a b s t r a c t

Background: Since the declaration of the novel Corona Virus Disease (COVID-19) as a global pandemic by the World Health Organization, frontline Healthcare workers (HCWs) and staff in the Emergency Departments (ED) started experiencing feelings of anxiety and fear from the projected exponential spread and the potential burden on the healthcare system and infrastructure. In Lebanon, major local factors contributing to this fear were the rapid escalation of COVID-19 cases across the country, the lack of preparedness, and the shortage of per- sonal protective equipment, in addition to the evolving economic crisis and financial restrictions. This study aims to investigate the immediate psychological impact of the Covid-19 outbreak on ED staff working in a hospital environment in relation to their household income.

Methods: Self-reported cross-sectional survey was delivered to the frontline staff working at the Department of Emergency Medicine of AUBMC in Beirut, Lebanon. General demographic characteristics, scores of Generalized Anxiety Disorder 7 (GAD-7), scores of Patient Health Questionnaire 9 (PHQ-9), and scores of Burnout Measure-Short (BMS) version were collected.

Results: 74 HCWs (49.6%) participated in the study. The mean age for participants was (31.78 +- 9.49). More than half of the participants were nurses and more than 70% reported a monthly salary of less than 2000 USD. The household income was negatively associated with the participants’ scores on the GAD-7 and PHQ-9, but not the BMS. Previous mental health diagnosis was positively associated with the PHQ-9 and BMS scores, while seek- ing mental health care was negatively associated with the PHQ-9 and BMS scores.

Conclusion: At our tertiary care center in a low-income, low resource country amidst the COVID-19 pandemic, the HCWs reported marked psychological disturbances on different scales. In particular, the Financial burden was associated with increased anxiety and clinical depression, but was not associated with burnout.

(C) 2021

1. Background

In January 2020, the World Health Organization (WHO) declared a novel coronavirus outbreak causing Corona Virus Disease (COVID-19)

Abbreviations: WHO, World Health Organization; AUBMC, American University of Beirut Medical Center; ED, Emergency Department; CDC, Center for Disease Control; PPE, Personal protective equipment; HCWs, Healthcare Workers; JCI, Joint Commission International; CAP, College of American Pathologists; ACGME-I, Accreditation Council for Graduate Medical Education - International; GAD-7, General Anxiety Disorder; BMS, Burnout Measure - Short questionnaire; PHQ-9, Patient Health Questionnaire-9.

* Corresponding author at: Department of Emergency Medicine, Massachusetts General Hospital, 55 Fruit Street, Boston, MA, United States of America.

E-mail addresses: [email protected] (M. Al Hariri), [email protected] (B. Hamade), [email protected] (M. Bizri), [email protected] (O. Salman), [email protected]

(H. Tamim), [email protected] (N. Al Jalbout).

and considered it a public health emergency of international concern. With its exponential spread across countries, the WHO considered COVID-19 a global pandemic on March 11, 2020 [1]. To date (October 6, 2021), 235,673,032 confirmed cases of COVID-19 have been reported globally. The total number of deaths secondary to COVID-19 has reached 4,814,651 cases [2].

In Lebanon, the first case of COVID-19 was diagnosed on February 21, 2020. Since then, there has been steep growth in the daily number of cases of COVID-19. To date (October 6, 2021), Lebanon has officially registered 627,722 confirmed cases and 8997 deaths [3].

On March 10, 2020, the American University of Beirut Medical Center (AUBMC) started performing COVID-19 PCR testing, rendering the Emergency Department (ED) at AUBMC the frontline recipient of COVID-19 suspected cases, testing between 80 and 200 cases per day

https://doi.org/10.1016/j.ajem.2021.10.055

0735-6757/(C) 2021

during the study period. Given the uncertainty of the mode of disease spread early on, conflicting data from WHO and Center for Disease Control (CDC), the global shortage of Personal protective equipment , and the large number of infected Healthcare workers in- ternationally, frontline staff in the ED began experiencing feelings of anxiety from the projected spread and Disease burden [1,4]. Additional factors, such as the observed high lethality in neighboring countries, and the daily change of Infection control protocols and public health recommendations, heightened the perception of personal danger and feelings of apprehension among staff. This is in addition to the fear of carrying the disease home, as well as the social stigmatization of HCWs as vectors for the disease.

