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. 2021 Dec 10:1–16. doi: 10.1017/neu.2021.38

Mental health and conspirasism in health care professionals during the spring 2020 COVID-19 lockdown in Greece

Konstantinos N Fountoulakis 1,✉, Maria K Apostolidou 2, Marina B Atsiova 2, Anna K Filippidou 2, Angeliki K Florou 2, Dimitra S Gousiou 2, Aikaterini R Katsara 2, Sofia N Mantzari 2, Marina Padouva-Markoulaki 2, Evangelia I Papatriantafyllou 2, Panagiota I Sacharidi 2, Aikaterini I Tonia 2, Eleni G Tsagalidou 2, Vasiliki P Zymara 2, Panagiotis E Prezerakos 3, Sotirios A Koupidis 4, Nikolaos K Fountoulakis 5, Anastasia Konsta 1, Eva Maria Tsapakis 6, Pavlos N Theodorakis 7, Elias Mossialos 8
PMCID: PMC8770848  PMID: 34886920

Abstract

Introduction:

The aim of the study was to investigate mental health and conspiracy theory beliefs concerning COVID-19 among health care professionals (HCPs).

Material and methods:

During lockdown, an online questionnaire gathered data from 507 HCPs (432 females aged 33.86 ± 8.63 and 75 males aged 39.09 ± 9.54).

Statistical analysis:

A post-stratification method to transform the study sample was used; descriptive statistics were calculated.

Results:

Anxiety and probable depression were increased 1.5–2-fold and were higher in females and nurses. Previous history of depression was the main risk factor. The rates of believing in conspiracy theories concerning the COVID-19 were alarming with the majority of individuals (especially females) following some theory to at least some extend.

Conclusions:

The current paper reports high rates of depression, distress and suicidal thoughts in the HCPs during the lockdown, with a high prevalence of beliefs in conspiracy theories. Female gender and previous history of depression acted as risk factors, while the belief in conspiracy theories might act as a protective factor. The results should be considered with caution due to the nature of the data (online survey on a self-selected but stratified sample).

Key words: COVID-19, health care workers, doctors, nurses, lockdown, depression, suicidality, mental health, conspiracy theories

Significant outcomes

  • The strengths of the current paper include the large number of persons who filled the questionnaire and the large bulk of information obtained, as well as the detailed way of post-stratification of the study sample.

Limitations

  • The major limitation was that the data were obtained anonymously online through self-selection of the responders.

  • Additionally, the assessment included only the cross-sectional application of self-report scales, although the advanced algorithm used for the diagnosis of probable depression corrected the problem to a certain degree. However, what is included under the umbrella of ‘probable depression’ in the stressful times of the pandemic remains a matter of debate.

  • Also, the lack of baseline data concerning the mental health of a similar study sample before the pandemic is also a problem.

Introduction

So far, it has been solidly proven that the COVID-19 outbreak triggered feelings of fear, worry and stress, as responses to an extreme threat for the community and the individual (Fountoulakis et al., 2021). Clinical depression, sleep disorders and post-traumatic stress disorder (PTSD) were also reported both in the general population as well as in health care professionals (HCP). Apart from the effect of the virus itself, in addition, changes in social behaviour, as well as in working conditions, daily habits and routine, are expected to impose further stress, especially with the expectation of an upcoming economic crisis and possible unemployment (Saladino et al., 2020). The term ‘infodemic’ was introduced for the first time to denote the overwhelming flow of information of unknown reliability and validity (Asmundson and Taylor, 2021).

Concerning the general population, a recent meta-analysis reported the presence of anxiety in 25% and depression in 28% of individuals (Ren et al., 2020) while a second one reported that 29.6% of people experienced stress, 31.9% anxiety and 33.7% depression (Salari et al., 2020). Meta-analytical studies with data on HCW reported that anxiety is present in 23-38%, depression in 22-32% and insomnia in 38.9% (Luo et al., 2020, Pappa et al., 2020). The prevalence of general psychiatric symptoms during outbreaks ranges between 17.3 and 75.3% (Preti et al., 2020).

In Greece, where the spring 2020 lockdown was extremely successful in terms of containing the outbreak, worries concerning the effects on mental health were also predominant. The ultra-fast application of measures was probably the reason for this outstanding success (Fountoulakis et al., 2020b); however, an impact on the mental health status of the general population and of university students has already been documented (Patsali et al., 2020, Kaparounaki et al., 2020, Fountoulakis et al., 2020a, Skapinakis et al., 2020, Parlapani et al., 2020). There were also some data on the impact on HCP (Blekas et al., 2020)

The aim of the study was to investigate the rate of anxiety, dysphoria, probable depression and suicidality in HCP in Greece, during the period of the spring 2020 lockdown. The secondary aim included the investigation of the spreading of conspiracy theory beliefs concerning the COVID-19 outbreak among HCP. Conspiracy theories concerning the origin of the outbreak or even their existence per se were widespread during the early phase of the pandemic, while later they were replaced by theories pertaining to vaccines. All these theories had a profound negative effect on health behaviours and reduced the efficacy of measures against COVID-19.

Material and methods

Method

The full protocol used has been published before and is available as a webappendix; each question was given an ID code; throughout the results, these ID codes were used for increased accuracy (Fountoulakis et al., 2020a). The protocol gathered demographic data and also data pertaining to general health, previous psychiatric history, current symptoms of anxiety (STAI-Y1 state) (Fountoulakis et al., 2006), depression (CES-D) (Fountoulakis et al., 2001) and suicidality (RASS), (Fountoulakis et al., 2012) as well as a detailed protocol to investigate changes because of the lockdown in sleep, sex, family relationships, finance, eating and exercising and religion/spirituality. Additionally, the beliefs concerning the COVID-19 outbreak, including the measures taken and conspiracy theories, were investigated.

According to a previously developed method (Fountoulakis et al., 2001, Fountoulakis et al., 2012, Fountoulakis et al., 2021), the cut-off score 23/24 for the CES-D and a derived algorithm were used to identify cases of probable depression, as those identified by both methods. This algorithm utilised the weighted scores of selected CES-D items in order to arrive at the diagnosis of probable depression and has already been validated. Cases identified by only either method were considered cases of distress (false positive cases in terms of depression), while cases identified by both the cut-off and the algorithm were considered as probable depression.

