Factors Influencing Coping Strategies of Women with Advanced Gynecolog

Introduction

Ovarian, endometrial, cervical, vaginal, and vulvar cancers are categorized as Gynecological Cancers (GC).¹ The largest number of estimated new cancer cases among GC in both the US and Korea was endometrial, followed by ovarian and cervical cancer.^2,3 The overall five-year survival rate of endometrial cancer is 81%; however, the five-year relative survival for distant metastasis was relatively low, at 18%.² The five-year relative survival rate for ovarian cancer is about 50% because more than 70% of ovarian cancers are diagnosed at stage III or IV.² The five-year relative survival rate of cervical cancer is 67%, and that of the early stage is more than five times higher than that of the advanced stage.²

Women with advanced GC receive various treatments and experience a low quality of life.^4–6 They often experience disease-related symptoms and side effects such as anemia, indigestion, and neuropathy.⁵ People with advanced cancer also fear cancer progression, upcoming pain, and death because of an uncertain prognosis.^7,8 Due to these significant physical symptoms and psychosocial burdens, advanced cancer is an existential threat and a major stressor for affected patients.⁹

Coping Strategies (CS) refer to constantly changing cognitive and behavioral means to manage specific external or internal needs generated by stressful events evaluated to exceed an individual’s resources.¹⁰ People with advanced cancer use various CS when faced with stressors.¹¹ Classifying and organizing CS have been major research topics.¹² Carver et al have developed a list of CS and aimed to confirm their usefulness.¹³ They suggested 14 distinct CS using elements of Lazarus and Folkman’s stress and coping model¹⁰ and Carver and Sheier’s self-regulation model.¹⁴ They are often categorized into three groups: Problem-focused Coping Strategies (PCS), Active Emotional Coping Strategies (Active ECS), and Avoidant Emotional Coping Strategies (Avoidant ECS).¹⁵ Specific CS are related to overall quality of life, including mental aspects such as depression and anxiety.¹¹ The use of PCS and Active ECS correlated positively with quality of life.^15,16 On the other hand, the use of Avoidant ECS negatively affected the quality of life.¹⁷

Previous studies have dealt with CS and the relationship between CS and quality of life in women with GC.^18,19 In addition, earlier studies focused on the CS used by patients with advanced cancer and factors influencing the chosen CS.^11,20 However, studies on CS used by women with advanced GC and the factors affecting the CS are limited.

Conceptual Framework

The Stress Adaptation Model by Stuart can provide an overview of the care process through predisposing factors, precipitating stressors, appraisal of stressors, coping resources, and coping mechanisms.²¹ The present study considered factors that affect CS based on the Stress Adaptation Model (Figure 1). This study modeled demographic characteristics as predisposing factors, clinical characteristics as precipitating stressors, and uncertainty as appraisal of stressors. In addition, three categories of CS are evaluated as a series of adaptive and maladaptive responses.

Figure 1 Conceptual framework of the study based on the Stress Adaptation Model by Stuart. Predisposing factors, precipitating stressors, appraisal of stressors, and coping strategies were arranged according to flow. The continuum of coping responses was evaluated as adaptive and maladaptive.

The purpose of the study was to identify the factors influencing CS in women with advanced GC. The specific aims were: 1) to determine if there are variations in the frequency of use of the 14 CS based on demographic and clinical characteristics, and 2) to ascertain whether there are differences in the frequency of use of the three categories of CS—PCS, Active ECS, and Avoidant ECS—based on demographic characteristics, clinical characteristics, and uncertainty.

