The Psychological State and Changes in the Routine of the Patients with Rheumatic Diseases during the First Month of the Lockdown of the Coronavirus Disease (COVID-19) Outbreak in Turkey

doi:10.21203/rs.3.rs-33318/v1

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Research Article

The Psychological State and Changes in the Routine of the Patients with Rheumatic Diseases during the First Month of the Lockdown of the Coronavirus Disease (COVID-19) Outbreak in Turkey

https://doi.org/10.21203/rs.3.rs-33318/v1

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published 22 Jun, 2020

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Objective: We hypothesized that patients with rheumatic diseases (RD) would have increased psychological distress during the COVID-19 outbreak; therefore assessed their psychological symptoms and changes in their routine.

Methods: A web-based study was conducted in a cross-sectional design in 3 groups of participants: 1. patients with RD, 2. hospital workers and 3. high-school teachers/non-medical academic staff. Psychiatric status was evaluated using Hospital Anxiety and Depression Scale and Impact of Event Scale-Revised scale.

Results: We studied 771 patients with RD, 535 hospital workers, and 917 teachers/academic staff. Most of the patients with RD were unwilling to go to the hospital (86 %) while 22 % discontinued their medications (78%). Biological DMARDS were the most frequent drugs whose doses were altered. Only 4 % were willing to take hydroxychloroquine for protection. Moreover, the frequency of anxiety (20%), depression (43%) and post-traumatic stress (28%) among patients with RD were found to be comparable to that among the teachers/academic staff (23%, 43% and 29%, respectively), whereas significantly less than that among the hospital workers (40%, 62% and 46%, respectively) (p<0.0001). Female gender, over social media exposure, comorbid disease, or a psychiatric disorder were found to be independently associated with psychiatric symptoms in total study population.

Conclusions: The majority of the patients were unwilling to attend outpatient visits and one fifth skipped or stopped their immunosuppressive agents. Psychiatric symptoms in patient’s and teacher’s populations were of considerable clinical concern, despite being significantly lower than that observed among the hospital workers.

Psychiatry

Hospital Medicine

COVID-19

Rheumatology

Anxiety

Depression

Post-traumatic stress

Hospital workers

Teachers

Academic staff

A great majority of the patients with RD complied strictly withrestrictions and were unwilling to attend outpatient visits.
One fifth discontinued or stopped taking theirimmunosuppressives.
Biological DMARDs were the most frequent agents which patientsskipped or stopped.
The anxiety, depression and post-traumatic stress levels amongpatients with RD were found to be similar to that found amongteachers/academic staff.
Hospital workers had the highest levels of anxiety, depression,post-traumatic stress and sleep problems in the whole studypopulation.

Coronavirus disease (COVID-19) was first identified in China inDecember 2019 and resulted in a pandemic. The first case in Turkeywas officially confirmed on March, 11 2020 and Istanbul became thehardest hit city so far (1). Starting from March 16, 2020, thegovernment issued several restrictions to prevent the spread of thevirus. First, schools and all public gathering places were closedand a permanent lockdown for elderly or with chronic illnesses wasdeclared, this was followed by weekend curfews. Eligible hospitalswere transformed into ‘pandemic hospitals’ (1). Many inpatientclinics became care units for COVID-19 patients, elective surgicalor interventional operations were postponed, and the performance ofoutpatient clinics was considerably reduced to prioritize the careof these patients. All these unprecedented measures have profoundlyaffected the health care system as well as the social life.

Several studies revealed that being older than 60 years, smokingand comorbid medical conditions such as cardiovascular disease,chronic lung disease, hypertension, diabetes mellitus, and obesityare the major contributors for the severe outcome among patientswith COVID-19 (2). Close monitoring of those withimmunosuppression, cancer and chronic renal disease is alsowarranted (2).

Since the time of the declaration of the first COVID-19 case, wehave received several calls from our patients having a rheumaticdiseases (RD) reflecting their concerns and fears regarding theircompromised immune status. We therefore assessed the impact of thepandemic and its related control measures on the psychologicalstate of patients with RD. As control groups, we investigated 2different occupational groups: the first was hospital workers inwhom a higher prevalence of psychological symptoms were observedduring the COVID-19 outbreak (3-6); and the other was high-schoolteachers or academic staff in whom we assumed that psychologicalsymptoms would be less, given that they were working from homesince the schools had been closed. Additionally, we investigatedthe immediate change in the routine concerning outpatient visits orregular use of drugs only among patients with RD.