The data were collected online and anonymously from April 11 to May 1, 2020, during the period of the full implementation of lockdown in the country. Announcements and advertisements were done on the social media and through news sites, but no other organised effort had been undertaken.

Approval was given by the Ethics Committee of the Faculty of Medicine, Aristotle University of Thessaloniki, Greece.

Participants were informed of the existence of the study and the questionnaire through announcements on the social media and news sites. The first page included a declaration of consent which everybody accepted by continuing with the participation.

Material

The survey collected data from 3399 persons from the general population, of which 512 were HCP. They included 432 females (84.37%; aged 33.86 ± 8.63) and 75 males (14.64%; aged 39.09 ± 9.54), while 5 declared ‘other’ (0.97%; aged 29.00 ± 5.29). The analysis included only the 507 individuals which were self-identified as either males or females because of the very small number of the third group. The results concerning the general population have been published and are available elsewhere (Fountoulakis et al., 2020a).

The study sample was self-selected, and there was no effort to adjust it to the characteristics of the respected health professionals population of the country since such data were not available. This constitutes one of the limitations of the current study.

Statistical analysis

The study population was self-selected. A method of simplified post-stratification was used (Sarndal, 1992, Holt and Smith, 1979, Little, 1993, Lavrakas, 2008, Keeble et al., 2015) in order to create a standardised study sample with characteristics as close as possible to those of the Greek general population. The detailed method can be found in the webappendix of the publication concerning the general population (Fountoulakis et al., 2020a).

Chi-square tests were used for the comparison of frequencies when categorical variables were present, and for the post hoc analysis of the results, a Bonferroni-corrected method of pair-wise comparisons was utilised (MacDonald and Gardner, 2016).

Multiple forward stepwise linear regression analysis was performed with Schefee as post hoc test to investigate which variables could contribute to the development of others.

Factorial analysis of variance (ANOVA) was used to test for the main effect as well as the interaction among categorical variables.

Results

Demographics (Table 1)

Table 1.

Demographics of the stratified study sample. Most groups (gender-by-profession) differ from most others in terms of age (Factorial ANOVA; df = 4, MS = 5120, F = 55.3, p < 0.001)

Gender-by-occupational group Age % of total sample
Mean SD
Females
Doctor 39.73 10.13 4.20
Nurse 42.07 10.46 12.10
Other clinical health professional 37.11 9.53 31.33
Administration staff 46.21 10.41 3.74
Other staff 39.89 10.77 3.60
Total 39.20 10.29 54.98
Males
Doctor 49.38 10.11 13.97
Nurse 30.67 4.68 2.54
Other clinical health professional 41.81 8.86 20.89
Administration staff 57.61 9.55 4.66
Other staff 42.29 9.84 2.96
Total 45.19 11.14 45.02
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The demographics of the stratified study sample are shown in Table 1. They are clearly different from those of the raw sample, are close to the general population in terms of gender and age. There was a difference in age concerning gender and specific profession as well as in their interaction (df = 4, MS = 5120, F = 55.3, p < 0.001). The study sample was quite heterogenous with most groups differing from most others in terms of age. Although official data are not available, these ages reflect the age of these professional groups in the country, at least concerning doctors and nurses.

Probable depression (Table 2)

Table 2.

Rates of dysphoria, clinical depression and anxiety in the standardised population as well as rates of change in comparison to the pre-COVID-19 period

Normal (%) Dysphoria (%) Probable
depression (%)		 Anxiety (STAI) Change in depression in comparison
to before COVID-19		 Change in anxiety in comparison
to before COVID-19
Mean SD Much worse Worse Same Better Much better Much worse Worse Same Better Much better
Females
Doctor 80.67 14.29 5.04 44.69 12.44 10.08 35.29 52.10 2.52 0.00 18.49 31.93 49.58 0.00 0.00
Nurse 84.55 4.37 11.08 46.52 12.05 7.00 22.74 65.01 1.75 3.50 5.25 35.28 51.60 3.50 4.37
Other clinical health professional 80.41 8.22 11.37 47.01 12.76 4.39 40.32 48.87 5.18 1.24 8.67 46.51 38.06 5.29 1.46
Administration staff 80.19 16.98 2.83 44.27 10.28 5.66 31.13 63.21 0.00 0.00 5.66 5.66 85.85 2.83 0.00
Other staff 76.47 3.92 19.61 42.34 14.99 6.86 29.41 53.92 9.80 0.00 7.84 41.18 44.12 6.86 0.00
Total 81.07 8.15 10.78 46.23 12.64 5.65 34.72 53.98 4.17 1.48 8.41 39.79 45.57 4.43 1.80
Males
Doctor 94.95 3.03 2.02 35.45 7.81 4.04 24.24 70.71 1.01 0.00 4.04 34.34 57.58 3.03 1.01
Nurse 100.00 0.00 0.00 42.17 10.57 0.00 33.33 33.33 16.67 16.67 0.00 33.33 66.67 0.00 0.00
Other clinical health professional 75.68 14.19 10.14 45.95 14.01 5.41 28.38 61.49 4.73 0.00 11.49 25.68 60.14 2.70 0.00
Administration staff 96.97 0.00 3.03 37.76 14.88 3.03 48.48 48.48 0.00 0.00 3.03 48.48 48.48 0.00 0.00
Other staff 100.00 0.00 0.00 44.14 9.10 0.00 14.29 85.71 0.00 0.00 14.29 14.29 71.43 0.00 0.00
Total 86.83 7.52 5.64 41.51 12.91 4.08 28.53 63.01 3.45 0.94 7.84 30.41 59.25 2.19 0.31
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Probable depression was present in 10.78% of females and 5.64% of males. In both cases, the results are approximately double of what is expected from the general population. For comparison, in the raw dataset, the overall rate of probable depression was 13.4% and was identical in the two sexes. This is three to four times higher than expected from the general population.

