The mediating role of medical coping modes between anxiety and fear of progression in patients with cervical intraepithelial neoplasia grade 3: a cross-sectional survey

Abstract

Background

Fear of progression (FOP) is a significant psychological burden among patients with cervical intraepithelial neoplasia grade 3 (CIN3) and negatively impacts their mental health and quality of life. This study aimed to explore the mediating role of medical coping modes in the relationship between anxiety and FOP in these patients.

Methods

This cross-sectional study included 168 patients with CIN3 from a university hospital in Nantong, China. The participants completed the FOP questionnaire, the self-rating anxiety (SAS) scale, and the medical coping modes questionnaire (MCMQ). Structural equation modeling (SEM) was used to analyze the mediating effects of medical coping modes (confrontation, avoidance, and resignation) on the relationship between anxiety and FOP.

Results

This study conducted an in-depth questionnaire survey and analysis of 168 patients with grade 3 CIN. The results revealed elevated scores on both the SAS and FOP scale, with 58.3% of patients exhibiting clinically significant FOP scores. With respect to medical coping styles, correlation analysis revealed that anxiety was significantly positively correlated with avoidance, resignation coping styles, and FOP scores (P < 0.05). Univariate analysis revealed trends toward significant differences in FOP scores based on disease duration and family history of cervical cancer. Multivariate logistic regression further confirmed that anxiety level (SAS) (OR = 1.11), avoidance coping (OR = 1.17), and resignation coping (OR = 1.26) were independent predictors of FOP (P < 0.05). Stratified analysis reinforced the stable associations between these predictors and FOP across different disease characteristics. The results of the mediation analysis revealed that resignation coping partially mediated the relationship between anxiety and FOP, whereas avoidance coping had no significant mediating effect. Finally, structural equation modeling validated the indirect pathway through which anxiety influences FOP through resignation coping.

Conclusion

Anxiety, avoidance, and resignation coping are significant predictors of FOP in patients with CIN3. Resignation coping plays a crucial mediating role in the relationship between anxiety and FOP. These findings suggest that targeted interventions addressing resignation coping may help reduce FOP and improve psychological well-being in these patients. Future research should explore longitudinal designs and culturally tailored interventions to further understand and mitigate FOP in this population. 

Supplementary Information

The online version contains supplementary material available at 10.1186/s40359-025-03323-6.

Introduction

According to the latest GLOBOCAN estimates released in 2025 by the International Agency for Research on Cancer, which were published via the Global Cancer Observatory at https://gco.iarc.who.int [1], there were an estimated 661,021 new cervical cancer cases globally in 2022, accounting for 3.3% of all cancer cases. Cervical cancer is one of the most common types of cancer in women and has the highest incidence rate among cancers in 157 countries. In the same year, cervical cancer resulted in approximately 348,189 deaths worldwide, accounting for 3.6% of all cancer deaths. It is the fourth leading cause of cancer death among women globally. The age-standardized incidence rate is 14.12 per 100,000, and the age-standardized mortality rate is 7.08 per 100,000. The incidence of cervical cancer varies significantly across regions. The highest incidence rates are found in sub-Saharan Africa and Melanesia, whereas the lowest rates are observed in North America, Australia, New Zealand, and Western Asia. Mortality rates also show similar geographical variations, with the highest rates in Melanesia, Micronesia/Polynesia, and regions of Eastern and Southern Africa [1]. According to the latest GLOBOCAN estimates released in 2025 by the IARC, in China, there were approximately 151,000 new cervical cancer cases and 56,000 deaths in 2022, with the number of deaths accounting for approximately one-sixth of the global cervical cancer deaths [2]. 

The primary etiology of cervical cancer is infection with human papillomavirus (HPV). The progression from HPV infection to invasive cervical cancer involves a distinct precancerous stage known as cervical intraepithelial neoplasia (CIN). According to the World Health Organization’s (WHO) 2003 publication, Pathology and Genetics of Tumors of the Breast and Female Genital Organs, the diagnostic criteria for CIN follow a histological classification system with a three-tier grading system (CIN grade 1, CIN grade 2, CIN grade 3) [3].

CIN grade 1 represents mild dysplasia and is classified as a low-risk lesion, with approximately 60% of CIN grade 1 cases regressing spontaneously, requiring only follow-up observation. CIN grade 2 indicates moderate dysplasia, with approximately 30% of cases potentially progressing to CIN grade 3. Management depends on the patient’s age and fertility requirements, involving either treatment or monitoring. CIN grade 3, characterized by severe dysplasia/carcinoma in situ (CIS), is associated with a 12–36% risk of progression to invasive carcinoma and typically requires surgical intervention (e.g., conization).

Patients at different stages of the disease face different pressures, resulting in many negative emotions that negatively affect their physical and mental health to varying degrees [4, 5]. In particular, CIN grade 3 patients face a high risk of malignant transformation [6], which induces fear, anxiety, and stigma [7, 8]. As a result, many patients with CIN grade 3 are chronically ill and very fearful of disease progression because cervical cancer threatens patients’ lives.

Background

Anxiety is an emotional state typically characterized by apprehension and fear regarding uncertain future events. It can serve as a normal, adaptive response that helps individuals cope with potential threats. However, when anxiety becomes excessive or persists for prolonged periods, it may develop into pathological anxiety, adversely affecting an individual’s daily life and mental health. The primary features of anxiety include excessive worry, tension, uneasiness, and uncertainty about the future. Among cancer patients, elevated psychological distress is commonly observed following diagnosis, particularly at the initiation of treatment, with stress levels significantly higher than those in healthy control groups. In the short term, anxiety is associated with reduced quality of life and decreased adherence to both treatment and follow-up care. In the long term, anxiety is positively correlated with cancer mortality rates [9].

According to Lazarus and Folkman’s stress and coping model [10], coping styles represent adaptive mechanisms through which individuals effectively manage, mitigate, or regulate the impact of stressors, involving dynamic cognitive and behavioral processes in response to traumatic life events [11]. These coping strategies are influenced by situational factors, individual differences, and external environmental conditions when facing stressful situations [11]. On the basis of their distinct characteristics and effects, coping styles can be categorized into three primary types: confrontation (problem-focused, adaptive), avoidance (threat-avoidant, maladaptive), and resignation (passive acceptance, maladaptive). The confrontation style is characterized by proactive and adaptive approaches where individuals directly address problems, actively seek solutions, and implement measures to reduce or eliminate stressors, thereby enhancing self-efficacy and confidence through behaviors such as seeking medical advice, joining support groups, and adhering to treatment regimens. In contrast, the avoidance style involves evasive strategies that temporarily alleviate stress by denying or avoiding stressors (e.g., skipping follow-ups, distraction, or minimizing severity), although this often exacerbates long-term psychological distress and amplifies anxiety-induced fear of progression (FOP). The resignation style reflects passive acceptance, where individuals relinquish control and submit to stressors without resistance, leading to diminished agency and motivation, as seen in cancer patients who adopt fatalistic beliefs (e.g., “nothing can be done”) and who discontinue treatment. Consequently, coping styles exhibit dual effects, exerting both positive and negative influences on cancer patients [12], with strategies aimed at managing stressor-related impacts to maintain psychological equilibrium and well-being.

FOP‌ refers to patients’ persistent fear of disease recurrence, deterioration, or metastasis [13]. Bultz et al. [14] proposed that psychological distress (including FOP) should be recognized as the “sixth vital sign” of cancer patients’ well-being, alongside respiration, body temperature, blood pressure, heart rate, and pain. Previous studies have confirmed that FOP is not only one of the most common distress symptoms among cancer patients but also one of the most prevalent yet unmet psychological needs [13]. Research indicates that approximately 50% of cancer survivors experience moderate-to-severe FOP, with its impact persisting from diagnosis through years of survivorship [15, 16]. In China, approximately 36% of adolescent and young adult cancer patients report FOP at functionally impairing levels [17]. FOP exerts multidimensional negative effects on cancer patients:

1. Psychological impact‌: FOP exacerbates mental health issues in cancer patients. Hall et al. [18] reported that FOP accounts for one-third of patients’ stress, undermining their motivation for cancer treatment and positive life outlook while significantly impairing their quality of life. Patients with elevated FOP are more prone to anxiety, depressive symptoms, and posttraumatic stress reactions [19, 20].

