Content of this journal is licensed under a Abstract
Background:
In early December 2019, during the outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which was first detected in Wuhan, COVID-19 was suspected, detected, and confirmed in an increasing number of patients every day. The clinical laboratory staff have always played an important role in the laboratory diagnosis of patients. Currently, there are many research studies on the mental health of the first-line doctors or nurses managing the COVID-19 outbreak, both domestically and overseas, but data of the mental health and associated factors among the clinical laboratory staff who handle the blood or biological samples of confirmed cases and are consequently exposed to COVID-19 are limited.
Methods:
This cross-sectional survey-based study was performed via an online survey in a single designated hospital from April 20 to April 23, 2020 in Yiwu,China. The online survey included questions on sociodemographic and clinical variables. Totally, 45 clinical laboratory staff and 20 nonmedical health workers participated. Mental health variables were assessed via 4 Chinese versions of validated measurement tools : Zung's Self-rating Depression Scale (SDS), Zung's Self-rating Anxiety Scale (SAS), the Pittsburgh Sleep Quality Index (PSQI), and the Eysenck Personality Questionnaire (EPQ).
Results:
Significant differences were observed in the SDS and SAS scores, between the clinical laboratory staff and the nonmedical health workers (P < .001, P < .003, respectively). The scores for exposure risk and neuroticism of participants were the main factors influencing both the SDS scores of the clinical laboratory staff (P = .002, P = .005, respectively), and also their SAS scores (P = .003 P = .006, respectively).
Conclusions:
The results showed that a significant proportion of clinical laboratory staff experienced anxiety and depression symptoms. Their scores for mental health problems, exposure risk, and neuroticism were associated with severe symptoms of depression and anxiety. Therefore, the high-risk group of the clinical laboratory staff and those individuals with higher neuroticism scores may need special attention.
Keywords: Mental health, COVID-2019 epidemic, clinical laboratory staff
Main Points
The clinical laboratory staff have always played an important role in the laboratory diagnosis of patients. Currently, there are many research studies on the mental health of the first-line doctors or nurses handling the COVID-19 outbreak, both domestically and overseas, but available data of the mental health and associated factors among the clinical laboratory staff handling the blood or biological samples of confirmed cases exposed to COVID-19 are limited.
Significant difference in the SDS and SAS scores were observed between clinical laboratory staff and nonmedical health workers. The exposure risk and neuroticism scores of participants were the main factors influencing both the SDS score of the clinical laboratory staff, and the SAS score.
During the outbreak, the clinical laboratory staff experienced symptoms of anxiety and depression. They had mental health problems and the exposure risk and neuroticism scores of participants were associated with severe symptoms of depression and anxiety.
The high-risk group staff and the individuals who had higher neuroticism scores may need special attention, and therefore, psychological interventions are essential.
Introduction
At the end of 2019, an outbreak of pneumonia caused by the novel coronavirus (SARS-CoV-2) infection, which was first detected in Wuhan, China, gradually became a public health emergency of international concern.1,2 The virus has been named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we will refer to the disease caused by SARS-CoV-2, COVID-19. According to the World Health Organization (https://www.who.int/dg/speeches/detail), COVID-19 is highly infectious and spreads rapidly, with the number of suspected and confirmed patients increasing daily. The medical staff, who directly participate in the diagnosis, treatment, and nursing of patients with COVID-19, may have psychological problems and other mental health symptoms while coping with this severe situation.3,4
At present, there are many research studies on the mental health of the first-line medical staff, both in our country and overseas,5-8 but there are few analyses of the mental health of the clinical laboratory staff. To address this gap, this study evaluated the mental health of the staff engaged in diagnostic procedures for virus detection, by quantifying the degree of depression, anxiety, and insomnia symptoms, and analyzing the potential risk factors related to these symptoms. This study aimed to assess the status of the mental health of clinical laboratory staff, which could provide important evidence so that appropriate psychological intervention measures can be adopted.
