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Original Article
Current Status and Associated Factors of Emotional Distress Due to COVID-19 Among People with Physical Disabilities Living in the Community: Secondary Data Analysis using the 2020 National Survey of Disabled Persons
Bohye Kim1orcid, Ju Young Yoon2orcid
Research in Community and Public Health Nursing 2024;35(1):37-50.
DOI: https://doi.org/10.12799/rcphn.2023.00374
Published online: February 29, 2024

1Ph.D. Student, College of Nursing, Seoul National University, Seoul, Korea

2Professor, College of Nursing, Seoul National University ∙ Research Institute of Nursing Science, Seoul National University, Seoul, Korea

Corresponding author: Ju Young Yoon College of Nursing and Research Institute of Nursing Science, Seoul National University, 103 Daehak-ro, Jongno-gu, Seoul 03080, Korea Phone: +82-2-740-8817, Fax: +82-2-741-5244, E-mail: yoon26@snu.ac.kr
• Received: October 31, 2023   • Revised: February 15, 2024   • Accepted: February 15, 2024

© 2024 Korean Academy of Community Health Nursing

This is an Open Access article distributed under the terms of the Creative Commons Attribution NoDerivs License. (http://creativecommons.org/licenses/by-nd/4.0) which allows readers to disseminate and reuse the article, as well as share and reuse the scientific material. It does not permit the creation of derivative works without specific permission.

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  • Purpose
    This study aimed to assess the current situation and factors associated with emotional distress due to COVID-19 among people with physical Disabilities living in the community, using a Social-Ecological Model.
  • Methods
    A secondary data analysis was performed using data from the 2020 National Survey of Disabled Persons. The study participants were 1,654 participants aged 19 years or older with physical Disabilities. For data analysis, complex sample logistic regression was conducted to identify factors associated with emotional distress due to COVID-19 in people with physical Disabilities.
  • Results
    The results showed that 55.7% of people with physical Disabilities living in the community experienced emotional distress due to COVID-19. This emotional distress was influenced by various factors, including intrapersonal factors (activities of daily living, difficulty in getting information about COVID-19, difficulty in obtaining and using equipment related to COVID-19), interpersonal factors (satisfaction with the number of friends), and community/policy factor (support related to COVID-19 from national and local governments).
  • Conclusion
    It is recommended to develop tailored interventions to prevent mental health issues among people with physical Disabilities by considering the factors related to their emotional distress in the event of future infectious disease disasters.
1. Background
The outbreak of the novel coronavirus disease-19 (COVID-19) had spread rapidly across the world since the first cases of COVID-19 were detected in Wuhan, China in December 2019, and the World Health Organization (WHO) declared COVID-19 as a global pandemic, the highest level of infectious diseases in terms of the rate of spread of a disease, on March 11, 2020 [1]. In Korea, after the first case of COVID-19 was detected in January 2020 [2], a rapid spread of the infectious disease occurred, so the government recommended that people follow social distancing and guidelines for infection prevention and control for COVID-19 to prevent the occurrence and spread of COVID-19 infections. As a result, people experienced unprecedented social isolation, and this social isolation during the COVID-19 pandemic had negative social, psychological, and economic impacts. This disaster situation causes psychological trauma in people nationwide, and results in social and economic losses and mental health problems even after the disaster situation comes to an end. Consequently, there emerged a new word ‘Corona Blue’, which means depression and anxiety due to COVID-19, and more emphasis has been placed upon the importance of preventive measures and interventions for the psychological impact of COVID-19 [1,3].
COVID-19 is a crisis equally experienced by all people, but its impact may be different depending on each individual’s situation and environment [3,4]. In particular, the vulnerable health conditions of people with disabilities put them at higher risk for infection, and in the absence of adequate welfare services, they experience more difficulties in daily life than people without disabilities, which may lead to a serious psychological impact [3,5]. In an early stage of the spread of COVID-19, there were not sufficient preventive measures against COVID-19 for people with disabilities, but the government strengthened the infection prevention and control system against the spread of COVID-19 after the occurrence of mass infections in residential facilities for people with disabilities [6]. Afterwards, the government provided support services such as emergency personal assistance support benefits and special benefits for the temporary absence of guardians not only to people with disabilities living in facilities but also to people with disabilities living in the community, but there was a lack of psychological support and services for the mental health of people with disabilities [6]. Therefore, there is a need to provide tailored psychological interventions by taking into account the special needs of people with disabilities in disaster situations such as the COVID-19 pandemic.
Previous studies showed that COVID-19 had a greater impact on mental health in people with disabilities than those without disabilities. According to prior studies conducted overseas, during the COVID-19 period, people with disabilities were found to have significantly greater amounts of symptoms of depression, anxiety, and loneliness, showed poorer sleep quality and poorer quality of life, and experienced a higher level of stress due to COVID-19, compared to those without disabilities [7,8]. In addition, a domestic study reported that after the COVID-19 pandemic, levels of loneliness, anxiety, and depression were 1.9 times higher, respectively, in people with disabilities, compared to those without disabilities, and there was a greater reduction in the level of satisfaction with life in people with disabilities (a 44.0% decrease) than those without disabilities (a 34.6% decrease) after the COVID-19 pandemic, compared to the pre-COVID-19 level of satisfaction with life [9]. Furthermore, previous studies have reported that gender, household income, disability grade, type of disability, chronic pain, social isolation, negative financial situations due to COVID-19, concerns about COVID-19, and increased loneliness were identified as factors affecting mental health in people with disabilities during the COVID-19 period, and that the level of depression was found to increase significantly over time in people with disabilities [3,10-13]. As described above, a review of domestic and foreign studies revealed that although many studies have been conducted to compare the impact of COVID-19 on mental health between people with disabilities and those without disabilities or to examine the effects of COVID-19 on mental health in people with disabilities as a whole, there has not been sufficient research to analyze the impact of COVID-19 on mental health in populations with each type of disability [3].
In particular, although people with physical disabilities account for the largest proportion of those with disabilities living in the community, there is a lack of research on the emotional impact of the COVID-19 pandemic on people with physical disabilities [14]. Persons with physical disabilities refer to people who have limitations on physical functions due to permanent impairment in the upper extremities, lower extremities, or body structure. As of 2020, among 15 types of disabilities, people with physical disabilities take up the largest proportion at 45.1% [15,16]. A previous study has revealed that elderly people with physical disabilities experience more emotional distress, including greater amounts of symptoms of depression and anxiety and a higher level of loneliness, compared to those without physical disabilities [7]. Under the circumstances of the COVID-19 pandemic, people with physical disabilities are more likely to experience increased levels of social isolation due to decreased access to healthcare services, changes in lifestyle habits, emotional changes, and reduced levels of physical activity, so it is necessary to provide adequate emotional support for them [6,14]. Therefore, in order to prevent the mental health problems of people with physical disabilities and reduce potential inequalities during disaster crises such as the COVID-19 pandemic, research should be conducted to systematically explore factors affecting mental health problems due to COVID-19 in such groups at higher risk for emotional distress in order to elucidate their psychological vulnerability and thereby contribute to the improvement of related policies and development of appropriate interventions.
Since mental health is influenced by various factors as well as individual factors, it is necessary to comprehensively consider environmental and social factors in addition to individual factors. The social-ecological model proposed by Mcleroy et al. [17] is one of the representative models widely used in the fields of public health and health promotion, and presents a theoretical framework that integrates individual and environmental dimensions that affect individuals’ health status and health behavior [18]. This social-ecological model can be used to assess influencing factors for human behavior and explore appropriate interventions in terms of five types of factors centered on intrapersonal factors: intrapersonal, interpersonal, institutional, community, and policy factors [17-19]. In previous studies, a social-ecological model has been employed to analyze factors affecting health and health behavior among various groups of people, such as people living in tiny single-room residences (residents of jjokbang villages) [20], caregivers [19], elderly people in rural villages [18], elderly people [21], adults [22,23], and people with intellectual and/or developmental disabilities [24]. Thus, this study aimed to investigate factors associated with emotional distress due to COVID-19 in people with physical disabilities living in the community in terms of intrapersonal, interpersonal, community, and policy levels by applying a social-ecological model. Through this investigation, the present study sought to provide an increased understanding of the impact of a crisis situation such as COVID-19 on mental health in people with physical disabilities in the event of future disaster situations such as COVID-19, and to present research results that can serve as basic data for the development of nursing intervention programs for mental health prevention and psychological support.
2. Research Objectives
This study aimed to identify factors affecting emotional distress due to COVID-19 in people with physical disabilities living in the community, and the specific objectives are as follows:
1) To identify the current status of socio-ecological factors and emotional distress due to COVID-19 in people with physical disabilities living in the community;
2) to explore factors affecting emotional distress due to COVID-19 in people with physical disabilities living in the community, based on a social-ecological model.
1. Study design
This study is a cross-sectional descriptive study using data from the 2020 National Survey of Disabled Persons conducted by the Korea Institute for Health and Social Affairs, and the present study attempted to identify factors influencing emotional distress due to COVID-19 in people with physical disabilities living in the community by applying a social-ecological model. The theoretical framework of this study is shown in Figure 1.
2. Participants
This study used data from the 2020 National Survey of Disabled Persons carried out by the Ministry of Health and Welfare through the Korea Institute for Health and Social Affairs. The National Survey of Disabled Persons has been conducted among registered people with disabilities nationwide every three years to examine the overall status of persons with disabilities since it was conducted for the first time in 1980, and the 2020 National Survey of Disabled Persons was the 11th survey [16]. This data was collected from a total of 7,025 people through interviews conducted by paying door-to-door visits to individual participants, and the survey participants were selected by the stratified cluster sampling method among registered people with disabilities in 17 cities and provinces in Korea [16]. The participants of this study were adults with physical disabilities, and a person with a physical disability refers to a person registered as physically disabled, a subcategory of the impairment of external physical functions among the types of disabilities stipulated in the Act on Welfare of Persons with Disabilities. Among a total of 7,025 people who participated in the survey, 1,785 adults with physical disabilities aged 19 or older were selected as the study participants, and a total of 1,654 people were finally included in the analysis excluding people with missing data (Figure 2).
3. Measures

