Exploring the influence of rumination and perceived social support on post-traumatic growth in postoperative gastric cancer patients: a network analysis

Co-author details

Title page

Title

LehanLi1

YuelinSong1✉EmailHappilyllh@126.com

ShimeiJin1✉Email1746635734@qq.com

HuiyingWang2✉Email18502270172@163.com

LinaWang2✉EmailApplepabo@163.com

XinranZhu1✉EmailLigyuhani@163.comEmail416310327@qq.com

ChangyuSong1✉EmailLeahzxr@163.com

XiaohongZhang1✉Emailsherosly@tmu.edu.cn

ShumeiZhuang

PhD

1✉Phone+86-13001378987Emailsnshumei@126.com

School of NursingTianjin Medical UniversityNo.22 Qixiangtai Road, Heping DistrictTianjinChina

2Tianjin Medical University Cancer Institute & HospitalTianjinChina

Lehan Li^1*, Yuelin Song^1*, Shimei Jin¹, Huiying Wang², Lina Wang², Xinran Zhu¹, Changyu Song¹, Xiaohong Zhang¹, Shumei Zhuang¹

Affiliation for authors

¹ School of Nursing, Tianjin Medical University, Tianjin, China.

² Tianjin Medical University Cancer Institute & Hospital, Tianjin, China.

*Lehan Li and Yuelin Song should be considered joint first authors.

Corresponding author address

Shumei Zhuang, PhD, School of Nursing, Tianjin Medical University, No.22 Qixiangtai Road, Heping District, Tianjin, China, + 86-13001378987. E-mail address: snshumei@126.com. ORCID ID: https://orcid.org/0000-0002-2079-8414.

Email address

Lehan Li: Happilyllh@126.com

Yuelin Song: 1746635734@qq.com

Shimei Jin :18502270172@163.com

Huiying Wang: Applepabo@163.com

Lina Wang: Ligyuhani@163.com

Xinran Zhu: Leahzxr@163.com

Changyu Song: sherosly@tmu.edu.cn

Xiaohong Zhang: 416310327@qq.com

Shumei Zhuang: snshumei@126.com

Ethical approval

The study was approved by the Ethical Committee at Tianjin Medical University (TMUhMEC20230008).

Consent to participate

All participants provided written informed consent.

Declaration of Interest

Statement

The authors have no conflicts of interest to disclose.

Funding Information

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

A conflict of interest statement

The authors have no conflicts of interest to disclose.

Acknowledgement

The authors thank students who took part in the survey, parents who supported the work, teachers who assisted with the field investigation, and all investigators.

ABSTACT

Propose

The exploration of pathways promoting positive psychological changes in gastric cancer survivors can significantly enhance post-traumatic growth (PTG) and improve overall physical and mental health. This study aimed to (1) explore the relationship between post-traumatic growth, event-related rumination, and perceived social support in postoperative gastric cancer patients to aid in their recovery from postoperative trauma; as well as (2) identify bridge nodes in the network of PTG with rumination and perceived social support.

Methods

This cross-sectional study included 398 gastric cancer survivors. Data were collected using the Chinese Post-traumatic Growth Inventory, Event-related Rumination Inventory, and Perceived Social Support Scale. Network analysis identified central and bridge nodes determined using the qgraph and networktools packages. The network stability was assessed by R package bootnet.

Results

Post-traumatic growth was used as the dependent variable. PTG1 (Appreciation of life)-E2 (Deliberate rumination), PTG2 (Personal strength)-E2 (Deliberate rumination), and PTG2 (Personal strength)-P1 (Family support) showed notable positive correlations. PTG4 (Relating to others) and E1 (Intrusive rumination) are negative correlated. PTG2 (Personal strength) had the highest centrality and was identified as a key factor. PTG2 (Personal strength) and E2 (Deliberate rumination) served as the key bridge nodes connecting the different communities.

Conclusion

Personal strength may have a significant impact on post-traumatic growth of gastric cancer patients. Notably, personal strength and deliberate rumination function as bridges in distinct directions. Targeting these factors could enhance intervention effectiveness, facilitate positive psychological transformation in patients, and achieve post-traumatic growth.

Keywords:

Posttraumatic growth

Psychological

Psycho-oncology

Gastric cancer

Network analysis

1 Introduction

Gastric cancer (GC) is among the most frequently occurring cancers worldwide. In 2022, it accounted for approximately 968,000 new cases and 659,000 deaths, ranking high in both incidence and mortality rates[1]. Gastrectomy is a potentially curative intervention for gastric cancer, but imposes multifaceted trauma on patients[2]. Beyond the unbearable physiological changes for patients, the procedure entails permanent anatomical alteration, enduring fears of recurrence, and profoundly affects mental health, family relationships, and social life[3, 4]. Notably, the majority of patients experience intolerable psychological challenges, which affect their prognosis and quality of life[2]. Research showed that depression was prevalent in 57% of gastric cancer patients[2], with gastric cancer patients having a 1.4 to 3.7 times higher risk of suicide compared to other cancer patients[5, 6]. The psychological burden of gastric cancer patients after surgery significantly affects cancer outcomes, treatment compliance, long-term psychosocial adaptation, and overall quality of life[2, 7]. Mental health is linked to survival benefits[7], making it crucial to understand how to improve mental health in gastric cancer patients.

