Introduction

Background

Coronavirus Disease 2019 (COVID-19), which caused a global pandemic in 2020, is known to be the third coronavirus deadly to humans, following Severe Acute Respiratory Syndrome (SARS) in 2003 and Middle East Respiratory Syndrome (MERS) in 2012 [1]. The SARS pandemic in 2003 and the novel influenza A (H1N1) virus pandemic in 2009 also had a significant impact on people’s lives, socioeconomic activities, and population movements [2], but compared to the previous pandemics, COVID-19 spread extensively on an unprecedentedly large scale [3]. In the early stage of the pandemic, COVID-19 was a deadly respiratory virus which could be easily transmitted from person to person and for which humans had no acquired immunity [4]. Also, many of the people infected with COVID-19 were asymptomatic, and people without symptoms could also spread the disease [4]. These characteristics of COVID-19 led to an unprecedented pandemic situation, and put the entire world in a state of a high level of uncertainty [5]. In particular, uncertainty about the transmissibility and case fatality rate of COVID-19 greatly increased fear and dread of the disease [6]. Fear of COVID-19 is an emotional response related to the transmissibility and case fatality rate of the virus. This fear can be further amplified as people experience loss of control over their life due to the characteristics of the virus, which is reported to be contagious and deadly to humans even during the asymptomatic incubation period [6], and such fear can also cause psychological distress [7].

During an early stage of a pandemic, individuals rely on media to reduce uncertainty and mitigate their fear, but repeated and long-term exposure to ambiguous or dramatic information through media may cause people to experience a continuous state of uncertainty and psychological distress [8]. In addition, misinformation can act as a major health risk factor in a pandemic situation, and may cause individuals not to follow recommended precautions for infection prevention, which can worsen the epidemic situation and cause an enormous social chaos [9]. Moreover, preconceptions related to previously known pathogens with similar characteristics made it difficult to reach a consensus about scientific evidence on new pathogens such as COVID-19. As a result, government agencies applied and interpreted scientific evidence in different ways, causing individuals to experience uncertainty [10]. Eventually, as there frequently occur situations where the government’s public health measures are ineffective due to the failure of media and the proliferation of misinformation, individuals who experience uncertainty and psychological distress may have difficulty sharing values that lead them to take responsibility for themselves and their communities [11], and may not follow the government’s recommendations due to weakened social conscience and solidarity [12].

Since uncertainty perceived by individuals in a pandemic situation can be considered an important factor that needs to be managed for adaptive coping, it is necessary to meticulously examine phenomena related to uncertainty experienced at the individual level. In this connection, Mishel’s uncertainty in illness theory (UIT) is the first theory that applied the concept of uncertainty to the context of illness, and UIT presents explanations about the uncertainty perceived by individuals in situations related to illness, diagnosis, and treatment [13]. Although UIT has been utilized in many areas of nursing practice related to acute and chronic diseases by applying the theory to patients or guardians of patients experiencing an illness event [14], a new approach is required to explain the uncertainty perceived by individuals who are not infected with COVID-19 but are at risk of infection for a considerable period of time in a pandemic situation. Therefore, this study attempted to develop a theory that explains the phenomena related to uncertainty about COVID-19 infection by using UIT as a guide for explaining the phenomenon of interest according to the strategy of theory derivation proposed by Walker and Avant [15]. The theory developed in this study is expected to contribute to efforts to manage uncertainty perceived by individuals and improve their health status in a pandemic situation by providing specific explanations about the composition of uncertainty on COVID-19 infection perceived at the individual level and about the overall processes of appraising and coping with the uncertainty.

Theoretical framework: Uncertainty in Illness Theory (UIT)

‘Uncertainty in Illness Theory (UIT)’ proposed by Mishel is the first theory that applied the concept of uncertainty to the context of health or illness, and this theory explains uncertainty in the diagnosis and treatment processes of illness and in the state of illness showing continuous deterioration [14]. Uncertainty, a central concept of UIT, is defined as ‘the inability to determine the meaning of illness-related events.’ Uncertainty is a cognitive state that occurs when an individual is unable to appropriately structure or categorize disease-related events due to insufficient cues, and uncertainty arises when a person cannot assign a definite value to disease-related events or clearly predict the outcomes [13]. UIT is a theory that applied the stress-appraisal-coping-adaptation structure presented by Lazarus and Folkman to uncertainty in the context of illness, and UIT is composed of a linear model centered on three themes: ① antecedents of uncertainty, ② appraisal of uncertainty, and ③ coping with uncertainty (Figure 1) [14]. UIT states that uncertainty in illness is divided into the following four forms of uncertainty: (a) ambiguity about disease status; (b) complexity related to treatment and the health care system; (c) lack of information about the diagnosis and severity of illness; (d) unpredictability of disease course and prognosis. In addition, according to UIT, uncertainty is neither considered desirable nor avoided until it has been appraised, and adaptation occurs when coping is effective after it has been assessed as a danger or an opportunity [13].

