INTRODUCTION
Coronavirus disease 2019 (COVID-19), a respiratory infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), first emerged in Wuhan, China, and has since spread across China and worldwide [1]. As of February 2024, approximately 774 million people worldwide have been infected with COVID-19, with approximately seven million deaths [2]. Two years after the World Health Organization (WHO) officially declared COVID-19 a pandemic in 2020, considerations for ending the pandemic began. Concurrently, in April 2022, South Korea downgraded COVID-19 to a Class 2 infectious disease. Furthermore, a disease control system was implemented that lifted the mandatory wearing of mask [3]. However, the number of people infected with and dying from COVID-19 continues to rise, and those infected complain of various health problems. Recent studies indicate that COVID-19 affects systemic functions other than the respiratory system and that health problems are pro-longed; therefore, people's interest in the importance of identifying symptoms that persist after infection is increasing [4].
Various terms have emerged to describe the state of long-term symptom experienced after COVID-19 infection. The term “ long COVID” first appeared on personal social media [5]. Thereafter, the Centers for Disease Control and Prevention (CDC) and the National Institutes of Health (NIH) described long COVID or post-acute sequelae of SARS-CoV-2 infection as a set of symptoms that people experience continuously for at least four weeks after infection with COVID-19[6,7]. Approximately 40% of infected people experience damage to several body systems after four weeks (the acute phase of infection) [8]. COVID-related symptoms range from mild to moderate fatigue, cough, shortness of breath, difficulty concentrating, headache, muscle pain, reduced appetite, depression, and hair loss, with several symptoms appearing simultaneously rather than singly. Additionally, 32.0% of those infected with COVID-19 experienced one or two or more symptoms, and 55.0% experienced three or more symptoms [9].
The simultaneous occurrence of two or more symptoms related to each other in a patient experiencing multiple symptoms is called a symptom cluster, a concept that has been studied in patients with various chronic diseases [10]. However, studies on the symptom cluster of people with long COVID have focused on early symptoms or inpatients experiencing severe health problems [11,12]. Symptom clusters provide a basis for identifying and diagnosing diseases, and the complex relationship between symptoms within a cluster is a target for new nursing interventions [10]. Therefore, identifying the symptom cluster is helpful in determining the direction of nursing interventions for people with Long COVID.
Quality of Life (QoL) is an important variable to understand in patients experiencing long COVID. People with long COVID exhibit a lower overall QoL than individuals without persistent long COVID-19 symptoms (<28 days) [13]. However, although QoL is a widely used health outcome in clinical studies, most of the studies investigating the QoL of people with long COVID have been conducted on those who complained of severe infection and received hospital treatment [14,15]. Understanding QoL and identifying the symptom cluster of long COVID that affects it is important to effectively deal with long COVID because it promotes people's rehabilitation. Therefore, to improve the QoL of people with long COVID, clinical symptoms should be clearly identified, and the relationship between symptoms and their persistence should be considered.
Approximately 65 million people worldwide experience long COVID; this number is expected to increase over time as the virus spreads [16]. Therefore, this study aims to elucidate symptom clusters among people with long COVID at a time when preventive measures for future infectious diseases are emphasized in the aftermath of the COVID-19 pandemic. Furthermore, it seeks to analyze the relationship between these symptom clusters and QoL. The results of this study are expected to be utilized for the long-term management and education of infectious disease patients.
METHODS
1. Study Design and Participants
This cross-sectional descriptive research was conducted. Individuals who complained of one or more symptoms for at least 4 weeks after confirming COVID-19 infection were recruited as participants. The inclusion criteria included those who were 19 years of age or older, had no underlying disease, had a clear level of consciousness, could fill out a questionnaire, agreed to participate in the study, and complained of one or more of the following symptoms for more than four weeks after being diagnosed with COVID-19: fatigue, post-exertional malaise, fever, breathlessness, cough, sore throat, chest pain, palpitation, cognitive impairment and loss of concentration, headache, sleep disturbance, dizziness, pins-and-needles feelings, depression, anxiety, loss of smell, loss of taste, nausea and vomiting, reduced appetite, diarrhea, abdominal pain, skin rash, hair loss, joint pain, muscle pain, and changes in menstrual cycle. The exclusion criteria were a diagnosis of alcoholism or mental illness by a doctor. Furthermore, as comorbidities affect the QoL of people with long COVID [15], those with comorbidities and long COVID complications (such as thrombotic thrombocytopenic purpura, pericarditis, encephalitis, etc.) were excluded from this study to identify the independent symptom cluster of long COVID.