The development of positive psychology has shifted the focus to constructive psychological adaptation to trauma[8]. Tedeschi and Calhoun proposed the concept of post-traumatic growth (PTG)[9], which has become a core construct in the rehabilitation process. PTG refers to the positive psychological transformation experienced through coping with highly challenging life crises[9]. It comprises five dimensions: new possibilities, relating to others, personal strength, mental changes, and appreciation of life[9]. For gastric cancer survivors navigating the aftermath of radical surgery, PTG can serve as a vital buffer against distress, fostering improved coping efficacy, treatment adherence, and ultimately higher life satisfaction[10]. Therefore, promoting post-traumatic growth in postoperative gastric cancer patients is critical for the development of survivorship care programs. However, the specific mechanisms driving PTG in this unique surgical population remain unclear.

Rumination is the event-related cognitive process of repetitive thinking. According to Tedeschi and Calhoun[9], rumination evolves from initial intrusive rumination to deliberate rumination. Intrusive rumination involves uncontrollable recollections of trauma-related events, while deliberate rumination involves actively contemplating and revisiting such events[11]. While intrusive rumination typically hinders adaptation, deliberate rumination is often seen as a potential catalyst for PTG. Concurrently, previous studies have shown that perceived social support (PSS) is a unique construct positively associated with PTG[12]. Perceived social support refers to an individual’s subjective emotional experience of feeling respected and understood by others[13]. A higher level of perceived social support is associated with better mental health[14].

Patients who perceive higher levels of social support can communicate more effectively with family and friends, receiving substantial care and support. This, in turn, mobilizes and strengthens their positive psychological attributes, enhances their ability to cope with the disease, and improves their negative perceptions of cancer[15]. Therefore, it promotes the occurrence of PTG by providing a foundation for emotional support and meaning reconstruction, which is particularly important for postoperative gastric cancer patients coping with the psychological challenges in life.

Future research should focus on pathways to facilitate positive changes[16]. Traditional statistical methods (e.g., regression analysis, structural equation modeling) primarily focus on estimating independent effects or overall model fit, and often fail to capture the interactions between specific types of rumination, the different dimensions of PSS, and the various aspects of PTG. They struggle to reveal which variables act as central hubs within the network or identify key bridge pathways. To address this issue, network analysis (NA) offers a powerful statistical tool[17]. NA conceptualizes psychological constructs as interconnected nodes within a system, with edges representing unique associations[18]. Additionally, NA provides metrics for centrality and bridge centrality, which aid in identifying more plausible targets for intervention[18].

Therefore, this study aims to employ NA to: (1) clarify the specific interrelationships between rumination, perceived social support and post-traumatic growth dimensions in postoperative gastric cancer patients; (2) identify central node in this psychological network; and (3) explore bridge nodes that may link rumination process and perceived social support to post-traumatic growth. The findings may support the development of targeted, efficient psycho-social interventions to promote postoperative growth and overall recovery in gastric cancer patients.

2 Method

2.1 Participants

From November 2023 to July 2024, a cross-sectional survey was conducted. A simple random sampling method was used to collect data from 398 patients in a tertiary care hospital in Tianjin. Patients met the following inclusion criteria: ①Aged ≥ 18 years; ②Diagnosed with gastric cancer and having undergone radical gastrectomy; ③Ability to read, write, listen and comprehend questionnaires independently or with the assistance of others; ④Voluntary participation with informed consent. The exclusion criteria were: ①With mental illnesses or cognitive impairment ② With serious physical comorbidities; ③Participated in other psychological studies. Detailed information about the participants is presented in Table 1.

Table 1
Demographic characteristics of participants (n = 398).
Characteristics	N	Percentage	Mean ± SD
Age	398		60.14 ± 11.54
Gender
Male	255	64.1%
Female	143	35.9%
Educational level
Primary school and below	94	23.6%
Junior high school	105	26.4%
Senior high school and above	199	50.0%
Ethnic group
Han nationality	385	96.7%
Other nationalities	13	3.3%
Marriage
Unmarried	6	1.5%
Married	390	98.0%
Divorce	2	0.5%
Long-term residence
City	181	45.5%
Town	66	16.6%
Countryside	151	37.9%
Occupation
Yes	230	57.8%
No	168	42.2%
Income (per capita)
<2000	107	26.9%
2000–5000	173	43.5%
≥ 5000	118	29.6%
Surgical modality
Subtotal gastrectomy	56	14.1%
Total gastrectomy	317	93.7%
Others	25	6.3%
Caregiver
Parents	5	1.26%
Spouse	132	33.17%
Children	218	54.77%
Nursing workers	16	4.02%
Cancer stage
Ⅰ	56	14.1%
Ⅱ	41	10.3%
Ⅲ	301	75.6%
3.2 Network structures and edges of interest
A The network visualization is shown in Fig. 1A. The model includes 34 edges, with weights ranging from − 0.16 to 0.54. There are 9 edges within the impact factor community, 10 edges within the PTG community, and 15 edges connect different communities. The strongest positive correlation was found between P1 (Family support) and P2 (Friend support) (edge weight = 0.32) in the impact factor community. While a negative correlation was between E1 (Intrusive rumination) and P3 (Significant others) (edge weight = -0.13). For PTG, the strongest positive correlation was found between PTG3 (New possibilities) and PTG5 (Self-transformation) (edge weight = 0.54).
In the global network, both PTG1 (Appreciation of life) and PTG2 (Personal strength) showed the strongest positive correlation with E2 (Deliberate rumination) (edge weight = 0.17; edge weight = 0.11). Followed by PTG2 (Personal strength) and P1 (Family support) (edge weight = 0.11). While a negative correlation was between PTG4 (Relating to others) and E1 (Intrusive rumination) (edge weight = -0.16). Table 2 shows the strength of other edge weights.

