Introduction
Pain is an unpleasant sensory and emotional experience associated with actual or potential tissue damage or described in terms of such damage. It is a common symptom in hematopoietic stem cell transplant (HSCT) patients [ 1 ] although its prevalence varies significantly depending on the type of transplant [ 2 ]. One study showed that 50% of autologous HSCT patients reported pain [ 3 ]. Another study, which included both autologous and allogeneic HSCT recipients, showed that 64% of the patients reported moderate to severe pain, while the remaining patients experienced only low levels of pain [ 4 ]. They may experience pre-transplant pain in the acute post-transplant phase, and months or years after HSCT [ 5 ]. Approximately half of the HSCT patients had clinical sleep disturbance as an indicator of physical well-being that might be improved over time [ 6 ]. Sleep disruption is associated with some complications, such as fatigue [ 7 ], stress [ 8 ], and depression symptoms [ 9 ]. On the other hand, improved sleep can enhance recovery, mental well-being, and overall quality of life in patients with HSCT [ 10 ]. Although few studies have been conducted on the pain and sleep quality in HSCT patients, the relationship between sleep quality and pain in HSCT patients has been less reported in the published studies.
Given the probable association between pain and sleep disturbances in HSCT patients, we sought to explore the underlying factors that may influence these symptoms. Prior experience and gender have been identified as the key factors affecting how individuals perceive pain [ 11 ]. In addition, the evaluation of fear and resilience as they relate to pain perception has demonstrated strong psychometric reliability across various groups, offering valuable understanding of the intricate relationship between psychological characteristics and pain responses [ 12 ]. A study showed that resilience improved psychological adjustment [ 13 ], post-traumatic growth [ 14 ], and spirituality in chronic condition [ 15 ]. On the other hand, lower resilience led to a decrease in mental [ 16 ], physical, and social dimensions of quality of life [ 17 ] and increased psychological distress [ 16 ] and anxiety in HSCT patients. Sleep duration was related to resilience in the general population [ 18 ]. Resilience is a protective factor in body image [ 19 ], and its association with body image [ 15 ] and anxiety [ 20 ] was reported in studies on cancer patients. To the best of our knowledge, no study has specifically examined the relationship between resilience and pain or sleep in HSCT patients; however, findings from research in other populations suggest that resilience may influence these symptoms, supporting the need to explore this association in the HSCT context.
Several psychological factors, particularly anxiety, may influence the experience of pain and sleep in HSCT patients. A study reported that pain was associated with anxiety in these patients who had undergone HSCT [ 3 ]. Pain was one of the predictors of anxiety in HSCT patients [ 3 ]. Aggravation of pain was associated with anxiety during the isolation period of HSCT [ 21 ]. More than half of HSCT patients reported moderate levels of state and trait anxiety [ 3 ]. Another study indicated that sleep disturbance affected approximately half of the subjects with anxiety [ 22 ]. Insomnia predicts anxiety and worry in response to stress exposure [ 23 ]. People with higher generalized anxiety disorder had worse sleep quality [ 24 ] although these studies have not been conducted on HSCT patients. Despite these findings, few studies have specifically examined anxiety, —and even fewer have addressed health anxiety, in HSCT patients; to our knowledge, no study has directly explored the associations between anxiety or health anxiety with pain or sleep disturbances in HSCT patients. Moreover, less research was conducted on health anxiety in these patients.
Other studies have been conducted on other psychological variables in HSCT patients. One study showed that more than one-third of HSCT patients were dissatisfied with their body image [ 25 ]. Body image refers to how a person perceives his/her own body. Having positive feelings toward one’s body plays a key role in self-esteem [ 26 ], psychological well-being [ 27 ], and sexual well-being [ 28 ]. Pain acceptance improves body image [ 29 ]. Chronic pain may destroy body image [ 30 ]. One study showed sleep was associated with body image and anxiety [ 31 ]. Although there have been few studies on the relationship between body image, pain, and sleep, these studies have paid less attention to HSCT patients.
A main objective of our study was to explore whether the relationship between pain and sleep quality was influenced by psychological factors such as resilience, health anxiety, and body image in HSCT patients. Our research is informed by the bio-psychosocial model [ 32 , 33 ], which emphasizes that psychological and social dimensions interact with physical health conditions, such as pain, to shape outcomes like sleep quality. Among individuals undergoing HSCT, pain is a common and distressing symptom that can disrupt sleep both directly and indirectly through psychological pathways [ 34 ]. Prior research has indicated the mediating role of resilience in various health-related contexts. For example, a statistically significant and substantial mediating effect of resilience has been found in the relationship between fear of progression and sleep in patients with hematological malignancies [ 35 ]. The mediating effect of resilience has also been shown in the relationship between sleep and well-being in young adults [ 36 ], between sleep and anxiety symptoms [ 37 ], and between sleep and depression in stroke patients [ 38 ]. Furthermore, researchers have indicated that the relationship between sleep and pain might be mediated by emotional distress [ 39 ]. A systematic review supported this by identifying negative mood and affect, depressive and anxiety symptoms, attention to pain, and activation of stress-related systems as mediators of the sleep-pain relationship [ 40 ]. As mentioned, the direct relationship of pain and sleep quality and the mediating role of health anxiety, body image, and resilience in HSCT patients are less well known. Although earlier studies have typically treated sleep as a contributing factor that influences resilience and mental health outcomes, our research takes a different yet theoretically reasonable approach. In patients undergoing HSCT, pain is a common and persistent physical symptom that can challenge emotional coping abilities. We suggest that chronic pain may diminish resilience, which in turn can negatively affect sleep quality. This perspective is consistent with the bio-psychosocial model [ 32 , 33 ], which emphasizes that physical stressors can undermine psychological functioning, ultimately impacting behavioral health outcomes like sleep. Thus, rather than contradicting previous findings, our study expands on them by exploring an alternative, context-specific pathway relevant to the unique experiences of HSCT patients.
We propose that health anxiety, body image perception, and resilience function as mediators in the link between pain and sleep disturbances. Specifically, pain may intensify health anxiety or contribute to negative self-perceptions of the body, both of which can interfere with restful sleep. On the other hand, higher resilience may serve as a protective role, enabling patients to better cope with discomfort and maintain sleep quality. These variables are conceptualized not as moderators that influence the strength of the pain-sleep relationship, but as underlying mechanisms that help explain how pain leads to poor sleep, the core concept of mediation analysis. To promote evidence-based practice, we conducted a study with the following hypotheses:
HSCT patients’ sleep quality as a dependent variable is associated with pain severity, resilience, health anxiety, and body image.
Resilience mediates the relationship between pain severity and sleep quality in HSCT patients. (Fig. 1 )
Health anxiety mediates the relationship between pain severity and sleep quality in HSCT patients. (Fig. 2 )
Body image mediates the relationship between pain severity and sleep quality in HSCT patients (Fig. 3 ).
Resilience, health anxiety, and body iamge mediate the relationship between pain severity and sleep quality in HSCT patients. (Fig. 4 )
Methods
Design
This cross-sectional study was conducted on 210 patients who had undergone HSCT.