For factor analysis, a sample size of about 200 is recommended when the number of measurement items is 40 or fewer [17]. In this study, the number of long COVID symptom items for factor analysis was 26; thus, the study targeted 220 individuals, and the sample size requirement was met.
2. Data Collection
Data were collected through an online survey from August 18 to September 5, 2022. After obtaining permission from the representatives of the four COVID-19 confirmed communities, the guidelines for recruiting participants were posted in these communities, including two Kakao Open Messengers and two long COVID Naver Cafes. In the online survey, recruitment notices for participation were promoted through QR codes and online survey links. Furthermore, a web survey was conducted after obtaining fully automatic consent, and if consent was not obtained, the survey was terminated on the relevant screen. Consent to participate in the study was determined by responding to the item, “ Do you voluntarily agree to participate in this study?” The online questionnaire took approximately 10∼15 minutes to complete. A small gift was provided to those who participated in the survey. None of the participants withdrew their participation; thus, 220 responses were collected.
3. Measures
1) Symptoms of long COVID
This study developed a symptom inventory tool by reviewing guidelines from the National Institute for Health and Care Excellence (NICE), CDC, and previous studies to measure long COVID symptoms. The long COVID symptoms presented in “ COVID-19 rapid guideline: managing the long-term effects of COVID-19,”[18] published by NICE in January 2022, are divided into nine areas: systemic symptoms, respiratory system, circulatory system, nervous system, digestive system, musculoskeletal system, skin system, otitis media, and mental health. The CDC presented 19 symptoms of long COVID in five areas— systemic symptoms, respiratory and circulatory system, nervous system, digestive system, and others [6]. Additionally, referring to three foreign meta-analysis studies [4,19,20], we selected 26 items for long COVID symptoms. To verify the validity, the content validity index (CVI) was calculated by a group of six experts, including one infectious diseases doctor, one infection control specialist nurse and four nursing professors. Each question was evaluated on a four-point scale as not reflected at all, not reflected, reflected, or very well reflected. The scale-level CVI value was 1.0, and the item-level CVI value was 1.0, indicating that all 26 items were valid and, thus, adopted.
A pilot test was conducted on 10 people who satisfied the inclusion criteria, and two items that the participants found difficult were corrected and supplemented (sore throat and nausea). The time taken to complete the questionnaire was approximately five minutes. The final completed long COVID symptom measurement tool comprised 26 items found to have the highest frequency or severity in people with long COVID, each was scored on an 11-point scale ranging from 0 (no symptoms) to 10 (imaginably severe symptoms). The frequency of symptoms among people with long COVID was calculated based on the number of individuals who reported each symptom with a score of 1 or more. The severity of symptoms refers to the average value for each symptom, including scores where respondents answered 0 for each item. Higher scores indicated greater severity of long COVID symptoms.
2) Quality of life
QoL was evaluated using the Korean version of the World Health Organization Quality of Life Instrument-Short Version (WHOQOL-BREF), originally developed by the WHOQOL Group. The Korean version of the WHOQOL-BREF comprises 26 items [21], with one item for general health, one for overall QoL, seven for the physical health dimension, six for the psychological dimension, three for the social relationship dimension, and eight for the environment dimension. The total QoL was calculated on a five-point scale, and the QoL for each subdomain was converted into a 100-point scale. The internal consistency reliability (Cronbach's ⍺) for the entire scale and each domain at the time of the development of the Korean version was .96 and .58∼.73, respectively [21]. In the present study, Cronbach's ⍺ was .92 for the overall QoL and .64∼.83 for each domain.
3) General characteristics
We gathered information on the participants’ sex, age, marital status, education, BMI (underweight (<18.5 kg/m2), normal (18.5∼22.9 kg/m2, overweight (23.0∼24.9 kg/m2) and obese (≥25.0 kg/m2)[22], time after COVID-19 diagnosis, COVID-19 vaccination, place of treatment, and duration of symptoms.
4. Ethical Considerations
This study was approved by the Institutional Review Board for the ethical protection of the participants (IRB No. 2022-06-021-002). Before data collection, all participants completed an online questionnaire with a research guide that provided information regarding the research content and purpose, no disadvantages due to participation in the research, and anonymity and confidentiality. It also stated that the collected data would be used only for research and that participation could be discontinued at any time if one did not wish to participate. If the partic-ipant desired, a copy of the consent form and a screen capture of the research explanation guide were provided. The research data were stored in a secure file and managed by applying a password so that only the researcher could access it.