Table 3
Mean, Standard Deviation, Expected Impact and Expected Bridge Impact of Nodes.
Node abbreviation	Node content	M	SD	EI	BEI
PTG1	Appreciation of life	14.66	8.79	0.78	0.10
PTG2	Personal strength	7.76	4.50	1.17	0.24
PTG3	New possibilities	10.65	5.93	0.98	-0.08
PTG4	Relating to others	7.26	4.32	0.74	-0.07
PTG5	Self-transformation	10.55	6.07	1.12	0.14
P1	Family support	22.84	2.38	0.44	0.16
P2	Friend support	18.65	3.24	0.77	0.06
P3	Significant others	15.89	3.34	0.32	0.13
E1	Intrusive rumination	7.33	4.27	-0.67	-0.33
E2	Deliberate rumination	11.24	3.06	0.35	0.31
M: Mean; SD: Standard Deviation; EI: Expected Influence; BEI: Bridge Expected Influences.
3.4 Network robustness
The CS-C values of EI and BEI are 0.749, indicating excellent network stability (Supplementary Figs. S1 and S2). The edge accuracy test shows a narrow bootstrap 95% CI, indicating good accuracy (Supplementary Fig. S3). The results of the difference test of EI, BEI and edge weights are shown in the Supplementary Fig. S4, S5, S6.
4. Discussion
This study is the first to apply network analysis to explore the complex interplay between PTG, rumination, and perceived social support among postoperative gastric cancer patients, offering a novel perspective beyond traditional regression models that focus on isolated associations. This study found that postoperative gastric cancer patients had moderate scores of PTG (M = 50.88) and perceived social support (M = 57.39), with a higher score of DR (M = 11.24) than IR (M = 7.33). This moderate PTG level aligns with Wang’s research[25]. This may be because the patient's physical and mental symptoms peak in the postoperative phase, severely disrupting daily life and causing significant trauma[26], which may temporarily eclipse cognitive resources for meaning-making[9]. The moderate perceived social support indicates that while patients receive certain external resources, these may lack specificity[27]. Notably, deliberate rumination scores were higher than IR, reflecting an adaptive rumination pattern in this population, with a tendency toward purposeful reflection rather than painful intrusive thoughts. This indicates that patients tend to respond positively, which is consistent with the findings of Dong et al.[28]. The transition from a negative to a positive mindset after experiencing a traumatic event may promote the development of PTG[29].
This study identified the significant associations among PTG dimensions and rumination. The global network revealed several critical connections, with deliberate rumination showing the strongest positive links to appreciation of life and personal strength. This is consistent with the literature[9]. Deliberate rumination helps individuals reframe adversity and identify new meaning in life through purposeful reflection on trauma-related experiences[11]. Research suggests that deliberate rumination can help individuals actively interpret and process traumatic events, overcome fear responses, and cultivate constructive responses, thereby supporting their growth after trauma[30]. In contrast, the lower IR score suggests that intrusive rumination is not the dominant pattern, but its negative correlation with relating to others in the network still warrants attention. Meaningful interpersonal relationships are one way to promote PTG[9]. Intrusive rumination, typically associated with negative, distressing thoughts[9], may hinder patients’ willingness to engage in social interactions[31], leading to increased helplessness and thus reducing the possibility of growth[9].
Notably, the positive association between “Personal strength” and family support highlights the role of familial care in fostering hope and inner strength in patients[32]. Ding et al. [15] showed that it is crucial to feel and receive support from family and friends. In China, where people emphasize interdependence and obligations to family members, family members are an important source of social support[33]. Family support can help patients build confidence in their recovery, thereby enhancing their perceived personal strength[15]. Family support positively influences the psychological state and resilience of cancer patients[15, 32]. Family support influences the cognitive processing of traumatic events: with the love and support of family members, patients may actively contemplate the impact of the trauma and their subjective feelings, thus increasing the likelihood of enhanced self-strength[34]. The support that patients perceived allows them to experience growth in self-strength and life perception, thereby promoting PTG[34].
Personal strength was identified as the central node of the network, indicating its significant role in PTG development. This is consistent with the view that individuals who have strong confidence or belief in their ability to overcome difficulties can better seize opportunities in stressful environments, thereby promoting their own growth[35]. Patients must adjust to the post-cancer period following treatment[4]. For gastric cancer patients, they face a series of stressors, including emotional instability, fear of recurrence, and role transitions (such as from “healthy individual” to “cancer survivor”)[4], while a strong sense of personal strength enables them to redefine these challenges as opportunities for growth. Changes in personal strength may produce chain reactions through its connections in the network, thereby enhancing other PTG domains. For example, enhancing personal strength may amplify appreciation of life by cultivating a sense of control over adversity, or enhance relating to others by boosting confidence in social interactions.
