery in women was lower than in men (Jaensson et al., 2019; Dığın & Özkan, 2021), another studyrevealed that there was a significant difference between gender and quality of recovery and women had a higher quality of recovery than men (Rahman et al. 2017). In our study, the responsibilities that our culture imposes on women and the inability to fulfill these responsibilities due to the hospitalization period may have affected the healing process. Besides, the fact that most of the women were housewives and unemployed may have contributed to this result.

It was determined that the QoR-40 mean score was higher in 64-year-olds and over. There was a weak positive correlation between the quality of recovery and age. As age increases, the quality of recovery increases. Besides, there was a weak negative correlation between age and the mean score of fear of surgery. There are conflicting results in the literature concerning the quality of recovery and age. In a study similar to our study, it was stated that 82% of individuals aged 75 and over were not afraid of death due to neurosurgery (Unterhofer et al. 2017). Contrary to our study, advanced age reduced the quality of recovery after colorectal surgery (Shida et al. 2015), in the study of Rahman et al., age affected the quality of postoperative recovery and younger patients had a faster recovery process (Rahman et al., 2017). As age increased, individuals' familial, social, and economic responsibilities decreased (Öztan Ulusoy 2020). The post-operative quality of recovery of individuals with more responsibility may be affected. In addition, the health literacy of elderly individuals is lower than young people. With the effective use of communication tools, young people are more likely to access bad health news. This may affect the quality of recovery. (Çelik & Edipoğlu 2018).

It is known that high anxiety and fear reduce sleep quality (Gould et al. 2018). The study by Glumac et al. reported that sleep deprivation and deterioration in sleep quality during the perioperative period are a major risk for the development of postoperative cognitive decline, which has negative consequences on patient prognosis and the healthcare system (Glumac et al 2019). In our study, a moderate negative relationship was found between preoperative fear of surgery and sleep, and sleep quality decreased as surgical fear increased. The results of our study show parallelism with the literature. In a study, it was stated that psychological stress impaired sleep quality (Zhang et al. 2020). In another study, it was found that the level of fear of surgery harmed nighttime sleep status in patients awaiting elective surgery (Altun et al. 2017).

A low negative correlation was found between preoperative fear of surgery and postoperative quality of recovery. As the fear of surgery increased, the quality of recovery decreased. In a study similar to ours, anxiety experienced in the preoperative period continued as anxiety, sadness, and depression in the postoperative period and affected the quality of recovery through emotions (Andersson et al. 2020). Likewise, it has been reported that preoperative anxiety levels of patients negatively affected the quality of post-operative recovery (Gümüş, 2021).

In this study, the determinants of postoperative quality of recovery were examined using a hierarchical regression model. The statistically best predictors of postoperative quality of recovery were the variables of fear, sleep, duration of hospital stay, pain, and age. The variables of fear, sleep, duration of hospital stay, pain, and age explained 29.5% of the postoperative quality of recovery. In addition, postoperative pain was the strongest predictor of recovery quality. A moderate negative correlation was found between the quality of postoperative recovery and the level of pain. As the level of pain increased, the quality of recovery decreased. A moderate and negative relationship was determined between preoperative sleep level and postoperative pain. As sleep quality decreased, the level of pain increased. Similar results were found in the literature. In a study, it was stated that the decrease in sleep quality caused an increase in the intensity of pain felt by lowering the pain threshold (Krause et al. 2019). Similarly, another study showed that a decrease in preoperative sleep quality increased postoperative pain (Luo et al. 2019). Surgical interventions threaten the physiological and psychological health of the individual and cause sleep problems. Decreased sleep quality leads to a decrease in the immune system, making individuals vulnerable to infections. Thus, the decrease in sleep quality may lead to a stoppage the recovery, a decrease in quality of life, and an increase in complication rates (Aksu &Erdoğan, 2017). Similar to the literature, in our study, as sleep quality increased, pain level decreased and the quality of postoperative recovery increased.

Conclusion

The results of the study revealed that as the fear of surgery increased, the quality of sleep before surgery and the quality of recovery after surgery decreased. It was revealed that the variables of fear of surgery, sleep quality, length of hospital stay, pain, and age affected the quality of postoperative recovery, and postoperative pain was the strongest predictor of the quality of recovery.

Strengths and limitations of the study

Our study makes an important contribution to the literature, as it is the first study to reveal the factors affecting the quality of recovery after surgery, starting from the preoperative period in patients undergoing surgery for brain tumors. However, the study has some limitations. Since the study covered the pre-and post-operative period, some of the patients included in the preoperative period were excluded from the study due to post-operative complications, and therefore data were lost. Not including patients with a single type of brain tumor in the study may have affected the results. In future studies, factors affecting the recovery process of patients who underwent surgery for the same type of tumor can be investigated. Another important limitation is that postoperative sleep quality was not evaluated. In future studies, post-discharge follow-up, including post-operative sleep quality, is important in terms of evaluating the quality of recovery. Since the study was conducted in the neurosurgery clinic of a single hospital, the results can only be generalized to these patients. Large-scale multicenter studies are needed to confirm our results and provide diagnostic and intervention strategies to improve the quality of recovery of patients after surgery.

Relevance to clinical practice

In order to accelerate the quality of post-operative recovery, psychological preparation by starting from the pre-operative period, providing sleep and rest, evaluation, and management of postoperative pain would contribute to the early recovery and discharge of patients.