2. Behavioral consequences‌: Excessive worry or fear triggers maladaptive behaviors and cognitive‒emotional responses, including avoidance of follow-ups, frequent medical visits, reduced treatment adherence, and difficulties in future planning in severe cases, potentially increasing mortality risk [21–23].

3. Physiological effects‌: Severe FOP is correlated with sleep disturbances (e.g., difficulty falling/staying asleep), which may negatively affect recovery and immune function [24].

4. Socioeconomic burden‌: FOP prolongs hospitalization, increases medical costs, and substantially diminishes patients’ well-being [25].

Therefore, healthcare providers should promptly identify the psychological factors contributing to FOP development in cancer patients and implement interventions to alleviate fears and improve quality of life.

The associations among anxiety, coping styles, and FOP have been well documented in cancer patients.

1. Anxiety → FOP. Anxiety plays a pivotal role in the development and exacerbation of FOP, as cancer patients frequently experience heightened fears regarding disease progression. Dinkel et al. [21] demonstrated through multivariate linear regression analyses that anxiety symptoms remained significantly associated with FOP even after controlling for sociodemographic variables, clinical characteristics, and symptom burden, establishing anxiety as a key predictor of FOP. Their research further revealed that psycho-oncological interventions targeting FOP, particularly modern cognitive‒behavioral therapies focusing on cognitive processes (e.g., worry or rumination), were effective in managing these symptoms [21]. Consistent with these findings, Yang et al. [26] identified life stress, anxiety, depressive symptoms, and passive personality traits as independent predictors of elevated FOP levels. In support of this evidence, Tu et al. [27] reported a significant positive correlation (r = 0.344) between health anxiety metacognition (e.g., catastrophizing thoughts) and FOP in patients with advanced ovarian cancer, further validating the positive relationship between anxiety and FOP. These collective findings underscore the critical role of anxiety in the pathogenesis of FOP among oncology patients.

2. Anxiety → medical coping styles‌: Similar to general coping styles, medical coping modes are also grounded in the stress and coping model, which refers to the cognitive and behavioral approaches individuals adopt when facing disease- and treatment-related stressors [28]. These modes encompass various strategies and behaviors patients employ to manage health crises and disease conditions [29]. Among cancer patients, these modes range from active engagement (e.g., confrontation) to more passive responses (e.g., avoidance and resignation) [30]. When examining the impact of medical coping strategies on patient health, it is essential to consider not only the strategies themselves but also the underlying psychological factors. The efficacy of these strategies is closely tied to psychological variables, with anxiety serving as a critical determinant [31]. Prior studies have indicated that in breast cancer patients, anxiety triggers threat vigilance, leading to avoidance/resignation coping (e.g., skipping fertility preservation consultations), which subsequently elevates FOP [32]. Ma et al. [33] further demonstrated that in lung cancer patients, medical coping modes mediated 35.1% of the effect of stigma on quality of life, paralleling anxiety-driven pathways.

3. Medical coping styles → FOP‌. FOP is influenced by multiple factors. A recent systematic review of cancer patients indicated that a younger age at diagnosis, female sex, and higher education levels are associated with increased susceptibility to FOP compared with peers [34]. Meta-analytic evidence further reveals that mastectomy [35], radiotherapy [36], and chemotherapy [37] are significant predictors of elevated FOP in breast cancer patients. According to Lee and Jones’ [38] self-regulatory model of illness, individual coping styles may correlate with FOP intensity, where patients with heightened FOP often encounter psychological and social adaptation challenges post-surgery. Coping strategies have been consistently reported as critical determinants of FOP in oncology populations [38]. For example, Lengacher et al. [39] demonstrated that psychological factors (e.g., illness uncertainty) and coping mechanisms significantly influence FOP levels in breast cancer patients. Moreover, Tewes et al. [40] reported lower FOP levels among breast cancer patients when effective coping strategies were employed. In Cai et al.’s [41] study, avoidance/resignation coping styles were positively correlated with FOP severity, corroborating findings that passive coping mechanisms exacerbate FOP symptoms.

While current studies have employed correlation or regression analyses to examine the relationships among anxiety, coping styles, and FOP in cancer patients separately, no research has comprehensively investigated the interrelationships and interactions among these three constructs, particularly their dynamic influences on the psychological care of female cervical cancer patients. Traditional analytical methods can provide only simple bivariate associations without distinguishing direct effects from indirect effects or accounting for mediating mechanisms. Structural equation modeling (SEM) represents an advanced statistical approach capable of handling multiple independent and dependent variables simultaneously while elucidating the structural relationships among factors [42]. SEM enables effect decomposition, quantifying both direct effects (anxiety → FOP) and indirect effects (anxiety → coping styles → FOP), which aligns with the cascade pathway of “cognitive appraisal → coping strategies → emotional outcomes” in stress-coping theory [10] (Fig. 1A). Compared with conventional regression, SEM offers superior model evaluation through fit indices (e.g., Standardized root mean squared error [SRMR] and Root mean squared error of approximation [RMSEA]) that assess the overall model adequacy, a capability absent in simple regression models [43]. Furthermore, SEM generates standardized path coefficients (β) that directly reflect the effect sizes of intervention targets. While prior research has explored these relationships primarily in breast [32] and lung cancer [44] populations, the associations among anxiety, coping styles, and FOP in patients with grade 3 CIN remain to be elucidated. 

Fig. 1.

A Theoretical framework; B research hypothesis

Therefore, in this study, SEM was applied on the basis of stress coping theory and a literature review. These findings can be used to analyze the impact path and effects of anxiety and coping styles on FOP, which may allow clinical staff to better understand FOP in patients with CIN grade 3 and implement appropriate psychological interventions.

Theoretical framework

Lazarus and Folkman [10] proposed a stress and coping model based on modern stress theory. This model holds significant importance in the fields of psychology and medicine. This emphasizes that stress arises from the dynamic interaction between individuals and their environment rather than being solely induced by external stimuli. The model aids in comprehending how individuals perceive, assess, and cope with stressful events in life. According to Lazarus and Folkman’s [10] stress and coping theory, coping is a response to stressful events that cause distress. Patients use appropriate coping strategies to address the physical discomfort and psychological challenges associated with their disease effectively [45]. This theory classifies relevant variables into prevariables, moderators, and outcome variables [2]. The theoretical framework is shown in Fig. 1A.

Specifically, the stress response begins with an individual’s appraisal of a stressor event, which can serve as a prevariable that influences the outcome through the mediating effects of coping strategies. During the appraisal phase, the individual determines whether the stressor event is a threat (something that may cause harm), a challenge (something that can be overcome with effort), or irrelevant. In Lazarus and Folkman’s [10] stress and coping theory, problem-focused coping and emotion-focused coping are two core coping strategies related to appraisal. Problem-focused coping involves taking direct action against the stressor itself in an attempt to resolve the problem or alter the environment to reduce stress. It is characterized by proactivity and goal-directedness. The positive effect of problem-focused coping lies in its ability to effectively alleviate stress, increase individuals’ self-confidence, and facilitate personal growth. In contrast to problem-focused coping, emotion-focused coping focuses primarily on regulating emotional responses related to stress rather than directly changing the stressor. It is marked by flexibility and passivity. Long-term reliance on emotion-focused coping may result in accumulated problems or a reduced ability of individuals to solve problems independently. The outcome measure indicates the ultimate level of adaptation to stress, encompassing positive emotions about the event’s outcome or distress.

