Skip to main content
NCBI home page
Elsevier - PMC COVID-19 Collection logoLink to Elsevier - PMC COVID-19 Collection
. 2022 Dec 16;323:834–840. doi: 10.1016/j.jad.2022.12.036

Suicidal ideation in the general population in China after the COVID-19 pandemic was initially controlled

Shuangyan Li a,b, Shuai Liu a,b, Puxiao Zhang c, Yanmei Lin a,b, Yingru Cui a,b, Yue Gu a,b, Jiajia Wang a,b, Zhongchun Liu d, Bin Zhang a,b,⁎
PMCID: PMC9754752  PMID: 36529410

Abstract

Background

The COVID-19 pandemic increases the risk of psychological problems including suicidal ideation (SI) in the general population. In this study, we investigated the risk factors of SI after the COVID-19 pandemic was initially controlled in China.

Methods

We conducted an online questionnaire via JD Health APP in China in June 2020. Demographic data, feelings and experiences related to the COVID-19 pandemic and psychological problems were collected. The participants (n = 14,690) were divided into the non-SI and SI groups. A binary logistic regression analysis was used to examine the correlates of SI.

Results

Nine percent of the participants (1328/14690) reported SI. The regression analysis showed that SI was positively associated with ethnic minority (OR = 1.42 [1.08–1.85]), age (e.g. 18–30 years: OR = 2.31 [1.67–3.20]), having history of mental disorders (OR = 2.75 [2.27–3.35]), daily life disturbance due to health problems (OR = 1.67 [1.38–2.01]), being around someone with the COVID-19 (OR = 1.58 [1.30–1.91]), being uncertain about effective disease control (OR = 1.23 [1.03–1.46]), and having depressive symptoms (OR = 4.40 [3.59–5.39]), insomnia symptoms (OR = 2.49 [2.13–2.90]) or psychological distress (OR = 1.87 [1.59–2.18]).

Limitations

The main limitation is that the cross-sectional design of this study could not allow us to further explore the causality of SI.

Conclusions

The prevalence of SI was relatively high in general population after the COVID-19 pandemic was initially controlled in China. SI should be monitored continually after the COVID-19 pandemic.

Keywords: Suicide, Mental health, Coronavirus, Infectious diseases, Cross-sectional survey, Psychological symptoms

Graphical abstract

Unlabelled Image

Open in a new tab

1. Introduction

The first wave of the coronavirus disease 2019 (COVID-19) swept China rapidly since the first case of COVID-19 was recorded on November 17, 2019. Since April 2020 the peak of the COVID-19 pandemic has passed and has essentially been brought under control in China (Kang and Xu, 2020; Hu et al., 2021). Up to now the COVID-19 pandemic has lasted for over 2 years. Outbreak, remission, and re-outbreak have been the norm during the COVID-19 era. The COVID-19 pandemic has had significant psychological and social impact on the general population, resulting in psychological problems such as stress, anxiety, depression and insomnia in the general population (Lin et al., 2022; Zhang et al., 2020; Hossain et al., 2020; Lindert et al., 2021). The fear of being infected with COVID-19, health threat, and social distance adherence during the COVID-19 pandemic led to a large number of negative emotions such as nervousness, fright, anger and the feeling of being frustrated (Bord et al., 2021). Suicide is known to be the most extreme outcome of all negative emotions (Raudales et al., 2020; Anestis and Joiner, 2011). Suicidal ideation (SI) confers risk for later suicidal thoughts and behaviors, although the magnitude of its effects varies. Early clinical interventions of suicidal ideation could be effective in reducing the suicidal behavior (Klonsky et al., 2016; Okado et al., 2021). The prevalence of SI in different population during the COVID-19 pandemic has been reported in China. The prevalence of SI among hospital workers (Xu et al., 2020), students aged 10–17 years old (Zhu et al., 2021), non-frontline medical workers (Cai et al., 2020) and frontline medical workers (Cai et al., 2020) was 6.47 %, 21 %, 9.0 % and 12.0 %, respectively. Shi et al. reported that the prevalence of SI among the general population was 16.4 % in China during the COVID-19 pandemic; the suicide rate was significantly higher among those with pre-existing mental illness, low-income individuals and healthcare workers during the COVID-19 pandemic (Shi et al., 2021). Other risk factors of SI included young age, ethnic minority background, essential worker status, families with children, being unmarried, poorer physical health, current lockdown, less social support, lower psychological resilience, concern about COVID-19, lower adherence to infection control guidance, loneliness and insomnia (Rogers et al., 2021). For example, the lockdown and economic consequences of the COVID-19 pandemic would strain mental health (e.g., symptoms of depression, anxiety, insomnia, and acute stress) for the vulnerable, low-income adults, leading to the increasing risk of SI (Kaniuka et al., 2021).

Psychological sequelae (such as anxiety and depression) caused by disasters such as severe life events usually last for a long time (Kolves et al., 2013). It was reported that the prevalence of SI was as high as 30.7 % at 18 months after the disaster in Chinese adolescents exposed to the 2008 Wenchuan earthquake (Ran et al., 2015). It has been shown that the rate of SI still was at a relative high level (10.8 %) even 10 years after the 2008 Wenchuan earthquake (Chen et al., 2020), compared to that in the general populations who were not exposed to a major disaster (3.9 %) (Cao et al., 2015).

Since 29th April of 2020, the first COVID outbreak occurred in Wuhan, Hubei province was initially controlled. The confirmed cases of local residents (except for the overseas import cases) decreased to zero in China after the governmental interventions. Unexpectedly, the prevalence of psychological problems, such as insomnia symptoms, depressive symptoms and anxiety symptoms, was still high after the COVID-19 pandemic had been initially controlled (Guo et al., 2021; Wang et al., 2021; Li et al., 2021). Wang et al. found that the prevalence of SI among college students was higher at the initial remission period than at the outbreak period of the COVID-19 pandemic (Wang et al., 2021). However, little is known about the prevalence of SI in general population after the COVID-19 pandemic was initially controlled. Therefore, in this study we aimed to investigate the factors related to SI in the general population of China after the COVID-19 pandemic was initially controlled. We hypothesized that after the COVID-19 pandemic was initially controlled the prevalence of SI would still be at high level for a long time.

