Abstract
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Purpose
This study aimed to identify predictors of quality of life (QoL), including self-efficacy, social support, illness perceptions, and resilience, among colorectal cancer patients during the first 1 to 6 months after stoma surgery.
-
Methods
A predictive correlational design was used with 142 adult patients who had undergone stoma surgery within the preceding 1 to 6 months. Data were collected using validated instruments measuring QoL, self-efficacy, social support, illness perceptions, and resilience. The data were analyzed using descriptive statistics, the independent t-test, one-way analysis of variance, the Games-Howell post-hoc test, Pearson correlation coefficients, and hierarchical multiple linear regression analysis.
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Results
The participants had a mean age of 56.15 years (standard deviation, 6.51 years); 67.6% were male, and 57.0% had a temporary stoma. In model 1, the method of paying medical expenses significantly predicted QoL, explaining 6.0% of the variance (adjusted R²=.06, p=.006), with self-financed patients reporting lower QoL than insured patients. In model 2, the addition of psychosocial variables (self-efficacy, social support, illness perceptions, and resilience) substantially improved the model, explaining 70.0% of the variance (adjusted R²=.70, p<.001). In the final model, illness perceptions (β=−.61), social support (β=.32), resilience (β=.20), and self-efficacy (β=.19) were significant predictors (all p<.001), whereas method of paying medical expenses was no longer significant.
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Conclusion
This study provides evidence to support the development of interventions targeting illness perceptions, social support, resilience, and self-efficacy to improve QoL among stoma patients during the early postoperative period.
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Key Words: Illness behavior; Quality of life; Resilience; Self efficacy; Social support
INTRODUCTION
Colorectal cancer (CRC) remains a major global public health concern. According to recent global estimates, it is the third most commonly diagnosed cancer, with Asia accounting for nearly half of all newly diagnosed cases [
1]. China has the highest incidence in the region, representing more than half of the CRC burden in Asia and approximately one-quarter of cases worldwide [
2]. Because incidence rises markedly after 50 years of age, CRC poses an increasing healthcare challenge both globally and within China [
3].
Surgery remains the cornerstone of CRC treatment, and many patients require a stoma, a surgically created opening that diverts feces, which may be temporary or permanent [
4]. Although stoma formation can be lifesaving, it can also substantially affect patients’ quality of life (QoL) by influencing their physical, psychological, social, and spiritual well-being.
The early postoperative period is particularly challenging for these patients. Previous studies have shown clinically meaningful declines in QoL after CRC surgery, especially during the first postoperative month [
5]. The presence of a stoma further complicates recovery by disrupting everyday life and requiring patients to adapt to new self-care demands and altered social interactions [
6]. Common physical problems include leakage, peristomal complications, pain, sleep disturbance, and gas incontinence [
7]. Patients also frequently experience psychological difficulties, including anxiety about the future, interpersonal strain, sexual dysfunction, and restrictions in physical activity and diet [
8].
Guided by individual and family self-management theory (IFSMT), this study conceptualized QoL as a distal outcome that emerges through the interaction of contextual, process, and proximal factors [
9]. Within this framework, contextual factors such as illness perceptions and resilience shape how patients with CRC and a stoma understand their condition, adjust to bodily changes, and cope with the uncertainty of illness. Process factors, including self-efficacy and social support, serve as central self-management mechanisms that help patients engage in health-promoting behaviors, adhere to treatment, and manage stoma-related symptoms effectively. These processes, in turn, influence proximal outcomes such as functional status, emotional adjustment, and role participation, all of which are important indicators of patient well-being in oncology care. Ultimately, these interrelated pathways converge to affect QoL.
Self-efficacy refers to an individual’s belief in their ability to organize and carry out the actions needed to manage health-related demands [
10]. It influences cognition, motivation, and coping behavior and has been associated with better QoL in patients with a colostomy [
11]. In contrast, lower self-efficacy has been associated with fatigue and more negative illness perceptions [
12]. By strengthening a sense of control, self-efficacy may help reduce stoma-related anxiety and depression and facilitate psychological adjustment [
13].