Purpose

This study aimed to develop a middle-range theory that can specifically and comprehensively explain the phenomena related to uncertainty on COVID-19 infection experienced by individuals who did not contract COVID-19 in a pandemic situation.

Methods

This study developed a theory by using the strategy of theory derivation proposed by Walker and Avant. Theory derivation is a process in which a set of interrelated concepts or an entire structure is transferred from one field to another and modified to fit the new field, and in this process, the method of analogy is used to explain or predict phenomena in another field by using explanations or predictions in one field [15]. The procedure of theory derivation presented by Walker and Avant is as follows: (a) Explore phenomena of interest and find insight into new concepts and structures through a literature review; (b) get ideas and discover useful analogies through an extensive literature review in other fields; (c) select a parent theory that provides useful concepts and a relevant structure that can explain the phenomenon of interest, redefine the concepts and statements of the parent theory, and develop new concepts and statements; (d) relevantly modify the structure of the parent theory so that the modified structure can better explain the phenomenon of interest [15].

PubMed, Web of Science, Scopus, PsycInfo, and CINAHL were used as the major databases for a literature review, and KMbase, KoreaMed, KISS, ScienceOn, and RISS were also employed for domestic literature searches. For search terms, Uncertainty AND COVID-19 OR coronavirus OR SARS-CoV-2 or the Korean word for uncertainty AND the Korean word for corona OR COVID were used. The literature search targeted the literature published from January 2020 to April 2021 in order to consider the situation in the early stage of the pandemic, when there was a high level of uncertainty about COVID-19 infection due to the lack of an established body of scientific knowledge on the characteristics of the pathogen, prevention, and treatment of COVID-19. The inclusion criteria for literature selection were as follows: articles written in English or Korean; studies conducted with the participants selected from the general population; and studies dealing with concepts related to uncertainty on COVID-19 or relationships between the concepts. Regarding the exclusion criteria for literature selection, this study excluded articles that dealt with fields (industry, economy, education, statistics, nutrition, etc.) or areas (diagnosis, treatment, and care) not related to COVID-19 infection and uncertainty. In addition, articles that dealt with populations vulnerable to COVID-19 infection, such as healthcare workers, caregivers, patients with chronic diseases, patients with neuropsychiatric disorders, confirmed COVID-19 patients, pregnant women, and migrant workers, were also excluded. In this study, it was considered appropriate to exclude studies on vulnerable populations from the analysis in order to exclude heterogeneous characteristics between population groups from the main concepts for theory construction. This is due to the fact that in the context of the COVID-19 pandemic, what people with chronic diseases or mental health problems or people providing treatment or care for patients such as healthcare workers and caregivers experienced could be significantly different from what the general population experienced in terms of the perception of uncertainty on COVID-19 infection and the levels and patterns of psychological distress from the uncertainty, including the perceived threat [16,17]. The researcher selected articles by reviewing titles, abstracts, and full-texts, and when it was unclear whether specific articles met the inclusion and exclusion criteria, whether to include them was determined through discussion and consensus between the researchers. In addition, when theories or previous studies that could contribute to explaining the phenomenon of interest were identified during the literature review process, a separate review of the articles was conducted.

In addition, this study used the strategy of concept synthesis presented by Walker and Avant in order to classify the forms of uncertainty on COVID-19 infection. The classification of the forms of uncertainty on COVID-19 infection was conducted to describe the relationship between uncertainty and its antecedents. Concept synthesis is a strategy used when the dimensions related to the phenomenon of interest are unclear or unknown. It is the process of classifying and grouping phenomena and naming the groups of phenomena based on observations or the literature related to the phenomenon of interest [15]. As for the data used for concept synthesis in this study, among articles selected for theory derivation, those that included variables or conceptual descriptions representing the meanings and dimensions of uncertainty were considered. In the context of disease, uncertainty refers to the psychological state of ‘not knowing’ [18], and the major dimensions through which uncertainty is conceptualized are the source and issue. The source refers to the characteristics that are causes of uncertainty, and the issue refers to what is uncertain [19]. Based on the previous studies that dealt with the above-described meanings and dimensions of uncertainty among the selected articles, concept synthesis was performed to classify the forms of uncertainty on COVID-19 infection. The concept synthesis procedure suggested by Walker and Avant is as follows: (a) Create a table showing a list of variables or conceptual descriptions related to uncertainty on COVID-19 infection; (b) group closely related phenomena and classify the groups that appear to overlap; (c) name the classified groups by considering the clearest descriptions based on the literature review [15].

Results

Exploration of the phenomenon of interest

First, 7,942 domestic and foreign articles were retrieved by a literature search. After excluding duplicate articles, 2,429 articles remained. Out of the 2,429 articles, 2,267 articles that dealt with fields and areas unrelated to COVID-19 infection and uncertainty, and 113 articles that dealt with vulnerable populations as research subjects were excluded. As a result, 58 articles, including 9 articles additionally found by a separate manual search, were finally selected. Based on a comprehensive review of the articles selected for theory derivation, this study examined the major concepts that explain the phenomena related to uncertainty on COVID-19 as well as relationships between the concepts. In addition, 11 studies selected from 58 articles were reviewed for concept synthesis to classify the forms of uncertainty on COVID-19 infection.