Setting
This study was conducted in HSCT center in Motahari clinic affiliated to Shiraz University of Medical Sciences, a major referral center for HSCT in southern Iran.
Sample
The inclusion criteria for this study were passing two months of HSCT, being 18–65 years old, being oriented to time, person and place, and being willing to participate in the study. Exclusion criteria included incomplete completion of the questionnaires and documented psychiatric or neurological disorders that could affect their response. It should be noted that no one was excluded because of the least exclusion criterion.
Sampling
Convenience sampling was used for data collection. The HSCT patients were recruited using convenience sampling by approaching patients who visited the HSCT center in Motahari clinic for their routine physician appointments and met the study criteria. This approach allowed for easy access to eligible individuals during their scheduled visits.
Sample size
Using the “Structural Equation Model Sample Size Calculator” available at Analytics Calculators ( https://www.analyticscalculators.com/calculator.aspx?id=89 ), the required sample size was estimated based on the following parameters: statistical power (1 - β) of 0.90, significance level (α) of 0.05, five latent variables, five observed variables, and an anticipated effect size (R²) of 0.30. The minimum sample size needed to detect the specified effect was calculated to be 188 HSCT participants. Given a potential dropout rate of 10%, the adjusted sample size was estimated to be 207. Ultimately, the data were collected from at least 210 HSCT participants.
Instruments
The data collection instruments in this study were demographic and clinical characteristics, Numeric Rating Scale of Pain, Pittsburgh Sleep Quality Index (PSQI), Connor-Davidson’s Resilience Scale (CD-RISC), Health Anxiety Inventory (HAI), and Body Image Scale.
Basic demographic and clinical data were collected including age, gender, marital status, education levels, disease diagnosis, the length of primary disease, length of the time passed from the HSCT, the number of hospitalization after HSCT, type of HSCT, the family relationship of the transplant donor with the patient, and the patients’ satisfaction.
Numeric Rating Scale of Pain was used. It was scored from 0 (no pain) to 10 (worst pain ever possible), with 1–3 = mild, 4–6 = moderate, and 7–10 = severe. The test-retest result of the scale was 0.94 [ 41 ].
PSQI, which assesses sleep quality, was used. It consists of nine questions. The components of PSQI include subjective sleep quality, sleep latency, sleep duration, sleep efficacy, sleep disturbance, use of sleep medication, and daytime dysfunction. Examples of the items are: “During the past month, what time have you usually gone to bed at night?”, “How long (in minutes) has it usually taken you to fall asleep each night?”, and “How would you rate your sleep quality overall?” In the components, the scores range from 0 to 3. The total score of PSQI is the sum of the scores of all components. It ranges from 0 to 21. Based on the cutoff, a score of < 5 and more than that shows good and poor sleep quality, respectively. The reliability of the Persian version of PSQI was estimated 0.83 and 0.85, using alpha Cronbach [ 42 ].
CD-RISC assesses resilience. It consists of 25 items. Example of the items: “Able to adapt to change”, “Close and secure relationships”, and “Sometimes fate or God can help”. Each item is scored using a 5-point Likert scale with a range of 0 to 4. The total scores range between 0 and 100. Higher scores show more resilience. The internal consistency coefficient of CD-RISC was estimated at 0.89, using Cronbach’s alpha. The convergent validity of CD-RISC with Kobasa’s hardiness questionnaire 2 was approved by a correlation coefficient equal to 0.83, and p < 0001 [ 43 ]. The reliability of CD-RISC, with a Cronbach’s alpha coefficient of 0.89, was approved [ 44 ]. In our study, the Cronbach’s alpha of CD‐RISC was 0.95.
The HAI consists of 18 items. Each item includes individual descriptions of worries/concerns regarding health and disease components, and their reaction if they deal with a serious condition. Examples of the items are: “I worry about my health”, “Compared to other people my age, I notice aches and pains”, and “I am afraid of having a serious illness”. Each item is scored from 0 to 3 points. The total scores range from 0 to 54. A higher score indicates higher health anxiety. Based on the scoring, scores 0 to 25 indicate non-clinical levels of health anxiety. Moreover, ranges 26–32, 33–39, and 40–53 indicate mild, moderate, and substantial pathological health anxiety, respectively. In addition, the score 54 reflects severe health anxiety. Salkovskis et al. reported the internal consistency of HAI as 0.89 [ 45 ]. HAI had good convergent validity by Hypochondriasis Salkovskis et al. [ 45 ]. HAI was translated into the Persian language by back-translation [ 46 ]. In our study, the Cronbach’s alpha of HAI was 0.92.
The Body Image Scale, which consists of 10 items, was developed to assess the change in body image in cancer patients. Examples of the items are: “Have you been feeling self-conscious about your appearance?”, “Have you felt less physically attractive as a result of your disease or treatment?”, and “Have you been dissatisfied with your appearance when dressed?”. The four-point scale ranges from “not at all” = 0 to “very much” = 3. The total score ranges from 0 to 30. Higher scores show a more negative view of body image. The reliability of this scale was reported as 0.93 [ 47 ]. In our study, reliability was obtained 0.81.
Data collection methods
To collect data, the researcher’s assistant attended the HSCT center in Motahari clinic affiliated to Shiraz University of Medical Sciences. After obtaining permission, HSCT patients were selected based on convenience sampling. The instruments were given to the HSCT patients, and they were asked to fill them out. During the data collection process, the research assistant was present with the HSCT patients to help them answer the questions, if necessary. After the data collection, it was entered into SPSS software for analysis.
Data analysis
Data analysis was conducted in SPSS software using descriptive statistics such as mean, standard deviation, frequency, and percentage. The association between the two variables was assessed by Pearson’s correlation coefficient. Based on the results of r-value, 0˗0.19, 0.2 ˗0.39, 0.40 ˗0.59, 0.6 ˗0.79, and 0.8 ˗ 1 are regarded as very weak, weak, moderate, strong, and very strong correlations, respectively. Then, a regression-based approach by Andrew F. Hayes was used to investigate the mediation process analysis. Based on Andrew F. Hayes’ models, in this study, model 4, which reported the mediator effect on one variable, and model 6, which reported the mediators’ effect on three variables at the same time, was used. R, R˗Square, Mean Square Error (MSE), F, and p -value of the model were reported.
Ethical considerations
This study was approved by the Research Ethics Committees of the Schools of Nursing and Midwifery, and Management and Medical Information Science, Shiraz University of Medical Sciences (IR.SUMS.NUMIMG.REC.1402.069, approval date: 2023-09-09). It was conducted based on the Declaration of Helsinki. The data collection on the HSCT patients was conducted anonymously. The written consent form to participate in this study was obtained from the HSCT patients. All the HSCT patients who participated in this study signed the written consent form. We confirm that this written consent form was informed.