Methods
Study Design
This cross-sectional survey-based study was performed via an online survey in a single designated hospital from April 20 to April 23, 2020 in Yiwu,China. The online survey included questions on sociodemographic and clinical variables. Participation was voluntary; informed consent, including permission to publish the results of the research, was obtained. The confidential information and personal data of participants were protected. Participants could terminate the survey at any time, with no need to state their reasons. This study was approved by the Institutional Ethics Committee of Fourth Affiliated Hospital, Zhejiang University School of Medicine.(Approval number: K2020046, 2020/05/18).
Participants
The target sample size of participants was determined using the formula N = Zα 2P (1 − P)/d2, in which α = 0.05 and Zα = 1.96, and the estimated acceptable margin of error for proportion was 0.1. The proportion of health care workers with psychological comorbidities was estimated at 35%, based on the reference study.8 This study collected demographic data and mental health measurements from all the clinical laboratory staff in a single designated hospital for the diagnosis and treatment of COVID-19. By means of convenience sampling, the clinical laboratory staff who were engaged in patient sample collection, handling blood or biological samples of confirmed cases, and SARS-CoV-2 nucleic acid detection, were selected to participate in the survey. As of April 23, 2020, all the staff were invited to participate in this study, and there were 45 respondents. Besides this, 20 nonmedical health workers were recruited in this study as the control group. The healthy controls were recruited from the same geographical areas as the patients, and they were well-matched with the patients’ group in terms of gender, age, and ethnicity. The control group comprised participants who did not have any psychological disease. The exclusion criteria for the control group were as follows: (1) worked in centers for the diagnosis and treatment of COVID-19 and (2) close contact with patients with a confirmed diagnosis of COVID-19.
Clinical Assessments
We focused on the symptoms of depression, anxiety, and insomnia for all participants, using the Chinese versions of validated measurement tools. Accordingly, 4 questionnaires were used in this study. Zung's Self-rating Depression Scale (SDS), Zung's Self-rating Anxiety Scale (SAS), and the Pittsburgh Sleep Quality Index (PSQI), were used to assess the severity of symptoms of depression, anxiety, and insomnia of participants, respectively. Participants who had greater scores were characterized as having more severe symptoms. In addition, the Eysenck Personality Questionnaire (EPQ) was used to assess the personality characteristics of participants. As a self-report scale, the EPQ used is the revised version in China, and includes 4 subscales: internal and external propensity scale (E), neuroticism (N), psychoticism (P), and validity (L).
Demographic Data
Basic information was self-reported by the participants, including details on occupation (clinical laboratory staff or nonmedical health workers), sex (male or female), age (18-25 or >25 years), marital status (single or married), educational level (junior college, undergraduate, or postgraduate), technical title (junior, intermediate, or senior), and the number of years of work (≤5, 5-10, or ≥10 years). The participants who worked as clinical laboratory staff were asked which department they worked in and whether they were directly engaged in the clinical activities of diagnosing patients with confirmed COVID-19. Based on the risks of exposure to COVID-19 during the laboratory procedure, the participants of this study were divided into 4 groups (high-risk group, intermediate-risk group, low-risk group, and nonmedical health workers group), and the nonmedical health workers group was the control group. According to the biosafety consensus for COVID-19 in the clinical laboratory,9 the criteria for dividing the participants into groups were : (1) The staff of the high-risk group engaged in nucleic acid testing and who directly touched the confirmed/suspected patients’ sputum; the biosafety protection is Level III. (2) The staff of the intermediate-risk group who were engaged in the non-respiratory specimen examination, such as urine, feces samples for bacterial culture or routine test, and directly touched the confirmed or suspected patients’ specimen; the biosafety protection is Level II. (3) The staff of the low-risk group, who were mainly in contact with blood samples by operating automatic instruments, indirectly touching the confirmed/suspected patients’ specimen; the biosafety protection is Level I.