2. Methods

2.1. Participants and procedures

The current study was approved by the Research Ethics Committee of Nanfang Hospital, Southern Medical University. A total of 14,690 individuals in China participated in this cross-sectional study. All participants were anonymous. An online questionnaire survey was conducted via a platform called JD Health APP from June 5, 2020 to June 7, 2020. The questionnaire was recycled automatically only after the participant finished answering all the questions. The signed informed consent form was obtained from all participants prior to starting the study. The questionnaire consisted of 4 parts: (1) demographic data, including gender, ethnicity, age, level of education, residence in the last month, habit of smoking and drinking, history of mental disorders (major depressive disorder, bipolar disorder, anxiety disorder, sleep disorder, schizophrenia, etc), history of chronic diseases (diabetes, hypertension, coronary disease, etc), and daily life disturbance due to health problems; (2) feelings and experiences related to the COVID-19 pandemic, such as being around with someone infected with COVID-19, fear of being infected with the COVID-19; (3) psychological problems including depressive symptoms, insomnia symptoms and psychological distress; and (4) SI-related questions.

The inclusion criteria were as follows: (1) the participants were JD Health APP users, (2) adults aged between 18 and 60 years. The exclusion criteria were as follows: (1) individual who were younger than 18 or older than 60, (2) individual was unable to understand the questionnaire, and (3) individual did not answer the SI-related questions.

We divided the participants into two groups by asking the question “Have you ever had suicidal ideation last eight weeks?”: the SI group (n = 1328), including the participants who answered this question with “At least once a week and you can't get rid of it” (n = 988), or “Every day and you can't get rid of it” (n = 215) or “Having this thought all the time” (n = 125); and the non-SI group (n = 13,362), including those who answered the above question with “Never” (n = 8392) or “Only a flash” (n = 4970).

2.2. Measures

2.2.1. Patient Health Questionnaire-9 (PHQ-9)

The PHQ-9 was used to evaluate the depressive symptoms. The PHQ-9 includes 9 items based on the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) for major depressive disease; each item reflects the frequency of symptoms during the preceding 2-week period (Arroll et al., 2010). Each item is rated on a 4-point scale (0 = none to 3 = extreme), yielding a total score ranging from 0 to 27. A PHQ-9 total score ≥ 5 is considered to have depressive symptoms (Yu et al., 2012). The internal consistency and test-retest reliability of PHQ-9 were 0.82 and 0.76, respectively (Yu et al., 2012).

2.2.2. Insomnia severity index (ISI)

The ISI was used to evaluate the severity of insomnia. ISI consists of seven items. A 5-point Likert scale is used to rate each item (0 = none to 4 = extreme), yielding a total score ranging from 0 to 28. An ISI total scores ≥8 is considered to have insomnia (Bastien et al., 2001). Previous study showed great reliability in the Chinese version of ISI (Yu, 2010).

2.2.3. Impact of Events Scale-Revised (IES-R)

The IES-R Chinese version was used to assess the psychological distress related to COVID-19. The IES-R consists 22 items and each item was rated by a 5-point Likert scale (0 = not at all, 4 = extremely), yielding a total score ranging from 0 to 88. An IES-R total score ≥ 20 is considered to have psychological distress (Wu et al., 2009). IES-R had high reliability and validity for the assessment of psychological distress in Chinese population (Wu and Chan, 2003).

2.3. Statistical analysis

All collected data were exported, evaluated, and analyzed by two analysts separately. All statistical analyses were conducted using SPSS version 26.0 for Windows. Descriptive statistics were used to determine the distributions and characteristics of all variables. The categorical variables were presented as numbers and percentages. The chi-square (χ2) test was used to compare difference between the two groups in univariate analyses and Bonferroni post hoc analyses were performed. We conducted the binary logistic regression to assess the association between SI and the variables with p < 0.05 in the univariate analyses above by using the “Enter” method. Results are presented as odds ratios (ORs) and 95 % confidence intervals (CI). A two-sided p-value of <0.05 was considered statistically significant.

3. Results

3.1. Demographic characteristics

The demographic data of the subjects of non-SI group and SI group are presented in Table 1 . Among the total participants (n = 14,690), 1328 participants (9.04 %) reported SI. There were significant differences in gender composition between the two groups; the percentage of females was 52.71 % and 57.77 % in the SI group and non-SI group, respectively. Higher percentage of ethnic minority (ethnic groups other than Han) was found in the SI group compared to the non-SI group (7.08 % vs. 4.02 %, p < 0.001). Higher SI rate was showed in ethnic minority group (14.90 %) than that of the Han group (8.78 %). Significant differences were observed in the age distribution between the non-SI group and the in the SI group. The SI group had a higher percentage of 18–30 years of age (35.24 % vs. 23.59 %, p < 0.001), and a lower percentage of 41–50 years of age (15.81 % vs. 26.03 %, p < 0.001) and 51–60 years of age (3.77 % vs. 7.18 %, p < 0.001) compared to the non-SI group. Among the four age groups, the 18–30-year-old group had the highest SI rate (12.93 %). For the place of residence in the past month, the percentage of the people who had lived in Wuhan city (center of the COVID outbreak in China) was higher in the SI group compared to the non-SI group (4.59 % vs. 2.64 %, p < 0.001). The percentage of people who had a habit of smoking or drinking was higher in the SI group. The percentage of people who had a history of mental disorders was higher in the SI group compared to the non-SI group (21.76 % vs. 2.81 %, p < 0.001). SI occurred in nearly half of the people who had a history of mental disorders (43.46 %). There was a higher percentage of participants had daily life disturbance due to health problems in the SI group compared to the non-SI group (19.73 % vs. 4.99 %, p < 0.001). The SI rate in the participants who had daily life disturbance due to health problems was 28.20 %. There were no significant differences between the two groups in education level and history of chronic diseases (Table 1).