In this study, the diagnosis of patients with CIN grade 3 served as the core stressor, triggering the stress-coping process in patients. Within Lazarus and Folkman’s [10] stress and coping model, patients exhibit differentiated characteristics in their perception of the disease during the cognitive appraisal phase: some patients may regard the diagnosis as a threat (e.g., worrying about the risk of malignant transformation), others may view it as a challenge (e.g., actively accepting treatment to control the condition), and a few may categorize it as an irrelevant event (e.g., ignoring follow-up recommendations). The study used scores from the Self-Rating Anxiety Scale (SAS) as a quantification index of threat appraisal. A high SAS score can reflect patients’ perception of a threat due to the uncertainty of the disease (e.g., “the lesion may become malignant”) [4]. The coping strategies following threat perception appraisal include mainly problem-focused coping and emotion-focused coping [5]. Confrontation, a typical type of problem-focused coping strategy, focuses on directly addressing the stressor. Its behavioral characteristics involve proactively acquiring medical information, participating in treatment decisions, or devising long-term health management plans (such as regular follow-ups). Avoidance and resignation coping are categorized as emotion-focused coping and alleviate stress primarily by regulating emotions. Avoidance is often seen in situations of resource shortage or when short-term stress relief is needed, such as avoiding follow-up visits or avoiding discussions about the illness. Resignation coping reflects an extremely negative resource assessment (e.g., “the outcome cannot be changed”), resulting in passive acceptance of the disease. The differentiated effects of these coping strategies influence the event outcome and directly shape the emotional outcome. In this study, distress, marked clinically by FOP, essentially reflected a combination of patients’ feelings of helplessness regarding disease progression and somatic anxiety. The aforementioned process is summarized in Fig. 1A: the stressor (the diagnosis of patients with CIN grade 3) directly impacts cognitive appraisal (threat perception and anxiety), which in turn drives coping strategies (such as confrontation, avoidance, or resignation), ultimately leading to emotional outcomes (FOP).

Research hypotheses and aims

On the basis of the above stress and coping model theory, this study adopted anxiety as the independent variable, coping styles (confrontation, avoidance and resignation) as the mediating variables, and FOP as the dependent variable. We proposed two hypotheses (Fig. 1 B):

• H1: Anxiety is positively associated with FOP.

• H2: Coping styles mediate the correlation between anxiety and FOP.

Therefore, this study constructed a SEM based on Lazarus and Folkman’s stress and coping theory to (1) verify the mediating pathways through which anxiety influences FOP by coping style (confrontation/avoidance/resignation); (2) quantify the direct and indirect effects of anxiety on FOP; and (3) allow clinical staff to better understand FOP in patients with CIN grade 3 and implement appropriate psychological interventions.

Methods

Design

This was a single-center, cross-sectional investigation of patients with precancerous cervical lesions. This study was approved by the local hospital’s ethics committee (2021—K051). Patients from the gynecological clinic or department of a large university hospital were sampled (i.e., from September 2022 to July 2023). All patients were involved in the treatment and nursing process by the researchers themselves, and all understood the purpose and significance of this investigation. Self-reporting was utilized for patient sociodemographic information collection. Electronic medical records were accessed to obtain clinical data related to hospitalization.

Patients in this study met the following inclusion criteria: (i) were adults > 18 years of age; (ii) were diagnosed with cervical precancerous lesions (CIN) grade 3 [46]; (iii) had verbal communication and information technology skills to complete the questionnaire; and (iv) agreed with the participation scope and provided informed consent. According to the WHO’s 2003 publication, Pathology and Genetics of Tumors of the Breast and Female Genital Organs, the diagnostic criteria for CIN follow a histological classification system with a three-tier grading system (CIN grade 1, CIN grade 2, CIN grade 3) [3]. CIN grade 3 is characterized by the following histological features: 1) abnormal cells occupying more than two-thirds or the full thickness of the epithelial layer with complete loss of cellular polarity; 2) marked nuclear atypia with frequent mitotic figures that may extend to the superficial epithelial layers, including the presence of pathological mitoses; and 3) CIS, representing the most severe manifestation of CIN grade 3, where full-thickness epithelial involvement results in malignant transformation while maintaining an intact basement membrane without stromal invasion. The diagnostic protocol requires all enrolled patients to undergo tissue sampling via cervical biopsy or conization, with pathological specimens independently reviewed by at least two senior pathologists according to the aforementioned criteria [3].

From a clinical risk perspective, patients with CIN grade 3 exhibit three distinctive characteristics: 1) CIN grade 3 patients have a significantly greater risk of progressing to invasive cervical cancer than low-grade CIN grade 1/CIN grade 2 patients do; 2) clinical guidelines typically recommend surgical treatment (such as the loop electrosurgical excision procedure or conization) for patients with CIN grade 3; and 3) CIN grade 3 patients are frequently associated with high-risk HPV genotypes (e.g., types 16/18) and demonstrate enhanced invasiveness and recurrence propensity when coexisting with adenocarcinoma in situ. Thus, as the highest-grade cervical precancerous lesion, the pathological severity of CIN grade 3 intensifies patients’ FOP and cancer identity distress, which are psychological burdens exacerbated by clinical messaging that emphasizes immediate intervention and high risk of malignant transformation. Unlike CIN grade 1/CIN grade 2 patients managed through surveillance, CIN grade 3 patients face dual psychological impacts from surgical treatments (e.g., cervical conization): procedural trauma itself and potential fertility implications. Studying patients with CIN grade 3 offers methodological advantages: standardized treatment protocols, follow-up regimens, and prognostic evaluations enable controlled analysis of FOP determinants, clinical homogeneity improves recruitment efficiency, and most critically, it allows precise identification of malignancy-specific fear factors.

Patients were excluded from the study if they met any of the following exclusion criteria: (i) had abnormal or impaired communication; (ii) had a malignant tumor elsewhere; (iii) had undergone major surgery or suffered severe cerebrovascular sequelae, acute heart failure, and/or acute infection; (iv) had a history of psychiatric disorders; or (v) were sexually inactive women. The exclusion of participants with ‌psychiatric histories‌ was methodologically justified for three key reasons. First, preexisting mental disorders may introduce ‌systematic bias‌ by altering baseline psychological metrics (e.g., anxiety severity), thereby obscuring the true associations between target variables. Second, psychiatric comorbidities are associated with distinct ‌neuroendocrine profiles‌, ‌illness perceptions‌, and ‌health behaviors‌ that could functionally interact with FOP mechanisms, compromising the study’s internal validity. Third, including this subpopulation would have required multidisciplinary collaboration‌ (e.g., liaison psychiatry), adapted assessment protocols‌ for comorbid conditions, and extended monitoring‌ to account for psychotropic medication effects. These requirements exceed the project’s ‌resource allocation‌ and ‌protocol standardization‌ capacities.

Sexual activity is a key risk factor for cervical cancer. Persistent HPV infection, which is transmitted mainly sexually, is the primary cause of Grade 3 CIN. Compared with sexually active women, women who are sexually inactive and lack this key exposure have different CIN mechanisms, progression risks, and fear sources. Including sexually inactive women might increase sample heterogeneity, bias the analysis of core variables such as HPV infection, lesion progression, and fear, and lead to biased results. Thus, we excluded sexually inactive women from this study.

Measures

Fear of progression questionnaire–short form

The 12-item short version of the FOP Questionnaire–Short Form (FOP-Q-SF) was used to measure patient FOP in this study. It consists of 12 items, including two dimensions of physical and social/family well-being, which have been successfully applied to patients with chronic diseases such as cancer [47]. The items are scored on a 5‐point Likert scale ranging from 1 to 5 (never to very often), with a total score ranging from 12 to 60. A score of ≥ 26 points implies that a patient experienced psychological impairment [48]. A higher score indicates a higher FOP for the patient. The Cronbach’s α value reported previously for the Chinese version of this scale is 0.883 [49].

Self-rating anxiety scale

The scale contains 20 items, and the higher the SAS score is, the greater the severity of anxiety. This scale contains 20 items, with each item scored from 1 (never) to 4 (always). The final evaluation score is obtained by multiplying the score of each item by 1.25. In China, the standard score is 50, a score between 50 and 59 indicates mild anxiety, a score between 60 and 69 indicates moderate anxiety, and a score above 70 indicates severe anxiety. The Cronbach’s α value reported previously for the Chinese version of this scale is 0.850 [50].

Medical coping modes questionnaire

The Medical Coping Modes Questionnaire (MCMQ) was developed by Feifel et al. [51] and translated into Chinese by Shen [52]. The MCMQ is a 20-item scale designed to assess disease-related cognitive and behavioral coping modes. It comprises three dimensions: confrontation (8 items), avoidance (7 items), and resignation (5 items). The respondents rated their experience on a 4-point Likert scale ranging from ‘never’ (1) to ‘always’ (4). Eight of the 20 items are reverse scored. Subscale scores are obtained by summing the scores of each item, with ranges as follows: confrontation (8–32), avoidance (7–28), and resignation (5–20). Higher scores indicate a greater frequency of the specific coping behaviors described by each subscale. The MCMQ has good internal consistency, with Cronbach’s α values as follows: confrontation, 0.74; avoidance, 0.73; and resignation, 0.83 [53].