Deliberate rumination and “Personal strength” were bridge nodes in the network, acting as key links connecting different communities within the network, and showing the dynamic pathway through which psychological resources are transformed into growth. Deliberate rumination serves as the primary bridge in the impact factor communities, while personal strength connects the PTG to these external factors. Deliberate rumination reflects its ability to translate external experiences into internal growth. It helps individuals rebuild their understanding of the post-traumatic world, others, and themselves[20]. During the rehabilitation process, patients feel support from family and friends, which can influence their cognitive processing of traumatic events. Active cognitive processing can help them enhance their resilience and gain a deeper understanding of the meaning of life[36]. This is consistent with research findings that deliberate rumination acts as a bridge, transforming perceived social support into psychological growth and external recognition into internal strength. Furthermore, as argued above, personal strength, as both a core and bridge node, further expands this connectivity by integrating growth within the PTG and external influences. The confidence gained from overcoming postoperative challenges can enhance patients’ ability to discover benefits, pursue spiritual growth, promote interpersonal relationships, and thereby achieve positive personal growth[37]. Healthcare providers should focus on patients’ psychological states and provide targeted psychological counseling. Recognizing perceived social support as an important external resource helps mobilize patients’ internal resources such as positive psychological states and enhance their personal strength[15].
These bridge nodes highlight the importance of targeting both cognitive processes and internal resilience in clinical interventions. Deliberate rumination can be fostered through psychological interventions, which guide patients to reflect on specific challenges and coping strategies, thereby effectively strengthening its role as a “bridge” between support and growth[15]. Similarly, interventions focused on cultivating personal strength, such as setting goals around self-care milestones, can enhance its capacity to transmit growth across PTG dimensions. By reinforcing these bridge nodes, healthcare providers can build a more interconnected network. Within this network, support and rumination not only promote the development of individual dimensions but also generate a ripple effect that further enhances overall post-traumatic growth. This approach goes beyond intervening on isolated factors; instead, it leverages the inherent connectivity of the network to bring about more comprehensive and sustainable psychological adaptation for gastric cancer survivors. For patients with high levels of intrusive rumination, interventions should prioritize improving their interpersonal relationships, such as organizing peer support groups and reducing social avoidance.
4.1 Clinical implications
Exploring precise interactions is essential for elucidating psychological mechanisms and guiding the development of tailored interventions to improve PTG and quality of life in gastric cancer patients. This study highlights the importance of personal strength and deliberate rumination in facilitating PTG among postoperative gastric cancer patients. By identifying bridge nodes and core nodes, effective intervention targets are clarified. These findings suggest that clinical interventions should prioritize strengthening deliberate rumination and personal strength, optimize family support to focus on empowerment, and mitigate the negative impact of intrusive rumination on interpersonal relationships. The study offers advice and new insights for addressing mental health issues and exploring personalized interventions for such patients.
4.2 Study limitations
There are some limitations in this study. The study was designed as a cross-sectional network analysis, limiting causal inference. In addition, the single-center sample may limit generalizability. Future research should adopt longitudinal designs to track network evolution during recovery, and multicenter studies should be conducted to enhance the representativeness of the findings and better generalize them to other populations. Furthermore, efforts should be made to validate the effectiveness of targeted interventions based on the identified core and bridge nodes.
5. Conclusion
This study enriches our understanding of the psychological process of post-traumatic growth in gastric cancer patients, providing a target for personalized treatments to promote psychological healing and enhance mental health in this population.
Funding Information
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