Table 1.

Demographic characteristics of the participants.

Total (n = 14,690) Non-SI (n = 13,362) SI (n = 1328) SI rate (%) χ2 p
Gender 12.63 <0.001
 Female 8419 (57.31) 7719 (57.77) 700 (52.71) 8.31
 Male 6271 (42.69) 5643 (42.23) 628 (47.29) 10.01
Ethnicity 27.50 <0.001
 Han 14,059 (95.70) 12,825 (95.98) 1234 (92.92) 8.78
 Ethnic minority 631 (4.30) 537 (4.02) 94 (7.08) 14.90
Age (years) 138.32 <0.001
 18–30 3620 (24.64) 3152 (23.59) 468 (35.24)* 12.93
 31–40 6373 (43.38) 5773 (43.20) 600 (45.18) 9.41
 41–50 3688 (25.11) 3478 (26.03) 210 (15.81)* 5.69
 51–60 1009 (6.87) 959 (7.18) 50 (3.77)* 4.96
Highest education level 0.88 0.65
 High school diploma or less 3405 (23.18) 3102 (23.22) 303 (22.82) 8.90
 Bachelor's degree 10,130 (68.96) 9218 (68.99) 912 (68.67) 9.00
 Master's or doctoral degree 1155 (7.86) 1042 (7.80) 113 (8.51) 9.78
Residence in the past month 24.94 <0.001
 Wuhan city 414 (2.82) 353 (2.64) 61 (4.59)* 14.73
 All regions other than Wuhan in Hubei 2130 (14.50) 1908 (14.28) 222 (16.72)* 10.42
 Provinces other than Hubei 11,633 (79.19) 10,638 (79.61) 995 (74.92)* 8.55
 Overseas 513 (3.49) 463 (3.47) 50 (3.77) 9.75
Smoking (yes) 2077 (14.14) 1822 (13.64) 255 (19.20) 12.28 30.83 <0.001
Drinking (yes) 5487 (37.35) 4846 (36.27) 641 (48.27) 11.68 74.34 <0.001
History of mental disorders (yes) 665 (4.53) 376 (2.81) 289 (21.76) 43.46 1003.46 <0.001
History of chronic diseases (yes) 474 (3.23) 425 (3.18) 49 (3.69) 10.34 1.00 0.32
Daily life disturbances due to health problems (yes) 929 (6.32) 667 (4.99) 262 (19.73) 28.20 442.85 <0.001
Open in a new tab

Note: Data are N (%); SI: Suicidal ideation; Non-SI: Non-suicidal ideation; * indicates significance (p < 0.05, Bonferroni post hoc).

3.2. Feelings and experiences related to the COVID-19 pandemic

The feelings and experiences related to the COVID-19 pandemic was demonstrated in Table 2 . The percentage of participants who had been around someone with COVID-19 was higher in the SI group. Higher percentage of participants had a fear of being infected with COVID-19 or had been uncertain about effective disease control in the SI group. The SI group had higher percentage of participants who had been searching for information related to COVID-19 frequently on the internet in the past month.

Table 2.

Feelings and experiences related to the COVID-19 pandemic.

Total (n = 14,690) Non-SI (n = 13,362) SI (n = 1328) SI rate (%) χ2 p
Having been around someone with COVID-19 (yes) 1082 (7.37) 811 (6.07) 271 (20.41) 25.05 363.91 < 0.001
Fear of being infected with COVID-19 (yes) 5119 (34.85) 4431 (33.16) 688 (51.81) 13.44 184.98 < 0.001
Being uncertain about effective disease control (yes) 10,297 (70.10) 9162 (68.57) 1135 (85.47) 11.02 164.57 < 0.001
Searching for COVID-19-related information frequently on the internet in the past month (yes) 11,079 (75.42) 9971 (74.62) 1108 (83.43) 10.00 50.59 < 0.001
Open in a new tab

Note: Data are N (%); SI: Suicidal ideation; Non-SI: Non-suicidal ideation.

3.3. Evaluations of depressive symptoms, insomnia symptoms and psychological distress

Table 3 shows the evaluations of depressive symptoms, insomnia symptoms and psychological distress. Higher percentage of participants in the SI group had depressive symptoms, insomnia symptoms and psychological distress compared to the non-SI group.

Table 3.

Evaluations of depression symptoms, insomnia symptoms and psychological distress.

Total (n = 14,690) Non-SI (n = 13,362) SI (n = 1328) SI rate (%) χ2 p
PHQ-9 ≥ 5 6221 (42.35) 5043 (37.74) 1178 (88.70) 18.94 1285.04 <0.001
ISI ≥ 8 4539 (30.90) 3541 (26.50) 998 (75.15) 21.99 1339.03 <0.001
IES-R ≥ 20 5460 (37.17) 4444 (33.26) 1016 (76.51) 18.61 967.43 <0.001
Open in a new tab

Note: Data are N (%); SI: Suicidal ideation; Non-SI: Non-suicidal ideation; PHQ-9: Patient Health Questionnaire; ISI: Insomnia Severity Index; IES-R: Impact of Events Scale-Revised.

3.4. Binary logistic regression analysis of factors associated with suicidal ideation

Table 4 shows the results of the binary logistic regression model. SI was associated with the following factors: ethnic minority (OR = 1.42 [1.08–1.85]), age (18–30 years: OR = 2.31 [1.67–3.20]; 31–40 years: OR = 1.76 [1.28–2.43], having a history of mental disorders (OR = 2.75 [2.27–3.35]), having daily life disturbance due to health problems (OR = 1.67 [1.38–2.01]), being around someone with the COVID-19 (OR = 1.58 [1.30–1.91]), being uncertain about effective disease control (OR = 1.23 [1.03–1.46]), and having depressive symptoms (OR = 4.40 [3.59–5.39]), insomnia symptoms (OR = 2.49 [2.13–2.90]) or psychological distress (OR = 1.87 [1.59–2.18]).