1) Dependent variables

According to WHO, mental health is more than the absence of mental disorders, such as depression, anxiety, and mental health conditions, and it is defined as a state of mental well-being that enables people to cope with stress, realize their abilities, and contribute to their community [25].
In this study, among the questions used in the 2020 Survey on Persons with Disabilities, the following item was operationally defined as emotional distress due to COVID-19: “During the recent spread of COVID-19 infections, how much difficulty did you experience in the following activities of daily living compared to usual? - regarding emotional stability (loneliness, depression, anxiety, stress, etc.)” The participants who answered that they experienced no difficulty were classified as having no emotional distress, and those who responded that they experienced somewhat or considerable difficulty were classified as having emotional distress.

2) Independent variables

This study posited factors affecting mental health reported in previous studies [3,7,12,26-28] as independent variables, based on a social-ecological model. The intrapersonal, interpersonal, and community/policy factors were defined as follows based on the survey items of the 2020 National Survey of Persons with Disabilities.

2-1) Intrapersonal factors

Intrapersonal factors are individual characteristics that affect mental health in people with disabilities, and the intrapersonal factors analyzed in this study were as follows: degree of disability, subjective health status, ADL (Activities of Daily Living), IADL (Instrumental Activities of Daily Living), difficulty in getting information related to COVID-19, and difficulty in obtaining and using equipment related to COVID-19. The degree of disability was classified as mild when it was assessed as not severe in the assessment of the level of disability or the existing grade of disability was 4-6. The degree of disability was classified as severe when it was assessed as severe or the existing grade of disability was 1-3. Subjective health status was measured using the question “How do you rate your usual health?”, and it was rated on a 5-point scale ranging from 1 point (=‘Very good’) to 5 points (=‘Very poor’). Higher scores indicate poorer subjective health status. ADL was categorized as not needing support (independent) when the respondent did not need assistance with any of the 12 items, and as needing support (dependent) when the respondent needed assistance with at least one of the 12 items. IADL was categorized as not needing support (independent) when the respondent did not need assistance with any of the eight items, and as needing support (dependent) when the respondent needed assistance with at least one of the eight items. Difficulty in getting information related to COVID-19 was assessed using the following question: “Have you experienced any difficulty related to infection prevention during the recent spread of COVID-19? – regarding the difficulty in getting information (status of the occurrence of infections, infection prevention and control guidelines, etc.)” People who answered that they had no difficulty in getting information were categorized as having no difficulty, and those who answered that they had some or considerable difficulty were classified as having difficulty. Difficulty in obtaining and using equipment related to COVID-19 was measured with the following question: “Have you experienced any difficulty related to infection prevention during the recent spread of COVID-19 (since February 2020)? – regarding obtaining and using infection prevention products related to COVID-19 (such as the purchase and use of masks and hand sanitizers, etc.).” People who answered that they had difficulty in obtaining and using equipment related to COVID-19 were classified as having no difficulty, and those who answered that they had some or considerable difficulty were classified as having difficulty.

