
==== Front
BMC Psychol
BMC Psychol
BMC Psychology
2050-7283
BioMed Central London

1964
10.1186/s40359-024-01964-7
Research
The bridge relationships of PTSD and depression symptoms among snakebite victims: a cross-sectional community-based survey
Chen Yu 1
Fu Wenning 2
Song Xingyue 3
Hu Yanlan 1
Wang Juntao 1
Hao Wenjie 1
He Lanfen 1
Diané Mohamed 4
Souaré Ibrahima Sory 4
Guo Wei 5
Lv Chuanzhu 67
Han Xiaotong Hanxiaotong2021@163.com

8
Yan Shijiao yanshijiao@hainmc.edu.cn

17
1 https://ror.org/004eeze55 grid.443397.e 0000 0004 0368 7493 School of Public Health, Hainan Medical University, Haikou, Hainan China
2 https://ror.org/00p991c53 grid.33199.31 0000 0004 0368 7223 School of Nursing, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei China
3 grid.443397.e 0000 0004 0368 7493 Department of Emergency, Hainan Clinical Research Center for Acute and Critical Diseases, The Second Affiliated Hospital of Hainan Medical University, Haikou, Hainan China
4 China-Guinea Friendship Hospital, Kipe Ratoma 030 BP710 Guinea Friendship Hospital, Conakry, Guinea
5 https://ror.org/013xs5b60 grid.24696.3f 0000 0004 0369 153X Emergency Department, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
6 grid.54549.39 0000 0004 0369 4060 Emergency Medicine Center, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan China
7 https://ror.org/004eeze55 grid.443397.e 0000 0004 0368 7493 Research Unit of Island Emergency Medicine, Chinese Academy of Medical Sciences (No. 2019RU013), Hainan Medical University, Haikou, Hainan China
8 grid.411427.5 0000 0001 0089 3695 Department of Emergency Medicine, Hunan Provincial Key Laboratory of Emergency and Critical Care Metabolomics, Hunan Provincial Institute of Emergency Medicine, Hunan Provincial People’s Hospital/The First Affiliated Hospital, Hunan Normal University, Changsha, Hunan China
4 9 2024
4 9 2024
2024
12 47016 6 2024
22 8 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Background

The incidence of comorbid depression and post-traumatic stress disorder (PTSD) symptoms is higher in snakebite victims. However, the present state and contributing factors of depression and PTSD among Chinese snakebite victims remain unclear.

Methods

A representative sample of 6837 snakebite victims were assessed with the Post-traumatic Stress Disorder Checklist (Civilian Version) and The Center for Epidemiologic Studies Depression Scale. Multivariate analyses, including network analysis, evaluated the contributing factors of PTSD and depression symptoms caused by snake bites, as well as the bridge symptoms of comorbidity networks.

Results

Among 6,837 snakebite victims, 79.5% reported PTSD symptoms and 81.4% reported depression symptoms. Comorbidity of PTSD and depression symptoms was found in 75.1%. Key factors included the presence sequelae after snakebite (ORPTSD = 2.31, ORDepression = 1.89), time to medical facilities (6–8 h: ORPTSD = 3.17, ORDepression = 2.46), and marital status (divorced/widowed: ORPTSD = 1.78, ORDepression = 1.76). Symptoms I1 ("Repeated disturbing memories") and D1 ("Bothered by things that don't usually bother me") bridged PTSD and depression networks.

Conclusion

The primary psychological challenges for snakebite victims in China are PTSD and depression symptoms, which is concerning. Standardized diagnosis and treatments, timely medical care, and stable marital relationships can reduce risks. Additional psychological support and management of negative memories, especially for those with severe bridge symptoms, can be beneficial. Further research should concentrate on understanding victims' psychological states and developing effective interventions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40359-024-01964-7.

Keywords

Snakebite
Post-traumatic stress disorder
Depression
Network analysis
Hainan Province Science and Technology Special FundZDKJ202004 Lv Chuanzhu National Natural Science Foundation of China82160647 Lv Chuanzhu Hainan Provincial Natural Science Foundation of China821RC557 Yan Shijiao Hainan Clinical Medical Research Center ProjectLCYX202310 Yan Shijiao issue-copyright-statement© BioMed Central Ltd., part of Springer Nature 2024
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pmcIntroduction

Snakebite envenomation is a severe injury characterized by local and systemic toxic reactions following the penetration of snake venom into an individual's skin through snake fangs [1]. Previous studies have indicated that snakebite victims may suffer from long-term psychological disorders in addition to physical sequelae. Post-traumatic stress disorder (PTSD) and depression are the most common psychological issues associated with snakebites [2]. Prevalence estimates variable with PTSD among snakebite victims ranging from 8 to 43% and depression prevalence ranging from 25 to 54% [3–6]. In China, however, there is a lack of comprehensive data on the mental health of snakebite victims, and the factors affecting these psychological conditions are not well defined.