Identification of theories and concepts related to the phenomenon of interest

The Health Belief Model (HBM) and Self-Affirmation Theory (SAT) provide useful concepts for explaining the process of appraising and coping with uncertainty on COVID-19 infection. According to HBM, health behaviors are affected not by the objective threat from a disease but by the subjectively perceived threat, and perceived threat is formed by a combination of perceived susceptibility and perceived severity [20]. Perceived susceptibility refers to the subjective perception and belief about the risk or likelihood of developing or contracting a disease, and perceived severity refers to the level of seriousness of the consequences of the disease as perceived by an individual. If the levels of perceived susceptibility and severity are low, the level of perceived threat also becomes low [21]. In addition, according to SAT, individuals identify aspects that are important and valuable to them in order to eliminate the influence of a specific threat, so the pressure of self-affirmation about a certain topic can be reduced through self-affirmation about another topic that is not related to the topic [22]. Therefore, ‘value-affirmation’ can not only increase psychological resources that enable individuals to cope with a threat by thinking of values important to them when they are faced with a threat that undermines personal integrity but also reduce stress generated by the threat [23].

Redefinition of the concepts and statements of the parent theory

This study selected UIT as the parent theory and investigated the concepts and structure of UIT that can be applied to explain the phenomena of interest. In addition, to explain the phenomena related to uncertainty regarding COVID-19 infection, the selected concepts were redefined, and new concepts were developed while maintaining the correspondence between the concepts of this theory and those of UIT (Table 1).

Definition of uncertainty on COVID-19 infection

Individuals who have not contracted COVID-19 may experience health-related uncertainty regarding COVID-19, and this uncertainty can be described as uncertainty about ‘the situations where COVID-19 infection occurs’ and ‘health-related situations that may result from the occurrence of COVID-19 infection’ [4,24,25]. Therefore, uncertainty on COVID-19 infection, which is a key concept of this study, is related to the situation related to the occurrence of COVID-19 infection, and more specifically, the uncertainty represents the uncertainty about ‘the situation in which COVID-19 infection occurs’ and ‘the health-related situation that may result from COVID-19 infection.’ Based on the above understanding of uncertainty on COVID-19 infection, the concept of uncertainty on COVID-19 infection was defined by redefining the concept of uncertainty in UIT as follows. In UIT, uncertainty is defined as ‘the inability to determine the meaning of a disease-related event’ [13], so uncertainty about COVID-19 infection was defined as ‘the inability to determine the meaning of situations related to the occurrence of COVID-19 infection.’ In addition, in order to understand the form of uncertainty on COVID-19 infection, variables or conceptual descriptions related to the meaning and dimension of uncertainty on COVID-19 infection were identified and organized. As a result, the clusters of phenomena closely related to uncertainty about COVID-19 infection were identified as ‘an insufficient amount of information on COVID-19’ [16,17], ‘inconsistent or conflicting information on COVID-19’ [26,27], ‘the lack of authenticity and reliability of information on COVID-19’ [28-30], ‘insufficient understanding of the situation related to COVID-19’ [31,32], and ‘key issues regarding COVID-19 that have not been scientifically proven’ [10,11]. These phenomena were grouped together and classified, and each category of the classified phenomena was named as follows: 1) insufficient information on COVID-19, 2) inappropriate information on COVID-19, 3) ambiguity of the situation related to the COVID-19 outbreak, and 4) scientific ambiguity related to COVID-19. In other words, the form of uncertainty on COVID-19 infection was classified into the above four types (Supplementary Table 1).

Antecedents of uncertainty on COVID-19 infection

1. Stimuli frame: epidemic control pattern, situation familiarity, and situation congruence

Uncertainty may be perceived when a person is unable to form a cognitive schema that can provide help for interpreting disease-related events [13]. The stimuli frame is composed of the epidemic control pattern, situation familiarity, and situation congruence, and constitutes a cognitive schema, which is an individual’s subjective interpretation of the situation related to the occurrence of COVID-19 infection. The ‘epidemic control pattern’ refers to the degree to which the COVID-19 epidemic is being controlled based on a decrease in the number of infected people through effective quarantine measures. ‘Situation familiarity’ refers to the degree to which situations related to the occurrence of contracting COVID-19 include repetitive or perceived cues, and ‘situation congruence’ refers to the consistency between what is expected and what actually occurs in situations related to the occurrence of contracting COVID-19. The epidemic control pattern, situation familiarity, and situation congruence can reduce uncertainty on COVID-19 infection by decreasing the ambiguity about situations related to the occurrence of COVID-19 infection.

2. Cognitive capacities

Cognitive capacities are an individual’s ability to process information, and when these capacities are limited, the individual’s ability to construct a stimuli frame is reduced [13]. ‘Cognitive capacities’ precede uncertainty on COVID-19 infection, and support the construction of the stimuli frame, but demand for excessive attention in the COVID-19 pandemic situation may cause uncertainty by interfering with the information processing of the stimuli frame.