A web-based survey was conducted in a cross-sectional designusing the Survey Monkey software (SurveyMonkey, San Mateo, CA, USA)and sent out to the participants via WhatsApp link. The studygroups consisted of patients with RD, hospital workers andhigh-school teachers or non-medical academic staff. The onlinesurvey contained three parts. The first part included questions onsocio-demographic and other variables. The second and third partsincluded the evaluation of psychological distress.

a) Identification of socio-demographic variables andprobable risk factors for COVID-19

Demographic data, age, gender, occupation, marital status,having child/children (yes or no), educational status, householdsize, source of information related with COVID-19, types of socialmedia and, daily hours of TV / social media exposure werecollected. The presence/absence of contracting COVID in theparticipant itself, in a close friend or in a family relative wassought. Participants were also asked whether they were smokers(active, quitted or never) and have been previously diagnosed witha comorbid disease (such as cardiovascular disease, chronic lungdisease, hypertension, diabetes mellitus or else) and a psychiatricdisorder or had previously used a psychiatric drug for at leastthree months.

The following questions were only asked to patients with RD.These were related with adherence to stay home warnings (loose;moderate or strict); the obligation to go outside for work;satisfaction with the medical support or information received forCOVID-19 (much; enough; not at all); visiting the outpatient clinic(regularly; as it was before; did not want to; wanted to but couldnot contact anyone; was advised not to come, or did not have ascheduled visit); proper use of the medications (yes, as it wasbefore; yes, but decreased or skipped the dose; no, completelystopped); the type of medication the patient altered the dose of orstopped taking and thought about taking hydroxychloroquine forprotective measures (Yes, I recently started; yes I thought aboutit but I have some hesitations; I already take it as a prescribeddrug; no, never thought about it) (7).

b) Evaluation of the psychiatric symptoms

Anxious and depressive symptoms were assessed using HospitalAnxiety and Depression Scale (HADS) (8). Scores for anxiety anddepression were derived by summing the responses for each of thesubscales (HADS-A and HADS-D). In addition, cut-off points of ≥11and ≥8 were used for quantification of anxiety and depression,respectively. Symptoms of post-traumatic stress (PTS) were assessedusing Impact of Event Scale-Revised (IES-R) (9-10). This toolevaluates intrusion, avoidance and hyperarousal in threesubdimensions and presents a total score for subjective stress(IES-R score). A cut-off point of ≥33 provided the bestdiagnostic accuracy for PTS (9-10). Both HADS and IES-R werevalidated previously in Turkish (11-12). In addition, sleepproblems were evaluated using two questions of IES-R; choosing’severe’ or ‘very severe’ as an answer was considered as thepresence of a trouble in maintaining sleep (no.2) and trouble infalling asleep (no.15).

Participants who completely responded filled in either the HADSor the IES-R were found eligible for thestudy.

Identification and selection of the studypopulation

A flow chart shows the evolution of the study population(Supplement Figure 1).

Group 1: Patients with RD

We identified sx subgroups of rheumatic diseases: 1) rheumatoidarthritis (RA); 2) connective tissue disease (CTD) which includedsystemic lupus erythematosus, systemic sclerosis and primarySjögren syndrome; 3) spondylarthropathies (SpA); 4) Behçet’ssyndrome (BS); 5) familal Mediterranean fever (FMF); 6) vasculitis.Patients who were examined within the last six months in ouroutpatient clinic were identified and 300 patients from eachsubgroup were consecutively selected as the target studypopulation. Of these 1800 patients, 771 (42.8 %) were foundeligible for the study.

Group 2: Hospital workers

The staff of a university hospital and two state hospitals inIstanbul, which became ‘coronavirus pandemic hospitals’ and alllocated in Istanbul were chosen as the target hospital workerspopulation. Web-based questionnaire was sent to medical (700doctors and 1400 nurses), and non-medical staff (n =300) such assecretaries, security guards, care takers, and lab workers. Ofthese 2400 hospital workers, only 535 (22.3%) were found suitablefor the study.

Group 3: Teachers and academic staff

This group included around 2000 high-school teachers from 50high-schools and 200 academic members from four non-medicaluniversities. All teachers and academic personnel were living andstudying in Istanbul. A total of 917 (41.7%) were eligible for thestudy.

Overall response rate was calculated as 34.7% (2223/ 6400) whilethat among the hospital workers (22.3%) was significantlylower than that observed among patients with RD (42.8%) andteachers/academic staff (41.7 %) (p<0.001). The survey ran frombetween 4-24 April, 2020.