Sociodemographic and clinical characteristics

The demographic variables included age, fertility status, marital status, occupation, educational level, residence, and monthly per capita income. Medical records were assessed to extract data on clinical characteristics. The clinical variables included the course of disease, treatment method(s), family history of cervical cancer, and chronic disease (e.g., gout, hypertension, diabetes, stroke, coronary heart disease, chronic lung disease).

Statistical analysis

The data were analyzed via R software (v4.2.3). The normality of distributions was assessed via the Shapiro‒Wilk test (P < 0.05 indicated nonnormality). Nonnormally distributed variables are reported as medians (interquartile ranges), whereas parametric data are expressed as the means ± standard deviations. Nonparametric tests (Mann‒Whitney U for two-group comparisons; Kruskal‒Wallis for multigroup comparisons) were employed for skewed data.

Spearman’s rank correlation was used to analyze associations between continuous variables. Variables with P < 0.1 in univariate analyses were included as candidates for multivariate logistic regression, and a less restrictive threshold was used to minimize type II error [54]. Statistical significance was defined as P < 0.05 (two-tailed). The variable (P < 0.1) in univariate analysis was also considered the covariant variable.

Mediation analysis was conducted via the Mediation package (v4.5.0) in R, with 2,000 bootstrap resamples to estimate indirect effects (2000 bootstrap resamples were used to determine the role of coping styles as a mediating variable for anxiety and FOP). Bias-corrected 95% confidence intervals (CIs) were calculated for the mediation effects. False discovery rate (FDR) adjustment was applied to address multiple comparisons in the regression models.

SEM was performed via the Lavaan package (v0.6.19) in R. Model fit was evaluated via the χ²/df ratio, SRMR, RMSEA with 90% CIs. Path coefficients were estimated via maximum likelihood, with significance assessed at P < 0.05.

Results

Study sample

Overall, a total of 181 questionnaires were distributed. We excluded 13 participants who filled out the questionnaire within a very short period of time or who filled it out incompletely. Finally, 168 participants were involved in this survey, and the response rate for the questionnaires was 93%. Table 1 presents the demographic and clinical characteristics of the 168 patients with Grade 3 CIN. The median age of the participants was 48 years. The majority of patients were aged between 45 and 59 years (82 patients), followed by those aged < 45 years (60 patients) and those aged ≥ 60 years (26 patients). The median course of disease was 30 years. Almost all patients reported being fertile (166 patients), with only 2 patients reporting infertility. Most patients were married (161 patients), divorced, or widowed (7 patients). In terms of occupation, 125 patients were employed and 43 patients were unemployed. In terms of educational level, 106 patients had a secondary school education or below, whereas 62 patients had a junior high school education or above. With respect to place of residence, 97 patients lived in villages and 71 patients resided in towns or cities. The monthly per capita income distribution was as follows: 31 patients earned less than 2000 RMB, 71 patients earned between 2000 and 3999 RMB, 27 patients earned between 4000 and 5999 RMB, and 39 patients earned 6000 RMB or more. A total of 29 patients reported having chronic diseases, whereas 139 patients did not. A family history of cervical cancer was present in 13 patients and absent in 155 patients. The detailed sociodemographic and clinical characteristics are presented in Table 1. 

Table 1.

Results of univariate analysis on the factors of FOP in patients with CIN grade 3 (n = 168)

Variables	Category	N	FOP Median [IQR]	Shapiro–Wilk normality test	Statistical Method	Statistic	P value
Age (year)				Statistic = 0.793 P < 0.001	Kruskal–Wallis	1.503	0.472
	< 45	60	27.000 [22.000,34.000]
	45–59	82	29.000 [20.250,34.000]
	≥ 60	26	24.500 [15.000,34.000]
Whether fertility				Statistic = 0.084 P < 0.001	Mannwhitney-U	1.543	0.124
	yes	166	27.000 [20.000,34.000]
	no	2	34.000 [34.000,42.000]
Marriage status				Statistic = 0.199 P < 0.001	Mannwhitney-U	0.699	0.487
	divorced or widowed	7	27.000 [20.000,34.000]
	married	161	33.000 [21.000,37.00]
Occupation				Statistic = 0.543 P < 0.001	Mannwhitney-U	0.514	0.608
	unemployed	43	29.000 [20.000,32.000]
	employed	125	27.000 [20.000,36.000]
Educational level				Statistic = 0.611 P < 0.001	Kruskal–Wallis	0.585	0.559
	secondary school or below	106	29.000 [20.000,34.000]
	junior high school or above	62	27.000 [20.000,34.000]
Residence				Statistic = 0.628 P < 0.001	Mannwhitney-U	−1.174	0.241
	village	97	27.000 [17.000,34.000]
	town or city	71	28.000 [24.000,34.000]
Monthly per capita income, RMB				Statistic = 0.846 P < 0.001	Kruskal–Wallis	1.782	0.619
	< 2000	31	28.000 [21.000,40.000]
	2000–3999	71	26.000 [18.000,34.000]
	4000–5999	27	29.000 [25.000,31.000]
	≥ 6000	39	28.000 [20.000,32.000]
Course of disease(day)				Statistic = 0.570 P < 0.001	Mannwhitney-U	1.832	0.067
	≤ 30	119	28.000 [22.000,36.000]
	> 30	49	26.000 [16.000,31.000]
Chronic diseases				Statistic = 0.457 P < 0.001	Mannwhitney-U	0.296	0.769
	yes	29	27.000 [17.000,40.000]
	no	139	28.000 [20.000,34.000]
Family history of cervical cancer				Statistic = 0.294 P < 0.001	Mannwhitney-U	2.318	0.021
	yes	13	37.000 [29.000,40.000]
	no	155	27.000 [18.000,34.000]

Variables in bold are those considered statistically significant(P < 0.1)

FOP Fear of progression, IQR Interquartile Range, CIN cervical intraepithelial neoplasia

Scores of the self-rating anxiety scale, medical coping modes questionnaire (confrontation, avoidance and resignation coping), and fear of progression

Among 168 patients with CIN grade 3, Shapiro‒Wilk normality tests revealed that scores for SAS, medical coping modes (confrontation, avoidance, and resignation coping), and FOP did not conform to normal distributions (P < 0.05). Consequently, the data are reported as medians (first quartile [Q1], third quartile [Q3]). The total SAS score was 42.500 (36.250, 47.500), while the FOP score was 27.500 (20.000, 34.000). For the medical coping modes, the scores were as follows: confrontation coping dimension, 19.000 (17.000, 21.000); avoidance dimension, 14.000 (12.000, 16.000); and resignation dimension, 7.000 (5.000, 9.000). On the basis of the criteria established by Ma et al. [48], an FOP score of ≥ 26 points indicated clinically significant psychological impairment. In this research, 58.3% (n = 98) of patients exceeded this clinical threshold (≥ 26 points), indicating substantial psychological distress. The detailed FOP score distributions are illustrated in Fig. 2 and Supplementary File 1.

Fig. 2.

Distribution of Fear of Progression (FOP) item scores in patients with CIN grade 3. Boxplots depict the median (horizontal line) and interquartile range (box) of individual FOP item scores (F1 to F12). The dashed horizontal line (2.167) indicates the clinical threshold per item (total clinical threshold: 26/12 items)

Spearman correlation analysis between anxiety, medical coping modes and fear of progression

The Spearman correlation analysis, which was based on data from Fig. 3 and Supplementary File 2, revealed significant relationships among anxiety (SAS), medical coping modes (confrontation, avoidance, and resignation), and FOP in patients with CIN grade 3. Anxiety exhibited significant positive correlations with avoidance coping (r = 0.341, P < 0.001), resignation coping (r = 0.16, P < 0.05), and FOP (r = 0.532, P < 0.001), suggesting that heightened anxiety is associated with increased reliance on avoidance and resignation behaviors, as well as intensified fears of disease deterioration. Furthermore, avoidance coping was positively correlated with FOP (r = 0.259, P < 0.01), whereas resignation coping was more strongly positively associated with FOP (r = 0.360, P < 0.001), indicating that both avoidance and resignation strategies may amplify patients’ FOP. No significant associations were detected between anxiety and confrontation coping (P > 0.05) or between confrontation coping and FOP/avoidance coping (both P > 0.05).