In addition, the rates of comorbidity between PTSD and depression are high [7]. Psychological research has demonstrated that PTSD and depression mutually affect each other [8–10]. However, analyzing the factors of PTSD and depression independently will ignore the complex relationship between them. Network analysis enables the exploration of bridge symptoms (the symptoms that connect the two mental disorders) and the interrelations between PTSD and depression. Studies have developed symptom networks for different populations, such as patients with cancer undergoing chemotherapy, individuals with bipolar disorder, and patients with acute PTSD, to identify the complex relationships between various disease symptoms [11–13]. A network analysis of 1,489 veterans seeking treatment found meaningful connections between PTSD and depression [14]. Furthermore, early interventions for bridge symptoms that reduced their severity could enhance the overall effectiveness of interventions, Castro et al. [15] summarized published data, reporting that interventions targeting bridge symptoms to be more effective than others. However, there is no research on the bridge symptoms between PTSD and depression among snakebite victims.

Therefore, this study aimed to clarify the psychological health status of snakebite victims in China, along with the associated factors with PTSD, depression, and their comorbidity due to snakebites. We also constructed a network of PTSD and depression symptoms using network analysis methods. This study explores the bridge symptom between PTSD and depression among snakebite victims in China, providing insights for developing psychological intervention strategies, addressing a gap in previous research.

Materials and methods

Study design

To investigate the associated factors of PTSD, depression and comorbidity, as well as bridge symptoms among snakebite victims in China, a cross-sectional survey is essential. This approach efficiently gathers extensive data at a single time point, offering a comprehensive overview of the current psychological health status of these patients. It aids in identifying key contributing factors and bridge symptoms, thereby providing a foundation for subsequent in-depth research, clinical interventions, and policy formulation.

Therefore, a community-based cross-sectional survey was conducted from May 2022 to February 2023 in 12 provinces and regions in China south of the Yangtze River that are known for their high incidences of snakebites (i.e., Hubei, Hunan, Guangdong, Guangxi, Hainan, Zhejiang, Fujian, Jiangxi, Sichuan, Guizhou, Yunnan, and Chongqing). This study employed multistage random and convenience sampling to select participants. Initially, three cities were selected from each province (municipality or autonomous region), three districts from each city, and three villages from each district, resulting in 324 community points. Subsequently, convenience sampling was used to survey 30 to 50 residents from each community or village. In areas with low literacy levels, oral questionnaires were provided to facilitate participation. At the same time, we used the instant message software WeChat (Shenzhen Tencent Computer System Co., Ltd, Shenzhen, China) and Tencent QQ (Shenzhen Tencent Computer System Co., Ltd, Shenzhen, China) to show advertisements or pop-up invitations in other regions to recruit random residents to participate in the same online survey we used in the villages. A total of 56,804 residents participated in the survey, of which 6,987 residents with a history of snakebite were followed up. The survey was conducted by students with a medical background, and quality control was supervised by two professors specializing in public health.

Participants

The inclusion criteria for participants included: 1) a history of snakebites; 2) ordinary residents aged 7–70; 3) a willingness to participate in this study. Exclusion criteria included: 1) a history of mental illness, including depression, anxiety, schizophrenia, etc.; 2) language barriers; 3) the presence of other severe underlying diseases.

To confirm participants' eligibility, we implemented the following procedures. An initial screening interview was conducted, which involved a detailed inquiry into the participants' health history to exclude individuals with unrecorded mental health issues. During this interview, participants' language abilities were also assessed to ensure that those with language barriers who might not fully understand or respond accurately to the survey questions were excluded. Additionally, for individuals with other serious underlying conditions, we used inquiries into their medical history to exclude those whose conditions might significantly impact the research outcomes. Following these rigorous screening procedures, a total of 6,987 snakebite victims were investigated, but 150 participants were missing covariates, so ultimately 6,837 investigators met the inclusion criteria and agreed to participate in this study (The flow chart is shown in Fig. 1).Fig. 1 Flow chart of participants included

Ethical statement

This study was approved by the Medical Ethics Committee of the Hainan Medical University (ethics number: HYLL-2022-226). Data were collected with the consent of all participants, who participated voluntarily and anonymously.

Survey instruments

Post-traumatic stress disorder checklist civilian version (PCL-C)

In this study, PTSD symptoms among snakebite victims were diagnosed using the PCL-C [16], which includes 17 items across three symptom clusters: re-experiencing (items 1–5), avoidance/numbing (items 6–12), and arousal (items 13–17). Items on the PCL-C are rated on a 5-point scale from 1 (not at all) to 5 (extremely), with a cumulative score range from 17–85. Higher scores indicated more severe PTSD-related symptoms. PCL-C scores ≥ 38 was used as the diagnostic criterion for PTSD. PCL-C has demonstrated strong reliability and validity in diverse trauma-exposed populations, including those in different cultural contexts [17, 18]. In this study, the Cronbach's α for the PCL-C scale was 0.97.

The center for epidemiologic studies depression scale (CES-D)

Depression symptoms among snakebite victims were diagnosed using the CES-D scale [19], which includes 20 items across four symptom clusters: depressed affect (items 1, 3, 6, 9, 10, 14, 17, and 18), positive affect (items 4, 8, 12, and 16), somatic complaints (items 2, 5, 7, 11, 13, and 20), and interpersonal problems (items 15 and 19). Positive affect statements were reverse-scored when the total score was calculated. Items were rated from 0 (Rarely or None of the Time) to 3 (Most or Almost All the Time), with a cumulative score range of 0–60. Higher scores indicate more severe depression-related symptoms. CES-D total scores ≥ 16 were used as the diagnostic criterion for depression. CES-D has been extensively validated for assessing depression severity across various demographic groups and has shown high sensitivity and specificity in clinical and general populations [20–22].In this study, the Cronbach's α for the CES-D scale was 0.97.

