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Effect of health anxiety on disease perception and treatment compliance in elderly patients during the COVID-19 pandemic in Turkey

      Highlights

      • Elderly are psychologically affected by COVID-19.
      • COVID-19 has significantly affected the health anxiety and perception of illness of the elderly.
      • The treatment of elderly people with chronic diseases has been affected in the COVID-19 pandemic.

      Abstract

      Purpose

      This study aimed to determine the effect of health anxiety experienced by elderly individuals during the coronavirus disease 2019 (COVID-19) pandemic on their disease perception and treatment compliance.

      Design and methods

      This was a descriptive, cross-sectional study conducted between November 2020 and March 2021. The research data was collected using the Patient Information Form, Health Anxiety Scale (HAS), Disease Perception Scale-Short Form (DPS-SF) and Turkish Modified Morisky Treatment Compliance Scale (MMTCS).

      Results

      Of the 401 study participants, 63.1% were in the 65–69 years age group. The mean HAS, DPS-SF and MMTCS motivation and knowledge level sub-dimension scores of the participants were 18.73 ± 8.87, 54.24 ± 9.98, 1.28 ± 0.74 and 2.04 ± 0.92, respectively.

      Conclusion

      The results of this study showed that the health anxiety and disease perception scores were high among elderly individuals during the COVID-19 pandemic, which hindered their treatment compliance.

      Keywords

      Introduction

      Infectious diseases have had significant impact on human history, and despite scientific and technological advancements they continue to do so in current times as well (
      • Guan W.J.
      • Ni Z.Y.
      • Hu Y.
      • Liang W.H.
      • Ou C.Q.
      • He J.X.
      • Liu L.
      • Shan H.
      • Lei C.L.
      • Hui D.
      • Du B.
      • Li L.J.
      • Zeng G.
      • Yuen K.Y.
      • Chen R.C.
      • Tang C.L.
      • Wang T.
      • Chen P.Y.
      • Xiang J.
      China Medical Treatment Expert Group for COVID-19
      Clinical characteristics of coronavirus disease 2019 in China.
      ). The coronavirus disease 2019 (COVID-19) is a highly contagious viral disease that emerged in China in 2019 and spread rapidly, continuing to have grave economic, cultural, social and psychological effects to date (
      • Guan W.J.
      • Ni Z.Y.
      • Hu Y.
      • Liang W.H.
      • Ou C.Q.
      • He J.X.
      • Liu L.
      • Shan H.
      • Lei C.L.
      • Hui D.
      • Du B.
      • Li L.J.
      • Zeng G.
      • Yuen K.Y.
      • Chen R.C.
      • Tang C.L.
      • Wang T.
      • Chen P.Y.
      • Xiang J.
      China Medical Treatment Expert Group for COVID-19
      Clinical characteristics of coronavirus disease 2019 in China.
      ;
      • Onder G.
      • Rezza G.
      • Brusaferro S.
      Case-fatality rate and characteristics of patients dying in relation to COVID-19 in Italy.
      ;
      • Saladino V.
      • Algeri D.
      • Auriemma V.
      The psychological and social impact of COVID-19: New perspectives of well-being.
      ). As has been observed in several previous outbreaks, such as severe acute respiratory syndrome (SARS), Ebola and influenza, elderly individuals were the most affected by the COVID-19 pandemic (
      • Dymecka J.
      • Gerymski R.
      • Machnik-Czerwik A.
      • Derbis R.
      • Bidzan M.
      Fear of COVID-19 and life satisfaction: The role of the health-related hardiness and sense of coherence.
      ;
      • Hasöksüz M.
      • Kiliç S.
      • Saraç F.
      Coronaviruses and SARS-COV-2.
      ;
      • Onder G.
      • Rezza G.
      • Brusaferro S.
      Case-fatality rate and characteristics of patients dying in relation to COVID-19 in Italy.
      ). According to Brooke and Jackson, 3.6% of individuals aged 60 years and above and 8%–14.8% of individuals in their 70s and 80s are at a risk of death from COVID-19 (
      • Brooke J.
      • Jackson D.
      Older people and COVID-19: Isolation, risk and ageism.
      ). Elderly individuals have constituted the high-risk group since the beginning of the pandemic, and similar to the measures taken in several countries, curfews in Turkey were first geared towards the elderly population, causing them to face numerous problems (
      • Kılınçel O.
      • Muratdağı G.
      • Aydın A.
      • Oksuz A.
      • Buyukdereli Atadağ Y.
      • Etcioglu E.
      • Ozen F.
      The anxiety and loneliness levels of geriatric population in-home quarantine during COVID-19 pandemic in Turkey.
      ;
      • Verity R.
      • Okell L.C.
      • Dorigatti I.
      • Winskill P.
      • Whittaker C.
      • Imai N.
      • Cuomo-Dannenburg G.
      • Thompson H.
      • Walker P.
      • Fu H.
      • Dighe A.
      • Griffin J.T.
      • Baguelin M.
      • Bhatia S.
      • Boonyasiri A.
      • Cori A.
      • Cucunubá Z.
      • FitzJohn R.
      • Gaythorpe K.
      • Green W.
      • Ferguson N.M.
      Estimates of the severity of coronavirus disease 2019: A model-based analysis.
      ). Literature data reports that the fear of COVID-19 infection reduces the quality of life (
      • Satici B.
      • Gocet-Tekin E.
      • Deniz M.E.
      • Satici S.A.
      Adaptation of the fear of COVID-19 scale: Its association with psychological distress and life satisfaction in Turkey.
      ), negatively affects the well-being of individuals (
      • Erdoğdu Y.
      • Koçoğlu F.
      • Sevim C.
      An investigation of the psychosocial and demographic determinants of anxiety and hopelessness during COVID-19 pandemic.
      ;
      • Li S.
      • Wang Y.
      • Xue J.
      • Zhao N.
      • Zhu T.
      The impact of COVID-19 epidemic declaration on Psychological Consequences: A study on active Weibo users.
      ) and leads to mental health problems, such as stress, depression and anxiety (
      • Saladino V.
      • Algeri D.
      • Auriemma V.
      The psychological and social impact of COVID-19: New perspectives of well-being.
      ).
      A Hong Kong study conducted on elderly individuals reported that the participants felt anxious and hopeless regarding the COVID-19 pandemic, which affected their daily lives and increased their health anxiety (
      • Kwok K.O.
      • Li K.K.
      • Chan H.
      • Yi Y.Y.
      • Tang A.
      • Wei W.I.
      • Wong S.
      Community responses during early phase of COVID-19 epidemic,Hong Kong.
      ). Health anxiety is a psychological experience characterized by a perceived threat to one's health, which triggers the symptoms of physical and emotional anxiety (
      • Aydemir Ö.
      • Kirpinar İ.
      • Sati T.
      • Uykur B.
      • Cengisiz C.
      Reliability and validity of the Turkish version of the Health Anxiety Inventory.
      ). Increased health anxiety negatively affects disease perception and hinders the adaptability of the individual regarding the process of their treatment compliance (
      • Aalto A.M.
      • Heijmans M.
      • Weinman J.
      • Aro A.R.
      Illness perceptions in coronary heart disease. Sociodemographic, illness-related, and psychosocial correlates.
      ). Adaptability refers to the fulfilment of lifestyle changes (
      • Krousel-Wood M.A.
      • Muntner P.
      • Islam T.
      • Morisky D.E.
      • Webber L.S.
      Barriers to and determinants of medication adherence in hypertension management: Perspective of the cohort study of medication adherence among older adults.
      ) and treatment compliance concerns attending all health check-ups, regularly participating in the treatment programme, using the prescribed drugs without interruption and applying the recommended behavioral patterns in daily life (
      • Demirkol M.E.
      • Tamam L.
      • Evlice Y.E.
      • Karaytuğ M.O.
      Adherence to the treatment in psychiatric patients.
      ). The restrictions introduced during the COVID-19 pandemic hampered the elderly individuals' ability to leave their homes, attend health check-ups and continue regular treatment (
      • Chhetri J.K.
      • Chan P.
      • Arai H.
      • Chul Park S.
      • Sriyani Gunaratne P.
      • Setiati S.
      • Assantachai P.
      Prevention of COVID-19 in older adults: A brief guidance from the International Association for Gerontology and Geriatrics (IAGG) Asia/Oceania region.
      ), in turn significantly affecting their treatment compliance. Furthermore, non-compliance with treatment increases the severity of the disease and cost of treatment and reduces the patients' faith in treatments (
      • Demirkol M.E.
      • Tamam L.
      • Evlice Y.E.
      • Karaytuğ M.O.
      Adherence to the treatment in psychiatric patients.
      ).
      The aim of this study was to assess the health anxiety experienced by elderly individuals during the COVID-19 pandemic and evaluate the effect of health anxiety on their disease perception and treatment compliance. The following research questions were proposed for this purpose:
      • What is the health anxiety level of elderly individuals?
      • What is the disease perception level of elderly individuals?
      • What is the treatment compliance level of elderly individuals?
      • Is there a relationship between the socio-demographic characteristics of elderly individuals and their health anxiety levels, disease perception and treatment compliance?
      • Are the health anxiety levels of elderly individuals affected by disease perception and treatment compliance?

