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. 2024 Mar 11;10:23779608241234980. doi: 10.1177/23779608241234980

Perceived Stress and Level of Uncertainty Among Hospitalized COVID-19 Patients

Mahdi Nabi Foodani 1, Zahra Abbasi Dolatabadi 1, Amir Rahbariyan 1, Arezoo Rasti 1, Zakiyeh Jafaryparvar 2, Masoumeh Zakerimoghadam 1,✉
PMCID: PMC10929029  PMID: 38476571

Abstract

Introduction

Disease uncertainty refers to the inability to assign meaning to events related to the illness. Uncertainty of the disease can affect various aspects of human life such as psychological aspects.

Objectives

This study aims to examine the relationship between disease uncertainty and perceived stress in COVID-19 patients.

Methods

An analytical cross-sectional study was conducted on 212 hospitalized COVID-19 patients who were initially admitted to the intensive care units (ICUs) and later transferred to general wards within the same hospitals. Three instruments were utilized to collect data for this study. The Demographic Information Questionnaire, Mishel Uncertainty in Illness Scale (MUIS) for disease uncertainty, and Perceived Stress Questionnaire. For data analysis, both descriptive and inferential statistics were employed using IBM SPSS Statistics version 25.

Results

The Pearson correlation coefficient matrix results showed a positive and significant relationship between uncertainty about the illness (P < .001, r = 0.829), ambiguity (P < .001, r = 0.795), complexity (P < .001, r = 0.835), inconsistency or instability (P < .001, r = 0.787), and unpredictability (P < .001, r = 0.776) with perceived stress in COVID-19 patients transferred from the intensive care units.

Conclusion

Based on the findings of the current study, both uncertainty and perceived stress are elevated among COVID-19 patients, and a significant and direct relationship exists between these two variables. Healthcare providers, particularly nurses, should address the uncertainties surrounding emerging diseases, both at the hospital and community levels.

Keywords: COVID-19, intensive care, uncertainty, anxiety, stress

Introduction

Since late 2019, the outbreak of a new virus from the coronavirus family has posed a threat to the health and safety of human societies (Doshmangir et al., 2019; Neher et al., 2020). The coronavirus disease of 2019 (COVID-19) leads to a wide range of physical symptoms in affected individuals. The severity of these symptoms varies among individuals and spans from asymptomatic cases to the development of multiple organ dysfunction syndrome (MODS) and mortality (Khadka et al., 2020; Singhal, 2020). Additionally, the repercussions of this disease are not limited to physical issues but also affect the mental well-being of individuals. Studies have shown that anxiety and depression levels have increased in communities after the COVID-19 pandemic (Yan et al., 2021). The results of a study conducted in the United States in 2021 indicated a significant rise in psychological damages, including anxiety, following the spread of COVID-19 (Daly & Robinson, 2021). The high prevalence of the disease and its unpredictable nature, health threats, and changes in social norms, including the imposition of restrictions, have all been reported as sources of stress during the COVID-19 pandemic (Nabi Foodani et al., 2023; Seyedin et al., 2022).

In comparison to other community members, patients with COVID-19 are more susceptible to psychological impairments. These individuals may experience varying degrees of anxiety, depression, and anger for various reasons, including the perceived threat of disease, social isolation, physical discomfort, medication side effects, financial burden from treatment, and fear of transmitting the virus to others (Dolatabadi et al., 2022). One of the most common psychological impairments in these patients is stress. Stress refers to an individual's process of adaptation when confronted with internal and external challenges (Dolatabadi et al., 2023; Graves et al., 2021). Therefore, the level of stress is determined not only by internal and external events but also by an individual's perspective and interpretation of these events (Lazarus & Folkman, 1984). According to Lazarus and Folkman's theory (1984), perceived stress refers to an individual's overall understanding and interpretation of vulnerability to stressors (Shokri et al., 2020). Contracting unfamiliar diseases can significantly elevate the level of perceived stress. In a study conducted by Lee et al. (2007) on individuals affected by severe acute respiratory syndrome (SARS), which shares significant structural similarities with the COVID-19 virus, it was demonstrated that patients experience elevated levels of perceived stress even 1 year after hospital discharge and recovery. This stress was accompanied by high levels of depression, anxiety, and posttraumatic stress (Sirati Nir et al., 2020).

