Disparities and Factors Associated with Coronavirus Disease-2019-Related Public Stigma: A Cross-Sectional Study in Thailand
by
, , and
Chidchanok Ruengorn
1,2,†, 
Ratanaporn Awiphan
1,2,
Chabaphai Phosuya
1,2,
Yongyuth Ruanta
1,2,
Kednapa Thavorn
2,3,4,5,
Nahathai Wongpakaran
6
,
Tinakon Wongpakaran
6
and
Surapon Nochaiwong
1,2,*,† 1
Department of Pharmaceutical Care, Faculty of Pharmacy, Chiang Mai University, Chiang Mai 50200, Thailand
2
Pharmacoepidemiology and Statistics Research Center (PESRC), Chiang Mai University, Chiang Mai 50200, Thailand
3
Ottawa Hospital Research Institute, Ottawa Hospital, Ottawa, ON K1H 8L6, Canada
4
ICES Ottawa, Ottawa, ON K1Y 4E9, Canada
5
School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, ON K1G 5Z3, Canada
6
Department of Psychiatry, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Int. J. Environ. Res. Public Health 2022, 19(11), 6436; https://doi.org/10.3390/ijerph19116436
Submission received: 19 April 2022
/
Revised: 16 May 2022
/
Accepted: 24 May 2022
/
Published: 25 May 2022
(This article belongs to the Collection COVID-19 Research)
Abstract
:Coronavirus disease 2019 (COVID-19)-related public stigma is a major challenge, with scarce available evidence. This study aimed to determine the disparities and factors associated with COVID-19-related public stigma in the Thai population. We conducted a cross-sectional study involving a voluntary online survey in Thailand from 21 April 2020 to 4 May 2020. We invited 4004 participants to complete a series of questionnaires, including the validated COVID-19 public stigma scale and questions on relevant COVID-19-related psychosocial issues. Multinomial logistic regression was performed to investigate the factors associated with COVID-19-related public stigma. The prevalence of COVID-19-related public stigma was 24.2% (95% confidence interval [CI], 22.2–26.2) for no/minimal, 35.5% (95% CI, 33.4–37.6) for moderate, and 40.3% (95% CI, 38.2–42.4) for high. We observed disparities in the prevalence of COVID-19-related public stigma according to participant characteristics and psychosocial factors. Using the no/minimal group as a reference group, the six predominant risk factors significantly associated with a moderate and high degree of COVID-19-related public stigma were middle-aged or older adults, male, divorced/widowed/separated, current quarantine status, moderate/severe fear of COVID-19, and medium/high perceived risk of COVID-19. Additional risk factors significantly related to a high degree of COVID-19-related public stigma were religion (Buddhist), region of residence (non-capital city), and exposure to COVID-19-related information. Disparities in COVID-19-related public stigma due to sociodemographic and psychosocial issues are frequent in the Thai population. To reduce public stigmatization, early identification of vulnerable groups and the development of tailored mitigation strategies should be implemented during the pandemic.
1. Introduction
The incidence of psychosomatic illness has increased since the emergence of coronavirus disease 2019 (COVID-19). These conditions are expected natural psychological responses to unpredictable, fast-spreading infectious diseases similar to conditions experienced during prior outbreaks such as SAR-CoV or MER-CoV [1]. Measures to contain the spread of the virus, such as lockdowns, home confinement strategies, restriction of travelling, and misinformation obtained from online social networking sites, have been shown to be detrimental [1,2].
COVID-19 has caused universal awareness, anxiety, and distress, partly due to fear of infection, leading to the so-called COVID-19 effect [3,4]. The COVID-19 effect provokes disease-associated social stigma, xenophobia, and discrimination against people who are perceived to have been in contact with the virus or those with certain ethnic backgrounds [3]. Social stigma or public stigma relating to infectious diseases has long been acknowledged in the past, such as that for HIV, hepatitis C virus, tuberculosis, and Zika, and is now acknowledged amid the COVID-19 pandemic [5]. Public stigma usually creates discriminatory behaviors, such as isolation, refusal to receive services, harassment, and bullying. People who are victims of social stigma can develop social avoidance, denial of healthcare, and perhaps even be in danger of violence [1]. The incidence of hate crime towards specific ethnicities (i.e., Asians) has been reported in the United States and worldwide. In addition, stigma toward COVID-19 may lead to adverse mental health outcomes, including suicidal behavior [6,7].
To date, few studies have reported the prevalence and factors associated with COVID-19-related public stigma. None of the existing studies have focused on public stigma in Thailand. While the pandemic is still ongoing, understanding COVID-19-related public stigma and its related factors can help define the target population prone to social stigma and develop tailored mitigation strategies. Therefore, we conducted this study to determine the prevalence of, and factors associated, with COVID-19-related public stigma in the Thai population.
