Prevalence of and risk factors for depression, anxiety, and stress in non-hospitalized asymptomatic and mild COVID-19 patients in East Java province, Indonesia.

BACKGROUND: Despite abundant data on mental health during the COVID-19 pandemic, 3 important knowledge gaps continue to exist, i.e., 1) studies from low-/middle income countries (LMICs); 2) studies in the later period of the COVID-19 pandemic; and 3) studies on non-hospitalized asymptomatic and mild COVID-19 patients. To address the knowledge gaps, we assessed the prevalence of and the risk factors for mental health symptoms among non-hospitalized asymptomatic and mild COVID-19 patients in one LMIC (Indonesia) during the later period of the pandemic.
METHODS: This cross-sectional study was conducted in September 2020 in East Java province, Indonesia. Study population consisted of non-hospitalized asymptomatic and mild COVID-19 patients who were diagnosed based on reverse transcriptase-polymerase chain reaction results from nasopharyngeal swab. Mental health symptoms were evaluated using the Depression Anxiety Stress Scale-21.
RESULTS: From 778 non-hospitalized asymptomatic and mild COVID-19 patients, 608 patients were included in the analysis. Patients' median age was 35 years old and 61.2% were male. Of these, 22 (3.6%) reported symptoms of depression, 87 (14.3%) reported symptoms of anxiety, and 48 (7.9%) reported symptoms of stress. Multivariate logistic regression analysis showed that females were more likely to report symptoms of stress (adjusted odds ratio (aOR) = 1.98, p-value = 0.028); healthcare workers were more likely to report symptoms of depression and anxiety (aOR = 5.57, p-value = 0.002 and aOR = 2.92, p-value = 0.014, respectively); and those with a recent history of self-quarantine were more likely to report symptoms of depression and stress (aOR 5.18, p = 0.004 and aOR = 1.86, p = 0.047, respectively).
CONCLUSION: The reported prevalence of mental health symptoms, especially depression, was relatively low among non-hospitalized asymptomatic and mild COVID-19 patients during the later period of the COVID-19 pandemic in East Java province, Indonesia. In addition, several risk factors have been identified.

Introduction

Since 11 March 2020, severe acute respiratory syndrome coronavirus-2 that causes coronavirus disease 2019 (COVID-19) has been classified as a pandemic by the World Health Organization [1]. Currently, this virus has infected more than 500 million people and cause over 6 million deaths worldwide [2]. As human-to-human transmission occurs upon close contact with an infected person via respiratory droplets or aerosols [3], various preventive public health measures such as quarantine, social distancing, curfews, and lockdowns were implemented to prevent the spread of infection [4].

While these measures were deemed effective in limiting progression of the pandemic, they were not without consequences. People had to abruptly change their daily routines, working models, and social interactions. For example, working parents had to also mind their child(ren) while working from home, all meetings had to be switched from offline to online, business and leisure trips had to be cancelled, and physical contact such as handshakes or hugs were even prohibited. Hence, an increase in the prevalence of individuals with mental health symptoms was to be expected [5-7].

In the beginning of the COVID-19 pandemic, only little attention was paid to the impact of the COVID-19 pandemic on mental health [8]; but now, a great number of studies on this topic have been published. In a recent meta-review of meta-analyses, the prevalence of depression and anxiety during the COVID-19 pandemic was reported to be 26.93% and 27.77%, respectively [9]. These values are strikingly higher compared to pre-pandemic era, where the prevalence was estimated to be 4.4% for depression and 3.6% for anxiety [10]. Additionally, several risk factors that could adversely affect mental health during the COVID-19 pandemic have been identified, such as age, gender, educational background, socioeconomic status, marital status, the presence of children, occupation as healthcare worker (HCW), and a history of self-quarantine [11-13]. Nevertheless, despite the growing body of scientific literature on mental health during the COVID-19 pandemic, 3 important knowledge gaps exist.

First, although the COVID-19 pandemic has affected all countries around the globe, its impact on mental health varies across countries, with mental health symptoms being more prevalent in low-/middle-income countries (LMICs) compared to high-income countries [14]. Even so, most of the studies that have evaluated the impact of mental health during the COVID-19 pandemic originated from China, while studies from LMICs are lacking [15-17]. Second, the impact of the COVID-19 pandemic on mental health differs across time periods, with mental health symptoms being more severe in the beginning of the pandemic and become significantly milder in the following months [18]. Nonetheless, majority of the studies that evaluated mental health were conducted in the beginning of the pandemic [16, 18, 19], which may overestimate the magnitude of mental health problems during the COVID-19 pandemic. Third, previous studies have shown that adverse mental health symptoms are more prevalent among COVID-19 patients compared to the general population or HCWs [12, 14, 16, 20, 21]. Even so, studies assessing mental health during the COVID-19 pandemic rarely focused on the COVID-19 patients [22]. Among COVID-19 patients, those who are hospitalized are at higher risk of having adverse mental health symptoms compared to those who are not hospitalized [23-25]. This is because most of the hospitalized patients are patients with severe COVID-19 symptoms [26], and patients with severe COVID-19 symptoms are more likely to have adverse mental health symptoms than the non-severe one [27, 28]. Nevertheless, majority of COVID-19 patients are asymptomatic or presented with only mild symptoms that do not require hospitalization [24, 25, 29–32]. However, data pertaining to the mental health condition of non-hospitalized asymptomatic and mild COVID-19 patients are lacking [33]. In addition, no study has explored the risk factors of adverse mental health symptoms in this group of patients.