3. Structure providers: trust in authorities, credible news media, and health literacy

Structure providers are available resources that help interpret the stimuli frame, and include trust in authorities, credible news media, and health literacy. ‘Trust in authorities’ refers to the degree of trust and confidence in the government’s quarantine measures and communications to manage the COVID-19 epidemic. When a public health emergency such as the COVID-19 pandemic occurs, increased trust in the policy implementation and information provision of the government can contribute to overcoming the pandemic situation [12]. Therefore, trust in the government’s disease prevention and control measures can indirectly reduce uncertainty on COVID-19 infection through the perception of the ‘epidemic control pattern.’ In addition, trust in the communication of the government can indirectly reduce uncertainty on COVID-19 infection by constructing ‘situation familiarity’ and ‘situation congruence’ based on up-to-date information or predictions about the situation related to the occurrence of COVID-19 infections. Additionally, it can directly decrease uncertainty on COVID-19 infection by reducing the perception that there is ambiguity or inappropriate information about the situations related to the COVID-19 outbreak.

‘Credible news media’ provide information that helps people to understand the meaning of situations related to the occurrence of COVID-19 infections. In a pandemic situation, news media act as an important source of information about the epidemic situation and infection prevention [33]. Credible news media can indirectly decrease uncertainty on COVID-19 infection by providing up-to-date information or predictions about the occurrence of COVID-19 infections and thereby helping to form a stimuli frame, and can directly decrease uncertainty by reducing ambiguity about situations related to the occurrence of COVID-19 infection or the perception that the information about the situations is inappropriate.

‘Health literacy’ helps to expand the knowledge base used to understand the meanings of situations related to the occurrence of COVID-19 infection. Health literacy refers to the motivation, knowledge, and ability required to access, understand, evaluate, and apply health information [34]. Based on health literacy, individuals can search for necessary health information and appropriately interpret it in the COVID-19 pandemic situation [30]. Health literacy can indirectly decrease uncertainty on COVID-19 infection by providing the meaning and context for situations related to the occurrence of COVID-19 infection and thereby forming a stimuli frame. It can also directly reduce uncertainty on COVID-19 infection by decreasing the level of perceived ambiguity about situations related to the occurrence of COVID-19 infection.

Appraisal of uncertainty on COVID-19 infection

1. Inference

Inference refers to the appraisal of uncertainty using related cases, based on the recall of past events, personality traits, and general experiences, and this process is based on the belief that major life events can be dealt with effectively [13]. Specifically, uncertainty on COVID-19 infection is a cognitive state in which a person cannot determine the meanings of ‘the situation in which COVID-19 infection occurs’ and ‘the health-related situation that may result from COVID-19 infection’, and uncertainty on COVID-19 infection can be perceived as the ‘perceived susceptibility’ and ‘perceived severity’ of COVID-19 infection in the inference process. Perceived susceptibility refers to the beliefs related to the likelihood of contracting COVID-19, and perceived severity refers to the beliefs related to the severity of contracting COVID-19. Uncertainty on COVID-19 infection can be assessed as a threat through the perceived susceptibility and perceived severity of COVID-19 infection.

2. Illusion

Illusion causes uncertainty to be appraised as an opportunity by leading people to place emphasis on the favorable aspects [13]. In a pandemic situation where the government’s disease prevention and control measures have been ineffective and the government’s decision-making processes are in a disorganized state, there may arise optimism bias, which is an irrational belief that negative events will not happen to oneself [35]. Therefore, as the COVID-19 pandemic worsens or continues, the perception that individuals’ coping behaviors are not capable of influencing the pandemic situation may result in an illusion that leads individuals to perceive uncertainty on COVID-19 infection as a preferred state.

Coping with uncertainty on COVID-19 infection

1. Threat and coping

Danger is a concept characterized by the absence of the action or intention of an agent. Typical examples of danger include infectious diseases, earthquakes, and climate phenomena. A threat is caused by an enemy, an agent with a malicious intention, and an enemy can be defined by a special context that explains the actual intention and functions of an agent [36]. In the case of COVID-19, which caused the worst pandemic of the 21st century, uncertainty on COVID-19 may be perceived as a threat, since infection events are expected to have clearly adverse consequences and are defined as an enemy by the public [37]. The perceived threats due to the COVID-19 pandemic are divided into realistic and symbolic threats. A realistic threat refers to a specific threat to individuals’ physical health or economic well-being, while a symbolic threat refers to a threat to the value system of a group, such as individuals’ religion, values, belief system, ideology, philosophy, or worldview [38]. Realistic and symbolic threats elicit different coping patterns. More specifically, a realistic threat induces people to perform preventive behaviors in the COVID-19 pandemic, and positively affects supportive attitudes toward preventive behaviors, whereas a symbolic threat prevents people from performing social distancing and personal hygiene rules, and negatively influences supportive attitudes toward such behaviors. In addition, although both realistic and symbolic threats cause negative emotions, including anxiety, symbolic threats generate avoidant responses to pandemic situations and give rise to positive emotions through individuals’ behavior to confirm their social identity [38].