2. Materials and Methods
2.1. Study Design and Participants
This was a cross-sectional analytical study based on the Health Outcomes and Mental Health Care Evaluation Survey, under the Pandemic Situation of COVID-19 (HOME-COVID-19). The details of the protocol have been published elsewhere [8]. In brief, an open, online, voluntary survey encompassing a set of questionnaires was sent via the SurveyMonkey® platform, which limits to one-time participation per unique Internet Protocol address. The samples were invited by a convenience and snowball sampling strategy from all the regions in Thailand through various social media networks including public websites, Facebook, LINE, Twitter, and Instagram. Eligible participants included (i) Thai citizens aged ≥18 years at the date of the survey, (ii) permanent residents or non-residents with work permits, (iii) those who could read and communicate in the Thai language, and (iv) those who could access the Internet. We excluded incomplete surveys and surveys that took <2 min or >60 min to complete. The current analysis was restricted to only wave I of information from 21 April 2020 to 4 May 2020 (during the national government’s protocols under lockdown in Thailand).
Under the HOME-COVID-19, this current study was approved by the Committee of Research Ethics of the Faculty of Public Health (ET010/2020) and the Faculty of Pharmacy (23/2563), Chiang Mai University. All participants provided written informed consent for the first page of the questionnaire. This study was in line with the Strengthening the Reporting of Observational Studies in Epidemiology Statement [9] and Improving the Quality of Web Surveys: The Checklist for Reporting Results of Internet E-Surveys [10].
2.2. Sample Size
The sample sizes for both prevalence and factors related to public stigma in the Thai population were estimated using (i) the overall mean ± standard deviation (SD) of COVID-19-related public stigma (based on the validated COVID-19 Public Stigma Scale (COVIDSS)) of 24.2 ± 7.6 [11], specified type I error at 0.05, and d equal to 0.5, a total sample size of 891; and (ii) linear multiple regression, R2 deviation from zero with a small effect size of 0.02, type I error of 0.05, 90% of power, and anticipated total predictors equal to 15, with a sample size needed of 1192 [12]. The sample size of our survey met both requirements and was sufficient to address the research questions.
2.3. Assessment Tools and Potential Risk Factors
Participants were asked to complete a set of questionnaires regarding COVID-19-related public stigma and relevant psychosocial issues as follows:
- Public stigma: COVID-PSS comprises ten items with three factors (stereotypes, prejudice, fear), and a possible score range of 10-50 points. The COVID-PSS revealed acceptable psychometric properties in the Thai population, with Cronbach’s α of 0.85. The degree of public stigma was established and classified as no/minimal (≤18 points), moderate (19–25 points), or high (≥26 points) [11].
- Perceived social support: The Multidimensional Scale of Perceived Social Support (MSPSS-12) consists of 12 items that measure individual perceptions of external social support. This scale has excellent internal consistency, with a Cronbach’s α of 0.92 [13]. Perceived social support was categorized as low (12–35 points), moderate (36–60 points), or high (61–84 points).
- Resilient coping: The Brief Resilient Coping Scale (BRCS) consists of four items to capture tendencies to cope with stress in a highly adaptive manner. The BRCS revealed satisfactory reliability (Cronbach’s α = 0.80) [8]. For scale interpretation, BRCS scores was classified as low- (≤13 points), medium- (14–16 points), or high (≥17 points) resilience copers [14].
- Fear of COVID-19 and perceived risk of COVID-19 infection: A numerical rating scale (NRS) of 0–10 points was used to measure the degree of fear or perceived risk of COVID-19 infection. The degree of fear or perceived risk was classified as no/minimal fear or low perceived risk (0–3 points), moderate fear or medium perceived risk (4–6 points), and severe fear or high perceived risk (7–10 points).
- A set of potential risk factors for public stigma, including sociodemographic characteristics (age, sexual identity, marital status, educational level, occupation, religion, region of residence, living status, personal income, reimbursement scheme, history of mental illness, chronic non-communicable diseases (NCDs)), and issues-related to the COVID-19 pandemic (economic burden (income loss, financial problems), duration of exposure to COVID-19-related information, confirmed cases in the community, quarantine status, and working from home status).
2.4. Statistical Analyses
All analyses were performed using Stata 14.0 (StataCorp, LP, College Station, TX, USA). Two-tailed tests were conducted with a type I error rate of 0.05. Respondents with missing data or incomplete data were excluded from the analysis. Descriptive statistics are expressed as frequency and percentage or mean ± SD, with a range (min-max). We categorized COVID-19-related public stigma into three groups according to total scores (no/minimal, moderate, and high degrees of stigma). Baseline participant characteristics, according to the degree of public stigma, were assessed using analysis of covariance for continuous data and Fisher’s exact test for categorical data. We applied survey weights to all analyses to ensure that our results represented the national population and rate of Internet use based on the National Statistic Office of the Thai Ministry of Information and Communication Technology.
We estimated the prevalence rate of COVID-19-related public stigma with 95% confidence intervals (CIs) and assessed the variation in these rates by participant characteristics. Using a trend test analysis, non-overlapping 95% CIs (p for trend <0.05) indicated a statistical difference in the prevalence rates across participant characteristic strata. We applied a two-stage multinomial logistic regression approach to determine factors associated with the degree of COVID-19-related public stigma (using no/minimal as a reference group). In the first stage, the crude association between participant characteristics and the degree of public stigma (moderate or high) was analyzed using univariable multinomial logistic regression models to identify candidate risk factors. Next, candidate risk factors with a p-value < 0.200 were included in the multivariable multinomial logistic regression models using the stepwise backward method. Variance inflation factors were used to identify multicollinearity in the final model. Moreover, an ancillary analysis was performed to confirm the robustness of the main analysis using multivariable linear regression to explore the linear relationship between the potential risk factors and COVID-PSS—public stigma score. The effect estimates of the risk factor models are expressed as odds ratios (ORs) or beta coefficients with 95% CIs.
