Mental health at the COVID-19 frontline: An assessment of distress, fear, and coping among staff and attendees at screening clinics of rural/regional settings of Victoria, Australia

How healthcare workers are coping with mental health challenges during COVID -19 pandemic? - A cross-sectional multi-countries study - Clinical  Epidemiology and Global Health

Abstract

Purpose

Research examining psychological well-being associated with COVID-19 in rural/regional Australia is limited. This study aimed to assess the extent of psychological distress, fear of COVID-19, and coping strategies among the attendees in COVID-19 screening clinics at 2 rural Victorian settings.

Methods

A cross-sectional study was conducted during July 2020 to February 2021 inclusive. Participants were invited to fill in an online questionnaire. Kessler Psychological Distress Scale (K-10), Fear of COVID-19 Scale, and Brief Resilient Coping Scale were used to assess psychological distress, fear of COVID-19, and coping, respectively.

Findings

Among 702 total participants, 69% were females and mean age (±SD) was 49 (±15.8) years. One in 5 participants (156, 22%) experienced high to very high psychological distress, 1 in 10 (72, 10%) experienced high fear, and more than half (397, 57%) had medium to high resilient coping. Participants with mental health issues had higher distress (AOR 10.4, 95% CI: 6.25-17.2) and fear (2.56, 1.41-4.66). Higher distress was also associated with having comorbidities, increased smoking (5.71, 1.04-31.4), and alcohol drinking (2.03, 1.21-3.40). Higher fear was associated with negative financial impact, drinking alcohol (2.15, 1.06-4.37), and increased alcohol drinking. Medium to high resilient coping was associated with being ≥60 years old (1.84, 1.04-3.24) and completing Bachelor and above levels of education.

Conclusion

People who had pre-existing mental health issues, comorbidities, smoked, and consumed alcohol were identified as high-risk groups for poorer psychological well-being in rural/regional Victoria. Specific interventions to support the mental well-being of these vulnerable populations, along with engaging health care providers, should be considered.

INTRODUCTION

The first case of confirmed COVID-19 was detected in Victoria, Australia, on January 25, 2020,1 and then subsequently found in other Australian states among returned travelers. The international borders were closed to all noncitizens and nonresidents in March 2020 to reduce the number of infections coming in from overseas.2 However, as local transmission increased, a number of measures were put in place to reduce opportunities for infection. Those measures included increased access to COVID-19 screening, social distancing, working from home, restriction of visitors to home gatherings, closure of educational facilities (schools, TAFE, and universities), introduction of remote learning, and restrictions to visitors to health services and aged care residences.3 At that stage, the wearing of face masks was not compulsory. In June 2020, a second wave of infections affected Victoria, spreading rapidly, with a peak of 687 infections/cases being reported in 1 day. Another period of lockdown was commenced and mandatory mask wearing was introduced, along with nightly curfews and the restriction of movement to a 5 km radius, which remained until November 22, 2020. While COVID transmission in regional Victoria occurred at lower levels than in Melbourne and some restrictions were lifted earlier, there were several outbreaks and cases (n = 610) in the Barwon South West region of Victoria. Those outbreaks mostly occurred around workplaces, such as abattoirs and aged care, and were linked to the movement of people from infected metropolitan to regional areas.4

Rural or regional areas are resource-stretched with specialists, doctors, nurses, and mental health worker shortages commonplace.5 Globally, there have been examples where regional villages have managed to reduce COVID-19 spread by proactively undertaking community screenings, enforcing social isolation, communicating actively with their communities, and reducing contagion through restrictions.6 In response to the COVID-19 outbreak in Victoria, some regional health services focused their services to prepare and manage potential outbreaks and concentrate heavily on prevention, detection, screening, community communication, and clinical management of suspected cases. That involved redeployment of staff to areas, such as drive-through screening clinics and respiratory assessment clinics (RACs), which included the likely contact with active COVID-19 cases. Such modified service delivery from hospital settings, along with the ongoing fear of coronavirus spread in communities, might increase stress levels for patients with health conditions that put them at higher risk for COVID-19.

Australian government pandemic restrictions have resulted in social, economic, and health consequences, affecting both health-seeking behaviors of Australians and the manner of interactions with health care workers.7, 8 A recent report in The Lancet highlighted the adverse effects of the pandemic, both on people with diagnosed mental illness and the general population’s mental health being exacerbated by fear, self-isolation, and stigma.9 In response to the growing global pandemic and potential COVID-19 spread across Victoria, COVID-19 screening clinics were established at Hamilton Base Hospital (300 km west of Melbourne) and South West Health Care, 256 km south west of Melbourne, to enable community members with respiratory symptoms or concerns of contact to be swabbed.10, 11 Both Hamilton and South West Health Care catchments extend to the South Australian border with some of the region’s working population commuting or transporting goods and livestock into South Australia.

Frontline health care workers were redeployed and rostered to assess attendees clinically and collect swabs if they met the latest and ever-changing testing criteria. Attendees were then instructed to self-isolate at home until the results were returned, usually within 48 hours; however, initially this was up to 168 hours (7 days).11 Pathology swabs had to be sent to Melbourne (300 km away) for analysis and then returned to the health service, resulting in delays of return of results to attendees.

Frontline health care workers reported stress due to the risk of transmission from confirmed, suspected, or asymptomatic cases, working with new and frequently shifting testing criteria, and the continual wearing of personal protective equipment (PPE).12, 13 Health care workers also reported anxiousness when returning home and possibly exposing their families to the risk of COVID-19. Higher rates of infection were reported among health care workers globally, particularly in staff undertaking testing.14

Focusing on the psychological impact of current and future outbreaks was important, as evidence from previous epidemics suggests that not only short-term but also long-term impacts could occur.15, 16 Improving our approach to community screening, whether through drive-through or community clinics, was important for both the current COVID-19 pandemic and for future operation. In this study, we aimed to assess the extent of psychological distress, fear of COVID-19, and coping strategies among attendees at 2 COVID119 screening clinics in regional/rural Victoria, Australia.