Thus, to address the aforementioned knowledge gaps, we conducted a study in Indonesia, one of the LMICs in Southeast Asia, during the later period of the COVID-19 pandemic, with non-hospitalized asymptomatic and mild COVID-19 patients as the study population.

Materials and methods

Study design and study population

This cross-sectional study was conducted between 1 and 30 September 2020 in East Java province, Indonesia. During this period, the number of cases was the highest in the country since the beginning of the pandemic [34]. Among 34 provinces in Indonesia, East Java province was the province with the second highest confirmed cases and the highest mortality rate [35].

The study population consisted of non-hospitalized asymptomatic and mild COVID-19 patients. Respondents were recruited at the Indrapura Emergency Field Hospital, the largest government-owned quarantine facility in East Java province, Indonesia. To be admitted to this quarantine facility, patients had to fulfill the following criteria: 1) Tested positive for COVID-19 on reverse transcriptase-polymerase chain reaction (RT-PCR) test; 2) Asymptomatic or having mild COVID-19 symptoms; and 3) able to take care of themselves.

To avoid the possible effect of facilitated quarantine on mental health, respondents were recruited before they underwent quarantine. When the patients came to the registration desk, those who fulfilled the inclusion criteria were verbally offered to participate in this study by the registrar. If the patients agreed to participate, they were asked to sign the informed consent and hand-filled the questionnaire on the spot.

Inclusion criteria for this study were as follows: age ≥ 18 years old, no history of mental illness, able to read and understand Bahasa Indonesia. History of mental illness among prospective respondents was ascertained by the registrar by verbally asking them if they had ever been diagnosed with mental illness or any mental health problems in the past.

Ethics approval

This study was conducted in accordance with the guidelines in the Declaration of Helsinki and was approved by the ethical review board of the Faculty of Medicine, Universitas Airlangga prior to study initiation (approval number: 201/EC/KEPK/FKUA/2020; approval date: 19 August 2020). All respondents provided written informed consent prior to their inclusion in the study, and information about the study was given before the consent form was signed. Details that might disclose the identity of the respondents were omitted.

Research instrument

The research instrument used in this study was a questionnaire requesting data on sociodemographic characteristics and responses to the Indonesian version of the Depression Anxiety Stress Scale-21 (DASS-21). Collected sociodemographic data were age, gender, education background, job status, marital status, number of children, and recent self-quarantine history. As this study also aimed to explore the possible risk factors of adverse mental health symptoms, the gathered sociodemographic data were based on literature concerning possible sociodemographic risk factors associated with mental health symptoms during the COVID-19 pandemic [20, 21]. However, since we want to avoid low response rate, we restricted the collection of sociodemographic data to the one that were easily and commonly gathered. DASS-21 is a self-report instrument for evaluating adverse mental health symptoms, which consists of 21 items that assess 3 components, namely symptoms of depression, anxiety, and stress. There are 7 questions for each component, and each question is scored on a 4-point Likert-scale, ranging from 0 (did not apply to me at all / never) to 3 (applied to me very much / almost always). The final score of each component is calculated by multiplying it by a factor of 2. The minimum final score is 0, and the maximum score is 42 for each component. Based on the total score of each component, the responses are categorized as normal, mild, moderate, severe, and extremely severe [36]. The categorization of each component, including the score range, is presented in Table 1. The Indonesian version of DASS-21 had been validated previously and showed good convergence, discriminant validity, and internal consistency (Cronbach’s alpha of 0.895) [37].

Table 1

Categorization and score range of DASS-21 [36].

	Normal	Mild	Moderate	Severe	Extremely severe
Depression	0–9	10–12	13–20	21–27	28–42
Anxiety	0–6	7–9	10–14	15–19	20–42
Stress	0–10	11–18	19–26	27–34	35–42

Statistical analysis

Data were analyzed using SPSS Statistic for Windows, version 25.0 (IBM Corp., Armonk, N.Y., USA). Data normality was evaluated using one-sample Kolmogorov-Smirnov test and was presented as mean ± standard deviation (SD) for normally distributed data, median [interquartile range (IQR)] for skewed data, and frequency (percentage) for nominal data. To identify the risk factors for depression, anxiety, and stress, two steps logistic regression analysis was used. First, univariate regression was used to identify each sociodemographic variable that was associated with depression, anxiety, and stress. Variables with p-value < 0.25 [38] were then subjected to multivariate regression using backward selection method. Variables with p-value < 0.05 from the multivariate regression analysis were considered as independent risk factors. During the logistic regression analysis, variables with missing data of more than 20% were excluded, and depression, anxiety, and stress variables were re-categorized as dichotomous (normal or not) variables with the cut-off scores as follows: 9 for depression, 6 for anxiety, and 10 for stress [36].