Fig. 3.

The heatmap illustrates standardized coefficients (β) for relationships among SAS, medical coping modes (confrontation coping modes, avoidance coping modes, and resignation coping modes), and FOP. Coefficients are color-coded (blue: negative effects; red: positive effects), with color intensity proportional to effect size. SAS: self-rating anxiety scale; FOP: fear of progression. ^*P < 0.05, ^**P < 0.01, ^***P < 0.001

Results of univariate analysis for demographic and clinical variables

The results of the univariate analysis for demographic and clinical variables are presented in Table 1. Shapiro‒Wilk normality testing revealed that all demographic and clinical characteristics associated with FOP violated the assumption of a normal distribution (P < 0.05). Consequently, nonparametric methods (Mann‒Whitney U or Kruskal‒Wallis tests) were employed for subsequent analyses. Using a screening threshold of P < 0.1, significant differences in FOP scores were observed based on disease duration (Mann‒Whitney U statistic = 1.832, P = 0.067) and a family history of cervical cancer (Mann‒Whitney U statistic = 2.318, P = 0.021). However, no significant differences were detected for age, fertility status, marital status, occupation, educational level, residence, monthly per capita income, or chronic diseases (all P > 0.05; Table 1).

Multivariate logistic regression analysis

To identify independent predictors of clinically significant FOP, we dichotomized the FOP scale using a validated clinical threshold of ≥ 26 points, which was consistent with prior research defining this cutoff as indicative of a high psychological burden requiring intervention [48]. As illustrated in Fig. 4, multivariate logistic regression was performed with FOP as the dependent variable, incorporating two variables identified in the Mann‒Whitney U analysis (disease duration and family history of cervical cancer) and four variables demonstrating statistical significance in the correlation analysis (SAS score, confrontation coping, resignation coping, and avoidance coping) as independent predictors.

Fig. 4.

Forest plot of multivariate logistic regression analysis for patients with CIN grade 3, with 95% confidence intervals (CIs) and P values. The variables included family history, disease course (≤ 30 vs. > 30 days), medical coping style (confrontation, avoidance, resignation), and SAS score. The horizontal lines represent 95% CIs; the marker size corresponds to the weight of each variable in the model. OR: odds ratio

The analysis revealed three significant predictors of elevated FOP: avoidance coping (odds ratio [OR] = 1.17, 95% CI = 1.05–1.30; P = 0.005), resignation coping (OR = 1.26, 95% CI: 1.10–1.45; P < 0.001), and higher self-reported anxiety (per 1-point increase in SAS score: OR = 1.11, 95% CI: 1.07–1.16; P < 0.001). These associations remained statistically significant after FDR adjustment (FDR_avoidance = 0.0125; FDR_resignation = 0.0003; FDR_SAS = 0.0003). In contrast, a family history of cervical cancer (OR = 0.23, 95% CI: 0.05–1.08; P = 0.063), a disease duration of > 30 days (OR = 0.99, 95% CI: 0.44–2.22; P = 0.973), and confrontation coping (OR = 1.08, 95% CI = 0.98–1.18; P = 0.120) were not significantly associated with FOP (Fig. 4).

Stratification analysis on the basis of disease duration, family history, age, educational level and occupational status

By using a stratified analysis, the stability of the correlation between SAS, medical coping modes, and FOP was further confirmed for different disease durations, family histories, ages, educational levels and occupation statuses (Tables 2 and 3). 

Table 2.

The scores of SAS, medical coping modes (confrontation coping modes, avoidance coping modes, and resignation coping modes), and FOP (n = 168)

Variables	Shapiro–Wilk normality test	Median [IQR]
SAS	Statistic = 0.951 P < 0.001	42.500 [36.250,47.500]
Medical coping modes
CCM	Statistic = 0.979 P = 0.012	19.000 [17.000,21.000]
ACM	Statistic = 0.984 P = 0.047	14.000 [12.000,16.000]
RCM	Statistic = 0.874 P < 0.001	7.000 [5.000,9.000]
FOP	Statistic = 0.969 P = 0.001	27.500 [20.000,34.000]

FOP Fear of progression, CCM Confrontation coping modes, ACM Avoidance coping modes, RCM Resignation coping modes, IQR Interquartile Range, SAS Self-Rating Anxiety Scale

Table 3.

Stratification analysis based on course of disease, family history, age, educational level and occupation (n = 168)

Variable/Category	SAS	Medical Coping Modes
		Confrontation	Avoidance	Resignation
	β (95% CI) P value	β (95% CI) P value	β (95% CI) P value	β (95% CI) P value
Course of disease (day)  ≤ 30  > 30	0.676 [0.499,0.853], P < 0.001 0.310 [0.071,0.550], P = 0.011	0.332 [−0.223,0.887], P = 0.241 0.359 [−0.467,1.185], P = 0.394	1.296 [0.699,1.893], P < 0.001 0.011 [−0.907,0.929], P = 0.981	1.901 [1.274,2.528], P < 0.001 0.824 [−0.427,2.075], P = 0.197
Family history of cervical cancer yes no	0.666[−0.483,1.814], P = 0.256 0.511[0.368,0.654], P < 0.001	0.570 [−0.625,1.766], P = 0.350 0.295 [−0.195,0.785], P = 0.237	0.691 [−0.680,2.062], P = 0.323 0.962 [0.428,1.496], P < 0.001	1.997 [0.526,3.467], P = 0.008 1.673 [1.081,2.265], P < 0.001
Age (Year)  < 45 45–59  ≥ 60	0.578 [0.356,0.801], P < 0.001 0.286 [0.042,0.530], P = 0.022 0.762 [0.491,1.033], P < 0.001	0.279 [−0.654,1.212], P = 0.558 0.447 [−0.107,1.000], P = 0.114 −0.154 [−1.703,1.395], P = 0.846	0.964 [0.058,1.869], P = 0.037 1.212 [0.561,1.863], P < 0.001 −0.217 [−1.710,1.276], P = 0.776	1.904 [1.162,2.645], P < 0.001 1.769 [0.913,2.626], P < 0.001 0.526 [−1.775,2.828], P = 0.654
Educational level secondary school or below junior high school or above	0.420 [0.224,0.617], P < 0.001 0.693 [0.501,0.884], P < 0.001	0.570 [0.016,1.124], P = 0.044 −0.179 [−1.032,0.675], P = 0.681	0.799 [0.172,1.427], P = 0.013 1.143 [0.254,2.032], P = 0.012	2.070 [1.290,2.849], P < 0.001 1.309 [0.476,2.142], P = 0.002
Occupation unemployed employed	0.685 [0.512,0.859], P < 0.001 0.216 [−0.011,0.444], P = 0.063	0.427 [−0.109,0.963], P = 0.118 −0.031 [−0.939,0.877], P = 0.946	1.245 [0.622,1.869], P < 0.001 0.023 [−0.766,0.812], P = 0.954	1.685 [1.001,2.369], P < 0.001 1.576 [0.619,2.533], P = 0.001

In terms of the course of disease, for ≤ 30 days, SAS (β = 0.676, P < 0.001), avoidance (β = 1.296, P < 0.001), and resignation (β = 1.901, P < 0.001) were significantly positively associated, whereas for > 30 days, only SAS (β = 0.310, P = 0.011) was significantly associated. With respect to a family history of cervical cancer, resignation was significantly associated (β = 1.997, P = 0.008) with a positive history, whereas with respect to those without, SAS (β = 0.511, P < 0.001), avoidance (β = 0.962, P < 0.001), and resignation (β = 1.673, P < 0.001) were significantly linked. With respect to age, in the < 45-year-olds and 45–59-year-olds, SAS, avoidance, and resignation were significantly associated (both P < 0.01), whereas for the ≥ 60-year-olds, only SAS (β = 0.762, P < 0.001) was significant. With respect to educational level, for secondary school or below, SAS (β = 0.420, P < 0.001), confrontation (β = 0.570, P = 0.044), avoidance (β = 0.799, P = 0.013), and resignation (β = 2.070, P < 0.001) were significantly associated, whereas for junior high school or above, SAS (β = 0.693, P < 0.001), avoidance (β = 1.143, P = 0.012), and resignation (β = 1.309, P = 0.002) were significantly associated. In terms of occupation, unemployed individuals were significantly associated with SAS (β = 0.685, P < 0.001), avoidance (β = 1.245, P < 0.001), and resignation (β = 1.685, P < 0.001), whereas employed individuals were significantly associated with only resignation (β = 1.576, P = 0.001).