Ethical statement

This study was approved by the Ethics Committee of I. U.-C.,Cerrahpaşa Medical Faculty. Electronic informed consent waspresented on the first page of the survey citing that the survey isvoluntary and participants could withdraw from the survey at anytime.

Statistical Analysis

Normality distribution of the numeric variables was tested bythe Shapiro Wilk test. Kruskal Wallis test was used for comparisonof IES-R and HAD scales’ scores, and then Dunn’s test withBonferroni correction was used for multiple comparisons when thesignificantly meaningful difference was obtained. Categoricalvariables were compared using Pearson’s chi-square test. The MannWhitney U test was used for comparison of the scale scores betweenmedical and non medical health workers. Reliability of the scaleswas assessed as Cronbach’s alpha coefficient.

We also used multivariate logistic regression analysis withenter method to examine the relationships among 13 varioussocio-demographic or clinical risk factors and the presence orabsence of anxiety, depression and PTS combining all three studygroups. The reference categories were identified as: Group 2 forthe group variable, male for gender, >8 years foreducation, married for marital status, none for having child, ≤3for household size, ≤1 hours for duration of TV or social mediaexposure, no for the presence of COVID-19 in the participant orfamily, no for the presence of someone ≥ 65 years in the household,never for smoking habit, no for the presence of comorbid diseases,and no for the history of psychiatric disorders or psychiatric druguse for at least three months. IBM SPSS Statistics for Windows,v.20.0 (IBM Corp., Armonk, NY, USA) was used in the statisticalanalysis. A p value of less than 0.05 was accepted as statisticalsignificance.

In total, we studied in total 771 (245 M/ 526 F) patients withRD (Group 1), 535 (181 M/ 354 F) hospital workers (Group 2) and 917(258 M/ 659 F) teachers/academic staff (Group 3). Patients with RDwere categorized in six subgroups: 1) RA (n=131; 21 M/ 110 F); 2)CTD (n= 171; 18 M/ 153 F); 3) SpA (n= 102; 58 M/ 44 F); 4) BS (n=171; 108 M/ 63 F); 5) FMF (n= 79; 21 M/58 F); 6) Vasculitis (n=117; 19 M/ 98 F). Of these 771 patients, 21 were offdrugs, while the remaining were prescribed one or more of thefollowing drugs such as biological disease-modifying anti-rheumaticdrugs (DMARDs) (n = 317, 42.3%), non-biological DMARDs (n =441,58.7%), and prednisolone (n = 340, 45.3%), at the time of thesurvey. Hydroxychloroquine (n= 198, 25.7%) and colchicine (n = 194,25.9%) were also listed among the prescribed drugs.

Hospital workers included medical [doctors (n= 233; 94 M/139 F)and nurses (n=158; 16 M/ 142 F)] and non-medical workers (n= 144;71 M/ 73 F). Group 3 included 851 (234 M/ 617 F) high-schoolteachers and 66 (24 M/ 42 F) academic personnel.

1) Socio-demographic characteristics (Table1)

Respondents were mostly female in all study groups, somewhatslightly more in teachers/academic staff group. Besides that, therewere significant socio-demographic differences between the studygroups. The most striking was that the patients with RD weresignificantly older and less educated compared to both hospitalworkers and teachers/academic staff. Additionally, most of thepatients with RD were married and had children and a household sizeof ≥ 4. While TV and social media were the basic sources ofinformation about COVID-19 for all study groups, hospital workersseemed to receive most of the information from their institution.Patients with RD appeared to use social media less frequently andto spend less hours watching TV or using social media when comparedto the rest of the study groups.