Data Analysis and Statistical Tests
The descriptive characteristics of the data obtained in the study are given with frequency, percentage distribution, and mean and standard deviation values. The t-test was used for comparison of the SDS and SAS scores between the 2 groups of gender (male and female), age (≤25 and >25), marital status (unmarried or married), and technical title (Junior and ≥intermediate). The single-factor analysis of variance (ANOVA) was used for comparisons of SDS and SAS between the multiple groups of exposure risk, education level, and years of work. The linear associations between the EPQ subscales and SDS or SAS were evaluated with a Pearson correlation test. Multiple linear regression analyses were used between exposure risk/EPQ subscales and SDS score.
All statistical analyses were performed using the Statistical Package for the Social Sciences (SPSS) version 22.0 (IBM SPSS Corp.; Armonk, NY, USA). The significance level was set at P < .05, and all tests were 2-tailed. The Least-Significant Difference test for was used for the post hoc analysis.
Results
The t-Test Comparisons of Symptoms of Depression, Anxiety, Insomnia Between the Clinical Laboratory Staff, and the Control Groups
This study compared 45 clinical laboratory staff with 20 nonmedical health workers. Significant differences in SAS scores were observed between the groups of participants (35.30 ± 6.25 vs 40.42 ± 9.38, t = 2.227, P < .05). Similar results were also observed for SDS scores, which were much higher in the clinical laboratory staff than in the controls (42.84 ± 11.12 vs 33.80 ± 4.56, t = 4.646, P < .01). However, there were no significant differences in the PSQI scores (4.00 ± 2.27 vs 5.36 ± 3.35, t = 1.903, P > .05).
Demographic Characteristics of the Clinical Laboratory Staff
The demographic characteristics of the groups and their comparison are given in Table 1. Out of the 45 clinical laboratory staff in the survey, 18 were male (40%), and 27 were female (60%). The participants were aged 21-48 years (28.56 ± 5.34), with the number of years of work ranging from 1 to 26 (5.73 ± 4.50) years. Of the 45 responding participants, 14 had attended junior college (31.11%), 24 were undergraduates (53.33%), and 7 had a master’s degree (15.56%). Most participants had an educational level of undergraduate or less (38, [84.4%]). The technical titles were as follows: junior: 31 (68.89%) and intermediate or senior: 14 (31.11%). With regard to marital status, 22 were married (48.89%) and 23 were unmarried (51.11%).The results showed that different levels of exposure risk impacted the participants’ SDS scores (P < .05). In addition, we found that differences in gender, exposure risk, and education level impacted the participants’ SDS scores (P < .05). However, there was no statistical significance in the other indicators, as follows (Table 1).
Table 1.
Single-Factor Analysis of the SDS and SAS of Participants with t-Test
| Characteristics | Total (n = 45) | SDS | t/F | Effect Size (r) | SAS | t/F | Effect Size (r) |
|---|---|---|---|---|---|---|---|
| Sex | 1.533 | 0.23 | 2.109* | 0.31 | |||
| Men | 18 | 39.78 ± 9.97 | 36.94 ± 7.50 | ||||
| Women | 27 | 44.89 ± 11.55 | 42.74 ± 9.91 | ||||
| Age, y | 0.725 | 0.11 | 0.377 | 0.11 | |||
| ≤ 25 | 14 | 44.64 ± 10.97 | 41.21 ± 10.09 | ||||
| > 25 | 31 | 42.03 ± 11.28 | 40.06 ± 9.19 | ||||
| Exposure risk | 3.429* | 0.45 | 3.442* | 0.39 | |||
| Low | 16 | 38.50 ± 9.33 | 36.00 ± 7.87 | ||||
| Intermediate | 20 | 43.10 ± 10.30 | 41.90 ± 7.73 | ||||
| High | 9 | 50.00 ± 13.03 | 45.00 ± 12.56 | ||||
| Low Risk<High Risk | Low Risk<High Risk | ||||||