MATERIALS AND METHODS

Study design and settings

This was a cross-sectional study. Two COVID-19 clinics, one a drive-through and the other an RAC, were selected as study sites. Those sites are approximately 100 km apart by road with one based in a predominantly agricultural setting and the other with a larger population, in manufacturing, agriculture, meatworks, and tourism. Both sites are more than 250 km away from metropolitan Melbourne. The study was conducted during January to February 2021 and included clinic attendees from July 2020 to February 2021 inclusive.

Study population

Participants, ≥18 years of age, capable of responding to an online questionnaire in English, and residing in rural/regional settings of Western Victoria, were invited to participate. The study participants included patients (attendees), who presented at the study screening sites, irrespective of test results for COVID-19 from July 2020 to February 2021. Participants who partially completed the questionnaire were excluded. In addition, participants who took <1 minute to complete the survey were excluded from the analyses to avoid information bias.

Sampling

All participants fulfilling the inclusion criteria were invited to participate. Sample size was calculated using OpenEpi. Considering a total population of 120,718 (covering the study hospital’s catchment areas of Warrnambool and the South-West region),17 assuming 50% prevalence of stress among Australians, 95% confidence intervals (CIs), and 80% power, the estimated minimum sample size was 383 at each site. Therefore, we aimed for a total of 766 participants as our total sample size.

Data collection

The 2 selected COVID-19 screening clinics operated independently of each other by the respective health services. Nevertheless, the services operated in a similar manner. Attendees who presented at the clinics for screening were treated as “patients” and their personal contact details were recorded by a health care worker during the screening process. Attendee details, including phone numbers, were saved and stored in the TrakCare® Electronic Medical Record System (InterSystems Corp, Cambridge, MA) at the relevant health service. Health information teams at both study sites extracted the mobile phone numbers securely from TrakCare®, which generated a list of deidentified mobile numbers (no names or other information) that was passed on securely to the research team.

An SMS was sent to all extracted mobile phone numbers with a short message inviting them to participate in the study. Invitations to complete the survey were generic, not specifically addressed to any individual, and were sent from Western District Health Service. The SMS included a QR code and the link to the online survey. Since the screening clinics were operating during the data collection period, eligible attendees at both clinics were also invited to participate with the study information included on the screening clinics handout. If anyone was interested in participating in the study, they were advised to hold their mobile phone over the QR code, which directed them to the survey on their phones immediately. The online survey was also advertised on flyers posted at the screening clinics.

The web-based survey was developed using the Qualtrics (Provo, UT) surveying platform by Federation University Australia. The first screen contained a Plain Language Information Statement (PLIS) and Consent Form. Only the participants who provided consent and agreed to participate in the study could move to the next screen containing the self-administered survey.

Study tool

A structured survey based on previously published studies by the first author (MAR) was used and adapted for this cohort.18, 19 Following the initial screening questions to confirm eligibility, the survey included questions on sociodemographics, self-reported comorbidities, behavioral risk factors, exposure and contact history of COVID-19, psychological distress (Kessler K-10),20 fear of COVID-19 (FCV-19S),21 and coping strategies (Brief Resilient Coping Scale – BRCS).22 Access to mental health resources and specific support pertaining to COVID-19 from the Victorian Department of Health and Human Services was also provided. Psychometric properties of the English version of those 3 tools were examined recently during the COVID-19 pandemic period, which demonstrated significant reliability for use among migrants and nonmigrants in Australia.23

Data analyses

Data were analyzed using SPSS v.25 (IBM Corp., Armonk, NY) and STATA v.12 (StataCorp LLC, College Station, TX). At first, study variables were analyzed for descriptive information. In addition to calculating proportions for categorical variables, mean and standard deviations were calculated for continuous variables. Based on the scoring from the K-10 scale, we categorized participants into low to moderate (score 10-21) and high to very high (score 22-50) psychological distress. BRCS scores were categorized into low (score 4-13) and medium to high (score 14-20) for resilient coping. Chi-square tests were used to compare responses according to age groups, gender, exposure history, comorbidities, and so on, for each study outcome (psychological distress, fear of COVID-19, and coping). We determined association through the P value of < .05 and strength of association was determined by binary logistic regression, which provided odds ratio (OR) and 95% CI. We considered sociodemographic variables (age, gender, living status, born in Australia, education, and employment) as potential confounders, which were adjusted during multivariate analyses, and we reported adjusted OR (AOR) with 95% CI.

Ethics

We obtained approval from the Human Research Ethics Committee at both Federation University Australia and South West Healthcare. All the responses were anonymous; therefore, no information which could identify any individual was collected. The PLIS included contact information for BeyondBlue, Lifeline, and Victorian government mental health resources on COVID-19.

RESULTS

A total of 10,599 people, who went through screening at both sites during the study period and had their mobile numbers listed, received the invitations to participate in this study. Among them, a total of 702 people (7%) participated. About two-thirds of the participants (452, 64%) had their tests undertaken at South West Healthcare at Warrnambool and the remainder (250, 36%) at Western District Health Service in Hamilton.