3. Results
3.1. Overview of Participant Characteristics
A total of 4997 people were identified through an online survey invitation. Of those, 4381 (87.7%) were willing to participate in the survey, and 4004 participants met the eligibility criteria and completed a set of mental health and psychosocial questions (completeness rate of 92.6%, Figure 1). Participant characteristics are described in Supplementary Table S1. Most participants were female (65.4%), with a mean age of 29.1 ± 10.8 years (range 18–79). Most participants resided in a non-capital city or its environs (64.4%). Most participants had moderate/high perceived social support and were medium/high resilient copers, whereas most participants reported having moderate/severe fear of COVID-19 and medium/high perceived risk of COVID-19 infection.
3.2. Prevalence and Disparities of COVID-19-Related Public Stigma
The overall mean COVID-PSS—public stigma score was 24.2 ± 7.6 (range 10–50). With respect to the degree of COVID-19-related public stigma, the unadjusted prevalence estimate was 24.2% (95% CI, 22.2–26.2) for no/minimal, 35.5% (95% CI, 33.4–37.6) for moderate, and 40.3% (95% CI, 38.2–42.4) for high. Remarkably, statistical differences in the prevalence rates across participants with a high degree of COVID-19-related public stigma were observed, particularly in participants who had a high perceived risk of COVID-19 infection (82.3%; 95% CI, 79.1–85.2), followed by participants aged ≥51 years (66.8%; 95% CI, 58.0–74.5) and participants who had a severe fear of COVID-19 (63.0%; 95% CI, 60.0–65.9) (Table 1). Moreover, participants’ age, sexual identity, marital status, religion, region of residence, reimbursement scheme, history of NCDs, information exposure during the COVID-19 pandemic, confirmed cases in the community, quarantine status, perceived social support, fear of COVID-19, and perceived risk of COVID-19 infection were associated with prevalence across the degree of COVID-19-related public stigma (p for trend <0.05, Table 1).
3.3. Risk Factors Associated with COVID-19-Related Public Stigma
With respect to participant characteristics (using no/minimal public stigma as a reference group), the univariable multinomial regression identified 16 candidate risk factors with p-value < 0.200 (Table 2). Subsequently, the final model based on multivariable multinomial regression models revealed six independent significant risk factors of moderate degree of COVID-19-related public stigma: (i) ages 31–50 years (adjusted OR, 1.59; 95% CI, 1.08–2.34) and ≥51 years (adjusted OR, 4.34; 95% CI, 1.49–12.64), (ii) male sex (adjusted OR, 1.68; 95% CI, 1.21–2.33), (iii) divorced/widowed/separated (adjusted OR, 3.88; 95% CI, 1.42–10.55), (iv) current quarantine status (adjusted OR, 2.08; 95% CI, 1.31–3.33), (v) moderate fear of COVID-19 (adjusted OR, 3.70; 95% CI, 1.95–7.03) and severe fear of COVID-19 (adjusted OR, 6.24; 95% CI, 3.16–12.36), and (vi) medium perceived risk of COVID-19 infection (adjusted OR, 7.78; 95% CI, 5.61–10.79) and high perceived risk of COVID-19 infection (adjusted OR, 41.94; 95% CI, 17.56–100.15) (Table 2).
Meanwhile, the multivariable multinomial regression models recognized nine independent significant risk factors for high degree COVID-19-related public stigma: (i) aged 31–50 years (adjusted OR, 2.22; 95% CI, 1.36–3.62) and ≥51 years (adjusted OR, 10.31; 95% CI, 3.13–34.01), (ii) male sex (adjusted OR, 2.35; 95% CI, 1.58–3.49), (iii) marital status—married/domestic partnership (adjusted OR, 1.97; 95% CI, 1.07–3.64) and divorced/widowed/separated (adjusted OR, 3.69; 95% CI, 1.00–13.60), (iv) religion—Buddhism (adjusted OR, 2.11; 95% CI, 1.22–3.63), (v) non-capital city and its environs (adjusted OR, 1.45; 95% CI, 1.08–1.95), (vi) exposure to COVID-19-related information 1–2 h/day (adjusted OR, 1.52; 95% CI, 1.05–2.21), (vii) current quarantine status (adjusted OR, 1.75; 95% CI, 1.03–2.97), (viii) moderate fear of COVID-19 (adjusted OR, 20.71; 95% CI, 4.11–104.19) and severe fear of COVID-19 (adjusted OR, 111.70; 95% CI, 21.90–569.63), and (ix) medium perceived risk of COVID-19 infection (adjusted OR, 60.15; 95% CI, 23.80–152.00) and high perceived risk of COVID-19 infection (adjusted OR, 2245.43; 95% CI, 667.25–7556.23) (Table 2).