Covariates

Covariates included participants' age, gender, marital status, educational level, occupation, severity of pain caused by snakebite, time to visit a medical facility after snakebite, injection of antivenom serum after snakebite, and presence of sequelae after snakebite. All covariates were collected using a standardized questionnaire. In addition to our established protocols, we have implemented strict data integrity measures to ensure accuracy and reliability. We designed our online survey using Questionnaire Star (Questionnaire Star, Hanover, Germany), which provided us with a weblink. This link was distributed to participants through advertisements and pop-ups on QQ and WeChat. All participants were assigned a unique identifier while completing the online survey to prevent repeat submissions.

Data analysis

All statistical analyses were performed using SPSS 27.0 and R 4.3.2. Descriptive statistics for categorical variables were summarized using percentages and frequencies, and Chi-square (χ2) tests were used to calculate associations between categorical variables. Generalized linear regression (for specific variable encoding, see Supplementary Materials Table S1) was conducted to clarify the prevalence of conditions among snakebite victims and identify related factors contributing to PTSD, depression, and comorbidities symptoms. All significance tests were two-sided, with p < 0.05 being considered statistically significant.

A network model was constructed using the Gaussian graphical model network method to model the partial correlations between PTSD and depression symptoms [23], employing LASSO regularization. Similar to previous concurrent mental symptom network studies [24], overlapping symptoms were removed from the CES-D, including Items 5 (difficulty sleeping) and 11 (difficulty concentrating; Supplementary Materials Table S2). The Bootnet package was used to evaluate the accuracy and stability of the network, and the accuracy was assessed by calculating the 95% Confidence Intervals (CI) of the edge weight values. Bridge expectation influence and bridge strength [25] were used to characterize the bridge symptoms between PTSD and depression. Additionally, centrality indices such as Strength, Betweenness, and Closeness were used to identify central symptoms in the snakebite victim network, with each node's predictability identified using the MGM package.

Results

Participant characteristics, prevalence, and contributing factors

The study included 6,837 snakebite victims: men (68.0%), aged 18–40 years (77.0%), married (51.8%), with less than a college education (83.5%), farmers (19.5%), mild pain (40.9%), time to medical facilities within 2 h (33.1%), receiving injection of antivenom serum after the snakebite (75.6%), and experiencing sequelae after the snakebite (55.3%).The study observed that 79.5% of snakebite victims reported symptoms of PTSD, 81.4% reported symptoms of depression, and 75.1% reported comorbid of PTSD and depression, based on self-reported measures. Chi-square tests demonstrated that PTSD, depression, and their comorbidity symptoms due to snakebite were significantly associated with age, marital status, educational level, occupation, severity of pain caused by snakebites, time to medical facility after snakebite, and presence of sequelae after snakebite (p < 0.05; Table 1). Table 1 Self-reported PTSD, depression, and comorbidity among 6,837 snakebite victims

