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Original Article

Factors Associated with Nursing Intention among Korean Clinical Nurses for COVID-19 Patient Care: a Cross-Sectional Study

Ji Hyun Kim1orcid, Sung Hee Shin2orcid, Soojung Jo3orcid, Vicki Simpson4orcid
Journal of Korean Academy of Nursing Administration 2026;32(1):39-48.
Published online: January 30, 2026

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Correspondence to: Sung Hee Shin College of Nursing Science, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Korea Tel: +82-2-961-0917, E-mail: sunghshin@khu.ac.kr
-This article is a condensed form of the first author's master's thesis from Kyung Hee University.
• Received: July 8, 2025   • Revised: December 17, 2025   • Accepted: December 18, 2025

© 2026 Korean Academy of Nursing Administration

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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  • Purpose
    The coronavirus disease 2019 (COVID-19) pandemic has substantially influenced nursing environments and has underscored the importance of active patient care. Nursing intention plays a critical role in the provision of care for patients with COVID-19; however, limited evidence exists regarding the factors that influence nurses’ intention to provide patient care specific to COVID-19. This study aimed to examine factors associated with nursing intention for COVID-19 patient care, guided by the Theory of Planned Behavior.
  • Methods
    This study employed a cross-sectional descriptive design. Data were collected from August 30 to October 1, 2020, using structured questionnaires completed by 169 clinical nurses working in hospitals with more than 600 beds in Seoul, Korea. The collected data were analyzed using multiple regression analysis.
  • Results
    Behavioral beliefs (β=.34, p<.001) and perceived behavioral control (β=.24, p<.001) were significantly associated with nursing intention for COVID-19 patient care.
  • Conclusion
    There is a need to develop specific strategies and educational programs to enhance nursing intention for COVID-19 patient care in the context of emerging infectious diseases by strengthening behavioral beliefs and perceived behavioral control. Providing up-to-date care protocols or simulation-based education may help increase nurses’ behavioral beliefs and perceived behavioral control.
  • Key Words: Nurse; Intention; COVID-19; Belief; Patients
Coronavirus disease 2019 (COVID-19) is an emerging infectious disease that spread globally. World Health Organization declared a pandemic on March 11, 2020 [1]. Korea is one of the countries that experienced significant transmission. Due to their prior experience with the Middle East Respiratory Syndrome (MERS) outbreak, Korean nurses faced heightened challenges during the pandemic, especially under strict government policies and extensive contact-tracing efforts. In the previous MERS outbreak in Korea, nurses experienced fear of infection, stress, and exhaustion [2]. Post-traumatic stress symptoms were also reported by nurses after contact with MERS patients [3]. Moreover, 36% of all confirmed cases of MERS were healthcare workers in Korea [4]. During the COVID-19 pandemic, research from Iran showed nurses were anxious about themselves or their families becoming infected [5]. The anxiety and high incidence of COVID-19 could influence nurses’ intention for COVID-19 patient care, ultimately impacting quality of care. Nurses cannot refuse to care for patients no matter what their nursing intention levels are. As the COVID-19 pandemic lasts longer than expected, countries and hospitals are struggling to meet the rising demand for hiring and retaining nurses. Therefore, this article aims to examine the factors associated with nursing intention using the Theory of Planned Behavior (TPB).
The TPB is a widely used framework for explaining human behavior [6]. Based on the TPB, human behavior is defined by the intention to perform the behavior. The behavior and the intention depend on attitudes toward the behavior, subjective norms, and perceived behavioral control [6]. A precursor to the TPB was the Theory of Reasoned Action (TRA) [7]. The TRA explains that human behavior is predicted by beliefs, attitudes, and intentions. It explains that behavior is determined by behavioral intention, and behavioral intention is determined by attitudes and subjective norms. The TRA assumes that individuals can control their behavior, limiting the utility of the theory when there are factors that individuals cannot control. To overcome this limitation, Ajzen developed the TPB by adding the concept of perceived behavioral control to the TRA [6].