Table 4.

Binary logistic regression analysis of factors associated with suicidal ideation.

Variable (reference) β OR (95 % CI) p
PHQ-9 ≥ 5 (PHQ-9 < 5) 1.48 4.40 (3.59–5.39) <0.001
ISI ≥ 8 (ISI < 8) 0.91 2.49 (2.13–2.90) <0.001
IES-R ≥ 20 (IES-R < 20) 0.62 1.87 (1.59–2.18) <0.001
Having history of mental disorders (no) 1.01 2.75 (2.27–3.35) <0.001
Having daily life disturbance due to health problems (no) 0.51 1.67 (1.38–2.01) <0.001
Having been around someone with COVID-19 (no) 0.46 1.58 (1.30–1.91) <0.001
Ethnic minority (Han) 0.35 1.42 (1.08–1.85) 0.01
Being uncertain about effective disease control (no) 0.20 1.23 (1.03–1.46) 0.03
Age groups
 18–30 years (51–60 years) 0.84 2.31 (1.67–3.20) <0.001
 31–40 years (51–60 years) 0.57 1.76 (1.28–2.43) <0.001
 41–50 years (51–60 years) 0.07 1.07 (0.76–1.50) 0.70
Female (male) 0.01 1.01 (0.88–1.17) 0.87
Residence in the last month
 All regions other than Wuhan in Hubei (Wuhan city) 0.18 1.20 (0.83–1.72) 0.34
 Provinces other than Hubei (Wuhan city) 0.01 1.01 (0.72–1.43) 0.94
 Overseas (Wuhan city) 0.25 1.29 (0.81–2.05) 0.29
Smoking (no) 0.06 1.07 (0.89–1.28) 0.49
Drinking (no) 0.10 1.11 (0.97–1.27) 0.15
Having fear of being infected with COVID-19 (no) 0.06 1.06 (0.93–1.21) 0.41
Searching frequently for COVID-19-related information on the internet in the past month (no) −0.08 0.93 (0.78–1.10) 0.37
Open in a new tab

Note: The binary logistic regression model included all factors which were significant in the univariate analysis by using Enter method. SI: Suicidal ideation; Non-SI: Non-suicidal ideation; PHQ-9: Patient Health Questionnaire; ISI: Insomnia Severity Index; IES-R: Impact of Events Scale-Revised; OR: odds ratio; 95 % CI: 95 % Confidence Interval.

4. Discussion

The present study is one of the few studies investigating the associated factors for SI after the COVID-19 pandemic was initially controlled in China. Our study contained a large sample size. In our study, 9.04 % of participants reported SI. Depressive symptoms, insomnia symptoms and psychological distress, ethnic minority, age, having a history of mental disorders, having daily life disturbance due to health problems, being around someone with COVID-19, and being uncertain about effective disease control were clearly associated with SI.

A meta-analysis showed that the prevalence of SI, pooling rates of four studies with a random effect model, was 3.9 % in the general population in China before the COVID-19 pandemic (Cao et al., 2015). Compare to the prevalence of SI (16.4 %) during the outbreak of COVID-19 pandemic (Shi et al., 2021), we found that the prevalence of SI (9.04 %) decreased after the COVID-19 pandemic was initially controlled, but was still higher than that before the COVID-19 pandemic. The change in prevalence of SI after the COVID-19 pandemic was initially controlled may be due to the implementation of measures, such as wearing of masks, maintaining social distance.

Our results showed that the ethnic minorities were at higher risk of SI compared to the Han ethnic group. In China, ethnic minorities account for 8.89 % of total populations (National Bureau of Statistics, China); most of them live in the remote rural areas. The unequal distribution of health care resources, language barriers, lower cognition of illness result in health inequality (Wang et al., 2020). It has been proposed that ethnic minority was more likely to be affected by mental disorders but less likely to use mental health services (Liu et al., 2022).

Our results showed that younger people (18–50 years old) were more vulnerable to develop SI. Similar results were demonstrated in a study investigating SI during the COVID-19 outbreak (O'Connor et al., 2021). It found that younger (18–30 years old) people had worse ability of information screening, such as appraising health information (Basch et al., 2021). During the COVID-19 pandemic the younger people may develop psychological panic because of overwhelming information about COVID-19 (Manzar et al., 2021). Mamun et al. showed that unstable psychological status could lead to increased SI among young people (Mamun et al., 2021a). The academic stressors in adolescents (Mamun et al., 2021b) and the financial pressures in adults (Kaniuka et al., 2021) may be some of the reasons for SI during the COVID-19 pandemic.

In our study, people who had a history of mental disorders were at high risk of SI. People with mental disorders faced fewer mental health services and social support, and aggravated psychiatric symptoms during the COVID-19 pandemic (Puangsri et al., 2021). People with pre-existing mental illness were more prone to suffering from other mental disorders at the same time (Hao et al., 2020). People with pre-existing mental disorders had a higher sensitivity to stigma, which may lead to SI (de Beurs et al., 2019).

Having daily life disturbance due to health problems was found to be associated with SI. Daily life disturbance due to health problems may lead to lack of autonomy, isolation, pain and even the development of depressive symptom (Fassberg et al., 2016), all of which have been demonstrated to be independent risk factors of SI during the COVID-19 pandemic (Sher, 2020).

Consistent with previous report (Kuriala, 2021), our results showed that having depressive symptom was the strongest positively associated factor for SI. It has been shown that depressive symptoms may lead to SI (Xu et al., 2021), and the more severe the depressive symptoms were, the more likely they were to predict SI (Melhem et al., 2019). Reduced interpersonal communication due to the COVID-19 pandemic could increase depressive symptoms, which was associated with SI (Carvalho and de Sousa, 2020). People with depressive symptoms during the COVID-19 pandemic were easy to experience hopelessness, increasing the possibility of suicide (Ustun, 2021).