With respect to the ancillary analysis, the findings showed consistent results for the set of factors associated with COVID-19-related public stigma (R2 = 0.58), except for exposure to COVID-19-related information, which was not significant. On the other hand, resilient coping perception has become a significant protective factor for COVID-19-related public stigma, with a small effect size (beta coefficient of −0.76; 95% CI, −1.46 to −0.05; p = 0.036 for medium resilient copers; −0.82, 95% CI, −1.51 to −0.14; p = 0.019 for high resilient copers; Supplementary Table S2).
4. Discussion
Our findings highlight the prevalence and disparities of COVID-19-related public stigma in the general Thai population. We found that COVID-19-related public stigma was common during the pandemic in Thailand. Critically, the estimated prevalence of a high degree of COVID-19-related public stigma was frequent at 40.3% (95% CI, 38.2–42.4); this rate was highly variable by participant characteristics and psychosocial issues regarding the pandemic. Moreover, our risks set findings for the development of a medium/high degree of COVID-19-related public stigma can provide information on the target-specific population and minimize public stigmatization in public health settings.
Few studies have addressed COVID-19-related public stigma in the general population owing to the lack of a validated tool. These studies have shown that COVID-19-related public stigma is a common phenomenon in several countries [15,16,17,18,19,20]. Similar to our study, the prevalence of moderate and high degrees of COVID-19-related public stigma accounts for more than half of the surveyed population in many countries. Furthermore, our findings underscore that participant characteristics as well as psychosocial issues during the pandemic are significantly associated with the degree of COVID-19-related public stigma.
Collectively, based on common risk factors, our findings revealed that middle-aged adults or older (31–50, ≥51 years) had a higher risk of being at a moderate/high degree of COVID-19-related public stigma than young adults. Not surprisingly, the older population, particularly in advanced age and with multi-morbidities, is at risk of a severe and critical stage if infected with COVID-19, leading to greater awareness of infection. Males have also been reported to have more severe COVID-19 [21], which may be recognized as at risk of experiencing moderate/high COVID-19-related public stigma than others. Interestingly, the explanation may be related to ideas of masculinity, in which norms are social rules that expect men to be strong, and may invoke behaviors showing responsibility towards protecting their family and community [22]. According to previous reports [23,24], we found that cohabitants are more aware of COVID-19 infection due to fear of infecting their partners. Additionally, married people, particularly healthcare workers, illustrated more personalized stigma and had concerns about public attitudes [24]. People who experienced the current quarantine status certainly perceived a higher risk of COVID-19 infection and had a higher stigma score in our observation. Some studies have shown that quarantine cases are prone to self-stigma and stigmatization by society [23]. In addition, a study involving quarantined healthcare workers also reported that guilt towards family members and friends leads to avoiding contact with neighbors and the community [25]. Finally, both perceived fear and risk of COVID-19 infection were recognized as strong factors contributing to COVID-19-related public stigma in our study. Indeed, the feeling of fear and subsequently the perceived risk of a newly emerging infectious disease usually arises from the uncertain and unpredictable course of the disease. Technology, including the internet and social media, creates “infodemics” spreading the news of COVID-19 cases, mortality, and its communicability. This can accelerate more fear and perceived dangerousness to people. Moreover, stigma from perceived risk can also be mediated by fear of COVID-19.
Apart from the common factors, some unique variables, including religion—Buddhism, living in a non-capital city, and exposure to COVID-19-related information, are associated only with a high degree of COVID-19-related public stigma. In Thailand, Buddhism is the religion of most of the population (93.5%), followed by Muslims (5.4%), and Christians and others (1.1%) [26]. Buddhists are associated with the doctrine of cultivating compassion to attenuate prejudiced attitudes towards other social groups [27]. In the case of the COVID-19 pandemic, comparison with the irreligious population may reflect aspects including liberality and acceptance of the behaviors of others, including mistakes or errors. However, some hidden residual factors, such as borderline personality disorder, narcissism, or carelessness towards religion, predominantly in the younger population, which are associated with lower stigmatization [28,29], were not investigated in our study. Therefore, this finding requires further confirmation. For residential areas, we postulated that people living in the non-capital area had a higher degree of COVID-19-related public stigma because of their fear and perceived risk of COVID-19 infection spreading from the capital city, because most cases in Thailand at the time of data collection were based in the capital city and its environs. Theoretically, media exposure has been suggested as a potential factor for perceived stigmatization among people at a high risk of contagion [30]. In this case, we can determine that media images and influences may lead to prejudice and discrimination related to COVID-19, resulting in violence against some ethnic groups, such as Asian people in the US and globally.