Mean age (±SD) of the participants was 49 (±15.8) years and the majority (386, 55%) were aged between 30 and 59 years. More than two-thirds were female (481, 69%), the majority (615, 88%) were born in Australia, and 302 participants (43%) identified themselves as frontline or essential service workers (such as health care workers, police, supermarket workers, ambulance, farmer, veterinarian, child protection, meat factory workers, taxi driver, petrol station attendants, teacher, and kerbside collection worker). About two-thirds (456, 65%) reported that COVID-19 did not have any impact on their financial situation and 16 participants (2%) reported losing their job due to the COVID-19 pandemic. A quarter of attendees (178, 25%) reported having multiple comorbidities and 121 (17%) reported having psychiatric/mental health issues. A quarter of the participants (175, 25%) reported smoking occasionally and 51 (7%) smoked at least monthly. Since July 2020, 46% (n = 19) of those who reported smoking daily (n = 41) increased smoking. More than two-thirds (486, 69%) reported current alcohol drinking, 21% (n = 101) reported consuming stronger alcohol, and 20% (n = 97) reported increased alcohol drinking since July 2020. Study participants had an average of 2 tests, 289 (41%) participants reported more than 1 test, and only 7 participants (1%) reported positive test results for COVID-19 (Table 1).

TABLE 1. Characteristics of the study population
Characteristics Total, n (%)
Total study participants 702
Age (in years) 702
Mean (±SD) 49 (15.8)
Range 18-87
Age groups 702
18-29 years 102 (14.5)
30-59 years 386 (55.0)
≥60 years 214 (30.5)
Gender 702
Male 215 (30.6)
Female 481 (68.5)
Others 1 (0.1)
Prefer not to say 5 (0.7)
Born in Australia 702
Yes 615 (87.6)
No 87 (12.4)
Living status 702
Live alone 108 (15.4)
Live with family members (partner and/or children) 518 (73.9)
Live with others (shared accommodation/others) 75 (10.7)
Completed level of education 700
Grade 1-12 144 (20.6)
Trade/Certificate/Diploma 228 (32.6)
Bachelor and above 328 (46.9)
Self-identification as a frontline or essential service worker 702
Yes 302 (43.0)
No 400 (57.0)
COVID-19 impacted financial situation 701
No impact 456 (65.0)
Positively 90 (12.8)
Negatively 155 (22.1)
Number of comorbidities 697
No 376 (53.9)
Single comorbidity 143 (20.5)
Multiple comorbidities 178 (25.4)
Specific comorbidities 697
No 376 (53.9)
Psychiatric/mental health issues 121 (17.4)
Other comorbiditiesa 200 (28.7)
Smoking 702
Never smokers 14 (2.0)
Ex-smokers 462 (65.8)
Current smokers (daily/weekly/monthly/occasionally) 226 (32.2)
Increased smoking since July 2020 (among daily smokers) 51
Yes 19 (37.3)
No 32 (62.7)
Current alcohol drinking 700
Yes 486 (69.4)
No 214 (30.6)
Frequency of alcohol drinking 486
Everyday 38 (7.8)
More than 5 times a week 43 (8.8)
2-4 times a week 154 (31.7)
Once a week 67 (13.8)
Only on weekends 65 (13.4)
On special occasions 119 (24.5)
Stronger alcohol drinking 486
Yes 101 (20.8)
No 385 (79.2)
Increased alcohol drinking since July 2020 486
Yes 97 (20.0)
No 389 (80.0)
Provided care to a family member/patient with known/suspected case of COVID-19 702
Yes 59 (8.4)
No 643 (91.6)
Identification as a patient/health care service use since July 2020 702
Yes 284 (40.5)
No 418 (59.5)
Health care service use to overcome COVID-19-related stress since July 2020 702
Yes 47 (6.7)
No 655 (93.3)
Test sites 702
Hamilton Base Hospital, Drive through 236 (33.6)
Hamilton Base Hospital, Accident and Emergency 14 (2.0)
South West Healthcare, Respiratory Clinic 93 (13.2)
South West Healthcare, Drive/Walk through 359 (51.1)
Number of tests done 539
Mean (±SD) 2 (1.3)
Mode 1
Range 0-10
  • a(Stroke/hypertension/hyperlipidemia/diabetes/cancer/chronic respiratory illness).

Psychological distress

The mean score (±SD) for psychological distress on the K10 tool was 17 (±7), with 1 in 5 participants (156, 22%) experiencing high to very high levels of psychological distress (score 22-50) in the previous 4 weeks (Table 2). High to very high psychological distress was associated with those who had a single comorbidity (AOR 3.70, 95% CI: 2.25-6.08) or multiple comorbidities (AOR 5.74, 95% CI: 3.38-9.74), who had psychiatric/mental health issues (AOR 10.4, 95% CI: 6.25-17.2) or other comorbidities (AOR 1.84, 95% CI: 1.08-3.14), daily smokers who had increased their smoking (AOR 5.71, 95% CI: 1.04-31.4), and those who increased alcohol drinking (AOR 2.03, 95% CI: 1.21-3.40) since July 2020, who identified themselves as patients/visited health care services since July 2020 (AOR 1.91, 95% CI: 1.30-2.79), who had higher levels of fear of COVID-19 (AOR 3.26, 95% CI: 1.93-5.53), and who used health care service to overcome COVID-19-related stress since July 2020 (AOR 4.79, 95% CI: 2.56-8.99). On the other hand, low to moderate psychological distress was associated with being >30 years old (Table 3).

