Different scoring standards were applied based on the type of literature. For case-control studies, we utilized the Newcastle-Ottawa Scale (NOS) (26, 27) recommended by the Cochrane Collaboration. This scale includes eight evaluation items, with a total score of 9, specifically divided into: selection of study population (four items, 4 points), comparability between groups (one item, 2 points), and outcome measurement (three items, 3 points). The evaluation results are presented in Table 1.

For cross-sectional studies, we employed the quality assessment tool from the Joanna Briggs Institute (JBI) Evidence-Based Healthcare Center (28). This tool comprises nine items covering aspects such as sampling methods, study subjects, data collection, and analysis methods, with each item rated as “Yes,” “No,” “Unclear,” or “Not Applicable.” The assessment results are presented in Table 2.

The assessment process was conducted independently by two researchers. In cases of disagreement, a third party was consulted for arbitration to reach a consensus.

Based on the requirements of the study, the following data were extracted from the full text: authors, year, region, type of literature, sample size, depression assessment scales, and related influencing factors, as shown in Table 3.

Data analysis was conducted by using Review Manager 5.4 and Stata 18. The odds ratio (OR) and its 95% confidence interval (CI) were utilized as the outcome measures. Heterogeneity among studies was evaluated by using the Q statistic and I² statistic; when P > 0.1 and I² < 50%, it indicated that the heterogeneity between studies was not significant, and a fixed-effect model was employed. Conversely, a random-effects model was used if the heterogeneity was significant. Publication bias was assessed by using Begg's test. Sensitivity analysis was performed by examining the magnitude of differences between the fixed-effect and random-effects model data. P < 0.05 was considered statistically significant.

A total of 1,108 articles were collected from seven databases. After a thorough screening process, 15 articles were included, comprising 14 in Chinese and one in English. The literature selection process is illustrated in Figure 1.

Due to the significant heterogeneity observed in the analysis of certain influencing factors, subgroup analysis is warranted to further explore the sources of this heterogeneity. Subgroup analyses stratified by different depression assessment scales revealed that for the factor “Inter-household Monthly Income Disparity” subgroup analysis significantly reduced heterogeneity. However, for the factor “Tumor Stage (Advanced Stage)” while heterogeneity decreased, it remained substantial, suggesting that the type of depression assessment scale may contribute to heterogeneity for both these factors. For the factor “Low Educational Attainment” heterogeneity was not reduced; therefore, differences in the depression scales are unlikely to be the source of its heterogeneity. Regarding the factor “age ≥45 years” subgroup analysis could not be performed due to an insufficient number of included studies. The heterogeneity results for each subgroup are presented in Table 4, and the effect size estimates for each subgroup are shown in Supplementary File 1.

A bias test was conducted on the influencing factors with a literature count of ≥10 in this study. The influencing factor identified with a literature count of ≥10 was the disparity in monthly family income; hence, a bias test was performed on this factor. Begg's test was conducted on the 12 included studies, yielding a P-value of 0.732 >0.05, indicating that there is no publication bias associated with the disparity in monthly family income.

The reliability of the results was assessed by observing the magnitude of differences between the fixed-effect model and the random-effect model data. The analysis revealed no essential differences between the two models for each influencing factor, suggesting that the results are stable and reliable, as shown in Table 5.

The results of this meta-analysis indicate that low educational attainment and insufficient disease awareness are risk factors for depression in cervical cancer patients. Educational attainment serves as an objective indicator of a patient's knowledge base; those with lower educational attainment have limited understanding of disease-related knowledge and weaker self-learning abilities. This not only restricts their comprehension and adherence to treatment plans but may also exacerbate their physical and mental burden due to cognitive biases (29). Scholar Song (10) pointed out that having an education attainment below junior high school is a relevant factor for post-operative depressive symptoms in cervical cancer patients. A meta-analysis based on 40 studies in China revealed that participants with the lowest educational attainment or those from rural areas had a significantly higher prevalence of moderate depression (30). Therefore, it is crucial to timely disseminate disease knowledge to patients to effectively improve their adverse emotional states.

An age of 45 years or older is a risk factor for depression in cervical cancer patients, consistent with the findings of Lao and Wu (22). Although some studies (31) investigated psychological distress among terminal cancer patients across different age groups, and they indicate that younger patients bear heavier psychological burdens due to multiple social responsibilities (such as care giving, child-rearing, and occupational stress), older patients typically exhibit more pronounced depressive states due to physiological decline and concerns about prognosis. As age increases, patients may develop multiple chronic diseases, experience a decline in physical function, and exhibit reduced treatment tolerance, thereby increasing the risk of depressive symptoms (32, 33). Therefore, clinical interventions should be stratified by age to provide targeted psychological support, enhance treatment adherence, alleviate mental stress, and ultimately improve the quality of life for patients.

Inter-household monthly income disparity is a risk factor for depression in cervical cancer patients. Zhou et al. (34) found that patients with low annual family income have a higher risk of depression, with a per capita monthly income of less than 1,000 yuan being significantly associated with post-operative depression in thyroid cancer patients (P < 0.05) (35). Economically disadvantaged patients may experience psychological fears, financial burdens, and uncertainties about future planning during diagnosis and treatment, making them more susceptible to depression (36–38). Therefore, it is recommended to alleviate patients' financial burdens through educating patients and their families about medical insurance policies, considering adjustments to medication brands (e.g., using more affordable alternatives), assisting with applications for medical financial aid. At the same time, excessive or unnecessary medical interventions should be avoided.

Insufficient social support also poses a risk for depression. A lack of social support can undermine patients' psychological resilience, leading to a lack of confidence in treatment outcomes (39). Adequate social support can enhance patients' psychological resilience, strengthen life beliefs, and divert attention from distress. Receiving care and support from others during difficult times can effectively reduce negative emotions such as anxiety and depression (40). Hence, medical staff should encourage patients to maintain good communication and connection with family, friends, or healthcare professionals, ensuring they can receive adequate support and assistance during treatment and recovery.

An advanced tumor stage significantly increases the risk of depression. Tosic et al. (41) study found that higher tumor stages correlate with more intense psychological stress responses in patients. Patients with advanced cervical cancer are prone to a decline in immune function and the exacerbation of negative emotions due to high treatment intensity, uncertainty regarding prognosis, and impaired physical function (42, 43). It is advisable to implement multidisciplinary collaborative care for late-stage patients, focusing on individualized intervention plans for adverse reactions such as cancer pain and bone marrow suppression.

Moderate to severe pain is an important trigger for depression. You and You (19) found that moderate to severe pain significantly contributes to depression in cervical cancer patients. Cancer-related pain, whether from the disease or treatment, often persists throughout therapy, causing substantial psychological stress that impairs recovery and quality of life (44). A patient-centered comprehensive pain management strategy (such as medication optimization combined with psychological desensitization) is recommended to alleviate the emotional chain reactions triggered by pain.

Hysterectomy is an independent risk factor for post-operative depression in cervical cancer patients (24). The uterus, as a core structure of the female reproductive system, may lead to identity crises regarding gender and mourning the loss of reproductive function following its removal (45). Furthermore, surgery-induced ovarian dysfunction or hormonal fluctuations may trigger emotional instability. It is suggested that pre-operative psychological assessments and educational interventions be conducted, followed by cognitive-behavioral interventions post-operatively to assist patients in rebuilding psychological adaptation, enhancing treatment tolerance, and improving quality of life.