Uncertainty on COVID-19 infection is assessed as a threat through the perceived susceptibility and perceived severity about COVID-19 infection through an inference process. A threat refers to the possibility of adverse outcomes for an individual’s physical and psychosocial conditions. When uncertainty on COVID-19 infection is assessed as a threat, preventive actions such as wearing masks and washing hands, information seeking for infection prevention, and body vigilance are considered as mobilizing strategies. Meanwhile, since humans are social beings who depend on cultural groups for their psychological well-being, they may experience a symbolic threat as group identity is weakened due to restrictive measures such as social distancing or isolation [38]. Therefore, when a person perceives that the values that he or she considers important are compromised in the process of coping with a threat, strategies such as value affirming, information avoiding, and situational vigilance may be mobilized. When mobilization strategies are not effective, affect-control strategies may be employed to control emotional responses, and the use of faith, disengagement, and cognitive support are considered [13].

2. Opportunity and coping

An opportunity represents the possibility of a positive outcome, and when uncertainty is assessed as an opportunity, buffering strategies are applied to block the inflow of new stimuli to maintain uncertainty [13]. Buffering strategies include avoidance, selective ignoring, reordering priorities, and neutralizing to prevent the inflow of new stimuli [13]. The COVID-19 pandemic weakened individuals’ normality in daily life, and the situation where unnatural ways of living continued led people not to take the threat seriously and made them have the will to avoid learning about the virus rather than trying to understand the mechanism of the transmission of COVID-19 in order to control the spread of the pandemic [39,40]. The state of incompetency where individuals’ coping behavior cannot influence the pandemic situation and the presence of a persistent threat due to the worsening epidemic situation may lead individuals to view the uncertain situation from a positive perspective through buffering strategies.

3. Physical and psychological outcomes

Physical and psychological outcomes refer to physical and psychological states resulting from the processes of appraising and coping with uncertainty on contracting COVID-19. Uncertainty on COVID-19 may lead to adverse psychological outcomes such as stress disorders, anxiety, and depression [16,17,27,28], and may set off stress responses within individuals’ emotional, behavioral, and physiological domains, thereby causing adverse physical conditions [41].

Establishment of the structure of the derived theory

The structure of the derived theory was established by modifying the structure of UIT, based on the relationships between the concepts that explain the phenomena related to uncertainty on COVID-19 infection. The theory of uncertainty on COVID-19 was constructed as a linear and unidirectional model mainly comprised of antecedents of uncertainty, appraisal of uncertainty, and coping with uncertainty (Figure 2).

Discussion

The theory of uncertainty on COVID-19 is a middle-range theory developed using the strategy of theory derivation proposed by Walker and Avant [15]. This study developed a new theory by redefining the concepts of UIT and modifying the structure of UIT in order to explain the phenomena related to uncertainty on COVID-19 infection experienced at the individual level. UIT explains the relationships between the concepts that constitute the construction, appraisal, and coping of uncertainty through the conceptualization of experiences about uncertainty perceived in the process of interpreting illness-related events. However, applying UIT to the phenomenon related to uncertainty on pandemic disease infections requires a careful, systematic analysis of the correspondence between the concepts of UIT and the phenomenon of interest. Therefore, this study developed the theory of uncertainty on COVID-19 through theory derivation based on UIT, and differences between the developed theory and UIT are as follows. First, UIT explains uncertainty in the diagnosis and treatment processes of a disease and in an illness state, but the theory developed in this study explains the uncertainty about infection experienced by individuals who have not contracted COVID-19 but are always at risk of infection in a situation where a body of scientific knowledge on COVID-19 has not been established. Second, while UIT explains that uncertainty is assessed as a danger as the possibility of adverse outcomes, the developed theory explains that uncertainty on COVID-19 infection is appraised as a threat through the perception of susceptibility and severity for COVID-19 infection. Third, UIT explains that uncertainty appraised as a danger triggers coping efforts to reduce uncertainty, while the developed theory explains that coping strategies that are contrary to existing strategies may be mobilized to regulate the cognitive responses resulting from the coping strategies mobilized as a result of judging uncertainty on COVID-19 infection as a threat.

The theory of uncertainty on COVID-19 developed through this study is a middle-range theory that has specificity that makes the developed theory applicable to practice. A middle-range theory is focused on specific situations and has a high level of specificity at the level of abstraction [42]. In addition, a middle-range theory is practically applicable at the level of nursing practice since a middle-range theory includes specific aspects such as particular situations, health conditions, population groups such as patient groups and age groups, places or practice areas (e.g., community), and nurses’ behaviors or interventions [43]. The theory developed in this study provides a specific and comprehensive explanation of the phenomena related to uncertainty on COVID-19 infection experienced by individuals. Further, the developed theory can contribute to efforts to improve individuals’ health because this theory pays attention to the biopsychosocial outcomes of uncertainty on COVID-19 infection perceived by the general population in the community.