Table1. Socio-demographic variables and resources of information aboutCOVID

	Group1 Patientswith RD (n=771)	Group2 Hospitalworkers (n =535)	Group3 Teachers/academic staff (n=917)	P
Age, mean± SD, years	42,8 ±12,7	33,8 ±8,7	37,4 ±10,3	<0.001*†§
Male/Female, n (rate)	245/526(0.46)	181/354(0.51)	258/659(0.39)	0.058
Educational status, n(%)
Primary/middle school	281(36.4)	18(3.4)	1(0.1)	<0.0001*†§
High school or higher	490(75.6)	517(96.6)	916(99.9)	<0.0001*†§
Maritalstatus, n (%)
Married	701(69)	284(53.3)	602(66.2)	<0.0001*§
Single	171(31)	249(46.7)	308(33.7)	<0.0001*§
Havechild, n (%)	524(68.8)	228(45.4)	497(57.6)	<0.0001*†§
Householdsize, n (%)
£3	408(52.9)	259(57.9)	545(63.3)	<0.0001†
≥4	363(47.1)	188(42.1)	316(36.7)	<0.0001†
Source ofinformation related to COVID-19, n (%)
TV	698(90.5)	367(68.6)	817(89.1)	<0.0001*§
Social media	479(62.1)	397(74.2)	824(89.9)	<0.0001*†§
Institution	79(10.2)	443(82.8)	224(24.4)	<0.0001*†§
Friends	167(21.7)	303(56.6)	428(46.7)	<0.0001*†§
Socialmedia resources
Instagram	425(55.1)	348(65.0)	628(68.5)	<0.0001*†
Twitter	206(26.7)	211(39.4)	535(58.3)	<0.0001*†§
Facebook	315(40.9)	192(35.9)	365(39.8)	0.175
WhatsApp groups	277(35.9)	371(69.3)	529(57.7)	<0.0001*†§
Internet websites	344(44.6)	349(65.2)	610(66.5)	<0.0001*
Hoursspent daily watching TV/using social media
≤ 1 hour	335(43.5)	142(26.5)	238(26.0)	<0.0001*†
≥2hours	436(56.5)	393(73.5)	679(74.0)	<0.0001*†

P*:Group 1 vs Group 2, †: Group 1 vs Group 3, §: Group 2 vsGroup 3

2) Frequency of COVID-19 diagnosis and the frequency ofits potential risk factors (Table 2)

Those who contracted COVID-19 were significantly more commonamong the hospital workers and this was also true for the familymembers and or close friends who had been diagnosed with COVID-19.Groups were roughly balanced regarding the presence of a householdmember of ≥ 65 years and the frequency of active smoking, whileboth risk factors were slightly higher in teachers/academic staffgroup. Patients with RD had the highest frequency of comorbid andpsychiatric diseases, whereas teachers/academic staff had thelowest.

Table2. COVID–19 diagnosis and risk factors for COVID-19

	Group1 Patientswith RD (n=771)	Group2 Hospitalworkers (n=535)	Group3 Teachers/academic staff(n=917)	P
Diagnosedwith COVID-19 (n %)	4(0.5)	14(2.6)	3(0.3)	<0.0001*§
Familyrelative or close friends diagnosed with COVID-19, n(%)	92(11.9)	174(32.8)	88(9.7)	<0.0001*†§
Presenceof a relative in the household ≥ 65 years of age, n(%)	367(48.0)	274(51.6)	525(57.6)	<0.0001†
Smokingstatus, n (%)
Active	290(37.8)	201(37.8)	390(42.8)	<0.0001*†
Quit	125(16.3)	40(7.5)	74(8.1)
Never	353(46.0)	291(54.7)	447(49.1)
Prrsenceof comorbid diseases, n (%)	257(33.3)	75(14.0)	122(13.3)	<0.0001*†
History ofpsychiatric disorders or psychiatric drug use for at least threemonths, n (%)	247(32.0)	129(24.1)	140(15.3)	<0.0001*†§

P *Group 1 vs Group 2, † : Group 1 vs Group 3, §: Group 2 vs Group 3

3) Socio-demographic characteristics and response to theoutbreak between different types of rheumatic diseases (Table3)

Patients with RA were the oldest, while patients with FMF werethe youngest among the subgroups. Males were in the majority in SpAand BS, whereas females predominated in the remaining subgroups. Itseemed that significant number of patients strictly adhered to stayhome warnings (> 89 %), while adherence was a bit less in theSpA and BS subgroups (82.4 % and 81.3 %, respectively). This wasalso true for being obliged to go out for work which wassignificantly higher among patients with SpA (40.6 %) and BS (44.7%), compared to the rest of the subgroups. Most of the patients inall subgroups (≥ 74%) were satisfied with the medical support orinformation about COVID-19. After the outbreak, a small percentageof the patients who had a scheduled out-patient visit (n = 382)attended the outpatient-clinic ‘as it was before’ (14.4%) and thiswas similar among all subgroups. The remaining either ‘did not wantto come’ (42.7%), ‘wanted to come but could not contact anyone inthe hospital’ (15.4%), or was advised to postpone their visits(27.5%). A significant number of patients continued theirmedications (582/750; 77.6%), while only 16.4% (123/750) decreasedor skipped their dose and 6.0% (45/750) stopped taking them. Thistrend was almost similar among all study groups, except patientswith SpA whose 53.7 % discontinued or stopped taking theirmedications.