Methods

Study Design

This study analyzed secondary data from a cross-sectional survey that examined the mediating effect of CS on the relationship between uncertainty and quality of life in women with GC.²²

Data Source

As a secondary data analysis study, this research used data. There was no missing data in the 143 data sets. The purpose of the original study was to investigate how CS mediated the association between quality of life and uncertainty in Korean women with GC. However, the goal of the current study was to focus more specifically on the variables influencing CS in women with advanced GC. Therefore, questionnaire items related to demographic and clinical characteristics, uncertainty, and CS were analyzed, while items assessing quality of life were excluded. The data for the present study were collected from a previous cross-sectional study performed between October and December 2022 with 165 participants at the Department of Gynecology at Hospital A, a tertiary medical institution in Seoul.²² The original data used in this study were informed of consent from study participants according to the guidelines set out in the Helsinki Declaration and approved by the Institutional Review Board of Asan Medical Center (S2022-2082-0001). Women to be included in the secondary data analysis were selected based on a diagnosis of GC in stage III or stage IV. A total of 143 participants were investigated. The statistical power analysis program G*POWER version 3.1.5 was used to determine whether the number of participants met the minimum sample size. The minimum required sample size was 139 to maintain a power level of 0.80, a medium effect size of 0.15, and a significance level α of 0.05 for multiple regression analysis.

Measurements

Uncertainty in Illness

The Mishel Uncertainty in Illness Scale (MUIS-A), developed based on disease uncertainty in illness theory, was administered to measure illness uncertainty.²³ This instrument has 33 items rated on a five-point Likert scale that ranges from strongly agree (5 points) to strongly disagree (1 point). The higher is the score, the greater is the degree of illness uncertainty. The Cronbach’s alpha in a study by Mishel was 0.91 to 0.93,²³ compared to 0.85 in a study conducted by Chung et al.²⁴ In the present study, the translated Korean version of the MUIS-A showed a Cronbach’s alpha of 0.89.

Coping Strategies

The participants’ CS were assessed using the Brief Coping Orientation to Problems Experienced (Brief COPE) survey.²⁵ This instrument has 28 items rated on a four-point Likert scale that ranges from “I haven’t been doing this at all” (1 point) to “I’ve been doing this a lot” (4 points). The Brief COPE was selected to measure CS, as it has the advantage of containing 14 different CS. Higher scores indicate a higher tendency to use the corresponding CS. The Cronbach’s alpha of the 14 sub-scales in a study by Carver ranged from 0.5 to 0.9,²⁵ and that in a study by Kim ranged from 0.52 to 0.96.²⁶ In the present study, 14 CS were grouped into three categories: PCS including active coping, planning, instrumental support, and religion; Active ECS including venting, positive reframing, humor, acceptance, and emotional support; Avoidant ECS including self-distraction, denial, behavioral disengagement, self-blame, and substance use.¹⁵ In this study, the translated Korean version of the Brief COPE showed a Cronbach’s alpha from 0.69 to 0.84.

Data Analysis

The analyses were conducted using IBM SPSS Statistics software Version 25.0 (IBM, Armonk, NY, USA). First, descriptive data were analyzed according to mean, standard deviation, frequency, and percentage. Second, differences in the frequency of use of 14 CS depending on demographic and clinical characteristics were analyzed through t-test and ANOVA. Third, the influences of demographic characteristics, clinical characteristics, and uncertainty on the tendency to use three categories of CS (PCS, Active ECS, Avoidant ECS) were analyzed through multiple linear regression. Simple linear regression was used to confirm whether these factors affected each of the three categories of CS. Then multiple linear regression was conducted using all significant factors from the simple linear regression. Multiple linear regression was used to identify the potential factors associated with the three categories of CS. A significant amount of linear intercorrelation between explanatory variables is represented by the multicollinearity, which is absent from the regression model as the variance inflation factor is lower than 10.²⁷