2-2) Interpersonal factors

Interpersonal factors are related to social networks and social support systems. In this study, satisfaction with the family relationship, satisfaction with the number of friends, leisure activities, and experiences of social discrimination were selected as interpersonal variables. Satisfaction with the family relationship was rated on a 4-point scale ranging from 1 point (= ‘Very satisfied’) to 4 points (= ‘Very dissatisfied’) by using the question “How satisfied are you with your current life? - regarding the family relationship.” This item was reverse-coded, and higher scores indicate higher levels of satisfaction with the family relationship. Satisfaction with the number of friends was assessed on a 4-point scale from 1 point (= ‘Very satisfied’) to 4 point (= ‘Very dissatisfied’) by using the question “How satisfied are you with your current life? -regarding the number of friends” This item was reverse-coded, and higher scores indicate higher levels of satisfaction with the number of friends. Regarding the presence or absence of leisure activities, the participants who had participated in at least one of the 15 leisure activities in the past week were categorized as having leisure activities, and those who had not participated in any of them were categorized as having no leisure activities. The experience of social discrimination was measured by using the question “Have you ever suffered any of the following social discrimination due to your current disability?” with respect to a total of 19 items. People with the experience of discrimination in at least one of the 19 items were classified as having the experience of discrimination. People without any experience of discrimination in all of the 19 items were classified as having no experience of discrimination.

2-3) Community/Policy factor

Community/policy factors refer to environmental assets and policies that can support individuals’ behavior and improve individuals’ health. In this study, support from national and local governments related to COVID-19 was selected as the community/policy factor. Among the survey items, the question “Have you received any additional support from national and local governments during the recent spread of COVID-19?” was used to examine the presence or absence of support from national and local governments related to COVID-19. In other words, participants who received support in at least one of the six items were categorized as receiving support, and those who did not receive support in any of the six items were categorized as not receiving support.