Results

From 778 non-hospitalized asymptomatic and mild COVID-19 patients who came to Indrapura Emergency Field Hospital during the study period, 763 participants fulfilled the inclusion criteria to be enrolled in the study. Of them, 608 patients were included in the analysis (79.7% response rate) (Fig 1). Sociodemographic characteristics of the study participants are presented in Table 2.

Fig 1

Flow diagram of study participants.

Table 2

Sociodemographic characteristic of the study participants.

Variables	N = 608
Age in years, median [IQR]	35 [27–45]
Gender, n (%)
Male	372 (61.2)
Female	236 (38.8)
Marital status, n (%)
Married	437 (71.9)
Single	162 (26.6)
Divorced	9 (1.5)
Have a child, n (%)
Yes	335 (55.1)
No	273 (44.9)
Educational background, n (%) *
Elementary graduate	16 (3.8)
Junior high graduate	23 (5.4)
Senior high graduate	207 (48.7)
University graduate	179 (42.1)
Job status as a healthcare worker, n (%)	27 (4.4)
Family income per month, n (%) #
< IDR 4.000.000	168 (41.2)
≥ IDR 4.000.000	240 (58.8)
Had undergone self-quarantine recently, n (%)
Yes	271 (44.6)
No	337 (55.4)

*Missing data on 183 (30.1%) respondents.

#Missing data on 200 (32.9%) respondents.

Median [IQR] score for depression was 0 [0-2], 2 [0-4] for anxiety, and 2 [0-6] for stress. Total score was 4 [0-12]. Of all respondents, 22 (3.6%) reported symptoms of depression, 87 (14.3%) reported symptoms of anxiety, and 48 (7.9%) reported symptoms of stress. Data on the severity of each component is presented in Table 3.

Table 3

Mental health severity symptoms distribution of the study participants.

	Depression	Anxiety	Stress
Normal, n (%)	586 (96.4)	521 (85.7)	560 (92.1)
Mild, n (%)	13 (2.1)	25 (4.1)	46 (7.6)
Moderate, n (%)	8 (1.3)	54 (8.9)	2 (0.3)
Severe, n (%)	1 (0.2)	7 (1.2)	0 (0)
Extremely severe, n (%)	0 (0)	1 (0.2)	0 (0)

For regression analysis, all sociodemographic variables from Table 1 were included, except educational background and family income, as these variables had a high percentage of missing data. Results of univariate and multivariate regression analysis for depression are presented in Table 4. Respondents who worked as HCWs and those who had undergone self-quarantine recently were more likely to report symptoms of depression (Table 4). Table 5 lists the results of regression analysis for anxiety. Respondents who worked as HCWs were more likely to report symptoms of anxiety (Table 5). Univariate and multivariate regression for stress are presented in Table 6. Female respondents and those who had undergone self-quarantine were more likely to report symptoms of stress (Table 6).

Table 4

Univariate and multivariate logistic regression analysis for depression.

Variables	Univariate			Multivariate
	COR	95%CI	p-value	AOR	95%CI	p-value
Gender
Male (ref)	-	-	-
Female	1.60	0.68–3.76	0.277
Age in years	1.01	0.97–1.04	0.720
Marital status
Married (ref)	-	-	-
Single	1.57	0.65–3.82	0.320
Divorced	0.0	0	0.999
Have a child
No (ref)	-	-	-
Yes	0.98	0.42–2.30	0.977
Job status
Healthcare workers	7.54	2.55–22.30	< 0.001	5.57	1.83–16.95	0.002
Other than healthcare workers (ref)	-	-	-	-	-	-
Had undergone self-quarantine recently
No (ref)	-	-	-	-	-	-
Yes	5.92	1.98–17.72	0.001	5.18	1.71–15.69	0.004

Variables with p-value < 0.25 in univariate analysis were subjected to multivariate analysis. Variables with p-value < 0.05 in multivariate analysis were defined as independent risk factors. AOR, adjusted odds ratio; COR, crude odds ratio; 95%CI, 95% confidence interval.

Table 5

Univariate and multivariate logistic regression analysis for anxiety.

