Fear of COVID-19 among patients with prior SARS-CoV-2 infection: A cross-sectional study in Estonian family practices
In March 2020, coronavirus disease 2019 (COVID-19) was declared a global pandemic by the World Health Organisation (WHO) . Since then, mental health has deteriorated compared with pre pandemic trends . In particular, COVID-19 survivors are believed to be at risk of a decrease in mental well-being . Due to their communicable and invisible nature, infections are a unique disorder that causes fear among people . Fear is an adequate reaction to a threat; at the same time, a high level of fear can be interpreted as an inadequate fear presentation due to its close relationship with anxiety . Higher COVID-19 fear has been associated with both positive and negative health factors. Fear has enhanced cautious behaviour, such as social distancing and improved hand hygiene . However, it has also been associated with factors that deteriorate mental health, such as anxiety , stress , depression  and perceptions of decreased quality of life . Greater fear of COVID-19 has been associated with being female, older and lower income . After acute infection, patients are at risk of developing long COVID syndrome . There is a lack of studies focussing on fear among COVID-19 survivors who experienced varying degrees of COVID-19 severity and assessing whether long COVID is associated with increased fear. Therefore, we aimed to investigate the level of and factors associated with COVID-19 fear among adults with a history of SARS-CoV-2 infection. Our second aim was to explore whether long COVID contributes to fear. 