In both sexes, the high rates of depression are driven by other ‘clinical health professionals’ and female nurses and female other staff while both male and female doctors manifest not higher than expected rates of probable depression. One-fifth of females belonging to ‘other staff’ were classified as suffering from probable depression, which is approximately four times higher than expected.

Chi-square test revealed a significant gender-by-occupation interaction (chi-square = 18.907, df = 4, p < 0.001).

The depressive affect was worse in 40.37% of females (same in 53.98%) and in 32.61% of males (same in 63.01%) in comparison to the pre-COVID-19 period (chi-square = 1.299, df=1, p = 0.254).

Dysphoria (Table 2)

Non-clinical dysphoria was found in 8.15% of females and 7.52% of males, which is very close to what is expected from the general population under normal conditions (Fountoulakis et al., 2001, Fountoulakis et al., 2012). No difference was found by chi-square test.

Anxiety (Table 2)

STAI scores were higher two-fold for females and 1.5-fold for males in comparison to what is expected from the general population and at the levels expected in patients with depression (Fountoulakis et al., 2006). Sub-analysis revealed that anxiety scores were elevated in all subgroups, including non-depressed individuals (41.09 ± 11.37), and were even higher for dysphoric individuals (56.09 ± 8.03), and depressed patients (62.77 ± 13.01). There was a difference in STAI score concerning gender and specific profession as well as in their interaction (df = 4, MS = 1696, F = 11.14, p < 0.001). Scheffe post hoc test revealed that the difference was due to the significantly lower scores male doctors and administration staff had in comparison to the rest.

In total, individuals with scores above two standard deviations from the expected mean (>67; severe anxiety) accounted for 4.57%, while those with scores one standard deviation above the mean (>36; at least moderate anxiety) accounted for 69.37%.

Increased anxiety due to the lockdown was reported by 48.20% of females (same in 45.57%) and by 38.25% of males (same in 59.25%) in comparison to the pre-COVID-19 period (chi-square = 2.017, df = 1, p = 0.1555).

Sleep problems (Table 3)

Table 3.

Changes in parameters of sleep in comparison to the pre-COVID-19 period

Much worse A little bit worse The same A little better Much better
The quality of my sleep has changed recently. It is:
Females
Doctor 7.56 28.57 37.82 21.01 5.04
Nurse 2.33 27.70 61.22 5.25 3.50
Other clinical health professional 12.50 34.68 32.43 12.95 7.43
Administration staff 2.83 11.32 83.02 0.00 2.83
Other staff 13.73 26.47 48.04 5.88 5.88
Total 9.31 30.55 43.65 10.53 5.97
Males
Doctor 0.00 6.06 69.70 24.24 0.00
Nurse 16.67 33.33 50.00 0.00 0.00
Other clinical health professional 9.46 22.97 54.05 11.49 2.03
Administration staff 6.06 9.09 72.73 12.12 0.00
Other staff 57.14 0.00 28.57 14.29 0.00
Total 9.72 15.36 58.93 15.05 0.94
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A recent worsening of the quality of sleep was reported by 39.86% of females and 25.08% of males while an improvement was reported by 16.5% and 15.99% respectively (worsening vs. the rest, chi-square = 4.981, df = 1, p = 0.0256). There was a high variability in terms of gender-by-professional identity subgrouping. On the contrary, there was a homogenous shift of the sleep timetable, with all subgroups reporting staying awake very late in the night and sleep much more during the day, but use of sleeping pills was negligible. Nightmares, recently, were reported by 26.89% of females and 17.55% of males, but with male nurses reporting the highest percentage (50%) (chi-square = 9.421, df = 1, p = 0.051).

Suicidality (Table 4)

Table 4.

Changes in suicidal thoughts and in relationship to a previous history of depression

How much has your tendency to think about death and/or suicide changed, compared to before the outbreak of COVID-19? Very much decreased Decreased a bit Neither increased nor decreased Increased a bit Very much increased No history of depression Depression history
RASS intention scale RASS life scale RASS history scale RASS total suicide score RASS intention scale RASS life scale RASS history scale RASS total suicide score
Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD
Females
Doctor 2.52 0.00 83.19 14.29 0.00 7.25 42.55 65.93 51.11 47.09 47.13 120.27 113.29 23.75 61.32 92.68 57.74 63.04 34.11 179.46 95.14
Nurse 12.54 0.87 78.72 7.00 0.87 37.06 97.04 59.26 63.14 30.22 37.42 126.53 153.19 11.42 29.09 119.37 65.49 64.07 39.11 194.85 101.43
Other clinical health professional 3.83 1.13 85.25 9.57 0.23 23.75 84.36 97.94 86.19 33.82 41.80 155.51 161.39 46.08 87.41 134.81 96.15 43.11 59.46 224.00 171.43
Administration staff 0.00 0.00 94.34 2.83 2.83 16.52 53.93 84.57 89.95 12.61 32.84 113.70 145.30 7.70 26.29 117.16 63.46 41.08 49.34 165.95 64.42
Other staff 2.94 0.98 86.27 5.88 3.92 12.41 40.89 71.36 89.99 39.14 59.91 122.90 163.61 154.76 190.75 219.05 130.50 115.2 122.77 489.05 398.73
Total 5.33 0.90 84.34 8.66 0.77 23.62 80.45 84.50 81.67 33.27 43.12 141.38 155.90 37.46 84.27 130.64 89.23 52.51 59.14 220.61 172.79
Males
Doctor 3.03 1.01 94.95 1.01 0.00 23.28 72.77 25.98 68.65 24.14 38.68 73.39 153.14 48.75 49.30 21.25 21.55 15.00 26.26 85.00 48.86
Nurse 0.00 0.00 100.00 0.00 0.00 0.00 0.00 95.83 78.40 50.00 37.68 145.83 58.10
Other clinical health professional 0.00 0.00 82.43 12.84 4.73 25.32 95.80 88.07 81.90 21.79 55.52 135.18 207.19 145.77 189.46 176.92 125.01 57.56 57.61 380.26 319.67
Administration staff 0.00 0.00 63.64 36.36 0.00 251.5 158.1 181.32 61.25 80.00 38.99 512.89 148.92 6.07 22.09 30.00 76.56 28.21 69.74 64.29 162.97
Other staff 0.00 0.00 85.71 14.29 0.00 15.83 35.65 125.00 78.81 0.00 0.00 140.83 110.18 290.00 0.00 85.00 0.00 90.00 0.00 465.00 0.00
Total 0.94 0.31 85.58 10.97 2.19 39.24 107.3 76.81 87.56 27.47 48.85 143.53 203.87 106.25 161.57 115.15 124.52 45.44 58.33 266.84 296.19
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A similar percentage in both sexes reported no change in suicidal thoughts (85%) but approximately in 10% these thoughts increased. In the total stratified sample, 7.26% (5% of females and 10.03% of males) answered that they think at least sometimes of killing themselves, and this is two-fold higher than what is expected. The highest percentage was found in male administrative staff (36.36%) and the lowest in male nurses (0%) and male doctors (2.02%).