Mediation analysis of medical coping modes in the anxiety‒fear of progression association

After verifying the assumptions of collinearity (VIF = 1.012–1.149; Supplementary File 3) and residual independence (Durbin‒Watson = 1.865, P = 0.379), mediation analysis revealed distinct roles of medical coping modes in linking anxiety to FOP.

Spearman correlation analysis revealed no significant association between FOP and confrontation coping (P > 0.05; Fig. 3; Supplementary File 2). Multivariate logistic regression analysis, which incorporates multiple variables to identify independent predictors of FOP, further revealed the nonsignificant predictive effects of confrontation coping (OR = 1.08, 95% CI = 0.98–1.18; P = 0.120; Table 3), supporting its insufficiency as a critical predictor of FOP.

Consequently, mediation analysis was conducted with anxiety as the independent variable, medical coping mode (avoidance and resignation coping) as the mediating variable, and FOP as the dependent variable. A bootstrap sampling test (5,000 iterations, R Mediation package v4.5.0) was employed to assess the mediation effects. The analysis revealed divergent mediation patterns:

1. Avoidance coping exhibited a nonsignificant average causal mediation effect (ACME: B = 0.0320, 95% CI [− 0.0065, 0.08], P = 0.10), indicating negligible mediation in the anxiety‒FOP relationship. The direct effect of anxiety remained robust (B = 0.4744, 95% CI [0.3301, 0.63], P < 0.001), with only 6.01% of the total effect (B = 0.5063) being nominally mediated (proportion mediated: 0.0601, 95% CI [− 0.0132, 0.61]; Table 4).

2. Resignation coping demonstrated significant partial mediation (ACME: B = 0.0853, 95% CI [0.0303, 0.1500], P < 0.01), accounting for 16.5% of the total effect (proportion mediated: 0.165, 95% CI [0.0616, 0.30]). While the direct effect of anxiety was attenuated, it remained significant (B = 0.4216, 95% CI [0.2779, 0.57], P < 0.001). Notably, both coping modes exhibited comparable total effects (B ≈ 0.506), underscoring the unique explanatory contribution of resignation in coping with anxiety-driven FOP (Table 4).

Table 4.

Mediation analysis for medical coping modes on the association between anxiety and FOP (n = 168)

Variables	Estimated	95% CI
Model 1: Anxiety ➝ ACM ➝ FOP
Average Causal Mediation Effect	0.0320	−0.0065 ~ 0.08
Average Direct Effect	0.4744	0.3301 ~ 0.63***
Total effect	0.5063	0.3658 ~ 0.66***
Proportion of Mediated effect	0.0601	−0.0132 ~ 0.61
Model 2: Anxiety ➝ RCM ➝ FOP
Average Causal Mediation Effect	0.0853	0.0303 ~ 0.15**
Average Direct Effect	0.4216	0.2779 ~ 0.57***
Total effect	0.5069	0.3543 ~ 0.65***
Proportion of Mediated effect	0.1650	0.0616 ~ 0.30**

FOP Fear of progression, ACM = Avoidance coping modes, RCM = Resignation coping modes, CI = confidence interval. ^** P < 0.01; ^*** P < 0.001

Structural equation modeling mapping the relationships between anxiety, medical coping modes, and fear of progression

Consistent with the Spearman correlation and multivariate logistic regression findings, confrontation coping was not significantly associated with FOP scores (P > 0.05), justifying its exclusion from SEM. Using the Lavaan package (v0.6.19) in R (v4.2.3), a SEM was developed with anxiety as the independent variable, medical coping modes (avoidance and resignation) as mediating variables, and FOP as the dependent variable.

The model fit indices of the measurement model with the avoidance coping mode as a mediating variable indicated that the data fit the model well (χ² [699] = 1734.056, P < 0.001, χ²/df = 2.481, SRMR = 0.113, and RMSEA [90% CI] = 0.088 [0.094, 0.099]). Next, the resignation coping mode was included in the measurement model as a second mediating variable. The results showed that the final measurement model also fit the data well (χ² [626] = 1615.245, P < 0.001, χ²/df = 2.580, SRMR = 0.113, and RMSEA [90% CI] = 0.097 [0.091, 0.100]).

The middle part of the diagram (Fig. 5) represents the structural model that allowed us to see the direct path of anxiety to FOP (path coefficient = 0.332) and the indirect path created through resignation coping. Importantly, all path coefficients concerning the structural model had a significant P value. Anxiety positively influenced resignation coping (β = 0.304, P = 0.006), and resignation coping positively predicted FOP (β = 0.332, P < 0.001; Fig. 5; Table 5). Thus, an indirect effect was proven, and it can be stated that anxiety impacted FOP through resignation coping (0.30 * 0.39), with an estimation value of 28% of the overall effect of anxiety on FOP.

Fig. 5.

Structural Equation Modeling: Model illustrating the mediating role of resignation in coping with anxiety and FOP. In the diagram, yellow triangles represent observed variables (OVs). A1-A20: Items from the Self-Rating Anxiety Scale (SAS). M10, M13, M18, M20, M6, M4: Resignation subscale items from the Medical Coping Modes Questionnaire. F1-F12: Items from the FOP scale. The blue ellipses denote latent variables (LV). Among latent variables, directional arrows indicate path relationships between variables, with adjacent numerical values representing standardized path coefficients (β). Darker arrows correspond to higher path coefficients. The asterisks above uniformly indicate significance levels: ^*P < 0.05, ^**P < 0.01, ^***P < 0.001. Each latent variable is accompanied by an R² value denoting the proportion of variance explained by its corresponding observed variables, with anxiety serving as the reference indicator. The arrows connecting yellow triangles represent covariances among the observed variables, whereas the arrows linking blue ellipses and yellow triangles indicate factor loadings, with darker color intensity reflecting higher values. Comprehensive details of the path coefficients, including estimates, standard errors, and P values, are provided in Supplementary File 4. Note: FOP = fear of progression

Table 5.

Path coefficient analysis between anxiety, medical coping modes, and fear of progression in patients with CIN grade 3 (n = 168)

Variables	β	SE	Z	P
Model 1
Anxiety ➝ ACM	0.300	0.055	1.853	0.064
ACM ➝ FOP	0.136	0.709	1.240	0.215
Anxiety➝ FOP	0.411	0.227	3.953	< 0.001
Model 2
Anxiety ➝ RCM	0.304	0.071	2.757	0.006
RCM ➝ FOP	0.390	0.353	3.738	< 0.001
Anxiety ➝ FOP	0.332	0.202	3.596	< 0.001

FOP Fear of progression, ACM Avoidance coping modes, RCM Resignation coping modes, SE standard error, CIN cervical intraepithelial neoplasia

In contrast, avoidance coping exhibited no meaningful mediation: anxiety did not significantly influence avoidance coping (β = 0.30, P = 0.064), nor did avoidance coping predict FOP (β = 0.14, P = 0.215; Fig. 6; Table 5). These results confirmed the unique role of resignation coping in mediating anxiety-driven FOP, whereas avoidance strategies lacked explanatory power (Figs. 5, 6; Table 5). The complete path coefficients, including standardized estimates, standard errors, z values and P values, are available in Supplementary File 4 and Supplementary File 5.

Fig. 6.