TABLE 2. Level of psychological distress among the study participants
Anxiety and Depression Checklist (K10) (last 4 weeks) Total, n (%)
About how often did you feel tired out for no good reason? 702
None 213 (30.3)
A little 184 (26.2)
Sometime 209 (29.8)
Most of the time 72 (10.3)
All the time 24 (3.4)
About how often did you feel nervous? 702
None 266 (37.9)
A little 208 (29.6)
Sometime 179 (25.5)
Most of the time 43 (6.1)
All the time 6 (0.9)
About how often did you feel so nervous that nothing could calm you down? 702
None 532 (75.8)
A little 113 (16.1)
Sometime 48 (6.8)
Most of the time 6 (0.9)
All the time 3 (0.4)
About how often did you feel hopeless? 702
None 472 (67.2)
A little 127 (18.1)
Sometime 74 (10.5)
Most of the time 24 (3.4)
All the time 5 (0.7)
About how often did you feel restless or fidgety? 702
None 331 (47.2)
A little 200 (28.5)
Sometime 122 (17.4)
Most of the time 38 (5.4)
All the time 11 (1.6)
About how often did you feel so restless you could not sit still? 702
None 483 (68.8)
A little 149 (21.2)
Sometime 57 (8.1)
Most of the time 9 (1.3)
All the time 4 (0.6)
About how often did you feel so depressed? 702
None 381 (54.3)
A little 184 (26.2)
Sometime 94 (13.4)
Most of the time 37 (5.3)
All the time 6 (0.9)
About how often did you feel that everything was an effort? 702
None 275 (39.2)
A little 248 (35.3)
Sometime 100 (14.2)
Most of the time 62 (8.8)
All the time 17 (2.4)
About how often did you feel so sad that nothing could cheer you up? 702
None 502 (71.5)
A little 126 (17.9)
Sometime 55 (7.8)
Most of the time 17 (2.4)
All the time 2 (0.3)
About how often did you feel worthless? 702
None 498 (70.9)
A little 113 (16.1)
Sometime 60 (8.5)
Most of the time 24 (3.4)
All the time 7 (1.0)
K10 score (total) 702
Mean (±SD) 17.1 (7.1)
Range 10-46
Level of psychological distress (K10 categories) 702
Low (score 10-15) 366 (52.1)
Moderate (score 16-21) 180 (25.6)
High (score 22-29) 100 (14.2)
Very high (score 30-50) 56 (8.0)
TABLE 3. Factors associated with psychological distress among the study population (based on K10 score)
High to very high (score 22+), n (%) Low to moderate (score 10-21), n (%) Unadjusted analyses Adjusted analyses
Characteristics P OR 95% CIs P AOR 95% CIs
Total study participants 156 546
Age groups 156 546
18-29 years 41 (26.3) 61 (11.2) 1 1
30-59 years 81 (51.9) 305 (55.9) .000 0.40 0.25-0.63 .018 0.51 0.30-0.89
≥60 years 34 (21.8) 180 (33.0) .000 0.28 0.16-0.48 .001 0.33 0.17-0.62
Gender 153 543
Male 38 (24.8) 177 (32.6) 1 1
Female 115 (75.2) 366 (67.4) .067 1.46 0.97-2.20 .445 1.18 0.77-1.82
Living status 155 546
Live alone 32 (20.6) 76 (13.9) .042 1.61 1.01-2.54 .794 1.10 0.54-2.25
Live with family members (partner and/or children) 95 (61.3) 423 (77.5) .000 0.46 0.31-0.67 .109 0.60 0.32-1.12
Live with others (shared accommodation/others) 28 (18.1) 47 (8.6) .001 2.34 1.41-3.89 NA NA NA
Born in Australia 156 546
No 18 (11.5) 69 (12.6) 1 1
Yes 138 (88.5) 477 (87.4) .713 1.11 0.64-1.93 .621 1.16 0.65-2.08
Completed level of education 155 545    
Grade 1-12 32 (20.6) 112 (20.6) 1 1
Trade/Certificate/Diploma 50 (32.3) 178 (32.7) .947 0.98 0.59-1.63 .879 1.04 0.61-1.77
Bachelor and above 73 (47.1) 255 (46.8) .993 1.00 0.63-1.61 .828 1.06 0.64-1.75
Self-identification as a frontline or essential service worker 156 546
No 87 (55.8) 313 (57.3) 1 1
Yes 69 (44.2) 233 (42.7) .729 1.07 0.74-1.52 .807 0.95 0.64-1.41
COVID-19 impacted financial situation 155 546
No 77 (49.7) 379 (69.4) 1 1
Positively 26 (16.8) 64 (11.7) .009 2.00 1.19-3.35 .015 1.96 1.14-3.37
Negatively 52 (33.5) 103 (18.9) .000 2.48 1.64-3.76 .000 2.49 1.62-3.84
Comorbidities 154 543
No 50 (32.5) 326 (60.0) 1 1
Single comorbidity 47 (30.5) 96 (17.7) .000 3.19 2.02-5.05 .000 3.70 2.25-6.08
Multiple comorbidities 57 (37.0) 121 (22.3) .000 3.07 2.00-4.74 .000 5.74 3.38-9.74
Comorbidities 154 543
No 50 (32.5) 326 (60.0) 1 1
Psychiatric/mental health issues 71 (46.1) 50 (9.2) .000 9.26 5.79-14.8 .000 10.4 6.25-17.2
Other comorbiditiesa 33 (21.4) 167 (30.8) .298 1.29 0.80-2.08 .025 1.84 1.08-3.14
Smoking 156 546
Never smoker 3 (1.9) 11 (2.0) 1 1
Ever smoker (daily/nondaily/ex) 153 (98.1) 535 (98.0) .942 1.05 0.29-3.81 .506 1.68 0.41-6.03
Increased smoking since July 2020 (among daily smokers) 19 32
No 7 (36.8) 25 (78.1) 1 1
Yes 12 (63.2) 7 (21.9) .005 6.12 1.75-21.4 .045 5.71 1.04-31.4
Current alcohol drinking 156 544
No 52 (33.3) 162 (29.8) 1 1
Yes 104 (66.7) 382 (70.2) .396 0.85 0.60-1.24 .611 0.90 0.60-1.35
Stronger alcohol drinking since July 2020 104 382
No 72 (69.2) 313 (81.9) 1 1
Yes 32 (30.8) 69 (18.1) .005 2.02 1.23-3.30 .213 1.41 0.82-2.41
Increased occasions of alcohol drinking since July 2020 104 382
No 70 (67.3) 319 (83.5) 1 1
Yes 34 (32.7) 63 (16.5) .000 2.46 1.51-4.02 .008 2.03 1.21-3.40
Provided care to a family member/patient with known/suspected case of COVID-19 156 546
No 139 (89.1) 504 (92.3) 1 1
Yes 17 (10.9) 42 (7.7) .205 1.47 0.81-2.66 .404 1.31 0.69-2.50
Identification as a patient/health care service use since July 2020 156 546
No 75 (48.1) 343 (62.8) 1 1
Yes 81 (51.9) 203 (37.2) .001 1.82 1.27-2.61 .001 1.91 1.30-2.79
Level of fear of COVID-19 (FCV-19S categories) 156 546
Low (score 7-21) 125 (80.1) 505 (92.5) 1 1
High (score 22-35) 31 (19.9) 41 (7.5) .000 3.05 1.84-5.07 .000 3.26 1.93-5.53
Level of coping (BRCS categories) 156 546
Low resilient copers (score 4-13) 76 (48.7) 229 (41.9) 1 1
Medium to high resilient copers (score 14-20) 80 (51.3) 317 (58.1) .133 0.76 0.53-1.09 .215 0.79 0.54-1.45
Health care service use to overcome COVID-19-related stress since July 2020 156 546
No 130 (83.3) 525 (96.2) 1 1
Yes 26 (16.7) 21 (3.8) .000 5.00 2.73-9.17 .000 4.79 2.56-8.99
  • Note: Adjusted for: age, gender, living status, born in Australia, and education.
  • a Cardiac disases/stroke/hypertension/hyperlipidemia/diabetes/cancer/chronic respiratory illness.