Results
The results of this study indicated that the mean age of the HSCT patients was 47.13 (SD = 11.90). As Table 1 shows, 65% of the subjects were male. Moreover, 85% of the patients were married. More than half of the HSCT patients had secondary and high school education. In addition, the length of primary disease was 27.25 (SD = 11.41) months. The length of the time passed from the HSCT was 14.97 (SD = 10.64) months. The number of hospitalizations after HSCT was 1.24 (1.00) times. As Table 1 displays, approximately half of the patients were diagnosed with leukemia before HSCT. Moreover, six patients (5.9%) were not hospitalized at all, and 80 patients (78.4%) were hospitalized once after HSCT. In addition, approximately two-thirds of the HSCT patients strongly agreed and agreed to the conducted HSCT (Table 1 ).
Table 1
The demographic and clinical characteristics of the HSCT patients and their donors and their association with sleep quality, pain severity, resilience, health anxiety, and body image
| Variables | n (%) | Sleep quality | Pain severity | Resilience | Health anxiety | Body image |
| Gender | t = 1.47 p = 0.22 | t = 0.35 p = 0.72 | t = 0.71 p = 0.47 | t = 0.47 p = 0.49 | t = 0.14 p = 0.70 | |
| Male Female | 134 (65.0) 72 (35.0) | |||||
| Marital status | F = 1.78 p = 0.17 | F = 0.40 p = 0.67 | F = 0.41 p = 0.66 | F = 0.64 p = 0.52 | F = 0.48 p = 0.61 | |
| Single Got married Widow | 30 (14.4) 177 (85.1) 1 (0.5) | |||||
| Education levels | F = 1.37 p = 0.24 | F = 1.05 p = 0.37 | F = 1.84 p = 0.12 | F = 1.69 p = 0.15 | F = 0.64 p = 0.63 | |
| Illiterate Primary school Secondary school High school and diploma Academic degree | 4 (2.1) 22 (11.4) 32 (16.6) 74 (38.3) 61 (31.6) | |||||
| Disease diagnosis | F = 1.53 p = 0.17 | F = 0.97 p = 0.43 | F = 0.98 p = 0.43 | F = 0.27 p = 0.92 | F = 1.21 p = 0.30 | |
| Acute myeloid leukemia Acute lymphoid leukemia Lymphoma Multiple myeloma Thalassemia Aplastic anemia | 87 (42.0) 23 (11.1) 42 (20.3) 50 (24.2) 2 (1.0) 3 (1.4) | |||||
| Number of hospitalization after HSCT | F = 1.52 p = 0.17 | F = 1.33 p = 0.25 | F = 0.68 p = 0.63 | F = 0.63 p = 0.67 | F = 1.82 p = 0.11 | |
| Not admission One time Two times Three times Six times Eight times | 6 (5.9) 80 (78.4) 9 (8.8) 5 (4.9) 1 (1.0) 1 (1.0) | |||||
| Kind of HSCT | t = 0.14 p = 0.70 | t = 0.35 p = 0.72 | t = 0.39 p = 0.39 | t = 0.46 p = 0.49 | t = 0.47 p = 0.49 | |
| Allograft Autograft | 51 (26.7) 140 (73.3) | |||||
| The family relationship of the transplant donor with the patient | F = 2.28 p = 0.11 | F = 2.57 p = 0.08 | F = 0.85 p = 0.42 | F = 0.65 p = 0.52 | F = 0.59 p = 0.55 | |
| Brother Sister Cousin’s son and daughter | 53 (84.1) 9 (14.3) 1 (1.6) |
The mean age of the donor was 36.06 (SD = 8.47). Moreover, 45 donors (73.8%) were married, and 16 (26.2%) were single. The satisfaction with the HSCT conducted in 101 patients (49.0%) was strongly agree, and in 44 (21.4%) of them was agree. On the other hand, 9 (4.4%), and 34 (16.5%) patients disagreed and strongly disagreed with the HSCT conducted, respectively.
This study showed that the mean scores of resilience, health anxiety, and body image in HSCT patients were 66.02 (SD = 14.85), 23.88 (SD = 10.30), and 5.90 (SD = 4.26), respectively. Based on the mean score of health anxiety, 125 (59.8%) HSCT patients reported non-clinical levels of health anxiety. Moreover, 47 (22.5%), 24 (11.5), and 13 (6.2%) showed mild, moderate, and substantial levels of health anxiety, respectively. On the other hand, no one reported severe health anxiety.
The mean scores of sleep quality and pain intensity were 5.54 (SD = 2.98) and 2.16 (SD = 1.56), respectively. As illustrated in Fig. 5 , approximately half of the participants reported good sleep quality, while the remaining half experienced poor sleep quality. Figure 6 reveals that no participants reported absence of pain (score = 0), while over two-thirds (83.8%) of HSCT patients experienced mild pain (scores 1–3).
As Table 1 shows, no significant difference was found between demographic and clinical characteristics and sleep quality, pain severity, resilience, health anxiety, and body image. Therefore, none of the demographic and clinical characteristics was a confounder on the study variables.
As Table 2 shows, a significant, but weak, association was found between sleep quality and pain severity ( r = 0.31, p < 0.001) and resilience ( r =˗0.39, p < 0.001). As Table 3 indicates, HSCT patients with a lower mean score of resilience and a higher mean score of pain intensity reported poor sleep quality. There was a strong, significant, positive, and moderate association between sleep quality and health anxiety ( r = 0.45, p < 0.001) and body image ( r = 0.42, p < 0.001). As Table 3 shows, HSCT patients with higher mean scores of health anxiety and body image reported poor sleep quality. The results of this study showed that the five variables of sleep quality, pain severity, health anxiety, resilience, and body image were significantly correlated two by two. Based on the findings, hypothesis 1 was confirmed.
Table 2
The association among sleep quality, pain severity, resilience, health anxiety, and body image in HSCT patients
**. Correlation is significant at the 0.01 level (2-tailed)
| Sleep quality | Pain Severity | resilience | Health anxiety | Body image | ||
| Sleep quality | Pearson Correlation | 1 | ||||
| Sig. (2-tailed) | ||||||
| Pain severity | Pearson Correlation | 0.31 ** | 1 | |||
| Sig. (2-tailed) | < 0.001 | |||||
| resilience | Pearson Correlation | -0.39 ** | -0.26 ** | 1 | ||
| Sig. (2-tailed) | < 0.001 | < 0.001 | ||||
| Health anxiety | Pearson Correlation | 0.45 ** | 0.24 ** | -0.43 ** | 1 | |
| Sig. (2-tailed) | < 0.001 | < 0.001 | < 0.001 | |||
| Body image | Pearson Correlation | 0.42 ** | 0.36 ** | -0.34 ** | 0.39 ** | 1 |
| Sig. (2-tailed) | < 0.001 | < 0.001 | < 0.001 | < 0.001 |
Table 3
Comparison the resilience, health anxiety, and body image in HSCT patients by sleep quality and pain severity
| Resilience | Health anxiety | Body image | Pain severity | |
| Sleep quality | ||||
| Good Poor t-test, p -value | 70.09 (13.25) 61.25 (15.24) 4.45, p < 0.001 | 20.05 (9.59) 28.23 (9.20) -6.23, p < 0.001 | 4.49 (2.98) 7.62 (4.94) -5.64, p < 0.001 | 1.64 (1.05) 2.75 (1.83) -5.50, p < 0.001 |
| Pain severity | ||||
| No Mild Moderate Severe ANOVA, p -value | ----- 67.85 (13.07) 56.96 (17.36) 55.00 (31.96) 8.69, p < 0.001 | ---- 22.71 (8.95) 29.93 (14.59) 29.60 (13.37) 7.30, 0.001 | ---- 5.42 (3.70) 7.24 (3.70) 15.40 (10.96) 17.23, p < 0.001 | ------ 5.21 (2.87) 7.35 (2.97) 7.00 (3.31) 7.27, 0.001 |
Based on the mediator model of resilience in the relationship between pain severity and sleep quality, the results of this model were R = 0.45, R˗Square = 0.20, MSE = 7.13, F = 26.16, and p < 0.001. According to Table 4 ; Fig. 1 , the direct effect of pain severity significantly correlated with sleep quality in HSCT patients (β = 0.43, t = 3.46, p = 0.0007). Resilience in HSCT patients was correlated with sleep quality (β=˗0.60, t = ˗5.27, p < 0.001. In addition, resilience was correlated with sleep quality in HSCT patients (β=˗2.38, t=˗3.72, p = 0.0002). Moreover, the relationship between pain severity and sleep quality was significantly mediated by resilience in HSCT patients (β = 0.16, CI = 0.03 to 0.31). Based on the findings, hypothesis 2 was confirmed.