Table3.Socio-demographic characteristics and immediate behavior changeafter the outbreak in different types of rheumaticdiseases

	Total n =771	RA n=131	CTDn=171	SpA n=102	BS n=171	FMF n=79	Vasculitisn=117	P
Age, meanage ± SD, years	42.8 ±12.7	51.0±13.3	43.0±12.6	41.3±10.6	40.9±10.0	31.5±10.0	45.0±12.2	<0.0001
Male/Female, n (%)	245/526	21/110	18/153	58/44	108/63	21/58	19/98	<0.0001
Strictcompliance with ‘stay home’ warnings’, n(%)	678(88.2)	122(93.8)	152(89.4)	84(82.4)	139(81.3)	72(91.1)	109(93.2)	0.002
Need to goout for work, n (%)	213(27.8)	21(16.0)	30(17.5)	41(40.6)	76(44.7)	24(30.8)	21(18.1)	<0.0001
Receivedenough medical support or information, n(%)	591(72.7)	103(78.6)	131(76.6)	78(76.5)	129(75.4)	63(79.7)	87(74.4)	0.675
Attendedthe outpatient clinic, n (%)*
Regularly, as it was before	55(14.4)	6(10.7)	5(6.2)	10(20.8)	14(16.1)	4(12.1)	16(20.8)	0.119
Did not want to	163(42.7)	26(46.4)	35(43.2)	16(33.3)	32(36.8)	18(54.5)	36(46.8)
Wanted to but could not contactanyone	59(15.4)	9(16.1)	11(13.6)	10(20.8)	13(14.9)	7(21.2)	9(11.7)
Was advised not to come	105(27.5)	15(26.8)	30(37.0)	12(25.0)	28(32.2)	4(12.1)	16(20.8)
Continuedmedications**
Yes, as it was before	582(77.6)	104(81.3)	142(85.5)	44(46.3)	132(79.5)	67(84.8)	93(80.2)	<0.0001
Yes but decreased or skipped thedose	123(16.4)	19(14.8)	21(12.7)	28(29.5)	22(13.3)	12(15.2)	21(18.1)
No, stopped taking them	45(6.0)	5(3.9)	3(1.8)	23(24.2)	12(7.2)	0	2(1.7)

RA:rheumatoid arthritis; CTD: connective tissue diseases; SpA:Spondylarthropathies; BS: Behçet’s syndrome; FMF: familialMediterranean fever;

SD:standard deviation; *n =382; ** n= 750

4) Medications that are decreased in dosage/ skipped orstopped (Table 4)

Biological DMARDs were the most frequent drugs which patientsdecreased their dose, skipped or stopped taking (anti-IL-1 agents:40 %, anti-TNF agents: 34.6 %, interferon: 33.3 %, tocilizumab 29.2%, rituximab: 6.7 %). Prednisolone (low dose), hydroxychloroquine,azathioprine, methotrexate, leflunomide, colchicine andsulfasalazine were least likely (≤10 % for each drug) to be skippedor stopped.

A total of 753 patients responded to the ‘Plaquenil’ question. Agreat majority of the patients (539/753; 71.6%) have not attemptedto take hydroxychloroquine for protective measures while 1.1%(8/753) had started taking it recently and 2.5% (19/753) werewilling to take it despite having hesitations. The remaining(187/753; 24.8%) were already regular users of hydroxychloroquine.

Table4. The prescribed drugs and those whose doses were either skippedor stopped

Drugs	Dosedecreased, skipped or stopped, n	Totalprescribed, n	%
BiologicalDMARDs
Anti-tumor necrosis factoragents	66	191	34.6
Tocilizumab	7	24	29.2
Anti-IL-1 agents	6	15	40.0
Rituximab	5	75	6.7
Interferon	3	9	33.3
Non-biologicalDMARDs
Azathioprine	18	187	9.6
Methotrexate	12	149	8.0
Leflunomide	2	26	7.7
Mycophenolate mofetil/sodium	6	29	20.7
Sulfasalazine	6	69	8.7
Others
Corticosteroids	32	340	9.4
Hydroxychloroquine	21	198	10.6
Colchicine	19	194	9.8
Cyclophosphamide	3	12	25.0

DMARDs:disease-modifying anti-rheumatic drugs

5) Psychological symptoms (Table 5)

Both HADS and IES-R exhibited high internal consistency;Cronbach’s alpha coefficients were 0.896 and 0.893, respectivelyfor HADS and IES-R.