Study design This cross-sectional study was conducted among Estonian family practice (FP) patients with a history of SARS-CoV-2 infection 6–14 months before enrolling. The study adheres to the Helsinki declaration’s ethical principles for medical research. Ethical approval for the study was received from the Tartu University Ethics Committee for Human Studies (protocol number 357/M-27). Recruitment and selection of study subjects Multistage sampling was used, which meant first involving a convenience sample of FP patients (amongst the 25 FP within the highest 5th percentile of numbers of SARS-CoV-2 infected patients) and then including a random sample of COVID-19 survivors. The target sample size was 370 COVID-19 survivors. Assuming a 65% response rate, the total sample retrieved from the family practices was 585 participants. Seventeen FP centres in Tallinn (capital), Saaremaa (the island with the most COVID-19 cases in 2020) and Tartu (the second largest city) consented to participate in the study. shows the total COVID-19 cases in Estonia in March 2020 and July 2021. Appropriate training on the practical and ethical aspects of the study was given to the staff of these centres. Recruitment of COVID-19 survivors took place between March 15 and 17 July 2021. Inclusion criteria were as follows: (i) 18 years or older; (ii) laboratory confirmed COVID-19 (nasopharyngeal specimen positive for SARS-CoV-2 RNA) in the period from February 25 to 14 September 2020; (iii) resident of Estonia and a patient of a FP physician enrolled in the study; (iv) Estonian or Russian language speaker; and (v) able to provide informed consent. Participants were identified in the national communicable diseases surveillance database at the Estonian Health Board and linked with the FPs using personal identification codes . Nearly all people living in Estonia with a valid residential permit are registered with an FP. The FP is the first place to contact regarding most health issues . All individuals meeting the first three eligibility criteria were invited by FP staff via telephone, email, or direct contact to schedule a study appointment. Participants were thoroughly instructed on the study procedure and asked to sign a written consent form before completing the questionnaire. Data collection Self-administered questionnaire Participants were asked to complete a multiple-choice questionnaire, including demographic information, pre acute and post acute COVID-19 health status, COVID-19 severity and COVID-19 fear . The questionnaire was available in Estonian and Russian. The questionnaire was translated according to relevant guidelines . The study visit took approximately 60 min. A €20 food shop gift card was given as a participant’s reward. Estonian Health Insurance Fund data Data on comorbidities preceding COVID-19 infection by three years were abstracted from the Estonian Health Insurance Fund (EHIF) database. The EHIF electronic administrative database contains personal information (sex, age), information on health care utilisation (date of service, type of service provided) and diagnostic codes based on the International Classification of Diseases, tenth revision. Variables A five-item self-rated instrument was used to measure participants’ self-rated health 6 months prior to infection. Responses were categorised into four groups (bad, n = 10, and very bad, n = 1, were merged into one group). Self-rated physical activity (defined as half an hour of activity leading to an increase in heart rate and respiration) during the past 6 months was categorised as follows: ≥2 times per week, once or less per week, inactive (sporadically during the year or never) and unable due to injury or illness. Data on experienced symptoms were requested for three points in time: 6 months prior to COVID-19, during COVID-19, and at the time of study participation. Data about self-reported symptoms at the time of study participation were used to identify patients with long COVID. To characterise COVID-19, three measures were used: (i) self-reported physical state during acute COVID-19 (classified into three groups: usual activity, limited activity, which meant being able to carry out vital household tasks, and bedridden); (ii) treatment setting (hospitalised vs. not); and (iii) assessment of long COVID. For long COVID, the WHO clinical case definition was used. Long COVID is defined as persistent or new onset symptoms in individuals with confirmed or suspected COVID-19 for at least 2 months within 3 months from the onset of COVID-19 that cannot be explained by an alternative diagnosis and that affect daily functioning . Onset of at least one new symptom in combination with a perceived health-related limitation on usual activities was classified as long COVID. Comorbidity burden was calculated based on the data from the EHIF according to the Charlson Comorbidity Index (CCI) for classifying comorbidity severity . A CCI score of 0 points was classified as no comorbidity, while a CCI score >0 was classified as comorbidity. Outcome variables To assess COVID-19 fear, the seven-item instrument Fear of COVID-19 Scale (FCV-19S) was used . Each item was answered on a seven-point Likert-scale ranging from strongly disagree to strongly agree, and the total score ranged from 7 to 49 (the higher the score was, the greater the COVID-19 fear). Fear was categorised as high or low with the cut-off at the sample mean value. Participants scoring > 17.8 were categorised as having a high level of COVID-19 fear, whereas participants scoring ≤ 17.8 were categorised as having a low level of COVID-19 fear. Statistical analysis First, a descriptive analysis was performed. Numbers and percentages were used to describe categorical variables. Participants missing answers on ≥ 4 items on the FCV-19S ( n = 6) were excluded from the analysis. Data for participants lacking fewer than three answers ( n = 6, total missing answers n = 8) were imputed. Imputing was done by calculating the mean item value for each individual, which then replaced the missing value. To assess differences between variables and mean FCV-19S score between those with respectively without high COVID-19 fear, we used t-tests for two-group analysis and analysis of variance (ANOVA) for multiple comparisons. To correct for multiple comparisons, Bonferroni correction was used. The significance level was set as <0.05. For analysis of factors associated with fear, the FCV-19S score was dichotomised with the cut-off at the sample mean value. To examine associations with a high level of COVID-19 fear, we used bivariate and multivariate logistic regression, from which odds ratios (ORs) and adjusted ORs (aORs) with corresponding 95% confidence intervals (CIs) were estimated. For all statistical analyses, STATA version 17 was used. 

This cross-sectional study was conducted among Estonian family practice (FP) patients with a history of SARS-CoV-2 infection 6–14 months before enrolling. The study adheres to the Helsinki declaration’s ethical principles for medical research. Ethical approval for the study was received from the Tartu University Ethics Committee for Human Studies (protocol number 357/M-27). 