| Education level | 2.101 | 0.35 | 3.449* | 0.45 | |||
| ≤ Junior college | 14 | 47.50 ± 10.84 | 45.00 ± 8.47 | ||||
| Undergraduates | 24 | 40.17 ± 8.60 | 37.29 ± 6.97 | ||||
| ≥ Postgraduate | 7 | 42.71 ± 17.03 | 42.00 ± 14.57 | ||||
| Marital status | 0.170 | 0.02 | −0.814 | 0.12 | |||
| Unmarried | 23 | 42.57 ± 10.63 | 39.30 ± 9.85 | ||||
| Married | 22 | 43.14 ± 11.86 | 41.59 ± 8.94 | ||||
| Technical title | 0.234 | 0.04 | −0.343 | 0.01 | |||
| Junior | 31 | 42.58 ± 10.37 | 40.97 ± 8.98 | ||||
| ≥ Intermediate | 14 | 43.43 ± 13.05 | 41.14 ± 10.54 | ||||
| Years of working, y | 0.085 | 0.07 | 0.755 | 0.21 | |||
| ≤ 5 | 24 | 42.42 ± 10.82 | 39.54 ± 9.78 | ||||
| 5-10 | 14 | 42.79 ± 9.28 | 39.93 ± 6.46 | ||||
| ≥ 10 | 7 | 44.43 ± 16.38 | 44.43 ± 12.88 |
Values are presented as M (mean) ± SD (standard deviation); * P < .05 considered statistically significant.
Subgroup Analysis of SDS/SAS/PSQI in Different Exposure-Risk Groups
The comparison of the subgroup analysis of SDS/SAS/PSQI in different exposure-risk groups using single-factor ANOVA tests is given in Figure 1. The difference in SDS scores among the 3 groups of participants was significant. (F = 3.429, P = .0042; Table 1). Further post hoc analysis indicated that the SDS scores were much higher in the high-risk group than in the low-risk group (50.00 ± 13.03 vs 38.50 ± 9.33, P < .05; Figure 1A). Similar results were also observed for SAS scores, which were much higher in high-risk group than in the low-risk group (45.00 ± 12.56 vs 36.00 ± 7.87, P < .05; Figure 1B). However, the PSQI scores among the 3 groups had no significant differences (P > .05; Figure 1C). In addition, no significant differences were observed in SDS or SAS scores in the intermediate-risk group (P > .05; Figure 1A, B, and C).
Figure 1.
Subgroup analysis of SDS/SAS/PSQI in different exposure risk groups with single-factor ANOVA tests. (A, B, C). SDS scores, SAS scores and PSQI scores in participants of 3 groups (low-risk group, intermediate-risk group, high-risk group). Data were shown as mean ± SD. LR, low-risk group; IR, intermediate-risk group; HR, high-risk group.
Correlation Analysis
The results of the correlation analysis between the EPQ subscales and SDS or SAS are given in Table 2. According to Pearson correlation analysis, the neuroticism (N) and psychoticism (P) of the EPQ were positively correlated with the SDS scores (the R-values were 0.489, 0.370, respectively. Table 2), and the correlation between neuroticism (N) and SAS scores was positive (the R-value was 0.451, Table 2).
Table 2.
Pearson Correlation Analysis Between the EPQ Subscales and SDS or SAS (N = 45)
| EPQ Subscales | SDS | SAS | ||
|---|---|---|---|---|
| R | 95% CI | R | 95% CI | |
| Internal and external propensity | −0.019 | −0.298 to 0.313 | 0.137 | −0.157 to 0.409 |
| Neuroticism | 0.489** | 0.226 to 0.708 | 0.451* | 0.180 to 0.662 |
| Psychoticism | 0.370* | 0.037 to 0.651 | 0.119 | −0.229 to 0.410 |
* P < .05
** P < .01
Multiple Linear Regression Analysis of SDS and SAS
The independent variables of the SDS and SAS scores are given in Table 3 and Table 4. Using a multiple linear regression analysis, the single-factor analysis of the SDS had statistically significant titles (exposure risk, neuroticism, and psychoticism) as independent variables, and we found that the higher the exposure risk and the score of neuroticisms, the higher the total SDS scores. The results showed that the exposure risk and neuroticism scores of participants were the main factors influencing the SDS total score of clinical laboratory staff, as follows (Table 3).