Social support, which includes assistance from family members, friends, and healthcare providers, is another important determinant of QoL. Support from healthcare professionals facilitates psychological adjustment, whereas family support plays a central role in self-care and emotional well-being [
7]. Previous evidence suggests that strong social support is associated with better QoL in CRC patients with a stoma [
14]. In addition, social support may indirectly strengthen self-efficacy, creating a reinforcing cycle that promotes self-management and adaptation.
Illness perceptions are also critical in shaping QoL outcomes. Patients’ beliefs about the severity, consequences, and emotional impact of illness strongly influence psychological adjustment [
12]. Among stoma patients, more negative illness perceptions have been associated with poorer psychological adaptation and lower QoL [
15].
Resilience, defined as the capacity to adapt positively in the face of adversity, has increasingly been recognized as a protective factor among cancer patients. Individuals with greater resilience tend to show better psychological adjustment, lower stress, and higher QoL, even under similar disease conditions [
16]. Thus, resilience may lessen the psychological burden associated with stoma care and support adaptive coping and longer-term well-being.
Although self-efficacy, social support, illness perceptions, and resilience are established correlates of QoL in CRC patients, most of the available evidence has been derived from Western populations. Cultural differences in lifestyle, social structure, and values may limit the generalizability of these findings to Asian populations. Given the increasing incidence of CRC in China [
17], context-specific research is needed. Therefore, this study aimed to identify predictors of QoL among CRC patients with a stoma in Wenzhou, China, in order to inform culturally appropriate interventions and improve health outcomes.
METHODS
1. Study Design
This study employed a predictive correlational design to examine factors associated with QoL in CRC patients with a postoperative stoma. The study was reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.
2. Participants and Setting
Participants were patients who had undergone stoma surgery for CRC at First Affiliated Hospital of Wenzhou Medical University. Recruitment was conducted in the outpatient clinic of the Department of Colorectal and Anal Surgery.
Eligible participants were adults aged 18 to 60 years who had undergone stoma surgery within the previous 1 to 6 months and were able to communicate in Mandarin or the Wenzhou dialect. The upper age limit of 60 years was determined on the basis of policy and clinical considerations. In China, individuals older than 60 years are officially classified as older adults according to national demographic and health policy standards [
18]. This population generally has a greater burden of comorbid conditions, reduced functional reserve (i.e., a decline in intrinsic capacity), and age-related changes in the interaction between personal capacity and social environments that affect functional ability. These factors are established influences on QoL outcomes [
19]. Restricting the sample to patients aged 60 years or younger was therefore intended to reduce age-related heterogeneity and allow a more focused examination of psychosocial predictors of QoL during the early postoperative adjustment period after stoma surgery.
Patients who were currently receiving chemotherapy or radiotherapy, those with metastatic disease, and those with a documented history of psychiatric disorders were excluded. The exclusion of patients undergoing active anticancer treatment was based on both clinical and methodological considerations. Clinically, chemotherapy and radiotherapy, as key components of multimodal cancer treatment, are associated with substantial adverse effects. Evidence from a randomized trial in rectal cancer has shown that such treatment can result in chronic toxicity, including neurotoxicity and diarrhea, as well as persistent functional deterioration such as stool incontinence, all of which can substantially impair health-related QoL [
20]. Methodologically, including patients receiving active treatment would have introduced a major confounding factor, making it difficult to distinguish the effects of stoma-related challenges and psychosocial adaptation from the acute systemic burden of adjuvant therapy. Accordingly, this study focused on patients in the early postoperative recovery phase who were not concurrently exposed to the substantial physiological and psychological burdens of active anticancer treatment.
The required sample size was calculated using G*Power ver. 3.1.9.2 [
17]. For multiple linear regression analysis, a medium effect size (f²=0.15), a significance level of .05, a statistical power of .95 [
18], and four predictor variables were specified, yielding a minimum required sample size of 129. After allowing for a 10% potential non-response rate, the target sample size was set at 142. A total of 142 questionnaires were distributed, and all were returned with complete data, resulting in a response rate of 100%.
The instruments used in this study, including the Chinese-language versions, were employed with permission from the original authors. Participants’ general characteristics included age, sex, marital status, education level, employment status, residence, household composition, monthly household income, the method of paying medical expenses, cancer stage, tumor location, postoperative period, surgical method, type of stoma, and postoperative complications.