The effect of history of mental disorder (Tables 5 and 6)

Table 5.

History of depression and rates of dysphoria and probable depression in individuals with and without history of depression

History of depression (%) No history of depression (%) History of depression (%) Ratio (history: no history)
Normal dysphoria Probable depression Normal dysphoria Probable depression dysphoria Probable depression
Females
Doctor 23.53 83.52 13.19 3.30 71.43 17.86 10.71
Nurse 39.07 91.39 1.44 7.18 73.88 8.96 17.16
Other clinical health professional 32.77 88.11 7.37 4.52 64.60 9.97 25.43
Administration staff 34.91 69.57 26.09 4.35 100.00 0.00 0.00
Other staff 20.59 85.19 4.94 9.88 42.86 0.00 57.14
Total 32.80 86.91 7.74 5.35 69.08 9.00 21.92 1.16 4.10
Males
Doctor 12.12 97.70 0.00 2.30 75.00 25.00 0.00
Nurse 0.00 100.00 0.00 0.00 0.00 0.00 0.00
Other clinical health professional 26.35 84.40 11.01 4.59 51.28 23.08 25.64
Administration staff 42.42 100.00 0.00 0.00 92.86 0.00 7.14
Other staff 14.29 100.00 0.00 0.00 100.00 0.00 0.00
Total 21.32 92.43 4.78 2.79 66.18 17.65 16.18 3.69 5.80
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Table 6.

Rates of history of suicidal attempts and change in suicidal ideation in subjects groups by history of depression

Change in suicidal ideation
History of suicidal attempts In subjects without history of depression In subjects with history of depression
Never Once 2–3 times At least once Very much decreased Decreased Unchanged Increased Very much increased Any increase Very much decreased Decreased Unchanged Increased Very much increased Any increase
Females
Doctor 99.16 0.84 0.00 0.84 3.30 0.00 80.22 16.48 0.00 16.48 0.00 0.00 92.86 7.14 0.00 7.14
Nurse 96.79 2.33 0.87 3.21 7.66 0.00 85.17 5.74 1.44 7.18 20.15 2.24 68.66 8.96 0.00 8.96
Other clinical health professional 97.41 2.25 0.34 2.59 4.69 0.50 90.79 3.85 0.17 4.02 2.06 2.41 73.88 21.31 0.34 21.65
Administration staff 100.00 0.00 0.00 0.00 0.00 0.00 91.30 4.35 4.35 8.70 0.00 0.00 100.00 0.00 0.00 0.00
Other staff 87.25 8.82 3.92 12.75 3.70 0.00 88.89 7.41 0.00 7.41 0.00 4.76 76.19 0.00 19.05 19.05
Total 96.92 2.44 0.64 3.08 4.78 0.29 88.63 5.64 0.67 6.30 6.46 2.15 75.54 14.87 0.98 15.85
Males
Doctor 98.99 0.00 1.01 1.01 3.45 1.15 94.25 1.15 0.00 1.15 0.00 0.00 100.00 0.00 0.00 0.00
Nurse 100.00 0.00 0.00 0.00 0.00 0.00 100.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Other clinical health professional 97.97 2.03 0.00 2.03 0.00 0.00 82.57 13.76 3.67 17.43 0.00 0.00 82.05 10.26 7.69 17.95
Administration staff 93.94 3.03 3.03 6.06 0.00 0.00 36.84 63.16 0.00 63.16 0.00 0.00 100.00 0.00 0.00 0.00
Other staff 100.00 0.00 0.00 0.00 0.00 0.00 100.00 0.00 0.00 0.00 0.00 0.00 0.00 100.00 0.00 100.00
Total 98.12 1.25 0.63 1.88 1.20 0.40 85.66 11.16 1.59 12.75 0.00 0.00 85.29 10.29 4.41 14.71
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The history of any mental disorder was driven exclusively by the history of unipolar depression, which was present in 32.80% of females and 21.32% of males, with doctors manifesting again the lower rates (Table 5). While in those without history of depression, the rates of the presence of probable depression were what expected cross-sectionally from the general population (5.35% for females and 2.79% for males); the respected rates for those with a history of depression were four to six times higher (21.92% for females and 16.18% for males), and the difference was significant (females: chi-square = 11.658, df = 1, p = 0.0006; males: chi-square = 10.442, df = 1, p = 0.0012).

The presence of dysphoria was not affected by the history of depression in females but in males with such a history, dysphoria was 3.69 times higher. Interestingly, while in persons without a history of depression, the sum of the rates of dysphoria and depression is approximately double in females in comparison to males (13.09% vs. 7.57%), in persons with a history of depression this sum is similar (30.92% vs. 33.83%) (Table 5), suggesting that in females the effect of history is stronger and they progress easier to clinical depression, although chi-square was not significant.

Overall, the rates of history of suicidal attempts are similar to what would be expected from the general population (Fountoulakis et al., 2012) and this adds to the validity of the stratification process. Males reported almost half the rates of history of suicidal attempts in comparison to females (1.88% vs. 3.08%; Table 6) but although they manifested lower rates of depression, their suicidal tendencies were higher than those of females. While for both sexes with a previous history of depression the increase in suicidal thoughts was similar (approximately 15%), in those without history of depression, the rates were double in males (12.75% vs. 6.30%; Table 6). The number of patients with history of suicidal attempts was too small to do a similar analysis with grouping subjects according to suicidal history.