Levels of fear

The mean score (±SD) on the FCV-19S tool was 15 (±5) and 1 in 10 participants (72, 10%) had high levels of fear of COVID-19 (score 22-35) (Table 4). Higher levels of fear were associated with those whose financial situation was impacted negatively (AOR 2.83, 95% CI: 1.62-4.97), who had psychiatric/mental health issues (AOR 2.56, 95% CI: 1.41-4.66), who drank stronger alcoholic beverages (AOR 2.15, 95% CI: 1.06-4.37), who increased alcohol drinking since July 2020 (AOR 2.75, 95% CI: 1.40-5.37), who had high to very high psychological distress (AOR 3.24, 95% CI: 1.91-5.51), and who used a health care service to overcome COVID-19-related stress since July 2020 (AOR 2.94, 95% CI: 1.39-6.22) (Table 5).

TABLE 4. Level of fear of COVID-19 among the study participants
Fear of COVID-19 Scale (FCV-19S) individual items Total, n (%)
I am most afraid of COVID-19 702
Strongly disagree 82 (11.7)
Somewhat disagree 165 (23.5)
Neither agree nor disagree 229 (32.6)
Somewhat agree 197 (28.1)
Strongly agree 29 (4.1)
It makes me uncomfortable to think about COVID-19 702
Strongly disagree 110 (15.7)
Somewhat disagree 221 (31.5)
Neither agree nor disagree 224 (31.9)
Somewhat agree 135 (19.2)
Strongly agree 12 (1.7)
My hands become clammy when I think about COVID-19 702
Strongly disagree 384 (54.7)
Somewhat disagree 239 (34.0)
Neither agree nor disagree 71 (10.1)
Somewhat agree 6 (0.9)
Strongly agree 2 (0.3)
I am afraid of losing my life because of COVID-19 702
Strongly disagree 227 (32.3)
Somewhat disagree 218 (31.1)
Neither agree nor disagree 136 (19.4)
Somewhat agree 113 (16.1)
Strongly agree 8 (1.1)
When watching news and stories about COVID-19 on social media, I become nervous or anxious 702
Strongly disagree 152 (21.7)
Somewhat disagree 175 (24.9)
Neither agree nor disagree 189 (26.9)
Somewhat agree 167 (23.8)
Strongly agree 19 (2.7)
I cannot sleep because I’m worrying about getting COVID-19 702
Strongly disagree 389 (55.4)
Somewhat disagree 235 (33.5)
Neither agree nor disagree 69 (9.8)
Somewhat agree 8 (1.1)
Strongly agree 1 (1.1)
My heart races or palpitates when I think about getting COVID-19 702
Strongly disagree 363 (51.7)
Somewhat disagree 235 (33.5)
Neither agree nor disagree 79 (11.3)
Somewhat agree 24 (3.4)
Strongly agree 1 (0.1)
FCV-19S score (total) 702
Mean (±SD) 15.2 (4.8)
Range 7-29
Level of fear of COVID-19 (FCV-19S categories) 702
Low (score 7-21) 630 (89.7)
High (score 22-35) 72 (10.3)
TABLE 5. Factors associated with levels of fear of COVID-19 among the study population (based on FCV-19S score)
High (score 22-35), n (%) Low (score 7-21), n (%) Unadjusted analyses Adjusted analyses
Characteristics P OR 95% CIs P AOR 95% CIs
Total study participants 72 630
Age groups 72 630
18-29 years 11 (15.3) 91 (14.4) 1 1
30-59 years 39 (54.2) 347 (55.1) .840 0.93 0.46-1.89 .888 1.06 0.46-2.44
≥60 years 22 (30.6) 192 (30.5) .891 0.95 0.44-2.04 .960 1.02 0.42-2.50
Gender 72 624
Male 17 (23.6) 198 (31.7) 1 1
Female 55 (76.4) 426 (68.3) .160 1.50 0.85-2.66 .121 1.59 0.88-2.87
Living status 72 630
Live alone 14 (19.5) 94 (14.9) .318 1.37 0.74-2.56 .576 1.35 0.48-3.81
Live with family members (partner and/or children) 50 (69.4) 468 (74.4) .365 0.78 0.46-1.33 .963 0.98 0.38-2.49
Live with others (shared accommodation/others) 8 (11.1) 67 (10.7) .905 1.05 0.48-2.28 NA NA NA
Born in Australia 72 630
No 10 (13.9) 77 (12.2) 1 1
Yes 62 (86.1) 553 (87.8) .685 0.86 0.42-1.75 .307 0.68 0.32-1.43
Completed level of education 72 628
Grade 1-12 18 (25.0) 126 (20.1) 1 1