      Methods

      Study design and sample

      This research was designed as a descriptive and cross-sectional study. The study population comprised 7,550,000 elderly individuals who were registered in the . This study aimed to cover all the elderly individuals living in Turkey. Using power analysis, the minimum sample size was calculated as 384 with a 5% margin of error and 95% confidence level. Owing to the Covid-19 pandemic, the participant data was collected via online surveys (Google Forms). The study purpose was outlined in the title section of the online forms. The participants were informed that the data would be used in a scientific study, and written informed consent was obtained from all the participants. The study sample consisted of 401 elderly participants who agreed to the study. The research data were collected between November 2020 and March 2021. It took the participants approximately 15–20 min to fill out the online form.

      Data collection tools

      The Patient Information Form, Health Anxiety Scale (HAS), Disease Perception Scale-Short Form (DPS-SF) and Turkish Modified Morisky Treatment Compliance Scale (MMTCS) were used for data collection.

      Patient Information Form

      This form was developed by the researchers in accordance with the literature. The form contained 18 questions about the socio-demographic characteristics (marital status, age, gender, etc.) and disease status (chronic diseases, COVID-19 positivity, COVID-19 knowledge level, etc.) of the participants (
      • Demirkol M.E.
      • Tamam L.
      • Evlice Y.E.
      • Karaytuğ M.O.
      Adherence to the treatment in psychiatric patients.
      ;
      • Hasöksüz M.
      • Kiliç S.
      • Saraç F.
      Coronaviruses and SARS-COV-2.
      ;
      • Li S.
      • Wang Y.
      • Xue J.
      • Zhao N.
      • Zhu T.
      The impact of COVID-19 epidemic declaration on Psychological Consequences: A study on active Weibo users.
      ;
      • Xie J.
      • Tong Z.
      • Guan X.
      • Du B.
      • Qiu H.
      • Slutsky A.S.
      Critical care crisis and some recommendations during the COVID-19 epidemic in China.
      ).

      Health Anxiety Scale

      This scale was developed by
      • Salkovskis P.M.
      • Rimes K.A.
      • Warwick H.M.
      • Clark D.M.
      The Health Anxiety Inventory: Development and validation of scales for the measurement of health anxiety and hypochondriasis.
      . The Turkish validity and reliability study was conducted by
      • Aydemir Ö.
      • Kirpinar İ.
      • Sati T.
      • Uykur B.
      • Cengisiz C.
      Reliability and validity of the Turkish version of the Health Anxiety Inventory.
      . The HAS is a self-report scale comprising 18 items. Each item is scored between 0 and 3. The highest score that can be obtained is 54, with higher scores indicating high levels of health anxiety (
      • Aydemir Ö.
      • Kirpinar İ.
      • Sati T.
      • Uykur B.
      • Cengisiz C.
      Reliability and validity of the Turkish version of the Health Anxiety Inventory.
      ;
      • Salkovskis P.M.
      • Rimes K.A.
      • Warwick H.M.
      • Clark D.M.
      The Health Anxiety Inventory: Development and validation of scales for the measurement of health anxiety and hypochondriasis.
      ). The Cronbach's alpha coefficient of the Turkish version was found to be 0.91 (
      • Aydemir Ö.
      • Kirpinar İ.
      • Sati T.
      • Uykur B.
      • Cengisiz C.
      Reliability and validity of the Turkish version of the Health Anxiety Inventory.
      ). In the present study, the Cronbach's alpha coefficient was 0.91.

      Disease Perception Scale-Short Form

      This scale was developed by
      • Broadbent E.
      • Petrie K.J.
      • Main J.
      • Weinman J.
      The brief illness perception questionnaire.
      and the Turkish validity and reliability study was conducted by
      • Kocaman N.
      • Özkan M.
      • Armay Z.
      • Özkan S.
      Hastalık Algısı Ölçeğinin Türkçe uyarlamasının geçerlilik ve güvenilirlik çalışması.
      . The DPS-SF consists of nine items regarding the cognitive and emotional representation of disease perception. Each item is scored between 0 and 10. The total score that can be obtained ranges between 0 and 80. Higher scores indicate higher disease perception (
      • Broadbent E.
      • Petrie K.J.
      • Main J.
      • Weinman J.
      The brief illness perception questionnaire.
      ;
      • Kocaman N.
      • Özkan M.
      • Armay Z.
      • Özkan S.
      Hastalık Algısı Ölçeğinin Türkçe uyarlamasının geçerlilik ve güvenilirlik çalışması.
      ). The Cronbach's alpha coefficient of DPS-SF was reported by
      • Broadbent E.
      • Petrie K.J.
      • Main J.
      • Weinman J.
      The brief illness perception questionnaire.
      as 0.82. In the present study, the Cronbach's alpha coefficient was 0.83.