Table 4
The mediating effect of resilience in the relationship between pain severity and sleep quality in HSCT patients
Resilience as a mediator, b Standard Error, c Bootstrapping Standard Error
| Coefficient | SE b | t Statistics | P -Values | 95% CI | |
| Direct effect | |||||
| Constant | 9.12 | 0.97 | 9.34 | < 0.001 | 7.19 to 11.04 |
| Path a: Pain severity ->Resilience | ˗2.38 | 0.63 | ˗3.72 | 0.0002 | ˗3.64 to ˗1.12 |
| Path b: Resilience ->Sleep quality | ˗0.06 | 0.01 | ˗5.27 | < 0.001 | ˗0.09 to ˗0.04 |
| Path cʹ: Pain severity ->Sleep quality | 0.43 | 0.12 | 3.46 | 0.0007 | 0.18 to 0.66 |
| Indirect effects | |||||
| Pain severity ->Resilience ->Sleep quality | 0.16 | 0.06 c | ---- | ---- | 0.03 to 0.31 |
| Total effect | |||||
| Path c: Pain severity ->Sleep quality | 0.59 | 0.12 | 4.74 | < 0.001 | 0.35 to 0.84 |
Table 5 ; Fig. 2 show the mediation effect of health anxiety in the relationship between pain severity and sleep quality in HSCT patients. The model was approved by R = 0.50, R˗Square = 0.25, MSE = 6.74, F = 34.40, and p < 0.001. As Table 4 shows, the direct effect was found between pain severity and sleep quality (β = 0.42, t = 3.53, p = 0.0005). Moreover, the direct effect of health anxiety and sleep quality in HSCT patients was significant (β = 0.11, t = 6.50, p < 0.001). In addition, the relationship between pain severity and sleep quality was significantly mediated by health anxiety in HSCT patients (β = 0.17, CI = 0.04 to 0.32). Based on the findings, hypothesis 3 was confirmed.
Table 5
The mediating effect of health anxiety in the relationship between pain severity and sleep quality in HSCT patients
Health anxiety as mediator, b Standard Error, c Bootstrapping Standard Error
| Coefficient | SE b | t Statistics | P -Values | 95% CI | |
| Direct effect | |||||
| Constant | 1.84 | 0.48 | 3.83 | 0.0002 | 0.89 to 2.80 |
| Path a: Pain severity ->Health anxiety | 1.49 | 0.44 | 3.34 | 0.001 | 0.61 to 2.36 |
| Path b: Health anxiety ->Sleep quality | 0.11 | 0.01 | 6.50 | < 0.001 | 0.08 to 0.15 |
| Path cʹ: Pain severity ->Sleep quality | 0.42 | 0.11 | 3.53 | 0.0005 | 0.18 to 0.65 |
| Indirect effects | |||||
| Pain severity ->Health anxiety ->Sleep quality | 0.17 | 0.07 c | ---- | ---- | 0.04 to 0.32 |
| Total effect | |||||
| Path c: Pain severity ->Sleep quality | 0.59 | 0.12 | 4.74 | < 0.001 | 0.35 to 0.84 |
Table 6 ; Fig. 3 show the mediation effect of body image in the relationship between pain severity and sleep quality in HSCT patients. The model was approved by R = 0.45, R˗Square = 0.21, MSE = 7.09, F = 27.61, and p < 0.001. As Table 5 indicates, a direct effect was observed between pain severity and sleep quality (β = 0.34, t = 2.70, p = 0.007). Moreover, the direct effect of body image and sleep quality in HSCT patients was significant (β = 0.25, t = 5.44, p < 0.001). In addition, the relationship between pain severity and sleep quality was significantly mediated by body image in HSCT patients (β = 0.25, CI = 0.10 to 0.43). Based on the findings, hypothesis 4 was confirmed.
Table 6
The mediating effect of body image in the relationship between pain severity and sleep quality in HSCT patients
Body image as mediator, b Standard Error, c Bootstrapping Standard Error
| Coefficient | SE b | t Statistics | P -Values | 95% CI | |
| Direct effect | |||||
| Constant | 3.30 | 0.35 | 9.20 | < 0.001 | 2.59 to 4.01 |
| Path a: Pain severity ->Body image | 1.00 | 0.17 | 5.67 | < 0.001 | 0.65 to 1.35 |
| Path b: Body image ->Sleep quality | 0.25 | 0.04 | 5.44 | < 0.001 | 0.16 to 0.34 |
| Path cʹ: Pain severity ->Sleep quality | 0.34 | 0.12 | 2.70 | 0.007 | 0.09 to 0.59 |
| Indirect effects | |||||
| Pain severity ->Body image ->Sleep quality | 0.25 | 0.08 c | ---- | ---- | 0.10 to 0.43 |
| Total effect | |||||
| Path c: Pain severity ->Sleep quality | 0.59 | 0.12 | 4.74 | < 0.001 | 0.35 to 0.84 |
Table 7 ; Fig. 4 show the mediation effect of resilience, health anxiety, and body image in the relationship between pain severity and sleep quality in HSCT patients. The model was approved by R = 0.56, R˗Square = 0.31, MSE = 6.22, F = 22.96, and p < 0.001. As Table 6 indicates, a direct effect was observed between sleep quality and pain severity (β = 0.24, t = 1.98, p = 0.04), resilience (β=˗0.03, t=˗2.74, p = 0.006), health anxiety (β = 0.07, t = 3.85, p = 0.0002), and body image (β = 0.15, t = 2.94, p = 0.003). In addition, the relationship between pain severity and sleep quality was significantly mediated by resilience, health anxiety and, body image in HSCT patients (β = 0.01, CI = 0.0007 to 0.02). Based on the findings, hypothesis 4 was confirmed.