Importantly, Lebanon was facing a challenging and unprecedented economic crisis. Amidst the COVID-19 pandemic, the Lebanese financial sector suffered from an exponential devaluation of the local currency [5]. Subsequently, the workers in the Lebanese industries lost between 61.5% to 84.7% of the value of their salaries compared to USD, thus reducing the workers’ purchasing power. Specifically, the Healthcare sector endured capital control and restrictions on utilizing their bank deposits for purchases of essential basic supplies.

The SARS outbreak in 2003 revealed that HCWs are at risk of experiencing an immediate psychological impact, including feelings of anxiety and sometimes post-traumatic stress disorder, affecting occupa- tional productivity [6-8]. On March 12, 2020, WHO initiated online education on the psychosocial considerations during the COVID-19 out- break [9], with a specific section dedicated to HCWs. With experience from SARS, and WHO’s early awareness campaigns on mental health during COVID-19, there was a need to evaluate the current psychologi- cal burden of COVID-19 among ED HCWs and staff in order to identify areas for possible prevention and intervention, especially in a region of continuous conflict and economic uncertainties. This will be vital in planning for future outbreaks of emerging infectious diseases.

The aim of this study was to investigate the immediate psychological impact on all ED staff working in a tertiary care hospital environment in Lebanon during the COVID-19 outbreak in conjunction with an ongoing national economic crisis, as related to their household income.

1. Methods
   1. Study design and population

This study was a self-reported cross-sectional survey of all staff working at the Department of Emergency Medicine of AUBMC in Beirut, Lebanon. AUBMC is a 330-bed tertiary care center and is recognized as one of the leading medical centers in Lebanon and the Middle East North Africa region. It is internationally accredited by the Joint Commis- sion International (JCI), Magnet(R), College of American Pathologists (CAP), and the Accreditation Council for Graduate Medical Education - International (ACGME-I). The AUBMC ED consists of a 36-bed clinical area and handles a patient census of around 48,000 visits per year, of which 72% are adult patients.

The study population consisted of 149 HCWs who responded to the online survey questions via LimeSurvey between May and July 2020. HCWs included attending physicians, house staff physicians, residents, registered and practical nurses, registration personnel, and clerks work- ing in the ED. All participants consented to participate in the study. We elected to adopt a convenience sampling technique by targeting all the HCWs in the department of emergency medicine at AUBMC. The institu- tional review Board at AUB approved the conduct of this study under the IRB ID SBS-2020-0169.

• 1. Measurements and variables

The survey included basic demographic information of the partici- pants: age, gender, marital status, presence of elderly or children at home, occupation, education, years in current occupation, working

hours per week, and full-time vs. part-time. In addition, we surveyed participants for the outcome of psychological impact using the follow- ing assessment tools screening for anxiety, burnout, and depression, respectively: General Anxiety Disorder (GAD-7) questionnaire [10], Burnout Measure- Short questionnaire (BMS) [11], and Patient Health Questionnaire-9 (PHQ-9) questionnaire [12].