Table 3.
Multiple Linear Regression Analysis of SDS Score
| Regression Coefficient | 95% CI | SE | Standardized Regression Coefficient | t | |
|---|---|---|---|---|---|
| Exposure risk | 5.969 | 1.671 to 10.223 | 1.790 | 0.396 | 3.335** |
| Neuroticism | 0.347 | 0.112 to 0.623 | 0.116 | 0.385 | 2.997** |
| Psychoticism | 0.374 | −0.079 to 0.784 | 0.187 | 0.259 | 2.003 |
Table 4.
Multiple Linear Regression Analysis of SAS Score
| Regression Coefficient | 95% CI | SE | Standardized Regression Coefficient | t | |
|---|---|---|---|---|---|
| Gender | 4.480 | −5.180 to 31.812 | 2.481 | 0.237 | 1.805 |
| Exposure risk | 5.026 | −1.141 to 9.183 | 1.574 | 0.395 | 3.194** |
| Education level | −0.797 | 1.018 to 8.574 | 1.803 | −0.057 | −0.442 |
| Neuroticism | 0.284 | −5.113 to 3.134 | 0.099 | 0.373 | 2.874** |
Similar results were also observed for the SAS scores. Using a multiple linear regression analysis, the single-factor analysis of the SAS had statistically significant titles (gender, exposure risk, education level, and neuroticism) as independent variables, and we found that the higher the exposure risk and the score of neuroticism, the higher the total SAS score, The results showed that the exposure risk and neuroticism scores of participants were the main factors of influencing the SAS total score of clinical laboratory staff, as follows (Table 4).
Discussion
The outbreak of novel coronavirus pneumonia has greatly impacted the operation of medical and health systems under the epidemic situation. Many agencies and organizations have paid close attention to the doctors and nurses at the front-line, and implemented many intervention measures to prevent possible mental health problems.10-15 Currently, there are many studies that have reported the mental health status of doctors and nurses within the country and overseas, while there are few of recognition about the status of the mental health of the clinical laboratory staff. The self-assessment scale of mental health symptoms used this study showed that the clinical laboratory staff had a significantly worse mental health status than the general population during the epidemic. The survey, involving 45 clinical laboratory staff, showed that the prevalence of mental health symptoms was high among the staff engaged in the diagnosis of COVID-19.
Based on the risks in being exposed to COVID-19 during the laboratory procedures, the participants of this study were divided into 4 groups (the high-risk group, medium-risk group, low-risk group, and the general population), and the differences between the different groups were compared. The staff of the laboratory performed a large number of specimen tests for confirmed cases and suspected cases. With the increasing severity of the epidemic, the number of positive samples detected every day gradually increased. In the early stage of the epidemic, according to the disease diagnosis guidelines (National Health Commission of the People's Republic of China. Diagnosis and Treatment Scheme of Novel Coronavirus Infected Pneumonia, Trial Version 5, http://www.gov.cn/zhuanti/2020-02/09/content_5476407.htm.; accessed February 09, 2020), the result of nucleic acid detection is the crucial standard for the confirmed patients and also the essential discharge criterion. It was urgent for doctors to judge whether to treat patients or allow them to leave the hospital, based on the nucleic acid test results. In addition to a large number of specimens, the staff of the laboratory would worry about the missed and delayed diagnoses of patients due to inaccurate tests (false positive or false negative),16-18 Therefore, they would have had certain psychological pressure, which explains why the mental health status of the high-risk group (personnel engaged in nucleic acid testing and positive sample testing) in this study was significantly different from that of other groups.