Table 7
The mediating effect of resilience, health anxiety, and body image in the relationship between pain severity and sleep quality in HSCT patients
Resilience, health anxiety and body image as mediators, b Standard Error, c Bootstrapping Standard Error
| Coefficient | SE b | t Statistics | P -Values | 95% CI | |
| Direct effect | |||||
| Path a 1 : Pain severity->Resilience | -2.35 | 0.64 | -3.67 | 0.0003 | -3.61 to -1.08 |
| Path a 2 : Pain severity ->Health anxiety | 0.83 | 0.42 | 1.95 | 0.04 | 0.0006 to 1.67 |
| Path a 3 : Pain severity->Body image | 0.69 | 0.15 | 4.39 | < 0.001 | 0.38 to 1.06 |
| Constant | 4.74 | 1.20 | 3.93 | 0.0001 | 2.36 to 7.12 |
| Path b 1 : Resilience ->Sleep quality | ˗0.03 | 0.01 | ˗2.74 | 0.006 | ˗0.06 to ˗0.01 |
| Path b 2 : Health anxiety ->Sleep quality | 0.07 | 0.01 | 3.85 | 0.0002 | 0.03 to 0.11 |
| Path b 3 : Body image ->Sleep quality | 0.15 | 0.05 | 2.94 | 0.003 | 0.05 to 0.25 |
| Path cʹ: Pain severity ->Sleep quality | 0.24 | 0.12 | 1.98 | 0.04 | 0.002 to 0.48 |
| Indirect effects | |||||
| Indirect total | 0.35 | 0.10 c | ----- | ------ | 0.15 to 0.56 |
| Pain severity ->Resilience ->Sleep quality | 0.08 | 0.04 c | ------ | ------ | 0.01 to 0.19 |
| Pain severity ->Health anxiety ->Sleep quality | 0.10 | 0.05 c | ------ | ------ | -0.002 to 0.14 |
| Pain severity ->Body image ->Sleep quality | 0.10 | 0.05 c | ------ | ------ | 0.01 to 0.21 |
| Pain severity ->Resilience ->Health anxiety ->Sleep quality | 0.04 | 0.02 c | ------ | ------ | 0.009 to 0.10 |
| Pain severity ->Resilience ->Body image ->Sleep quality | 0.01 | 0.01 c | ------ | ------ | -0.001 to 0.03 |
| Pain severity ->Health anxiety ->Body image ->Sleep quality | 0.01 | 0.009 c | ------ | ------ | -0.001 to 0.03 |
| Pain severity ->Resilience ->Health anxiety ->Body image ->Sleep quality | 0.01 | 0.007 c | ---- | ---- | 0.0007 to 0.02 |
| Total effect | |||||
| Path c: Pain severity ->Sleep quality | 0.59 | 0.12 | 4.74 | < 0.001 | 0.35 to 0.84 |
Discussion
This study showed that HSCT patients who had a higher mean score of pain severity reported a lower mean score of sleep quality. Another study found that individuals with chronic low pain who experienced higher pain intensity reported poorer sleep quality at night [ 48 ]. A review study reported that researchers believed that sleep quality predicted the next day pain [ 34 ]. The association between restricted sleep and greater pain was indicated in another study [ 49 ]. Patients with chronic pain had trouble sleeping [ 50 ]. Poor sleep was effective in the development and maintenance of chronic pain [ 51 ]. Poor sleep affects inflammation, pain response, and experience. Therefore, it affects general health [ 49 ]. Mechanisms of association between sleep and pain are diverse and unclear. A possible explanation could be related to the effect of sleep on inflammatory mechanisms that sensitize pain pathways. Sleep is a powerful modulator of systemic inflammation. Different stages of sleep (i.e. rapid eye movement and three non-rapid eye movement stages) differentially regulate nocturnal levels of inflammatory factors (such as cytokines), and this provides the stage for daytime inflammatory levels. Sleep loss or disruption can alter this immune balance by activating the “stress response” (such as the hypothalamic-pituitary-adrenal axis and activation of the sympathetic nervous system and/or inflammatory pathways). Increasing the levels of pro-inflammatory cytokines during the day rather than at night leads to a transient change in the temporal pattern of inflammatory responses. These effects are observed after a night of partial sleep loss. Repeated or persistent episodes of sleep loss/disruption can lead to excessive and sustained activation of this inflammatory response, leading to chronic high inflammation. Many cytokines and factors involved in this “inflammatory response” are known to amplify pain by directly sensitizing peripheral and central nervous system tissues. Despite this knowledge, no study has yet tested and confirmed these “complete” pathways linking sleep and increased or chronic pain [ 52 ]. Moreover, our interpretation requires caution because we did not track infections, Graft Versus Host Disease (GVHD), or other health problems at the time of the study. Future research should include these factors to better understand how sleep affects pain.
Our study indicated a significant, but weak, association between sleep quality and resilience in HSCT patients. The association between resilience and sleep quality has been reported in some studies [ 37 , 53 ]. A population-based study indicated that longer sleep duration was associated with higher psychological resilience [ 13 ]. Researchers believe that sleep deprivation can lead to an increase in stress hormones, including cortisol, so a person’s resilience decreases. Sleep deprivation can affect coping strategies and lead to a decrease in coping with challenges, thus reducing a person’s resilience [ 18 ]. Given the limited research on the relationship between resilience and sleep quality in HSCT patients, our findings provide valuable insight into the psychological factors that may affect sleep health.
Our study indicated the relationship between pain severity and sleep quality was significantly mediated by resilience in HSCT patients. Moreover, 20% of the total effect of sleep quality on the severity of pain was explained by a pathway through resilience. Although this finding is novel, a study indicated that psychological resilience mediated the relationship between the quality of sleep and symptoms of anxiety [ 37 ]. Another study showed the mediator role of resilience in the relationship between sleep quality and post-traumatic stress [ 38 ]. Researchers reported the mediator role of the psychological and physiological aspects of experiences in the relationship between pain and sleep [ 40 ]. Importantly, our findings extend this body of knowledge by identifying resilience as a key psychological mechanism linking sleep and pain specifically in HSCT patients, a population that faces unique physical and emotional challenges during recovery.
This study showed that HSCT patients who had higher mean scores of health anxiety reported worse sleep quality. Because the concept of health anxiety is somewhat a part of anxiety, the literature was reviewed with the keyword anxiety. Researchers believe that people who experience high anxiety are more prone to insomnia [ 54 ]. Other researchers also stated that short sleep duration was correlated to anxiety symptoms, and short sleep duration predicted anxiety symptoms [ 23 ]. Another study reported the relationship between anxiety and sleep disorders [ 55 ].
The present study revealed that the relationship between pain severity and sleep quality was significantly mediated by health anxiety in HSCT patients. Moreover, 25% of the total effect of HSCT sleep quality on the severity of pain was explained by a pathway through health anxiety. Consistent with our study, in a systematic review, it was indicated that depressive and anxiety symptoms mediated the relationship between sleep and pain [ 40 ]. They reported that anxiety symptoms mediated the relationship between sleep problems and abdominal pain severity [ 40 ]. Another study indicated that the relationship between pain severity and sleep quality was mediated by anxiety about sleep [ 39 ]. It shows that anxiety is related to health, and sleep has a mediator role in the relationship between pain and sleep.