Anxiety, depression and IES-R scores of the patients with RD(Group 1) were found similar when compared to that of theteachers/academic staff (Group 3), whereas significantly lower whencompared with that of the hospital workers (Group 2). The sameholds true for all sub-dimensions of IES-R, except avoidance whichwas evenly distributed among the study groups while being slightlyhigher in Group 3. Although the hospital workers had the highestscores in both HADS and IES-R as well as the highest frequencyrates of anxiety (39.8 %), depression (61.6 %) and PTS (46.4%) asdetermined by the cut-off values, they still thought significantlyless that the outbreak was very dangerous. The frequency of sleepproblems in patients with RD was significantly higher than that ofthe teachers/academic staff, but then again, significantly lowerthan that reported in the hospital workers. These results were alsotrue when we excluded those with a previous history of psychiatricdisorder or the use of psychiatric drug for at least three months.

Additionally, all psychological symptoms were similar infrequency among the subgroups in Group 1 and between medical andnon-medical hospital workers in Group 2 (data not shown).

It has to be noted that anxiety, depression and PTS symptomsabove the severity threshold for clinical concern were notinfrequent in Group 1 and Group 3. They had a prevalence of 19.6%,42.8% and 28.4% respectively, in Group 1 and a prevalence of 23.1%,42.7 % and 29.1% respectively, in Group 3. The same holds true forthe sleep problems.

Table5. Psychiatric symptoms

	Group1 Patientswith RD n=771	Group2 Hospitalworkers n =535	Group3 Teachers/Academic staff n=917	P
HADAnxiety level, mean±SD	7 ±4.4	9.3 ±4.9	7.4 ±4.3	<0.001*§
≥11 cutoff, n (%)	148(19.6)	200(39.8)	202(23.1)	<0.001*§
HADDepression level, mean±SD	6.9 ±4.2	8.7 ±4.4	6.8 ±3.9	<0.001*§
≥8 cutoff, n (%)	324(42.8)	309(61.6)	373(42.7)	<0.001*§
IES-R(total), mean±SD	25.5 ±14.2	31.3 ±16	26.3 ±13.4	<0.001*§
Intrusion	7.7 ±6.2	11.1 ±7.6	8.2 ±5.9	<0.001*§
Avoidance	11.3 ±5	11.5 ±5.2	12.1 ±4.9	0.012†
Hyperarousal	6.5 ±5.5	8.6 ±5.8	6.1 ±5	<0.001*§
PTS cutoff (≥33)	210(28.4)	219(46.4)	232(29.1)	<0.001*§
Sleepdisturbances, n (%)
Trouble staying asleep	175(23.7)	139(29.4)	128(16.0)	<0.001*†§
Trouble falling asleep	176(23.8)	139(29.4)	145(18.2)	<0.001*†§
Is theoutbreak dangerous? n (%)				0.001*§
Very dangerous	681(88.3)	432(81.2)	792(86.6)
Partly or no dangerous at all	90(11.7)	103(18.8)	125(13.4)

RD:rheumatic disease; HADS: Hospital anxiety and depression scale;IES-R: Impact of event scale-revised version; PTS: post-traumaticstress; SD: standard deviation

P:*: Group 1 vs Group 2; †: Group 1 vs Group 3; §: Group 2 vs Group3

Risk factors associated withpsychological symptoms (Table 6)

Of the 13 probable risk factors that were entered to themultivariate logistic regression model, seven variables (groups,age, gender, hours spent watching TV or using social media,diagnosis of COVID-19 in the participant or in a relative or closefriend, presence of a comorbid or psychiatric disorder) were foundto be independently associated with at least one of thepsychological symptoms. According to these analyses, femalegender, working in a hospital, a lower level of education, having achild, living in a crowded family, watching TV or social media for≥ 1 hour, contracting COVID (the participant itself, familyrelative or a close friend), being a smoker (either currently or inthe past), having a comorbid disease, and a history of psychiatricillness increase the odds ratios of psychiatric symptoms during theCOVID-19 outbreak. Although being elderly emerged as an independentprotective risk factor, its effect seems to be considerably weakwith an odds ratio of 0.95 for 1 year increase (CI 95 %: 0.93 -0.96).