3) Covariates

Gender, age, education level, household income, residence, and household type were set as covariates, based on previous studies [3,7,12] that identified factors affecting mental health problems due to COVID-19 in people without disabilities. Gender was divided into male and female, and age was classified into four age groups: ages below 40 (≤39), ages 40-59, ages 60-79, and ages above 79 (≥80). Education level was classified into elementary school or lower, middle school, high school, and college or higher. Based on the quartiles of average monthly household income, average monthly household income was divided into four income groups: low (800,000 won or less), lower middle (more than 800,000 won and less than 1.5 million won), upper middle (more than 1.5 million won and less than 2.9 million won), and high (more than 2.9 million won). Residence was classified into metropolitan cities, small and middle cities, and rural areas, and household type was categorized into single-person households and non-single-person households.
4. Statistical analysis
This study conducted an analysis of survey data from a complex sample design by applying weights from the National Survey of Persons with Disabilities to ensure that data of the sample was representative of the population, and the statistical significance level was set at less than .05. In a complex sample analysis, the standard error bias of estimates may occur when cases are deleted or selected, so data analysis is performed by generating cluster variables and using them to specify the parent population [29]. Specifically, statistical analysis was carried out as follows. First, to analyze the participants’ sociodemographic characteristics, socio-ecological factors, and emotional distress due to COVID-19 by using descriptive statistics, unweighted frequencies were presented, and percentages, and all other statistical values were analyzed by applying weights. Second, to compare differences in the presence or absence of emotional distress due to COVID-19 according to the socio-demographic characteristics and socio-ecological factors of the participants, the Rao-Scott x2 test, which is a complex samples cross-tabulation analysis, and the t-test of the complex samples general linear model were conducted. Third, a complex samples logistic regression analysis was conducted to analyze factors affecting emotional distress due to COVID-19 in the participants. All statistical analyses were conducted using the analysis methods for complex sample design data of SPSS 23.0.
5. Ethical considerations
This study received an exemption determination from the IRB of Seoul National University (IRB No. E2308/001-010). The researcher downloaded and used the raw data, questionnaire, and codebook of the 2020 National Survey of Disabled Persons from the health and welfare data portal of the Korea Institute for Health and Social Affairs after applying and receiving approval for the use of data from the National Survey of Disabled Persons through application for access to microdata of the above-mentioned data portal. The data provided was anonymized using unique numbers to make personal data unidentifiable.
1. Distributions of sociodemographic characteristics, socio-ecological factors, and factors affecting emotional distress due to COVID-19 in participants
With respect to the sociodemographic characteristics of the participants, in gender, males (55.8%) took up the larger proportion of the participants than females. In age, the 60-79 age group (51.3%) made up the largest proportion of the participants. As for the average monthly household income, the low income group with an average monthly household income of ≤800,000 won (26.3%) made up the largest proportion, and for residence, people living in metropolitan cities (37.7%) accounted for the largest proportion. In terms of intrapersonal factors among the socio-ecological factors of the participants, 80.5% of the participants had mild disability. 23.7% of the participants needed support for ADL or were dependent on others in ADL, and 34.3% needed support for IADL. 55.1% of the participants had no difficulty in getting information related to COVID-19, and 54.0% had no difficulty in obtaining and using equipment related to COVID-19. With respect to interpersonal factors, the average score for satisfaction with family relationships was 3.08±0.02 points out of 4, and the average score for satisfaction with the number of friends was 2.79±0.02 points out of 4. As for the community/policy factor, 58.8% of the participants received no support related to COVID-19 from national and local governments. Lastly, regarding emotional distress due to COVID-19, 55.7% of the participants responded that they experienced emotional distress (Table 1).
2. Differences in emotional distress due to COVID-19 according to the characteristics of participants
A comparative analysis of differences in emotional distress due to COVID-19 according to the characteristics of participants revealed that there were significant differences in emotional distress according to all the variables except the degree of disability (Table 2). With respect to the presence or absence of emotional distress due to COVID-19 according to intrapersonal factors, there were statistically significant differences according to subjective health status (t=6.36, p<.001), ADL(x2=48.27, p<.001), IADL(x2=34.41, p<.001), difficulty in getting information related to COVID-19 (x2=333.74, p<.001), and difficulty in obtaining and using equipment related to COVID-19 (x2=306.54, p<.001), although the degree of disability was not significantly associated with emotional distress due to COVID-19. Regarding the presence or absence of emotional distress due to COVID-19 according to interpersonal factors, there were statistically significant differences according to satisfaction with family relationships (t=-7.49, p<.001), satisfaction with the number of friends (t=-9.85, p<.001), leisure activities (x2=12.19, p<.001), and experience of social discrimination (x2=13.63, p<.001). In the case of the presence or absence of emotional distress due to COVID-19 according to the community/policy factor, there was a statistically significant difference in emotional distress according to the presence or absence of support related to COVID-19 from the national and local governments (x2=10.35, p=.001).
3. Factors affecting emotional distress due to COVID-19 in participants
Before identifying factors associated with emotional distress due to COVID-19 in the participants, a test for multicollinearity between independent variables was performed. The tolerance value was found to be greater than 0.1, ranging from 0.272 to 0.954, and the variance inflation index (VIF) was less than 10, ranging from 1.048 to 3.677. As a result, it was confirmed that there was no problem of multicollinearity between independent variables. Next, a complex samples logistic regression analysis was performed by including all socio-ecological factor variables and considering sociodemographic variables (Table 3). First, among sociodemographic variables, gender and residence showed a statistically significant relationship with emotional distress due to COVID-19. Compared to women with physical disabilities, men with physical disabilities were found to be 0.73 times less likely to experience emotional distress due to COVID-19 (95% CI=0.54-0.98). People with physical disabilities living in small or middle cities were shown to be 1.78 times more likely to experience emotional distress due to COVID-19 than those living in rural areas (95% CI=1.27-2.50). Next, with respect to socio-ecological factors affecting emotional distress due to COVID-19, first, in the case of intrapersonal factors, ADL, difficulty in getting information related to COVID-19, and difficulty in obtaining and using equipment related to COVID-19 were identified as factors associated with emotional distress due to COVID-19. More specifically, people who needed support for ADL were 1.58 times more likely to experience emotional distress due to COVID-19 than those who did not need support for ADL (95% CI=1.01-2.47). People who had difficulty getting information related to COVID-19 were 3.79 times more likely to experience emotional distress due to COVID-19, compared to those who had no difficulty (95% CI=2.43-5.89). People who had difficulty obtaining or using related equipment were 3.02 times more likely to experience emotional distress due to COVID-19, compared to those who had no difficulty (95% CI=1.97-4.62). Second, among interpersonal factors, satisfaction with the number of friends was identified as a significant influencing factor for emotional distress due to COVID-19. The higher level of satisfaction with the number of friends was associated with 0.64 times lower likelihood to experience emotional distress due to COVID-19 (95% CI=0.51-0.81). Lastly, regarding the community/policy factor, the presence or absence of support from national and local governments related to COVID-19 was found to affect emotional distress due to COVID-19. People who received support related to COVID-19 from the national and local governments were 1.47 times more likely to experience emotional distress due to COVID-19 (95% CI=1.11-1.94).
This study aimed to examine the current status of socio-ecological factors selected based on a socio-ecological model and emotional distress due to COVID-19 in people with physical disabilities living in the community by using data from the 2020 National Survey of Disabled Persons, and also attempted to identify factors affecting emotional distress due to COVID-19 in people with physical disabilities by using a complex samples logistic regression analysis. The analysis results of this study showed that 55.7% of people with physical disabilities living in the community experienced emotional distress due to COVID-19. In other words, more than half of the participants were found to have experienced more mental health problems such as loneliness, depression, anxiety, and stress during the COVID-19 period than usual. Previous domestic and foreign studies have reported negative impacts of COVID-19 on mental health among people with disabilities [3,8,12,13,30]. In particular, people with physical disabilities were shown to have experienced mental health problems such as depression, anxiety, and loneliness during the COVID-19 period [7,9]. Although these findings of prior studies are in agreement to the results of this study, the indicator of emotional distress due to COVID-19 was not specific in this study, so caution is needed in interpreting the results of this study. In disaster situations such as COVID-19, people with physical disabilities experience higher levels of perceived social isolation among because of restrictions on support for activities of people with physical disabilities due to concerns about infection as well as the suspension and reduction of the use of services, and also have financial problems due to reduced income, and these factors negatively affect mental health [3,5]. Therefore, it is essential to comprehensively examine and understand factors affecting mental health in people with physical disabilities in disaster situations such as the COVID-19 pandemic.