Further, our study indicated that HSCT patients who had negative view of body image reported worse sleep quality. In line with this study, the researchers stated that there was a relationship between the body image and quality of sleep in cancer patients and those people who had a better body image had better sleep quality [ 56 ]. Researchers showed that negative body image led to worse sleep quality [ 57 ]. This highlights the importance of addressing body image concerns in supportive care for HSCT patients to potentially improve sleep outcomes.
The present study showed that the relationship between pain severity and sleep quality was significantly mediated by body image in HSCT patients. Moreover, 21% of the total effect of HSCT sleep quality on the severity of pain was explained by a pathway through body image. In our review of the literature, no study reported the mediating effect of body image on the relationship between pain and sleep. However, a review study indicated the role of psychological factors such as negative mood and depressive symptoms in the relationship between pain and sleep [ 40 ]. Researchers stated that biological, psychosocial, and behavioral factors might affect pathways between pain and sleep [ 39 ], and body image as a psychological factor was identified as a mediator in our study. A study reported the direct effect of positive body image and adequate sleep. They stated that the relationship between sleep and body image was mediated by a psychological factor such as depression [ 31 ].
Moreover, our findings showed that the relationship between pain severity and sleep quality was significantly mediated by resilience, health anxiety, and body image in HSCT patients. Also, 31% of the total effect of HSCT sleep quality on the severity of pain was explained by a pathway through resilience, health anxiety, and body image. Resilience, health anxiety, and body image are psychological factors. A systematic review study carried out to determine the mediators between pain and sleep showed that psychological factors such as negative mood/affect, depressive and anxiety symptoms, and stress were the mediators in the relationship between pain and sleep [ 40 ]. It showed that psychological factors were important in the relationship between pain and sleep. Moreover, our results are consistent with earlier studies showing that resilience and psychological traits related to pain are crucial in comprehending how patients perceive and cope with pain [ 12 ]. Furthermore, the impact of variables like gender and previous experiences on pain perception underscores the need for comprehensive, multidimensional psychological strategies in clinical care [ 11 ].
Clinical implications
The present study presented a new model of the relationship between sleep quality and severity of pain with the mediating role of psychological variables such as resilience, health anxiety, and body image in HSCT patients, which could be helpful in clinical environments and patient care at home. According to the results of this study, it is possible to enhance the quality of sleep of the HSCT patient who is in pain by improving resilience and body image and reducing health anxiety.
Strength and limitations
Our study was novel in that it examined different psychological variables such as resilience, health anxiety, and body image in the relationship between pain severity and sleep quality in HSCT patients. Using a structure equation model that assessed the fit model and the complex relationship among variables as direct and indirect effects was one of the advantages of this study.
As this is a cross-sectional study, we could not assess the structure of such concepts as severity of pain, sleep quality, resilience, health anxiety, and body image over time. In addition, due to the cross-sectional design, this study cannot establish causal relationships between the variables. Another limitation is that we did not assess whether patients were in complete remission, which may have influenced the study variables. Another limitation is that sleep quality and related variables were assessed only through self-report questionnaires. Future studies should incorporate objective measures, such as polysomnography and biomarkers of inflammation, to provide a more comprehensive evaluation. The generalizability of the findings may be limited due to the single-center nature of the sample. Future studies should involve more diverse HSCT populations across multiple centers.
Future research may benefit from including a broader range of psychological factors—such as differences related to gender and individuals’ prior experiences with pain—to deepen insight into the complexities of pain perception within clinical environments [ 11 , 12 ]. Another limitation of this study lies in the potential constraints of the sample. While including 210 patients provides a solid foundation, the sample may not fully represent the broader population, especially if key demographic characteristics are not adequately controlled. Additionally, the absence of potentially influential factors—such as the levels of social support or presence of comorbid conditions—may have introduced confounding effects that were not considered. Lastly, the study does not address the long-term psychological or physical outcomes associated with the variables examined, leaving uncertainty regarding the predictive relevance of the findings over time. Furthermore, future longitudinal studies are recommended to clarify the temporal relationships between pain, sleep quality, and psychological factors in HSCT patients. Since peer support improved hope in chronic disease [ 58 ], and this study did not examine additional potential mediators or moderators, such as social support, hope and coping strategies, which may influence the relationship between pain and sleep. Future research should consider these factors to provide a more comprehensive understanding of this relationship.
While this study relied on self-reported data, which carries a risk of common method bias, several precautions were implemented to minimize its impact. Anonymous participation was ensured to encourage candid responses, and scale formats were diversified to reduce patterned answering. Nevertheless, the cross-sectional design means some shared variance may persist due to measurement methodology rather than true relationships. Future research could strengthen the findings by incorporating objective measures or temporal separation between the predictor and outcome assessments.
Conclusion
This study showed that there was a direct relationship between sleep quality and severity of pain, resilience, health anxiety, and body image in HSCT patients. Moreover, resilience played a mediating role in the relationship between severity of pain and sleep quality. Moreover, health anxiety mediated the relationship between the severity of pain and sleep quality in HSCT patients. In addition, a pathway through body image mediated the association between HSCT sleep quality and severity of pain. These findings highlight the importance of considering psychological and physical factors when addressing sleep quality in HSCT patients. Performing interventions aiming at reducing pain and health anxiety, as well as enhancing body image and resilience, may potentially contribute to better sleep outcomes; however, longitudinal or experimental studies are needed to confirm these relationships.
Acknowledgements
This study was extracted from an MSc thesis written by Bahman Mokhtarinia, which was financially supported by Shiraz University of Medical Sciences (Code Number: 28802). The researchers would like to thank HSCT patients who participated in this study. We appreciate Shiraz University of Medical Sciences for its financial support of this study. The authors would also like to thank the Center for Development of Clinical Research of Nemazee Hospital and Dr Nasrin Shokrpour for English language editorial assistance.
Abbreviations
Hematopoietic stem cell transplantation
Pittsburgh Sleep Quality Index
Connor-Davidson’s Resilience Scale
Health Anxiety Inventory
Graft Versus Host Disease
Author contributions
Masoume Rambod, Nilofar Pasyar, Bahman Mokhtarinia, Mani Ramzi, Mahdi Salmanpour participated in the conceptualization of this study. Bahman Mokhtarinia participated in the management of the data collection. Masoume Rambod and Mahdi Salmanpour managed the data analysis. All authors participated in writing and approving the original draft of the manuscript.
Funding
With the Grant Number (28802), Shiraz University of Medical Sciences financially supported this study.
Data availability
The data of this study will be available by email to Masoume Rambod.
Declarations
Ethical approval and consent to participate
This study was approved by the Research Ethics Committees of Schools of Nursing and Midwifery, Management and Medical Information Science, Shiraz University of Medical Sciences (IR.SUMS.NUMIMG.REC.1402.069, approval date: 2023-09-09). It was conducted based on the Declaration of Helsinki. The data collection on the HSCT patients was conducted anonymously. The written consent form to participate in this study was obtained from the HSCT patients. All the HSCT patients who participated in this study signed the written consent form. We confirm that this written consent form was informed.