Multistage sampling was used, which meant first involving a convenience sample of FP patients (amongst the 25 FP within the highest 5th percentile of numbers of SARS-CoV-2 infected patients) and then including a random sample of COVID-19 survivors. The target sample size was 370 COVID-19 survivors. Assuming a 65% response rate, the total sample retrieved from the family practices was 585 participants. Seventeen FP centres in Tallinn (capital), Saaremaa (the island with the most COVID-19 cases in 2020) and Tartu (the second largest city) consented to participate in the study. shows the total COVID-19 cases in Estonia in March 2020 and July 2021. Appropriate training on the practical and ethical aspects of the study was given to the staff of these centres. Recruitment of COVID-19 survivors took place between March 15 and 17 July 2021. Inclusion criteria were as follows: (i) 18 years or older; (ii) laboratory confirmed COVID-19 (nasopharyngeal specimen positive for SARS-CoV-2 RNA) in the period from February 25 to 14 September 2020; (iii) resident of Estonia and a patient of a FP physician enrolled in the study; (iv) Estonian or Russian language speaker; and (v) able to provide informed consent. Participants were identified in the national communicable diseases surveillance database at the Estonian Health Board and linked with the FPs using personal identification codes . Nearly all people living in Estonia with a valid residential permit are registered with an FP. The FP is the first place to contact regarding most health issues . All individuals meeting the first three eligibility criteria were invited by FP staff via telephone, email, or direct contact to schedule a study appointment. Participants were thoroughly instructed on the study procedure and asked to sign a written consent form before completing the questionnaire. 

Self-administered questionnaire Participants were asked to complete a multiple-choice questionnaire, including demographic information, pre acute and post acute COVID-19 health status, COVID-19 severity and COVID-19 fear . The questionnaire was available in Estonian and Russian. The questionnaire was translated according to relevant guidelines . The study visit took approximately 60 min. A €20 food shop gift card was given as a participant’s reward. Estonian Health Insurance Fund data Data on comorbidities preceding COVID-19 infection by three years were abstracted from the Estonian Health Insurance Fund (EHIF) database. The EHIF electronic administrative database contains personal information (sex, age), information on health care utilisation (date of service, type of service provided) and diagnostic codes based on the International Classification of Diseases, tenth revision. 

Participants were asked to complete a multiple-choice questionnaire, including demographic information, pre acute and post acute COVID-19 health status, COVID-19 severity and COVID-19 fear . The questionnaire was available in Estonian and Russian. The questionnaire was translated according to relevant guidelines . The study visit took approximately 60 min. A €20 food shop gift card was given as a participant’s reward. 

Data on comorbidities preceding COVID-19 infection by three years were abstracted from the Estonian Health Insurance Fund (EHIF) database. The EHIF electronic administrative database contains personal information (sex, age), information on health care utilisation (date of service, type of service provided) and diagnostic codes based on the International Classification of Diseases, tenth revision. 

A five-item self-rated instrument was used to measure participants’ self-rated health 6 months prior to infection. Responses were categorised into four groups (bad, n = 10, and very bad, n = 1, were merged into one group). Self-rated physical activity (defined as half an hour of activity leading to an increase in heart rate and respiration) during the past 6 months was categorised as follows: ≥2 times per week, once or less per week, inactive (sporadically during the year or never) and unable due to injury or illness. Data on experienced symptoms were requested for three points in time: 6 months prior to COVID-19, during COVID-19, and at the time of study participation. Data about self-reported symptoms at the time of study participation were used to identify patients with long COVID. To characterise COVID-19, three measures were used: (i) self-reported physical state during acute COVID-19 (classified into three groups: usual activity, limited activity, which meant being able to carry out vital household tasks, and bedridden); (ii) treatment setting (hospitalised vs. not); and (iii) assessment of long COVID. For long COVID, the WHO clinical case definition was used. Long COVID is defined as persistent or new onset symptoms in individuals with confirmed or suspected COVID-19 for at least 2 months within 3 months from the onset of COVID-19 that cannot be explained by an alternative diagnosis and that affect daily functioning . Onset of at least one new symptom in combination with a perceived health-related limitation on usual activities was classified as long COVID. Comorbidity burden was calculated based on the data from the EHIF according to the Charlson Comorbidity Index (CCI) for classifying comorbidity severity . A CCI score of 0 points was classified as no comorbidity, while a CCI score >0 was classified as comorbidity. 