Consisted with previous study (Wang et al., 2021), our results showed that insomnia was an independent positively associated factor for SI after the COVID-19 pandemic was initially controlled. Our previous study showed that the COVID-19 pandemic caused changes in sleep patterns in the general population (Lin et al., 2022). It has been shown that people who had insomnia symptoms were 3.5 times more likely to report suicide-related ideation (Vargas et al., 2020). The prevalence of insomnia was shown to be 30.9 % in the general population in China after the COVID-19 pandemic had been initially controlled (Guo et al., 2021). In addition, insomnia may exacerbate the feelings of loneliness or social isolation, which may lead to SI (Chu et al., 2016).

In this study we also found that psychological distress was significantly associated with SI. Previous studies reported a high prevalence of psychological distress in the general population during the COVID-19 pandemic (Xiong et al., 2020; Qiu et al., 2020). It has been shown that the progressive development of psychological distress into SI was mediated by the sense of being a burden on others (Rainbow et al., 2021). The COVID-19 pandemic was a new multiple complex traumatic stressor, the causes of psychological distress during the COVID-19 pandemic included having been around someone with COVID-19, fears of infection, and being uncertain about effective disease control (Kira et al., 2021). Firstly, in most communities, clustered transmission occurred when people contacted the respiratory droplets of the infected person in the proximity (Sheervalilou et al., 2020). People worried about themselves or their family members being infected when they were around someone who was infected with COVID-19. Those who reporting more COVID-19 fears reported more mental health symptoms, especially for depression and anxiety symptoms (Fitzpatrick et al., 2020). Fears of COVID-19 infection have been shown to be associated with SI (Dsouza et al., 2020). Secondly, the serious illness stigma of COVID-19 and the discrimination against the people who were infected with COVID or being a close contact of a confirmed case may result in new psychological problems or worsen a pre-existing medical condition (Peprah and Gyasi, 2021). Thirdly, the increased number of confirmed COVID cases around people may intensify the doubtfulness about effective COVID-19 disease control, leading to exacerbated psychological distress and triggering SI in the susceptible population (Pinto et al., 2020).

This study has several limitations. Firstly, the cross-sectional design of this study could not allow us to further explore the causality of SI. Secondly, all data in our study were self-reported. The data may be prone to social desirability bias. Thirdly, some other suicide-related factors, such as the duration of previous illness, previous suicide history and the experiences of self-harm, were not examined in this study. Fourthly, all of the self-designed questions employed were developed for the purpose of this study and therefore were not validated in some way. Fifthly, we only divided the ethnicity into two groups. We only classified the living areas into four regions rather than specific regions. However, the cultures and living habits may differ among ethnic groups and from place to place, which may influence the results. Finally, the subjects were recruited using convenience sampling method and only the JD Health APP users could attend the survey. The recruitment strategy may limit the representativeness of population.

In conclusion, in our study 9.04 % of participants reported SI after the COVID-19 pandemic was initially controlled in China. The factors positively associated with SI included ethnic minority, younger age, having history of mental disorders, having daily life disturbance due to health problems, being around someone with COVID-19, and being uncertain about effective disease control, and having depressive symptoms, insomnia symptoms or psychological distress, which lead to targeted prevention strategies. SI should be continually monitored after the COVID-19 pandemic.

CRediT authorship contribution statement

Shuangyan Li: formal analysis, investigation, resources, writing - original draft, visualization. Shuai Liu: methodology, writing - review and editing. Puxiao Zhang: investigation, data curation. Yanmei Lin: formal analysis, investigation. Yingru Cui: investigation, resources. Yue Gu: resources, data curation. Jiajia Wang: investigation, resources. Zhongchun Liu: supervision and project administration. Bin Zhang: conceptualization, writing - review and editing, funding acquisition, supervision and project administration. All authors have approved the final manuscript.

Funding

This work was supported by the National key R&D Program of China (Grant No. 2021YFC2501500), the National Natural Science Foundation of China (Grant No. 82071488 and 81901348), the President Foundation of Nanfang Hospital, Southern Medical University (Grant No. 2019Z014) and the Education Research Projects of Nanfang Hospital (Grant No. 21NJ-ZDPY01).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

Acknowledgments

We would like to thank all the individuals that have supported this research.

Ethics statement

The studies involving human participants were reviewed and approved by the Ethics Committee of Nanfang Hospital of Southern Medical University and was conducted in accordance with the Declaration of Helsinki. The participant consent form was obtained from all participants prior to the study. To protect the respondents' privacy, the survey was conducted anonymously.