2.2 Ethical approval

The study procedures followed the Declaration of Helsinki and the ethical permissions were granted by the Ethical Committee at Tianjin Medical University (TMUhMEC20230008).

All participants were voluntary to join in this study and signed the informed consent form.

2.3 Measurements

2.3.1 Chinese Post-traumatic Growth Inventory

The Chinese Post traumatic Growth Inventory (C-PTGI) was used to assess PTG. Developed by Tedeschi et al. [11] and adapted into Chinese by Wang et al.[19], it contains 20 items across five dimensions: appreciation of life, personal strength, new possibilities, relating to others and self-transformation. Responses are rated on a 6-point Likert scale, with higher scores indicating greater PTG. C-PTGI has been widely used in cancer patients[10]. The Cronbach’s α coefficient for this scale demonstrates excellent reliability (α = 0.977).

2.3.2 Event-related Rumination Inventory

The Event-related Rumination Inventory (ERRI) was used to assess rumination. Developed by Cann et al. [20] and adapted into Chinese by Dong et al. [21], it contains 20 items across two dimensions: intrusive rumination and deliberate rumination. Responses are rated on a 4-point Likert scale, with higher scores indicating greater intrusive thinking and deliberate thinking. The Cronbach’s α coefficients for the two dimensions of the scale demonstrate good reliability (intrusive α = 0.818, deliberate α = 0.709).

2.3.3 Perceived Social Support Scale

The Perceived Social Support Scale (PSSS) revised by Zimit et al.[22] was used to assess perceived social support, which has been translated and validated for the Chinese population[15]. The scale includes 12 items across three dimensions: family, friends, and significant others. Responses are rated on a 7-point Likert scale, with higher scores indicating greater perceived social support. The Cronbach’s α coefficient for this scale has good reliability (α = 0.888).

2.3.4 Demographic and clinical characteristics

Demographic data included indicators such as gender, age, and education, while disease-related data included diagnosis duration and cancer stage. Sociodemographic and clinical information were selected based on related studies, and data were collected from patient records.

2.4 Statistical analysis

2.4.1 Network estimation

Use R software to construct a network and analyze the relationships between rumination and perceived social support on PTG. Graph Gaussian Model (GGM) with the graphic least absolute shrinkage and selection operator (LASSO) and the Extended Bayesian Information Criterion (EBIC) were used to calculate the polychoric correlations between influencing factors and PTG[17]. The network was visualize using R package qgraph[23]. The edge thickness and saturation represented the strength of connections. Blue edges represented positive correlations and red edges represented negative correlations. Nodes represented dimensions of rumination, perceived social support, and PTG. All nodes were grouped into two communities named impact factors (rumination, perceived social support) and PTG.

The study used the R package qgraph to calculate the Expected Impact (EI) to determine each node's significance within the network. Higher EI indicates greater importance. Additionally, the Bridge Expected Impact (BEI) was calculated to identify bridge nodes connecting different communities. Higher BEI was considered to have greater connectivity with other communities.

2.4.2 Network robustness test

The R package bootnet was used to do the robustness test[24]. Stability of EI and BEI was examined through the correlation stability coefficient (CS-C), with a CS-C value above 0.5 indicating sufficient stability[23]. Edge accuracy was tested by calculating 95% confidence intervals (95% CI) of edge weights. To examine the difference between edge weights, EI, and BEI, bootstrapping tests were also conducted.

3 Results

3.1 Participant characteristics

The demographic and clinical characteristics of the participants are shown in Table 1. A total of 431 participants were enrolled, and 398 participants completed the study. The mean age of the 398 patients was 60.14 ± 11.54 years, with 35.9% were female and 64.1% were male.

Fig. 1

Network Structure with Node EI and BEI Plot. Note: (A) Network Structure of Rumination, Perceived social support and Post-traumatic Growth; (B) Node EI; (C) Node BEI.

Table 2. Correlation matrix.	PTG5	-0.01389	0	0.022146	0.062077	0.06857	0.075903	0.047999	0.542592	0.305143	0	Abbreviations: PTG1-Appreciation of life, PTG2-Personal strength, PTG3-New possibilities, PTG4-Relating to others, PTG5-Self-transformation. P1-Family support, P2-Friend support, P3-Significant others. E1-Intrusive rumination, E2-Deliberate rumination.
	PTG4	-0.15713	0.009559	0	0.001436	0.084078	0.068671	0.366082	0.063588	0	0.305143
	PTG3	-0.09863	0.022628	0	0	0	0.217647	0.22723	0	0.063588	0.542592
	PTG2	0	0.109333	0.113319	0	0	0.305967	0	0.22723	0.366082	0.047999
	PTG1	-0.05937	0.171114	0.022834	0	-0.02282	0	0.305967	0.217647	0.068671	0.075903
	P3	-0.12953	0.022852	0.011627	0.284092	0	-0.02282	0	0	0.084078	0.06857
	P2	0	0.103596	0.315668	0	0.284092	0	0	0	0.001436	0.062077
	P1	-0.08834	0.047606	0	0.315668	0.011627	0.022834	0.113319	0	0	0.022146
	E2	-0.12375	0	0.047606	0.103596	0.022852	0.171114	0.109333	0.022628	0.009559	0
	E1	0	-0.12375	-0.08834	0	-0.12953	-0.05937	0	-0.09863	-0.15713	-0.01389
		E1	E2	P1	P2	P3	PTG1	PTG2	PTG3	PTG4	PTG5

3.3 Network stability

Fig. 1B

shows the EI values of each node, with PTG2 (Personal strength) (EI = 1.17) identified as the core node in the network. Additionally, the BEI values of each node were calculated to identify bridge nodes. Figure 1C shows the BEI value for each node. PTG2 (Personal strength) has the highest value in the PTG community (BEI = 0.24), while E2 (Deliberate rumination) has the highest value in the impact factor community (BEI = 0.31), indicating these two nodes serve as bridges connecting different communities, promoting interaction within the network. Table 3 shows the mean scores and standard deviations for all variables across all dimensions, and the EIs and BEIs in the network.