This study has significance in that it is the first attempt to investigate the phenomena related to uncertainty about pandemic disease infections, focusing on COVID-19, from a perspective of the science of nursing. The developed theory explains how the general population cognitively processes stimuli regarding situations related to the occurrence of COVID-19 infection, and constructs meanings through the process, and this theory is focused on the individual-level experiences of appraising and coping with perceived uncertainty. The theory developed through this study has significance for nursing in that it is a middle-range theory that contains concreteness that enables its application to nursing practice, and can thereby contribute to managing uncertainty perceived by individuals and improving their health in future pandemic situations. Above all, the developed theory can be used to gain a comprehensive understanding of the phenomena related to uncertainty regarding pandemic disease infections experienced at the individual level, so it is expected to contribute to producing basic data required for the development of strategies to manage uncertainty regarding pandemic diseases in the future.

Lastly, in a pandemic situation, the scientific evidence about a new pathogen is not clear, making it difficult to reach a consensus, and this scientific uncertainty can lead to reconstructed uncertainty in a socio-political context, such as the establishment of public health policies [44,45]. The theory of uncertainty on COVID-19 explains that the capabilities of the government, media, and individuals as structure providers not only directly affect the perception of uncertainty on COVID-19 infection but also indirectly influence the perception of the uncertainty by helping to form a stimuli frame. In view of these research findings, it is suggested that the government should explore practical strategies, such as overhauling the health care system, exploring effective communication methods, establishing an integrated communication strategy to consistently provide reliable information through various media including social media, and developing and implementing measures and interventions for supporting the improvement of health literacy by helping individuals to possess the necessary knowledge and attitudes in a pandemic situation.

Conclusions

This study developed a theory that specifically and comprehensively explains the phenomena related to uncertainty on COVID-19 infection experienced at the individual level by applying the strategy of theory derivation proposed by Walker and Avant. The developed theory can hopefully contribute to efforts to manage the uncertainty on pandemic disease infections perceived by individuals, and improve biopsychosocial health in the community in the future. Meanwhile, this study has the following limitations. First, the theory developed through this study was not validated, so there is a need to validate the theory through follow-up research to verify the empirical validity of the relationships between the concepts explained by the theory. Second, another limitation of the proposed theory is that it is difficult to directly apply to vulnerable population groups. Therefore, follow-up research in the field of nursing should be conducted to derive more meaningful research results and richer implications in order to apply the developed theory to various groups and situations and supplement the theory.

Supplementary Materials

Figure 1.

Model of Uncertainty in Illness Theory (Mishel, 1988). Components highlighted in grey and concepts described in italics have been modified and redefined in the derived theory

Figure 2.

Model of Theory of Uncertainty on COVID-19. This model is derived from Uncertainty in Illness Theory (Mishel, 1988). Components and concepts from the UIT that are modified and redefined are highlighted in grey and described in italics. Newly added concepts are marked with an asterisk and described in italics.