1) City of Hope Quality of Life-Ostomy Questionnaire
The City of Hope Quality of Life-Ostomy Questionnaire was originally developed by Grant and Davis [
21] to assess QoL across four domains: physical, psychological, social, and spiritual. The Chinese version, translated and validated by Gao et al. [
22], consists of 32 items rated on an 11-point Likert scale ranging from 0 to 10. Each item is scored from 0 to 10, with higher total scores indicating better QoL. Negatively worded items were reverse-coded before analysis. The overall QoL score calculated as the mean of all items. Cronbach’s α for the scale was .95 in the study of Gao et al. [
22] and .93 in the present study.
2) General Self-Efficacy Scale
The General Self-Efficacy Scale was originally developed by Schwarzer and Jerusalem [
23]. The Chinese version, translated and adapted by Zhang and Schwarzer [
24], retains the original structure and has shown good reliability. The scale consists of 10 items rated on a 4-point Likert scale ranging from “not at all true” (1 point) to “exactly true” (4 points). Total scores range from 10 to 40, with higher scores indicating greater self-efficacy. Cronbach’s α for the scale was .91 in the original study [
24] and .79 in the present study.
3) Perceived Social Support Scale
The Perceived Social Support Scale was developed by Zimet et al. [
25] and translated into Chinese by Jiang. It consists of 12 items measuring support from three sources: family, friends, and significant others. Each item is rated on a 7-point Likert scale ranging from “strongly disagree” (1 point) to “strongly agree” (7 points). Total scores range from 12 to 84. For descriptive purposes and to facilitate clinical interpretation, total scores were categorized as low (12–36), moderate (37–60), or high (61–84), based on categorizations used in prior studies involving Chinese patient populations [
26]. Higher scores indicate greater perceived social support. Cronbach’s α for the scale was .84 in the study of Zhang et al. [
26] and .87 in the present study.
4) Brief Illness Perception Questionnaire
The Brief Illness Perception Questionnaire was developed by Broadbent et al. [
27] to assess cognitive and emotional representations of illness. The Chinese version, validated by Mei et al. [
28], consists of nine items. Items 1 to 8 are rated on a scale from 0 to 10, with higher scores indicating more negative perceptions; among these, items 3, 4, and 7 are reverse-coded. Item 9 is an open-ended question asking patients to list the perceived causes of their illness. Total scores range from 0 to 80, with higher scores reflecting more negative illness perceptions overall. Cronbach’s α for the scale was .77 in the study of Mei et al. [
28] and .80 in the present study.
5) Connor-Davidson Resilience Scale
The Connor-Davidson Resilience Scale was developed by Connor and Davidson [
29] and adapted into Chinese by Yu and Zhang [
30] through forward-backward translation. The scale contains 25 items across three domains: tenacity (13 items), strength (8 items), and optimism (4 items). Each item is rated on a 5-point Likert scale ranging from “not true at all” (0 points) to “true nearly all the time” (4 points). Total scores range from 0 to 100, with higher scores indicating greater resilience. Cronbach’s α for the scale was .91 in Yu and Zhang’s study [
30] and .89 in the present study.
Data were collected between April and September 2024 in the outpatient departments of the First Affiliated Hospital of Wenzhou Medical University, China. Before the study began, ethical approval was obtained from Burapha University and the hospital’s Institutional Review Board.
Each day, a complete list of patients attending the colorectal and anal surgery outpatient clinic was generated from the hospital’s electronic medical record system. This list served as the sampling frame. Trained clinical staff screened patients against the predefined inclusion and exclusion criteria, and all eligible patients were approached and informed about the study. Those who expressed an initial willingness to participate were included on the daily eligibility list.
Simple random sampling was then applied to the list of eligible patients. Specifically, each eligible patient was assigned a unique numerical identification code. A computerized random number generator, specifically the Microsoft Excel RAND function, was used by the researcher to select approximately 50% of eligible patients each day for study enrollment. This procedure ensured that each eligible patient had an equal and known probability of selection, thereby supporting probability-based sampling and population inference.
The researcher then contacted the randomly selected patients in person in the outpatient clinic, provided a detailed explanation of the study, obtained written informed consent, and administered the self-report questionnaires. Recruitment was conducted consecutively using the same procedure until the predetermined sample size of 142 participants was reached.