Results

Characteristics, Uncertainty, and Coping Strategies of the Participants

The participant characteristics, uncertainty and CS are shown in Tables 1 and 2. The demographic data indicated that 67.2% of the participants were in their 50s or 60s, 81.8% were married, and 79.7% were unemployed. Most participants were in the middle subjective economic level (74.1%) and were high school graduates or above (72.8%). Of the participants, 55.2% identified as religious. Analysis of the clinical data indicated that 63.6% of participants had one or more comorbidities and 58.7% had ovarian cancer. Most participants experienced recurrence (60.1%) and metastases (75.5%). Regarding treatment experience, 70.6% underwent both surgery and chemotherapy. Of those participating in the study, 48.3% had been diagnosed for fewer than two years and 28.0% for more than four years. The mean score of uncertainty was 94.80 (SD = 14.05). The scores of the 14 CS were as follows. The three most used CS were acceptance, positive reframing, and self-distraction. The mean score of acceptance was 6.24 (SD = 1.22), positive reframing was 6.16 (SD = 1.76), and self-distraction was 5.98 (SD = 1.91). On the other hand, the least used CS was substance use, with a mean score of 2.03 (SD = 0.33).

Table 1 Demographic and Clinical Characteristics of the Participants

Table 2 Uncertainty and Coping Strategies of the Participants

Demographic and Clinical Characteristics Influencing the 14 Coping Strategies

Table 3 shows the differences in PCS according to demographic and clinical characteristics. Among the four sub-scales, there were significant differences in active coping, planning, and religion. Significant factors in active coping and planning were age, education, religion, comorbidity, and treatment experience. Participants in their 70s were less likely to use active coping (p <0.01) and planning (p <0.001) than those in their 40s. Compared to participants who were middle school graduates or below, those who had undergraduate degrees or above more frequently used active coping and planning (p <0.001). Participants who identified as Christian tended to use more active coping and planning than those who identified as Buddhist (p <0.01). Those who had one or more comorbidities were less likely to use active coping and planning than those who did not (p <0.001). Those who experienced both surgery and chemotherapy more frequently used active coping (p <0.05) and planning (p <0.01) compared to those who experienced only chemotherapy. Regarding religion, significant factors were education and subjective economic level. The participants who were undergraduates or above tended to use more religious coping than those who were elementary school graduates or below (p <0.01). Those in the higher subjective economic level were likely to use more religious coping than those in the lower (p <0.05).

Table 3 Differences in Problem-Focused Coping Strategies According to Demographic and Clinical Characteristics

The Table 4 shows the differences in Active ECS and Avoidant ECS according to demographic and clinical characteristics. Among the five sub-scales of Active ECS, there were significant differences in positive reframing and acceptance. Regarding positive reframing, a significant factor was subjective economic level. Participants in the higher subjective economic level tended to more frequently use positive reframing than those in the lower (p <0.05). Regarding acceptance, significant factors were education, subjective economic level, comorbidity, and recurrence. Compared to others, those who were elementary school graduates or below used acceptance less frequently (p <0.001). Those in the higher subjective economic level more frequently used acceptance than those in the middle, and those in the middle more frequently used acceptance than those in the lower (p <0.001). Those who had one or more comorbidities were less likely to use acceptance than those who did not (p <0.01). Those who experienced recurrence tended to use acceptance more frequently than those who did not (p <0.05).

Table 4 Differences in Active Emotional and Avoidant Emotional Coping Strategies According to Demographic and Clinical Characteristics

Among the five sub-scales of Avoidant ECS, there were significant differences in behavioral disengagement. The significant factors were subjective economic level and lymphedema. Compared to other participants, those in the higher subjective economic level tended to use less frequent behavioral disengagement than those in the lower and middle levels (p <0.01). Those with lymphedema were more likely to use more behavioral disengagement than those who did not (p <0.05).