Consent for publication
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. Ma JD, El-Jawahri AR, LeBlanc TW, Roeland EJ. Pain syndromes and management in adult hematopoietic stem cell transplantation. Hematology/Oncology Clin. 2018;32(3):551–67.
2. Rischer J, Scherwath A, Zander AR, Koch U, Schulz-Kindermann F. Sleep disturbances and emotional distress in the acute course of hematopoietic stem cell transplantation. Bone Marrow Transplant. 2009;44(2):121–8.
3. Kapucu S, Karacan Y. Physiological problems in patients undergoing autologous and allogeneic hematopoietic stem cell transplantation. Asia-Pacific J Oncol Nurs. 2014;1(1):50–4.
4. Pasyar N, Rambod M, Zahedi F, Ramzi M. Pain, fatigue, nausea, and vomiting as the predictors of anxiety in patients undergoing hematopoietic stem cell transplantation: a prospective cohort study. Support Care Cancer. 2022;30(7):5871–9.
5. O’Sullivan ML, Shelby RA, Dorfman CS, Kelleher SA, Fisher HM, Rowe Nichols KA, Keefe FJ, Sung AD, Somers TJ. The effect of pre-transplant pain and chronic disease self-efficacy on quality of life domains in the year following hematopoietic stem cell transplantation. Support Care Cancer. 2018;26:1243–52.
6. Jim HS, Sutton S, Majhail NS, Wood WA, Jacobsen PB, Wingard JR, Wu J, Knight JM, Syrjala KL, Lee SJ. Severity, course, and predictors of sleep disruption following hematopoietic cell transplantation: a secondary data analysis from the BMT CTN 0902 trial. Bone Marrow Transplant. 2018;53(8):1038–43.
7. Rentscher KE, Carroll JE, Juckett MB, Coe CL, Broman AT, Rathouz PJ, Hematti P, Costanzo ES. Sleep disruption, fatigue, and depression as predictors of 6-year clinical outcomes following allogeneic hematopoietic cell transplantation. JNCI: J Natl Cancer Inst. 2021;113(10):1405–14.
8. Lee MS, Asvat Y, Gonzalez BD, Jacobsen PB, Jim HS. Coping, stress, and insomnia in hematopoietic stem cell transplant candidates. Psycho-oncology. 2016;26(4):560.
9. Ghazikhanian SE, Dorfman CS, Somers TJ, O’Sullivan ML, Fisher HM, Edmond SN, Wren AA, Kelleher SA, Rowe Nichols KA, Chao N, Shelby RA. Cognitive problems following hematopoietic stem cell transplant: relationships with sleep, depression and fatigue. Bone Marrow Transplant. 2017;52(2):279–84.
10. Wang YM, Huber JF, Flesch L, Demmel K, Lane A, Beebe DW, Crosby LE, Hogenesch JB, Smith DF, Davies SM, Dandoy CE. Trajectory of sleep, depression, and quality of life in pediatric HSCT recipients. Transplantation Cell Therapy. 2024;30(6):632–e1.
11. Diotaiuti P, Corrado S, Mancone S, Palombo M, Rodio A, Falese L, Langiano E, Siqueira TC, Andrade A. Both gender and agonistic experience affect perceived pain during the cold pressor test. Int J Environ Res Public Health. 2022;19(4):2336.
12. Diotaiuti P, Corrado S, Mancone S, Cavicchiolo E, Chirico A, Siqueira TC, Andrade A. A psychometric evaluation of the Italian short version of the fear of pain Questionnaire-III: psychometric properties, measurement invariance across gender, convergent, and discriminant validity. Front Psychol. 2023;13:1087055.
13. Campo RA, Wu LM, Austin J, Valdimarsdottir H, Rini C. Personal resilience resources predict post-stem cell transplant cancer survivors’ psychological outcomes through reductions in depressive symptoms and meaning-making. J Psychosoc Oncol. 2017;35(6):666–87.
14. Şanlı ME. The relationships between posttraumatic growth and psychological resilience in individuals with chronic disease. Gümüşhane Üniversitesi Sağlık. Bilimleri Dergisi. 2024;13(2):561–70.
15. Yıldırım Üşenmez T, Öner U, Şanlı ME, Dinç M. The effect of spirituality on psychological resilience in women with breast cancer who have received chemotherapy: a cross-sectional study from Turkey. J Relig Health. 2023;62(3):1964–75.
16. Rosenberg AR, Syrjala KL, Martin PJ, Flowers ME, Carpenter PA, Salit RB, Baker KS, Lee SJ. Resilience, health, and quality of life among long-term survivors of hematopoietic cell transplantation. Cancer. 2015;121(23):4250–7.
17. Schumacher A, Sauerland C, Silling G, Berdel WE, Stelljes M. Resilience in patients after allogeneic stem cell transplantation. Support Care Cancer. 2014;22:487–93.
18. Zhu Y, Zhang Y, Zhuang M, Ye M, Wang Y, Zheng N, Zhan Y. Association between sleep duration and psychological resilience in a population-based survey: A cross-sectional study. J Educ Health Promotion. 2024;13(1):43.
19. Izydorczyk B, Kwapniewska A, Lizinczyk S, Sitnik-Warchulska K. Psychological resilience as a protective factor for the body image in post-mastectomy women with breast cancer. Int J Environ Res Public Health. 2018;15(6):1181.
20. Niamhom P, Wonghongkul T, Chaiard J, Srirat C. Factors influencing resilience in patients with advanced cancer: A cross-sectional study. Belitung Nurs J. 2023;9(3):227.
21. Seo HJ, Baek YG, Cho BS, Kim TS, Um YH, Chae JH. Anxiety and depression of the patients with hematological malignancies during hospitalization for hematopoietic stem cell transplantation. Psychiatry Invest. 2019;16(10):751.
22. Chellappa SL, Aeschbach D. Sleep and anxiety: from mechanisms to interventions. Sleep Med Rev. 2022;61:101583.
23. Kalmbach DA, Abelson JL, Arnedt JT, Zhao Z, Schubert JR, Sen S. Insomnia symptoms and short sleep predict anxiety and worry in response to stress exposure: a prospective cohort study of medical interns. Sleep Med. 2019;55:40–7.
24. Alqahtani JS, AlRabeeah SM, Aldhahir AM, Siraj R, Aldabayan YS, Alghamdi SM, Alqahtani AS, Alsaif SS, Naser AY, Alwafi H. Sleep quality, insomnia, anxiety, fatigue, stress, memory and active coping during the COVID-19 pandemic. Int J Environ Res Public Health. 2022;19(9):4940.
25. Kang D, Kim IR, Choi HJ, Jung CW, Yoon SS, Kim JS, Lee CH, Jang JH, Cho J. Association between body image dissatisfaction and poor quality of life and depression among patients with hematopoietic stem cell transplantation. Support Care Cancer. 2021;29:3815–22.
26. Aggarwal R, Ranjan D, Chandola R. Effect of body image on self esteem: a systematic literature review and future implication. Eur Chem Bull. 2023;12:6087–95.