Trade/Certificate/Diploma 29 (40.3) 199 (31.7) .951 1.02 0.54-1.91 .934 1.03 0.54-1.96
Bachelor and above 25 (34.7) 303 (48.2) .093 0.58 0.30-1.10 .059 0.52 0.27-1.02
Self-identification as a frontline or essential service worker 72 630
No 41 (56.9) 359 (57.0) 1 1
Yes 31 (43.1) 271 (43.0) .995 1.00 0.61-1.64 .821 1.06 0.63-1.80
COVID-19 impacted financial situation 72 629
No 32 (44.4) 424 (67.4) 1 1
Positively 13 (18.1) 77 (12.2) .022 2.24 1.12-4.45 .026 2.23 1.10-4.52
Negatively 27 (37.5) 128 (20.3) .000 2.79 1.61-4.84 .000 2.83 1.62-4.97
Comorbidities 72 625
No 31 (43.1) 345 (55.2) 1 1
Single comorbidity 17 (23.6) 126 (20.2) .203 1.50 0.80-2.81 .206 1.51 0.80-2.85
Multiple comorbidities 24 (33.3) 154 (24.6) .056 1.73 0.99-3.05 .060 1.80 0.98-3.34
Comorbidities 72 625
No 31 (43.1) 345 (55.2)   1   1
Psychiatric/mental health issues 23 (31.9) 98 (15.7) .001 2.61 1.46-4.68 .002 2.56 1.41-4.66
Other comorbiditiesa 18 (25.0) 182 (29.1) .757 1.10 0.60-2.02 .838 1.07 0.56-2.04
Smoking 72 630
Never smoker 0 (0) 14 (2.2) 1 1
Ever smoker (daily/nondaily/ex) 72 (100) 616 (97.8) NA NA NA NA NA NA
Increased smoking since July 2020 (among daily smokers) 10 41
No 6 (60.0) 26 (63.4) 1 1
Yes 4 (40.0) 15 (36.6) .841 1.16 0.28-4.76 .483 1.78 0.35-8.97
Current alcohol drinking 72 628
No 25 (34.7) 189 (30.1) 1 1
Yes 47 (65.3) 439 (69.9) .420 0.81 0.48-1.35 .665 0.89 0.53-1.51
Stronger alcohol drinking 47 439
No 31 (66.0) 354 (80.6)   1   1
Yes 16 (34.0) 85 (19.4) .021 2.15 1.12-4.11 .034 2.15 1.06-4.37
Increased alcohol drinking since July 2020 47 439
No 29 (61.7) 360 (82.0)   1   1
Yes 18 (38.3) 79 (18.0) .001 2.83 1.50-5.35 .003 2.75 1.40-5.37
Provided care to a family member/patient with known/suspected case of COVID-19 72 630
No 65 (90.3) 578 (91.7) 1 1
Yes 7 (9.7) 52 (8.3) .671 1.20 0.52-2.74 .281 1.62 0.67-3.90
Identification as a patient/health care service use since July 2020 72 630
No 43 (59.7) 375 (59.5) 1 1
Yes 29 (40.3) 255 (40.5) .974 0.99 0.60-1.63 .954 1.02 0.61-1.69
Level of psychological distress (K10 categories) 72 630
Low to moderate (score 10-21) 41 (56.9) 505 (80.2) 1 1
High to very high (score 22+) 31 (43.1) 125 (19.8) .000 3.05 1.84-5.07 .000 3.24 1.91-5.51
Level of coping (BRCS categories) 72 630
Low resilient copers (score 4-13) 33 (45.8) 272 (43.2) 1 1
Medium to high resilient copers (score 14-20) 39 (54.2) 358 (56.8) .666 0.90 0.55-1.47 .839 0.95 0.57-1.57
Health care service use to overcome COVID-19-related stress since July 2020 72 630
No 61 (84.7) 594 (94.3) 1 1
Yes 11 (15.3) 36 (5.7) .003 2.98 1.44-6.14 .005 2.94 1.39-6.22
  • Note: Adjusted for: age, gender, living status, born in Australia, and education.
  • a Cardiac disases/stroke/hypertension/hyperlipidemia/diabetes/cancer/chronic respiratory illness.
  • The bold itlaic values indicate ‘statistical significance’.

Coping strategies

The mean score (±SD) on the BRCS tool was 14 (±3) and more than half of the participants (397, 57%) were medium to high resilient copers (score 14-20) (Table 6). Medium to high resilient coping was associated with being ≥60 years old (AOR 1.84, 95% CI: 1.04-3.24) and those who completed Bachelor or above level of education (AOR 2.20, 95% CI: 1.45-3.34). Conversely, low resilient coping was associated with having multiple comorbidities, having psychiatric/mental health issues, providing care to a family member/patient with a known/suspected case of COVID-19, and using health care services to overcome COVID-19-related stress since July 2020 (Table 7).