Table 6. Effect of socio-demographic variables, resources ofinformation about COVID-19, COVID – 19 diagnosis, and riskfactors for COVID-19 on anxiety, depression andIES-R

		HADS-Anxiety≥11		HADS-Depression≥8		IES-R≥33
		P	OR (95%CI)	p	OR (95%CI)	p	OR (95%CI)
Groups	Group 1 (Patients withRD)	<0.001	0.39 (0.28- 0.54)	<0.001	0.52 (0.39- 0.70)	<0.001	0.45 (0.33- 0.62)
Groups	Group 3 (Teachers/Academicstaff)	<0.001	0.50 (0.37- 0.67)	<0.001	0.52 (0.40- 0.68)	<0.001	0.51 (0.38- 0.69)
Age,one year increase		<0.001	0.95 (0.93- 0.96)	<0.001	0.97 (0.96- 0.98)	<0.001	0.97 (0.95- 0.98)
Gender,being female		<0.001	3.07 (2.29- 4.12)	<0.001	1.57 (1.27- 1.95)	<0.001	2.54 (1.97- 3.29)
Lengthof education , ≤8 years		0.023	1.60 (1.07- 2.40)	0.548	1.11 (0.80- 1.53)	0.002	1.78 (1.24- 2.54)
Maritalstatus, being single		0.190	0.81 (0.58- 1.11)	0.216	0.84 (0.64- 1.10)	0.944	0.99 (0.73- 1.33)
Havechild, yes		0.011	1.59 (1.11- 2.26)	0.283	1.17 (0.88- 1.58)	0.006	1.59 (1.14- 2.20)
Household size, ≥4		0.022	1.32 (1.04- 1.68)	0.262	1.12 (0.92- 1.37)	0.710	0.96 (0.77- 1.20)
Timespent watching TV or using socialmedia, >1hours		0.008	1.44 (1.10- 1.88)	0.010	1.33 (1.07- 1.65)	0.004	1.43 (1.12- 1.83)
Presenceof COVID-19 in the participant, or in family or close friends,Yes		0.005	1.52 (1.13- 2.04)	0.005	1.48 (1.13- 1.95)	0.062	1.31 (0.99- 1.75)
Presenceof a relative in the household ≥ 65 years of age,Yes		0.190	1.17 (0.93- 1.48)	0.033	1.24 (1.02- 1.5)	0.108	1.19 (0.96- 1.48)
Smokingstatus, Active orquit		0.057	1.25 (0.99- 1.58)	0.001	1.39 (1.14- 1.69)	0.004	1.38 (1.11- 1.72)
Comorbiddiseases, Yes		0.006	1.45 (1.11- 1.89)	<0.001	1.67 (1.33- 2.10)	<0.001	1.55 (1.21- 1.99)
Historyof psychiatric disorders or psychiatric drug use for at least threemonths, Yes		<0.001	1.95 (1.50- 2.54)	0.008	1.38 (1.09- 1.74)	0.002	1.49 (1.16- 1.92)

Referencecategories are as follows: Group 2 (Hospital workers) for Groupvariable, one year decrease for age, being male forgender, >8 years for lenght of education, beingmarried for marital status, no for having child, ≤3 forhousehold size, ≤1 hour for time spent watching TV or using socialmedia, no for presence of COVID-19 in the participant orfamily, no for the presence of a relative in the household of ≥ 65years of age, never for smokingstatus, none for comorbid diseases, and none for history ofpsychiatric disorders or psychiatric drug use for at least threemonths.

This cross-sectional web based survey done in a large populationduring the first month of COVID-19 outbreak revealed ratherimportant findings. Faced with an unprecedented situation, patientswith RD tried to adapt expectedly by changing their routine: 85.6 %were unwilling to attend outpatient visits, 88.2% complied strictlywith the restrictions, and 22.4 % discontinued or stopped theirmedications. They seemed to be satisfied with the medicalsupport/information and were unwilling to use ‘hydroxychloroquine’which became increasingly attractive during the COVID-19 outbreak(7). The frequency of the psychological symptoms among patientswith RD was similar to that found among teachers/academic staff,whereas significantly lower than that observed among the hospitalworkers. Nevertheless, anxiety, depression and PTS levels definedas above the severity threshold for clinical concern were notinfrequent in patient’s and teacher’s population. Significantanxiety was reported by one fifth, significant depressive symptomsby a nearly half and PTS by one third of the patients. The sameholds true for the sleep problems, for which more than 20% in thesample reported at least severe or very severe degree of trouble.These findings indicate a significant traumatic impact of COVID-19pandemic and related control measures over psychological well-beingof individuals in a deeply affected city.