Variables	Univariate			Multivariate
	COR	95%CI	p-value	AOR	95%CI	p-value
Gender
Male (ref)	-	-	-
Female	1.57	1.00–2.48	0.052
Age in years	0.99	0.97–1.01	0.550
Marital status
Married (ref)	-	-	-
Single	0.85	0.50–1.45	0.554
Divorced	0.72	0.09–5.82	0.754
Have a child
No (ref)	-	-	-
Yes	1.40	0.88–2.23	0.159
Job status
Healthcare workers	3.22	1.40–7.43	0.006	2.92	1.24–6.88	0.014
Other than healthcare workers (ref)	-	-	-	-	-	-
Had undergone self-quarantine recently
No (ref)	-	-	-
Yes	1.56	0.99–2.46	0.057

Variables with p-value < 0.25 in univariate analysis were subjected to multivariate analysis. Variables with p-value < 0.05 in multivariate analysis were defined as independent risk factors. AOR, adjusted odds ratio; COR, crude odds ratio; 95%CI, 95% confidence interval.

Table 6

Univariate and multivariate logistic regression analysis for stress.

Variables	Univariate			Multivariate
	COR	95%CI	p-value	AOR	95%CI	P-value
Gender
Male (ref)	-	-	-	-	-	-
Female	2.16	1.19–3.92	0.011	1.98	1.08–3.64	0.028
Age in years	1.00	0.97–1.02	0.882
Marital status
Married (ref)	-	-	-
Single	0.92	0.47–1.82	0.808
Divorced	1.44	0.18–11.81	0.737
Have a child
No (ref)	-	-	-
Yes	1.39	0.76–2.56	0.284
Job status
Healthcare workers	3.67	1.40–9.58	0.008
Other than healthcare workers (ref)	-	-	-
Had undergone self-quarantine recently
No (ref)	-	-	-	-	-	-
Yes	2.01	1.10–3.66	0.023	1.86	1.01–3.44	0.047

Variables with p-value < 0.25 in univariate analysis were subjected to multivariate analysis. Variables with p-value < 0.05 in multivariate analysis were defined as independent risk factors. AOR, adjusted odds ratio; COR, crude odds ratio; 95%CI, 95% confidence interval.

Discussion

Our analysis indicates that, in the later period of the COVID-19 pandemic, the prevalence of depression, anxiety, and stress was 3.6%, 14.3%, and 7.9%, respectively, among non-hospitalized asymptomatic and mild COVID-19 patients in the East Java province, Indonesia. Further, we were able to identify job status as HCWs and recent self-quarantine history to be the risk factors for depression, while that for anxiety was job status as HCWs, and those for stress were female gender and recent self-quarantine history.

To the best of our knowledge, there are only 4 studies that evaluate the mental health of non-hospitalized asymptomatic and/or mild COVID-19 patients to this date [33, 39–41]. Guo et al (2020) evaluated the mental health symptoms of mild COVID-19 patients in China and revealed that the prevalence of depression and anxiety were 17.5% and 6.8%, respectively. Additionally, compared to matched normal individuals, total score for depression and anxiety were significantly higher in mild COVID-19 patients [39]. In Korea, the prevalence of depression and anxiety among asymptomatic and mild COVID-19 patients were 10.3–24.3% and 14.9–15.9%, respectively [33, 40]. A study among asymptomatic COVID-19 patients from India showed that the prevalence of depression, anxiety, and stress were 49.4%, 40.9%, and 75.8%, respectively [41].

There are several possible explanations for such differences in terms of prevalence rates between this current study and previous studies. First, while our study was done in September 2020, previous studies were done during the initial stage of the pandemic. A recent meta-analysis of a longitudinal cohort studies showed that the prevalence of adverse mental health symptoms was the highest during March–April 2020 and decreased significantly afterward [18]. It is because perceived risks on COVID-19 infection and mortality, financial stability, and lifestyle changes rose sharply in the initial stages of the pandemic and declined in the later stages, and these factors were positively associated with changes in mental health symptoms [42]. Second, as the condition of healthcare systems and the government’s response to the pandemic differ across countries, the prevalence of depression, anxiety, and stress are likely to be lower in countries where both are adequate [43, 44]. Third, the instrument used to measure mental health status in this study is different from those used previously [33, 39, 40], which would have also contributed to the observed variation. For example, compared to DASS-21, 8-item Patient Health Questionnaire instrument is more likely to classify individuals as having depression, while 7-item General Anxiety Disorder instrument is more likely to classify individuals as having anxiety [45]. However, the best instrument to measure depression, anxiety, and stress remains contentious, and we used the DASS-21 because it can measure depression, anxiety, and stress with the least number of questions and has already been adapted to Bahasa Indonesia.

Several studies have evaluated the prevalence of mental health symptoms during the COVID-19 pandemic in Indonesia using DASS-21. However, all of the studies focused on either general population [46-48] or healthcare workers [49-53], with none on the asymptomatic and/or mild COVID-19 patients. Depending on the study population and data collection period, the prevalence of depression, anxiety, and stress was 8.5–32.6%, 9.3–44.9%, and 2.4–31.8%, respectively [46-53]. Other than study period differences that has been discussed in the paragraph above and the difference in study population, varying prevalence rates may also be explained by differences in data collection methods used. While previous studies collected the data using online survey [46-52], we directly approached potential respondents and asked them to fill in the questionnaire. When collecting data for mental health studies, it has been reported that respondents provide a more negative response in online surveys than in offline surveys [54]. We hypothesized that this may be due to the anonymity associated with online questionnaires, because the respondents believe that their true identity can be fully protected in online but not in offline surveys. The identity issue might also be associated with societal stigma and discrimination toward people with mental health problems, especially in Asian countries, including Indonesia [55-57].