Competing interests

The authors have no conflicts of interest to disclose.

Ethics approval

The study protocol complied with the Declaration of Helsinki and was approved by the Ethics Committee of Tianjin Medical University with approval number TMUhMEC20230008.

Consent to participate

All participants provided written informed consent.

Data availability statement

The clinical dataset used during the current study is available from the corresponding author on reasonable request.

Author Contribution

All authors contributed to the study conception and design. All listed authors meet the authorship criteria and agree with the content of the manuscript.Lehan Li: Conceptualization, Methodology, Formal analysis, Visualization, Writing-original draft. Yelin Song: Conceptualization, Data curation, Investigation, Writing-review & editing. Shimei Jin: Methodology, Validation, Writing-review & editing. Huiying Wang: Investigation, Data curation. Lina Wang: Investigation, Data curation. Xinran Zhu: Data curation, Writing-review & editing. Changyu Song: Writing-review & editing. Xiaohong Zhang: Writing-review & editing. Shumei Zhuang: Resources, Conceptualization, Supervision, Writing-review & editing.

Lehan Li: Conceptualization, Methodology, Formal analysis, Visualization, Writing-original draft. Yelin Song: Conceptualization, Data curation, Investigation, Writing-review & editing. Shimei Jin: Methodology, Validation, Writing-review & editing. Huiying Wang: Investigation, Data curation. Lina Wang: Investigation, Data curation. Xinran Zhu: Data curation, Writing-review & editing. Changyu Song: Writing-review & editing. Xiaohong Zhang: Writing-review & editing. Shumei Zhuang: Resources, Conceptualization, Supervision, Writing-review & editing.

Electronic Supplementary Material

Below is the link to the electronic supplementary material

Supplementary Material 1

Supplementary Material 2

Supplementary Material 3

Supplementary Material 4

Supplementary Material 5

Supplementary Material 6

References

Bray F, Laversanne M, Sung H, et al (2024) Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: A Cancer Journal for Clinicians 74:229–263. https://doi.org/10.3322/caac.21834

Christodoulidis G, Konstantinos-Eleftherios K, Marina-Nektaria K (2024) Double role of depression in gastric cancer: As a causative factor and as consequence. World Journal of Gastroenterology 30:1266. https://doi.org/10.3748/wjg.v30.i10.1266

Gallanis AF, Gamble LA, Samaranayake SG, et al (2024) Costs of Cancer Prevention: Physical and Psychosocial Sequelae of Risk-Reducing Total Gastrectomy. J Clin Oncol 42:421–430. https://doi.org/10.1200/JCO.23.01238

Wang X, Li X, Zhang Z, et al (2024) A latent profile analysis of psychological resilience in gastric cancer survivors: A cross-sectional study. European Journal of Oncology Nursing 70:102612. https://doi.org/10.1016/j.ejon.2024.102612

Misono S, Weiss NS, Fann JR, et al (2008) Incidence of Suicide in Persons With Cancer. J Clin Oncol 26:4731–4738. https://doi.org/10.1200/JCO.2007.13.8941

Are C, Murthy SS, Sullivan R, et al (2023) Global Cancer Surgery: pragmatic solutions to improve cancer surgery outcomes worldwide. The Lancet Oncology 24:e472–e518. https://doi.org/10.1016/S1470-2045(23)00412-6

Kwon S, Kim J, Kim T, et al (2022) Association between gastric cancer and the risk of depression among South Korean adults. BMC Psychiatry 22:207. https://doi.org/10.1186/s12888-022-03847-w

Shand LK, Cowlishaw S, Brooker JE, et al (2015) Correlates of post-traumatic stress symptoms and growth in cancer patients: a systematic review and meta-analysis. Psycho-Oncology 24:624–634. https://doi.org/10.1002/pon.3719

Tedeschi RG, Calhoun LG (2004) Posttraumatic Growth: Conceptual Foundations and Empirical Evidence. https://doi.org/10.1207/s15327965pli1501_01

10.

Adamkovič M, Fedáková D, Kentoš M, et al (2022) Relationships between satisfaction with life, posttraumatic growth, coping strategies, and resilience in cancer survivors: A network analysis approach. Psycho-Oncology 31:1913–1921. https://doi.org/10.1002/pon.5948

11.

Tedeschi RG, Calhoun LG (1996) The Posttraumatic Growth Inventory: measuring the positive legacy of trauma. J Trauma Stress 9:455–471. https://doi.org/10.1007/BF02103658

12.

Mah A, D’Agostino N, Santiago AT, et al (2024) Connectedness to the young adult cancer community and post-traumatic growth: A young adults with cancer in their prime study. Psycho-Oncology 33:e6325. https://doi.org/10.1002/pon.6325

13.