Structural Equation Modeling: Model illustrating the mediating role of avoidance coping modes between anxiety and FOP. In the diagram, yellow triangles denote observed variables (OVs). A1-A20: Items from the Self-Rating Anxiety Scale (SAS). M17, M14, M11, M9, M8, M7, M3: Avoidance coping subscale items from the Medical Coping Modes Questionnaire. F1-F12: Items from the Fear of Progression (FOP) scale. The blue ellipses represent latent variables (LVs). Among latent variables, directional arrows depict path relationships between variables, with adjacent numerical values indicating standardized path coefficients (β). Darker arrow shades correspond to higher path coefficients. Asterisks superscripted to coefficients uniformly denote significance levels: ^*P < 0.05, ^**P < 0.01, ^***P < 0.001. Each latent variable is accompanied by an R² value reflecting the proportion of variance explained by its observed variables, with anxiety specified as the reference indicator. The arrows connecting yellow triangles signify covariances among the observed variables, whereas the arrows linking blue ellipses and yellow triangles represent factor loadings, with color intensity increasing with increasing values. The full details of the path coefficients, including estimates, standard errors, and P values, are provided in Supplementary File 5. Note: FOP = fear of progression

Discussion

Summary of key findings

This study conducted an in-depth questionnaire survey and analysis of 168 patients with grade 3 CIN. The results revealed elevated scores on both the SAS and FOP scales, with 58.3% of patients exhibiting clinically significant FOP scores. With respect to medical coping styles, correlation analysis revealed that anxiety was significantly positively correlated with avoidance and resignation coping styles and FOP scores (P < 0.05). Univariate analysis revealed trends toward significant differences in FOP scores based on disease duration and a family history of cervical cancer. Multivariate logistic regression further confirmed that anxiety level (OR = 1.11), avoidance coping (OR = 1.17), and resignation coping (OR = 1.26) were independent predictors of FOP (P < 0.05). Stratified analysis reinforced the stable associations between these predictors and FOP across different disease characteristics. The results of the mediation analysis revealed that resignation coping partially mediated the relationship between anxiety and FOP, whereas avoidance coping had no significant mediating effect. Finally, SEM validated the indirect pathway through which anxiety influences FOP through resignation coping.

Analysis of fear of progression scoring dimensions

Interestingly, the FOP scores indicate that the higher scoring entries were: “I become anxious at the thought that the disease may progress,” “I feel nervous before a doctor’s appointments and regular checkups,” and “I am afraid of the pain caused by the disease.” The source of patients’ fearfulness was mainly the symptoms of the disease and stemmed from the social family dimension to a lesser extent. Like Nakata’s [55] findings, patients were concerned about the severity of their symptoms and the results of their tests. Moreover, patients with CIN grade 3 undergo frequent tests, and each time they face a change in the results, it is a psychological ordeal for them [56]. Several psychological interventions have been shown to be effective in reducing patients’ FOP [57, 58] and the results of the present study add to previous findings that healthcare professionals should pay more attention to patients’ disease symptoms and reduce their excessive fear of medical visits and examinations.

Anxiety is a core factor that affects fear of progression

Our analysis revealed that anxiety was the main relevant determinant of FOP. Anxiety is an irritable emotion caused by excessive worry about one’s life safety and future destiny [30, 56]. The more anxious the patient with CIN grade 3 was, the more severe the FOP. Anxiety in cervical cancer survivors was a risk factor for FOP in Hanprasertpong’s [56] study. In this study, patients with CIN grade 3 faced great uncertainty, as it was difficult to determine whether there would be further deterioration and what future treatment would be needed. The resulting anxiety further exacerbated FOP. Therefore, alleviating patients’ anxiety may be critical to improving their psychological state and reducing their fear in the face of the disease.

Some qualitative studies suggest that sources of patient anxiety may include the following consequences of cancer: thoughts about death or its impact on loved ones, the increased perceived risk of cancer, stigma, and fertility worries (for younger women) [5, 59]. Healthcare professionals can address these aspects by providing patients with specialized knowledge about the disease, thereby reducing their worries and rumination. Patients with CIN grade 3 certainly experience anxiety, which is normal, especially for women [60–62]. The results of previous studies have confirmed that measures such as knowledge education and mindfulness-based cognitive therapy are effective in relieving patients’ anxiety [63, 64]. We should learn from these effective psychological intervention measures to reduce the anxiety of patients and thereby alleviate their FOP.

Theoretical framework

According to Lazarus and Folkman’s [10] stress and coping model, stressors trigger individuals’ appraisal of disease threat (anxiety), which subsequently elicits distinct coping strategies (mediating variables), ultimately influencing FOP as the emotional outcome. Consistent with Lazarus and Folkman’s [10] stress and coping model, the diagnosis of CIN grade 3 as the primary stressor triggered patients’ differential cognitive appraisal processes. The SAS scores (median 42.5 > clinical threshold of 40) quantified threat appraisal, indicating that patients predominantly perceived the condition as a high-threat event (e.g., “potential malignant transformation”) rather than a challenge or neutral occurrence. This tendency was corroborated by 58.3% of patients exhibiting clinically significant FOP (≥ 26; Fig. 2). The key findings included the following: (1) problem-focused coping (confrontation) was not significantly associated with anxiety or FOP (P > 0.05; Fig. 3); (2) for emotion-focused coping, anxiety was positively correlated with both resignation (r = 0.16, P < 0.05) and avoidance (r = 0.341, P < 0.001), which subsequently exacerbated FOP (resignation: r = 0.360; avoidance: r = 0.259; Fig. 3). These results aligned with those of Cai et al. [41], who reported similar positive associations between avoidance/resignation and FOP in breast cancer patients. Notably, patients with CIN grade 3 predominantly adopted emotion-focused (vs. problem-focused) coping for FOP management. This preference may have reflected disease chronicity, as problem-focused strategies dominate during initial diagnosis/treatment phases [65], whereas chronic cases (> 30-day duration in 1/3 of this study) increasingly utilize emotion-focused adaptation [66]. The observed resignation coping bias in prolonged cases paralleled Greer’s [67] findings regarding patients with chronic recurrence and limited recovery prospects.

Previous studies have established mediating relationships between FOP and psychological factors such as anxiety [21, 68], whereas coping strategies serve as mechanisms for individuals to manage stressful situations and maintain psychological equilibrium [69]. Therefore, the present study examined the mediating pathways of resignation and avoidance between anxiety and FOP in patients with Grade 3 CIN. The key results demonstrated that resignation constituted the central mediating pathway, accounting for 16.5% of the total anxiety → FOP effect (ACME: B = 0.0853, 95% CI [0.0303, 0.1500]; Fig. 6), revealing a passive acceptance‒fear reinforcement cycle, wherein this coping style directly amplified the emotional outcome (FOP), which was consistent with Lazarus and Folkman’s [10] stress and coping model (Fig. 1) [1]. Further analysis suggested that disease progression unpredictability and prognostic uncertainty may induce psychological compromise, reduce treatment adherence, and exacerbate emotional disturbances that increase FOP by impairing medication efficacy and intensifying stress responses [70]. Although cognitive behavioral interventions could theoretically mitigate FOP by enhancing coping strategies, their feasibility appeared limited in this study: 64.28% of patients were > 45 years old, and 63.1% had education levels at secondary school or below, suggesting poor expected adherence to skill-based training. This may explain the growing preference for complementary and alternative medicine (CAM; e.g., qigong, yoga, Baduanjin, tai chi, meditation) reported in recent studies [71, 72].

According to Lazarus and Folkman’s [10] stress and coping model, patients who adopt confrontation coping styles may effectively alleviate fear-related emotions through proactive disease management. Yu et al. [73] demonstrated that confrontation coping styles better predict quality of life across physiological, psychological, and social domains in cancer patients, with this approach becoming a primary coping strategy for lung cancer in European countries [74]. However, our study revealed no significant association between confrontation coping styles and FOP (P > 0.05; Fig. 3), with most patients with Grade 3 CIN preferring resignation coping. This aligned with East Asian studies where resignation predominates cancer responses. Yang et al. [44] and Wang et al. [75] reported its prevalence among lung cancer patients during immunotherapy. Guo et al.’s [76] SEM revealed disease uncertainty’s direct effect (β = 0.275) and resignation-mediated indirect effects (β = 0.254) on FOP, with resignation itself exerting a direct effect (β = 0.375). Cultural factors likely explain this divergence: East Asian philosophies emphasizing natural harmony and fatalism foster resignation as a culturally embedded mechanism [77]. Collective family-centric values further shape medical decision-making, wherein physicians typically disclose diagnoses to family members first and emotional restraint is valorized to maintain familial harmony [70]. Clinically, culturally tailored interventions are essential for optimizing psychological support. Hospitalization—an additional stressor—intensifies psychological burdens, particularly in recurrent admissions, in which resignation coping becomes more prevalent [78].