5. Statistical Analysis
All statistical analyses and data processing in this study were completed using the IBM SPSS Statistics 28.0 (IBM Corp., USA). The demographic and clinical characteristics, symptoms, and QoL of the participants were analyzed using descriptive statistics (frequency, percentage, mean, standard deviation (SD), and range). The frequency of symptoms among people with long COVID was analyzed using multiple response frequency analysis. Exploratory factor analysis (EFA) was conducted along with item analysis. EFA was performed to identify the symptom clusters. Factors were extracted by performing factor analysis using the principal component method, and factor rotation was performed using the varimax rotation method. Kaiser Meyer Olkin (KMO) and Bartlett's tests were performed to confirm the suitability of the data. Ward's method of statified clustering analysis was used to identify the relationship between symptom clusters and QoL, and k-means clustering was used to classify the symptom-higher and symptom-lower groups. Subsequently, the differences in QoL scores according to group were analyzed by performing an independent t-test. K-means clustering was performed to classify subgroups for each symptom cluster, and the Mann-Whitney U test was performed to identify the relationship between each symptom cluster and QoL. The study employed p-values with two significant tails at .05.
RESULTS
1. Participant Characteristics
The participants included 95 men (43.2%) and 125 women (56.8%). The average age was 32.26±6.87 years (range: 19∼69); 100 (45.5%), 90 (40.9%), 26 (11.8%), and 4 (1.8%) participants were in their 30s, 20s, 40s, and over 50s, respectively. Furthermore, 148 (67.3%) participants were un-married, and 178 (80.9%) were the most educated, with a college degree or higher. The BMIs were normal weight, overweight, obese, and underweight for 126 (57.3%), 54(24.5%), 24 (10.9%), and 16 (7.3%) participants, respectively. The average period since COVID-19 infection was 5.27± 3.84 months (range: 1∼19); 160 (72.7%) participants were vaccinated, while 60 (27.3%) were not. Home care was the most common location of treatment (208 patients, 94.5%). The average duration of symptoms with 220 patients was 8.17±7.94 weeks (range: 4∼60), with 182 patients (82.7%) having symptoms lasting over four weeks and less than 12 weeks, and 38 patients (17.3%) having symptoms for over 12 weeks (Table 1).
Table 1.
Participants’ Characteristics (N=220)
2. Symptoms of the Participants with Long COVID
The most frequently experienced symptoms were fatigue (94.5%), sore throat (89.1%), post-exertional malaise (88.2%), cough (88.2%), fever (85.5%), muscle pain (78.2%), cognitive impairment and loss of concentration (76.8%), breathlessness (76.4%), headache (73.6%), and loss of taste (70.9%) (Table 2).
Table 2.
Frequency and Severity of Symptoms in People with Long COVID (N=220)
| Symptoms (ranked by frequency) | Frequency† | Severity‡ | ||||
|---|---|---|---|---|---|---|
| n (%) | M± SD | Min. | Max. | Skewness | Kurtosis | |
| Fatigue§ | 208 (94.5) | 6.21±2.31 | 0 | 10.0 | -1.04 | 1.13 |
| Sore throat§ | 196 (89.1) | 5.78±2.78 | 0 | 10.0 | -0.79 | 0.04 |
| Post-exertional malaise§ | 194 (88.2) | 5.46±2.64 | 0 | 10.0 | -0.54 | -0.76 |
| Cough§ | 194 (88.2) | 5.64±2.84 | 0 | 10.0 | -0.26 | -1.11 |
| ever§ | 188 (85.5) | 5.21±2.90 | 0 | 10.0 | -0.71 | -0.41 |
| Muscle pain§ | 172 (78.2) | 4.48±3.05 | 0 | 10.0 | -0.73 | -0.15 |