Variable	n (%)	Presence of PTSD	p	Presence of depression	p	Comorbidity	p	
No	Yes	No	Yes	No	Yes	
n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	
Overall	6837(100.0)	1404(20.5)	5433(79.5)		1275(18.6)	5562(81.4)		1700(24.9)	5137(75.1)		
Gender				0.984			0.002			0.096	
 Men	4652(68.0)	955(20.5)	3697(79.5)		821(17.6)	3831(82.4)		1129(24.3)	3523(75.7)		
 Women	2185(32.0)	449(20.5)	1736(79.5)		454(20.8)	1731(79.2)		571(26.1)	1614(73.9)		
Age (years)				 < .001			 < .001			 < .001	
 < 18	433(6.3)	116(26.8)	317(73.2)		87(20.1)	346(79.9)		132(30.5)	301(69.5)		
 18–40	5262(77.0)	888(16.9)	4374(83.1)		849(16.1)	4413(83.9)		1114(21.2)	4148(78.8)		
 41–60	912(13.3)	295(32.3)	617(67.7)		265(29.1)	647(70.9)		340(37.3)	572(62.7)		
 > 60	230(3.4)	105(45.7)	125(54.3)		74(32.2)	156(67.8)		114(49.6)	116(50.4)		
Marital Status				 < .001			 < .001			 < .001	
 Married	3541(51.8)	867(24.5)	2674(75.5)		810(22.9)	2731(77.1)		1054(29.8)	2487(70.2)		
 Unmarried	2606(38.1)	435(16.7)	2171(83.3)		373(14.3)	2233(85.7)		523(20.1)	2083(79.9)		
 Divorced/Widowed	690(10.1)	102(14.8)	588(85.2)		92(13.3)	598(86.7)		123(17.8)	567(82.2)		
Educational Level				 < .001			0.039			0.006	
 Primary school or below	1539(22.5)	341(22.2)	1198(77.8)		281(18.3)	1258(81.7)		396(25.7)	1143(74.3)		
 Junior high school	1333(19.5)	265(19.9)	1068(80.1)		222(16.7)	1111(83.3)		320(24.0)	1013(76.0)		
 High school/Technical school	1509(22.1)	276(18.3)	1233(81.7)		272(18.0)	1237(82.0)		337(22.3)	1172(77.7)		
 Junior college	1331(19.5)	250(18.8)	1081(81.2)		260(19.5)	1071(80.5)		326(24.5)	1005(75.5)		
 Bachelor's degree or above	1125(16.5)	272(24.2)	853(75.8)		240(21.3)	885(78.7)		321(28.5)	804(71.5)		
Occupation				 < .001			 < .001			 < .001	
 Farmer	1334(19.5)	397(29.8)	937(70.2)		335(25.1)	999(74.9)		466(34.9)	868(65.1)		
 Skilled laborer	1247(18.2)	199(16.0)	1048(84.0)		193(15.5)	1054(84.5)		255(20.4)	992(79.6)		
 Cadre Employee	1038(15.2)	179(17.2)	859(82.8)		161(15.5)	877(84.5)		218(21.0)	820(79.0)		
 Service worker	1136(16.6)	159(14.0)	977(86.0)		161(14.2)	975(85.8)		207(18.2)	929(81.8)		
 Medical staff	499(7.3)	137(27.5)	362(72.5)		119(23.8)	380(76.2)		159(31.9)	340(68.1)		
 Land and sea field operator	171(2.5)	20(11.7)	151(88.3)		28(16.4)	143(83.6)		31(18.1)	140(81.9)		
 Snake catcher or operator	219(3.2)	27(12.3)	192(87.7)		32(14.6)	187(85.4)		39(17.8)	180(82.2)		
 Student	347(5.1)	82(23.6)	265(76.4)		57(16.4)	290(83.6)		91(26.2)	256(73.8)		
 Freelancer	373(5.5)	98(26.3)	275(73.7)		92(24.7)	281(75.3)		112(30.0)	261(70.0)		
 Self-employed	345(5.0)	77(22.3)	268(77.7)		72(20.9)	273(79.1)		91(26.4)	254(73.6)		
 Not reported	128(1.9)	29(22.7)	99(77.3)		25(19.5)	103(80.5)		31(24.2)	97(75.8)		
Severity of Pain				 < .001			 < .001			 < .001	
 No significant pain	1493(21.8)	341(22.8)	1152(77.2)		320(21.4)	1173(78.6)		406(27.2)	1087(72.8)		
 Mild pain (does not affect sleep)	2793(40.9)	498(17.8)	2295(82.2)		475(17.0)	2318(83.0)		610(21.8)	2183(78.2)		
 Moderate pain (affects normal sleep)	1947(28.5)	410(21.1)	1537(78.9)		351(18.0)	1596(82.0)		485(24.9)	1462(75.1)		
 Severe pain (severely affects sleep)	604(8.8)	155(25.7)	449(74.3)		129(21.4)	475(78.6)		199(32.9)	405(67.1)		
Time to medical facility (hours)				 < .001			 < .001			 < .001	
 Within 2 h	2265(33.1)	688(30.4)	1577(69.6)		619(27.3)	1646(72.7)		799(35.3)	1466(64.7)		
 2–4 h	1377(20.1)	255(18.5)	1122(81.5)		205(14.9)	1172(85.1)		303(22.0)	1074(78.0)		
 4–6 h	1192(17.4)	165(13.8)	1027(86.2)		143(12.0)	1049(88.0)		205(17.2)	987(82.8)		
 6–8 h	773(11.3)	88(11.4)	685(88.6)		93(12.0)	680(88.0)		113(14.6)	660(85.4)		
 8–10 h	427(6.2)	51(11.9)	376(88.1)		60(14.1)	367(85.9)		76(17.8)	351(82.2)		
 10–12 h	337(4.9)	27(8.0)	310(92.0)		40(11.9)	297(88.1)		49(14.5)	288(85.5)		
 > 12 h	213(3.1)	44(20.7)	169(79.3)		47(22.1)	166(77.9)		61(28.6)	152(71.4)		
 Unclear	253(3.7)	86(34.0)	167(66.0)		68(26.9)	185(73.1)		94(37.2)	159(62.8)		
Injection of antivenom serum				0.534			0.406			0.473	
 No	1665(24.4)	333(20.0)	1332(80.0)		299(18.0)	1366(82)		403(24.2)	1262(75.8)		
 Yes	5172(75.6)	1071(20.7)	4101(79.3)		976(18.9)	4196(81.1)		1297(25.1)	3875(74.9)		
Sequelae after snakebite				 < .001			 < .001			 < .001	
 No	3059(44.7)	882(28.8)	2177(71.2)		749(24.5)	2310(75.5)		1011(33.1)	2048(66.9)		
 Yes	3778(55.3)	522(13.8)	3256(86.2)		526(13.9)	3252(86.1)		689(18.2)	3089(81.8)		

Generalized linear regression of PTSD, depression, and comorbidity symptoms among snakebite victims

Generalized linear regression identified several significant factors associated with the occurrence of PTSD symptoms and depression symptoms in snakebite victims. Marital status (divorced/widowed: OR = 1.78, 95% CI: 1.40–2.27), the severity of pain caused by snakebite (mild pain, not affecting sleep: OR = 1.42, 95% CI: 1.20–1.67), time to medical facilities (10–12 h: OR = 4.27, 95% CI: 2.82–6.46), not receiving antivenom serum (OR = 1.24, 95% CI: 1.06–1.45), and the presence sequelae after snakebite (OR = 2.31, 95% CI: 2.02–2.64) were identified as risk factors for developing PTSD symptoms. Conversely, age (> 60 years: OR = 0.47, 95% CI: 0.33–0.68) was found to be a protective factor against PTSD symptoms occurrence.