The TPB consists of three major concepts: attitude towards the behavior, subjective norm, and perceived behavioral control, and these three concepts are affected by the individuals’ factors such as demographic characteristics [8]. According to a meta-analysis of the TPB, TPB constructs can explain 31.5% of the variance in behavioral intention [9]. In terms of the constructs related to the TPB, the literature reported that attitudes toward the behavior are affected by behavioral beliefs. Subjective norms are by normative beliefs. Perceived behavioral control is influenced by control beliefs. These beliefs in turn are affected by other circumstances such as individual or sociological characteristics [8]. Ajzen explains the three beliefs are strongly related to behavioral intention, and sometimes predict behavioral intention [8].
In a previous study in Korea about nursing intention utilizing the TPB during the Severe Acute Respiratory Syndrome (SARS) pandemic, Kim et al. [10] verified that these three beliefs were all significantly associated with nursing intention for SARS patient care. Therefore, behavioral, normative, and control beliefs are necessary components to predict behavioral intention. In another study conducted in Taiwan, self-efficacy and attitude toward behavior were significantly associated with nursing intention during the SARS pandemic [11]. In a study conducted during the H1N1 pandemic, subjective norms and perceived behavioral control were both associated with nursing intention [12]. Studies during the MERS epidemic in Korea reported that perceived behavioral control, attitude toward the behavior, subjective norms, normative beliefs, control beliefs, and behavioral beliefs were associated with nursing intention [13,14]. Therefore, this study includes behavioral, normative, and control beliefs as well as the three major concepts of the TPB in examining nursing intention during the COVID-19 pandemic.
Specific research questions of this study are as follows: RQ1. Are belief factors such as behavioral beliefs, normative beliefs, or control beliefs associated with nursing intention for COVID-19 patient care? RQ2. Are TPB factors such as attitudes to the behavior, subjective norms, or perceived behavioral control associated with nursing intention for COVID-19 patient care?
Study Design
This is a cross-sectional study which used a paper-based survey to collect data regarding the intention to care for COVID-19 patients.
Participants
The target population consisted of nurses working in four tertiary medical centers in Seoul, Korea. The inclusion criteria for these hospitals were: (1) having more than 600 beds, (2) being designated COVID-19 treatment facilities by the Korean government, and (3) having established isolation units for infectious disease patient care. All four hospitals shared similar characteristics including academic affiliation with medical schools, availability of negative pressure isolation rooms, standardized personal protective equipment (PPE) supply systems, and institutional protocols for emerging infectious disease management. The hospitals had comparable staffing ratios and provided similar in-service training programs for COVID-19 care. During the data collection period (August–October 2020), all facilities were actively treating COVID-19 patients, although the exact patient volumes varied with community transmission rates. Nurses who have more than one-year clinical experience were included in the study. Nurses who have less than one year experience were excluded since previous research concluded nurses who are 10 months post-graduation had attained clinical competences [15].
Power analysis was conducted by using G*Power version 3.1 program (Heinrich-Heine-Universität Düsseldorf) [16] for multiple regression using medium size effect (.15), α=.05, 1-β=.9 with 8 factors. The desired sample size was 136 and we recruited 170 by considering the attrition of 25%.
Measurements
This survey collected demographic characteristics, nursing intention for COVID-19 patient care, belief factors, and TPB constructs. Demographic characteristics include years in practice, position, educational level, working department, or COVID-19 patient care experience. The questionnaires on nursing intention for COVID-19 patient care was adapted from the edited version [17] of a survey originally developed to measure SARS patient care intention [18]. It is measured by three items and using a 7-point Likert scale (-3: not at all, 3: very much). A mean score is calculated, with a higher score indicating higher intention for COVID-19 patient care. Cronbach’s alpha was .92 in this study.
In terms of belief factors, normative beliefs, behavioral beliefs, and control beliefs were measured. Survey items measuring behavioral belief included 10 items focused on positive behavioral beliefs and 8 items focused on negative behavioral beliefs. The negative items (item 11–18) were reverse coded for analysis. A mean score is calculated using item responses; a higher mean score reflects a positive behavioral belief. Cronbach’s alpha for these 18 items was .84 in this study. Normative belief was measured by four items focused on positive normative beliefs, and four items focused on negative normative beliefs. A higher mean score indicates that nurses believe people around them agree with COVID-19 patient care. Cronbach’s alpha for these survey items was .85 in this study. Survey items measuring control beliefs included two items focused on positive control beliefs and eight items focused on negative control beliefs. The negative items (Items 1, 3, and 5–10) were reverse coded for analysis. A higher mean score reflects the belief that patient care can be easily provided. Cronbach’s alpha for these items was .81 in this study.