We used the English version of these assessment tools, as English is the primary language used at our institution. The questions of the GAD- 7 and PHQ-9 tools have four responses. “Not at all” was assigned a score of “0”, “Several days” was assigned a score of “1”, “More than half of the days” was assigned a score of “2”, and “Nearly every day” was assigned a score of “3” [10,12]. The questions of the BMS tool have seven responses. “Never” was assigned a score of “1”, “Almost never” was assigned a score of “2”, “Rarely” was assigned a score of “3”, “Sometimes” was assigned a score of “4”, “Often” was assigned a score of “5”, “Very often” was assigned a score of “6”, and “Always” was assigned a score of “7” [11]. Cut-off scores of 10 or more were used to define cases at high risk for depression by PHQ-9 [13], and generalized anxiety by GAD-7 [10], while a cut-off score of 4 was used to indicate a high level of exposure to burnout by BMS [11]. The participant’s monthly income was selected to stratify the population into two groups (<$2000 or >= $2000). The minimum monthly wage in Lebanon was around

$466 during the study period [14,15]. The 2000$ income cut-off was

selected based on the reported average wages of HCWs in Lebanon dur- ing 2020 and based on a previous study by Kassak et al. that surveyed the Lebanese physicians registered in the Lebanese Order of Physicians, showing an average salary of more than $1800 with a median around

$1300 [14,16].

• 1. Statistical analysis

All statistical analyses were performed using IBM SPSS 24(C). Charac- teristics and demographics were described and reported as mean +- standard deviation for continuous variables, and frequency and percentage for categorical variables. As applicable, Chi-Square and Fisher exact tests were used to assess the association between the cate- gorical variables and the outcome at the bivariate level. t-test was used to assess the association between the continuous variables and the out- come at the bivariate level. Linear regression was used to assess the association of the predictors with the values of the scores of the three tools (GAD-7, PHQ-9, and BMS) used in this study.

1. Results
   1. Description of the participants

Out of the 149 HCWs at the AUBMC ED, 74 (49.6%) completed the study survey. The participants’ mean age was 31.78 +- 9.49 years, and males constituted 62.16% (n = 46). 59 participants (79.73%) completed medical or postgraduate education, and 45 participants (60.81%) were single. Physicians (attending and clinical associates) constituted 18.92% (n = 14), residents and house staff constituted 29.73% (n = 22), and nurses (registered, practical, and clerks) constituted 51.35% (n = 38) of the participants. Among the participants, 35.14% (n = 26) reported having an elderly at home, and 39.19% (n = 29) reported hav- ing children at home. 60.81% (n = 45) reported having less than 5 years of professional experience, 91.98% (n = 68) had full-time Employment status, and 66.22% (n = 49) worked for at least 40 h per week. 5.41% (n = 4) of the participants reported being previously diagnosed with mental health problems and 6.76% (n = 5) previously sought mental health care (Table 1).

When comparing the characteristics of the participants according to their average monthly income (<$2000 or >=$2000), the participants’ age, occupation, and employment status were significantly different be- tween the two groups (Table 1). The participants in the higher-income group were older (37.9 +- 12.44 vs. 29.36 +- 6.77 years, p = 0.006),

Comparative characteristics of the study participants.

	Total (N = 74)	<$2000 (n = 53)	>=$2000 (n = 21) P value
Age Years	31.78 +- 9.49	29.36 +- 6.77	37.9 +- 12.44 0.006
Gender Female	28 (37.84)	20 (37.74)	8 (38.1) 1.000
Male	46 (62.16)	33 (62.26)	13 (61.9)
Education College level	15 (20.27)	13 (24.53)	2 (9.52) 0.206
Medical/Postgraduate	59 (79.73)	40 (75.47)	19 (90.48)
Marital status Single	45 (60.81)	35 (66.04)	10 (47.62) 0.189
Married	29 (39.19)	18 (33.96)	11 (52.38)
Attending Physician or Clinical associate	14 (18.92)	0 (0)	14 (66.67)
Occupation Resident/house staff	22 (29.73)	18 (33.96)	4 (19.05) <0.0001
RN/PN/Clerk	38 (51.35)	35 (66.04)	3 (14.29)
Presence of Elderly (65 years) at home Yes	26 (35.14)	17 (32.08)	9 (42.86) 0.425
Presence of Children at home Yes	29 (39.19)	20 (37.74)	9 (42.86) 0.793
Years in Current Occupation <5 year	45 (60.81)	35 (66.04)	10 (47.62) 0.189
>=5 years	29 (39.19)	18 (33.96)	11 (52.38)
Employment Status Full-time	68 (91.89)	53 (100)	15 (71.43) <0.0001
Part-time	6 (8.11)	0 (0)	6 (28.57)
working hours per week <40 h	25 (33.78)	16 (30.19)	9 (42.86) 0.414
>=40 h	49 (66.22)	37 (69.81)	12 (57.14)
History of mental health diagnosis Yes	4 (5.41)	3 (5.66)	1 (4.76) 1.000
Prior seeking any mental health care Yes	5 (6.76)	3 (5.66)	2 (9.52) 0.618