Scrignaro M, Barni S, Magrin ME (2011) The combined contribution of social support and coping strategies in predicting post-traumatic growth: a longitudinal study on cancer patients. Psycho-Oncology 20:823–831. https://doi.org/10.1002/pon.1782

14.

Wilson JM, Weiss A, Shook NJ (2020) Mindfulness, self-compassion, and savoring: Factors that explain the relation between perceived social support and well-being. Personality and Individual Differences 152:109568. https://doi.org/10.1016/j.paid.2019.109568

15.

Ding Y, Wang X, Zhang F, et al (2024) The relationship between perceived social support, coping style, and the quality of life and psychological state of lung cancer patients. BMC Psychol 12:439. https://doi.org/10.1186/s40359-024-01927-y

16.

Menger F, Mohammed Halim NA, Rimmer B, Sharp L (2021) Post-traumatic growth after cancer: a scoping review of qualitative research. Support Care Cancer 29:7013–7027. https://doi.org/10.1007/s00520-021-06253-2

17.

Epskamp S, Fried EI (2018) A tutorial on regularized partial correlation networks. Psychol Methods 23:617–634. https://doi.org/10.1037/met0000167

18.

Borsboom D, Deserno MK, Rhemtulla M, et al (2021) Network analysis of multivariate data in psychological science. Nat Rev Methods Primers 1:58. https://doi.org/10.1038/s43586-021-00055-w

19.

Wang J, Chen Y, Wang Y, Liu X (2011) Revision of the posttraumatic growth inventory and testing its reliability and validity. J Nurs Sci 26:26–28

20.

Cann A, Calhoun LG, Tedeschi RG, et al (2011) Assessing posttraumatic cognitive processes: the Event Related Rumination Inventory. Anxiety Stress Coping 24:137–156. https://doi.org/10.1080/10615806.2010.529901

21.

Dong C, Gong S, Liu X (2013) Reliability and validity of the simplified Chinese Version of Event Related Rumination Inventory among accidentally injured patients. Chinese Journal of Nursing 48:831–834

22.

Zimet GD, Powell SS, Farley GK, et al (1990) Psychometric characteristics of the Multidimensional Scale of Perceived Social Support. J Pers Assess 55:610–617. https://doi.org/10.1080/00223891.1990.9674095

23.

Epskamp S, Borsboom D, Fried EI (2018) Estimating psychological networks and their accuracy: A tutorial paper. Behav Res Methods 50:195–212. https://doi.org/10.3758/s13428-017-0862-1

24.

McNally RJ (2021) Network Analysis of Psychopathology: Controversies and Challenges. Annu Rev Clin Psychol 17:31–53. https://doi.org/10.1146/annurev-clinpsy-081219-092850

25.

Wang J, Li R, Zhang H, Hao N (2019) The Mediating Effect of Perceived Social Support on Family Function and Post-Traumatic Growth in Patients with Gastric Cancer. Chinese Medical Ethics 32:1481–1486

26.

Lilley EJ, Lu P, Robinson K, et al (2024) High symptom burden in patients undergoing gastrectomy for cancer. Journal of Surgical Oncology 129:228–232. https://doi.org/10.1002/jso.27492

27.

Bou-Samra P, Scott P, Cheng H, et al (2021) Social Support is Associated with Survival in Patients Diagnosed with Gastrointestinal Cancer. Journal of gastrointestinal cancer 53:854. https://doi.org/10.1007/s12029-021-00741-8

28.

Dong C, Gong S, Jiang L, et al (2015) Posttraumatic growth within the first three months after accidental injury in China: the role of self-disclosure, cognitive processing, and psychosocial resources. Psychol Health Med 20:154–164. https://doi.org/10.1080/13548506.2014.913795

29.

Wan X, Zhang Y, Peng Q, et al (2024) A study of the relationship and mediating effects of perceived stress and post-traumatic growth in patients undergoing postoperative chemotherapy for breast cancer. European Journal of Oncology Nursing 71:102659. https://doi.org/10.1016/j.ejon.2024.102659

30.

Sun L, Deng J, Xu J, Ye X (2022) Rumination’s Role in Second Victim Nurses’ Recovery From Psychological Trauma: A Cross-Sectional Study in China. Frontiers in Psychology 13:860902. https://doi.org/10.3389/fpsyg.2022.860902

31.

Song Y-Y, Liu H, Wang S, Jiang X-L (2022) Dyadic effects of rumination and self-disclosure on posttraumatic growth in newly diagnosed gynecological cancer couples: an actor-partner interdependence modeling approach. Support Care Cancer 30:5167–5174. https://doi.org/10.1007/s00520-022-06869-y

32.

Song D, Bai Y, Liu Y, Li Y (2024) Patterns and predictors of symptom burden and posttraumatic growth among patients with cancer: a latent profile analysis. Support Care Cancer 32:363. https://doi.org/10.1007/s00520-024-08577-1

33.