We found that people who worked as HCWs were more likely to report symptoms of depression and anxiety compared to non-HCWs, a finding not consistent with previous reports. For example, a study from China showed that the general population was at greater risk of developing depression and anxiety compared to HCWs [58], and another study from Italy reported that the general population and frontline HCWs were at similar risk of developing depression and anxiety [59]. We posit that disparities in healthcare systems across countries during a pandemic lead to differential impact on the mental health among HCWs [60], and that they are responsible for the observed differences in results.

The capacity of Indonesia’s healthcare system and infrastructure is far from adequate to battle the COVID-19 pandemic. Since before the COVID-19 pandemic, there has been a significant shortage of HCWs and their distribution is uneven throughout the country [61]. However, during the COVID-19 pandemic, the shortage of HCWs is aggravated by high mortality among those treating COVID-19 patients [62, 63], resulting in higher workload and longer working hours for the remaining personnel, especially when the number of COVID-19 patients continue to increase. Moreover, similar to other countries, there is a lack of personal protective equipment (PPE) for HCWs on duty in Indonesia, with this shortage being worsened by the panic buying and stockpiling of medical-grade PPE by the public [63, 64]. Other than that, the number of hospitals, bed capacities, and supporting facilities to treat COVID-19 patients such as negative pressure wards and ICU rooms are lacking and also not evenly distributed in Indonesia [61-63]. The lack of facilities putting HCWs in difficult position, where they have to decide to whom the treatments should be given [65]. The above-mentioned issues might explain why HCWs in Indonesia are more prone to adverse mental health symptoms compared to the general population.

In our study, we discovered that women were more likely to report symptoms of stress, and previous studies, either before [66-69] or during the COVID-19 pandemic [48, 70–72], also showed that women register higher stress scores and are at greater risk of developing stress. Gender differences in mental health have been discussed since the 1970s, and women have been reported to experience distress more frequently and develop more symptoms than men under identical levels of stress [73]. Several explanations have been proposed for greater stress susceptibility in women. Biologically, women express higher levels of corticotropin-releasing factor (CRF) and had more CRF receptors compared to men, and upon its release from the hypothalamus during a stressful event, CRF activates the hypothalamus-pituitary-adrenal axis by stimulating adrenocorticotropic hormone (ACTH) to produce cortisol, which is a primary stress hormone in the body, from the adrenal cortex [74]. Additionally, at identical levels of ACTH, the female adrenal cortex is more responsive to cortisol production than the male adrenal cortex [75]. Furthermore, fluctuations in sex hormones, either due to menstrual cycle or reproductive status, also contribute to stress vulnerability [76]. Psychologically, women tend to express distress by internalizing problems rather than externalizing them [77]. Apart from that, as women are the primary caregivers within the household, and they often prioritize the condition of family members over their own [78, 79]. During the COVID-19 pandemic, it can be assumed that they may be apprehensive of no one being able to take care of the family if they are diagnosed with COVID-19 and had to be quarantined or hospitalized.

Interestingly, although mental health problems appear to be more common in women, suicide rates have been noted to be higher in men [80-82]. It can then be argued that mental health problems are underdiagnosed in men. Several possible explanations have been proposed, and they include: 1) men are less likely to express troubles, discuss sensitive issues, or solve emotional problems [83]; 2) men are more likely to express the distress by externalizing problems rather than internalizing them because of the fear of stigma [77]; and 3) men seek help for mental health care far less often than women as help-seeking behavior is viewed as a weakness and is contrary to masculine traits [84, 85]. In addition to that, it has also been suggested that there is a measurement bias in the currently available self-report instrument for mental health [83]. For instance, the experience of stress is different between sexes, where men feel more depersonalized, while women tend to feel emotionally exhausted [86]. Nevertheless, available instruments to measure stress do not assess psychological stress as depersonalization [68]. Thus, although the current study and a great body of evidence support the notion that women are at higher risk of developing mental health symptoms, we believe that investigations using structured diagnostic interviews should be done in the future to clarify whether one gender is at higher risk of developing mental health symptoms than the other.

In this study, we also found that people who had undergone self-quarantine recently were more likely to report symptoms of depression and stress. Since the 14th century, quarantine has been an important public health measure to reduce incidence and mortality during any outbreak [87, 88]. However, quarantine negatively affects mental health, and data from previous outbreaks have described several adverse psychological effects such as depression, anxiety, stress, low mood, and anger [89]. A recently published meta-analysis revealed a significant relationship between mass quarantine and mental health during the COVID-19 pandemic [90], and a multi-center study from 7 middle-income countries in Asia showed that those who have ever been quarantined during the COVID-19 pandemic were at higher risk of depression, anxiety, and stress [11]. Studies from China also demonstrate that people who were quarantined had higher risk of depression, anxiety, and stress. Furthermore, those who were diagnosed or suspected of having COVID-19 infection were at even greater risk of depression, anxiety, and stress compared to uninfected individuals [21, 91].