| Cognitive impairment and loss of concentration§ | 169 (76.8) | 4.56±3.15 | 0 | 10.0 | 0.04 | -1.30 |
| Breathlessness§ | 168 (76.4) | 4.30±2.91 | 0 | 10.0 | 0.07 | -1.36 |
| Headache§ | 162 (73.6) | 4.36±3.23 | 0 | 10.0 | -0.23 | -1.16 |
| Loss of taste§ | 156 (70.9) | 3.94±3.25 | 0 | 10.0 | -0.09 | -1.25 |
| Chest pain | 155 (70.5) | 3.76±3.05 | 0 | 10.0 | 0.20 | -1.33 |
| Dizziness | 153 (69.5) | 3.83±3.10 | 0 | 10.0 | 0.02 | -1.26 |
| Anxiety | 152 (69.1) | 3.78±3.15 | 0 | 10.0 | 0.59 | -0.96 |
| Palpitation | 150 (68.2) | 3.62±3.07 | 0 | 10.0 | 0.19 | -1.42 |
| Changes in menstrual cycle (n=125) | 84 (67.2) | 1.98±2.95 | 0 | 10.0 | 1.30 | -1.37 |
| Loss of smell | 145 (65.9) | 3.64±3.32 | 0 | 10.0 | 0.67 | -0.80 |
| Reduced appetite | 144 (65.5) | 3.56±3.20 | 0 | 10.0 | 0.91 | -0.41 |
| Depression | 142 (64.5) | 3.50±3.15 | 0 | 10.0 | 0.91 | -0.30 |
| Sleep disturbance | 143 (65.0) | 3.64±3.26 | 0 | 10.0 | 0.24 | -1.27 |
| Joint pain | 130 (59.1) | 2.91±3.00 | 0 | 10.0 | 0.49 | -1.02 |
| Pins-and-needles feelings | 123 (55.9) | 2.84±3.08 | 0 | 10.0 | -0.26 | -1.15 |
| Nausea and vomiting | 117 (53.2) | 2.71±3.04 | 0 | 10.0 | 0.93 | -0.56 |
| Diarrhea | 111 (50.5) | 2.35±2.92 | 0 | 10.0 | 0.72 | 0.51 |
| Skin rashes | 108 (49.1) | 1.99±2.57 | 0 | 8.0 | 0.19 | -1.41 |
| Abdominal pain | 108 (49.1) | 2.18±2.73 | 0 | 10.0 | 0.06 | -1.36 |
| Hair loss | 96 (43.6) | 1.83±2.69 | 0 | 10.0 | 1.21 | 0.14 |
† The frequency of symptoms was calculated based on the number of individuals who reported each symptom with a score of 1 or more. This is the result of multiple responses;
Participants were asked to indicate the symptoms they experienced on a scale of 0 to 10. The symptoms with the highest intensity were fatigue (6.21±2.31 points), sore throat (5.78±2.78 points), cough (5.64±2.84 points), post-exertional malaise (5.46±2.64 points), fever (5.21±2.90 points), cognitive impairment and loss of concentration (4.56±3.15 points), muscle pain (4.48±3.05 points), headache (4.36±3.23 points), breathlessness (4.30±2.91 points), and loss of taste (3.94±3.25 points), each rated on a 10- point scale (Table 2).
3. Symptom Cluster of the Participants with Long COVID
In this study, before conducting EFA, an item analysis was performed on the 26 items. The means, standard deviations, minimum and maximum values, skewness, and kurtosis for each item are presented in Table 2. The inter-item correlation coefficients ranged from .28 to .64, and the corrected item-total correlations were above .40 for all items (Table 3). Before conducting the EFA, the KMO value (.92) and the results of Bartlett's test of sphericity (χ2=3349.58, df=300, p<.001) were confirmed.
Table 3.
Exploratory Factor Analysis of Symptoms (N=220)
A factor analysis was performed on 26 preliminary items. First, as communality shows a high level when the explanatory power of one variable is .60 or higher [23], the menstrual cycle change (.49) item with .50 or less was excluded, along with factors with an eigenvalue of 1.0 or higher. Five factors were derived, which explained 66.3% of the total variance. In this study, the factor loading values of all items except for muscle pain (.48) were above .50. Muscle pain (.48) was included as an individual factor. This is because SARS-CoV-2 accelerates the aging of joints and muscles simultaneously, and as joint pain and muscle pain were derived as the same factor in a previous study [24]. We thought it appropriate to include the muscle pain item in the cluster formation (Table 3).