In the TPB, subjective norms, attitudes toward the behavior, and perceived behavioral control were measured. Three variables are from the edited version [17] of intention for SARS patient care [18]. It used a 7-point Likert scale (-3: not at all, 3: very much). Attitudes toward the behavior consisted of three survey items. Subjective norm consisted of two items. Perceived behavioral control consisted of two items. Mean scores are calculated for each variable. A higher mean score reflects having a positive attitude on COVID-19 patient care, a higher belief that peers approve of and support their intention for COVID-19 patient care, and a higher level of confidence with COVID-19 patient care respectively. The Cronbach’s alpha for these items was .70.
Data Collection
Data collection was from August 30, 2020, to October 1, 2020. The researchers sent survey information and a paper-based survey to the participants. Participants returned the survey to the researchers after its completion.
Data Analysis
Group differences were analyzed using t-tests and Analysis of Variance. Multiple regression was utilized to investigate the factors associated with nursing intention for COVID-19 patient care. Significant demographic variables were added in the multiple regression as independent variables. All analysis was conducted using IBM SPSS version 22.0 (IBM Corp.).
Ethical Consideration
This study was conducted after the Institutional Review Board approval of Asan Medical Center (No. S2020-1808-0001). The participants conducted the survey after they consented.
Demographic Characteristics
Among 170 potential participants, a total of 169 surveys were returned. Five records had missing data and were removed from analysis. Therefore, 164 responses were used in the analysis. The demographic characteristics are shown in Table 1. The mean age was 30.26 years (standard deviation [SD], 6.53). Participants aged less than 25 years were 19 (11.6%), aged between 25 and 29 were 78 (47.6%), aged between 30 and 34 were 34 (20.7%), and aged over 34 were 34 (20.7%). Most participants were female (n=149, 90.9%) and single (n=121, 73.8%). Mean years in practice was 7.12 (SD, 6.55). The number of nurses who have less than 5 years clinical experience was 89 (54.3%), from 5 to 9 was 31 (18.9%), and over 9 years was 44 (26.8%). Most of the respondents were staff nurses (n=155, 94.5%). The majority (n=123, 75.0%) had a bachelor’s degree. Seventy-seven participants were working in the internal medicine unit (46.9%), fifty-one were working in the surgical unit (31.1%), and nineteen were working in specialty units (11.6%). Most nurses did not have previous experience caring for emerging infectious disease patients (n=134, 81.7%) nor COVID-19 patients (n=147, 89.6%).
The mean score of COVID-19 patient care nursing intention was 0.38±1.32. In terms of belief factors, the behavioral belief mean score was 0.18±0.70, normative belief was -0.15±0.90, and control belief was - 0.98±0.75. Attitude toward the behavior was 0.96±1.15, the subjective norm was 0.64±0.88, and perceived behavioral control was 0.28±1.20.
Group Differences on COVID-19 Patient Care Nursing Intention by Demographic Characteristics
Group differences by demographic characteristics are described in Table 2. Nurses’ intention to care was significantly different by whether they had previously cared for COVID-19 patients (1.27 vs. 0.28, p=.003), but was not significant if they had cared for previous emerging infectious diseases patients (p=.27). No significant differences were found using the remaining demographic. Therefore, the variable reflecting COVID-19 patient care experience was added in the regression model.
Factors Associated with COVID-19 Patient Care Nursing Intention
Table 3 shows the results of the multiple regression. Assumptions for the regression analysis were examined, and all criteria were met in terms of independence of errors, homoscedasticity, linearity, and normality of residuals [19]. The Durbin–Watson statistic was 2.16, indicating no autocorrelation. Tolerance values were greater than 0.1, and all variance inflation factors values were below 10, demonstrating the absence of multicollinearity among the independent variables. A significant regression equation was found (F=23.48, p<.001) with an R2 of .51. Behavioral belief (β=.34, p<.001) and perceived behavioral control (β=.24, p<.001) were significantly associated with COVID-19 patient care nursing intention. Unlike the group differences represented in Table 2, previous experience for COVID-19 patient care was not found to be significantly associated with nursing intention. This indicates that the effect of previous COVID-19 patient care experience may be attenuated after adjusting for other TPB-related factors in the multivariable analysis, suggesting that these psychological constructs may account for the association observed in the univariate comparison.