To assess COVID-19 fear, the seven-item instrument Fear of COVID-19 Scale (FCV-19S) was used . Each item was answered on a seven-point Likert-scale ranging from strongly disagree to strongly agree, and the total score ranged from 7 to 49 (the higher the score was, the greater the COVID-19 fear). Fear was categorised as high or low with the cut-off at the sample mean value. Participants scoring > 17.8 were categorised as having a high level of COVID-19 fear, whereas participants scoring ≤ 17.8 were categorised as having a low level of COVID-19 fear. 

First, a descriptive analysis was performed. Numbers and percentages were used to describe categorical variables. Participants missing answers on ≥ 4 items on the FCV-19S ( n = 6) were excluded from the analysis. Data for participants lacking fewer than three answers ( n = 6, total missing answers n = 8) were imputed. Imputing was done by calculating the mean item value for each individual, which then replaced the missing value. To assess differences between variables and mean FCV-19S score between those with respectively without high COVID-19 fear, we used t-tests for two-group analysis and analysis of variance (ANOVA) for multiple comparisons. To correct for multiple comparisons, Bonferroni correction was used. The significance level was set as <0.05. For analysis of factors associated with fear, the FCV-19S score was dichotomised with the cut-off at the sample mean value. To examine associations with a high level of COVID-19 fear, we used bivariate and multivariate logistic regression, from which odds ratios (ORs) and adjusted ORs (aORs) with corresponding 95% confidence intervals (CIs) were estimated. For all statistical analyses, STATA version 17 was used. 

Characteristics of participants The inclusion process is shown in . In total, 341 participants met the inclusion criteria and completed enough answers on the FCV-19S. Comparing the overall age and sex distribution of study participants with nonparticipants, we observed an overrepresentation of women ( p < 0.01) and younger participants (mean age 51.8 ( SD 17.8) vs. 61.3 ( SD 26.0) years, p < 0.01). The baseline characteristics of the participants are presented in and . Most participants were female (60%), working (78.9%) and living in a city (79.9%). Few respondents (9.7%) had CCI ≥1. The mean age was 49.4 years ( SD 15.3), ranging from 18 to 89 years. The mean time elapsed since COVID-19 infection was 276 days ( SD 87.85 days, ranging from 63 to 449 days). COVID-19 fear among participants COVID-19 fear among participants is presented in . The mean score on the FCV-19S was 17.78 ( SD 9.56, range 7–49). In total, 143 (42%) participants showed high fear. For the distribution of FCV-19S scores among subgroups, see in the Appendix. Factors associated with COVID-19 fear In total, 14 factors were significantly associated with COVID-19 fear in the bivariate analysis. Based on the multivariate analysis (presented in , the factors associated with higher fear were female sex (aOR 2.12, 95% CI 1.14–3.95), age ≥61 years (aOR 3.23, CI 1.28–8.16), household consisting of two members (aOR 3.70, 95% CI 1.40–9.77), being physically inactive (and not prohibited by any injury or illness) within 6 months prior to COVID-19 (aOR 3.53, 95% CI 1.26–9.95), and experiencing more physically debilitating symptoms during COVID-19 (usual activity vs. limited activity aOR 2.14, 95% CI 1.08–4.24; usual activity vs. bedridden aOR 2.66, 95% CI 1.21–5.87) during COVID-19. 

The inclusion process is shown in . In total, 341 participants met the inclusion criteria and completed enough answers on the FCV-19S. Comparing the overall age and sex distribution of study participants with nonparticipants, we observed an overrepresentation of women ( p < 0.01) and younger participants (mean age 51.8 ( SD 17.8) vs. 61.3 ( SD 26.0) years, p < 0.01). The baseline characteristics of the participants are presented in and . Most participants were female (60%), working (78.9%) and living in a city (79.9%). Few respondents (9.7%) had CCI ≥1. The mean age was 49.4 years ( SD 15.3), ranging from 18 to 89 years. The mean time elapsed since COVID-19 infection was 276 days ( SD 87.85 days, ranging from 63 to 449 days). 