4.1. Strengths and Limitations
To our knowledge, this is the first study to report on the prevalence of COVID-19-related public stigma in Thailand. This study was based on a nationwide survey with a large sample size. Unlike previous studies, we used the validated COVID-PSS to measure COVID-19-related public stigma among the Thai population [11]. However, our results should be used with consideration of some limitations. First, we used Wave I of the HOME-COVID-19, representing only the early phase of the pandemic when circumstances could be different from other periods, for example, due to the availability of the COVID-vaccine. We also lacked information regarding knowledge of COVID-19 infection, in which misinformation or lack of knowledge may generate more fear and anxiety about the disease and increase stigma. Although stigma changes over time and context, the results of this study are believed to be beneficial for future emerging infectious diseases. Second, our findings were based on an open online survey; therefore, information bias should be considered. In addition, it may be generalized only to those with access to the Internet. Third, fear of COVID-19 and perceived risk of COVID-19 infection was assessed via a non-validated NRS of 0–10 points questionnaire which may limit comparison to other settings, or international comparisons with respect to these issues. However, NRS—unidimensional assessment is practical, reasonable, and applicable for capturing participants’ feelings or opinions via a public survey. Fourth, despite an ancillary analysis confirming risk factors in line with the main analysis, uncertainty with respect to exposure to COVID-19-related information, resilient coping perception, and the risk of COVID-19-related public stigma need to be confirmed in further studies. Fifth, further associations between public stigma and adverse mental health (i.e., anxiety, stress, and depression) are warranted to address public health concerns. Lastly, the longer-term effect of stigma research needs to be studied, because our findings reflected only the short-term effects, and the impact of stigma may change as the pandemic evolves.
4.2. Implications for Public and Future Research
Given the high burden of mental health and psychosocial issues during the pandemic, it is crucial to minimize COVID-19-related public stigma due to the negative consequences of stigma, including an unwillingness to disclose COVID-19 infection or to test and seek treatment. Recently, a randomized trial in the general United States population by [31] suggested that video-based interventions involving reliable information on COVID-19 prevention strategies, video encouraging digital social activity, and video sensitizing to COVID-19-related stigma are effective in reducing COVID-19-related public stigma. However, its utility could be limited by its generalizability to other populations and cross-cultural adaptation to larger public health effects. To help the target population and supplement the previous intervention trial, our findings support proactive mental health surveillance by identifying the person who may be vulnerable or at risk of public stigmatization middle-aged adults or older, male sex, married/domestic partnership, divorced/widowed/separated, Buddhist, living in the non-capital city, current quarantine status, high perceived fear or risk of COVID-19 infection. To promote mental health well-being, multimodal mitigation strategies involving public health education and knowledge, programs for empowering and supporting vulnerable populations, and anti-stigma policies enforced in legal legislation should be promptly implemented during the pandemic.
5. Conclusions
COVID-19-related public stigma is highly prevalent and varies among the Thai populations. The results of this study highlight the disparities in the prevalence of COVID-19-related public stigma according to sociodemographic and psychosocial issues. Our study also shows the possibility of identifying vulnerable groups and participants who are at risk of stigma during the pandemic, which should be targeted by strategies aimed at mitigating the impact of public stigma on health.
Supplementary Materials
The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijerph19116436/s1, Table S1: Participants Characteristics According to the Degree of Stigma towards COVID-19 Infection in Thailand; Table S2: Linear Regression Model Results of Factors Associated with Stigma towards COVID-19 Infection (n = 4004).
Author Contributions
Conceptualization, C.R., N.W., T.W. and S.N.; methodology, C.R., K.T. and S.N.; software; C.R. and S.N.; data curation, R.A., C.P. and Y.R.; validation, R.A., C.P. and Y.R.; formal analysis, C.R. and S.N.; investigation, all authors; resources, C.R. and S.N.; writing—original draft preparation, C.R. and S.N.; writing—review and editing, N.W., T.W. and K.T.; supervision, C.R. and S.N.; project administration, C.R. and S.N.; funding acquisition, S.N. All authors have read and agreed to the published version of the manuscript.
Funding
This research was supported by a grant from the Pharmacoepidemiology and Statistics Research Center (PESRC) through the Chiang Mai University (ORA2564/635).
Institutional Review Board Statement
The study was conducted in accordance with the Declaration of Helsinki. Approval for the conduct of the HOME-COVID-19 was obtained from the Committee of Research Ethics of the Faculty of Public Health (ET010/2020) and the Faculty of Pharma-cy (23/2563), Chiang Mai University.
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
Data will be shared upon reasonable request and with permission according to the Health Outcomes and Mental Health Care Evaluation Survey Research Group (HOME-Survey) data release policy.
Acknowledgments
The authors thank the research assistances and all staff of Pharmacoepidemiology and Statistics Research Center (PESRC), Chiang Mai, Thailand. Particular thanks are given to the study participants for their contribution to the project.
Conflicts of Interest
The authors declare no conflict of interest.