The stress induced by COVID-19 can significantly impact individuals’ health, potentially causing more harm than the disease itself (Li, Tian, et al., 2021). Stress, in general, can alter an individual's psychological and physiological functioning, leading to the emergence of other conditions, including psychological disorders (such as depression and memory impairment), chronic illnesses (cancer, diabetes, cardiovascular diseases, asthma, and rheumatoid arthritis), and pain disorders (Mishel & Braden, 1988; Seyedin et al., 2015; Zhang, 2017). One of the stress-inducing factors in COVID-19 patients is disease uncertainty. Disease uncertainty refers to the inability to assign meaning to events related to the illness. In situations where the patient or their family cannot evaluate events or predict disease outcomes due to a lack of sufficient information, they experience distress due to disease uncertainty (Liu et al., 2020). Disease uncertainty is more prevalent during the stages of diagnosis and treatment initiation because patients are confronted with new and unfamiliar experiences (Hagen et al., 2015). However, disease uncertainty has been observed in all stages of diagnosis, treatment, recovery, and even after disease improvement.

Review of Literature

Numerous studies have investigated the perceived stress levels among hospitalized COVID-19 patients. Bramanti et al. (2021) conducted a cross-sectional study in Italy, revealing elevated perceived stress levels among hospitalized COVID-19 patients with chronic diseases (Bramanti et al., 2021). In a similar vein, the work of Bonazza et al. (2020) explored the psychological outcomes after hospitalization for COVID-19, emphasizing the role of isolation and fear of the unknown in contributing to heightened stress levels. These studies collectively highlight the importance of assessing and addressing perceived stress as a critical component of the overall well-being of hospitalized COVID-19 patients (Bonazza et al., 2020).

Understanding the level of uncertainty experienced by COVID-19 patients during hospitalization is equally vital. Koffman et al. (2020) delved into the uncertainties faced by healthcare providers and patients related to treatment outcomes, potential complications, and the overall trajectory of their situations. The study revealed that a lack of clear information and communication exacerbated the sense of uncertainty among patients and healthcare providers (Koffman et al., 2020). Additionally, a study conducted by Hagen et al. (2015) aimed to investigate the impact of disease uncertainty on cancer patients and demonstrated a significant correlation between disease uncertainty and hospital-related stress and depression (Hagen et al., 2015). However, there are limited studies in the field of uncertainty of disease.

In a study conducted by Zandifar et al. (2020) in Iran, the prevalence and severity of depression, stress, anxiety, and perceived stress among COVID-19 patients were investigated. The results of this study indicate a high to moderate level of perceived stress among individuals afflicted with COVID-19 (Zandifar et al., 2020). However, uncertainty in the disease and its relationship with perceived stress was not examined in this study.

While existing research provides valuable insights into perceived stress and uncertainty among hospitalized COVID-19 patients, there are notable gaps that warrant further investigation. Few studies have explored the association between uncertainty and perceived stress among hospitalized COVID-19 patients in Iran.

In conclusion, the literature on perceived stress and level of uncertainty among hospitalized COVID-19 patients highlights the multifaceted challenges faced by individuals during their hospitalization. As the pandemic continues to evolve, ongoing research efforts are essential to inform targeted interventions, improve patient care, and enhance mental health outcomes for this vulnerable population.

With the recent emergence of COVID-19, studies investigating uncertainty and stress in affected patients have been limited. Moreover, despite the extensive psychological health implications, this aspect of the disease has received less attention. Additionally, due to the novel and acute nature of this disease, there have been few quantitative investigations into uncertainty and perceived stress in COVID-19 patients. Therefore, to address this informational gap, our study aimed to examine the relationship between disease uncertainty and perceived stress in COVID-19 patients.

Methods

This study adheres to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.