With respect to intrapersonal factors among the social-ecological factors, ADL was found to have a significant impact on emotional distress due to COVID-19 in people with physical disabilities. First, it was shown that a greater need for support in ADL was positively associated with a higher likelihood of emotional distress among people with physical disabilities. A number of previous studies [26,28,31] have reported similar findings regarding the relationship between the ability to perform ADLs and mental health problems such as depression. The results of this study are also consistent with a previous study showing that a higher level of dependence on others in ADL is associated with an increased level of depression among people with physical disabilities [31]. People who have a higher level of dependency in ADL need to receive more help from others, such as family members or disability support workers. During the COVID-19 period, people with disabilities who are highly dependent on others for ADLs find it difficult to maintain social distancing with others, and are at higher risk for infection through contact with others, and this situation would affect psychological factors such as anxiety, fear, and depression in people with disabilities [13]. Therefore, it is necessary to identify people with physical disabilities who need support for ADLs as a high-risk group for mental health, and to give priority to them when applying psychological interventions.
In this study, among the intrapersonal factors of people with physical disabilities, difficulty in getting information related to COVID-19 and difficulty in obtaining and using equipment related to COVID-19 were found to be significant influencing factors for emotional distress due to COVID-19. This finding is consistent with a previous study showing that obtaining more accurate information related to COVID-19 is linked to the reduction of negative impacts of COVID-19 on mental health [32]. A previous study by the National Rehabilitation Center reported that 15.0% of people with physical disabilities found it difficult to get information related to COVID-19 [9], and this proportion is lower than the result of this study (44.9%), but this difference may be attributed to differences in the sample size and research methods. Regarding the main reasons why people with physical disabilities have difficulty accessing information, a previous study reported that the most common reason given by more than half of the respondents (55.6%) was ‘I don’t know the methods’, followed by ‘a lack of guidance through easy-to-understand pictures and videos’ (24.6%) [9]. The results of this study also showed that greater difficulty in obtaining and using equipment related to COVID-19 was associated with a higher likelihood of experiencing emotional distress due to COVID-19. A previous study reported that infection prevention and control measures such as wearing masks and using hand sanitizers reduce psychological impacts, depression, anxiety, and stress [32]. However, since people with physical disabilities have limitations on physical functioning, they experience more difficulty in complying with general infection prevention and control guidelines for COVID-19 than people without disabilities [9,33,34]. In disaster situations such as COVID-19, difficulty in accessing information related to infectious diseases as well as obtaining and using products for infection prevention and control are likely to be perceived as discrimination against disabled persons by people with physical disabilities [9,12], and this increases anxiety and fear about disease infections, leading a negative impact on mental health. Therefore, it is necessary to develop guidelines for infection prevention and control and information access and delivery methods by taking into account the characteristics of people with physical disabilities in order to keep difficulties related to infection prevention and control measures from negatively affecting mental health in people with physical disabilities, and prevent psychological distress among people with physical disabilities in the event of future infectious disease disasters.
In this study, regarding interpersonal factors among socio-ecological factors, satisfaction with the number of friends was found to be negatively correlated with emotional distress due to COVID-19. In other words, a higher level of satisfaction with the number of friends was associated with a lower likelihood of experiencing emotional distress due to COVID-19. In this connection, a previous study mentioned that COVID-19 had a negative impact on social interactions in elderly people with physical disabilities, and that less social interaction was associated with a greater degree of deterioration of mental health problems such as depression and loneliness in people with physical disabilities [7]. Satisfaction with the number of friends is a measure of social support and indicates satisfaction with social networks, and positive experiences from social support increase psychological well-being in people with disabilities [35]. During the COVID-19 period, people with disabilities are more likely to become socially isolated due to social distancing, self-quarantine, and disruption of the use of welfare services, so there arises a need to provide sufficient emotional support for them [6]. In an infectious disease outbreak situation such as COVID-19, people without disabilities can maintain social relationships online through social media, but people with disabilities may have limitations due to the constraints related to their disabilities [3]. Therefore, it is necessary to provide support through various media to ensure that people with physical disabilities will not be isolated from social relationships and can receive continuous emotional support through the social support system in an infectious disease disaster situation.
In this study, support related to COVID-19 from national and local governments was considered as a community/policy factor, and it was found that people with disabilities who received support related to COVID-19 from national and local governments were more likely to have emotional distress due to COVID-19. In general, support policies such as personal assistance services for people with disabilities were found to have a positive emotional impact on people with disabilities [36], and the results of this study are not consistent with such findings. In this study, the additional support items related to COVID-19 that people with physical disabilities received from national and local governments were found to be mostly products for infection prevention and control (Table 4). Thus, it seems that there was not sufficient support for mental health and psychological support, and simply providing supplies is thought to have no significant effect on mental health. A previous research reported that providing external support such as products for infection prevention and control and food to people with pre-existing depression prior to the COVID-19 period was associated with a decrease in the prevalence of anxiety and depression[37], but it is difficult to compare the findings of the prior study with the results of this study. This study is a cross-sectional study, and there is a need to conduct a longitudinal research to investigate the relationship of community-based and policy-based support services with mental health through in the future. The National Center for Disaster and Trauma and mental health centers of local governments provide counseling and psychological support services for mental health problems due to disasters such as COVID-19, but there are not services available that reflect the reality and characteristics of people with disabilities [1]. Therefore, there is a need to strengthen psychological support services for people with physical disabilities, and in particular, it is necessary to provide tailored psychological support services based on understanding of people with disabilities by considering measures such as utilization of peer counselors [5]. These efforts are expected to help detect emotional distress early in people with physical disabilities living in the community in disaster situations such as COVID-19 and provide effective support for them in the community.
This study has the following limitations. First, since this study was conducted using secondary data to identify influencing factors for emotional distress due to COVID-19, variables included in the analysis were not sufficient to measure various aspects of socio-ecological factors. In particular, this study had included only one variable related to community and policy factors in the analysis due to the limitation of data available, and there was some difficulty in interpreting variables such as satisfaction with the number of friends, which is an interpersonal factor. Therefore, in a follow-up research, it is necessary to conduct more comprehensive research by considering socio-ecological variables using valid tools. Additionally, since this study analyzed cross-sectional data, it had limitations in explaining causal relationships between variables. Moreover, because this study was conducted not with the entire population of people with physical disabilities but with a group of people with physical disabilities, there are limitations in generalizing and applying the results of this study to all people with physical disabilities. However, this study analyzed the current status and associated factors of emotional distress due to COVID-19 in people with physical disabilities living in the community for the first time in Korea by using a nationwide survey data by complex sample analysis methods. As a result, this research demonstrated that there is a need to develop an intervention program for providing psychological support in infectious disease disaster situations such as COVID-19. The results of this study showed that in the event of an infectious disease outbreak disaster in the future, it is necessary to give priority to people with physical disabilities who need support for ADLs when applying psychological interventions in order to prevent their psychological distress, and there is also a need for support services to provide appropriate information and help to use infection prevention control products. In addition, it is necessary to expand the provision of tailored psychological support services for people with physical disabilities instead of providing only some supplies and to strengthen the social support system to prevent their social isolation.
This study investigated socio-ecological factors and emotional distress due to COVID-19 in people with physical disabilities by using data from the 2020 National Survey of Disabled Persons, and attempted to identify factors associated with emotional distress due to COVID-19 by a complex samples logistic regression analysis. The analysis results of this study showed that more than half of adults with physical disabilities living in the community experienced emotional distress due to COVID-19. Factors associated with emotional distress due to COVID-19 were found to be gender and residence among sociodemographic factors, ADL, difficulty in getting information related to COVID-19, and difficulty in obtaining and using equipment related to COVID-19 among interpersonal factors, satisfaction with the number of friends as an interpersonal factor, and support from the national and local governments related to COVID-19 as a community/policy factor. Therefore, in order to provide adequate support for the mental health of people with physical disabilities in the event of future disaster situations due to the outbreak of infectious diseases such as COVID-19, it is necessary to pay more attention to people with physical disabilities living in the community with these characteristics, and identify mental health risk groups for early prevention and management. Additionally, it is required to improve support policies and systems for the promotion of mental health at the national and community levels by taking into consideration the characteristics of each type of disability. 