The RASS Suicidal intention score was higher in the group with previous history of depression and while in the subgroup without depression the RASS scores were similar between the two genders, in the group with a history of depression the total RASS score was double in males. Additionally, the RASS subscale scores were similar to the scores expected in the general population (Fountoulakis et al., 2012) except from those of males with a positive history of depression (Table 4). Factorial ANOVA suggested a significant difference among the groups defined by gender-by-profession concerning RASS Intention and Life subscales. The Scheffe post hoc test suggested that these differences were due to the high scores of the male administration and other staff (p < 0.001).

Believing in conspiracy theories (Table 7)

Table 7.

Rates of believing in various conspiracy theories related to the COVID-19 outbreak, with subjects grouped by gender and occupational position

No history of depression History of depression
I don’t believe it at all A little bit Maybe Much Very much I don’t believe it at all A little bit Maybe Much Very much
Do you believe that the COVID-19 vaccine was ready even before the virus broke out and they conceal it from us for the benefit of pharmaceutical companies?
Females
Doctor 68.13 13.19 16.48 2.20 0.00 60.71 28.57 10.71 0.00 0.00
Nurse 36.84 12.92 17.70 16.75 15.79 24.63 2.24 64.18 4.48 4.48
Other clinical health professional 49.58 15.58 23.95 7.37 3.52 50.86 2.41 31.27 7.22 8.25
Administration staff 8.70 21.74 47.83 4.35 17.39 48.65 8.11 32.43 0.00 10.81
Other staff 24.69 7.41 53.09 14.81 0.00 95.24 0.00 4.76 0.00 0.00
Total 44.03 14.61 25.88 9.17 6.30 46.18 4.11 37.77 5.28 6.65
Males
Doctor 83.91 13.79 1.15 1.15 0.00 100.00 0.00 0.00 0.00 0.00
Nurse 33.33 16.67 16.67 16.67 16.67 0.00 0.00 0.00 0.00 0.00
Other clinical health professional 37.61 10.09 35.78 2.75 13.76 51.28 17.95 25.64 0.00 5.13
Administration staff 100.00 0.00 0.00 0.00 0.00 0.00 7.14 92.86 0.00 0.00
Other staff 33.33 0.00 66.67 0.00 0.00 100.00 0.00 0.00 0.00 0.00
Total 57.77 10.36 21.91 2.79 7.17 51.47 11.76 33.82 0.00 2.94
Do you believe that COVID-19 was created in a laboratory to be used as a biochemical weapon for the extermination of the human population?
Females
Doctor 37.36 32.97 23.08 6.59 0.00 60.71 7.14 10.71 21.43 0.00
Nurse 23.92 10.05 35.89 15.79 14.35 33.58 4.48 54.48 4.48 2.99
Other clinical health professional 34.34 18.59 25.29 14.57 7.20 34.36 13.06 31.27 5.84 15.46
Administration staff 21.74 8.70 56.52 8.70 4.35 40.54 32.43 16.22 0.00 10.81
Other staff 19.75 6.17 59.26 12.35 2.47 76.19 14.29 9.52 0.00 0.00
Total 30.56 16.52 31.90 13.56 7.45 37.77 11.94 34.25 5.68 10.37
Males
Doctor 70.11 13.79 14.94 0.00 1.15 75.00 0.00 25.00 0.00 0.00
Nurse 33.33 16.67 33.33 16.67 0.00 0.00 0.00 0.00 0.00 0.00
Other clinical health professional 30.28 11.93 24.77 19.27 13.76 41.03 17.95 25.64 7.69 7.69
Administration staff 78.95 21.05 0.00 0.00 0.00 7.14 0.00 7.14 0.00 85.71
Other staff 16.67 0.00 83.33 0.00 0.00 0.00 100.00 0.00 0.00 0.00
Total 47.01 12.75 24.30 9.56 6.37 38.24 14.71 20.59 4.41 22.06
Do you believe that COVID-19 is the result of 5G technology antenna?
Females
Doctor 94.51 0.00 4.40 1.10 0.00 78.57 21.43 0.00 0.00 0.00
Nurse 58.85 5.74 20.10 8.13 7.18 58.96 26.87 11.94 2.24 0.00
Other clinical health professional 75.71 7.87 12.73 2.68 1.01 79.38 8.59 7.90 3.09 1.03
Administration staff 86.96 4.35 4.35 4.35 0.00 89.19 0.00 0.00 0.00 10.81
Other staff 50.62 27.16 22.22 0.00 0.00 95.24 0.00 4.76 0.00 0.00
Total 72.78 8.02 13.66 3.53 2.01 75.34 13.11 7.83 2.35 1.37
Males
Doctor 100.00 0.00 0.00 0.00 0.00 75.00 0.00 25.00 0.00 0.00
Nurse 66.67 0.00 33.33 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Other clinical health professional 90.83 0.00 8.26 0.00 0.92 89.74 0.00 10.26 0.00 0.00
Administration staff 100.00 0.00 0.00 0.00 0.00 0.00 7.14 7.14 0.00 85.71
Other staff 100.00 0.00 0.00 0.00 0.00 100.00 0.00 0.00 0.00 0.00
Total 93.63 0.00 5.98 0.00 0.40 69.12 1.47 11.76 0.00 17.65
Do you believe that COVID-19 appeared accidentally from human contact with animals and it was something that generally happens and was generally expected?
Females
Doctor 3.30 21.98 17.58 39.56 17.58 10.71 0.00 3.57 67.86 17.86
Nurse 19.62 11.48 41.15 17.70 10.05 19.40 8.96 55.22 16.42 0.00
Other clinical health professional 19.60 15.24 36.85 22.28 6.03 17.87 10.65 36.43 23.02 12.03
Administration staff 26.09 30.43 34.78 8.70 0.00 0.00 32.43 48.65 10.81 8.11
Other staff 22.22 7.41 55.56 14.81 0.00 4.76 0.00 14.29 47.62 33.33
Total 18.82 15.47 37.34 21.39 6.97 16.05 10.76 39.53 23.87 9.78
Males
Doctor 1.15 0.00 39.08 14.94 44.83 0.00 0.00 25.00 0.00 75.00
Nurse 16.67 0.00 66.67 0.00 16.67 0.00 0.00 0.00 0.00 0.00
Other clinical health professional 33.03 11.01 30.28 22.94 2.75 5.13 10.26 56.41 25.64 2.56
Administration staff 0.00 0.00 78.95 21.05 0.00 0.00 7.14 85.71 7.14 0.00