Although avoidance coping demonstrated a direct correlation with FOP (r = 0.259, P < 0.01), it failed to show significant mediating effects (ACME: B = 0.0320, 95% CI [− 0.0065, 0.08]; P = 0.10), suggesting that it may represent a comorbid manifestation of anxiety rather than a causal pathway converting anxiety to FOP. This aligned with Chen et al.’s [79] findings that avoidance coping does not mediate the relationship between psychological status and quality of life in Chinese lung cancer patients. The role of avoidance coping in oncology remains debated: while Yang et al. [80] and Faul [81] reported its transient protective effects as a psychological buffer, other studies characterized it as maladaptive for long-term quality of life [82]. Thomsen [83] noted that short-term stress reduction benefits may compromise active problem solving over time. In our study, patients acknowledged their diagnosis but struggled to mentally distance themselves from it, a paradoxical state that may explain the nonsignificant mediation. This phenomenon reflects avoidance’s complex duality: it serves immediate emotional regulation needs yet fails to address the core cognitive–emotional processes driving FOP development.

Neurobiological underpinnings

Anxiety disorders are characterized by functional abnormalities in the prefrontal cortex (PFC) and amygdala, with the amygdala serving as the hub for threat detection and fear processing, whereas the PFC modulates emotional responses by inhibiting amygdala overactivation [84]. In patients with CIN grade 3, elevated anxiety may impair PFC-mediated top-down control, leading to amplified amygdala reactivity and maladaptive threat perception and manifesting as somatic symptom amplification and catastrophic interpretation. Chronic stress exacerbates this imbalance, as evidenced by dorsomedial prefrontal cortex-to-basolateral amygdala pathway dysfunction in rodent models of chronic restraint stress. Anxiety is correlated with the dysregulation of monoaminergic systems (e.g., serotonin and norepinephrine). Genetic polymorphisms in the 5-HT transporter (SERT), particularly the short allele (5-HTTLPR), are linked to increased anxiety susceptibility in cancer patients. This allele reduces SERT expression, impairing synaptic 5-HT reuptake and emotional regulation [85].

The results of the mediation analysis indicated that resignation coping mediates the relationship between anxiety and FOP (Fig. 6). From a neurobiological perspective, chronic stress disrupts threat signal regulation in the dorsal anterior cingulate cortex (dACC), leading to behavioral withdrawal and passive coping strategies such as resignation [86, 87]. This finding is supported by functional magnetic resonance imaging (fMRI) evidence demonstrating that hypoactivation of the dACC during stress tasks is significantly correlated with passive coping behaviors [88]. Concurrently, patients adopting maladaptive coping strategies often exhibit hypothalamic‒pituitary‒adrenal (HPA) axis dysfunction, characterized by disrupted cortisol circadian rhythms and blunted stress responses. Prolonged cortisol elevation under chronic stress may impair PFC-mediated cognitive control, further reinforcing resignation behaviors [89].

Emerging research highlights the pivotal roles of the ventrolateral PFC (vlPFC) and ventromedial PFC in fear regulation. Enhanced activation of the vlPFC facilitates cognitive reappraisal, potentially reducing FOP risk, whereas hyperactivation of the default mode network promotes rumination, exacerbating FOP susceptibility [90]. At the neuroendocrine level, chronic FOP triggers HPA axis activation, resulting in sustained cortisol elevation that directly suppresses natural killer cell activity, thereby impairing tumor immunosurveillance and promoting oncogenesis [91, 92]. Concurrently, excessive catecholamine release further stimulates tumor angiogenesis, increasing the risk of cancer progression.

Implications for clinical practice

On the basis of these findings, in clinical practice, targeted interventions for resignation coping and stratified management of high-risk populations should be prioritized. First, a CIN grade 3 psychological risk stratification system should be established, centering on the anxiety-resignation cognition–fear consolidation mechanism to optimize resource allocation and provide precise psychological intervention targets. Given that resignation coping partially mediates the anxiety‒FOP relationship (β = 1.901, P < 0.001 for patients with a disease duration of ≤ 30 days), routine screening for resignation should be integrated into clinical care protocols to identify and intervene in high-risk patients, thereby mitigating FOP progression and improving treatment outcomes. Future screening could incorporate biomarkers (e.g., cortisol levels) and neuroimaging (e.g., fMRI-based PFC–amygdala functional connectivity analysis) to increase detection accuracy. Second, early cognitive‒behavioral interventions (CBIs) are recommended for recent-onset patients to prevent resignation consolidation, whereas CAM (e.g., Baduanjin, Tai Chi, yoga, meditation) may supplement the CBI for older, less-educated patients [71, 72]. Notably, confrontation coping showed no association with FOP (P > 0.05), suggesting that generalized encouragement of active coping should be avoided, particularly in resource-limited settings. Third, artificial intelligence (AI)-driven personalized interventions leveraging natural language processing to detect resignation keywords (e.g., “incurable,” “fate acceptance”) could trigger automated CBI dialog flows, offering real-time AI psychotherapy support.

Limitations

This study had several limitations that warrant acknowledgment.‌ First, the use of convenience sampling restricted to China’s Nantong region limited sample representativeness; future studies should incorporate diverse populations to increase generalizability. Second, the cross-sectional design precluded causal inferences between anxiety, coping styles, and FOP; longitudinal designs are needed to establish temporal relationships. Third, retrospective data collection may have introduced recall bias, necessitating prospective methods for improved accuracy. Fourth, the exclusive focus on Chinese patients overlooked potential cultural and socioeconomic influences; cross-cultural comparisons are recommended. Finally, reliance solely on quantitative methods calls for complementary qualitative research to explore the underlying causes and context-specific solutions for FOP in CIN grade 3 patients.

Conclusion

Anxiety, avoidance, and resignation coping are significant predictors of FOP in patients with CIN grade 3. Resignation coping plays a crucial mediating role in the relationship between anxiety and FOP. These findings suggest that targeted interventions addressing resignation coping may help reduce FOP and improve psychological well-being in these patients. Future research should explore longitudinal designs and culturally tailored interventions to further understand and mitigate FOP in this population. 

Abbreviations

CIN

Cervical intraepithelial neoplasia

HPV

Human papillomavirus

FOP

Fear of progression

SAS

Self-rating anxiety scale

MCMQ

Medical coping mode questionnaire

GLOBOCAN

Global cancer observatory

IARC

International Agency for Research on Cancer

GCO

Global Cancer Observatory

ASIR

Age-Standardized Incidence Rate

ASMR

Age-Standardized Mortality Rate

WHO

World Health Organization

CI

Confidence interval

OR

Odds ratio

ACME

Average causal mediation effect

PFC

Prefrontal cortex

dACC

Dorsal anterior cingulate cortex

vlPFC

Ventrolateral prefrontal cortex

vmPFC

Ventromedial prefrontal cortex

DMN

Default mode network

HPA

Hypothalamic–Pituitary–Adrenal

NK

Natural Killer

CBI

Cognitive‒Behavioral Interventions

CAM

Complementary and alternative medicine

NLP

Natural Language Processing

fMRI

Functional Magnetic Resonance Imaging

PFC

Prefrontal Cortex Amygdala

5-HT

Serotonin

SERT

5-HT Transporter

5-HTTLPR

5-HT Transporter-Linked Polymorphic Region

Authors’ contributions

Authors’ contributions (I) Conception and design:; (II) Administrative support:; (III) Provision of study materials or patients:; (IV) Collection and assembly of data:; (V) Data analysis and interpretation:; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

Funding

None.

Data availability

The datasets presented in this article are not readily available because participants did not provide consent for public availability of the data.

Declarations

Ethics approval and consent to participate

The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013).

This study was approved by Ethics Committee of the Affiliated Hospital of Nantong University (2022–K023–01), and signed informed consent was obtained from all patients.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.