Feng Y, Liu X, Zhang S, et al (2024) Relationship among post-traumatic growth, spiritual well-being, and perceived social support in Chinese women with gynecological cancer. Sci Rep 14:4847. https://doi.org/10.1038/s41598-024-55605-5

34.

Wang D, Zhang Z, Lin B, et al (2022) Mediating Effect of Rumination between Perceived Social Support and Post-Traumatic Growth among Young and Middle-aged Stroke Patients and Differences between Genders. Military Nursing 39:48–52

35.

Bandura A (1999) Social Cognitive Theory: An Agentic Perspective. Asian Journal of Social Psychology 2:21–41. https://doi.org/10.1111/1467-839X.00024

36.

Liu G, Lai H, Yao J (2024) Mediating effect of rumination between post-traumatic growth and perceived social support in patients with accidental trauma. Clinical Research and Practice 9:76–79 + 133. https://doi.org/10.19347/j.cnki.2096-1413.202422019

37.

Li L, Su Y (2024) Mediation Effects of Self-care Self-efficacy and Health-promoting Behaviors on Fear of Cancer Recurrence and Posttraumatic Growth in Postoperative Patients With Cervical Cancer: A Cross-sectional Study. Asian Nursing Research 18:468–478. https://doi.org/10.1016/j.anr.2024.10.003

Table 3. Mean, Standard Deviation, Expected Impact and Expected Bridge Impact of Nodes.

Table 2. Correlation matrix.	PTG5	-0.01389	0	0.022146	0.062077	0.06857	0.075903	0.047999	0.542592	0.305143	0	Abbreviations: PTG1-Appreciation of life, PTG2-Personal strength, PTG3-New possibilities, PTG4-Relating to others, PTG5-Self-transformation. P1-Family support, P2-Friend support, P3-Significant others. E1-Intrusive rumination, E2-Deliberate rumination.
	PTG4	-0.15713	0.009559	0	0.001436	0.084078	0.068671	0.366082	0.063588	0	0.305143
	PTG3	-0.09863	0.022628	0	0	0	0.217647	0.22723	0	0.063588	0.542592
	PTG2	0	0.109333	0.113319	0	0	0.305967	0	0.22723	0.366082	0.047999
	PTG1	-0.05937	0.171114	0.022834	0	-0.02282	0	0.305967	0.217647	0.068671	0.075903
	P3	-0.12953	0.022852	0.011627	0.284092	0	-0.02282	0	0	0.084078	0.06857
	P2	0	0.103596	0.315668	0	0.284092	0	0	0	0.001436	0.062077
	P1	-0.08834	0.047606	0	0.315668	0.011627	0.022834	0.113319	0	0	0.022146
	E2	-0.12375	0	0.047606	0.103596	0.022852	0.171114	0.109333	0.022628	0.009559	0
	E1	0	-0.12375	-0.08834	0	-0.12953	-0.05937	0	-0.09863	-0.15713	-0.01389
		E1	E2	P1	P2	P3	PTG1	PTG2	PTG3	PTG4	PTG5

Node abbreviation	Node content	M	SD	EI	BEI
PTG1	Appreciation of life	14.66	8.79	0.78	0.10
PTG2	Personal strength	7.76	4.50	1.17	0.24
PTG3	New possibilities	10.65	5.93	0.98	-0.08
PTG4	Relating to others	7.26	4.32	0.74	-0.07
PTG5	Self-transformation	10.55	6.07	1.12	0.14
P1	Family support	22.84	2.38	0.44	0.16
P2	Friend support	18.65	3.24	0.77	0.06
P3	Significant others	15.89	3.34	0.32	0.13
E1	Intrusive rumination	7.33	4.27	-0.67	-0.33
E2	Deliberate rumination	11.24	3.06	0.35	0.31

M: Mean; SD: Standard Deviation; EI: Expected Influence; BEI: Bridge Expected Influences.

Table 1. Demographic characteristics of participants (n = 398).

Characteristics	N	Percentage	Mean ± SD
Age	398		60.14 ± 11.54
Gender
Male	255	64.1%
Female	143	35.9%
Educational level
Primary school and below	94	23.6%
Junior high school	105	26.4%
Senior high school and above	199	50.0%
Ethnic group
Han nationality	385	96.7%
Other nationalities	13	3.3%
Marriage
Unmarried	6	1.5%
Married	390	98.0%
Divorce	2	0.5%
Long-term residence
City	181	45.5%
Town	66	16.6%
Countryside	151	37.9%
Occupation
Yes	230	57.8%
No	168	42.2%
Income (per capita)
<2000	107	26.9%
2000–5000	173	43.5%
≥ 5000	118	29.6%
Surgical modality
Subtotal gastrectomy	56	14.1%
Total gastrectomy	317	93.7%
Others	25	6.3%
Caregiver
Parents	5	1.26%
Spouse	132	33.17%
Children	218	54.77%
Nursing workers	16	4.02%
Cancer stage
Ⅰ	56	14.1%
Ⅱ	41	10.3%
Ⅲ	301	75.6%

Yes