TABLE 6. Coping during COVID-19 pandemic among the study participants
Brief Resilient Coping Scale (BRCS) individual items Total, n (%)
I look for creative ways to alter difficult situations 702
Does not describe me at all 50 (7.1)
Does not describe me 90 (12.8)
Neutral 252 (35.9)
Describes me 243 (34.6)
Describes me very well 67 (9.5)
Regardless of what happens to me, I believe I can control my reaction to it 702
Does not describe me at all 18 (2.6)
Does not describe me 73 (10.4)
Neutral 237 (33.8)
Describes me 294 (41.9)
Describes me very well 80 (11.4)
I believe I can grow in positive ways by dealing with difficult situations 702
Does not describe me at all 8 (1.1)
Does not describe me 30 (4.3)
Neutral 188 (26.8)
Describes me 379 (54.0)
Describes me very well 97 (13.8)
I actively look for ways to replace the losses I encounter in life 702
Does not describe me at all 19 (2.7)
Does not describe me 73 (10.4)
Neutral 293 (41.7)
Describes me 262 (37.3)
Describes me very well 55 (7.8)
BRCS score (total) 702
Mean (±SD) 13.9 (2.7)
Range 4-20
Level of coping (BRCS categories) 702
Low resilient copers (score 4-13) 305 (43.4)
Medium resilient copers (score 14-16) 299 (42.6)
High resilient copers (score 17-20) 98 (14.0)
  • The bold itlaic values indicate ‘statistical significance’.
TABLE 7. Factors associated with levels of coping among the study population (based on BRCS score)
Medium to high resilient copers (score 14-20), n (%) Low resilient copers (score 4-13), n (%) Unadjusted analyses Adjusted analyses
Characteristics P OR 95% CIs P AOR 95% CIs
Total study participants 397 305
Age groups 397 305
18-29 years 54 (13.6) 48 (15.7) 1 1
30-59 years 208 (52.4) 178 (58.4) .865 1.04 0.67-1.61 .936 1.02 0.61-1.72
≥60 years 135 (34.0) 79 (25.9) .086 1.52 0.94-2.45 .035 1.84 1.04-3.24
Gender 393 303
Male 111 (28.2) 104 (34.3) 1 1
Female 282 (71.8) 199 (65.7) .086 1.33 0.96-1.83 .049 1.41 1.00-1.99
Living status 397 305
Live alone 60 (15.1) 48 (15.8) .806 0.95 0.63-1.43 .632 0.85 0.43-1.67
Live with family members (partner and/or children) 297 (74.8) 221 (72.7) .528 1.12 0.79-1.57 .943 1.02 0.57-1.84
Live with others (shared accommodation/others) 40 (10.1) 35 (11.5) .542 0.86 0.073 NA NA NA
Born in Australia 397 305
No 57 (14.4) 30 (9.8) 1 1
Yes 340 (85.6) 275 (90.2) .073 0.65 0.41-1.04 .191 0.72 0.44-1.18
Completed level of education 397 303
Grade 1-12 66 (16.6) 78 (25.7) 1 1
Trade/Certificate/Diploma 122 (30.7) 106 (35.0) .150 1.36 0.90-2.07 .115 1.42 0.92-2.18
Bachelor and above 209 (52.6) 119 (39.3) .000 2.08 1.39-3.09 .000 2.20 1.45-3.34
Self-identification as a frontline or essential service worker 397 305
No 222 (55.9) 178 (58.4) 1 1
Yes 175 (44.1) 127 (41.6) .517 1.1 0.82-1.49 .324 1.18 0.85-1.64
COVID-19 impacted financial situation 397 304
No 262 (66.0) 194 (63.8) 1 1
Positively 52 (13.1) 38 (12.5) .955 1.01 0.64-1.60 .801 1.06 0.66-1.72
Negatively 83 (20.9) 72 (23.7) .397 0.85 0.59-1.23 .555 0.89 0.61-1.30
Comorbidities 393 304
No 222 (56.5) 154 (50.7) 1 1
Single comorbidity 80 (20.4) 63 (20.7) .523 0.88 0.60-1.30 .593 0.90 0.60-1.34
Multiple comorbidities 91 (23.2) 87 (28.6) .080 0.73 0.51-1.04 .017 0.61 0.41-0.92
Comorbidities 393 304
No 222 (56.5) 154 (50.7) 1 1
Psychiatric/mental health issues 56 (14.2) 65 (21.4) .014 0.60 0.40-0.90 .012 0.57 0.37-0.88
Other comorbiditiesa 115 (29.3) 85 (28.0) .721 0.94 0.66-1.33 .548 0.89 0.61-1.30
Smoking 397 305
Never smoker 7 (1.8) 7 (2.3) 1 1
Ever smoker (daily/nondaily/ex) 390 (98.2) 298 (97.7) .618 1.31 0.45-3.77 .919 1.06 0.35-3.18
Increased smoking since July 2020 (among daily smokers) 17 34    
No 10 (58.8) 22 (64.7) 1 1
Yes 7 (41.2) 12 (35.3) .682 1.28 0.39-4.24 .658 1.38 0.33-5.80
Current alcohol drinking 396 304
No 131 (33.1) 83 (27.3) 1 1
Yes 265 (66.9) 221 (72.7) .100 0.76 0.55-1.05 .089 0.74 0.53-1.05
Stronger alcohol drinking 265 221
No 219 (82.6) 166 (75.1) 1 1
Yes 46 (17.4) 55 (24.9) .043 0.63 0.41-0.98 .090 0.66 0.41-1.07
Increased alcohol drinking since July 2020 265 221
No 212 (80.0) 177 (80.1) 1 1
Yes 53 (20.0) 44 (19.9) .980 1.01 0.64-1.57 .651 1.12 0.69-1.79
Provided care to a family member/patient with known/suspected case of COVID-19 397 305
No 370 (93.2) 273 (89.5) 1 1
Yes 27 (6.8) 32 (10.5) .083 0.62 0.36-1.06 .043 0.56 0.30-0.98
Identification as a patient/health care service use since July 2020 397 305
No 237 (59.7) 181 (59.3)   1   1
Yes 160 (40.3) 124 (40.7) .925 0.99 0.73-1.34 .381 0.87 0.63-1.19
Level of psychological distress (K10 categories) 397 305
Low to moderate (score 10-21) 317 (79.8) 229 (75.1) 1 1
High to very high (score 22+) 80 (20.2) 76 (24.9) .133 0.76 0.53-1.09 .212 0.79 0.54-1.15
Level of fear of COVID-19 (FCV-19S categories) 397 305
Low (score 7-21) 358 (90.2) 272 (89.2) 1 1
High (score 22-35) 39 (9.8) 33 (10.8) .666 0.90 0.55-1.47 .816 0.94 0.57-1.56
Health care service use to overcome COVID-19-related stress since July 2020 397 305
No 376 (94.7) 279 (91.5) 1 1
Yes 21 (5.3) 26 (8.5) .092 0.60 0.33-1.09 .047 0.53 0.29-0.99
  • Note: Adjusted for: age, gender, living status, born in Australia, and education.
  • a Cardiac disases/stroke/hypertension/hyperlipidemia/diabetes/cancer/chronic respiratory illness.
  • The bold itlaic values indicate ‘statistical significance’.