5. Ethical Considerations
The study protocol was approved by the Institutional Review Board (IRB) of Burapha University in Thailand (No. G-HS117/2566) and the First Affiliated Hospital of Wenzhou Medical University in China (No. KY2024-003). All participants were fully informed about the study’s purpose, procedures, potential risks and benefits, and their right to withdraw at any time without penalty. Written informed consent was obtained from each participant before data collection. All consent forms were submitted to the IRBs upon completion of the study. The collected data were anonymized, assigned unique identification codes, and stored in encrypted electronic files. All data will be securely retained for three years after study completion and then permanently deleted.
6. Data Analysis
Data were analyzed using IBM SPSS ver. 27.0.1 (IBM Corp., Armonk, NY, USA). Descriptive statistics were used to summarize participant characteristics and study variables. Differences in QoL according to categorical variables were examined using the independent t-test or one-way analysis of variance (ANOVA) with the Games-Howell post-hoc test, as appropriate. Pearson correlation coefficients were calculated to assess bivariate associations among continuous variables.
Before the predictor analysis, all assumptions for multiple regression were examined. Normality of the residuals was supported by the Shapiro-Wilk test (p=.932) and visual inspection of the Q-Q plot, which showed close alignment with the 45° reference line. Homoscedasticity was confirmed using the Breusch-Pagan test (p=.566), and residual scatterplots indicated a random and uniform distribution. The Durbin-Watson statistic (1.61) suggested independence of residuals. In addition, variance inflation factor values ranged from 1.00 to 1.08, indicating no evidence of multicollinearity.
Hierarchical multiple regression analysis was conducted to examine factors associated with QoL among CRC patients with a stoma. Variables that showed significant associations with QoL in univariate analyses (p<.05) were considered potential covariates and entered in the first block of the model to control for their effects. Categorical variables were dummy-coded before analysis, with appropriate reference categories specified.
RESULTS
1. Participant General Characteristics
Most participants (88.8%) were 51 to 60 years of age, with a mean age of 56.15 years (standard deviation [SD]=6.51). The majority were male (67.6%), married (93.0%), had completed primary education (62.8%), and were unemployed (45.7%). The most common monthly household income category was 2,000 to 3,999 Renminbi (31.6%). In terms of clinical characteristics, 55.7% had stage III CRC, and 73.9% had rectal cancer. Most participants (64.1%) were within 1 to 2 months after surgery, and 57.0% had a temporary stoma. Postoperative complications were reported by 6.3% of the participants.
Differences in QoL according to general characteristics were statistically significant only for the method of paying medical expenses (F=5.40,
p=.006). Post-hoc comparisons using the Games-Howell test showed that participants who self-financed their medical expenses reported significantly lower QoL scores than those covered by medical insurance (
p<.05) or rural insurance (
p<.05). No significant difference was observed between the medical insurance and rural insurance groups (
Table 1).
As shown in
Table 2, the overall QoL score was 3.86 (SD=1.60) on a scale ranging from 0 to 10. This mean score was substantially below the midpoint of the scale (5.00), suggesting a generally low level of perceived QoL among the participants. This interpretation is further supported by the sub-dimension scores, as physical, social, and spiritual well-being all averaged below 4.0. Although the psychological well-being subscale score (5.14) was closer to the midpoint, it remained only modest. The developers of the Chinese version noted that a mean item score above 5 generally indicates at least moderate QoL [
22]. In the present sample, the overall mean item score (3.86) and most of the sub-dimension scores were below this threshold, collectively indicating compromised QoL during the early postoperative period.
Pearson correlation analysis was performed to examine the relationships among QoL, self-efficacy, social support, illness perceptions, and resilience. In addition, to assess the association between the categorical variable method of paying medical expenses and the continuous study variables, eta (η) coefficients were calculated from one-way ANOVA. As shown in
Table 3, self-efficacy (r=.38,
p<.001) and social support (r=.43,
p<.001) were significantly and positively correlated with QoL at a moderate level. Resilience also showed a weak positive correlation with QoL (r=.20,
p<.05). In contrast, illness perceptions were significantly and negatively correlated with QoL at a high level (r=−.70,
p<.001). Furthermore, the method of paying medical expenses was significantly associated with QoL (η=.27,
p<.01), indicating that patients with different payment methods had different QoL scores.