This study provides the levels of the COVID-19 patient care nursing intention, and the associated factors with the nursing intention. The mean score of nursing intention was 0.38 (from -3 to 3). This result is in agreement with the findings from Moon and Park which showed nursing intention for emerging infectious disease patient care was 0.17 (from -3 to 3) among national and public hospital nurses [14]. In addition, another study found nursing intention for SARS patient care was 0.56±1.18 (from -3 to +3), which also supports our result [10]. However, a study about influenza A patient care reported higher nursing intention to care (5.14; range, 1.00–7.00) [12], while another study about Ebola patient care reported somewhat lower nursing intention: only 26.8% of nurses stated willingness to care for Ebola patients [20]. These differences may be explained by the availability of effective treatments for influenza A during the pandemic, whereas no such treatment was available for Ebola. These findings suggest that nursing intention to care may be influenced by factors such as uncertainty and the perceived severity or mortality of the emerging disease, rather than demonstrating a direct causal effect. As there was no available vaccine at the survey period, COVID-19 may have posed additional uncertainty for nurses. Furthermore, factors such as organizational preparedness and infection-control policies during the outbreak may have contributed to nurses’ burnout [21] and subsequently influenced their intention to provide care. In addition, during the COVID-19 pandemic, infection control operated under a centralized infectious disease control structure [22], and Korea had prior experience managing emerging infectious diseases such as MERS. As a result, the country had relatively well-established preparedness systems and more recent training compared with many other countries. The findings of this study should be interpreted in light of these contextual factors.
The findings contribute to understanding the psychological factors influencing nurses' intention for patient care during an ongoing pandemic. Notably, behavioral beliefs emerged as a significant factor during the active pandemic phase, which differs from some post-outbreak studies where this factor was not significant [14]. This discrepancy may be explained by the temporal context of data collection period. This study occurred in the middle of the COVID-19 pandemic, possibly contributing to this finding. Information on COVID-19 patient outcomes in the middle of the pandemic was limited, and patient outcomes were unpredictable compared to post-pandemic outcomes. Thus, nurses who have a positive belief that COVID-19 patients would recover may have a higher nursing intention. This result may suggest the need for comprehensive strategies to enhance nurses' behavioral beliefs. Healthcare organizations could consider implementing evidence-based educational programs that emphasize positive patient outcomes and recovery cases from COVID-19 care [23]. Possible examples for the strategies could include: (1) regular case conferences highlighting successful patient recoveries to reinforce positive beliefs, (2) mentoring programs pairing experienced nurses with those new to infectious disease care, (3) establishing psychological support systems including debriefing sessions after challenging cases, and (4) creating peer support networks where nurses can share positive care experiences. Additionally, hospital administrators may develop recognition programs that acknowledge nurses' contributions to COVID-19 patient care, which may help strengthen positive behavioral beliefs while reducing negative perceptions. These organizational interventions, combined with continuous education on emerging evidence regarding COVID-19 treatment outcomes, can systematically enhance nurses' behavioral beliefs and their intention for emerging infectious diseases patient care.