Study Design and Setting

The present study is conducted as an analytical cross-sectional study. From the second half of 2021 to the first half of 2022, a total of 212 COVID-19 patients who had been initially admitted to the intensive care units (ICUs) of selected hospitals affiliated with Tehran University of Medical Sciences (Iran) were included in the study. The selected hospitals for inclusion were those admitting COVID-19 patients during this period. It is important to note that, due to the unique circumstances of the COVID-19 pandemic, certain hospitals opted not to admit COVID-19 patients to prioritize other cases. This decision was made in the interest of infection control. Consequently, we specifically chose hospitals that did admit COVID-19 patients for the purpose of our study. The patients were later transferred to general wards within the same hospitals. The research employed a convenience sampling method. The inclusion criteria for the study included the absence of diagnosed cognitive and perceptual disorders, no diagnosed history of mental and psychological illnesses, the ability to read and write for questionnaire completion, a definitive diagnosis of COVID-19, and a Glasgow Coma Scale (GCS) score of 15 to assess alertness. These criteria were carefully selected to ensure the absence of prior predisposition of patients to psychological issues such as stress and to evaluate their ability to complete the questionnaires. The exclusion criterion for the study was incomplete questionnaire responses exceeding 10%.

Sample Size

The sample size was calculated considering a significance level of .05, a statistical power of 0.80, and a minimum correlation coefficient of 0.20. Based on the formula provided, a sample size of 194 individuals was calculated. Taking into account a 10% potential dropout rate, the sample size was increased to 214 individuals.

n=[Z1−α2+Z1−β0.5ln(1+r1−r)]2+3=(1.96+0.840.5×0.618)2+3≈194

Data Collection and Measurement

Three instruments were utilized to collect data for this study. These instruments included the Demographic Information Questionnaire, the Mishel Uncertainty in Illness Scale (MUIS) for disease uncertainty, and the Perceived Stress Questionnaire.

The MUIS comprises 33 items within a Likert-type spectrum ranging from (1) strongly disagree to (5) strongly agree. The score range of this tool is from 33 to 165, with higher scores indicating higher levels of illness-related uncertainty. The original version of this questionnaire's validity and internal consistency was assessed for caregivers of patients with various chronic diseases, and its alpha coefficient was reported to range from 0.64 to 0.89 across domains (Mishel, 1981). This tool has been used in various studies and its validity and reliability have been measured. The Persian version of this questionnaire has been psychometrically evaluated by Sajjadi et al., demonstrating adequate internal consistency (Cronbach's alpha of 0.89) and satisfactory internal homogeneity (Ahmadian, 2012).

The Perceived Stress Questionnaire consists of 14 items, each rated on a five-point Likert scale (none, low, moderate, high, and very high) (Hatamabadi et al., 2022). Ahmadian (2012) examined the validity and reliability of the Persian version of this tool, revealing internal consistency coefficients through Cronbach's alpha of 0.71 for the positive perception of controllability, 0.75 for the negative perception of controllability, and 0.84 for the overall questionnaire scores (Ahmadian, 2012). Additionally, correlations obtained for the positive perception of controllability ranged from 0.49 to 0.70, and for the negative perception of controllability, it ranged from 0.52 to 0.77, while the correlation coefficients for the total controllability perception scale ranged from 0.51 to 0.78 (Grasselli et al., 2020).

After obtaining ethical approval, the researcher visited the post-ICU sections of the selected hospitals affiliated with Tehran University of Medical Sciences. Following self-introduction to the relevant authorities and units under study and obtaining their permission, the study tools were provided to the research units for completion. Ethical considerations, including the confidentiality of participants’ information, were diligently addressed. Additionally, patients’ rights were fully preserved through the establishment of trust, detailed explanation of confidentiality measures, and obtaining informed consent from all participants.

Quantitative Variables and Statistical Analysis

For data analysis, both descriptive and inferential statistics were employed using IBM SPSS Statistics version 25. In the descriptive statistics section, frequency indices, percentage frequencies, mean, and standard deviation were reported. In the inferential statistics section, the Kolmogorov–Smirnov test was utilized to assess the normality of the variables. If the variables were found to be parametric, independent t-tests, analysis of variance (ANOVA), Pearson correlation coefficient, and regression analysis were used. For nonparametric variables, those not following a normal distribution, the Mann–Whitney U test, the Kruskal–Wallis test, and Spearman's correlation coefficient were employed. Multiple regression analysis was used to investigate the relationship between independent variables and dependent variables.

Ethical Approval

The Ethics Committee at the School of Nursing and Midwifery, Tehran University of Medical Sciences, approved this study (IR.TUMS.FNM.REC.1401.004). Ethical considerations, including the confidentiality of participants’ information, were diligently addressed. Additionally, patients’ rights were fully preserved through the establishment of trust, a detailed explanation of confidentiality measures, and obtaining informed consent from all participants.