      Turkish Modified Morisky Treatment Compliance Scale

      This scale was developed by
      • Morisky D.E.
      • Green L.W.
      • Levine D.M.
      Concurrent and predictive validity of a self-reported measure of medication adherence.
      and consists of eight items. The Turkish validity and reliability study was conducted by
      • Vural B.
      • Acar Ö.T.
      • Topsever P.
      • Filiz T.M.
      Reliability and validity of Turkish Version of Modified Morisky Scale.
      . The Turkish MMTCS consists of six items. The scale has two sub-dimensions: motivation and knowledge level. All items are ‘yes/no’ questions. Yes corresponds to 0 points and no to 1 point. A sub-dimension score of 0 or 1 indicates low motivation and knowledge levels, whereas a score above 1 indicates high motivation and knowledge levels. In the present study, the Cronbach's alpha coefficient for the overall scale was 0.51, 0.55 for the motivation sub-dimension and 0.59 for the knowledge level sub-dimension.

      Ethical considerations

      Ethical approval was obtained from the Scientific Research Ethics Committee of the relevant university (decision no. 2020/111). The individuals were asked to ‘accept’ or ‘reject’ participating in the study by selecting the appropriate option on the online forms (Google Forms). The study was conducted in accordance with the principles of the Helsinki Declaration. Written permissions were obtained via e-mail from the authors of the scales used in the study.

      Data analysis

      The research data was analysed using the SPSS (Windows 25.0) programme. Descriptive statistics were presented as number, percentage, minimum and maximum values, median, mean and standard deviation. Conformity to normal distribution was evaluated using normality tests and Kurtosis–Skewness values. The scale scores were found to be not normally distributed. Hence, Mann–Whitney U test was used to compare the quantitative variables between the two groups and Kruskal–Wallis H test was used to compare the quantitative variables between more than two groups. In cases with significant differences, Bonferroni correction was performed to determine the source of the difference. The relationship among the continuous variables was assessed by Spearman correlation analysis (
      • George D.
      • Mallery P.
      IBM SPSS statistics 25 step by step: A simple guide and reference.
      ).

      Results

      The demographic characteristics and COVID-19-related information of the participants is shown in Table 1. Of the 401 participants, 63.1% were 65–69 years old, 54.6% were women, 57.6% were married, 63.1% were literate and 82.5% were retired. Regarding the COVID-19-related data, 44.9% of the participants had been tested for COVID-19, 14.7% had been diagnosed with COVID-19, 78.6% had at least one relative who was diagnosed with COVID-19 and 36.9% stated that their daily lives were significantly impacted by COVID-19. During the pandemic, 37.2% of the participants stated that they were unable to do activities/walk, 19.0% could not go to the hospital for health check-ups, 25.2% expressed concerns regarding having to stay away from their family and loved ones and 18.0% reported an increase in psychological problems. Furthermore, 70.3% of the participants reported that COVID-19 affected their health and treatment process and 72.6% reported experiencing anxiety concerning their own health as well as the health of their loved ones during the pandemic (Table 1).
      Table 1Demographic characteristics and COVID-19-related information of the participants (n = 401).
      Variablesn%COVID-19-related informationn%
      Age65–69 years25363.1Getting a COVID 19 testYes18044.9
      70–74 years9623.9No22155.1
      75–79 years307.5Getting a diagnosis of COVID-19Yes5914.7
      Above 80 years225.5No34285.3
      GenderFemale21954.6Having a family history of COVID-19Yes31578.6
      Male18245.4No8621.4
      Marital statusMarried23157.6Impact of COVID-19 on daily lifeNone4912.2
      Single174.2Somewhat20450.9
      Widowed15338.2Quite14836.9
      EducationLiterate25363.1Feelings of COVID-19None5213.0
      Primary/secondary school9623.9Fear266.5
      High school338.2Anxiety12230.4
      Graduate or postgraduate194.7Hopelessness266.5
      Working statusWorker123.0Fear of death/loss17543.6
      Retired33182.5Worrying about your own/loved ones' healthYes29172.6
      Unemployed5814.5No153.7
      Sometimes9523.7
      The mean HAS, DPS-SF and MMTCS motivation and knowledge level sub-dimension scores of the participants were 18.73 ± 8.87, 54.24 ± 9.98, 1.28 ± 0.74 and 2.04 ± 0.92, respectively.
      No statistically significant correlation was found between the total HAS and DPS-SF scores; however, a statistically significant positive correlation between the total HAS and MMTCS knowledge sub-dimension scores was observed by correlation analysis (r = 0.123; p < 0.05) (Table 2).
      Table 2The correlation between the scales.
      HASDPS-SFTurkish MMTCS motivation sub-dimensionTurkish MMTCS knowledge sub-dimension
      HAS1.000
      DPS-SF0.0141.000
      Turkish MMTCS motivation sub-dimension0.083−0.0641.000
      Turkish MMTCS knowledge sub-dimension0.123*−0.119*0.123*1.000
      HAS: Health Anxiety Scale; DPS-SF: Disease Perception Scale-Short Form; Turkish MMTCS: Turkish Modified Morisky Treatment Compliance Scale. * Correlation is significant at the 0.05 level (two-tailed)
      Data on the relationship between the socio-demographic characteristics of the elderly participants and their scale scores are presented in Table 3. A significant difference was found in MMTCS sub-dimension scores with regard to participant age (p = 0.02). It was found that the HAS scores of the unemployed participants were higher compared with the retired participants (p = 0.014). The MMTCS motivational sub-dimension scores of the unemployed participants were higher compared with the working participants (p = 0.002). The MMTCS knowledge level sub-dimension scores of the retired participants were higher compared with the working and unemployed participants (p = 0.001) (Table 3).
      Table 3Comparison of descriptive characteristics of elderly and HAS, DPS-SF, Turkish MMTCS scores.
      Variable (n = 401)HASDPS-SFTurkish MMTCS
      Motivation sub-dimensionKnowledge sub-dimension
      X¯ ± SDStatistical analysisX¯ ± SDStatistical analysisX¯ ± SDStatistical analysisX¯ ± SDStatistical analysis
      Age65–701 years19.02 ± 8.97KW = 1.344 p = 0.71954.98 ± 10.8KW = 5.837 p = 0.1201.29 ± 0.76KW = 2.640

      p = 0.451
      1.93 ± 0.98KW = 9.856 p = 0.020

      1 < 2
      71–752 years17.64 ± 7.9553.32 ± 8.171.21 ± 0.632.26 ± 0.71
      76–803 years19.53 ± 8.8852.00 ± 9.061.33 ± 0.762.30 ± 0.84
      Above 80 years419.09 ± 11.4652.86 ± 7.761.50 ± 0.802.00 ± 0.98
      GenderFemale19.81 ± 9.49MWU = −1.803

      p = 0.071
      54.83 ± 10.07MWU = −1.628

      p = 0.103
      1.32 ± 0.76MWU = −1.140

      p = 0.254
      1.97 ± 0.93MWU = −1.93

      p = 0.054
      Male17.43 ± 7.8853.54 ± 9.851.24 ± 0.692.13 ± 0.90
      Marital statusMarried18.95 ± 8.98KW = 0.792