The significant association between perceived behavioral control and nurses’ intention to care aligned with previous research. Literature has shown that perceived behavioral control has a significant association with a nurses’ emerging infectious disease patient and influenza A patient care [12,13]. Interestingly, actual COVID-19 patient care was not significantly associated with nurses’ intention in the multivariate analysis, despite showing significant differences in univariate comparisons. This finding is consistent with previous research that direct care experience with emerging infectious diseases was not significantly related to subsequent nursing intention or psychological resilience [13,21]. Several theoretical and practical explanations may account for this finding. First, from the perspective of the TPB, intention is primarily shaped by cognitive evaluations (attitudes, beliefs, and perceived behavioral control) rather than past behavior alone. While experience may inform these cognitive evaluations, it does not directly translate into intention if the experience reinforces negative beliefs or reduces perceived behavioral control. For instance, nurses caring for COVID-19 patients may have confronted challenging situations, witnessed patient deterioration, or experienced inadequate resources, potentially diminishing their behavioral beliefs and perceived behavioral control despite gaining experience. Second, the quality and nature of care experience may matter more than the mere presence of experience. A single negative experience with inadequate preparation or support could decrease intention, while well-supported experiences with positive outcomes could enhance intention. Our study did not differentiate between these different types of experiences, which may explain why experience per se was not significant when controlling for beliefs and perceived behavioral control. Third, during the pandemic's early phase when data was collected, the small number of nurses with COVID-19 care experience (10.4%) and the relatively limited duration of such experiences may have insufficient to meaningfully influence intention compared to more established cognitive factors. Additionally, the unpredictable nature of COVID-19 patient outcomes during this period may have created mixed experiences that did not consistently influence intention in either direction. These findings imply that simply exposing nurses to infectious disease patient care without adequate preparation, support, and debriefing may be insufficient to explain intention to provide such care. Rather, healthcare organizations could focus on enhancing cognitive factors—particularly behavioral beliefs and perceived behavioral control—through structured educational programs, simulations, and organizational support, which our results indicate have stronger associations with nursing intention than experience alone.
Rather, involvement in development of COVID-19 preparedness policies or procedures appeared to be more impactful for resilience [24]. This suggests that, in highly uncertain environments, nurses place greater value on having autonomy and a sense of influence over their work processes than on direct care experience alone. Uncertainty about nursing care, compounded by inefficient working environments that were common during the pandemic, also affect nurses’ behavioral control and influence their care intention for COVID-19 patients. Given that the working environment has a substantial impact on nurses’ psychological well-being [25], organizational factors may play a more critical role than clinical experience in shaping their care intention.
In Korea, the COVID-19 response was centrally controlled by the government [22], and all confirmed patients were hospitalized [26], which substantially increased nurses’ workloads compared with usual conditions. This unprecedented situation may have further heightened the importance of nurses’ autonomy and perceived behavioral control in their clinical decision-making. Additionally, a previous study has reported that nurses often expressed complaints when clinical protocols were not updated in real time, which may contribute to feelings of uncertainty or anxiety during the COVID-19 pandemic [27]. Therefore, organizational supports such as providing real-time updates on clinical protocols, along with structured debriefing sessions or peer- and mentor-support programs where nurses can openly share concerns [28], may help reduce these uncertainties and ultimately increase nurses’ behavioral control, thereby increasing their confidence in patient care.
Moreover, providing needed supplies such as PPE helps increase nurses’ perception of behavioral control. As COVID-19 becomes more endemic, it underscores the need for the healthcare sector to be well-prepared for potential future pandemics or epidemics. Nurses continue to shoulder heavier workloads, and there remains a persistent nursing shortage. Simulation education based on the virtual environment may help nurses learn how to manage the care of patients with COVID-19 by increasing infection control knowledge and proper use of PPE.