Nevertheless, the negative effects of quarantine on mental health appears to occur only during self-quarantine and not in facilitated quarantine. In the initial stage of the pandemic, Jeong et al (2020) evaluated the mental health of asymptomatic and mildly symptomatic COVID-19 patients who were admitted to the non-hospital facilities for isolation and monitoring in South Korea. Mental health status was evaluated twice in that study, i.e., after the 2nd week of quarantine and 1 week after the first survey, and they found no significant differences in anxiety or depression scores [33]. A similar study from South Korea also found that the prevalence of depression, anxiety, suicidal risk, and stress was constant until the 4th week of quarantine [40]. We have also previously reported that being quarantined in a quarantine facility did not worsen the mental health status of asymptomatic and mild COVID-19 patients [92]. Some of the known psychological stressors during quarantine are frustration, boredom, and inadequate supplies [89], but in a quarantine facility, patients are provided free meals thrice daily, including snacks and entertainment facilities. In contrast, people who undergo self-quarantine are not provided such things by the government, and this might explain these differences in terms of mental health status.

This study has several important limitations. First, the symptoms of depression, anxiety, and stress were based on self-reported questionnaire; hence, they may not always concur with objective assessment by health professionals. Second, the cross-sectional nature of this study precludes any inference of causality or evaluation of longitudinal changes in mental health symptoms during the COVID-19 pandemic. Third, socioeconomic status and educational background were not included in the regression model due to the missing data in more than 30% of the respondents. Fourth, it has been shown that longer quarantine time was associated with worsen mental health status [90, 93]. However, data regarding the number of days in self-quarantine were not available for a majority of the respondents because they could not adequately recall relevant details. Fifth, we did not evaluate the mental health prevalence from other groups, e.g., general population, hospitalized COVID-19 patients, and long COVID-19 patients. Thus, difference in mental health symptoms prevalence between non-hospitalized asymptomatic and mild COVID-19 patients and other groups could not be seen. Last, data collection for this study was done in September 2020. The situation in that period was different than when Indonesia became the epicentrum of the COVID-19 pandemic in Asia [94], or in the recent outbreak of the Omicron variant [95].

Conclusion

To the best of our knowledge, this is the first study to investigate the mental health symptoms among non-hospitalized asymptomatic and mild COVID-19 patients during the later period of the COVID-19 pandemic. We report that the prevalence of mental health symptoms, especially depression, is relatively low among these patients in East Java province, Indonesia. Despite the low prevalence, our finding showed that HCWs are more vulnerable to depression and anxiety; females are more vulnerable to stress; and those who had undergone self-quarantine recently are more vulnerable to depression and stress.

(SAV)

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21 Oct 2021

PLOS ONE

Dear Dr. Salamah,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

I have read your manuscript with interest and received the comments of two independent reviewers. The comments of the reviewers are attached in this letter. I agree with their very critical comments and will try to prevent repeating them as much as possible.

My general impression is that a lot of work needs to be done to address the comments of the reviewers and to address my comments. I would like to advise you strongly to ask a native speaker to check/correct the revised manuscript (the language errors distract too much).

Your introduction lacks, given your research question, a clear overview of what is (un)known about the mental health of the infected and/or people who are forced to stay in quarantine, as well as groups at risk for mental health problems. It is simply incomplete and too short. Please pay more attention towards the different periods during this pandemic.

Please be much more critical on studies examining effects of the pandemic (very often using convenience samples and cross sectional studies without reference data prohibiting any valid conclusion about the effects of this pandemic on mental health), and include the recent meta-analysis of prospective studies of Robinson et al. 2021 (doi: 10.1016/j.jad.2021.09.098).

Clarify which IRB was involved (not only the code of 201…..).

Please explain how potentially respondents were contacted to ask to participate in your study. How were the questions administered (written, online, verbal?).  When were the questions administered (during quarantine, afterwards and how many weeks after the quarantine). Were other family members infected, in hospital because of infection, deceased following infection, etc.

No information is provided about the non-response and results of the non-response analyses.

Cronbachs alpha’s of the DASS-21 scales of the study sample are missing.

Explain how a history of mental illness was assessed.

Explain and clarify which “independent variables” were examined (and introduce/explain alll in the introduction).

You entered the variables in the multivariate analyses that were significant in the univariate analyses on p <.025 level. I don’t understand this strategy. It is more informative to include all predictors in the multivariate analyses (and thus you can skip the univariate analyses).