Hierarchical multiple linear regression analysis was conducted to identify factors associated with QoL among CRC patients with a stoma (n=142). The results are summarized in
Table 4. Variables that showed significant associations with QoL in univariate analyses (
p<.05) were considered candidate covariates. Among these, the method of paying medical expenses was identified as the only demographic variable meeting the inclusion criterion and was therefore entered as a control variable in the first block of the model after dummy-coding (reference category: medical insurance). Clinical variables such as type of stoma and surgical method were not included because they were not significantly associated with QoL in univariate analyses and showed limited variability within the sample; therefore, their inclusion was unlikely to contribute meaningfully to the explanatory power or stability of the model.
In model 1, the method of paying medical expenses was entered as a control variable. This model was statistically significant (F=5.40, p=.006) and accounted for 6.0% of the variance in QoL (R²=.07, adjusted R²=.06). Compared with patients covered by medical insurance, who served as the reference group, self-financed patients reported significantly lower QoL (β=−.21, p=.014), whereas rural insurance was not significantly associated with QoL (β=.13, p=.115).
In model 2, four psychosocial variables derived from the IFSMT, namely self-efficacy, social support, illness perceptions, and resilience, were added. The overall model was statistically significant and explained 70.0% of the variance in QoL (R²=.71, adjusted R²=.70). The addition of psychosocial variables produced a significant increase in explanatory power compared with model 1 (ΔR²=.64, F=54.56, p<.001).
In the final model, illness perceptions (β=−.61, p<.001), social support (β=.32, p<.001), resilience (β=.20, p<.001), and self-efficacy (β=.19, p<.001) were significantly associated with QoL. After adjustment for these psychosocial variables, the associations between method of paying medical expenses and QoL were no longer statistically significant (rural insurance: β=.06, p=.227; self-financed: β=−.07, p=.143). The standardized regression coefficients represent the expected change in QoL, expressed in SD units, associated with a one-standard-deviation increase in each predictor after adjustment for covariates. Illness perceptions showed the strongest association (β=−.61), indicating that a one-standard-deviation increase in negative illness perceptions was associated with an approximately 0.61-standard-deviation decrease in QoL. Similarly, higher levels of social support, resilience, and self-efficacy were associated with increases of 0.32, 0.20, and 0.19 SDs in QoL, respectively. These effect sizes correspond to small-to-moderate associations for self-efficacy and resilience and a moderate association for social support, suggesting that variation in these psychosocial factors is meaningfully related to patients’ perceived QoL during postoperative recovery.
Overall, psychosocial factors accounted for most of the variance in QoL during the early postoperative period, whereas the independent contribution of financial payment method diminished after these variables were taken into account.
DISCUSSION
This study aimed to identify factors associated with QoL in CRC patients with a stoma during the early postoperative period, defined as 1 to 6 months after surgery. Overall, the participants reported relatively low QoL, particularly in the physical and social domains, underscoring the substantial challenges faced during early recovery. Guided by the IFSMT, this study identified four psychosocial variables, illness perceptions, social support, resilience, and self-efficacy, as significant correlates of QoL.
The strong association between illness perceptions and QoL highlights the central role of cognitive appraisal in postoperative adaptation. Patients who perceived their condition as less threatening and more controllable reported better QoL, consistent with previous findings in cancer and chronic illness populations [
15,
31,
32]. In the present study, the predominance of married participants and the availability of family support may have contributed to more adaptive illness representations by providing reassurance and practical assistance. These findings suggest that maladaptive illness perceptions are closely associated with poorer perceived QoL. However, because of the cross-sectional design, the direction of this relationship cannot be determined.
Social support emerged as the second strongest predictor of QoL, consistent with earlier studies [
14,
33]. In this study, social support was derived primarily from spouses and immediate family members, underscoring the central role of the proximal social network during early recovery. This pattern is consistent with the IFSMT framework, which identifies contextual factors such as social support as foundational to the self-management process [
9]. At the same time, the concentration of support within the family may suggest a limited breadth of social resources. The univariate association between method of paying medical expenses and QoL further suggests that material and social resources are intertwined and that financial strain may reduce patients’ capacity to benefit fully from available support.