(psychiatrist/psychologist/counseling)

physicians (66.67%, p < 0.0001), and were employed full time (71.43%, p < 0.0001).

• 1. Outcomes

Upon assessing the participants’ responses to the GAD-7 tool, the higher-income group scored 2.65 points lower on the total score compared to the lower-income group (5.1 +- 2.36 vs. 7.75 +- 4.63, p = 0.002) (Table 2). Additionally, the higher-income group scored sig- nificantly lower than the lower-income group on specific questions in GAD-7 such as “Being so restless that it’s hard to sit still” (0.29 +- 0.56 vs. 0.68 +- 0.73, p = 0.016), “Becoming easily annoyed or irritable” (0.76 +- 0.54 vs. 1.19 +- 1, p = 0.021), and “Feeling afraid as if something awful might happen” (0.38 +- 0.5 vs. 1 +- 1, p = 0.009). Moreover, our data showed that 32.08% of HCWs in the lower-income group scored more than 10 points on the GAD-7 tool (moderate to severe groups) compared to 4.76% of the HCWs in the higher-income group (p = 0.015).

Upon evaluating the responses of the participants to the PHQ-9 tool, the higher-income group scored 2.5 points lower on the total score compared to the lower-income group (5.24 +- 3.7 vs. 7.74 +- 4.95, p = 0.022) (Table 3). Additionally, the higher-income group scored significantly lower than the lower-income group on specific questions in PHQ-9 such as “Trouble concentrating on things, such as reading the newspaper or watching television?” (0.33 +- 0.66 vs. 0.81 +- 0.96, p = 0.018) and “Thoughts that you would be better off dead, or thoughts of hurting yourself in some way?” (0.05 +- 0.22 vs. 0.26 +- 0.59, p = 0.025). Moreover, our data showed that 32.08% of HCWs in

the lower-income group scored more than 10 on the PHQ-9 tool (moderate to severe groups) compared to 9.52% of the HCWs in the higher-income group, though the difference was not statistically signif- icant (p = 0.074).

Upon assessing the participants’ responses to the BMS tool, the higher-income group scored 2.63 points lower on the total score com- pared to the lower-income group (32.33 +- 11.7 vs. 34.96 +- 11.95), though the difference was not statistically significant (Table 4). Addi- tionally, our data did not show any statistically significant difference in the participants’ responses to any BMS question. Importantly, our data showed that 42.86% of HCWs in the lower-income group were categorized in the burnout category compared to 49.06% of the HCWs in the higher-income group, though the difference was not statistically significant (p = 0.797).

1. Discussion

All ED HCWs at a tertiary care center in a low-resource country were surveyed to assess the direct psychological impact of COVID-19 on their wellbeing, during an unprecedented national economic crisis. The re- sults of this survey showed a negative association between HCWs’ psy- chological health and COVID-19 in relationship to the household income. The scores on the anxiety and depression scales (GAD-7 and PHQ-9) were statistically significantly higher among participants in the lower-income group working during the COVID-19 outbreak.

During the 2020 COVID-19 pandemic, Lebanon faced a tragic eco- nomic crisis that led to the devaluation of the current currency (Leba- nese pound- LBP) from 1505 LBP per dollar to a range of 3900 to 9800

Table 2

Comparative responses of the participants to the GAD-7 tool questions. The participants were asked to rate their responses to the various questions in relation to the past 2 weeks.