For self-reported depression, risk factors included marital status (divorced/widowed: OR = 1.76, 95% CI: 1.38–2.25), the severity of pain caused by snakebite (mild pain, not affecting sleep: OR = 1.38, 95% CI: 1.17–1.64), time to medical facilities (6–8 h: OR = 2.46, 95% CI: 1.93–3.14), not receiving antivenom serum (OR = 1.18, 95% CI: 1.01–1.39), and the presence sequelae after snakebite (OR = 1.89, 95% CI: 1.65–2.16). Protective factors against depression included gender (OR = 0.84, 95% CI: 0.73–0.95) and age (> 60 years: OR = 0.58, 95% CI: 0.40–0.86).

The factors associated with comorbidity symptoms of PTSD and depression among snakebite victims closely aligned with those impacting self-rated PTSD and depression (Table 2). Specifically, age (> 60 years: OR = 0.50, 95% CI: 0.35–0.71), marital status (divorced/widowed: OR = 1.92, 95% CI: 1.53–2.39), educational level (bachelor's degree or above: OR = 0.73, 95% CI: 0.60–0.88), the severity of pain caused by snakebite (mild pain, not affecting sleep: OR = 1.37, 95% CI: 1.17–1.60), time to medical facilities (6–8 h: OR = 2.96, 95% CI: 2.36–3.71), not receiving antivenom serum (OR = 1.20, 95% CI: 1.04–1.39), and the presence of sequelae after snakebite (OR = 2.04, 95% CI: 1.80–2.31) were the main factors associated with comorbidity of PTSD and depression. Table 2 Contributing factors of PTSD, depression, and comorbidity in snakebite victims (N = 6,837)