Additionally, being female, a lover level of education, having achild, living in a crowded family, a duration of social media/TVexposure above 1 hour per day, participant or someone in thevicinity contracting COVID-19, having a comorbid disease or aprevious psychiatric diagnosis were found to be independent riskfactors associated with the increased PTS, anxiety and depressionin our total study population, in line with the previous reports(6, 13-20).These findings essentially emphasize a higher risk forcertain individuals for psychological distress during the pandemic,based on their pre-trauma features such as gender, education andpsychiatric or medical history, as well as features such as traumadirectness, personal victimization of the individual and closerelatives and the amount of exposure through TV and social media.Of concern, the latter two can become particularly fertile groundsfor anxiety-provoking information and disinformation during apandemic.

We observed that patients with SpA and BS were less likely tocomply strictly to ‘stay home’ restrictions and more likely to goout for work, most probably due to the male predominance andrelatively younger age. Additionally, it was not surprising to seethat SpA subgroup which is usually treated with anti-TNF agents wasthe only subgroup in which regular drug use had been considerablydisrupted. Biological DMARDs were by far the most frequent drugswhich patients skipped or stopped completely. Another importantfinding of the study is that patients in the great majority quitepossibly consider low dose prednisolone and many of thenon-biological DMARDs ‘safe’ since the discontinuation rate wasonly < 10% for each of the drug.

We would have expected that patients with RD to have higherlevels of anxiety or depression because of the several potentialrisk factors. Much to our surprise, the level of theirpsychological distress did not significantly differ from that ofthe teachers/academic staff, a group which we assumed to beunlikely to be exposed to trauma that the frontline healthcareworkers are encountering, and which therefore would show lesssevere distress. This finding may suggest that patients with RDmight have developed a positive adaptation to the stressors relatedto having a chronic disease with unpredictable exacerbations andremissions for many years, and became more resilient to furtherstressors concerning health. Compared to teachers and academicstaff group, patients with RD reported having more sleep problems,which in our opinion could be related with increased frequency ofpsychiatric disorders, problems of pain and/or increased frequencyof regular prednisoloneuse.

In line with what we have found, health workers had highprevalence rates of severe insomnia, anxiety, depression,somatization, and obsessive-compulsive symptoms during the ongoingCOVID-19 pandemic, as reported in several studies (3-6, 15,20-21).This was also evident with previous outbreaks such as thatof SARS and MERS-Cov (22-25). The reluctance of hospital workers toparticipate in our study as observed by the lower response ratecould be also interpreted as a reflection of their low mood.Interestingly, contrary to what have been reported, the level ofpsychological distress did not differ between medical andnon-medical hospital workers in our survey (15).

This study has several limitations. We were not able to evaluatethe psychological state before the outbreak. It is difficult tomake causal inferences. There is possibility of selection bias. Thesampling of our study was voluntary; therefore those who had beenseverely affected mentally may not be available for the evaluation.Due to the socio-cultural differences, our results may not begeneralized. Absence of a disease control group could be anotherlimitation. Finally, while we think that our results reflect theimmediate response of the population as the survey was done 3 weeksafter the outbreak, it could be rather difficult to discriminatethe effect of the lockdown itself from that of the COVID-19outbreak.

During the first month of the COVID-19 outbreak, most of thepatients with RD could not attend outpatient visits. About onefifth discontinued or stopped their medications. The level ofpsychiatric distress observed among patients with RD was comparableto that among teacher’s/academic staff, whereas significantly lesswhen compared to that among hospital workers. Yet, significantanxiety reported by a fifth, depression by nearly a half, and PTSby a third of both patient’s and teacher’s population were ofconsiderable concern indicating significant traumatic impact ofCOVID-19 pandemic on general population. Additionally, femalegender, lower level of education, living in a crowded family,social media exposure, contracting COVID, smoking, having acomorbid disease, or a psychiatric disorder were found to beindependently associated with psychiatric symptoms during theCOVID-19 outbreak.

Conflict of interest: The authors declare nocompeting interests.

Funding source: The authors have not receivedany financial support.

Acknowledgments: The authors thank SerdalUgurlu, MD, Selma Karagoz, MD, Sinem Nihal Esatoglu, MD,Yesim Ozguler, MD, Ali Serdar Seker, Dilsen Cevirgen, Unal Sarıtac,Sultan Tura, Kader Bilgen and Adem Cetin for their effort inreaching the participants and Edward Tony Karakas for Englishediting.

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The Psychological State and Changes in the Routine of the Patients with Rheumatic Diseases during the First Month of the Lockdown of the Coronavirus Disease (COVID-19) Outbreak in Turkey

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