GAD7 questions	Total (N = 74)	<$2000 (n = 53)	>=$2000 (n = 21)	P value
Feeling nervous, anxious, or on edge	1.04 +- 0.82	1.15 +- 0.89	0.76 +- 0.54	0.065
Not being able to stop or control worrying	0.92 +- 0.84	1.02 +- 0.84	0.67 +- 0.8	0.104
Worrying too much about different things	1.36 +- 0.93	1.43 +- 0.99	1.19 +- 0.75	0.258
Trouble Relaxing	1.22 +- 0.88	1.28 +- 0.95	1.05 +- 0.67	0.234
Being so restless that it’s hard to sit still	0.57 +- 0.7	0.68 +- 0.73	0.29 +- 0.56	0.016
Becoming easily annoyed or irritable	1.07 +- 0.91	1.19 +- 1	0.76 +- 0.54	0.021
Feeling afraid as if something awful might happen	0.82 +- 0.93	1 +- 1	0.38 +- 0.5	0.009
GAD-7 score	7.00 +- 4.27	7.75 +- 4.63	5.1 +- 2.36	0.002

GAD-7 categories Mild anxiety 56 (75.68) 36 (67.92) 20 (95.24) 0.015

Moderate and sever anxiety 18 (24.3) 17 (32.1) 1 (4.8)

Comparative responses of the participants to the PHQ-9 tool questions. The participants were asked to rate their responses to the various questions in relation to the past 2 weeks.

PHQ-9 questions	Total (N = 74)	<$2000 (n = 53)	>=$2000 (n = 21)	P value
Little Interest or pleasure in doing things?	0.91 +- 0.85	1.02 +- 0.89	0.62 +- 0.67	0.067
Feeling down, depressed or hopeless?	0.85 +- 0.68	0.92 +- 0.68	0.67 +- 0.66	0.14
Trouble falling or staying asleep or sleeping too much?	1.15 +- 1.02	1.21 +- 1.06	1 +- 0.89	0.432
Feeling tired or having little energy?	1.23 +- 0.8	1.3 +- 0.85	1.05 +- 0.67	0.179
Poor appetite or overeating?	1.05 +- 0.98	1.11 +- 1.01	0.9 +- 0.89	0.412
Feeling bad about yourself — or that you are a failure or have let yourself or your family down?	0.69 +- 0.84	0.77 +- 0.89	0.48 +- 0.68	0.173
Trouble concentrating on things, such as reading the newspaper or watching television?	0.68 +- 0.91	0.81 +- 0.96	0.33 +- 0.66	0.018

Moving or speaking so slowly that other people could have noticed? Or so fidgety or restless that you have been moving a lot more than usual?

Thoughts that you would be better off dead, or thoughts of hurting yourself in some way?	0.2 +- 0.52	0.26 +- 0.59	0.05 +- 0.22	0.025
PHQ-9score	7.04 +- 4.74	7.74 +- 4.95	5.24 +- 3.7	0.022

0.27 +- 0.48 0.32 +- 0.51 0.14 +- 0.36 0.096

PHQ-9 categories Mild depression 55 (74.32) 36 (67.92) 19 (90.48) 0.074

Moderate to severe depression 19 (25.68) 17 (32.08) 2 (9.52)

LBP per dollar during the study period [5]. The majority of the workers in the Lebanese industries, including the majority of the surveyed par- ticipants, continued to receive their salaries in LBP. Therefore, the partic- ipants in this study had lost between 61.5% to 84.7% of the value of their salaries compared to USD, thus reducing their purchasing power.