      p = 0.673
      53.53 ± 10.48KW = 3.058

      p = 0.217
      1.32 ± 0.77KW = 2.313

      p = 0.315
      2.04 ± 0.96KW = 1.856

      p = 0.395
      Single18.88 ± 7.8457.24 ± 11.131.06 ± 0.831.71 ± 1.10
      Widowed18.38 ± 8.8454.98 ± 8.961.25 ± 0.652.08 ± 0.83
      EducationLiterate118.57 ± 9.11KW = 1.906

      p = 0.592
      54.51 ± 9.09KW = 6.979

      p = 0.073
      1.24 ± 0.59KW = 2.963

      p = 0.397
      2.17 ± 0.81KW = 20.773

      p = 0.0001

      4 < 1
      Primary/secondary school218.81 ± 7.8955.49 ± 9.661.34 ± 0.791.98 ± 1.01
      High school318.97 ± 10.6651.76 ± 14.631.27 ± 1.041.67 ± 1.05
      Graduate or postgraduate420.00 ± 7.3548.63 ± 11.301.58 ± 1.261.21 ± 1.08
      Working statusWorker119.42 ± 5.99KW = 8.539

      p = 0.014

      2 < 3
      50.58 ± 8.55KW = 3.062

      p = 0.216
      0.67 ± 0.78KW = 12.448

      p = 0.002

      1 < 3
      0.67 ± 0.89KW = 58.907

      p = 0.001
      Retired217.91 ± 8.2154.2 ± 9.991.28 ± 0.72.23 ± 0.75
      Unemployed323.28 ± 11.455.26 ± 10.11.41 ± 0.821.26 ± 1.131 < 2, 3 < 2
      Note: Bold markers in the table show statistically significant relationships; Superscripts 1-4: shows groups; HAS: Health Anxiety Scale; DPS-SF: Disease Perception Scale-Short Form; Turkish MMTCS: Turkish Modified Morisky Treatment Compliance Scale.
      P < 0.05, MWU = Mann Whitney U Testi; KW = Kruskal Wallis H Testi
      The HAS, DPS-SF and MMTCS scores of the participants with respect to COVID-19-related characteristics are presented in Table 4. A significant difference was found in the HAS (p = 0.0001) and MMTCS sub-dimension scores (p = 0.036) between the COVID-19 tested and untested participants. In addition, the HAS scores (p = 0.0001) of the participants who were diagnosed with COVID-19 was found to be higher than that of the participants who were not diagnosed with COVID-19. The HAS (p = 0.0001) and MMTCS sub-dimension scores (p = 0.043) of the participants who had a relative diagnosed with COVID-19 were higher than that of the participants who did not have a relative diagnosed with COVID-19. The motivation sub-dimension scores (p = 0.007) of the participants who had no relative diagnosed with COVID-19 were higher than those with a relative diagnosed with COVID-19. The HAS (p = 0.0001) and MMTCS motivation sub-dimension scores (p = 0.0001) of the participants whose daily lives were seriously affected by COVID-19 were higher than those who were mildly affected or unaffected by the COVID-19 pandemic. The HAS scores of the participants who experienced severe fear due to the COVID-19 pandemic were higher than the other participants. Similarly, the HAS scores were higher among the participants who experienced the fear of death and loss, high levels of anxiety and hopelessness owing to the COVID-19 pandemic than those who were unaffected (p = 0.0001). The DPS-SF scores of the participants who experienced the fear of death and loss related to COVID-19 were higher than those who experienced anxiety (p = 0.006). The MMTCS sub-dimension scores of the participants who experienced the fear of death and loss were higher compared with the participants who were fearful and experienced anxiety regarding COVID-19 (p = 0.0001). The HAS (p = 0001), DPS-SF (p = 0001) and MMTCS motivation (p = 0.012) and knowledge level (p = 0.005) sub-dimension scores were higher among the participants whose sleep patterns were negatively affected by the COVID-19 pandemic compared with the participants whose sleep patterns were unaffected. The HAS (p = 0.0001), DPS-SF (p = 0.004) and MMTCS motivation sub-dimension (p = 0.046) scores were higher among the participants who paid more attention to their health during the COVID-19 pandemic than that of the rest of the participants (Table 4).
      Table 4Comparison of COVID-19–related features of elderly and HAS, DPS-SF, Turkish MMTCS scores.
      Variable (n = 401)HASDPS-SFTurkish MMTCS
      Motivation sub-dimensionKnowledge sub-dimension
      X¯ ± SDStatistical analysisX¯ ± SDStatistical analysisX¯ ± SDX¯ ± SDX¯ ± SDStatistical analysis
      Getting a COVID 19 testYes20.84 ± 8.39MWU = −4.717

      p = 0.0001
      53.68 ± 10.13MWU = −0.615

      p = 0.538
      1.28 ± 0.77MWU = −0.290

      p = 0.772
      2.11 ± 0.98MWU = −2.094

      p = 0.036
      No17.00 ± 8.8954.70 ± 9.851.29 ± 0.701.99 ± 0.87
      Getting a diagnosis of COVID-19Yes24.85 ± 8.73MWU = −5.520

      p = 0.0001
      53.03 ± 10.08MWU = 1.066

      p = 0.286
      1.37 ± 0.95MWU = −0.552

      p = 0.581
      2.12 ± 1.13MWU = −1.834

      p = 0.067
      No17.67 ± 8.4754.45 ± 9.961.27 ± 0.692.03 ± 0.88
      Having a family history of COVID-19Yes19.98 ± 8.89MWU = −5.783

      p = 0001
      54.11 ± 10.19MWU = −0.345

      p = 0.730
      1.25 ± 0.71MWU = −2.028

      p = 0.043
      2.10 ± 0.91MWU = −2.674

      0.007
      No14.15 ± 7.1454.71 ± 9.191.42 ± 0.791.83 ± 0.94
      Impact of COVID-19 on daily lifeNone18.41 ± 5.26KW = 107.06

      p = 0001

      1 < 2 1 < 3 2 < 3
      54.10 ± 8.91KW = 0.517

      p = 0.772
      1.22 ± 0.55KW = 24.537

      p = 0001

      1 < 3 2 < 3
      2.14 ± 0.61KW = 0.726

      p = 0.696
      Somewhat217.97 ± 6.9153.88 ± 10.151.12 ± 0.572.01 ± 0.91
      Quite323.2 ± 9.0954.78 ± 10.111.53 ± 0.902.04 ± 1.02
      Feelings of COVID-19None18.23 ± 5.12KW = 109.934

      p = 0001

      1 < 2 1 < 3 1 < 4

      1 < 5 3 < 2 4 < 2

      5 < 2 3 < 5
      51.81 ± 11.73KW = 14.609

      p = 0006

      3 < 5
      1.31 ± 0.64KW = 6.664

      p = 0.155
      2.06 ± 0.7KW = 26.158

      p = 0001

      3 < 5 2 < 5
      Fear225.46 ± 7.1654.92 ± 10.631.58 ± 0.91.38 ± 1.2
      Anxiety317.59 ± 7.0952.56 ± 9.791.29 ± 0.781.86 ± 0.93
      Hopelessness420.81 ± 8.6552.35 ± 9.841.12 ± 0.712.04 ± 1.04
      Fear of death/loss521.33 ± 8.4856.32 ± 9.111.26 ± 0.692.26 ± 0.84
      Impact of COVID-19 on treatmentYes20.68 ± 8.49MWU = −6.375