Conflict of interest

Ju Young Yoon has been editorial board member of the Research in Community and Public Health Nursing. She was not involve in the review process of this manuscript. No conflict of interest has been declared by authors.

Funding

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. 2022R1I1A207290712) and was supported by the BK21 four project (Center for Human-Caring Nurse Leaders for the Future) funded by the Ministry of Education (MOE, Korea) and National Research Foundation of Korea (NRF).

Authors’ contributions

Bohye Kim contributed to conceptualization, data curation, formal analysis, methodology, visualization, and writing – original draft, review & editing. Ju Young Yoon contributed to conceptualization, methodology, writing – review & editing, supervision, and validation.

Data availability

The National Survey of Disabled Persons (2020) were obtained from the Korea Institute for Health and Social Affairs Health and Welfare Data Portal(https://data.kihasa.re.kr/kihasa/main.html).

None.
Figure 1.
Research Framework of This Study
rcphn-2023-00374f1.jpg
Figure 2.
Participants Selection Flowchart
rcphn-2023-00374f2.jpg
Table 1.
Characteristics of Study Participants (N=1,654)
Variables Categories(Range) n(%) or M±SE
General characteristics Gender Female 702(44.2)
Male 952(55.8)
Age 19~39 58(4.1)
40~59 474(29.2)
60~79 888(51.3)
≥80 234(15.4)
Education ≤Elementary school 635(37.6)
Middle school 328(20.1)
High school 448(27.7)
≥College 243(14.6)
Household income Low 426(26.3)
Middle-low 421(23.7)
Middle-high 396(24.7)
High 411(25.4)
Residence Metropolitan cities 726(37.7)
Middle and small cities 441(28.1)
Rural area 487(34.2)
Household type Single 419(25.6)
Not single 1235(74.4)
Intrapersonal factors Degree of disability Mild 1084(80.5)
Severe 570(19.5)
Subjective health status 1-5 3.45±0.02
ADL Dependent 465(23.7)
Independent 1189(76.3)
IADL Dependent 643(34.3)
Independent 1011(65.7)
Difficulty in getting information about COVID-19 Yes 703(44.9)
No 951(55.1)
Difficulty in obtaining and using equipment related to COVID-19 Yes 739(46.0)
No 915(54.0)
Interpersonal factors Satisfaction with family 1-4 3.08±0.02
Satisfaction with the number of friends 1-4 2.79±0.02
Leisure Yes 1545(93.8)
No 109(6.2)
Discrimination Yes 562(31.1)
No 1092(68.9)
Community/Policy factor Support related to COVID-19 from national and local governments Yes 673(41.2)
No 981(58.8)
Emotional distress due to COVID-19 Yes 909(55.7)
No 745(44.3)

Unweighted N(weighted %); ADL=Activities of daily living; IADL=Instrumental activities of daily living

Higher scores indicate worse subjective health status; Higher scores indicate greater satisfaction

Table 2.
Differences in Emotional Distress due to COVID-19 according to Variables (N=1,654)
Variables Categories (Range) Emotional distress due to COVID-19 Rao-Scott χ2/t p
Yes (n=909) No (n=745)
n(%) or M±SE n(%) or M±SE
General characteristics Gender Female 432(62.0) 270(38.0) 17.29 <.001
male 477(50.7) 475(49.3)
Age 19~39 30(55.5) 28(44.5) 4.17 .006
40~59 245(52.0) 229(48.0)
60~79 482(54.4) 406(45.6)
≥80 152(66.9) 82(33.1)
Education ≤Elementary school 397(62.7) 238(37.3) 9.80 <.001
Middle school 188(58.8) 140(41.2)
High school 218(51.0) 230(49.0)
≥College 106(42.1) 137(57.9)
Household income Low 279(67.4) 147(32.6) 16.10 <.001
Middle-low 262(60.9) 159(39.1)
Middle-high 195(51.0) 201(49.0)
High 173(43.2) 238(56.8)
Residence Metropolitan cities 378(52.1) 348(47.9) 3.01 .050
Middle and small cities 266(60.3) 175(39.7)
Rural area 265(55.8) 222(44.2)
Household type Single 269(64.1) 150(35.9) 13.27 <.001
Not single 640(52.8) 595(47.2)
Intrapersonal factors Degree of disability Mild 577(55.0) 507(45.0) 1.88 .170
Severe 332(58.7) 238(41.3)
Subjective health status 1-5 3.57±0.03 3.29±0.03 6.36 <.001
ADL Dependent 320(71.5) 145(28.5) 48.27 <.001
Independent 589(50.8) 600(49.2)
IADL Dependent 416(66.3) 227(33.7) 34.41 <.001
Independent 493(50.1) 518(49.9)
Difficulty in getting information about COVID-19 Yes 584(83.1) 119(16.9) 333.74 <.001
No 325(33.4) 626(66.6)
Difficulty in obtaining and using equipment related to COVID-19 Yes 590(81.0) 149(19.0) 306.54 <.001
No 319(34.1) 596(65.9)
Interpersonal factors Satisfaction with family 1-4 2.97±0.03 3.22±0.02 -7.49 <.001
Satisfaction with the number of friends 1-4 2.63±0.03 2.99±0.03 -9.85 <.001
Leisure Yes 830(54.5) 715(45.5) 12.19 <.001
No 79(73.5) 30(26.5)
Discrimination Yes 344(62.9) 218(37.1) 13.63 <.001
No 565(52.4) 527(47.6)
Community/policy factor Support related to COVID-19 from national and local governments Yes 420(60.9) 253(39.1) 10.35 0.001
No 489(52.0) 492(48.0)