A study from Qatar reported that simulation-based education was provided to non-critical care nurses to enhance their competencies in caring for patients with various clinical conditions, including respiratory, cardiovascular, genitourinary, gastrointestinal, and neurological issues [29]. In addition, a hospital in the New York City, the United States implemented comprehensive simulation programs that covered PPE training, intubation and airway management, emergency code response, ventilator management, and proning procedures [30]. These examples illustrate the range of simulation strategies that can be used to prepare nurses for emerging infectious diseases and may be associated with higher perceived behavioral control by increasing familiarity and confidence with essential clinical skills.
The findings of this study must be interpreted within the broader social and healthcare context in Korea. Unlike previous infectious disease outbreaks, COVID-19 presented unprecedented challenges due to its global scale, prolonged duration, and the resulting healthcare system strain. During the study period (August–October 2020), Korea was experiencing its second wave of COVID-19, characterized by rising community transmission and increasing demands on healthcare resources. The Korean government implemented aggressive containment strategies including extensive contact tracing, mandatory isolation, and strict infection control policies in healthcare facilities, which significantly impacted nursing work environments.
Several contextual factors specific to this pandemic period warrant consideration. First, the healthcare system faced extraordinary pressures including bed shortages, increased workload, and reallocation of nursing staff to COVID-19 units, creating additional stress beyond infection concerns. Second, social stigma associated with COVID-19 affected not only patients but also healthcare workers, with some nurses reporting discrimination or social isolation due to their occupational exposure risk. Third, the pandemic's prolonged nature led to cumulative physical and emotional exhaustion among nurses, different from the acute crisis nature of previous outbreaks like SARS or MERS.
Furthermore, policy responses in Korea emphasized protecting healthcare workers through prioritized PPE distribution and establishing designated COVID-19 treatment facilities, which may have influenced nurses' perceived behavioral control. However, rapid policy changes and evolving clinical guidelines during the pandemic's early phase created uncertainty that could have affected behavioral beliefs. The government's decision to mandate universal healthcare worker testing and implement strict quarantine protocols for exposed workers also had practical implications for nursing staffing and workload distribution.
The broader social context included public recognition of healthcare workers' contributions alongside intense public scrutiny of healthcare-associated transmission events, creating a complex environment of appreciation and pressure. These unique pandemic-related social and policy factors likely influenced the psychological constructs measured in this study and should inform the interpretation of our findings and the development of support strategies for nurses during prolonged public health crises.
Several limitations have remained and should be cautious when interpreting the findings. First, since a cross-sectional design, the results of this study cannot make a causal inference, and the directionality of the relationships among behavioral beliefs, perceived behavioral control, and intention cannot be established. Because data were collected at a single time point during the pandemic, temporal changes in nurses’ beliefs and intentions as the pandemic situation and related information evolved could not be examined. Second, the sample was drawn from four large tertiary hospitals in Seoul, all of which were government-designated COVID-19 treatment centers with relatively similar facilities, staffing, and care systems. These institutional similarities, as well as the focus on metropolitan tertiary centers, may limit this study’s generalizability to other settings such as smaller hospitals, community facilities, or rural institutions with different resource and organizational environments. Furthermore, the use of self-reported measures may have introduced response bias and potential common method bias, which should be considered when interpreting the findings.
This study examined associated factors on nursing intention for COVID-19 patient care. Behavioral beliefs and perceived behavioral control were both positively associated with nursing intention, but previous experience with COVID-19 patient care was not a significant factor. The results of this study suggest hospitals enhance working environments for infectious disease patient care and provide up-to-date protocols for nurses. Simulation education could be a useful strategy to support nurses’ beliefs and perceived behavioral control for infectious disease patient care. Increasing confidence in emerging infectious disease patient care may be associated with higher nursing intention and potentially better quality of care, although causal relationships cannot be inferred from this cross-sectional study.