      p = 0001
      56.17 ± 9.06MWU = −6.114

      p = 0001
      1.28 ± 0.71MWU = −0.288

      p = 0.77
      2.10 ± 0.90MWU = −2.290

      p = 0.022
      No14.10 ± 8.0249.67 ± 10.581.29 ± 0.781.89 ± 0.95
      Worrying about your own/loved ones' healthYes121.00 ± 8.39KW = 74.947

      p = 0001

      2 < 1 3 < 1
      54.72 ± 10.19KW = 3.497

      p = 0.174
      1.30 ± 0.76KW = 0.789

      p = 0.674
      2.06 ± 0.94KW = 2.209

      p = 0.331
      No29.73 ± 5.7452.20 ± 11.401.20 ± 0.771.73 ± 1.03
      Sometimes313.19 ± 7.2653.09 ± 8.991.24 ± 0.652.03 ± 0.83
      Having sleep problemsYes122.30 ± 8.61KW = 77.129

      p = 0001

      2 < 1 3 < 1
      56.52 ± 9.38KW = 21.159

      p = 0001

      2 < 1 3 < 1
      1.32 ± 0.75KW = 8.784

      p = 0.012

      2 < 1. 3 < 1
      2.12 ± 0.95KW = 10.650

      p = 005

      2 < 1
      No212.14 ± 7.8649.86 ± 11.221.47 ± 0.941.78 ± 0.93
      Sometimes317.63 ± 7.2753.64 ± 9.151.14 ± 0.532.07 ± 0.86
      The state of caring about healthYes20.38 ± 8.35MWU = −8.408

      p = 0.0001
      54.83 ± 10.01MWU = −2.847

      p = 0.004
      1.32 ± 0.76MWU = −2.000

      p = 0.046
      2.03 ± 0.95MWU = −0.106

      p = 0.916
      No10.65 ± 6.6451.34 ± 9.371.12 ± 0.562.09 ± 0.77
      Note: Bold markers in the table show statistically significant relationships; Superscripts 1-4: shows groups; HAS: Health Anxiety Scale; DPS-SF: Disease Perception Scale-Short Form; Turkish MMTCS: Turkish Modified Morisky Treatment Compliance Scale.
      P < 0.05, MWU = Mann Whitney U Testi; KW = Kruskal Wallis H Testi.