Results

In the current study, a total of 212 COVID-19 patients were hospitalized in selected hospitals affiliated with Tehran University of Medical Sciences from the second half of the year 2021 to the first half of the year 2022. The participants, with an average age of 44.73 ± 11.66 years falling within the age range of 18 to 65 years, had a mean duration of hospitalization in the ICUs of 9.15 ± 4.26 days. The demographic characteristics of the study participants are presented in Table 1. The mean and standard deviation of the uncertainty score were relatively high, measuring 111.45 ± 31.05. The level of uncertainty was high in 127 patients (59.9%), moderate in 25 patients (11.8%), and low in 60 patients (28.3%) who were transferred to general wards from the ICUs. Other subscales of uncertainty are reported in Table 2. The mean and standard deviation of the perceived stress score were relatively high, measuring 37.18 ± 11.61. The level of perceived stress was high in 133 patients (62.7%), moderate in 51 patients (24.1%), and low in 28 patients (13.2%) who were transferred from the ICUs (see Table 2).

Table 1.

Univariate Analysis Between Sociodemographic Variables, Uncertainty, and Perceived Stress.

Demographic characteristics Number Percentage Uncertainty Perceived stress
Mean ± SD P-value Mean ± SD P-value
Gender Female 100 47.2 114.33 ± 29.96 P = 0.204 38.01 ± 11.62 P = 0.329
Male 112 52.8 108.89 ± 31.91 36.44 ± 11.60
Marital status Single 28 13.2 103.78 ± 34.60 P = 0.211 33.32 ± 12.79 P = 0.133
Married 147 69.3 113.96 ± 30.20 38.38 ± 11.24
Death of partner 32 15.1 109.50 ± 31.85 35.01 ± 7.14
Divorced 5 2.4 93.20 ± 22.87 35.40 ± 12.22
Education Diploma and subdiploma 115 54.2 111.98 ± 31.06 P = 0.628 37.47 ± 11.36 P = 0.475
Bachelor's degree and higher 97 45.8 109.43 ± 31.27 36.06 ± 12.57
Job Has an official job 85 40.1 115.71 ± 29.06 P = 0.102 36.60 ± 10.05 P = 0.377
Does not have an official job 127 59.9 108.60 ± 32.11 38.04 ± 10.94
Underlying disease Yes 119 56.1 110.58 ± 30.83 P = 0.646 37.30 ± 12.23 P = 0.897
No 93 43.9 112.56 ± 31.46 37.09 ± 11.15
Age (year) Mean (standard deviation) Pearson correlation coefficient P-value Pearson correlation coefficient P-value
44.73 (11.66) r = .066 P = 0.338 r = .089 P = 0.199
Duration of hospitalization in the intensive care unit (days) 9.15 (4.26) r = 0.446 P < .001 r = 0.438 P < .001
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Table 2.

Descriptive Statistics Related to Uncertainty and Perceived Stress.

Research variables Mean ± SD Leveling
Low number (percentage) Moderate number (percentage) High number (percentage)
Uncertainty 111.45 ± 31.05 60 (28.3) 25 (11.8) 127 (59.9)
Ambiguity 45.63 ± 12.71
Complexity 25.08 ± 6.76
Inconsistency or instability 22.93 ± 7.56
Unpredictability 17.80 ± 5.17
Perceived stress 37.18 ± 11.61 28 (13.2) 51 (24.1) 133 (62.7)
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A statistically significant relationship was found between the duration of hospitalization in the ICU, the uncertainty of illness, and the perceived stress of COVID-19 patients transferred from the ICUs (p < .05). Specifically, as the duration of hospitalization in the ICU increased, both the level of uncertainty about the illness and the perceived stress of COVID-19 patients transferred from the ICUs also increased. The relationship between perceived stress, uncertainty, and other demographic variables is reported in Table 1.

The Pearson correlation coefficient matrix results showed a positive and significant relationship between uncertainty about the illness (P < .001, r = 0.829), ambiguity (P < .001, r = 0.795), complexity (P < .001, r = 0.835), inconsistency or instability (P < .001, r = 0.787), and unpredictability (P < .001, r = 0.776) with perceived stress in COVID-19 patients transferred from the ICUs. This indicates that as uncertainty about the illness increases in COVID-19 patients transferred from the ICUs, the level of perceived stress also increases (Table 3).