Resilience and self-efficacy also showed significant, although relatively modest, associations with QoL. Patients with greater resilience appeared to adapt better to stoma-related challenges, consistent with findings reported by Franjic et al. [
16], whereas greater self-efficacy was associated with a stronger sense of competence in daily self-management, in line with previous studies by Xu et al. [
11,
12]. Although the correlations among social support, resilience, and self-efficacy were modest, each construct remained independently significant in the regression model. This pattern suggests that these variables represent conceptually distinct yet complementary components of postoperative adaptation. Social support reflects external contextual resources that provide emotional reassurance and practical assistance [
14]; self-efficacy reflects patients’ task-specific confidence in managing stoma care and daily activities [
11]; and resilience reflects broader emotional regulation and the ability to recover from stress [
16]. Within the IFSMT framework, these resources operate through different mechanisms (i.e., environmental facilitation, behavioral self-regulation, and emotional coping), thereby contributing unique explanatory value even when their bivariate associations are relatively weak [
9]. This distinction helps explain why all three variables independently predicted QoL and underscores the importance of addressing multiple psychosocial domains when designing supportive interventions.
Among the demographic and clinical characteristics, only the method of paying medical expenses was associated with QoL in the univariate analysis, and this association weakened after adjustment for psychosocial variables. Self-financed patients reported poorer QoL, reflecting the continuing financial burden of stoma care, including the costs of appliances and follow-up services. This finding is consistent with evidence linking out-of-pocket medical expenditures to reduced QoL in populations with chronic illness [
32]. In contrast, clinical variables such as stoma type and surgical method were not associated with QoL and did not provide additional explanatory value in the multivariable models. This pattern suggests that, during the early postoperative phase, subjective appraisal and psychosocial resources may have a stronger relationship with perceived well-being than biomedical characteristics, especially in relatively homogeneous clinical samples.
The large proportion of variance explained by the psychosocial model should be interpreted cautiously. Although the adjusted R² is comparable to, or slightly higher than, that reported in similar psychosocial studies of cancer-related QoL [
12,
31], explaining nearly 70% of the variance with four predictors represents a substantial effect in practical terms. Importantly, the QoL instrument used in this study focused on patients’ experiences of living with a stoma and did not include items directly assessing social support, self-efficacy, or resilience, suggesting that the findings are unlikely to be explained simply by content overlap among the measures. Rather, the strong associations observed may reflect the central role of psychosocial adaptation processes in shaping perceived QoL during the early postoperative period, as proposed by the IFSMT framework.
From a clinical perspective, these findings identify several actionable targets for nursing and multidisciplinary interventions. Early postoperative care should include structured psychoeducation and cognitive-behavioral strategies to address maladaptive illness perceptions [
15]. Family-inclusive approaches, including training in basic stoma care and supportive communication, may strengthen effective social support [
14]. Skills-based training programs supported by visual aids and supervised practice may enhance self-efficacy [
11], whereas brief counseling focused on stress management and adaptive coping may help foster resilience [
16]. Integrated intervention models that extend from hospital discharge to community follow-up may be particularly beneficial for improving QoL during this vulnerable period [
7].
Several limitations should be considered when interpreting these findings. First, the cross-sectional design precludes causal inference regarding the relationships between psychosocial factors and QoL. Second, excluding patients who were receiving chemotherapy or radiotherapy may limit the generalizability of the results to individuals with a greater disease burden or more complex treatment trajectories. Third, although simple random sampling was used, recruitment through outpatient clinics and voluntary participation may still have introduced selection bias. Fourth, restricting the sample to patients aged 60 years and younger limits the applicability of the findings to older populations, who may differ in psychosocial resources and adaptation patterns. Finally, the exclusive use of self-reported measures raises the possibility of recall and social desirability bias. Future longitudinal, multicenter studies that incorporate objective indicators and broader patient populations are needed to clarify causal pathways and longer-term QoL trajectories following stoma surgery.