      Discussion

      Understanding and outlining the effects of psychological factors, such as health anxiety and disease perception, associated with epidemics is imperative for their appropriate management. This research evaluated the effect of health anxiety experienced by elderly individuals during the COVID-19 pandemic on disease perception and treatment compliance.
      While no statistically significant difference was found in the HAS and DPS-SF scores with regard to the age of the elderly individuals participating in the study, a significant difference was found among the MMTCS knowledge level sub-dimension scores (p < 0.05). COVID-19 leads to high morbidity and mortality rates in elderly individuals; thus, the significant difference between the age groups is an expected result. Although not significantly, the health anxiety and disease perception also differs across the age groups of the elderly participants of this study. The participants between the ages of 70 and 74 years demonstrated higher treatment compliance than the individuals aged 69 years and under. The comorbidities and prescribed medication of the study participants also differed.
      • Kılınçel O.
      • Muratdağı G.
      • Aydın A.
      • Oksuz A.
      • Buyukdereli Atadağ Y.
      • Etcioglu E.
      • Ozen F.
      The anxiety and loneliness levels of geriatric population in-home quarantine during COVID-19 pandemic in Turkey.
      reported that home quarantine caused the development of anxiety symptoms in 14%–20% of the geriatric population in Turkey. A study conducted by
      • Tian F.
      • Li H.
      • Tian S.
      • Yang J.
      • Shao J.
      • Tian C.
      Psychological symptoms of ordinary Chinese citizens based on SCL-90 during the level I emergency response to COVID-19.
      in China during the COVID-19 pandemic concluded that people above the age of 50 years tended to demonstrate more obsessive-compulsive symptoms, interpersonal sensitivity, phobic anxiety and psychotic symptoms during the pandemic. In addition,
      • Tian F.
      • Li H.
      • Tian S.
      • Yang J.
      • Shao J.
      • Tian C.
      Psychological symptoms of ordinary Chinese citizens based on SCL-90 during the level I emergency response to COVID-19.
      reported higher health anxiety levels among the elderly population compared with the other age groups.
      Although the HAS, DPS-SF and MMTCS scores were higher among the female participants, the difference between the sexes was not statistically significant (p > 0.05). Previous studies on other epidemics, such as SARS and Ebola, (
      • Affleck W.
      • Carmichael V.
      • Whitley R.
      Men's mental health: Social determinants and implications for services.
      ;
      • Albert P.R.
      Why is depression more prevalent in women?.
      ;
      • Lehmann M.
      • Bruenahl C.A.
      • Löwe B.
      • Addo M.M.
      • Schmiedel S.
      • Lohse A.W.
      • Schramm C.
      Ebola and psychological stress of health care professionals.
      ;
      • Lin C.Y.
      • Peng Y.C.
      • Wu Y.H.
      • Chang J.
      • Chan C.H.
      • Yang D.Y.
      The psychological effect of severe acute respiratory syndrome on emergency department staff.
      ) reported that women were more likely to be adversely affected by an epidemic and experience higher levels of anxiety and depression than men. However, measures such as curfews, which have forced both men and women to stay home, work from home and undertake household responsibilities such as cleaning, meeting the needs of the family members, cooking for more number of people and other chores, have led to an increase in the anxiety levels of both men and women during the COVID-19 pandemic.
      No statistically significant difference was found in the HAS and DPS-SF scores of the elderly individuals with respect to educational level (p > 0.05). This is likely because of the similar social and health restrictions, forced lifestyle changes and visitor restrictions that were implemented for all individuals regardless of education level during the COVID-19 pandemic. However, a statistically significant difference was found in the MMTCS knowledge level sub-dimension scores with respect to the educational status of the elderly (p < 0.05). It was found that the mean knowledge level score of the literate participants was higher than that of the university graduates. In contrary,
      • Tian F.
      • Li H.
      • Tian S.
      • Yang J.
      • Shao J.
      • Tian C.
      Psychological symptoms of ordinary Chinese citizens based on SCL-90 during the level I emergency response to COVID-19.
      and
      • Öztürk Z.
      • Karakuş G.
      • Tamam L.
      Death anxiety in elderly cases.
      reported that increase in the level of knowledge also increased compliance with treatment. Some studies have emphasized that the non-compliance with treatment that is observed in elderly individuals is associated with their individual development and education level (
      • Krousel-Wood M.A.
      • Muntner P.
      • Islam T.
      • Morisky D.E.
      • Webber L.S.
      Barriers to and determinants of medication adherence in hypertension management: Perspective of the cohort study of medication adherence among older adults.
      ). In the present study, the difference in the knowledge level scores between the literate and university graduate elderly participants may have been due to elderly individuals with higher education levels spending longer time on social media during the COVID-19 pandemic and the associated effect of misinformation and confusion. Furthermore, the low number of university graduates participating in the study may have been an additional factor.
      The has recommended certain guidelines regarding the protection of the elderly population from the negative effects of the pandemic, including curfews for individuals above the age of 65 years; the elderly population were asked to remain at home and the elderly individuals who were employed were asked to work from home to reduce the spread of the virus as well as its mortality rate. The difference in the DPS-SF scores with regard to the employment status of the participants was not statistically significant (p > 0.05), indicating that disease perception has increased in all the elderly individuals regardless of their employment status. Furthermore, the HAS scores of the participants who were unemployed were higher than that of the retired participants. Workplace closure, economic difficulties, following protective measures against the COVID-19 pandemic and the lack of access to sheltered households, clothes, cleaning, hygiene and adequate nutritional support directly affected the health anxiety of individuals during the COVID-19 pandemic. A statistically significant difference was found among the MMTCS motivational sub-dimension scores with respect to the employment status of the participants (p < 0.05). The motivation and knowledge level scores were higher among the unemployed participants compared with the working participants. This suggests that the participants do not consider their workplaces to be safe during the COVID-19 pandemic or consider the protective measures taken by their workplaces to be insufficient.
      It was also found that the mean HAS score of the elderly individuals who had been tested for COVID-19 were higher than that of the individuals who had not been tested. This result indicates that the elderly people with high health anxiety are more likely to take precautions regarding their health; however, the higher mortality rate among the elderly population may have a contributing effect as well. Additionally, the emphasis on the elderly and those with chronic diseases as the primary risk group for COVID-19 in the media at the beginning of the pandemic played a role.
      • Guan W.J.
      • Ni Z.Y.
      • Hu Y.
      • Liang W.H.
      • Ou C.Q.
      • He J.X.
      • Liu L.
      • Shan H.
      • Lei C.L.
      • Hui D.
      • Du B.
      • Li L.J.
      • Zeng G.
      • Yuen K.Y.
      • Chen R.C.
      • Tang C.L.
      • Wang T.
      • Chen P.Y.
      • Xiang J.
      China Medical Treatment Expert Group for COVID-19
      Clinical characteristics of coronavirus disease 2019 in China.
      reported a higher risk of mortality with regard to COVID-19 in individuals above the age of 60 years and in those with serious and chronic conditions.
      In the present study, the mean HAS scores of the elderly individuals diagnosed with COVID-19 was higher than that of those who were not diagnosed with COVID-19. A previous study analysing Chinese data reported that the hospitalization rates following COVID-19 diagnosis increased with age, with a hospitalization rate of 18% for those above the age of 80 years (
      • Verity R.
      • Okell L.C.
      • Dorigatti I.
      • Winskill P.
      • Whittaker C.
      • Imai N.
      • Cuomo-Dannenburg G.
      • Thompson H.
      • Walker P.
      • Fu H.
      • Dighe A.
      • Griffin J.T.
      • Baguelin M.
      • Bhatia S.
      • Boonyasiri A.
      • Cori A.
      • Cucunubá Z.
      • FitzJohn R.
      • Gaythorpe K.
      • Green W.
      • Ferguson N.M.
      Estimates of the severity of coronavirus disease 2019: A model-based analysis.
      ). Furthermore, China Center for Disease Control and Prevention reported an 8%–15% COVID-19 mortality rate in individuals aged 70–80 years and above (
      • Wu Z.
      • McGoogan J.M.
      Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: Summary of a report of 72 314 cases from the Chinese Center for Disease Control and Prevention.
      ). In Italy, the mortality rate was 12%–20% for the same age group (
      • Onder G.
      • Rezza G.
      • Brusaferro S.
      Case-fatality rate and characteristics of patients dying in relation to COVID-19 in Italy.
      ), and 80% of the people that died from COVID-19 in the United States were ≥65 years old (). It is highly likely that these significant mortality rates had an impact on the health anxiety levels of the elderly population.
      In the present study, the HAS and MMTCS knowledge level sub-dimension scores of the elderly individuals diagnosed with COVID-19 were higher than the rest of the participants. In addition, the MMTCS motivation sub-dimension scores of the participants who did not have a relative diagnosed with COVID-19 were higher compared with the participants who had a relative diagnosed with COVID-19. The results suggest that even the thought that the elderly individual or his/her relatives may get sick increases the level of health anxiety in the elderly population, consequently affecting their compliance with treatment. These results are consistent with the literature (
      • Altın Z.
      Elderly people in COVID-19 outbreak.
      ;
      • Dymecka J.
      • Gerymski R.
      • Machnik-Czerwik A.
      • Derbis R.
      • Bidzan M.
      Fear of COVID-19 and life satisfaction: The role of the health-related hardiness and sense of coherence.
      ).
      In the present study, the HAS scores of the elderly participants who experienced a severe fear of COVID-19 as well as of death and loss due to COVID-19 were higher than those who did not experience such fear. Furthermore, the elderly participants who experienced the fear of death and loss had higher MMTCS knowledge level sub-dimension scores. It was observed that the fear of sickness, death and loss due to COVID-19 significantly affect the elderly. From the results of the present study, it can be concluded that this fear of death and loss leads to an increased health anxiety and disease perception in elderly individuals.
      • Erdoğdu Y.
      • Koçoğlu F.
      • Sevim C.
      An investigation of the psychosocial and demographic determinants of anxiety and hopelessness during COVID-19 pandemic.
      reported that 16.4% and 7.9% of the elderly population experienced moderate and severe anxiety, respectively.
      • Li S.
      • Wang Y.
      • Xue J.
      • Zhao N.
      • Zhu T.
      The impact of COVID-19 epidemic declaration on Psychological Consequences: A study on active Weibo users.
      reported that with the increase in the levels of anxiety, depression and anger during the COVID-19 pandemic, a decrease in positive feelings and the joys of life was observed in the elderly individuals as they began worrying more about their families and their health.
      It was observed that the daily lives of the elderly individuals included in the study were affected by the COVID-19 pandemic. It was found that the HAS scores of those whose daily lives were affected were especially high than of those whose daily lives were not affected by the pandemic. The results showed that the daily lives of the elderly were highly affected during the pandemic, becoming more difficult due to the rise in their health anxiety levels, leading to difficulty in maintaining their treatment.
      • Ağan B.
      COVID-19 pandemic process in behavioral economics: The impact of anxiety level on SocioEconomic decision-making behaviors.
      reported that 61% of the study participants' daily lives were highly affected, and a study conducted in Hong Kong on elderly individuals stated that participants felt anxious and hopeless regarding the COVID-19 pandemic, which affected their daily lives and increased their health anxiety levels (
      • Kwok K.O.
      • Li K.K.
      • Chan H.
      • Yi Y.Y.
      • Tang A.
      • Wei W.I.
      • Wong S.
      Community responses during early phase of COVID-19 epidemic,Hong Kong.
      ).
      The HAS and MMTCS knowledge level sub-dimension scores were higher among the participants whose treatments were affected by the COVID-19 pandemic than of those whose treatments remained unaffected. In addition, the DPS-SF scores of the elderly individuals whose treatments were not affected by the COVID-19 pandemic were higher compared with the rest of the participants. These results further showed that COVID-19 caused physical and psychological problems in the elderly individuals, making it difficult for them to comply with the treatment of their comorbidities. It can be deduced that the treatment compliance of the elderly individuals decreases especially as health anxiety levels increase. Even in cases where in COVID-19 does not affect the treatment of the elderly individuals, an increase in disease perception has been observed over the course of the pandemic.
      • Altın Z.
      Elderly people in COVID-19 outbreak.
      stated that curfews imposed on the elderly population to protect their health and the consequent prolonged stay at home produce negative effects on their psychological and physical health.
      In the present study, the HAS, DPS-SF and MMTCS motivation and knowledge level sub-dimension scores were higher among the elderly individuals whose sleep patterns were affected by the pandemic than among those with unaffected sleep patterns. As the results demonstrated, insomnia greatly affected the health anxiety, disease perception and treatment compliance of the elderly individuals.
      • Altın Z.
      Elderly people in COVID-19 outbreak.
      stated that there was an increase in the incidence of insomnia and associated problems among the individuals who received a probable or definitive COVID-19 diagnosis.
      The HAS, DPS-SF and MMTCS motivation sub-dimension scores were higher among the participants who were more cautious regarding their health during the COVID-19 pandemic compared with the rest of the participants. These results reveal that the development of health anxiety among the elderly is caused by a significant perceived threat to their well-being. In addition, the health-related perspectives, concerns and behaviors of the elderly also affect their disease perception. The results of this study indicate that elderly individuals experience anxiety concerning the prognosis of their diseases.