COVID-19 is a highly complicated, infectious disease, and people are generally susceptible because it can spread by direct transmission from person to person.9 At present, effective treatment for COVID-19 is still unavailable, and information about the spread, pathogenicity, and mortality due to the virus is unknown.20,21 According to the existing research,22 the virus has been detected in the sputum, urine, feces, and blood of patients. The daily work of the clinical laboratory staff involves processing these types (sputum, urine, feces, and blood) of samples and testing for some indicators in them. The high-risk group and the middle-risk group directly touch the confirmed or suspected patients’ sputum, urine, or feces samples, and therefore, they would feel anxiety, helplessness, and depression due to the worry about being infected. The low-risk group mainly comes into contact with the blood samples operating automatic instruments, and the risk of exposure is greatly reduced; therefore, the overall psychological state of this group would be better. However, our results showed that there were individuals with obvious anxiety and depression in the low-risk group, which indicated the individual differences in psychological endurance. In addition, we found that the neuroticism scores of participants were the main factors influencing the anxiety and depression symptoms. More attention should be paid to the individuals with higher neuroticism scores. To cope with adverse psychological problems, everyone should be encouraged to seek help actively, so as to avoid negative effects such as post-traumatic stress disorder. However, this is not enough. The staff also need to feel that their needs are cared for and that they are safe, with adequate personal protective equipment in all settings. They need access to good peer and team support and to leaders who will continue to care for them well after the pandemic is over. The results of this study showed that in terms of sleep disorders, no matter which group of employees, there is no significant difference from the general population, which is inconsistent with the previous studies.2,10,11,23 It may be due to the relatively fixed working hours of the clinical laboratory staff, which can basically ensure regular work and rest time.
Conclusion
To sum up, our findings aimed to shed more light on the mental health of clinical laboratory staff participating in the task of testing for COVID-19. A significant proportion of participants in this study experienced anxiety and depression symptoms. Therefore, it is not only important to pay attention to the front-line doctors and nurses, but also to the clinical laboratory staff, and we need to correctly understand their mental health. Due to the high risk of anxiety and depression, the mental health of the high-risk group of staff and the individuals who had higher neuroticism scores may need special attention. At the same time, more attentive study and exploration is needed to identify ways to implement interventional measures in advance, to address the psychological problems that may be caused by emergency events, and also methods to reduce the negative impact of such critical stress events to special groups of people.
The results of this study showed that during the outbreak, the clinical laboratory staff experienced symptoms of anxiety and depression. They had mental health problems, and the exposure risk and neuroticism scores of participants were associated with severe symptoms of depression and anxiety. Therefore, the high-risk group staff and the individuals who had higher neuroticism scores may need special attention, and psychological interventions are essential.
Limitations
Several limitations should be considered. First, participants in this study were only recruited from 1 hospital, without additional data from other provinces and other hospitals. Thus, the number of research participants in the sample group was small, and results might show some bias. Second, the study was unable to distinguish between pre-existing mental health symptoms and new symptoms. Finally, besides the factors mentioned in this study, there might be other factors that affect mental health. Therefore, future research could enlarge the sample size and evaluate the working pressure of the clinical laboratory staff after the outbreak of the epidemic.
Funding Statement
This work was supported by Science and Technology program of Yiwu Science and Technology Bureau(18-3-110), the Basic Public Welfare Research Program of Zhejiang Province (LGF21H090012). Partially supported by Science and Technology program of Jinhua Science and Technology Bureau (2019-4-134).
Footnotes
Ethics Committee Approval: Ethical committee approval was received from the Ethics Committee of Fourth Affiliated Hospital, Zhejiang University School of Medicine. (Approval NO.: K2020046).
Informed Consent: Written informed consent was obtained from all participants who participated in this study.
Peer Review: Externally peer-reviewed.
Author Contributions: Concept –C.C.; Design -C.C.; Supervision - YR.L.; Resource -YR.L.; Materials - YB.R.; Data Collection and/or Processing - YB.R.; Analysis and/or Interpretation - YB.R; Literature Search - YB.R.; Writing - C.C.; Critical Reviews -YR.L.
Conflict of Interest: The authors have declared that no conflicts of interest exist.
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