References
- Dubey, S.; Biswas, P.; Ghosh, R.; Chatterjee, S.; Dubey, M.J.; Chatterjee, S.; Lahiri, D.; Lavie, C.J. Psychosocial impact of COVID-19. Diabetes Metab. Syndr. 2020, 14, 779–788. [Google Scholar] [CrossRef] [PubMed]
- Ransing, R.; Ramalho, R.; Orsolini, L.; Adiukwu, F.; Gonzalez-Diaz, J.M.; Larnaout, A.; Pinto da Costa, M.; Grandinetti, P.; Bytyçi, D.G.; Shalbafan, M.; et al. Can COVID-19 related mental health issues be measured? Brain Behav. Immun. 2020, 88, 32–34. [Google Scholar] [CrossRef] [PubMed]
- International Federation of Red Cross and Red Crescent Societies; UNICEF. A Guide to Preventing and Addressing Social Stigma; International Federation of Red Cross and Red Crescent Societies: Geneva, Switzerland, 2020. [Google Scholar]
- Kaufman, K.R.; Petkova, E.; Bhui, K.S.; Schulze, T.G. A global needs assessment in times of a global crisis: World psychiatry response to the COVID-19 pandemic. BJPsych Open. 2020, 6, e48. [Google Scholar] [CrossRef]
- Baldassarre, A.; Giorgi, G.; Alessio, F.; Lulli, L.G.; Arcangeli, G.; Mucci, N. Stigma and Discrimination (SAD) at the Time of the SARS-CoV-2 Pandemic. Int. J. Environ. Res. Public Health 2020, 17, 6341. [Google Scholar] [CrossRef] [PubMed]
- Griffiths, M.D.; Mamun, M.A. COVID-19 suicidal behavior among couples and suicide pacts: Case study evidence from press reports. Psychiatry Res. 2020, 289, 113105. [Google Scholar] [CrossRef]
- Guo, Q.; Zheng, Y.; Shi, J.; Wang, J.; Li, G.; Li, C.; Fromson, J.A.; Xu, Y.; Liu, X.; Xu, H.; et al. Immediate psychological distress in quarantined patients with COVID-19 and its association with peripheral inflammation: A mixed-method study. Brain Behav. Immun. 2020, 88, 17–27. [Google Scholar] [CrossRef]
- Nochaiwong, S.; Ruengorn, C.; Awiphan, R.; Ruanta, Y.; Boonchieng, W.; Nanta, S.; Kowatcharakul, W.; Pumpaisalchai, W.; Kanjanarat, P.; Mongkhon, P.; et al. Mental health circumstances among health care workers and general public under the pandemic situation of COVID-19 (HOME-COVID-19). Medicine 2020, 99, e20751. [Google Scholar] [CrossRef]
- Von Elm, E.; Altman, D.G.; Egger, M.; Pocock, S.J.; Gøtzsche, P.C.; Vandenbroucke, J.P. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: Guidelines for reporting observational studies. BMJ 2007, 335, 806–808. [Google Scholar] [CrossRef] [Green Version]
- Eysenbach, G. Improving the quality of Web surveys: The Checklist for Reporting Results of Internet E-Surveys (CHERRIES). J. Med. Internet Res. 2004, 6, e34. [Google Scholar] [CrossRef]
- Nochaiwong, S.; Ruengorn, C.; Awiphan, R.; Kanjanarat, P.; Ruanta, Y.; Phosuya, C.; Boonchieng, W.; Nanta, S.; Chongruksut, W.; Thavorn, K.; et al. COVID-19 Public Stigma Scale (COVID-PSS): Development, validation, psychometric analysis and interpretation. BMJ Open 2021, 11, e048241. [Google Scholar] [CrossRef]
- Cohen, J. Statistical Power Analysis for the Behavioral Sciences; Lawrence Erlbaum Associates: Hillsdale, NJ, USA, 1988. [Google Scholar]
- Wongpakaran, N.; Wongpakaran, T. A revised Thai Multi-Dimensional Scale of Perceived Social Support. Span. J. Psychol. 2012, 15, 1503–1509. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sinclair, V.G.; Wallston, K.A. The development and psychometric evaluation of the Brief Resilient Coping Scale. Assessment 2004, 11, 94–101. [Google Scholar] [CrossRef] [PubMed]
- Chory, A.; Nyandiko, W.; Ashimosi, C.; Aluoch, J.; Martin, R.; Biegon, W.; Munyoro, D.; Apondi, E.; Vreeman, R. Social Stigma Related to COVID-19 Disease Described by Primary and Secondary School Teachers and Adolescents Living with HIV in Western Kenya. Front. Public Health 2021, 9, 757267. [Google Scholar] [CrossRef] [PubMed]
- Li, M.; Long, J.; Wang, X.; Liao, Y.; Liu, Y.; Hao, Y.; Wu, Q.; Zhou, Y.; Wang, Y.; Wang, Y.; et al. A Comparison of COVID-19 Stigma and AIDS Stigma During the COVID-19 Pandemic: A Cross-Sectional Study in China. Front. Psychiatry 2021, 12, 782501. [Google Scholar] [CrossRef] [PubMed]