References

• 1. Zhou P, Yang XL, Wang XG, Hu B, Zhang L, Zhang W, et al. A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature. 2020;579(7798):270–273. https://doi.org/10.1038/s41586-020-2012-7ArticlePubMedPMC
• 2. Xiao Y, Tang S, Wu J. Media impact switching surface during an infectious disease outbreak. Scientific Reports. 2015;5(1):7838. https://doi.org/10.1038/srep07838ArticlePubMedPMC
• 3. Wilder-Smith A, Chiew CJ, Lee VJ. Can we contain the COVID-19 outbreak with the same measures as for SARS? The Lancet Infectious Diseases. 2020;20(5):e102–e107. https://doi.org/10.1016/S1473-3099(20)30129-8ArticlePubMedPMC
• 4. Dangi RR, George M. A review on theories and models of disease causation for COVID-19. Social Science Research Network. 2020. Forthcoming.
• 5. Rettie H, Daniels J. Coping and tolerance of uncertainty: Predictors and mediators of mental health during the COVID-19 pandemic. American Psychologist. 2021;76(3):427–437. https://doi.org/10.1037/amp0000710ArticlePubMed
• 6. Finset A, Bosworth H, Butow P, Gulbrandsen P, Hulsman RL, Pieterse AH, et al. Effective health communication – a key factor in fighting the COVID-19 pandemic. Patient Education and Counseling. 2020;103(5):873–876. https://doi.org/10.1016/j.pec.2020.03.027ArticlePubMedPMC
• 7. Taylor S, Landry CA, Paluszek MM, Fergus TA, McKay D, Asmundson GJ. COVID stress syndrome: Concept, structure, and correlates. Depression and Anxiety. 2020;37(8):706–714. https://doi.org/http://doi.org/10.1002/da.23071ArticlePubMedPMC
• 8. He X, Zhang Y, Chen M, Zhang J, Zou W, Luo Y. Media exposure to COVID-19 predicted acute stress: A moderated mediation model of intolerance of uncertainty and perceived social support. Frontiers in Psychiatry. 2021;11:613368. https://doi.org/10.3389/fpsyt.2020.613368ArticlePubMedPMC
• 9. Krause NM, Freiling I, Beets B, Brossard D. Fact-checking as risk communication: The multi-layered risk of misinformation in times of COVID-19. Journal of Risk Research. 2020;23(7-8):1052–1059. https://doi.org/10.1080/13669877.2020.1756385Article
• 10. Tang JW. COVID-19: Interpreting scientific evidence–uncertainty, confusion and delays. BMC Infectious Diseases. 2020;20(1):653. https://doi.org/10.1186/s12879-020-05387-8ArticlePubMedPMC
• 11. Abel T, McQueen D. Critical health literacy in pandemics: The special case of COVID-19. Health Promotion International. 2021;36(5):1473–1481. https://doi.org/10.1093/heapro/daaa141ArticlePubMedPMC
• 12. Ölcer S, Yilmaz-Aslan Y, Brzoska P. Lay perspectives on social distancing and other official recommendations and regulations in the time of COVID-19: A qualitative study of social media posts. BMC Public Health. 2020;20(1):963. https://doi.org/10.1186/s12889-020-09079-5ArticlePubMedPMC
• 13. Mishel MH. Uncertainty in illness. Image: The Journal of Nursing Scholarship. 1988;20(4):225–232. https://doi.org/10.1111/j.1547-5069.1988.tb00082.xArticlePubMed
• 14. Bailey DE, Stewart J. Uncertainty in Illness Theory. In: Alligood MR, editor. Nursing Theorists and Their Work. 8th ed. St. Louis, MO: Mosby; 2013. p. 555-573..
• 15. Walker LO, Avant KC. Strategies for theory construction in nursing. 5th ed. Upper Saddle River NJ: Pearson Prentice Hall; 2005. 256 p.
• 16. Newby JM, O’Moore K, Tang S, Christensen H, Faasse K. Acute mental health responses during the COVID-19 pandemic in Australia. PloS one. 2020;15(7):e0236562. https://doi.org/10.1371/journal.pone.0236562ArticlePubMedPMC
• 17. Wang C, Pan R, Wan X, Tan Y, Xu L, Ho CS, et al. Immediate psychological responses and associated factors during the initial stage of the 2019 coronavirus disease (COVID-19) epidemic among the general population in China. International Journal of Environmental Research and Public Health. 2020;17(5):1729. https://doi.org/10.3390/ijerph17051729ArticlePubMedPMC
• 18. Kuang K. Reconceptualizing uncertainty in illness: Commonalities, variations, and the multidimensional nature of uncertainty. Annals of the International Communication Association. 2018;42(3):181–206. https://doi.org/10.1080/23808985.2018.1492354Article
• 19. Lipshitz R, Strauss O. Coping with uncertainty: A naturalistic decision-making analysis. Organizational Behavior and Human Decision Processes. 1997;69(2):149–163. https://doi.org/10.1006/obhd.1997.2679Article
• 20. Becker MH. The health belief model and sick role behavior. Health Education & Behavior. 1974;2(4):409–419. http://doi.org/10.1177/109019817400200407Article
• 21. Skiner CS, Tiro J, Champion VL. The Health Belief Model. In: Glanz K, Rimer BK, Viswanath K, editors. Health Behavior: Theory, Research, and Practice. 5th ed. San Francisco, CA: John Wiley & Sons; 2015. p. 75–94.
• 22. Steele CM. The psychology of self-affirmation: Sustaining the integrity of the self. Advances in Experimental Social Psychology. 1988;21:261–302. https://doi.org/10.1016/S0065-2601(08)60229-4Article
• 23. Sherman DK. Self‐affirmation: Understanding the effects. Social and Personality Psychology Compass. 2013;7(11):834–845. https://doi.org/10.1111/spc3.12072Article