CONCLUSION
This study found that CRC patients with a stoma experienced compromised QoL during the early postoperative period, particularly in the physical and social domains. Illness perceptions, social support, resilience, and self-efficacy were strongly associated with QoL and together accounted for a substantial proportion of its variability, highlighting the central role of psychosocial adaptation during this phase of recovery. These findings underscore the importance of moving beyond a purely biomedical focus in postoperative care. Nursing interventions should include strategies to modify maladaptive illness perceptions, strengthen family and social support, enhance patients’ confidence in stoma self-management, and promote psychological resilience. Early, structured, and family-inclusive psychosocial support may be especially beneficial in improving patients’ perceived well-being after stoma surgery. Future research using longitudinal and multicenter designs is needed to clarify the temporal relationships among psychosocial factors and QoL and to evaluate the effectiveness of theory-based, integrated intervention programs tailored to this vulnerable patient population.
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CONFLICTS OF INTEREST
The authors declared no conflict of interest.
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AUTHORSHIP
Study conception and design acquisition - BY, CCOP, and PH; data collection - BY, CCOP, and PH; analysis and interpretation of the data - BY, CCOP, and PH; drafting and critical revision of the manuscript - BY, CCOP, and PH; final approval of the version to be published - BY, CCOP, and PH.
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FUNDING
This research was funded through a graduate research grant provided by Burapha University, Thailand.
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ACKNOWLEDGEMENT
This article is a condensed form of the Bicong Yang’s master’s thesis from Burapha University. The author thanked the participants in this study and the nurse managers who supported the data collection process.
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DATA AVAILABILITY STATEMENT
The data can be obtained from the corresponding authors.
Table 1.Univariate Analysis of Quality of Life (N=142)
|
Variables |
Categories |
n (%) or M±SD |
Quality of life |
t or F (p) |
|
M±SD |
|
Age (year) |
31–40 |
9 (6.3) |
4.29±1.86 |
0.92 (.400) |
|
41–50 |
7 (4.9) |
3.20±1.55 |
|
51–60 |
126 (88.8) |
3.87±1.58 |
|
56.15±6.51 |
|
|
Sex |
Male |
96 (67.6) |
3.86±1.56 |
–0.04 (.965) |
|
Female |
46 (32.4) |
3.87±1.69 |
|
Marital status |
Married |
132 (93.0) |
3.84±1.59 |
–0.50 (.615) |
|
Others†
|
10 (7.0) |
4.11±1.79 |
|
Education level |
Illiteracy |
7 (4.9) |
4.79±1.51 |
1.99 (.099) |
|
Primary school |
89 (62.8) |
3.96±1.63 |
|
Secondary school |
32 (22.5) |
3.27±1.45 |
|
High school |
9 (6.3) |
3.93±1.56 |
|
Diploma or higher |
5 (3.5) |
4.46±1.48 |
|
Employment status |
Unemployed |
65 (45.7) |
4.02±1.61 |
0.90 (.464) |
|
Retirement |
39 (27.5) |
3.63±1.54 |
|
Self-employed |
22 (15.5) |
3.74±1.61 |
|
Farmer |
14 (9.9) |
3.75±1.76 |
|
Officer |
2 (1.4) |
5.45±0.77 |
|
Residence |
In Wenzhou |
131 (92.3) |
3.88±1.60 |
0.46 (.648) |
|