Other staff 0.00 16.67 66.67 16.67 0.00 0.00 100.00 0.00 0.00 0.00
Total 15.94 5.98 42.23 17.93 17.93 2.94 11.76 54.41 16.18 14.71
Do you believe that COVID-19 has much lower mortality rate but there is misinformation and terror-inducing propaganda?
Females
Doctor 49.45 4.40 16.48 25.27 4.40 46.43 3.57 28.57 21.43 0.00
Nurse 40.19 11.48 27.75 9.09 11.48 29.10 11.19 40.30 12.69 6.72
Other clinical health professional 35.51 22.11 22.45 14.24 5.70 25.77 22.34 30.58 15.81 5.50
Administration staff 39.13 17.39 17.39 0.00 26.09 48.65 40.54 0.00 10.81 0.00
Other staff 19.75 7.41 50.62 7.41 14.81 38.10 28.57 33.33 0.00 0.00
Total 36.68 17.00 24.83 12.70 8.79 29.94 19.96 30.92 14.29 4.89
Males
Doctor 56.32 25.29 18.39 0.00 0.00 50.00 0.00 25.00 25.00 0.00
Nurse 0.00 33.33 50.00 16.67 0.00 0.00 0.00 0.00 0.00 0.00
Other clinical health professional 26.61 15.60 33.03 19.27 5.50 25.64 7.69 53.85 7.69 5.13
Administration staff 0.00 36.84 0.00 63.16 0.00 0.00 0.00 85.71 14.29 0.00
Other staff 0.00 66.67 0.00 16.67 16.67 0.00 0.00 100.00 0.00 0.00
Total 31.08 25.50 24.30 15.54 3.59 23.53 4.41 57.35 11.76 2.94
Do you believe that COVID-19 is a creation of the world’s powerful leaders to create a global economic crisis?
Females
Doctor 40.66 0.00 38.46 7.69 13.19 64.29 14.29 10.71 10.71 0.00
Nurse 33.97 11.48 27.27 13.88 13.40 26.87 20.15 46.27 4.48 2.24
Other clinical health professional 35.85 17.92 25.29 13.74 7.20 36.77 13.40 25.77 17.87 6.19
Administration staff 8.70 26.09 52.17 4.35 8.70 48.65 40.54 0.00 0.00 10.81
Other staff 19.75 7.41 53.09 4.94 14.81 57.14 38.10 4.76 0.00 0.00
Total 32.86 14.80 30.75 11.94 9.65 37.38 18.20 27.59 11.94 4.89
Males
Doctor 80.46 13.79 4.60 1.15 0.00 75.00 0.00 0.00 25.00 0.00
Nurse 16.67 0.00 50.00 16.67 16.67 0.00 0.00 0.00 0.00 0.00
Other clinical health professional 21.10 17.43 41.28 5.50 14.68 23.08 46.15 7.69 17.95 5.13
Administration staff 100.00 0.00 0.00 0.00 0.00 0.00 0.00 14.29 0.00 85.71
Other staff 0.00 16.67 83.33 0.00 0.00 100.00 0.00 0.00 0.00 0.00
Total 45.82 13.55 29.08 3.98 7.57 30.88 26.47 7.35 14.71 20.59
Do you believe that CONID-19 is a sign of divine power to destroy our planet?
Females
Doctor 74.73 16.48 7.69 1.10 0.00 53.57 42.86 3.57 0.00 0.00
Nurse 69.38 13.40 15.79 0.00 1.44 76.87 9.70 13.43 0.00 0.00
Other clinical health professional 77.22 13.40 7.20 1.51 0.67 74.23 15.12 10.65 0.00 0.00
Administration staff 69.57 8.70 21.74 0.00 0.00 59.46 8.11 32.43 0.00 0.00
Other staff 76.54 3.70 4.94 14.81 0.00 85.71 14.29 0.00 0.00 0.00
Total 74.88 12.61 9.74 2.10 0.67 73.19 14.68 12.13 0.00 0.00
Males
Doctor 86.21 0.00 13.79 0.00 0.00 75.00 25.00 0.00 0.00 0.00
Nurse 83.33 0.00 16.67 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Other clinical health professional 82.57 14.68 2.75 0.00 0.00 92.31 0.00 7.69 0.00 0.00
Administration staff 100.00 0.00 0.00 0.00 0.00 14.29 0.00 0.00 0.00 85.71
Other staff 100.00 0.00 0.00 0.00 0.00 100.00 0.00 0.00 0.00 0.00
Total 86.45 6.37 7.17 0.00 0.00 73.53 4.41 4.41 0.00 17.65
The information and use of the internet worry me about the issue regarding the COVID-19:
Females
Doctor 29.67 29.67 20.88 17.58 2.20 57.14 14.29 21.43 7.14 0.00
Nurse 44.02 31.58 14.83 5.26 4.31 17.91 38.81 37.31 0.75 5.22
Other clinical health professional 25.13 33.33 23.28 14.91 3.35 20.62 20.96 25.09 22.68 10.65
Administration staff 17.39 39.13 13.04 26.09 4.35 75.68 16.22 0.00 8.11 0.00
Other staff 40.74 14.81 40.74 3.70 0.00 23.81 14.29 33.33 9.52 19.05
Total 29.99 31.61 22.06 13.09 3.25 26.03 24.66 26.61 14.48 8.22
Males
Doctor 65.52 33.33 0.00 0.00 1.15 25.00 25.00 25.00 25.00 0.00
Nurse 50.00 16.67 16.67 0.00 16.67 0.00 0.00 0.00 0.00 0.00
Other clinical health professional 33.03 35.78 22.02 5.50 3.67 12.82 51.28 10.26 23.08 2.56
Administration staff 15.79 84.21 0.00 0.00 0.00 85.71 0.00 0.00 14.29 0.00
Other staff 66.67 0.00 16.67 16.67 0.00 0.00 0.00 100.00 0.00 0.00
Total 46.61 34.66 11.95 3.59 3.19 29.41 33.82 14.71 20.59 1.47
Generally, most of the internet sources regarding information about COVID-19 are misinforming/misleading:
Females
Doctor 26.37 14.29 34.07 23.08 2.20 42.86 3.57 25.00 28.57 0.00
Nurse 5.74 17.70 35.89 31.58 9.09 0.00 25.37 27.61 36.57 10.45
Other clinical health professional 6.37 24.46 27.30 30.49 11.39 4.47 27.49 34.36 24.74 8.93
Administration staff 0.00 39.13 21.74 4.35 34.78 0.00 8.11 81.08 0.00 10.81
Other staff 3.70 11.11 53.09 16.05 16.05 0.00 47.62 19.05 28.57 4.76
Total 7.35 22.16 31.23 27.22 12.03 4.89 25.05 34.83 26.42 8.81
Males
Doctor 44.83 14.94 24.14 14.94 1.15 0.00 0.00 75.00 25.00 0.00
Nurse 0.00 16.67 33.33 33.33 16.67 0.00 0.00 0.00 0.00 0.00
Other clinical health professional 9.17 16.51 51.38 17.43 5.50 0.00 25.64 35.90 30.77 7.69
Administration staff 63.16 0.00 36.84 0.00 0.00 0.00 7.14 92.86 0.00 0.00
Other staff 0.00 66.67 0.00 0.00 33.33 0.00 100.00 0.00 0.00 0.00
Total 24.30 18.33 35.86 15.14 6.37 0.00 20.59 52.94 22.06 4.41
Open in a new tab