• 24. Li X, Li T, Wang H. Treatment and prognosis of COVID‑19: Current scenario and prospects. Experimental and Therapeutic Medicine. 2021;21(1):1–10. https://doi.org/10.3892/etm.2020.9435ArticlePubMed
• 25. Voitsidis P, Nikopoulou VA, Holeva V, Parlapani E, Sereslis K, Tsipropoulou V, et al. The mediating role of fear of COVID‐19 in the relationship between intolerance of uncertainty and depression. Psychology and Psychotherapy: Theory, Research and Practice. 2021;94(3):884–893. https://doi.org/10.1111/papt.12315ArticlePubMedPMC
• 26. Farooq A, Laato S, Islam AKMN. Impact of online information on self-isolation intention during the COVID-19 pandemic: Cross-sectional study. Journal of Medical Internet Research. 2020;22(5):e19128. https://doi.org/10.2196/19128ArticlePubMedPMC
• 27. Holman EA, Thompson RR, Garfin DR, Silver RC. The unfolding COVID-19 pandemic: A probability-based, nationally representative study of mental health in the United States. Science Advances. 2020;6(42):eabd5390. https://doi.org/10.1126/sciadv.abd5390ArticlePubMedPMC
• 28. Lin D, Friedman DB, Qiao S, Tam CC, Li X, Li X. Information uncertainty: A correlate for acute stress disorder during the COVID-19 outbreak in China. BMC Public Health. 2020;2(1):1867. https://doi.org/10.1186/s12889-020-09952-3ArticlePubMedPMC
• 29. Mora-Rodríguez A, Melero-López I. News consumption and risk perception of COVID-19 in Spain. Comunicar. 2021;29(66):71–81. https://doi.org/10.3916/C66-2021-06Article
• 30. Okan O, Bollweg TM, Berens E-M, Hurrelmann K, Bauer U, Schaeffer D. Coronavirus-related health literacy: A cross-sectional study in adults during the COVID-19 infodemic in Germany. International Journal of Environmental Research and Public Health. 2020;17(15):5503. https://doi.org/10.3390/ijerph17155503ArticlePubMedPMC
• 31. Lalot F, Abrams D, Travaglino GA. Aversion amplification in the emerging COVID‐19 pandemic: The impact of political trust and subjective uncertainty on perceived threat. Journal of Community & Applied Social Psychology. 2021;31(2):213–222. https://doi.org/10.1002/casp.2490Article
• 32. Scarinci IC, Pandya VN, Kim YI, Bae S, Peral S, Tipre M, et al. Factors associated with perceived susceptibility to COVID-19 among urban and rural adults in Alabama. Journal of Community Health. 2021;46:932–941. https://doi.org/10.1007/s10900-021-00976-3ArticlePubMedPMC
• 33. Yan Q, Tang Y, Yan D, Wang J, Yang L, Yang X, et al. Impact of media reports on the early spread of COVID-19 epidemic. Journal of Theoretical Biology. 2020;502:110385. https://doi.org/10.1016/j.jtbi.2020.110385ArticlePubMedPMC
• 34. Sørensen K, Van den Broucke S, Fullam J, Doyle G, Pelikan J, Slonska Z, et al. Health literacy and public health: A systematic review and integration of definitions and models. BMC Public Health. 2012;12:80. https://doi.org/10.1186/1471-2458-12-80ArticlePubMedPMC
• 35. Asimakopoulou K, Coulson N, Gilbert D, Scambler S. COVID-19: Social and behavioural responses to chaotic decision making. BMJ (Clinical Research ed). 2021;372:n249. https://doi.org/10.1136/bmj.n249ArticlePubMed
• 36. Battistelli F, Galantino MG. Dangers, risks and threats: An alternative conceptualization to the catch-all concept of risk. Current Sociology. 2019;67(1):64–78. https://doi.org/10.1177/0011392118793675Article
• 37. Kruglanski AW, Molinario E, Lemay EP. Coping with COVID-19-induced threats to self. Group Processes & Intergroup Relations. 2021;24(2):284–289. https://doi.org/10.1177/1368430220982074Article
• 38. Kachanoff FJ, Bigman YE, Kapsaskis K, Gray K. Measuring realistic and symbolic threats of COVID-19 and their unique impacts on well-being and adherence to public health behaviors. Social Psychological and Personality Science. 2021;12(5):603–616. https://doi.org/10.1177/1948550620931634Article
• 39. Zizek S. Pandemic!: COVID-19 shakes the world. 1st Kor. Ed. Kang WS, translator. Seoul: BookHouse; 2020. 200 p.
• 40. Zizek S. Pandemic! 2: Chronicles of a time lost. 1st Kor. Ed. Kang WS, translator. Seoul: BookHouse; 2021. 268 p.
• 41. Gica S, Kavakli M, Durduran Y, Ak M. The effect of COVID-19 pandemic on psychosomatic complaints and investigation of the mediating role of intolerance to uncertainty, biological rhythm changes and perceived COVID-19 threat in this relationship: a web-based community survey. Psychiatry and Clinical Psychopharmacology. 2020;30(2):89–96. Article
• 42. Alligood MR. The structure of specialized nursing knowledge. In: Alligood MR, editor. Nursing Theorists and Their Work. 8th ed. St. Louis, MO: Mosby; 2013. p. 38-41.
• 43. Hardin SR. Theory development process. In: Alligood MR, editor. Nursing Theorists and Their Work. 8th ed. St. Louis, MO: Mosby; 2013. p. 23-37.
• 44. Williams SN. ‘Plausible uncertainty’: The negotiated indeterminacy of pandemic influenza in the UK. Critical Public Health. 2008;18(1):77–85. https://doi.org/10.1080/09581590701877241Article
• 45. Lipsitch M, Riley S, Cauchemez S, Ghani AC, Ferguson NM. Managing and reducing uncertainty in an emerging influenza pandemic. The New England Journal of Medicine. 2009;361(2):112–115. https://doi.org/10.1056/NEJMp0904380ArticlePubMedPMC

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