- Jiang, T.; Zhou, X.; Lin, L.; Pan, Y.; Zhong, Y.; Wang, X.; Zhu, H. COVID-19-related stigma and its influencing factors: A nationwide cross-sectional study during the early stage of the pandemic in China. BMJ Open 2021, 11, e048983. [Google Scholar] [CrossRef]
- Smith, L.E.; Potts, H.W.W.; Amlȏt, R.; Fear, N.T.; Michie, S.; Rubin, G.J. Holding a stigmatizing attitude at the start of the COVID-19 outbreak: A cross-sectional survey. Br. J. Health Psychol. 2021, 27, 588–604. [Google Scholar] [CrossRef]
- Zhang, T.M.; Fang, Q.; Yao, H.; Ran, M.S. Public Stigma of COVID-19 and Its Correlates in the General Population of China. Int. J. Env. Res. Public Health 2021, 18, 11718. [Google Scholar] [CrossRef]
- Cassiani-Miranda, C.A.; Campo-Arias, A.; Tirado-Otálvaro, A.F.; Botero-Tobón, L.A.; Upegui-Arango, L.D.; Rodríguez-Verdugo, M.S.; Botero-Tobón, M.E.; Arismendy-López, Y.A.; Robles-Fonnegra, W.A.; Niño, L.; et al. Stigmatisation associated with COVID-19 in the general Colombian population. Int. J. Soc. Psychiatry 2020, 67, 728–736. [Google Scholar] [CrossRef]
- Gao, Y.D.; Ding, M.; Dong, X.; Zhang, J.J.; Kursat Azkur, A.; Azkur, D.; Gan, H.; Sun, Y.L.; Fu, W.; Li, W.; et al. Risk factors for severe and critically ill COVID-19 patients: A review. Allergy 2021, 76, 428–455. [Google Scholar] [CrossRef]
- Chatmon, B.N. Males and Mental Health Stigma. Am. J. Mens Health 2020, 14, 1557988320949322. [Google Scholar] [CrossRef]
- Yuan, Y.; Zhao, Y.J.; Zhang, Q.E.; Zhang, L.; Cheung, T.; Jackson, T.; Jiang, G.Q.; Xiang, Y.T. COVID-19-related stigma and its sociodemographic correlates: A comparative study. Glob. Health 2021, 17, 54. [Google Scholar] [CrossRef] [PubMed]
- Mostafa, A.; Sabry, W.; Mostafa, N.S. COVID-19-related stigmatization among a sample of Egyptian healthcare workers. PLoS ONE 2020, 15, e0244172. [Google Scholar] [CrossRef] [PubMed]
- Do Duy, C.; Nong, V.M.; Ngo Van, A.; Doan Thu, T.; Do Thu, N.; Nguyen Quang, T. COVID-19-related stigma and its association with mental health of health-care workers after quarantine in Vietnam. Psychiatry Clin. Neurosci. 2020, 74, 566–568. [Google Scholar] [CrossRef] [PubMed]
- National Statistical Office; Ministry of Digital Economy and Society. The 2018 Survey on Conditions Of Society, Culture and Mental Health; Statistical Forecasting Division, National Statistical Office: Bangkok, Thailand, 2020. [Google Scholar]
- Davidson, R.J.; Anne, H. Visions of Compassion: Western Scientists and Tibetan Buddhists Examine Human Nature; Oxford University Press: Oxford, UK, 2002. [Google Scholar]
- Meaney, R.; Hasking, P.; Reupert, A. Prevalence of Borderline Personality Disorder in University Samples: Systematic Review, Meta-Analysis and Meta-Regression. PLoS ONE 2016, 11, e0155439. [Google Scholar] [CrossRef]
- Yuan, Q.; Seow, E.; Abdin, E.; Chua, B.Y.; Ong, H.L.; Samari, E.; Chong, S.A.; Subramaniam, M. Direct and moderating effects of personality on stigma towards mental illness. BMC Psychiatry 2018, 18, 358. [Google Scholar] [CrossRef] [Green Version]
- Duan, W.; Bu, H.; Chen, Z. COVID-19-related stigma profiles and risk factors among people who are at high risk of contagion. Soc. Sci. Med. 2020, 266, 113425. [Google Scholar] [CrossRef]
- Valeri, L.; Amsalem, D.; Jankowski, S.; Susser, E.; Dixon, L. Effectiveness of a Video-Based Intervention on Reducing Perceptions of Fear, Loneliness, and Public Stigma Related to COVID-19: A Randomized Controlled Trial. Int. J. Public Health 2021, 66, 1604164. [Google Scholar] [CrossRef]
Figure 1.
Flow diagram for study participants. Abbreviation: HOME-COVID-19, The Health Outcomes and Mental Health Care Evaluation Survey Research Group-Coronavirus disease 2019.
Figure 1.
Flow diagram for study participants. Abbreviation: HOME-COVID-19, The Health Outcomes and Mental Health Care Evaluation Survey Research Group-Coronavirus disease 2019.
Table 1.
Prevalence of COVID-19-related public stigma among general population in Thailand.