      Conclusion and recommendations

      The COVID-19 pandemic has significantly affected all elderly individuals. The present study demonstrated that the health anxiety and disease perception experienced by the elderly population during the COVID-19 pandemic were high, subsequently making it difficult for them to comply with treatment. In particular, the fear of death/loss, loss of loved ones, negative news regarding the elderly population in the media and restrictions imposed on them greatly affected the level of their health anxiety. Therefore, suitable health policies need to be developed for the elderly individuals who are vulnerable to outbreaks and epidemics, cooperation with professionals for health, treatment and care needs of the elderly individuals should be improved and at-home support should be provided to the elderly individuals in need of psychological support.

      Limitations of research

      Due to the COVID-19 pandemic, the data was collected via online questionnaires (Google Forms) instead of in person interviews. The data collection step took approximately 5 months. Since the target population of the study was elderly individuals, the differences in their education level and lack of or difficulty in using smartphones and social media, such as WhatsApp, constituted the limitations of the study.

      CRediT authorship contribution statement

      The conception and design of the study: ÜV, NA; acquisition of data: ÜV, NA; analysis and interpretation of data: ÜV, NA; drafting the article or revising it critically for important intellectual content: ÜV, NA; final approval of the version to be submitted: ÜV, NA

      Acknowledgments

      The authors would like to thank all the elderly individuals.