Not in Wenzhou |
11 (7.7) |
3.65±1.63 |
|
Household composition |
Husband or wife |
126 (88.8) |
3.84±1.60 |
0.21 (.810) |
|
Sons and daughters |
11 (7.7) |
3.83±1.68 |
|
Others‡
|
5 (3.5) |
4.32±1.76 |
|
Monthly household income in RMB (7 RMB=1 USD) |
Less than 2,000 |
12 (8.5) |
4.41±1.65 |
0.75 (.585) |
|
2,000 to 3,999 |
45 (31.6) |
3.94±1.55 |
|
4,000 to 5,999 |
42 (29.5) |
3.64±1.51 |
|
6,000 to 7,999 |
16 (11.3) |
3.65±1.75 |
|
8,000 to 9,999 |
14 (9.9) |
3.62±1.88 |
|
More than 10,000 |
13 (9.2) |
4.28±1.55 |
|
Method of paying medical expenses§
|
Medical insurancea
|
61 (43.0) |
3.70±1.59 |
5.40 (.006) (a>c, b>c) |
|
Rural insuranceb
|
76 (53.5) |
4.12±1.56 |
|
Self-financedc
|
5 (3.5) |
1.90±0.46 |
|
Cancer stage |
Stage I |
31 (21.8) |
3.71±1.61 |
0.65 (.524) |
|
Stage II |
32 (22.5) |
3.67±1.74 |
|
Stage III |
79 (55.7) |
4.00±1.54 |
|
Location of tumor |
Colon |
37 (26.1) |
3.81±1.62 |
–0.23 (.819) |
|
Rectum |
105 (73.9) |
3.88±1.60 |
|
Postoperative date (month)ǁ
|
1 to <2 |
91 (64.1) |
3.82±1.61 |
0.21 (.933) |
|
≥2 to <3 |
16 (11.3) |
4.02±1.60 |
|
≥3 to <4 |
9 (6.3) |
4.10±1.75 |
|
≥4 to <5 |
9 (6.3) |
3.53±1.49 |
|
≥5 to <6 |
17 (12.0) |
3.96±1.64 |
|
Surgical method |
Colostomy |
69 (48.6) |
4.04±1.65 |
1.29 (.279) |
|
Ileostomy |
70 (49.3) |
3.72±1.54 |
|
Small bowel stoma |
3 (2.1) |
2.86±1.51 |
|
Type of stoma |
Temporary stoma |
81 (57.0) |
3.70±1.56 |
–1.41 (.160) |
|
Permanent stoma |
61 (43.0) |
4.08±1.64 |
|
Postoperative complications |
No |
133 (93.7) |
3.82±1.60 |
–1.07 (.285) |
|
Yes |
9 (6.3) |
4.41±1.48 |
Table 2.QoL Levels among the Participants (N=142)
|
Variables |
M±SD (range) |
|
Overall QoL |
3.86±1.60 (0–6.0) |
|
Physical well-being |
3.91±2.05 (0–8.2) |
|
Social well-being |
2.44±1.87 (0–6.3) |
|
Psychological well-being |
5.14±1.63 (0–8.0) |
|
Spiritual well-being |
3.43±1.52 (0–6.8) |
Table 3.Correlations among Study Variables (N=142)
|
Variables |
1 |
2 |
3 |
4 |
5 |
|
r |
|
1. Self-efficacy |
1 |
|
|
|
|
|
2. Social support |
.08 |
1 |
|
|
|
|
3. Illness perceptions |
–.24**
|
–.13 |
1 |
|
|
|
4. Resilience |
.03 |
.02 |
.04 |
1 |
|
|
5. Quality of life |
.38***
|
.43***
|
–.70***
|
.20*
|
1 |
|
6. Method of paying medical expenses (η) |
.17 |
.15 |
.10 |
.20 |
.27**
|
Table 4.Hierarchical Multiple Linear Regression Model Predicting Quality of Life (N=142)
|
Variables |
Categories |
Model 1 |
Model 2 |
|
B |
SE |
β |
t |
p
|
B |
SE |
β |
t |
p
|
|
Constant |
|
3.70 |
0.20 |
- |
18.62 |
<.001 |
2.73 |
0.38 |
- |
7.28 |
<.001 |
|
Method of paying medical expenses |
1. Medical insurance (ref) |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
|
2. Rural insurance |
0.42 |
0.27 |
.13 |
1.59 |
.115 |
0.19 |
0.15 |
.06 |
1.21 |
.227 |
|
3. Self-financed |
–1.80 |
0.72 |
–.21 |
–2.49 |
.014 |
–0.63 |
0.43 |
–.07 |
–1.47 |
.143 |
|
Self-efficacy |
- |
- |
- |
- |
- |
0.34 |
0.09 |
.19 |
3.91 |
<.001 |
|
Social support |
- |
- |
- |
- |
- |
0.02 |
<0.01 |
.32 |
6.72 |
<.001 |
|
Illness perceptions |
- |
- |
- |
- |
- |
–0.04 |
<0.01 |
–.61 |
–12.65 |
<.001 |
|
Resilience |
- |
- |
- |
- |
- |
0.01 |
<0.01 |
.20 |
4.13 |
<.001 |
|
R² |
.07 |
.71 |
|
Adjusted R² |
.06 |
.70 |
|
F |
5.40 |
54.56 |
|
p
|
.006 |
<.001 |
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