The rates of the believing in conspiracy theories concerning the COVID-19 epidemic are at least partially impressive and alarming. For example, only one-third of HCP definitely rejects the belief that COVID-19 is deliberately exaggerated via terror-inducing propaganda, and this includes an astonishingly low rate close to 50% for doctors. Only 30.56% of females and 47.01% of males reject the idea that the COVID-19 was created in a laboratory and deliberately released as a biochemical weapon to exterminate human population. To at least some extent, this idea is followed by more than 60% of female and almost 30% of male doctors. The 5G conspiracy theory is to some extend accepted by approximately 23% of females (including 5.5% of female doctors) and 6.5% of males (including one-third of male nurses). Conceptualising the outbreak as a form of direct and real divine punishment was embraced by 25% of females and almost 15% of males, and these same rates hold for doctors.

Discussion

During lockdown, among health professionals, probable depression was present in 10.78% of females and 5.64% of males (increased 2-fold) and was higher in females and nurses but levels of dysphoria were not increased. Depressed affect worsened in 40.37% of females and in 32.61% of males in comparison to the pre-COVID-19 period. Anxiety increased two-fold for females and 1.5-fold in males and worsening of the quality of sleep in 39.86% of females and 25.08% of males. Nightmares, recently, were reported by 26.89% of females and 17.55% of males, but with male nurses reporting the highest percentage (50%). Previous history of depression was the main risk factor behind high rates of depression especially in females and the 2-fold increase in suicidal thoughts especially in males. The rates of the believing in conspiracy theories concerning the COVID-19 epidemic were alarming with the majority of individuals following some theory to at least some extend and with females having higher acceptance rates. Even among doctors, these beliefs were highly prevalent, and this concerned even the most extreme of them.

While the results concerning probable depression are more or less similar to those previously reported concerning the general population (Fountoulakis et al., 2020a), there is a significant difference: in HCP, the history of depression seems to be the decisive factor; individuals without such a history manifest the rates expected from the general population during normal periods (which is still high because ‘general population’ includes also persons with positive history of depression), while those with such a history had at least four to six times higher rates. These results suggest a probable increase in first episodes of depression but also an explosive increase in relapses during lockdown. It is unknown which percentage of those persons with a previous history manifested a relapse and which had an ongoing episode with onset before the outbreak.

Concerning the increase of suicidal ideation in HCP, this seems to be higher concerning the reported from the general population (Fountoulakis et al., 2020a).

The results of the current study should be considered by having in mind that they were gathered during a period of strict lockdown. This kind of lockdowns have a complex but overall negative impact on the mental status of the population, and it is believed they cause distress and depression (Foa et al. 2020, Recchi et al., 2020, Di Blasi et al., 2021, Rossi et al., 2021).

The literature is already rich concerning the mental health of HCPs although the bulk of data come from a limited number of countries, and generalisability is questionable. Most of the data were gathered through online questionnaires and their study samples are not standardised. However, concerning doctors, most of the data suggest high rates of up to 60% of psychopathology (Maciaszek et al., 2020) and especially of anxiety (Al Mahyijari et al., 2020, Amin et al., 2020) and depression (Amin et al., 2020). Rates vary from 32.9% for stress and anxiety (Chatterjee et al., 2020) 34.9% for depression (Chatterjee et al., 2020) and 45% of symptoms of stress (Das et al., 2020) and 63.5% of symptoms of depression (Das et al., 2020). Female gender was related to higher rates of anxiety and depression (Hacimusalar et al., 2020, Maciaszek et al., 2020).

Also in nurses, there are reports of high anxiety (Al Mahyijari et al., 2020), higher than those reported in other health professionals (Wang et al., 2020, Ning et al., 2020, Lai et al., 2020, Jo et al., 2020, Cabarkapa et al., 2020, Azoulay et al., 2020), and this is also true concerning depression (Hacimusalar et al., 2020) and PTSD (Wang et al., 2020, Song et al., 2020). Rates of anxiety are reported to be up to 50.4% (Azoulay et al., 2020), depression being as high as 30.4–43.61% (An et al., 2020, Azoulay et al., 2020) and trauma-related disorders up to 32–39.3% (Azoulay et al., 2020, Chen et al., 2020). In terms of symptomatology, it has been reported that 8.1–40% had anxiety, 9.4–46% had depressive symptoms, and 42.7% had somatic symptom, while 6.5% reported suicidal ideation (Hong et al., 2020, Hu et al., 2020, Tu et al., 2020, Xiong et al., 2020). Up to 60% reported poor sleep quality (Tu et al., 2020). Again, also in nurses, female gender was related with higher scores of depression, anxiety and trauma-related disorders (Hacimusalar et al., 2020, Cabarkapa et al., 2020, Chen et al., 2020, AlAteeq et al., 2020), although there are also negative reports concerning the effect of gender (Xiong et al., 2020). Other risk factors included lack of access to adequate personal protective equipment (Arnetz et al., 2020).