Author contributions

Conceptualization: JHK, SSH. Methodology: JHK, SSH. Formal analysis: JHK, SSH. Data curation: JHK, SSH. Visualization: SJ, VS. Project administration: JHK, SSH. Funding acquisition: JHK. Writing - original draft: JHK, SSH **. Writing - review & editing: SSH, SJ, VS **. All authors read and agreed to the published version of the manuscript.

Conflict of interest

None.

Funding

This study was supported by Hanmaum scholarship of Seoul Nurses Association in 2020 (No. 542).

Data availability

Please contact the corresponding author for data availability.

Acknowledgments

None.

Table 1.
Demographic Characteristics of the Sample (N=164)
Characteristics Category n (%) or M±SD
Age (yr) <25 19 (11.6)
25~29 78 (47.6)
30~34 34 (20.7)
≥35 33 (20.1)
Gender Man 15 (9.1)
Woman 149 (90.9)
Marital status Single 121 (73.8)
Married 43 (26.2)
Years in practice <5 89 (54.3)
5~9 31 (18.9)
≥10 44 (26.8)
Position Staff nurse 155 (94.5)
Charge nurse 9 (5.5)
Educational level Associate degree 2 (1.2)
Bachelor’s degree 123 (75.0)
Master’s student 24 (14.6)
≥Master 15 (9.1)
Working department Internal medicine 77 (46.9)
Surgery 51 (31.1)
Special 19 (11.6)
Other 17 (10.4)
EID patient care No 134 (81.7)
Yes 30 (18.3)
COVID-19 patient care No 147 (89.6)
Yes 17 (10.4)
Nursing intention for COVID-19 patient care 0.38±1.32
Behavioral belief 0.18±0.70
Normative belief -0.15±0.90
Control belief -0.98ଐ.75
Attitude toward the behavior 0.96±1.15
Subjective norm 0.64±0.88
Perceived behavioral control 0.28±1.20

M=mean; SD=standard deviation; EID=emerging infectious disease; COVID-19=coronavirus disease 2019.

Table 2.
Group Differences in Nursing Intention for COVID-19 Patient Care (N=164)
Characteristics Category n M±SD t or F p
Age (yr) <25 19 0.07±1.16 0.50 .68
25~29 78 0.40±1.36
30~34 34 0.35±1.26
≥35 33 0.54±1.42
Gender Man 15 0.67±1.46 0.88 .38
Woman 149 0.35±1.31
Marital status Unmarried 121 0.35±1.31 -0.49 .63
Married 43 0.47±1.38
Years in practice <5 89 0.31±1.30 0.57 .57
5~9 31 0.60±1.22
≥10 44 0.37±1.44
Position Staff nurse 155 0.35±1.34 -1.10 .27
Charge nurse 9 0.85±0.88
Educational level Associate degree 2 0.83±1.18 1.47 .23
Bachelor’s degree 123 0.27±1.33
Master’s student 24 0.56±1.36
≥Master 15 0.98±1.18
Working department Internal medicine 77 0.25±1.36 1.81 .15
Surgery 51 0.28±1.32
Special 19 0.65±1.34
Other 17 0.98±1.04
EID patient care No 134 0.33±1.33 -1.10 .27
Yes 30 0.62±1.29
COVID-19 patient care No 147 0.28±1.29 -3.01 < .01
Yes 17 1.27±1.31

COVID-19=coronavirus disease 2019; M=mean; SD=standard deviation; EID=emerging infectious disease.

Table 3.
Factors Associated with Nursing Intention for COVID-19 Patient Care (N=164)
Variable B SE β t p
Behavioral belief 0.65 0.14 .34 4.62 <.001
Normative belief 0.10 0.10 .07 1.04 .300
Control belief 0.17 0.13 .10 1.29 .200
Attitude toward the behavior 0.14 0.08 .12 1.78 .077
Subjective norm 0.07 0.09 .05 0.78 .439
Perceived behavioral control 0.27 0.08 .24 3.26 .001
COVID-19 patient care 0.47 0.26 .11 1.84 .068
Durbin-Watson=2.16, R2=.51, Adj R2=.49, F=23.48, p<.001

COVID-19=coronavirus disease 2019; SE=standard error; Adj=adjusted.