DISCUSSION

Those attendees with pre-existing mental health issues showed low resilience, high psychological distress and fear of COVID, and had multiple comorbidities, psychiatric/mental health problems, and had used health care services to overcome COVID-19-related stress. A number of factors could negatively affect people with existing mental health conditions, including poorer physical health, social isolation, reduced service utilization, and poorer adherence to prescribed medications. Additionally, during the COVID pandemic, changed health-seeking behaviors for those with chronic conditions have been reported, including a reticence to attend or follow-up.24, 25 According to Neelam et al, people with pre-existing mental illness had significantly more psychiatric symptoms, anxiety, and depressive symptoms compared to others during a pandemic.26 Surprisingly, Neelam et al also found that there was a reduction in both the utilization of mental health services and mental health-related hospitalizations during pandemics. That could be due to the barriers in seeking direct consultations with mental health care providers, as many of those providers had a preference for telehealth consultations during the pandemic, which might not meet patients’ preference for face-to-face contacts.25 Those who did attend their health care providers (for any reason) to manage COVID-19-related stress also reported higher distress and fear.

While Australia had been largely shielded from the high numbers of mortalities experienced globally, there was ample evidence published to show that mortality and complications were high among people with physical comorbidities when coupled with COVID-19. The risk of severe disease, hospitalization, and death was strongly age-related, but it also included pregnant women, leading to greater anxiety and stress for these groups.27 Using a model-based analysis, Holt et al found that hospitalization estimates for COVID-19 increased with age: 1.04% for people aged 20–29 years, increasing to 18.40% for those aged over 80 years.28

Behavioral risk factors, such as smoking and alcohol consumption, also increased in this study. The finding was consistent with evidence showing that as anxiety increased, some people self-medicated using tobacco or alcohol to ameliorate the discomfort they experience due to stress or uncertainty, or to use as a coping mechanism.29 Recent studies also reported association between coping during the COVID-19 pandemic and smoking rates, pointing to a need to develop programs that support coping for those most at risk of increased smoking behavior.30 The World Health Organization (WHO) also argued that the pandemic made it harder, but more important than ever to quit smoking.31 Recommended strategies from WHO included proven effective strategies, such as free cessation services, support from primary health care, and nicotine replacement therapy.

Attendees affected financially (positively and negatively) experienced increased psychological distress and fear of COVID-19. Increased demand for essential workers (given the relatively high self-reported number of essential workers in this survey of 43%) might involve working extra shifts and longer hours, resulting in less leisure and self-care time. For health care workers and other essential frontline workers, the requirement to work with PPE, coupled with concerns regarding the adequacy, efficacy, and availability of masks and shields, resulted in adverse health effects, such as respiratory issues, dermatitis, and anxiety.32

Unlike numerous other studies that found females to be more fearful and anxious about COVID-19, that was not found to be a factor in our study. Living alone was also not associated with more stress, fear, or less coping ability. While this survey did not ask about social media use, some research suggests that engaging with social media may have adverse effects on well-being, and other research reports social media producing positive outcomes.33 In a recent paper, Pandey et al noted that digital interactions during the COVID-19 pandemic assisted in mitigating boredom, loneliness, and irritability caused by lockdowns or quarantining at home.34 As this study focused on a rural and regional area, self-reliance for social connection and physical geographical distance was the nature of those environments and possibly those attributes might assist in higher coping and resilience during a pandemic.

Limitations

Our study had some limitations. As the study was conducted online and in English, selection bias was not unlikely as such methodology allowed only participants who were literate and had internet access to use online platforms in English. The cross-sectional nature of the study design limited our ability to draw a causal relationship between different study variables. However, invitations to participate in this study were sent to all attendees of both study hospitals who had mobile phones, and we had a very good sample size from both sites. Therefore, findings could be generalizable to attendees at such screening clinics in regional Victoria.

CONCLUSIONS

Our study showed that people with pre-existing mental health issues, comorbidities, smokers, and alcohol consumers were high-risk groups in regional Victoria during the COVID-19 pandemic. Additionally, it highlighted the complexity of who was negatively affected psychologically, including those with negative financial impacts. The changed nature of health-seeking behavior, access to services, and modes of health service delivery affected many people throughout the pandemic and highlighted further disparities for vulnerable populations. The study also uncovered some unexpected findings that being female, aged over 60 years, and living alone were not associated with increased stress, fear, or lower resilience, the reasons for which would be interesting to explore in future studies. Policy makers and health service providers in regional settings of Australia could consider utilizing the findings from this study to plan health promotion activities and make support services available for the high-risk groups in regional settings. Specific interventions to support the mental well-being of these vulnerable populations along with engaging health care providers should be considered.

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