Data availability

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

References

  1. Anestis M.D., Joiner T.E. Examining the role of emotion in suicidality: negative urgency as an amplifier of the relationship between components of the interpersonal-psychological theory of suicidal behavior and lifetime number of suicide attempts. J. Affect. Disord. 2011;129(1–3):261–269. doi: 10.1016/j.jad.2010.08.006. [DOI] [PubMed] [Google Scholar]
  2. Arroll B., Goodyear-Smith F., Crengle S., Gunn J., Kerse N., Fishman T., Falloon K., Hatcher S. Validation of PHQ-2 and PHQ-9 to screen for major depression in the primary care population. Ann. Fam. Med. 2010;8(4):348–353. doi: 10.1370/afm.1139. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Basch C.H., Meleo-Erwin Z., Fera J., Jaime C., Basch C.E. A global pandemic in the time of viral memes: COVID-19 vaccine misinformation and disinformation on TikTok. Hum. Vaccin. Immunother. 2021;17(8):2373–2377. doi: 10.1080/21645515.2021.1894896. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Bastien C.H., Vallieres A., Morin C.M. Validation of the insomnia severity index as an outcome measure for insomnia research. Sleep Med. 2001;2(4):297–307. doi: 10.1016/s1389-9457(00)00065-4. [DOI] [PubMed] [Google Scholar]
  5. de Beurs D., Ten H.M., Cuijpers P., de Graaf R. The longitudinal association between lifetime mental disorders and first onset or recurrent suicide ideation. BMC Psychiatry. 2019;19(1):345. doi: 10.1186/s12888-019-2328-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Bord S., Schor A., Satran C., Ali S.O., Inchi L., Halperin D. Distancing adherence and negative emotions among the israeli elderly population during the COVID-19 pandemic. Int. J. Environ. Res. Public Health. 2021;18(16):8770. doi: 10.3390/ijerph18168770. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Cai Q., Feng H., Huang J., Wang M., Wang Q., Lu X., Xie Y., Wang X., Liu Z., Hou B., Ouyang K., Pan J., Li Q., Fu B., Deng Y., Liu Y. The mental health of frontline and non-frontline medical workers during the coronavirus disease 2019 (COVID-19) outbreak in China: a case-control study. J. Affect. Disord. 2020;275:210–215. doi: 10.1016/j.jad.2020.06.031. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Cao X.L., Zhong B.L., Xiang Y.T., Ungvari G.S., Lai K.Y., Chiu H.F., Caine E.D. Prevalence of suicidal ideation and suicide attempts in the general population of China: a meta-analysis. Int. J. Psychiatry Med. 2015;49(4):296–308. doi: 10.1177/0091217415589306. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Carvalho A.M.M., de Sousa S.D. Impact of social distancing on mental health during the COVID-19 pandemic: an urgent discussion. Int. J. Soc. Psychiatry. 2020;66(6):625–626. doi: 10.1177/0020764020927047. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Chen X.Y., Zhou Y., Shi X., Ma Z., Fan F. Longitudinal associations between adolescents' trajectory membership of depressive symptoms and suicidality in young adulthood: a 10-year cohort of Chinese Wenchuan earthquake survivors. Epidemiol. Psychiatr. Sci. 2020;29 doi: 10.1017/S2045796020000827. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Chu C., Hom M.A., Rogers M.L., Ringer F.B., Hames J.L., Suh S., Joiner T.E. Is insomnia lonely? Exploring thwarted belongingness as an explanatory link between insomnia and suicidal ideation in a sample of south korean university students. J. Clin. Sleep Med. 2016;12(5):647–652. doi: 10.5664/jcsm.5784. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Dsouza D.D., Quadros S., Hyderabadwala Z.J., Mamun M.A. Aggregated COVID-19 suicide incidences in India: fear of COVID-19 infection is the prominent causative factor. Psychiatry Res. 2020;290 doi: 10.1016/j.psychres.2020.113145. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Fassberg M.M., Cheung G., Canetto S.S., Erlangsen A., Lapierre S., Lindner R., Draper B., Gallo J.J., Wong C., Wu J., Duberstein P., Waern M. A systematic review of physical illness, functional disability, and suicidal behaviour among older adults. Aging Ment. Health. 2016;20(2):166–194. doi: 10.1080/13607863.2015.1083945. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Fitzpatrick K.M., Harris C., Drawve G. Fear of COVID-19 and the mental health consequences in America. Psychol. Trauma. 2020;12(S1):S17–S21. doi: 10.1037/tra0000924. [DOI] [PubMed] [Google Scholar]
  15. Guo J., Yang L., Xu Y., Zhang C., Luo X., Liu S., Yao L., Bai H., Zong X., Zhang J., Liu Z., Zhang B. Prevalence and risk factors associated with insomnia symptoms among the Chinese general public after the coronavirus disease 2019 epidemic was initially controlled. Nat. Sci. Sleep. 2021;13:703–712. doi: 10.2147/NSS.S307996. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Hao F., Tan W., Jiang L., Zhang L., Zhao X., Zou Y., Hu Y., Luo X., Jiang X., McIntyre R.S., Tran B., Sun J., Zhang Z., Ho R., Ho C., Tam W. Do psychiatric patients experience more psychiatric symptoms during COVID-19 pandemic and lockdown? A case-control study with service and research implications for immunopsychiatry. Brain Behav. Immun. 2020;87:100–106. doi: 10.1016/j.bbi.2020.04.069. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Hossain M.M., Tasnim S., Sultana A., Faizah F., Mazumder H., Zou L., McKyer E., Ahmed H.U., Ma P. Epidemiology of mental health problems in COVID-19: a review. F1000Res. 2020;9:636. doi: 10.12688/f1000research.24457.1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Hu X., Flahault A., Temerev A., Rozanova L. The progression of COVID-19 and the government response in China. Int. J. Environ. Res. Public Health. 2021;18(6):3002. doi: 10.3390/ijerph18063002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Kang Y., Xu S. Comprehensive overview of COVID-19 based on current evidence. Dermatol. Ther. 2020;33(5) doi: 10.1111/dth.13525. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Kaniuka A.R., Cramer R.J., Wilsey C.N., Langhinrichsen-Rohling J., Mennicke A., Patton A., Zarwell M., McLean C.P., Harris Y.J., Sullivan S., Gray G. COVID-19 exposure, stress, and mental health outcomes: results from a needs assessment among low income adults in Central North Carolina. Front Psychiatry. 2021;12 doi: 10.3389/fpsyt.2021.790468. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Kira I.A., Shuwiekh H., Ashby J.S., Elwakeel S.A., Alhuwailah A., Sous M., Baali S., Azdaou C., Oliemat E.M., Jamil H.J. The impact of COVID-19 traumatic stressors on mental health: is COVID-19 a new trauma type. Int. J. Ment. Heal. Addict. 2021;1–20 doi: 10.1007/s11469-021-00577-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Klonsky E.D., May A.M., Saffer B.Y. Suicide, suicide attempts, and suicidal ideation. Annu. Rev. Clin. Psychol. 2016;12:307–330. doi: 10.1146/annurev-clinpsy-021815-093204. [DOI] [PubMed] [Google Scholar]
  23. Kolves K., Kolves K.E., De Leo D. Natural disasters and suicidal behaviours: a systematic literature review. J. Affect. Disord. 2013;146(1):1–14. doi: 10.1016/j.jad.2012.07.037. [DOI] [PubMed] [Google Scholar]
  24. Kuriala G.K. Covid-19 and its impact on global mental health. Sens. Int. 2021;2 doi: 10.1016/j.sintl.2021.100108. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Li Y., Zhao J., Ma Z., McReynolds L.S., Lin D., Chen Z., Wang T., Wang D., Zhang Y., Zhang J., Fan F., Liu X. Mental health among college students during the COVID-19 pandemic in China: a 2-wave longitudinal survey. J. Affect. Disord. 2021;281:597–604. doi: 10.1016/j.jad.2020.11.109. [DOI] [PubMed] [Google Scholar]
  26. Lin Y., Liu S., Li S., Zuo H., Zhang B. Relationships between the changes in sleep patterns and sleep quality among chinese people during the 2019 coronavirus disease outbreak. Sleep Med. 2022;91:154–160. doi: 10.1016/j.sleep.2021.01.021. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Lindert J., Jakubauskiene M., Bilsen J. The COVID-19 disaster and mental health-assessing, responding and recovering. Eur. J. Pub. Health. 2021;31(Supplement_4):v31–v35. doi: 10.1093/eurpub/ckab153. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Liu X., Zhao W., Hu F., Hao Q., Hou L., Sun X., Zhang G., Yue J., Dong B. Comorbid anxiety and depression, depression, and anxiety in comparison in multi-ethnic community of West China: prevalence, metabolic profile, and related factors. J. Affect. Disord. 2022;298(Pt A):381–387. doi: 10.1016/j.jad.2021.10.083. [DOI] [PubMed] [Google Scholar]
  29. Mamun M.A., Mamun M.A., Hosen I., Ahmed T., Rayhan I., Al-Mamun F. Trend and gender-based association of the Bangladeshi student suicide during the COVID-19 pandemic: a GIS-based nationwide distribution. Int. J. Soc. Psychiatry. 2021 doi: 10.1177/00207640211065670. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Mamun M.A., Sakib N., Gozal D., Bhuiyan A.I., Hossain S., Bodrud-Doza M., Al M.F., Hosen I., Safiq M.B., Abdullah A.H., Sarker M.A., Rayhan I., Sikder M.T., Muhit M., Lin C.Y., Griffiths M.D., Pakpour A.H. The COVID-19 pandemic and serious psychological consequences in Bangladesh: a population-based nationwide study. J. Affect. Disord. 2021;279:462–472. doi: 10.1016/j.jad.2020.10.036. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Manzar M.D., Albougami A., Usman N., Mamun M.A. Suicide among adolescents and youths during the COVID-19 pandemic lockdowns: a press media reports-based exploratory study. J. Child Adolesc. Psychiatr. Nurs. 2021;34(2):139–146. doi: 10.1111/jcap.12313. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Melhem N.M., Porta G., Oquendo M.A., Zelazny J., Keilp J.G., Iyengar S., Burke A., Birmaher B., Stanley B., Mann J.J., Brent D.A. Severity and variability of depression symptoms predicting suicide attempt in high-risk individuals. JAMA Psychiat. 2019;76(6):603–613. doi: 10.1001/jamapsychiatry.2018.4513. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. O'Connor R.C., Wetherall K., Cleare S., McClelland H., Melson A.J., Niedzwiedz C.L., O'Carroll R.E., O'Connor D.B., Platt S., Scowcroft E., Watson B., Zortea T., Ferguson E., Robb K.A. Mental health and well-being during the COVID-19 pandemic: longitudinal analyses of adults in the UK COVID-19 Mental Health & Wellbeing study. Br. J. Psychiatry. 2021;218(6):326–333. doi: 10.1192/bjp.2020.212. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Okado I., Floyd F.J., Goebert D., Sugimoto-Matsuda J., Hayashi K. Applying ideation-to-action theories to predict suicidal behavior among adolescents. J. Affect. Disord. 2021;295:1292–1300. doi: 10.1016/j.jad.2021.08.137. [DOI] [PubMed] [Google Scholar]
  35. Peprah P., Gyasi R.M. Stigma and COVID-19 crisis: a wake-up call. Int. J. Health Plann. Manag. 2021;36(1):215–218. doi: 10.1002/hpm.3065. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Pinto S., Soares J., Silva A., Curral R., Coelho R. COVID-19 suicide survivors-a hidden grieving population. Front Psychiatry. 2020;11 doi: 10.3389/fpsyt.2020.626807. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Puangsri P., Jinanarong V., Wattanapisit A. Impacts on and care of psychiatric patients during the outbreak of COVID-19. Clin. Pract. Epidemiol. Ment. Health. 2021;17:52–60. doi: 10.2174/1745017902117010052. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Qiu J., Shen B., Zhao M., Wang Z., Xie B., Xu Y. A nationwide survey of psychological distress among Chinese people in the COVID-19 epidemic: implications and policy recommendations. Gen. Psychiatr. 2020;33(2) doi: 10.1136/gpsych-2020-100213. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Rainbow C., Baldwin P., Hosking W., Gill P., Blashki G., Shand F. Psychological distress and suicidal ideation in Australian online help-seekers: the mediating role of perceived burdensomeness. Arch. Suicide Res. 2021;1–14 doi: 10.1080/13811118.2021.2020191. [DOI] [PubMed] [Google Scholar]