Factors Influencing the Three Categories of Coping Strategies

In Table 5, the use of CS was influenced by various factors including demographic characteristics, clinical characteristics, and uncertainty. Regarding PCS, there were significant differences according to education, religion, and uncertainty. The use of PCS by those with elementary school degrees or below versus those with undergraduate degrees or above differed significantly (β = 0.353, p <0.05). There were significant differences in the use of PCS by Christian and non-religious participants (β = 0.330, p <0.001). There were negative relationships between PCS and uncertainty (β = −0.256, p <0.01). The regression model was statistically significant (F: 8.133, p <0.001), and the explanatory power of the model was 39.5% (R²: 0.450, R² adjusted: 0.395). Regarding Active ECS, there was a significant difference according to uncertainty. There was a negative association between Active ECS and uncertainty (β = −0.394, p <0.001). The regression model was statistically significant (F: 4.669, p <0.001), and the explanatory power of the model was 20.5% (R²: 0.261, R² adjusted: 0.205). Regarding Avoidant ECS, there was a significant difference according to uncertainty. There was a positive relationship between Avoidant ECS and uncertainty (β = 0.434, p <0.001). The regression model was statistically significant (F: 6.379, p <0.001), and the explanatory power of the model was 21.0% (R²: 0.249, R² adjusted: 0.210).

Table 5 Factors Influencing Three Categories of Coping Strategies

Discussion

Based on the Stress Adaptation Model, this study identified adaptive or maladaptive CS used by women with advanced GC and evaluated the factors influencing CS. The study provided insight into the provision of interventions to help women with advanced GC use adaptive CS.

Demographic and Clinical Characteristics Influencing the 14 Coping Strategies

Modifiable Variables

There were differences in active coping, planning, and acceptance depending on the participants’ level of education. Some previous studies suggested that patients with lower education levels were able to cope more effectively with stress, as they are more likely to believe in recovery and accept cancer and therapy more readily.²⁸ However, participants with less education used active coping and planning less frequently than those with higher levels of education in this study. Participants with higher levels of education were more likely to adopt effective stress-reduction strategies because they actively sought out opportunities to learn relevant information.²⁹

There were differences in positive reframing, acceptance, behavioral disengagement, and religion depending on the degree of participants’ subjective economic level. Women suffered financial burdens and distress in the long-term course of cancer treatment, and these economic constraints could be important considerations in choosing CS.^30,31

Non-Modifiable Variables

There were differences in CS depending on age, treatment experience, comorbidity, and lymphedema. Health providers should identify women with non-modifiable influencing factors associated with the use of maladaptive CS as a high-risk group and provide additional interventions.

In this study, older women with cancer used less frequent active coping and planning than younger women with cancer. Young women with breast cancer also perceived cancer as a challenge and took an active role in their treatment and recovery, while older women were more likely to experience hopelessness and helplessness when faced with cancer.³²

Participants who have undergone both chemotherapy and surgery often use more active coping and planning than those who have only undergone chemotherapy. Surgery is an important treatment method for women with advanced GC.⁶ However, women who did not undergo surgery due to a terminal stage or changes in their condition or those who received neoadjuvant chemotherapy only underwent chemotherapy.⁶ Even if chemotherapy reduced the cancer size, they felt anxious because they did not undergo surgery, which is considered an PCS.³³

Participants who had one or more comorbidities were less likely to use active coping, planning, and acceptance than those who did not. When experiencing new symptoms or deterioration, participants with one or more comorbidities were focused on diseases rather than health.³⁴ In this situation, they used avoidant ECS such as not thinking or crying to gain energy to withstand stressful situations.³⁴

Whether a person had lymphedema or not affected their level of behavioral disengagement. While patients with lymphedema in a previous study tended to adopt confrontation—a positive CS—the participants in the present study frequently employed behavioral disengagement, one of the avoidant ECS.³⁵ This difference may be attributed to the clinical characteristics of the participants in this study, who had advanced cancer and experienced more severe symptoms compared to those in the previous study, which included patients with lower stages of swelling and less pain. These differences appear to have influenced the choice of CS. Women with lymphedema felt uncomfortable due to swelling symptoms and changes in body image.³⁶ They used passive CS such as helplessness and depression to alleviate emotional damage.³⁶

Factors Influencing the Three Categories of Coping Strategies

There were differences in PCS depending on education, religion, uncertainty, and Active/Avoidant ECS depending on uncertainty. In this study, uncertainty affected the three groups of CS; the higher was the level of uncertainty, the more frequent was the Avoidant ECS, and the less frequent were the PCS and Active ECS. If the uncertainty was high, women with advanced GC more often used maladaptive CS that were negatively related to quality of life.¹⁷