COVID-19 fear among participants is presented in . The mean score on the FCV-19S was 17.78 ( SD 9.56, range 7–49). In total, 143 (42%) participants showed high fear. For the distribution of FCV-19S scores among subgroups, see in the Appendix. 

In total, 14 factors were significantly associated with COVID-19 fear in the bivariate analysis. Based on the multivariate analysis (presented in , the factors associated with higher fear were female sex (aOR 2.12, 95% CI 1.14–3.95), age ≥61 years (aOR 3.23, CI 1.28–8.16), household consisting of two members (aOR 3.70, 95% CI 1.40–9.77), being physically inactive (and not prohibited by any injury or illness) within 6 months prior to COVID-19 (aOR 3.53, 95% CI 1.26–9.95), and experiencing more physically debilitating symptoms during COVID-19 (usual activity vs. limited activity aOR 2.14, 95% CI 1.08–4.24; usual activity vs. bedridden aOR 2.66, 95% CI 1.21–5.87) during COVID-19. 

Main findings In this study, we assessed fear among COVID-19 survivors and examined factors associated with a higher fear level, including whether having long COVID contributed to COVID-19 fear. A sizeable proportion (42%) of participants reported high COVID-19 fear for more than 6 months after acute infection. Sociodemographic characteristics were associated with higher fear as well as pre-COVID-19 physical activity and COVID-19 symptom severity. However, long COVID was not independently associated with higher fear. Interpretation In line with previous studies, we found that older age and being female were associated with higher levels of fear . Elderly individuals are at higher risk for severe COVID-19 infection . Fear in general has been shown to be greater among women than men, which might be due to differences in patterns of gender socialisation . Additionally, women have suffered from worse overall mental health during the pandemic . Low levels of self-reported physical activity were associated with higher levels of fear. Physical activity has been associated with fewer anxiety symptoms during the COVID-19 pandemic . This suggests that primary health care workers should enquire about and encourage patients’ physical activity, as this may be a way to ease fear and improve patient health. In contrast to prior studies that indicated higher fear among singles , we found that households consisting of two persons were associated with higher fear. Two-member households might be a surrogate marker for older age or other sociodemographic factors we did not account for. However, worry about loved ones becoming infected with COVID-19 is a predictor of fear, although it was not measured with the FCV-19S . Patients suffering more severely during the acute infection phase (irrespective of being hospitalised for COVID-19) displayed higher levels of fear, which might be interpreted as an expression of adequate fear due to COVID-19 being a fatal disease . Interestingly, we found no association between higher fear level and long COVID or hospitalisation. Previously, worry about COVID-19 has been found to increase the risk of long COVID . Hospitalisation and long COVID could be seen as markers for disease severity and be thought to impact fear level. However, our study oversampled patients hospitalised because of COVID-19. This might inflate our sample-based estimate on COVID-19 fear. Nonetheless, patients’ physical state remained significant in multivariate analysis. This shows that even among patients not hospitalised, the infection considerably affected the health status. It might be that hospitalised patients felt better-taken care of and therefore were less worried. The classification of COVID-19 fear has varied in previous studies: some have considered the answers of agree or strongly agree to any item on the FCV-19S as high fear , others have calculated fear levels with receiver operating analysis and others have, similarly to this study, used the mean value as the cut-off . A meta-analysis