The healthcare facilities in Lebanon also suffered restrictions on mobilizing their capital deposited in banks for healthcare supplies, which led to a reduced ability to purchase personal protective equip- ment essential for the safe management of COVID-19 patients. As other hospitals in Lebanon, the ED at AUBMC lacked an adequate num- ber of negative pressure rooms for the proper isolation of COVID-19 positive patients; this constituted a major burden on HCWs, who felt vulnerable and exposed while fighting COVID-19. While the financial situation had a major contribution to the above-mentioned burden on the HCWs, the rapid exponential increase in the COVID-19 positive cases had its toll on our study participants. During the study period, Lebanon was observing the first wave of COVID-19 cases. The number of the COVID-19 confirmed cases increased from 729 accumulated cases on April 30, 2020 (before the initiation of the study) to 4549 accu- mulated cases on July 31, 2020 (at the end of this study) (Fig. 1). AUBMC was among the first medical centers in the country to receive COVID-19 suspected patients to diagnose and treat. The majority of the COVID-19 suspected patients at AUBMC presented to the ED for initial workup and management. During the study period, the AUBMC ED treated 6746 pa- tients, among which 2146 (31.8%) were suspected of having COVID-19 (underwent a COVID-19 RNA PCR testing), and 55 patients (2.6%) were COVID-19 confirmed cases.

We investigated which of the participants’ characteristics could pre-

dict the scores on the utilized tools (Table 5). Using GAD-7, our data

Table 4

Comparative responses of the participants to the BMS tool questions. The participants were asked to rate their responses to the various questions in relation to the past 2 weeks.

showed that 24.32% of the HCWs displayed moderate to severe symp- toms of anxiety due to COVID-19, which is comparable to the preva- lence of COVID-19 related anxiety (23.21%) of HCWs (n = 6968) reported in a meta-analysis of 12 studies conducted in China and Singapore [17]. Our GAD-7 score linear regression results showed that the household income (? = -2.66, p = 0.015, 95% CI [-4.78, -0.54] was the only significant predictor for GAD-7 scores in our sample. Zhou et al. surveyed 606 frontline HCWs in China to assess psychologi- cal disturbances due to the COVID-19 outbreak. This study reported a trend of association between family income and anxiety symptoms in the participants, although the association did not reach statistical signif- icance (p = 0.08) [18]. Zhu et al. surveyed more than 5000 frontline HCWs in China to assess psychological disorders in response to COVID-19. Their results showed that “Living with family members” and “Have history of Mental disorders” are associated with higher odds of anxiety. Our data failed to show an association with these variables potentially due to the low number of HCWs who had elderly family members in their homes. Moreover, unlike our findings, the re- sults of Zhu et al. showed that a higher percentage of the participants in the higher-income group reported anxiety compared to those in the lower-income group [19]. While Huang et al. surveyed 2250 HCWs in China who reported a high Anxiety score that was associated with youn- ger age (<35 years of age), our data did not show an association between age and anxiety scores [20].

With respect to the PHQ-9 score, 25.68% of the HCWs in our study exhibited moderate to severe symptoms of depression due to COVID- 19, which is higher than the prevalence of depression (22.8%) of the HCWs (n = 6968) reported in a meta-analysis of 10 studies conducted in China and Singapore [17]. Additionally, Lai et al. reported that the odds of reporting depression among the 1257 surveyed HCWs in China were 52% more among the frontline HCWs than the other HCWs [21]. It is worth noting that the participants in the lower-

BMS questions	Total (N = 74)	<$2000 (n = 53)	>=$2000 (n = 21)	P value
Tired?	4.49 +- 1.45	4.53 +- 1.44	4.38 +- 1.5	0.695
Disappointed with people?	3.22 +- 1.73	3.32 +- 1.77	2.95 +- 1.63	0.413
Hopeless?	4.32 +- 1.4	4.25 +- 1.33	4.52 +- 1.57	0.443
Trapped?	3.51 +- 1.75	3.53 +- 1.65	3.48 +- 2.02	0.909
Helpless?	3.31 +- 1.9	3.45 +- 1.84	2.95 +- 2.06	0.311
Depressed?	3.35 +- 1.38	3.43 +- 1.43	3.14 +- 1.24	0.417
Physically weak/Sickly?	3.15 +- 1.7	3.25 +- 1.72	2.9 +- 1.67	0.441
Worthless/Like a failure?	2.39 +- 1.6	2.47 +- 1.62	2.19 +- 1.57	0.5
Difficulties sleeping?	3.57 +- 2.03	3.83 +- 2.08	2.9 +- 1.76	0.077
“I’ve had it”?	3.01 +- 2.02	3.06 +- 2.08	2.9 +- 1.89	0.773
BMS score	34.22 +- 11.86	34.96 +- 11.95	32.33 +- 11.7	0.394