Variable	PTSD	Depression	Comorbidity	
B	SE	Wald χ2	OR (95%CI)	B	SE	Wald χ2	OR (95%CI)	B	SE	Wald χ2	OR (95%CI)	
Constant	-0.18	0.14	1.62	0.84(0.63–1.1)	0.38	0.15	6.41	1.46(1.09–1.95)*	-0.24	0.13	3.16	0.79(0.61–1.03)	
Gender	
 Male				1				1				1	
 Female	0.03	0.07	0.17	1.03(0.90–1.18)	-0.18	0.07	6.98	0.84(0.73–0.95)**	-0.07	0.06	1.20	0.93(0.82–1.06)	
Age	
 < 18				1				1				1	
 18–40	0.52	0.13	17.33	1.69(1.32–2.16)***	0.24	0.14	3.17	1.27(0.98–1.66)	0.45	0.12	14.37	1.57(1.24–1.99)***	
 41–60	-0.23	0.14	2.67	0.79(0.60–1.05)	-0.40	0.15	7.13	0.67(0.50–0.90)**	-0.22	0.14	2.62	0.80(0.62–1.05)	
 > 60	-0.76	0.19	16.61	0.47(0.33–0.68)***	-0.54	0.20	7.56	0.58(0.40–0.86)**	-0.70	0.18	15.13	0.50(0.35–0.71)***	
Marital Status	
 Married				1				1				1	
 Unmarried	0.27	0.07	14.6	1.31(1.14–1.51)***	0.40	0.07	30.74	1.50(1.30–1.73)***	0.34	0.07	27.26	1.41(1.24–1.6)***	
 Divorced/Widowed	0.58	0.12	22.3	1.78(1.40–2.27)***	0.57	0.12	20.57	1.76(1.38–2.25)***	0.65	0.11	32.90	1.92(1.53–2.39)***	
Educational Level	
 Primary school or below				1				1				1	
 Junior high school	0.02	0.10	0.03	1.02(0.83–1.24)	0.04	0.11	0.18	1.05(0.85–1.29)	-0.02	0.09	0.06	0.98(0.81–1.18)	
 High school/Technical school	0.06	0.10	0.40	1.07(0.88–1.29)	-0.13	0.10	1.59	0.88(0.72–1.07)	0.01	0.09	0.02	1.01(0.84–1.21)	
 Junior college	-0.01	0.10	0.01	0.99(0.81–1.21)	-0.24	0.10	5.36	0.78(0.64–0.96)	-0.14	0.10	2.07	0.87(0.72–1.05)	
 Bachelor's degree or above	-0.30	0.10	8.39	0.74(0.60–0.91)**	-0.33	0.11	9.23	0.72(0.58–0.89)**	-0.32	0.10	10.74	0.73(0.60–0.88)**	
Severity of pain	
 No significant pain				1				1				1	
 Mild pain (not affecting sleep)	0.35	0.09	16.36	1.42(1.20–1.67)***	0.32	0.09	14.06	1.38(1.17–1.64)***	0.31	0.08	15.45	1.37(1.17–1.60)***	
 Moderate pain (affecting normal sleep)	0.13	0.09	2.11	1.14(0.96–1.36)	0.26	0.09	8.07	1.30(1.09–1.56)**	0.14	0.08	2.77	1.15(0.98–1.36)	
 Severe pain (severely affecting sleep)	0.02	0.12	0.02	1.02(0.8–1.29)	0.14	0.13	1.23	1.15(0.9–1.47)	-0.14	0.11	1.64	0.87(0.69–1.08)	
Time to medical facility	
 < 2 h				1				1				1	
 2–4 h	0.55	0.09	40.57	1.74(1.47–2.06)***	0.66	0.09	51.75	1.94(1.62–2.32)***	0.57	0.08	47.71	1.76(1.50–2.07)***	
 4–6 h	0.88	0.10	77.00	2.41(1.98–2.93)***	0.87	0.10	70.42	2.39(1.95–2.93)***	0.85	0.09	83.77	2.33(1.94–2.79)***	
 6–8 h	1.15	0.13	82.41	3.17(2.47–4.07)***	0.90	0.12	52.88	2.46(1.93–3.14)***	1.08	0.12	88.20	2.96(2.36–3.71)***	
 8–10 h	1.02	0.16	39.76	2.77(2.02–3.81)***	0.66	0.15	19.04	1.94(1.44–2.6)***	0.77	0.14	30.68	2.16(1.65–2.84)***	
 10–12 h	1.45	0.21	47.07	4.27(2.82–6.46)***	0.86	0.18	23.00	2.36(1.66–3.35)***	1.01	0.17	36.88	2.74(1.98–3.79)***	
 > 12 h	0.62	0.19	11.09	1.86(1.29–2.67)**	0.29	0.18	2.59	1.33(0.94–1.89)	0.38	0.17	5.24	1.47(1.06–2.03)*	
 Unclear	-0.05	0.15	0.13	0.95(0.71–1.27)	0.10	0.16	0.40	1.11(0.81–1.51)	0.03	0.15	0.05	1.03(0.78–1.38)	
Injection of antivenom serum	
 Yes				1				1				1	
 No	0.22	0.08	7.22	1.24(1.06–1.45)**	0.17	0.08	4.24	1.18(1.01–1.39)*	0.18	0.07	6.08	1.20(1.04–1.39)*	
Sequelae after snakebite	
 No				1				1				1	
 Yes	0.84	0.07	151.67	2.31(2.02–2.64)***	0.63	0.07	84.32	1.89(1.65–2.16)***	0.71	0.06	128.71	2.04(1.80–2.31)***	
Abbreviations: Cl Confidence interval, OR Odds ratio

*p < .05

**p < .01

***p < .001

Characteristics and interrelationships of symptom networks

Network analysis was employed to explore the interconnections between PTSD and depression symptoms and identify the bridge relationships between them. Figure 2 (a) illustrates the symptom network for snakebite victims with PTSD and depression symptoms, featuring 35 nodes and 410 non-zero edges. The blue lines connecting the nodes indicate positive edge weights, and the red lines represent negative edge weights. The magnitude of the edge weights is indicated by the thickness and color intensity of the lines. Bootstrap analysis of the edge weights (Fig. 2 (b)) yields small confidence intervals, indicating the high precision of the network.Fig. 2 a PTSD and depression network among snakebite victims. Positive edges appear in blue and negative appear in red. The stronger and saturated edges represent stronger regularized partial correlations, the circle around the node represent it's predictability (see Supplementary Materials Table S2 for specific node symptoms and short names); b Bootstrapped confidence intervals of all edge weights of PTSD and depression network among snakebite victims. The red line represents sample values, the black line represents bootstrap means, and the gray area is the bootstrapped CIs. Each horizontal line represents one edge of the network, ordered from the edge with the highest edge-weight to the edge with the lowest edge-weight

Supplementary Materials Figure S1 shows that the strongest edge weight between D1 ("I was bothered by things that usually don't bother me") and D2 ("I did not feel like eating"; r = 0.20 ± 0.016) was significantly different from other edge weights. Moreover, the connection between I1 ("Repeated disturbing memories") and D1 ("I was bothered by things that usually don't bother me") represented the strongest dominance (r = 0.12 ± 0.014) within the PTSD and depression clusters.

Centrality of bridge

Figure 3 illustrates the centrality of bridge symptoms within two clusters, while Supplementary Materials Figure S2 and S3 present the confidence intervals for the bridge expected influence and bridge strength. Supplementary Materials Table S3 details the specific and standardized values of the bridge expected influence and strength. Within the PTSD cluster, symptom I1 ("Repeated disturbing memories") was identified as a bridge symptom with a high bridge expected influence and bridge strength (rBridge expected influence = 0.80, rBridge strength = 3.76). In the depression cluster, D1 ("I was bothered by things that usually don't bother me") exhibits the highest bridge expected influence and bridge strength (rBridge expected influence = 1.35, rBridge strength = 1.52).Fig. 3 a The bridge expected influence and bridge strength measure for PTSD and depression network among snakebite victims; b Stability analysis of bridge expected influence and bridge strength of PTSD and depression network among snakebite victims

The stability coefficient, a crucial metric for assessing the consistency and stability of correlation coefficients across different samples, reflects the comparison between the correlation coefficients and initial network coefficients as the sample size in the network analysis decreases. The stability coefficients for the bridge expected influence and bridge strength in the network of individuals with snakebite-induced comorbidity (Fig. 3 (b)) were 0.75 and 0.439, respectively. Since correlation coefficients should be greater than 0.5 but at least greater than 0.25 [26], the findings indicated significant network stability.