Table 3.

Matrix of Pearson Correlation Coefficients Between Perceived Stress and Uncertainty Subscales.

Research variables Uncertainty Ambiguity Complexity Inconsistency or instability Unpredictability Perceived stress
Uncertainty 1
Ambiguity r = 0.977 1
p < .001
Complexity r = 0.957 r = 0.902 1
p < .001 p < .001
Inconsistency or instability r = 0.967 r = 0.908 r = 0.933 1
p < .001 p < .001 p < .001
Unpredictability r = 0.936 r = 0.896 r = 0.856 r = 0.888 1
p < .001 p < .001 p < .001 p < .001
Perceived stress r = 0.829 r = 0.79 r = 0.835 r = 0.787 r = 0.776 1
p < .001 p < .001 p < .001 p < .001 p < .001
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A stepwise multiple regression analysis was performed to examine the relationship between demographic variables and quantitative variables. Initially, the assumptions of the regression model were tested, and all assumptions were met. The results of the multiple regression analysis indicate that uncertainty about the illness and the duration of stay in the ICU have significant predictive power for perceived stress.

Uncertainty about the illness had the highest standardized beta coefficient (0.790) on perceived stress. This means that with an increase of one standard deviation in uncertainty about the illness, there is a 0.790 increase in perceived stress in COVID-19 patients transferred from ICUs. Furthermore, the results showed that the duration of stay in the ICU had a standardized beta coefficient of .085, following uncertainty about the illness, indicating that with an increase of one standard deviation in the duration of stay, there is a .085 increase in perceived stress in COVID-19 patients transferred from ICUs (Table 4).

Table 4.

Regression Model to Predict Perceived Stress Among COVID-19 Patients.

Variables β Standard error t P-value
Standard Nonstandard
Constant - 2.11 1.682 1.255 0.211
Uncertainty 0.790 6.290 .016 18.431 >.001
Duration of hospitalization in the intensive care unit .085 0.233 0.117 1.993 .048
Summary of the model F = 235.083 P < .001 R-square  = 0.692 Adjusted R-square = 0.689
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Discussion

The findings of the current study demonstrate a significant and positive relationship between uncertainty and perceived stress in COVID-19 patients. Additionally, according to the final regression model, uncertainty in the disease and the duration of hospitalization in the ICU predict perceived stress significantly in this group of patients.

In the present study, the mean age of participants was 44.73 ± 11.66 years, ranging from 18 to 65 years. The results of the study by Hatamabadi et al. (2020) indicated that the mean age of COVID-19 patients hospitalized in hospitals was 60 years, with an age range of 46 to 74 years (Gardashkhani et al., 2021). In the study by Grasselli et al. (2020), the mean age was 63 years (Li, Huang, et al., 2021), and in the study by Gardashkhani et al. (2021), the mean age was 51.67 years (Zhang, 2017). The average age of participants in the current study was lower compared to other conducted studies.

Briefly, in the present study, the hospitalization rate of men in the ICUs was higher than that of women. A review study by Li et al. (2021), which examined a total of approximately 281,000 individuals from both hospitalized and nonhospitalized populations through a review of 212 studies, reported that the infection rate of men with COVID-19 was 51.9% and women's infection rate was 48.9% (Freeston et al., 2020), which is consistent with the results of the current study. This slight difference could possibly stem from women's more responsible behavior in dealing with pandemics and diseases.

The results of the current study indicate that uncertainty is at a high level in COVID-19 patients, with a mean score of 31.05 ± 45.111 (59.5% of the population). Notably, the number of individuals at different levels of uncertainty does not follow a strict descending pattern, and the number of individuals who have experienced high and/or low uncertainty (28.3%) is greater than those at an average level (11.8%). The present study supports Michel's theoretical hypotheses about uncertainty. According to Michel's theory, when an unusual and ambiguous event like COVID-19 occurs, uncertainty about it is expected to be high due to the low familiarity of society with it (Dong et al., 2022). Moreover, in the current study, after ambiguity, the dimension of the highest uncertainty score was noted. In the case of COVID-19, this unfamiliarity and lack of knowledge are believed to contribute to uncertainty (Lan et al., 2021). A study conducted by Dong et al. (2022) reported an average level of uncertainty in COVID-19 patients (12.5 ± 52.2), which differs from the current study. This difference could be attributed to varying criteria for including patients in the study. Patients in Dong's study were those attending a mobile medical center, while the participants in the current study were patients who had been admitted to the ICU for at least 24 h.