reviewing fear with the FCV-19S globally found that fear levels were similar worldwide. However, Asian countries expressed the highest fear, whereas the Australian continent reported the lowest . Even though the absolute difference was small in number, geographical, cultural and sociodemographic factors might contribute to differences in fear levels. Numbers of individuals experiencing fear also vary due to differences in measurement methods and periods during the pandemic. A better understanding of how fear changes over time and which levels of fear contribute to worsening mental health is needed. Strengths and limitations To our knowledge, this is the first study to target fear among COVID-19 survivors in FP. A strength of this study is the participant recruitment method reflecting the general population since almost everyone living in Estonia is registered as FP patient. However, the results might be biased by some individuals being more prone to non-participation (e.g. older individuals with poor health and men). The nonresponse bias and oversampling of patients hospitalised with COVID-19 might bias our high COVID-19 fear prevalence estimate. Using multiple regression analysis to explore factors associated with high fear mitigates some of this bias for the high fear correlates. We used a seven-point Likert scale to assess fear, which complicates comparisons between absolute figures on the scale, although it may add greater characterisation to the fear. The FCV-19S has not been validated for an Estonian population. However, the FCV-19S is a strong and valid instrument for assessing fear across different languages  including several European countries. Using this instrument allows for comparisons of fear levels with other countries. In this study, we used self-reported health and symptoms as health status measures. Self-rated health has been proven to be a valid and efficient measure of physical and mental health across the European continent . Self-reported symptoms are considered the golden standard for measuring subjective experiences since the information comes directly from the patient. The study design is limited by its incapacity to assess temporality. However, we used the format ‘time-line follow-back’, which anchors the respondent in their symptoms and health status prior to COVID-19 and at the time of the disease. Furthermore, focusing on events before the infection might imply recall bias. No symptom scales were used to assess depression, anxiety, panic disorders and sleep problems in the study population. Therefore, the results do not necessarily reflect the actual prevalence of these disorders. Additionally, we used participants’ self-reported symptom burden before and after initial infection to classify long COVID. No clinical examination of the participants was conducted regarding the diagnosis. This might therefore be seen as a subjective measure and induce bias since it is based on patient reports. Another limitation is using the CCI, which was developed as a mortality predictor with strict comorbidity classification. However, it is commonly used and enables comparisons with prior studies. Implications As higher fear may affect and deteriorate overall mental health in the population, there is a need to identify vulnerable groups to target with correct information to help increase their health literacy. FP doctors are in a perfect position to screen fear and tackle mental health deterioration due to their role as healthcare gatekeepers and the broad spectrum of patients they see. A first step would be to ask patients whether they experience fear and assess whether they need psychological treatment to handle the fear. Previously, treatment with cognitive behavioural therapy through the internet is helpful in reducing anxiety , which could be a proper means of treating people with high fear during pandemics. In addition, the pedagogic aspect of the doctor’s role cannot be forgotten. 