Nine symptoms were included as the first factor, named the "digestive-cognitive cluster," with an eigenvalue of 4.82, explaining 19.3% of the total variance. Six symptoms were included as the second factor, named the "respiratory-fatigue cluster," with an eigenvalue of 3.96, explaining 15.8% of the total variance. Six symptoms were included as the third factor, named the "pain-dermatological cluster," with an eigenvalue of 3.41, explaining 13.6% of the total variance. Two symptoms were included as the fourth factor, named the "sensory cluster," with an eigenvalue of 2.28, explaining 9.1% of the total variance. Finally, two symptoms were included as the fifth factor, named the "emotional cluster," with an eigenvalue of 2.11, explaining 8.5% of the total variance (Table 3).
4. Relationship between Symptom Clusters and Quality of Life
To perform cluster analysis, the sum of symptom clusters was scored, and groups were classified accordingly. A two-step cluster analysis was conducted to identify clusters based on symptom severity, using hierarchical cluster analysis (Ward's method) followed by non-hierarchical cluster analysis (K-means method). First, hierarchical cluster analysis was performed to determine the number of clusters by symptom severity. Based on the Ward method and dendrogram results (profile matching degree and classified case consistency), and previous study analyzing the severity of 30 symptoms in hemodialysis patients divided into two groups [25], the optimal number of clusters was determined to be two. The centroids and Euclidean distances from the K-means cluster analysis are shown in Table 4. As the number of clusters was specified in advance, their appropriateness was evaluated, and the subgroup was used as the two-cluster solution. Consequently, 103 (46.8%) and 117 (53.2%) participants were in the higher and lower symptom groups, respectively.
Table 4.
Quality of Life According to Subgroups of Symptom Cluster (N=220)
| Variables | Range | Total | Higher-symptom group (n=103)† | Lower-symptom group (n=117)† | t | p |
|---|---|---|---|---|---|---|
| M± SD | M± SD | M± SD | ||||
| Overall quality of life | 1∼5 | 3.08±0.56 | 2.99±0.61 | 3.17±0.51 | 2.34 | .020 |
| Physical health domain | 0∼100 | 51.85±15.66 | 49.17±16.94 | 54.21±14.10 | 2.41 | .017 |
| Psychological health domain | 0∼100 | 52.81±15.72 | 50.37±16.15 | 54.97±15.09 | 2.18 | .030 |
| Social relationships domain | 0∼100 | 55.65±18.60 | 55.23±19.09 | 56.03±18.24 | 0.32 | .753 |
| Environment domain | 0∼100 | 53.46±15.71 | 50.43±16.94 | 56.14±14.07 | 2.73 | .007 |
Total overall QoL of the participants with long COVID averaged 3.08±0.56 points. QoL scores ranged from 0 to 100 points, with the social relationship domain having the highest average score (55.65±18.60 points), followed by the environment (53.46±15.71 points), psychological health (52.81±15.72 points), and physical health (51.85±15.66 points) domains (Table 4).
The overall QoL of the symptom-higher group (2.99± 0.61 points) was lower than that of the symptom-lower group (3.17±0.51 points; t=2.34, p=020). The physical health QoL (t=2.41, p=.017), psychological health QoL (t=2.18, p=.030), and environmental QoL (t=2.73, p=.007) domains of the symptom-higher group were lower than those of the symptom-lower group. However, in social relations, the difference in scores between the two groups was not statistically significant (t=0.32, p=.753) (Table 4).
5. Quality of Life According to the Subgroup of the Symptom Cluster
To identify the subgroups for each identified symptom cluster, two clusters (symptom-higher vs. symptom-lower group) were set, and K-means cluster analysis was performed. Table 5 displays the centroids and Euclidean distances derived from the K-means cluster analysis. In the “ digestive-cognitive cluster,” the symptom-higher and symptom-lower groups had 74 (33.6%) and 146 (66.4%) participants, respectively. In the “ respiratory-fatigue cluster,” the symptom-higher and symptom-lower groups had 145 (65.9%) and 75 (34.1%) participants, respectively. In the “ pain-dermatological cluster,” the symptom-higher and symptom-lower groups had 94 (42.7%) and 126 (57.3%) participants, respectively. In the “ sensory cluster,” the symptom-higher and symptom-lower groups had 124(56.4%) and 96 (43.6%) participants, respectively. Finally, in the “ emotional cluster,” the symptom-higher and symptom-lower groups had 105 (47.7%) and 115 (52.3%) participants, respectively.
Table 5.