When considering health care workers as a whole, anxiety disorders were present in 10–27.1% (Wang et al., 2020, Awano et al., 2020, Badahdah et al., 2020, Salopek-Ziha et al., 2020), while depression was present in 11–27.9% (Salopek-Ziha et al., 2020, Awano et al., 2020). There is also a high prevalence of up to 28–98.5% concerning symptoms of anxiety (Zhang et al., 2020, Xing et al., 2020, Suryavanshi et al., 2020, Shechter et al., 2020, Lai et al., 2020, Firew et al., 2020, Awano et al., 2020, Juan et al., 2020, Khanal et al., 2020, Que et al., 2020, Sahin et al., 2020), 25.2–92.5% concerning those of depression (Zhang et al., 2020, Xing et al., 2020, Suryavanshi et al., 2020, Song et al., 2020, Shechter et al., 2020, Sahin et al., 2020, Lai et al., 2020, Khanal et al., 2020, Firew et al., 2020, Awano et al., 2020, Juan et al., 2020, Que et al., 2020), and 32–37.5% for symptoms of peritraumatic dissociation (Juan et al., 2020, Azoulay et al., 2020). Insomnia was reported by 28.75–50.4% (Sahin et al., 2020, Que et al., 2020, Lai et al., 2020, Khanal et al., 2020). PTSD was reported in 9.1–9.8% (Song et al., 2020, Wang et al., 2020). Burnout and distress are also frequently reported (Zhang et al., 2020, Firew et al., 2020, Sahin et al., 2020, Salopek-Ziha et al., 2020, Shechter et al., 2020) as well as low quality of life (Suryavanshi et al., 2020).

In general, being female appeared to confer greater risk (Cabarkapa et al., 2020, Elkholy et al., 2020, Kang et al., 2020, Lai et al., 2020, Ning et al., 2020), and this was also true concerning individuals with a history of mental disorder (Sahin et al., 2020).

Meta-analytical studies reported that in health care professionals anxiety was found in 23–38% and depression in 22-32% and was similar with that of the general population and insomnia in 38.9% (Luo et al., 2020, Pappa et al., 2020). In general, during epidemics, depressive symptoms are reported in 27.5–50.7%, insomnia symptoms in 34–36.1% and severe anxiety symptoms in 45%. General psychiatric symptoms during outbreaks have a range comprised between 17.3 and 75.3%; high levels of stress related to working are reported in 18.1–80.1% (Preti et al., 2020).

The results of the current study, while in accord with more or less with the literature, point also to the decisive effect of the previous history of depression, and in this way, our results identify a particularly vulnerable population among HCPs.

Also, the high rates of believing in conspiracy theories are in accord with findings from other countries (Ahmed et al., 2020, Uscinski et al., 2020, Fountoulakis & in 2021) and are a worrying manifestation. Conspiracy beliefs – especially those regarding science, medicine, and health-related topics – are widespread (Oliver and Wood, 2014) and capable of prompting people to eschew appropriate health-related behaviours (Jolley and Douglas, 2014, Bogart et al., 2010). Being widely spread within HCPs is an even greater danger for public health. Our results are in accord with the announcement by the Greek Ministry of Health that by August 19, 2021 in hospitals, and in primary care units, 90% and 93% of doctors, 78% and 85% of nurses, 79% and 82% of administration staff and 74% and 83% of other health professionals, respectively, were either vaccinated or had suffered from COVID-19 and are immune. The percentage that had suffered and was at that time immune was 3% and 4% of doctors, 5% and 6% of nurses, 6% and 7% of administration staff and 5% and 6% of the rest of health professionals.

The probability they constitute a dysfunctional coping mechanism as they probably constitute in the general population is strong also here (Fountoulakis et al., 2020a, Freyler et al., 2019, Tomljenovic et al., 2020). This probability of an affective component in the frame of a dysfunctional copying mechanism is in accord with the finding that believing was more frequent in females and could be explained through higher temperamental levels of anxiety and harm avoidance (Sacher et al., 2013, Aleman and Swart, 2008, Fischer et al., 2004, Lee et al., 2005, Lee et al., 2002, McClure et al., 2004, Schirmer et al., 2004, Schroeder et al., 2004, Fusar-Poli et al., 2009).

However, one should have in mind that believing in conspiracy theories does not necessarily mean that one acts in accord with these beliefs. On the contrary, the discrepancy between beliefs and behaviour is what distinguishes conspiracy beliefs from delusional ideas.

Conclusion

The current paper reports high rates of depression, distress and suicidal thoughts in the HCPs during the lockdown, with a high prevalence of beliefs in conspiracy theories. Female gender as well as previous history of depression acted as risk factors, while it is possible that belief in conspiracy theories acts as a protective factor. These results are alarming in many ways, especially concerning the wide prevalence of believing in conspiracy theories and the suggested impact of these beliefs on mental health and health-related behaviours. Probably, countries should invest in the targeted training and education of health professionals concerning health-related conspiracy theories but also on topics of specific interest, for example better education on how the system works and why some assumptions (e.g. the inflated number of deaths theory) could not be right. Overall, it seems unlikely that a single country can make a difference concerning in its own people; internationally coordinated action seems necessary.

Acknowledgements

None.

Author contributions

All authors contributed equally to the paper.

KNF conceived and designed the study. The other authors participated formulating the final protocol, designing and supervising the data collection and creating the final dataset. KNF did the data analysis and wrote the first draft of the paper. All authors participated in interpreting the data and developing further stages and the final version of the paper.

Financial support

None.

Conflict of interest

None pertaining to the current paper.

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