Unweighted N(weighted %); ADL=Activities of daily living; IADL=Instrumental activities of daily living

Higher scores indicate worse subjective health status; Higher scores indicate greater satisfaction

Table 3.
The Results of Complex Sample Logistic Regression (N=1,654)
Variables Categories Emotional Distress due to COVID-19
B SE OR 95% CI p
Covariates Gender Male (ref. Female) -0.32 .15 0.73 0.54-0.98 .036
Age 19~39 0.69 .45 1.99 0.83-4.76 .123
40~59 0.38 .28 1.46 0.85-2.52 .171
60~79(ref. ≥80) 0.09 .22 1.10 0.72-1.68 .665
Education ≤Elementary school 0.21 .25 1.23 0.75-2.02 .407
Middle school 0.35 .26 1.42 0.86-2.36 .170
High school (ref. ≥College) 0.18 .22 1.19 0.77-1.84 .431
Household income Low 0.43 .22 1.54 0.99-2.39 .053
Middle-low 0.38 .21 1.46 0.97-2.19 .068
Middle-high (ref. high) 0.20 .19 1.22 0.85-1.77 .278
Residence Metropolitan cities 0.15 .16 1.16 0.85-1.59 .347
Middle and small cities (ref. rural area) 0.58 .17 1.78 1.27-2.50 .001
Household type Single (ref. Not single) -0.04 .17 0.96 0.68-1.35 .817
Intrapersonal factors Degree of disability Severe (ref. Mild) -0.24 .15 0.79 0.59-1.06 .116
Subjective health status 1-5 0.07 .09 1.08 0.90-1.28 .426
ADL Dependent (ref. Independent) 0.46 .23 1.58 1.01-2.47 .047
IADL Dependent (ref. Independent) 0.17 .20 1.18 0.80-1.74 .394
Difficulty in getting information about COVID-19 Yes (ref. No) 1.33 .23 3.79 2.43-5.89 <.001
Difficulty in obtaining and using equipment related to COVID-19 Yes (ref. No) 1.10 .22 3.02 1.97-4.62 <.001
Interpersonal factors Satisfaction with family 1-4 -0.23 .12 0.64 0.63-1.00 .054
Satisfaction with the number of friends 1-4 -0.44 .12 0.64 0.51-0.81 <.001
Leisure Yes (ref. No) -0.45 .27 0.64 0.38-1.08 .092
Discrimination Yes (ref. No) 0.23 .15 1.26 0.95-1.68 .115
Community/Policy factor Support related to COVID-19 from national and local governments Yes (ref. No) 0.38 .14 1.47 1.11-1.94 .008
Cox & Snell .31
Nagelkerke R2 .41
McFadden .27

CI=Confidence interval; OR=Odds ratio; ref.=Reference group; ADL=Activities of daily living; IADL=Instrumental activities of daily living

Higher scores indicate worse subjective health status; Higher scores indicate greater satisfaction

Table 4.
Frequency of Support related to COVID-19 from National and Local Governments (N=673)
Item n (%)
(1) Emergency care for social welfare facilities and special schools 20(3.0)
(2) Special benefits for personal assistance services  30(4.5)
(3) Food and supplies delivery 62(9.2)
(4) Infection protection supplies 642(95.4)
(5) Support for online lecture learning aids 22(3.3)
(6) Others 23(3.4)

Unweighted n (unweighted %); Multiple choices available;