Show the prevalence of anxiety, depression and stress of all predictors in the table, and clarify which cut-off’s were used in the logistic regression analyses.

The text suggest that you only examined age, gender, marital status, having a child, and income, besides administering the DASS-21. Is this correct? If not, why did you not include these other variables?

Please improve your tables and present all relevant info, including explained variance, statistics of all include variables.

As the reviewers noted, the discussion is not a discussion (for example a limitation section and comparisons with the results of other studies on infected/quarantined are completely absent). I would like to advise you to read other COVID-19 papers published in PLOS ONE on the mental health of patients/general population, that can be used as examples.

Please submit your revised manuscript by Dec 04 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: No

Reviewer #2: Partly

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: No

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: No

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: No

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This is an interesting study but it needs mayor revision before it can be considered again.

Authors should explain that they assessed non-hospitalized COVID.19 patients during the 14 days of quareenten. It is not clear. more data of COVID.19 fatures is needed. time from diagnosis is needeed. maybe anxiety and depression is not the same day one than 10 days after reclusing at home.

Differentiation between anciety and depresison in general population, hospitalized COVID-19 patients and long COVID patients is needed. Authors have assess moddo disorders in a manner that it is not commonly investigated in the literature, which increases the relevance of the paper, but more justification and discussion is needed.

What happened with these patients about 14 days? was any follow-up of them?

The role of gender needs extensive discussion since there is available data on the liteature for that

In conclusion, the paper needs xtensive inclusion of more data and extensive work before it can be reconsidered again.

Reviewer #2: Summary

The authors have attempted to assess the severity and prevalence of anxiety, depression, and stress and to identify risk factors in an adult cohort of participants with non-severe COVID-19 in the East Java province in Indonesia. They observed that depression was prevalent in 3.6% of the participants, anxiety in 14.3%, and stress in 7.9%. Furthermore, female gender was associated with a higher risk of anxiety and stress, and higher depression, anxiety, stress and total score. Based on these results, the authors conclude that depression, anxiety, and stress was prevalent in 3.6%, 14.3%, and 7.9%, that women are at higher risk and that women with confirmed COVID-19 should therefore be regularly evaluated.

Although this is an interesting study, a lot of work should be done prior to this work being ready to be published. My suggestions are described below:

General recommendations

- In my opinion, the level of English used could and should be better. There are quite many grammatical errors, suboptimal choices of verbs etc. Consider asking a native speaking colleague to copy-edit the manuscript.

- Including the outcomes of the univariate regression models does not fulfill the criteria of making all data underlying the findings described fully available; please add a dataset containing the raw data to fulfill this criterion.

Specific recommendations

Title

- I think “risk factor” should be “risk factors”, even though only one risk factor was identified.

Abstract

- I am missing the importance of your work/knowledge gap your research is filling in in your abstract

- “Study population was non-severe…” (line 31); I think “comprised” or “consisted of” would be a better verb

- “that was” (lines 31) should be “which were”

- “Collected data …. version 25.0” (lines 33-34) should be omitted from the abstract.

- “There were … in this study” (lines 34-35); Out of how many patients were those 608 included, in other words what was the inclusion/response rate.

- “From 608 respondents …” (line 35); in the phrase before it was already mentioned that there were 608 participants. I would suggest changing this to “Of these… “

- As you only used a screening instrument to detect psychological symptoms, I would suggest weaken the statements regarding having depression, anxiety, or stress. I think “reported” would be a better choice of verb.

- I would suggest adding the association between the severity of psychological symptoms (i.e., the scores) and female gender to your abstract.

- I don’t think the conclusion drawn can be extrapolated from the data presented. Although you demonstrate that female sex is a risk factor for psychological symptomatology, this does not mean that males doesn’t report any psychological symptoms (I imagine, as this comparison is not ready made in the manuscript).

Introduction

- I think in general the introduction is lacking important references.

- Lines 44 to 50 are not relevant, as everybody already knows about the COVID-19 pandemic. Try to be more creative when writing your introduction.

- I think much more literature regarding recent findings about psychological distress during COVID-19 should be added and described. The introduction in its present form lacks a description of why this research is important and what are the knowledge gaps. Why would you think that patients have psychological distress during COVID-19/a SARS-CoV-2 infection? What is already known? What isn’t known? What is your research going to add to the literature. I think “However, there is no study conducted that evaluates the mental health conditions among confirmed COVID-19 patients in Indonesia to this date” is not enough justification for your research.

- Overall, I think the introduction is to general, especially the first paragraph, and lacks a clear description of already published literature concerning this subject.

Methods

- “Study population was” (line 65): This is not correct English. Also, this sentence is too long, I would split it up in more sentences for clarity.

- “Inclusion criteria was … in this study” (lines 69-70): There are various grammatical errors in this sentence, please rephrase.

- “relevant institutional reviewer board” (lines 71-72): Please include the name of the institutional review board.