Node centrality and predictability

In network analysis, Strength, Closeness, and Betweenness are three commonly employed nodal centrality metrics that assess the significance of nodes within a network. Strength indicated a node's importance within the network, whereas Closeness measured the degree of proximity between a node and other nodes in the network. Betweenness evaluated the extent to which a node acted as a conduit to control and disseminate information within a network. Within the field of psychopathology, the importance of Strength surpasses that of Closeness and Betweenness [27].

Figure 4 (a) shows the distribution of these three centrality indices, whereas Fig. 4 (b) illustrates their stability, with the respective stability coefficients for Strength, Closeness, and Betweenness being 0.595, 0.439, and 0.595, respectively, which all exceeded the 0.25 threshold. Supplementary Materials Table S4 presents the specific and standardized values of these centrality indices. Of the PTSD symptoms, the node representing E6 ("Feeling emotionally numb") possessed the highest centrality values (rStrength = 1.64, rCloseness = -0.43, rBetweeness = -0.63). Within the spectrum of depression symptoms, D4 ("I thought my life had been a failure") had the highest centrality values (rStrength = 2.45, rCloseness = 0.28, rBetweeness = 0.04).Fig. 4 a Three centrality indices (i.e., strength, closeness, betweenness) measure for PTSD and depression network among snakebite victims; b Stability analysis of strength, closeness, betweenness of PTSD and depression network among snakebite victims

Predictability denotes the extent to which the variance in a given node can be anticipated based on the variance in its connected nodes. In Fig. 2 (a), predictability is represented by circles surrounding the nodes. Supplementary Materials Table S2 shows that the node predictability values ranged from 74.9% to 81.0%. Nodes V5 ("Feeling jumpy"), V4 ("Being super alert"), I4 ("Feeling upset when reminded of a stressful moment"), and I3 ("Acting as if reliving the stressful moment") exhibited the highest predictability. Furthermore, the predictability of all nodes exceeded 74%, suggesting that within the network structure of comorbid PTSD and depression in snakebite victims, the symptoms reliably predicted each other, with external factors accounting for a minimal portion of the variance.

Discussion

Contributing factors

This study contributes initial findings on the comorbidity of PTSD and depression among snakebite victims in China, with a reported prevalence of 75.1%. This rate appears higher compared to a 46% comorbidity rate among Bosnian refugees [28]. A descriptive study in Nigeria identified snakebite complications as major factors affecting the occurrence of depression [5]. Our study identified that physical sequelae from snakebites, the time taken to reach medical facilities, and marital status were significant determinants of PTSD and depression symptoms in Chinese snakebite victims. These effects may be related to psychological barriers caused by post-bite sequelae (e.g., amputations) and fear arising from delayed treatment [29, 30]. The injection of snake antivenom was identified as a secondary related factor for PTSD symptoms and depression symptoms. Given that snake antivenom is the only effective treatment for snakebites [31], its administration may provide psychological reassurance to patients, reducing the incidence of PTSD symptoms and depression symptoms.

Network analysis

This is the first comorbidity network study of PTSD and depression symptoms in snakebite victims. Our findings in a sample of snakebite victims highlighted I1 ("Repeated disturbing memories") and D1 ("I was bothered by things that usually don't bother me") as bridge symptom for PTSD and depression. However, the relationship between PTSD and depression varies across traumatic events. Studies have identified numbness and feelings of sadness as bridge symptoms between PTSD and depression in a sample of firefighters [32]. This disparity could be related to a lack of knowledge related to snakebites, particularly the long-term functional impairments and unfamiliarity with treatment and rehabilitation processes, which could foster fear and concern about death and future life conditions. According to research in Iran, the results indicate that traumatic recollections of snakebites are the most common PTSD symptoms reported by snakebite victims. The re-enactment of snakebite scenes results in victims being in a continuous state of heightened stress, potentially leading to the overactivation of the hypothalamic–pituitary–adrenal axis and subsequent depressive symptoms [33]. Moreover, the recurrence of snakebite images may lead patients to overinterpret events in the surrounding environment as threatening, and physical changes or sequelae from snakebites could lead to distress and agitation in daily life, exacerbating depressive symptoms. Thus, invasive memories caused by snakebites could maintain individuals in a prolonged state of stress, triggering and possibly intensifying depressive symptoms.

Furthermore, by calculating the Strength within the PTSD and depression comorbidity network, symptoms E6 ("Feeling emotionally numb") and D4 ("I thought my life had failed") were identified as core symptoms within the network model. The high stability coefficients for related indices and the high predictability of nodes suggest that this network is applicable to most snakebite victims in China.