      Funding

      This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

      References

        • Aalto A.M.
        • Heijmans M.
        • Weinman J.
        • Aro A.R.
        Illness perceptions in coronary heart disease. Sociodemographic, illness-related, and psychosocial correlates.
        Journal of Psychosomatic Research. 2005; 58: 393-402https://doi.org/10.1016/j.jpsychores.2005.03.001
        • Affleck W.
        • Carmichael V.
        • Whitley R.
        Men's mental health: Social determinants and implications for services.
        Canadian Journal of Psychiatry. Revue Canadienne de Psychiatrie. 2018; 63: 581-589https://doi.org/10.1177/0706743718762388
        • Ağan B.
        COVID-19 pandemic process in behavioral economics: The impact of anxiety level on SocioEconomic decision-making behaviors.
        Electronic Turkish Studies. 2020; 15: 1001-1006https://doi.org/10.7827/TurkishStudies.43731
        • Albert P.R.
        Why is depression more prevalent in women?.
        Journal of Psychiatry & Neuroscience. 2015; 40: 219-221https://doi.org/10.1503/jpn.150205
        • Altın Z.
        Elderly people in COVID-19 outbreak.
        Tepecik Eğitim ve Araştırma Hastanesi Dergisi. 2020; 30: 49-57https://doi.org/10.5222/terh.2020.93723
        • Aydemir Ö.
        • Kirpinar İ.
        • Sati T.
        • Uykur B.
        • Cengisiz C.
        Reliability and validity of the Turkish version of the Health Anxiety Inventory.
        Noropsikiyatri Arsivi. 2013; 50: 325-331https://doi.org/10.4274/npa.y6383
        • Broadbent E.
        • Petrie K.J.
        • Main J.
        • Weinman J.
        The brief illness perception questionnaire.
        Journal of Psychosomatic Research. 2006; 60: 631-637https://doi.org/10.1016/j.jpsychores.2005.10.020
        • Brooke J.
        • Jackson D.
        Older people and COVID-19: Isolation, risk and ageism.
        Journal of Clinical Nursing. 2020; 29: 2044-2046https://doi.org/10.1111/jocn.15274
        • Centers for Disease Control and Prevention (CDC)
        Coronavirus disease 2019 (COVID-19).
        • Chhetri J.K.
        • Chan P.
        • Arai H.
        • Chul Park S.
        • Sriyani Gunaratne P.
        • Setiati S.
        • Assantachai P.
        Prevention of COVID-19 in older adults: A brief guidance from the International Association for Gerontology and Geriatrics (IAGG) Asia/Oceania region.
        The Journal of Nutrition, Health & Aging. 2020; 24: 471-472https://doi.org/10.1007/s12603-020-1359-7
        • Demirkol M.E.
        • Tamam L.
        • Evlice Y.E.
        • Karaytuğ M.O.
        Adherence to the treatment in psychiatric patients.
        Cukurova Medical Journal. 2015; 40: 555-568
        • Dymecka J.
        • Gerymski R.
        • Machnik-Czerwik A.
        • Derbis R.
        • Bidzan M.
        Fear of COVID-19 and life satisfaction: The role of the health-related hardiness and sense of coherence.
        Frontiers in Psychiatry. 2021; 12712103https://doi.org/10.3389/fpsyt.2021.712103
        • Erdoğdu Y.
        • Koçoğlu F.
        • Sevim C.
        An investigation of the psychosocial and demographic determinants of anxiety and hopelessness during COVID-19 pandemic.
        Turkish Journal of Clinical Psychiatry. 2020; 23: 24-37https://doi.org/10.5505/kpd.2020.35403
        • George D.
        • Mallery P.
        IBM SPSS statistics 25 step by step: A simple guide and reference.
        15th ed. Routledge, 2018https://doi.org/10.4324/9781351033909
        • Guan W.J.
        • Ni Z.Y.
        • Hu Y.
        • Liang W.H.
        • Ou C.Q.
        • He J.X.
        • Liu L.
        • Shan H.
        • Lei C.L.
        • Hui D.
        • Du B.
        • Li L.J.
        • Zeng G.
        • Yuen K.Y.
        • Chen R.C.
        • Tang C.L.
        • Wang T.
        • Chen P.Y.
        • Xiang J.
        • China Medical Treatment Expert Group for COVID-19
        Clinical characteristics of coronavirus disease 2019 in China.
        The New England Journal of Medicine. 2020; 382: 1708-1720https://doi.org/10.1056/NEJMoa2002032
        • Hasöksüz M.
        • Kiliç S.
        • Saraç F.
        Coronaviruses and SARS-COV-2.
        Turkish Journal of Medical Sciences. 2020; 50: 549-556https://doi.org/10.3906/sag-2004-127
        • Kılınçel O.
        • Muratdağı G.
        • Aydın A.
        • Oksuz A.
        • Buyukdereli Atadağ Y.
        • Etcioglu E.
        • Ozen F.
        The anxiety and loneliness levels of geriatric population in-home quarantine during COVID-19 pandemic in Turkey.
        Turkish Journal of Clinical Psychiatry. 2020; 23: 7-14https://doi.org/10.5505/kpd.2020.04382
        • Kocaman N.
        • Özkan M.
        • Armay Z.
        • Özkan S.
        Hastalık Algısı Ölçeğinin Türkçe uyarlamasının geçerlilik ve güvenilirlik çalışması.
        Anadolu Psikiyatri Dergisi. 2007; 8: 271-280
        • Krousel-Wood M.A.
        • Muntner P.
        • Islam T.
        • Morisky D.E.
        • Webber L.S.
        Barriers to and determinants of medication adherence in hypertension management: Perspective of the cohort study of medication adherence among older adults.
        The Medical Clinics of North America. 2009; 93: 753-769https://doi.org/10.1016/j.mcna.2009.02.007
        • Kwok K.O.
        • Li K.K.
        • Chan H.
        • Yi Y.Y.
        • Tang A.
        • Wei W.I.
        • Wong S.
        Community responses during early phase of COVID-19 epidemic,Hong Kong.
        Emerging İnfectious Diseases. 2020; 26: 1575-1579https://doi.org/10.3201/eid2607.200500
        • Lehmann M.
        • Bruenahl C.A.
        • Löwe B.
        • Addo M.M.
        • Schmiedel S.
        • Lohse A.W.
        • Schramm C.
        Ebola and psychological stress of health care professionals.
        Emerging İnfectious Diseases. 2015; 21: 913-914https://doi.org/10.3201/eid2105.141988
        • Li S.
        • Wang Y.
        • Xue J.
        • Zhao N.
        • Zhu T.
        The impact of COVID-19 epidemic declaration on Psychological Consequences: A study on active Weibo users.
        International Journal of Environmental Research and Public Health. 2020; 17: 2032https://doi.org/10.3390/ijerph17062032
        • Lin C.Y.
        • Peng Y.C.
        • Wu Y.H.
        • Chang J.
        • Chan C.H.
        • Yang D.Y.
        The psychological effect of severe acute respiratory syndrome on emergency department staff.
        Emergency Medicine Journal. 2007; 24: 12-17https://doi.org/10.1136/emj.2006.035089
        • Morisky D.E.
        • Green L.W.
        • Levine D.M.
        Concurrent and predictive validity of a self-reported measure of medication adherence.
        Medical Care. 1986; 24: 67-74https://doi.org/10.1097/00005650-198601000-00007
        • Onder G.
        • Rezza G.
        • Brusaferro S.
        Case-fatality rate and characteristics of patients dying in relation to COVID-19 in Italy.
        JAMA. 2020; 323: 1775-1776https://doi.org/10.1001/jama.2020.4683
        • Öztürk Z.
        • Karakuş G.
        • Tamam L.
        Death anxiety in elderly cases.
        Anatolian Journal of Psychiatry. 2011; 12: 37-43
        • Saladino V.
        • Algeri D.
        • Auriemma V.
        The psychological and social impact of COVID-19: New perspectives of well-being.
        Frontiers in Psychology. 2020; 11577684https://doi.org/10.3389/fpsyg.2020.577684
        • Salkovskis P.M.
        • Rimes K.A.
        • Warwick H.M.
        • Clark D.M.
        The Health Anxiety Inventory: Development and validation of scales for the measurement of health anxiety and hypochondriasis.
        Psychological Medicine. 2002; 32: 843-853https://doi.org/10.1017/s0033291702005822
        • Satici B.
        • Gocet-Tekin E.
        • Deniz M.E.
        • Satici S.A.
        Adaptation of the fear of COVID-19 scale: Its association with psychological distress and life satisfaction in Turkey.
        International Journal of Mental Health and Addiction. 2020; (Advance online publication): 1-9https://doi.org/10.1007/s11469-020-00294-0
        • Tian F.
        • Li H.
        • Tian S.
        • Yang J.
        • Shao J.
        • Tian C.
        Psychological symptoms of ordinary Chinese citizens based on SCL-90 during the level I emergency response to COVID-19.
        Psychiatry Research. 2020; 288112992https://doi.org/10.1016/j.psychres.2020.112992
        • Turkish Population Statistics Agency
        İstatistiklerle Yaşlılar.
        • Verity R.
        • Okell L.C.
        • Dorigatti I.
        • Winskill P.
        • Whittaker C.
        • Imai N.
        • Cuomo-Dannenburg G.
        • Thompson H.
        • Walker P.
        • Fu H.
        • Dighe A.
        • Griffin J.T.
        • Baguelin M.
        • Bhatia S.
        • Boonyasiri A.
        • Cori A.
        • Cucunubá Z.
        • FitzJohn R.
        • Gaythorpe K.
        • Green W.
        • Ferguson N.M.
        Estimates of the severity of coronavirus disease 2019: A model-based analysis.
        The Lancet. Infectious Diseases. 2020; 20: 669-677https://doi.org/10.1016/S1473-3099(20)30243-7
        • Vural B.
        • Acar Ö.T.
        • Topsever P.
        • Filiz T.M.
        Reliability and validity of Turkish Version of Modified Morisky Scale.
        The Journal of Turkish Family Physician. 2012; 3: 17-20
        • World Health Organization
        Coronavirus disease 2019 (COVID-19) situation report–52.
        • Wu Z.
        • McGoogan J.M.
        Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: Summary of a report of 72 314 cases from the Chinese Center for Disease Control and Prevention.
        JAMA. 2020; 323: 1239-1242https://doi.org/10.1001/jama.2020.2648
        • Xie J.
        • Tong Z.
        • Guan X.
        • Du B.
        • Qiu H.
        • Slutsky A.S.
        Critical care crisis and some recommendations during the COVID-19 epidemic in China.
        Intensive Care Medicine. 2020; 46: 837-840https://doi.org/10.1007/s00134-020-05979-7