  40. Ran M.S., Zhang Z., Fan M., Li R.H., Li Y.H., Ou G.J., Jiang Z., Tong Y.Z., Fang D.Z. Risk factors of suicidal ideation among adolescents after wenchuan earthquake in China. Asian J. Psychiatr. 2015;13:66–71. doi: 10.1016/j.ajp.2014.06.016. [DOI] [PubMed] [Google Scholar]
  41. Raudales A.M., Short N.A., Schmidt N.B. Emotion dysregulation as a prospective predictor of suicidal ideation in an at-risk mixed clinical sample. Arch. Suicide Res. 2020;24(sup2):S310–S322. doi: 10.1080/13811118.2019.1598526. [DOI] [PubMed] [Google Scholar]
  42. Rogers J.P., Chesney E., Oliver D., Begum N., Saini A., Wang S., McGuire P., Fusar-Poli P., Lewis G., David A.S. Suicide, self-harm and thoughts of suicide or self-harm in infectious disease epidemics: a systematic review and meta-analysis. Epidemiol. Psychiatr. Sci. 2021;30 doi: 10.1017/S2045796021000214. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Sheervalilou R., Shirvaliloo M., Dadashzadeh N., Shirvalilou S., Shahraki O., Pilehvar-Soltanahmadi Y., Ghaznavi H., Khoei S., Nazarlou Z. COVID-19 under spotlight: a close look at the origin, transmission, diagnosis, and treatment of the 2019-nCoV disease. J. Cell. Physiol. 2020;235(12):8873–8924. doi: 10.1002/jcp.29735. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Sher L. The impact of the COVID-19 pandemic on suicide rates. QJM. 2020;113(10):707–712. doi: 10.1093/qjmed/hcaa202. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Shi L., Que J.Y., Lu Z.A., Gong Y.M., Liu L., Wang Y.H., Ran M.S., Ravindran N., Ravindran A.V., Fazel S., Bao Y.P., Shi J., Lu L. Prevalence and correlates of suicidal ideation among the general population in China during the COVID-19 pandemic. Eur. Psychiatry. 2021;64(1) doi: 10.1192/j.eurpsy.2021.5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Ustun G. Determining depression and related factors in a society affected by COVID-19 pandemic. Int. J. Soc. Psychiatry. 2021;67(1):54–63. doi: 10.1177/0020764020938807. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Vargas I., Perlis M.L., Grandner M., Gencarelli A., Khader W., Zandberg L.J., Klingaman E.A., Goldschmied J.R., Gehrman P.R., Brown G.K., Thase M.E. Insomnia symptoms and suicide-related ideation in U.S. Army Service Members. Behav. Sleep Med. 2020;18(6):820–836. doi: 10.1080/15402002.2019.1693373. [DOI] [PubMed] [Google Scholar]
  48. Wang Y.J., Chen X.P., Chen W.J., Zhang Z.L., Zhou Y.P., Jia Z. Ethnicity and health inequalities: an empirical study based on the 2010 China survey of social change (CSSC) in western China. BMC Public Health. 2020;20(1):637. doi: 10.1186/s12889-020-08579-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Wang D., Ross B., Zhou X., Meng D., Zhu Z., Zhao J., Fan F., Liu X. Sleep disturbance predicts suicidal ideation during COVID-19 pandemic: a two-wave longitudinal survey. J. Psychiatr. Res. 2021;143:350–356. doi: 10.1016/j.jpsychires.2021.09.038. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Wu K.K., Chan K.S. The development of the chinese version of impact of event scale-revised (CIES-R) Soc. Psychiatry Psychiatr. Epidemiol. 2003;38(2):94–98. doi: 10.1007/s00127-003-0611-x. [DOI] [PubMed] [Google Scholar]
  51. Wu P., Fang Y., Guan Z., Fan B., Kong J., Yao Z., Liu X., Fuller C.J., Susser E., Lu J., Hoven C.W. The psychological impact of the SARS epidemic on hospital employees in China: exposure, risk perception, and altruistic acceptance of risk. Can J Psychiatry. 2009;54(5):302–311. doi: 10.1177/070674370905400504. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Xiong J., Lipsitz O., Nasri F., Lui L., Gill H., Phan L., Chen-Li D., Iacobucci M., Ho R., Majeed A., McIntyre R.S. Impact of COVID-19 pandemic on mental health in the general population: a systematic review. J. Affect. Disord. 2020;277:55–64. doi: 10.1016/j.jad.2020.08.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Xu X., Ai M., Hong S., Wang W., Chen J., Zhang Q., Hu H., Li X., Wang L., Cao J., Shi L., Lv Z., Du L., Li J., Yang H., Qiu H., He X., Chen X., Chen R., Luo Q., Zhou X., Tan J., Tu J., Jiang G., Han Z., Baltha N., Kuang L. The psychological status of 8817 hospital workers during COVID-19 epidemic: a cross-sectional study in Chongqing. J. Affect. Disord. 2020;276:555–561. doi: 10.1016/j.jad.2020.07.092. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Xu X., Wang W., Chen J., Ai M., Shi L., Wang L., Hong S., Zhang Q., Hu H., Li X., Cao J., Lv Z., Du L., Li J., Yang H., He X., Chen X., Chen R., Luo Q., Zhou X., Tan J., Tu J., Jiang G., Han Z., Kuang L. Suicidal and self-harm ideation among chinese hospital staff during the COVID-19 pandemic: prevalence and correlates. Psychiatry Res. 2021;296 doi: 10.1016/j.psychres.2020.113654. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Yu D.S. Insomnia severity index: psychometric properties with chinese community-dwelling older people. J. Affect. Disord. 2010;66(10):2350–2359. doi: 10.1111/j.1365-2648.2010.05394.x. [DOI] [PubMed] [Google Scholar]
  56. Yu X., Tam W.W., Wong P.T., Lam T.H., Stewart S.M. The patient health Questionnaire-9 for measuring depressive symptoms among the general population in Hong Kong. Compr. Psychiatry. 2012;53(1):95–102. doi: 10.1016/j.comppsych.2010.11.002. [DOI] [PubMed] [Google Scholar]
  57. Zhang C., Yang L., Liu S., Ma S., Wang Y., Cai Z., Du H., Li R., Kang L., Su M., Zhang J., Liu Z., Zhang B. Survey of insomnia and related social psychological factors among medical staff involved in the 2019 novel coronavirus disease outbreak. Front Psychiatry. 2020;11:306. doi: 10.3389/fpsyt.2020.00306. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Zhu S., Zhuang Y., Lee P., Wong P. The changes of suicidal ideation status among young people in Hong Kong during COVID-19: a longitudinal survey. J. Affect. Disord. 2021;294:151–158. doi: 10.1016/j.jad.2021.07.042. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Articles from Journal of Affective Disorders are provided here courtesy of Elsevier

RESOURCES