BMS

categories

No Burnout

39 (52.7) 27 (50.94) 12 (57.14)

0.797

Fig. 1. Accumulated number of confirmed COVID-19 cases in Lebanon between May and July 2020. The data was extracted from the Lebanese Ministry of Public Health dashboard

Burnout 35 (47.3) 26 (49.06) 9 (42.86) for “Monitoring of COVID-19 infection In Lebanon” [3].

Table 5

Linear regression to assess the predictors of the scores on the psychological tools.

Variable

GAD7a

PHQ-9b

BMSc

B

p

95% CI

B

p

95% CI

B

p

95% CI

Household income

-2.66

0.015

[-4.78, -0.54]

-3.1

0.010

[-5.43, -0.76]

History of mental health diagnosis

13.82

0.008

[3.72, 23.93]

25.69

0.049

[0.09, 51.29]

Prior seeking any mental health care

-12.27

0.009

[-21.4, -3.15]

-25.69

0.030

[-48.76, -2.62]

Age

-0.25

0.079

[-0.54, 0.03]

^a Accounting for: Age, Gender, Education, Marital status, Occupation, Presence of Elderly (>= 65 years) at home, Presence of Children at home, Years in Current Occupation, Employment Status, Working hours per week, History of mental health diagnosis, and Prior seeking any mental health care (psychiatrist/psychologist/counseling).

^b Accounting for: Age, Gender, Education, Marital status, Occupation, Presence of Elderly (>= 65 years) at home, Presence of Children at home, Years in Current Occupation, Employment Status, and Working hours per week.

^c Accounting for: Gender, Education, Marital status, Occupation, Household income, Presence of Elderly (>= 65 years) at home, Presence of Children at home, Years in Current Occupation, Employment Status, and Working hours per week.

income group of this study significantly scored higher on the last item of the PHQ-9 (suicidal ideation) compared to the higher-income group. This finding warrants Timely interventions to ensure the safety of the HCWs.

Our linear regression results showed that household income (? =

-3.1, p = 0.01, 95% CI [-5.43, -0.76]), a history of mental health diag- nosis (? = 13.82, p = 0.008, 95% CI [3.72, 23.93]), and prior seeking of mental health care (? = -12.27, p = 0.009, 95% CI [-21.4, -3.15]) were significant predictors of PHQ-9 scores in our sample. The high ? of these two associations is most likely due to the low number of partic- ipants who reported any “Mental Health diagnosis” or “Seeking of men- tal health care” in our sample (5.41% and 6.76%, respectively).

Zhou et al. surveyed 606 frontline HCWs in China to assess psycho- logical disturbances due to the COVID-19 outbreak. This study reported a trend of association between family income and depressive symptoms in the participants, although the association did not reach statistical significance (p = 0.07) [18]. Zhu et al. surveyed more than 5000 front- line HCWs in China to assess psychological disorders in response to COVID-19. Their results showed that “Women” and “Have history of mental disorders” are associated with higher odds of depression. Our data failed to show an association between gender and depression scores in our population, which was in line with the findings of the Obeid et al. study assessing the depression prevalence among the Leba- nese population [22].