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      Current Status and Associated Factors of Emotional Distress Due to COVID-19 Among People with Physical Disabilities Living in the Community: Secondary Data Analysis using the 2020 National Survey of Disabled Persons
      Image Image
      Figure 1. Research Framework of This Study
      Figure 2. Participants Selection Flowchart
      Current Status and Associated Factors of Emotional Distress Due to COVID-19 Among People with Physical Disabilities Living in the Community: Secondary Data Analysis using the 2020 National Survey of Disabled Persons
      Variables Categories(Range) n(%) or M±SE
      General characteristics Gender Female 702(44.2)
      Male 952(55.8)
      Age 19~39 58(4.1)
      40~59 474(29.2)
      60~79 888(51.3)
      ≥80 234(15.4)
      Education ≤Elementary school 635(37.6)
      Middle school 328(20.1)
      High school 448(27.7)
      ≥College 243(14.6)
      Household income Low 426(26.3)
      Middle-low 421(23.7)
      Middle-high 396(24.7)
      High 411(25.4)
      Residence Metropolitan cities 726(37.7)
      Middle and small cities 441(28.1)
      Rural area 487(34.2)
      Household type Single 419(25.6)
      Not single 1235(74.4)
      Intrapersonal factors Degree of disability Mild 1084(80.5)
      Severe 570(19.5)
      Subjective health status 1-5 3.45±0.02
      ADL Dependent 465(23.7)
      Independent 1189(76.3)
      IADL Dependent 643(34.3)
      Independent 1011(65.7)
      Difficulty in getting information about COVID-19 Yes 703(44.9)
      No 951(55.1)
      Difficulty in obtaining and using equipment related to COVID-19 Yes 739(46.0)
      No 915(54.0)
      Interpersonal factors Satisfaction with family 1-4 3.08±0.02
      Satisfaction with the number of friends 1-4 2.79±0.02
      Leisure Yes 1545(93.8)
      No 109(6.2)
      Discrimination Yes 562(31.1)
      No 1092(68.9)
      Community/Policy factor Support related to COVID-19 from national and local governments Yes 673(41.2)
      No 981(58.8)
      Emotional distress due to COVID-19 Yes 909(55.7)
      No 745(44.3)
      Variables Categories (Range) Emotional distress due to COVID-19 Rao-Scott χ2/t p
      Yes (n=909) No (n=745)
      n(%) or M±SE n(%) or M±SE
      General characteristics Gender Female 432(62.0) 270(38.0) 17.29 <.001
      male 477(50.7) 475(49.3)
      Age 19~39 30(55.5) 28(44.5) 4.17 .006
      40~59 245(52.0) 229(48.0)
      60~79 482(54.4) 406(45.6)
      ≥80 152(66.9) 82(33.1)
      Education ≤Elementary school 397(62.7) 238(37.3) 9.80 <.001
      Middle school 188(58.8) 140(41.2)
      High school 218(51.0) 230(49.0)
      ≥College 106(42.1) 137(57.9)
      Household income Low 279(67.4) 147(32.6) 16.10 <.001
      Middle-low 262(60.9) 159(39.1)
      Middle-high 195(51.0) 201(49.0)
      High 173(43.2) 238(56.8)
      Residence Metropolitan cities 378(52.1) 348(47.9) 3.01 .050
      Middle and small cities 266(60.3) 175(39.7)
      Rural area 265(55.8) 222(44.2)
      Household type Single 269(64.1) 150(35.9) 13.27 <.001
      Not single 640(52.8) 595(47.2)
      Intrapersonal factors Degree of disability Mild 577(55.0) 507(45.0) 1.88 .170
      Severe 332(58.7) 238(41.3)
      Subjective health status 1-5 3.57±0.03 3.29±0.03 6.36 <.001
      ADL Dependent 320(71.5) 145(28.5) 48.27 <.001
      Independent 589(50.8) 600(49.2)
      IADL Dependent 416(66.3) 227(33.7) 34.41 <.001
      Independent 493(50.1) 518(49.9)
      Difficulty in getting information about COVID-19 Yes 584(83.1) 119(16.9) 333.74 <.001
      No 325(33.4) 626(66.6)
      Difficulty in obtaining and using equipment related to COVID-19 Yes 590(81.0) 149(19.0) 306.54 <.001
      No 319(34.1) 596(65.9)
      Interpersonal factors Satisfaction with family 1-4 2.97±0.03 3.22±0.02 -7.49 <.001
      Satisfaction with the number of friends 1-4 2.63±0.03 2.99±0.03 -9.85 <.001
      Leisure Yes 830(54.5) 715(45.5) 12.19 <.001
      No 79(73.5) 30(26.5)
      Discrimination Yes 344(62.9) 218(37.1) 13.63 <.001
      No 565(52.4) 527(47.6)
      Community/policy factor Support related to COVID-19 from national and local governments Yes 420(60.9) 253(39.1) 10.35 0.001
      No 489(52.0) 492(48.0)
      Variables Categories Emotional Distress due to COVID-19
      B SE OR 95% CI p
      Covariates Gender Male (ref. Female) -0.32 .15 0.73 0.54-0.98 .036
      Age 19~39 0.69 .45 1.99 0.83-4.76 .123
      40~59 0.38 .28 1.46 0.85-2.52 .171
      60~79(ref. ≥80) 0.09 .22 1.10 0.72-1.68 .665
      Education ≤Elementary school 0.21 .25 1.23 0.75-2.02 .407
      Middle school 0.35 .26 1.42 0.86-2.36 .170
      High school (ref. ≥College) 0.18 .22 1.19 0.77-1.84 .431
      Household income Low 0.43 .22 1.54 0.99-2.39 .053
      Middle-low 0.38 .21 1.46 0.97-2.19 .068
      Middle-high (ref. high) 0.20 .19 1.22 0.85-1.77 .278
      Residence Metropolitan cities 0.15 .16 1.16 0.85-1.59 .347
      Middle and small cities (ref. rural area) 0.58 .17 1.78 1.27-2.50 .001
      Household type Single (ref. Not single) -0.04 .17 0.96 0.68-1.35 .817
      Intrapersonal factors Degree of disability Severe (ref. Mild) -0.24 .15 0.79 0.59-1.06 .116
      Subjective health status 1-5 0.07 .09 1.08 0.90-1.28 .426
      ADL Dependent (ref. Independent) 0.46 .23 1.58 1.01-2.47 .047
      IADL Dependent (ref. Independent) 0.17 .20 1.18 0.80-1.74 .394
      Difficulty in getting information about COVID-19 Yes (ref. No) 1.33 .23 3.79 2.43-5.89 <.001
      Difficulty in obtaining and using equipment related to COVID-19 Yes (ref. No) 1.10 .22 3.02 1.97-4.62 <.001
      Interpersonal factors Satisfaction with family 1-4 -0.23 .12 0.64 0.63-1.00 .054
      Satisfaction with the number of friends 1-4 -0.44 .12 0.64 0.51-0.81 <.001
      Leisure Yes (ref. No) -0.45 .27 0.64 0.38-1.08 .092
      Discrimination Yes (ref. No) 0.23 .15 1.26 0.95-1.68 .115
      Community/Policy factor Support related to COVID-19 from national and local governments Yes (ref. No) 0.38 .14 1.47 1.11-1.94 .008
      Cox & Snell .31
      Nagelkerke R2 .41
      McFadden .27
      Item n (%)
      (1) Emergency care for social welfare facilities and special schools 20(3.0)
      (2) Special benefits for personal assistance services  30(4.5)
      (3) Food and supplies delivery 62(9.2)
      (4) Infection protection supplies 642(95.4)
      (5) Support for online lecture learning aids 22(3.3)
      (6) Others 23(3.4)
      Table 1. Characteristics of Study Participants (N=1,654)

      Unweighted N(weighted %); ADL=Activities of daily living; IADL=Instrumental activities of daily living

      Higher scores indicate worse subjective health status; Higher scores indicate greater satisfaction

      Table 2. Differences in Emotional Distress due to COVID-19 according to Variables (N=1,654)

      Unweighted N(weighted %); ADL=Activities of daily living; IADL=Instrumental activities of daily living

      Higher scores indicate worse subjective health status; Higher scores indicate greater satisfaction

      Table 3. The Results of Complex Sample Logistic Regression (N=1,654)

      CI=Confidence interval; OR=Odds ratio; ref.=Reference group; ADL=Activities of daily living; IADL=Instrumental activities of daily living

      Higher scores indicate worse subjective health status; Higher scores indicate greater satisfaction

      Table 4. Frequency of Support related to COVID-19 from National and Local Governments (N=673)

      Unweighted n (unweighted %); Multiple choices available;


      RCPHN : Research in Community and Public Health Nursing
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