- I was expecting a paper describing the validity of the used screening questionnaire for reference 8. This reference however does not study this matter, but only uses the same instrument. Please provide a reference that is indeed studying the validity of the instrument. Are there any other references about the development of the DASS-21?

- Which sociodemographic characteristics were asked for? In the results, only age, sex, marital status, having a child and incomes are listed, are those also the only demographic variables that were gathered?

- I think the listing of the cut-off values is quite chaotic. Maybe it is an idea to add a table (in the main manuscript or additional files) which gives a clear oversight of the cut-of values.

- It is totally unclear to me why only the abovementioned variables were used to identify risk factors for the development of anxiety, depression, or stress. Was this based on existing literature? Please describe this in much more detail in the manuscript.

- Were all patients included in just one month (September 2020)? Otherwise, specify the start and ending date of the study.

- When and how were patients recruited and included?

- Why were patients with a history of mental illness excluded? How was this determined?

- You only describe that you use logistic and linear regression analysis, but it is not clear for which they are used. This should be made more clear.

Results

- I am missing the total number of patients who were eligible, from which the 608 participants were included. It might be an idea to include a flow diagram to show this.

- I am missing a table depicting the descriptives of the main outcomes, which are the prevalence and severity (i.e., sum scores) of the domains of the DISS-21. It is now only described in the text. In this way, you can omit the text regarding the distribution among mild, moderate or severe psychological distress, and just refer to the table.

- It might be an interesting idea to group the cohort based on their outcomes (i.e., patients who reported psychological stress vs. patients who did not), and compare these groups.

- I think the first paragraph could be written in a less point-to-point manner.

- Table S1: Where does ‘COR’ stand for? Abbreviations should be explaned for each table (not this is only done for table S2 and Table 3.

- Table 2: I do not understand why ‘having at least one child’ is not added to the multiple logistic regression model, as these variables had a p-value <0.25 in the univariate logistic regression model.

- Tabel 2: Why does this table include ‘depression’ as no multiple regression analysis was conducted for this outcome?

- Table 3: I would suggest adding all variables, including their Beta, SE, etc. for all components which were added to the model. In that way, you don’t have to describe everywhere for which other variables were adjusted.

- Table 3: I do not understand why the multiple linear model for anxiety was adjusted for having a child and marital status, when marital status did not have a p-value below 0.25 in the univariate analysis.

- Overall, I think the results section can be written in a more clear and organized manner.

Discussion

I think the discussion needs a lot of work; in its present form it is 1) way too shallow and 2) the authors have failed to discuss any truly important topics.

Try to rewrite the discussion using the following paragraphs:

First paragraph: Short repetition of the main results.

Second and further paragraphs: Discussing observed main results with recent literature.

Last paragraph: Limitations

In its present form, the authors already start discussing their results in the first paragraph by mentioning another study in COVID-19 confirmed cases. I think, if that is a point of discussion, the authors should elaborate more on these results, and also compare with, for instance, papers which report the prevalence of psychological distress after COVID-19. Other literature concerning this matter is hardly referred to.

Also, the only true discussion the authors describe is the fact the women are more prone to psychiatric sequelae after COVID-19. That is, in my opinion, not new or surprising at all and definitely not enough on its own for a discussion. The fact that the whole manuscript only counts 17 references, of which 5 are not even scientific papers, underscores my point.

Conclusion

The conclusion in its present form is just a repetition of the main results of this study and not so much of an conclusion, except that the psychological well-being of COVID-19 positive women should be evaluated regularly. In my opinion, the conclusion section should never contain number, as the results section is the only place to report these. As such, I think the conclusion should be rewritten.

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6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

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Reviewer #1: No

Reviewer #2: No

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23 Feb 2022

Dear editor and reviewers,

Thank you for the comments and suggestions for this manuscript. We have uploaded the point-to-point response in the submission files.

Submitted filename: Response to reviewer.docx

Click here for additional data file.

4 Apr 2022

21 Apr 2022

Dear reviewers,

Thank you for the comments and suggestions for this manuscript. We have uploaded the point-to-point response in the online submission system.

Submitted filename: Response to reviewer.docx

Click here for additional data file.

22 Jun 2022

Prevalence of and risk factors for depression, anxiety, and stress in non-hospitalized asymptomatic and mild COVID-19 patients in East Java province, Indonesia

PONE-D-21-21429R2

Dear Dr. Salamah,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards and congratulations with your paper,

Peter G. van der Velden, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Authors have addressed all comments properly from this reviewer and the other reviewer. The paper can be now accepted

Reviewer #2: I would like to congratulate the authors on their revision, which considerably improved the manuscript.

I believe that it is now ready for publication.

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Johan Hendrik Vlake

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27 Jun 2022

PONE-D-21-21429R2

Prevalence of and risk factors for depression, anxiety, and stress in non-hospitalized asymptomatic and mild COVID-19 patients in East Java province, Indonesia

Dear Dr. Salamah:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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on behalf of

Prof. dr. Peter G. van der Velden

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PLOS ONE