Clinical Implications

The findings of this study provide valuable evidence for developing interventions by identifying factors that affect CS of women with advanced GC. First, health providers should educate women with lower levels of education on adaptive CS and their implementation. In this study, women with higher education levels more frequently used active coping, planning, and acceptance than those with lower education levels. To address this gap, healthcare providers can introduce participants with limited educational backgrounds to adaptive strategies such as Acceptance and Commitment Therapy and problem-solving skills training.^16,37 Education on adaptive CS may help these individuals better accept their condition, commit to value-based action, and improve self-management.^16,37

Second, policy managers should provide social support to reduce the economic burden of the patients, while health providers should connect financially distressed women with advanced GC to appropriate support services. In this study, women with lower perceived economic status demonstrated less frequent use of positive reframing and acceptance, and more frequent use of behavioral disengagement. To address this, policies aimed at reducing the financial burden of cancer care are needed. Healthcare providers may guide patients to available financial assistance services within clinics or cancer centers.³⁰

Third, health providers should identify women with non-modifiable influencing factors as a high-risk group and provide additional interventions. For high-risk groups, intensive interventions that encourage the early and sustained use of adaptive CS—such as acceptance, planning, and positive reframing—can reduce anxiety and depression and improve quality of life.³⁸ In addition, social support from family and health professionals can enhance the use of adaptive CS among these high-risk groups.²⁰

Fourth, uncertainty management interventions should be provided for women with advanced GC. The study found that women with higher levels of uncertainty were less likely to use PCS and Active ECS, and more likely to use Avoidant ECS. When individuals learn from their own experiences, cultural background, social resources, and medical professionals, their uncertainty can gradually decrease.²³ In addition to educating women with advanced GC, health providers should support women in evaluating their situations and help them gain autonomy and a sense of control in managing illness-related uncertainty.³⁹

Study Limitations

This study had several limitations. First, changes in CS over time and unique CS could not be observed because data were cross-sectional and quantitative. Future studies should explore how the use of different CS evolves throughout the course of cancer treatment and survivorship. In addition, incorporating qualitative data would help identify culturally specific CS that may not be captured through standardized instruments.

Second, the findings cannot be generalized as this study included a convenience sample of women with advanced GC from one tertiary medical center in Korea. While this study offers a valuable foundation for developing tailored interventions for women with advanced GC, its applicability to other cancer populations is limited. To reduce generalization bias, future research should include participants from hospitals of varying sizes and geographic regions. Additionally, further studies are needed to validate these findings across diverse populations, including individuals of different genders, nationalities, and cancer types.

Third, the study cannot identify all effects of factors affecting CS because this was a secondary analysis study using data collected for other studies. Future research should consider various factors that can affect CS based on the unique disease-related characteristics of women with advanced GC.

Conclusion

This study investigated the factors influencing CS used by women with advanced GC, based on the Stress Adaptation Model by Stuart. The findings revealed that acceptance, positive reframing, and self-distraction were most frequently employed, whereas substance use was the least. The statistically significant factors associated with the 14 CS were divided into modifiable (education and subjective economic level) and non-modifiable (age, treatment experience, comorbidity, and lymphedema) groups. The factor influencing all three groups of CS (PCS, Active ECS, and Avoidant ECS) was uncertainty.

Exploring and developing interventions that help women with advanced GC use adaptive CS should first identify factors associated with the CS. Considering the modifiable variables, health providers can provide educational programs and guide financial search services to women with lower education levels and subjective economic levels. In addition, considering the non-modifiable variables, health providers can perform intensive and individualized interventions by selecting women with variables that are highly related to maladaptive CS. Additionally, uncertainty management would be important when caring for women with advanced GC because uncertainty affected all three categories of CS.

Funding

There are no sources of funding for the original study.

Disclosure

The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.

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