Nevertheless, our data showed that a history of mental health diag- nosis is associated with higher depression scores. This finding is in line with the findings of Zhu et al. [19]. However, unlike our findings, Zhu et al. showed no difference in the percentages of the participants who reported depression in the higher or lower-income groups. On the other hand, Furgusson et al. and Pine et al. longitudinally investigated a cohort of patients and reported that a diagnosis of depression in the adolescent years of a subject is associated with depression in adulthood years [23,24]. In parallel, a systematic review and meta-analysis showed that mental health illnesses are among the risk factors for developing depression [25].

Our results revealed that prior seeking of mental care is associated with a lower score of PHQ-9. This can be explained by the fact that seek- ing mental health evaluation and treatment ensures control of symp- toms and disease and lowers the scores. This is in line with a study by Schwenk et al. that assessed the responses of 1154 physicians. Participants in this study reported a delay in seeking mental care for physicians with minimal to mild depressions and their preference to self-care [26].

With respect to the BMS scores, 47.3% of our participants experi- enced burnout symptoms, which was comparable to the burnout levels of HCWs (between 44 and 45%) reported in a systematic review and meta-analysis of 15 RCTs and 37 cohort studies (3630 physicians) by West et al. but higher than the burnout levels of HCWs (40.1%) reported in a cross-sectional study by Macia-Rodriguez et al. [27,28]. The latter study pinpointed the association between burnout scores and PPE avail- ability and overtime work compensation [27]. Our linear regression

results indicated that a history of mental health diagnosis (? = 25.69, p = 0.049, 95% CI [0.09, 51.29]) and prior seeking of mental health care (? = -25.69, p = 0.03, 95% CI [-48.76, -2.62]) were significant predictors of burnout scores. Similarly, the association between mental health illness and higher burnout was discussed by Baigent and Baigent [29]. Additionally, Dobson et al. investigated the predictors of burnout among HCWs in one of the major Tertiary care centers in Melbourne, Australia. The results of their cross-sectional study showed that burnout was associated with “Past psychiatric history” of the participants [30]. As for seeking mental health care, our findings could be explained by the fact that previously seeking mental health care could help HCWs cope better with psychological stressors and subsequently lower their burnout score.

1. Limitations

Our study has some limitations. The study was a self-reported survey in a single center in Beirut, Lebanon. We elected to use this design to preserve the participants’ social distancing and avoid exposure and virus spread, especially prior to the vaccine availability. Moreover, dur- ing our study period, multiple groups in the institution were sending various surveys to the AUBMC community, which might have caused survey fatigue resulting in a low response rate. Additionally, half of the participants were nurses, which is proportional to their representa- tion in our department, and the majority of the participants were in the lower-income group which could have potentially skewed the results of our study. Finally, mental health is a culturally sensitive topic among the Lebanese population, which could have reduced the reporting rate on the various psychological scores.

1. Conclusions

While Lebanon was facing one of its most complex economic crisis, and amidst the COVID-19 pandemic, HCWs surveyed in a tertiary care center reported major psychological disturbances on multiple levels. The pandemic, faced with the additional financial burden, was a pri- mary determinant of anxiety and depression scores, but not burnout scores. Therefore, strategic planning focusing on wellness programs in addition to creating a financial safety net is essential for assisting the frontline workers in coping with the impact of this unprecedented out- break.

Funding source

Not applicable.

Credit authorship contribution statement

Moustafa Al Hariri: Data curation; Methodology; Formal analysis; Writing - original draft; Writing - review & editing. Bachar Hamade: Conceptualization; Methodology; Writing - original draft; Writing -

review & editing. Maya Bizri: Conceptualization; Methodology; Writing

- original draft; Oday Salman: Data curation; Methodology; Writing - original draft; Hani Tamim: Methodology; Formal analysis; Writing - original draft; Nour Al Jalbout: Conceptualization; Data curation; Methodology; Supervision; Writing - original draft; Writing - review & editing.

Declaration of Competing Interest

MAH, BH, MB, OS, HT and NA report no conflict of interest with the original work presented below.

Acknowledgments

Not Applicable. All contributing parties were eligible for authorship status.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi. org/10.1016/j.ajem.2021.10.055.

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