Quality of Life According to Subgroups of Symptom Cluster (N=220)
| Cluster | Symptom subgroup (n) | Cluster centroids | Euclidean distance | Quality of life | U† | Z | p‡ | |
|---|---|---|---|---|---|---|---|---|
| Mean rank | Rank sum | |||||||
| Digestive-cognitive SC | Higher-symptom (74) | 6.16 | 4.26 | 88.57 | 6,554.00 | 3,779.00 | -3.64 | ＜.001 |
| Lower-symptom (146) | 1.90 | 121.62 | 17,756.00 | |||||
| Respiratory-fatigue SC | Higher-symptom (145) | 6.64 | 3.55 | 105.45 | 15,290.00 | 4,705.00 | -1.64 | .051 |
| Lower-symptom (75) | 3.10 | 120.27 | 9,020.00 | |||||
| Pain-dermatological SC | Higher-symptom (94) | 5.13 | 3.55 | 86.41 | 8,123.00 | 3,658.00 | -4.85 | ＜.001 |
| Lower-symptom (126) | 1.58 | 128.47 | 16,187.00 | |||||
| Sensory SC | Higher-symptom (124) | 6.20 | 5.52 | 111.37 | 13,810.00 | 5,855.00 | -0.23 | .409 |
| Lower-symptom (96) | 0.68 | 109.38 | 10,500.00 | |||||
| Emotional SC | Higher-symptom (105) | 6.21 | 4.92 | 95.80 | 10,058.50 | 4,493.50 | -3.28 | ＜.001 |
| Lower-symptom (115) | 1.29 | 123.93 | 14,251.50 | |||||
In three clusters except for the respiratory-fatigue (U=4,705.00, p=.051) and sensory (U=5,855.00, p=.409) clusters, there was a statistically significant difference in the average rank of QoL according to the subgroup of the cluster (digestive-cognitive [U=3,779.00, p <.001]; pain-dermatological [U=3,658.00, p<.001]; and emotional [U=4,493.50, p<.001] clusters).
DISCUSSION
After the COVID-19 pandemic, long-term symptoms began to appear among people with COVID-19 who appeared to have recovered. Symptoms appearing after the acute phase of infection (four weeks) and the collection of health problems experienced by people after COVID-19 infection are called “ long COVID.” Symptoms appear ex-tensively and complexly in multiple organs of the body, lowering patients’ QoL. This study aimed to identify the main symptoms of individuals who experience health is-sues persisting for more than 4 weeks after being diagnosed with COVID-19, clarify symptom clusters, and investigate the relationship between symptom clusters and QoL.
In this study, participants average age was 32.26±6.87 years, which was lower than in previous studies (48 years, range: 32∼56) [26]. This may be because the previous study collected large-scale data from approximately 900 people, leading to a higher average age. In addition, many young adults were included in this study because those with comorbidities were excluded to confirm the independent effects of symptoms on QoL after COVID infection.
In this study, among the long COVID symptoms, fatigue was the most common symptom, experienced by 94.5% of participants, and its intensity was 6.21±2.31 out of 10 points. This study's results supported the results of a previous systematic literature review, in which fatigue was the most common symptom of long COVID [27], and a study on fatigue experienced by approximately 55% of participants [4]. Post-exertional malaise also exhibited high frequency and intensity. This study's results supported previous findings that approximately 71% of participants who were limited in their usual work capacity complained of post-exertional malaise four weeks after COVID-19 infection [27]. Sore throat had the second highest frequency and intensity of symptoms in this study. Sore throat may be experienced, accompanied by fever, as a mechanism of inflammation and may progress to life-threatening epiglottitis. Therefore, prompt examination and treatment are required [28]. Identifying the symptoms of a specific disease is an important part of understanding the symptoms that may occur in other individuals [29]. Fatigue, sore throat, post-exertional malaise, cough, and fever, which were reported to be high in frequency and intensity in this study, were found in people with long COVID. This should be considered first in symptom management. In addition, although the participants of this study were mostly young adults, the prevalence of almost all symptoms experienced by them was high. This may be because most young adults were experiencing chronic symptoms for the first time and were thus highly sensitivity to symptoms.