In this study, we assessed fear among COVID-19 survivors and examined factors associated with a higher fear level, including whether having long COVID contributed to COVID-19 fear. A sizeable proportion (42%) of participants reported high COVID-19 fear for more than 6 months after acute infection. Sociodemographic characteristics were associated with higher fear as well as pre-COVID-19 physical activity and COVID-19 symptom severity. However, long COVID was not independently associated with higher fear. 

In line with previous studies, we found that older age and being female were associated with higher levels of fear . Elderly individuals are at higher risk for severe COVID-19 infection . Fear in general has been shown to be greater among women than men, which might be due to differences in patterns of gender socialisation . Additionally, women have suffered from worse overall mental health during the pandemic . Low levels of self-reported physical activity were associated with higher levels of fear. Physical activity has been associated with fewer anxiety symptoms during the COVID-19 pandemic . This suggests that primary health care workers should enquire about and encourage patients’ physical activity, as this may be a way to ease fear and improve patient health. In contrast to prior studies that indicated higher fear among singles , we found that households consisting of two persons were associated with higher fear. Two-member households might be a surrogate marker for older age or other sociodemographic factors we did not account for. However, worry about loved ones becoming infected with COVID-19 is a predictor of fear, although it was not measured with the FCV-19S . Patients suffering more severely during the acute infection phase (irrespective of being hospitalised for COVID-19) displayed higher levels of fear, which might be interpreted as an expression of adequate fear due to COVID-19 being a fatal disease . Interestingly, we found no association between higher fear level and long COVID or hospitalisation. Previously, worry about COVID-19 has been found to increase the risk of long COVID . Hospitalisation and long COVID could be seen as markers for disease severity and be thought to impact fear level. However, our study oversampled patients hospitalised because of COVID-19. This might inflate our sample-based estimate on COVID-19 fear. Nonetheless, patients’ physical state remained significant in multivariate analysis. This shows that even among patients not hospitalised, the infection considerably affected the health status. It might be that hospitalised patients felt better-taken care of and therefore were less worried. The classification of COVID-19 fear has varied in previous studies: some have considered the answers of agree or strongly agree to any item on the FCV-19S as high fear , others have calculated fear levels with receiver operating analysis and others have, similarly to this study, used the mean value as the cut-off . A meta-analysis reviewing fear with the FCV-19S globally found that fear levels were similar worldwide. However, Asian countries expressed the highest fear, whereas the Australian continent reported the lowest . Even though the absolute difference was small in number, geographical, cultural and sociodemographic factors might contribute to differences in fear levels. Numbers of individuals experiencing fear also vary due to differences in measurement methods and periods during the pandemic. A better understanding of how fear changes over time and which levels of fear contribute to worsening mental health is needed. 

To our knowledge, this is the first study to target fear among COVID-19 survivors in FP. A strength of this study is the participant recruitment method reflecting the general population since almost everyone living in Estonia is registered as FP patient. However, the results might be biased by some individuals being more prone to non-participation (e.g. older individuals with poor health and men). The nonresponse bias and oversampling of patients hospitalised with COVID-19 might bias our high COVID-19 fear prevalence estimate. Using multiple regression analysis to explore factors associated with high fear mitigates some of this bias for the high fear correlates. We used a seven-point Likert scale to assess fear, which complicates comparisons between absolute figures on the scale, although it may add greater characterisation to the fear. The FCV-19S has not been validated for an Estonian population. However, the FCV-19S is a strong and valid instrument for assessing fear across different languages  including several European countries. Using this instrument allows for comparisons of fear levels with other countries. In this study, we used self-reported health and symptoms as health status measures. Self-rated health has been proven to be a valid and efficient measure of physical and mental health across the European continent . Self-reported symptoms are considered the golden standard for measuring subjective experiences since the information comes directly from the patient. The study design is limited by its incapacity to assess temporality. However, we used the format ‘time-line follow-back’, which anchors the respondent in their symptoms and health status prior to COVID-19 and at the time of the disease. Furthermore, focusing on events before the infection might imply recall bias. No symptom scales were used to assess depression, anxiety, panic disorders and sleep problems in the study population. Therefore, the results do not necessarily reflect the actual prevalence of these disorders. Additionally, we used participants’ self-reported symptom burden before and after initial infection to classify long COVID. No clinical examination of the participants was conducted regarding the diagnosis. This might therefore be seen as a subjective measure and induce bias since it is based on patient reports. Another limitation is using the CCI, which was developed as a mortality predictor with strict comorbidity classification. However, it is commonly used and enables comparisons with prior studies. 

As higher fear may affect and deteriorate overall mental health in the population, there is a need to identify vulnerable groups to target with correct information to help increase their health literacy. FP doctors are in a perfect position to screen fear and tackle mental health deterioration due to their role as healthcare gatekeepers and the broad spectrum of patients they see. A first step would be to ask patients whether they experience fear and assess whether they need psychological treatment to handle the fear. Previously, treatment with cognitive behavioural therapy through the internet is helpful in reducing anxiety , which could be a proper means of treating people with high fear during pandemics. In addition, the pedagogic aspect of the doctor’s role cannot be forgotten. 

In this cross-sectional study involving 341 FP patients in Estonia with a historically positive SARS-CoV-2 PCR test, almost half reported great fear. Higher levels of fear were associated with sociodemographic factors, self-rated physical activity prior to COVID-19 and disease severity during COVID-19. 