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      Factors Associated with Nursing Intention among Korean Clinical Nurses for COVID-19 Patient Care: a Cross-Sectional Study
      J Korean Acad Nurs Adm. 2026;32(1):39-48.   Published online January 30, 2026
      DOI: https://doi.org/10.11111/jkana.2025.0043
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      Factors Associated with Nursing Intention among Korean Clinical Nurses for COVID-19 Patient Care: a Cross-Sectional Study
      J Korean Acad Nurs Adm. 2026;32(1):39-48.   Published online January 30, 2026
      DOI: https://doi.org/10.11111/jkana.2025.0043
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      Factors Associated with Nursing Intention among Korean Clinical Nurses for COVID-19 Patient Care: a Cross-Sectional Study
      Factors Associated with Nursing Intention among Korean Clinical Nurses for COVID-19 Patient Care: a Cross-Sectional Study
      Characteristics Category n (%) or M±SD
      Age (yr) <25 19 (11.6)
      25~29 78 (47.6)
      30~34 34 (20.7)
      ≥35 33 (20.1)
      Gender Man 15 (9.1)
      Woman 149 (90.9)
      Marital status Single 121 (73.8)
      Married 43 (26.2)
      Years in practice <5 89 (54.3)
      5~9 31 (18.9)
      ≥10 44 (26.8)
      Position Staff nurse 155 (94.5)
      Charge nurse 9 (5.5)
      Educational level Associate degree 2 (1.2)
      Bachelor’s degree 123 (75.0)
      Master’s student 24 (14.6)
      ≥Master 15 (9.1)
      Working department Internal medicine 77 (46.9)
      Surgery 51 (31.1)
      Special 19 (11.6)
      Other 17 (10.4)
      EID patient care No 134 (81.7)
      Yes 30 (18.3)
      COVID-19 patient care No 147 (89.6)
      Yes 17 (10.4)
      Nursing intention for COVID-19 patient care 0.38±1.32
      Behavioral belief 0.18±0.70
      Normative belief -0.15±0.90
      Control belief -0.98ଐ.75
      Attitude toward the behavior 0.96±1.15
      Subjective norm 0.64±0.88
      Perceived behavioral control 0.28±1.20
      Characteristics Category n M±SD t or F p
      Age (yr) <25 19 0.07±1.16 0.50 .68
      25~29 78 0.40±1.36
      30~34 34 0.35±1.26
      ≥35 33 0.54±1.42
      Gender Man 15 0.67±1.46 0.88 .38
      Woman 149 0.35±1.31
      Marital status Unmarried 121 0.35±1.31 -0.49 .63
      Married 43 0.47±1.38
      Years in practice <5 89 0.31±1.30 0.57 .57
      5~9 31 0.60±1.22
      ≥10 44 0.37±1.44
      Position Staff nurse 155 0.35±1.34 -1.10 .27
      Charge nurse 9 0.85±0.88
      Educational level Associate degree 2 0.83±1.18 1.47 .23
      Bachelor’s degree 123 0.27±1.33
      Master’s student 24 0.56±1.36
      ≥Master 15 0.98±1.18
      Working department Internal medicine 77 0.25±1.36 1.81 .15
      Surgery 51 0.28±1.32
      Special 19 0.65±1.34
      Other 17 0.98±1.04
      EID patient care No 134 0.33±1.33 -1.10 .27
      Yes 30 0.62±1.29
      COVID-19 patient care No 147 0.28±1.29 -3.01 < .01
      Yes 17 1.27±1.31
      Variable B SE β t p
      Behavioral belief 0.65 0.14 .34 4.62 <.001
      Normative belief 0.10 0.10 .07 1.04 .300
      Control belief 0.17 0.13 .10 1.29 .200
      Attitude toward the behavior 0.14 0.08 .12 1.78 .077
      Subjective norm 0.07 0.09 .05 0.78 .439
      Perceived behavioral control 0.27 0.08 .24 3.26 .001
      COVID-19 patient care 0.47 0.26 .11 1.84 .068
      Durbin-Watson=2.16, R2=.51, Adj R2=.49, F=23.48, p<.001
      Table 1. Demographic Characteristics of the Sample (N=164)

      M=mean; SD=standard deviation; EID=emerging infectious disease; COVID-19=coronavirus disease 2019.

      Table 2. Group Differences in Nursing Intention for COVID-19 Patient Care (N=164)

      COVID-19=coronavirus disease 2019; M=mean; SD=standard deviation; EID=emerging infectious disease.

      Table 3. Factors Associated with Nursing Intention for COVID-19 Patient Care (N=164)

      COVID-19=coronavirus disease 2019; SE=standard error; Adj=adjusted.

      Table 1.

      Table 2.

      Table 3.

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