In this study, based on 26 symptoms, five symptom clusters were identified: digestive-cognitive, respiratory-fatigue, pain-dermatological, sensory, and emotional. The relationship between symptoms in the digestive-cognitive cluster supported the research result that there was a correlation between intestinal pathogens and neuropsychiatric symptoms [30], In addition, dyspnea is a predictor of persistent fatigue, and fatigue has been shown to be associated with several respiratory symptoms, including breathlessness, chest pain, and cough [31], The pain-der-matological cluster found that vascular skin lesions caused by COVID-19 infection caused overall musculoskeletal pain in joints and muscles through the blood [32], and the relationship between the symptoms could be identified. In this study, the sensory cluster comprised the loss of smell and taste. This study's results support previous findings of simultaneous olfactory and gustatory dysfunction in patients [33]. Finally, the emotional cluster was consistent with the results of Sykes et al.'s study, as depression and anxiety became one of the factors [24].
In this study, the average scores for each domain of participants’ QoL varied from 51.85 points (physical health) to 55.65 points (social relationship). These results are relatively similar to the scores reported in a previous study [34], which used the same measurement tool to assess the QoL of adults with symptomatic long COVID (more than 4 weeks post-diagnosis), where scores ranged from 50.2 points (social relationship) to 58.8 points (physical health). However, in this study, the physical health domain had the lowest QoL score, whereas in the existing literature, the social relationship domain was the lowest [13,34]. This discrepancy may be attributed to the data collection period of this study, which was in 2022, compared to the early stages of the pandemic in 2020 for the previous research. During the initial pandemic phase, the necessity for iso-lation and mobility restrictions during the recovery process from infection likely influenced the results.
In current study, among the five clusters, groups with high cluster scores in the digestive-cognitive, pain-derma-tological, and emotional clusters had lower quality of life scores compared to groups with low cluster scores. This indicates that the digestive-cognitive, pain-dermatological, and emotional clusters are significantly associated with the QoL of the participants. Specifically, digestive-cognitive symptoms (e.g., diarrhea, abdominal pain, nausea and vomiting) were frequently encountered but tended to be less severe. However, we found that these symptoms were also closely related to the overall QoL of the participants. In a six-month cohort study based in China [11], it was found that the domains most closely related to health-related QoL were pain (41%) and depression and anxiety (32%). Therefore, it is believed that understanding these symptom clusters and applying nursing interventions that can alleviate these symptoms is necessary to improve the QoL for long COVID patients. In sum, it is difficult to integrate and interpret the results of previous studies because the tools for measuring symptoms and QoL are still inconsistent for each study. Moreover, existing studies are limited because they focused on continuous symptoms and rehabilitation of inpatients. It is important to predict the long-term impact of COVID-19 with systematic and consistent guidelines because participants will experience negative psychological effects if healthcare providers provide inconsistent and inaccurate information [35].
Several limitations of this study were that confirming the causality of the long-term effects of COVID was not possible in a cross-sectional study. Nevertheless, while much of the information in previous studies was collected from a limited population that visited hospitals, this study included data from the general population who were not hospitalized, excluding those with underlying diseases that could potentially affect their QoL. Furthermore, the utilization of a self-report survey for data collection in research may have introduced bias into the results. In Addition, in the current guidelines of the Korean Society of Infectious Diseases, long COVID is defined as symptoms persisting beyond 12 weeks. Symptoms lasting between 4 to 12 weeks are classified as post-acute COVID-19. Therefore, it is deemed necessary to exercise caution when inter-preting the results of this study in accordance with the recent guidelines [16]. Finally, this study did not consider the known side effects of pharmacological therapies administered to the participants. Therefore, it is recommended that future research consider treatment methods, including drug administration, and any associated side effects.
CONCLUSION
This study aimed to provide basic data for the development of systematic symptom management interventions for long COVID in clinical practice by understanding the symptom clusters experienced by participants. Among the most severe symptoms experienced by long COVID patients were fatigue, sore throat, cough, post-exertional malaise, and fever. It was found that the digestive-cognitive, pain-dermatological, and emotional clusters among the five symptom clusters were related to the QoL. Therefore, it was confirmed that understanding these symptom clusters and adopting a nursing approach to them is necessary to improve the QoL for long COVID patients. Based on the results of this study, there is a need to share and educate on clinical case information related to long COVID from the onset of initial symptoms in patients, as such education is expected to help quickly identify and prevent the persistence of symptoms. Furthermore, this study provides significant foundational data for developing nursing intervention strategies aimed at improving the QoL for long COVID patients. Lastly, it is recommended that lon-gitudinal cohort studies be conducted to reduce the impact of digestive-cognitive, pain-dermatological, and emotional clusters. Additionally, practical application and effectiveness verification studies should be conducted for the standardization of tools for measuring long COVID symptoms.
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