27. Merino M, Tornero-Aguilera JF, Rubio-Zarapuz A, Villanueva-Tobaldo CV, Martín-Rodríguez A, Clemente-Suárez VJ. Body perceptions and psychological well-being: a review of the impact of social media and physical measurements on self-esteem and mental health with a focus on body image satisfaction and its relationship with cultural and gender factors. InHealthcare. 2024;12(14):1396.
28. Şanlı ME, Üşenmez TY. Effect of body image on sexual quality of life in married women with physical disabilities. Anatol J Health Res. 2024;5(2):93–8.
29. Markey CH, Dunaev JL, August KJ. Body image experiences in the context of chronic pain: an examination of associations among perceptions of pain, body dissatisfaction, and positive body image. Body Image. 2020;32:103–10.
30. Senkowski D, Heinz A. Chronic pain and distorted body image: implications for multisensory feedback interventions. Neurosci Biobehavioral Reviews. 2016;69:252–9.
31. Rosenbaum DL, Gillen MM, Bloomer SA. The effects of sleep on body image: examining the roles of depression, perceived stress, and anxiety. J Am Coll Health 2023 Mar 3:1–9.
32. Bolton D, Gillett G, Bolton D, Gillett G. The biopsychosocial model 40 years on. The biopsychosocial model of health and disease: New philosophical and scientific developments. 2019:1–43.
33. Nicholas MK. The biopsychosocial model of pain 40 years on: time for a reappraisal? Pain. 2022;163(S1):S3–14.
34. Finan PH, Goodin BR, Smith MT. The association of sleep and pain: an update and a path forward. J Pain. 2013;14(12):1539–52.
35. Tian Y, Wang YL. Resilience provides mediating effect of resilience between fear of progression and sleep quality in patients with hematological malignancies. World J Psychiatry. 2024;14(4):541.
36. Su P, He M. Relationship between sleep quality and subjective well-being: resilience as a mediator and belief in a just world as a moderator. Front Psychiatry. 2023;14:1297256.
37. Cai H, Guo J, Zhou J, Lai Y. Psychological resilience mediates the association between sleep quality and anxiety symptoms: A repeated measures study in college students. PLoS ONE. 2023;18(10):e0292887.
38. Zhao L, Yang F, Sznajder KK, Zou C, Jia Y, Yang X. Resilience as the mediating factor in the relationship between sleep disturbance and post-stroke depression of stroke patients in china: a structural equation modeling analysis. Front Psychiatry. 2021;12:625002.
39. Rakhimov A, Whibley D, Tang NK. Cognitive-behavioural pathways from pain to poor sleep quality and emotional distress in the general population: the indirect effect of sleep-related anxiety and sleep hygiene. PLoS ONE. 2022;17(1):e0260614.
40. Whibley D, AlKandari N, Kristensen K, Barnish M, Rzewuska M, Druce KL, Tang NK. Sleep and pain: a systematic review of studies of mediation. Clin J Pain. 2019;35(6):544–58.
41. Rambod M, Pasyar N, Karimian Z, Farbood A. The effect of lemon inhalation aromatherapy on pain, nausea, as well as vomiting and neurovascular assessment in patients for lower extremity fracture surgery: a randomized trial. BMC Complement Med Ther. 2023;23(1):208.
42. Buysse DJ, Reynolds CF III, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh sleep quality index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989;28(2):193–213.
43. Connor KM, Davidson JR. Development of a new resilience scale: the Connor-Davidson resilience scale (CD‐RISC). Depress Anxiety. 2003;18(2):76–82.
44. Rambod M, Pasyar N, Soltanian M. The predictive role of resilience and the ethical climate of hospital in the fatigue of surgical technologists working in operating rooms. BMC Psychol. 2024;12(1):380.
45. Salkovskis PM, Rimes KA, Warwick HM, Clark D. The health anxiety inventory: development and validation of scales for the measurement of health anxiety and hypochondriasis. Psychol Med. 2002;32(5):843–53.
46. Rabiei M, Kalantari M, Asgari K, Bahrami F. Factor structure analysis, validity and reliability of the health anxiety inventory short form. J Depress Anxiety. 2013;2(1):2–5.
47. Hopwood P, Fletcher I, Lee A, Al Ghazal S. A body image scale for use with cancer patients. Eur J Cancer. 2001;37(2):189–97.
48. Bintang AK, Santosa I, Goysal Y, Akbar M, Aulina S. Relationship between sleep quality and pain intensity in patients with chronic low back pain. Med Clínica Práctica. 2021;4:100208.
49. Whale K, Gooberman Hill R. The importance of sleep for people with chronic pain: current insights and evidence. J Bone Mineral Res Plus. 2022;6(7):e10658.
50. Duo L, Yu X, Hu R, Duan X, Zhou J, Wang K. Sleep disorders in chronic pain and its neurochemical mechanisms: a narrative review. Front Psychiatry. 2023;14:1157790.
51. Lenzo V, Sardella A, Musetti A, Freda MF, Lemmo D, Vegni E, Borghi L, Plazzi G, Palagini L, Castelnuovo G, Cattivelli R. The relationship between resilience and sleep quality during the second wave of the COVID-19 pandemic: a longitudinal study. Nat Sci Sleep 2022 Jan 6:41–51.
52. Klyne DM, Hall M. Is sleep the new treatment for pain? Two issues need resolving before deciding. Sleep. 2024;47(6):1–4.
53. Zila-Velasque JP, Grados-Espinoza P, Chuquineyra BS, Diaz-Vargas M, Sierra Calderón GS, Choquegonza S, Temoche-Rivas MS, Siguas Peixoto K, Valladares-Garrido MJ, Failoc-Rojas VE. Resilience, sleep quality and sleepiness in Peruvian medical students: a multicenter study. Front Psychiatry. 2024;15:1284716.
54. Oh CM, Kim HY, Na HK, Cho KH, Chu MK. The effect of anxiety and depression on sleep quality of individuals with high risk for insomnia: a population-based study. Front Neurol. 2019;10:849.
55. Yu C, Liu Z, Su T, Li Z, Jiang Z, Zhong W, Xiao Z. The effect of anxiety on sleep disorders in medical students: a moderated mediation model. Front Psychol. 2024;15:1338796.
56. Li S, Xiang Y, Li H, Yang C, He W, Wu J, Knobf MT, Ye Z. Body image, self-efficacy, and sleep quality among patients with breast cancer: A latent profile and mediation analysis. Eur J Oncol Nurs. 2024;71:102652.
57. Azizi Kutenaee M, Amirjani S, Asemi Z, Taghavi SA, Allan H, Kamalnadian SN, Khashavi Z, Bazarganipour F. The impact of depression, self-esteem, and body image on sleep quality in patients with PCOS: a cross-sectional study. Sleep Breath. 2020;24:1027–34.
58. Pasyar N, Rambod M, Jowkar M. The effect of peer support on hope among patients under Hemodialysis. Int J Nephrol Renovascular Disease 2020 Mar 13:37–44.
Associated Data
Data Availability Statement
The data of this study will be available by email to Masoume Rambod.