Suggestion for psychological intervention

A randomized controlled trial conducted in Sri Lanka revealed that psychological interventions could alleviate mental symptoms in snakebite victims but did not significantly reduce the severity of PTSD or depression [34]. Currently, no well-established psychological interventions exist for snakebite victims. Borsboom [35] offered a developmental description of psychopathology based on network analysis, which is divided into four stages—asymptomatic, network activation, symptom spread, and symptom maintenance.

First, when addressing snakebite victims, recognizing the stress and fear responses that these experiences can provoke is crucial. In China, the public is often advised to memorize the appearance and characteristics of snakes after a bite. However, healthcare professionals may inadvertently prompt patients to recall snakebite incidents for diagnosis and treatment purposes, potentially leading to invasive memories and prematurely triggering network activation and symptom spread stages and facilitating the comorbid PTSD and depression. Healthcare providers and family members should avoid prompting patients to recall the circumstances of their snakebites. Healthcare professionals could consider utilizing artificial intelligence technology to identify snakebites and snake species [36] to develop targeted treatment plans.

Second, snakebites may lead to physical impairments or other sequelae, causing disturbances in daily life and inconvenience to patients. Without timely psychological counseling, these issues may accelerate the development of mental disorders, advancing to network activation or symptom spread stages. Therefore, family members or friends should avoid conveying negative emotions or ideas during interactions with patients and offer increased support and a positive emotional atmosphere.

Finally, when the comorbidity symptoms become severe and mental disorders enter the maintenance stage, providing ample social support to patients while avoiding triggers for invasive memories related to the snakebite event and mitigating the onset of bridge symptoms is suggested. Controlling core symptoms through appropriate interventions, such as helping patients relieve emotional distress, enhancing emotional regulation capabilities, and gradually rebuilding confidence and hopefulness, is recommended.

Advantages and limitations

The strength of this study lies in its analysis of the current state and related factors of PTSD, depression, and comorbidities among snakebite victims. It employed network analysis to further reveal bridge symptoms between PTSD and depression and their interrelationships, offering a degree of novelty. Additionally, during the data collection and analysis process, we employed a multi-stage random convenient sampling method to select participants, which helped to reduce selection bias and enhance the reliability of the study results. We also implemented stringent data integrity measures, including regular data audits, to ensure accuracy and completeness. These measures collectively minimized potential biases and errors, thereby strengthening the validity of our research. Nonetheless, this study had some limitations. First, as a cross-sectional study, causal relationships between variables cannot be identified and can only offer potential recommendations for future longitudinal and intervention research. Second, relying on self-reported questionnaires without a professional psychiatric diagnosis leads to problems with objectively diagnosing participants with PTSD, depression, and their comorbidity. Furthermore, participants' baseline mental health was unknown, which could lead to overestimating the prevalence of PTSD and depression. Finally, only one follow-up survey was conducted with the participants; thus, we encourage further research that uses prospective cohort studies to observe the dynamic psychological network effects among snakebite victims in China.

Conclusion

The study observed that 79.5% of snakebite victims reported symptoms of PTSD, 81.4% reported symptoms of depression, and 75.1% reported comorbid symptoms, based on self-reported measures. Residual physical sequelae of snakebites, time to medical facilities, and unstable marital status have been identified as significant risk factors. Additionally, individuals aged 18–40 are at an increased risk of PTSD and depression caused by snakebites compared to those over age 60, possibly due to increased daily life stress in this demographic, necessitating timely psychological interventions. Network analysis suggested that "Repeated disturbing memories" and "I was bothered by things that usually don't bother me" may serve as bridge symptoms between PTSD and depression. These symptoms could represent crucial targets for psychological intervention. However, further research is needed to confirm these results across different populations.

Supplementary Information

Supplementary Material 1.

Acknowledgements

We would like to thank the people who participated in the study, for generously sharing their time with us. We are also grateful to the research assistants, who supported and facilitated our data collection and transcription efforts.

Authors’ contributions

YC and WNF contributed equally to this work. SJY, XTH and CZL conceptualized and designed the study. SJY, XYS, YC, YLH, JTW, WJH, LFH, Mohamed Diané, Ibrahima Sory Souaré and WG participated in the acquisition of data. YC and WNF analyzed the data and drafted the manuscript. SJY, XTH revised the manuscript. All authors read and approved the final manuscript.

Funding

This study was supported by Hainan Province Science and Technology Special Fund (ZDKJ202004), National Natural Science Foundation of China (82160647), Hainan Clinical Medical Research Center Project (LCYX202310),CAMS Innovation Fund for Medical Sciences(2019-I2M-5-023).

Availability of data and materials

The datasets are not publicly available due to privacy or ethical restrictions. The data are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

The Ethics Committee of Hainan Medical College approved the study protocol (No. HYLL-2022–226). We obtained informed consent from all survey participants (For minors under 18, we have obtained the informed consent from their parents or guardians). All data collection is carried out in accordance with the relevant guidelines and regulations described in the Helsinki Declaration.

Competing interests

The authors declare no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Yu Chen and Wenning Fu contributed equally to this work and should be considered co-first authors.
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