Furthermore, the results of the current study do not align with the study conducted by Lan et al. (2021). This study, which focused on 56 COVID-19 patients, reported a lower level of uncertainty in these patients with a score of 17.25 ± 66.26. However, despite the difference in the level of uncertainty, the study by Lan et al. (2021) also found that, like the current study, the highest uncertainty score was attributed to the dimension of ambiguity among various dimensions of uncertainty (Kovács et al., 2021). One possible reason for this discrepancy is that COVID-19 is a novel disease, and its long-term effects are still uncertain. Also, a qualitative study by Shahabi et al. (2020) in Iran emphasized the global nature of uncertainty experienced by Iranian people during the COVID-19 pandemic (Shahabi et al., 2020). The results of this study are aligned with the current study; however, the participants in this study differ from those in the current study.

The results of the current study highlight that perceived stress in COVID-19 patients who were hospitalized in the ICU for at least 24 h is high. The study by Faghankhani et al. (2022) in Iran indicated that over half of the study population had high stress levels, and those who were hospitalized experienced more stress compared to other individuals (Faghankhani et al., 2022). Furthermore, in another study conducted in Tehran, Iran, perceived stress among hospitalized COVID-19 patients was reported to be moderate to high (Zandifar et al., 2020). The proximity of these results to each other is likely due to the close alignment of the contexts and cultural conditions prevailing in the Iranian society. Similarly, the study by Kovács et al. (2021) revealed that the perceived stress level in healthcare workers was high and not significantly different from that of COVID-19 patients (Cui et al., 2021). These findings are consistent with the current study. Also, in a study conducted by Dousti et al. (2021) in Iran, high perceived stress was observed in COVID-19 patients (Dousti et al., 2021). These results are consistent with the findings of the present study.

The findings of the current study, in line with its main objective, demonstrate a positive and meaningful relationship between uncertainty in the disease and factors such as ambiguity, complexity, contradiction, and unpredictability, with perceived stress in COVID-19 patients. This finding is well supported by the study conducted by AlHadi et al. (2021). This study mentioned that problems such as depression, anxiety, and stress are exacerbated by uncertainty and intolerance of uncertainty (AlHadi et al., 2021). The research by Cui et al. (2021) on patients with SLE also indicated a strong and positive relationship between uncertainty and mental health problems such as stress, anxiety, and depression, similar to the current study (Cui et al., 2021).

Strengths and Limitations

It is essential to consider the limitations of each study alongside its findings. One limitation of the present study is the nonrandom nature of the sampling method, which may affect the generalizability of the study's findings. To mitigate this limitation, the research was conducted in large hospitals in Tehran and followed a multicenter approach. For future studies, it is recommended to investigate uncertainty and perceived stress in emerging and recurring diseases.

Implications for Practice

This study revealed that both uncertainty and perceived stress are elevated among COVID-19 patients, and a significant and direct relationship exists between these two variables. These findings emphasize the necessity for healthcare providers, particularly nurses, to actively address uncertainties associated with emerging diseases at both hospital and community levels.

Conclusion

The present study reveals a substantial increase in both uncertainty and perceived stress among COVID-19 patients, underscoring a significant and direct correlation between these variables. Moreover, the observed positive correlation between disease-related uncertainty and perceived stress suggests that targeted interventions to reduce uncertainty may effectively contribute to alleviating perceived stress among patients. These insights not only advance our comprehension of the psychological aspects of COVID-19 but also offer practical implications for healthcare professionals, policymakers, and researchers in the ongoing endeavor to enhance patient well-being during the pandemic.

Acknowledgments

We thank all the patients who participated in this study.

Footnotes

Author Contribution: MNF write the manuscript, ZAD was the methodologist, AR collected the data, AR provided statistical analysis, ZJ submitted the manuscript, and MZ supervised the research.

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethical Statement: This study was conducted after receiving the code of ethics (IR.TUMS.FNM.REC.1401.004).

Funding: The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iD: Zakiyeh Jafaryparvar https://orcid.org/0000-0003-0111-1784

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