| Participant Characteristics | Degree of COVID-19-Related Public Stigma | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| No/Minimal: COVID-PSS ≤ 18 Points (n = 983) | Moderate: COVID-PSS 19–25 Points (n = 1364) | High: COVID-PSS ≥ 26 Points (n = 1657) | |||||||
| No. of Cases/No. of Total | Prevalence Estimated (% [95% CI]) † | p-Value | No. of Cases/No. of Total | Prevalence Estimated (% [95% CI]) † | p-Value | No. of Cases/No. of Total | Prevalence Estimated (% [95% CI]) † | p-Value | |
| Age, year | |||||||||
| ≤30 | 704/2659 | 25.9 (23.7–28.4) | <0.001 | 953/2659 | 37.1 (34.5–39.8) | <0.001 | 1002/2659 | 37.0 (34.4–39.6) | <0.001 |
| 31–50 | 253/1088 | 23.8 (20.3–27.7) | 355/1088 | 33.6 (29.9–37.5) | 480/1088 | 42.6 (38.7–46.7) | |||
| ≥51 | 26/257 | 8.0 (4.6–13.6) | 56/257 | 25.2 (18.2–33.8) | 175/257 | 66.8 (58.0–74.5) | |||
| Sexual identity | |||||||||
| Female | 673/2619 | 25.5 (23.3–28.0) | <0.001 | 896/2619 | 35.4 (32.8–38.0) | 0.845 | 1050/2619 | 39.1 (36.5–41.8) | 0.227 |
| Male | 260/1231 | 19.3 (16.4–22.6) | 415/1231 | 36.0 (32.3–39.9) | 556/1231 | 44.7 (40.8–48.6) | |||
| Others | 50/154 | 34.5 (24.3–46.4) | 53/154 | 34.1 (24.2–45.7) | 51/154 | 31.4 (21.7–43.0) | |||
| Marital status | |||||||||
| Single | 854/3208 | 26.2 (24.1–28.4) | <0.001 | 1162/3208 | 37.7 (35.4–40.2) | <0.001 | 1192/3208 | 36.1 (33.8–38.5) | <0.001 |
| Married/domestic partnership | 115/693 | 17.6 (13.8–22.2) | 170/693 | 23.6 (19.6–28.1) | 408/693 | 58.8 (53.6–63.8) | |||
| Divorced/widowed/separated | 14/103 | 5.6 (2.9–10.7) | 32/103 | 42.6 (29.4–57.0) | 57/103 | 51.7 (38.0–65.2) | |||
| Education level | |||||||||
| Illiterate/primary school/junior high school | 28/127 | 21.0 (12.1–33.9) | 0.474 | 41/127 | 35.6 (24.9–47.9) | 0.784 | 58/127 | 43.4 (32.0–55.6) | 0.373 |
| Senior high school/diploma/high vocational | 482/1893 | 25.4 (22.7–28.2) | 654/1893 | 36.4 (33.4–39.5) | 757/1893 | 38.2 (35.2–41.4) | |||
| Bachelor’s degree/ higher education | 473/1984 | 23.1 (20.6–25.8) | 669/1984 | 34.4 (31.5–37.4) | 842/1984 | 42.5 (39.4–45.6) | |||
| Occupation | |||||||||
| Unemployed/retried | 95/391 | 23.4 (18.3–29.5) | 0.276 | 129/391 | 38.1 (31.3–45.5) | 0.112 | 167/391 | 38.4 (31.9–45.3) | 0.074 |
| Employed | 480/2024 | 24.2 (21.6–27.0) | 663/2024 | 32.4 (29.7–35.3) | 881/2024 | 43.3 (40.3–46.4) | |||
| College student | 408/1589 | 24.4 (21.6–27.5) | 572/1589 | 38.0 (34.7–41.5) | 609/1589 | 37.5 (34.2–41.0) | |||
| Religion | |||||||||
| Irreligion | 143/375 | 32.9 (26.8–39.6) | 0.167 | 126/375 | 39.1 (32.2–46.6) | 0.795 | 106/375 | 28.0 (22.0–34.9) | <0.001 |
| Buddhist | 787/3454 | 35.3 (33.1–37.6) | 1183/3454 | 35.3 (33.1–37.6) | 1484/3454 | 41.8 (39.4–44.1) | |||
| Christian/Muslim/Others | 53/175 | 28.8 (21.1–38.1) | 55/175 | 29.6 (21.4–39.4) | 67/175 | 41.6 (32.6–51.2) | |||
| Region of residence | |||||||||
| Capital city and its environs | 412/1425 | 28.9 (26.6–31.3) | <0.001 | 498/1425 | 34.9 (32.5–37.5) | 0.382 | 515/1425 | 36.1 (33.7–38.7) | <0.001 |
| Non-capital city and its environs | 571/2579 | 22.9 (20.6–25.3) | 866/2579 | 35.6 (33.0–38.3) | 1142/2579 | 41.5 (38.8–44.2) | |||
| Living status | |||||||||
| Alone | 161/576 | 27.0 (22.0–32.7) | 0.547 | 203/576 | 36.7 (31.2–42.5) | 0.473 | 212/576 | 36.3 (30.7–42.3) | 0.224 |
| With family | 745/3164 | 23.4 (21.4–25.6) | 1074/3164 | 35.4 (33.0–37.8) | 1345/3164 | 41.2 (38.8–43.6) | |||
| With others | 77/264 | 29.8 (22.3–38.6) | 87/264 | 34.5 (26.4–43.6) | 100/264 | 35.6 (27.4–44.8) | |||
| Person income, baht/month § | |||||||||
| ≤10,000 (≤308 USD) | 465/1905 | 24.8 (22.1–27.7) | 0.124 | 654/1905 | 36.2 (33.1–39.4) | 0.747 | 786/1905 | 39.0 (35.9–42.2) | 0.100 |
| 10,001–20,000 (309–616 USD) | 299/1054 | 28.0 (24.3–32.0) | 357/1054 | 35.7 (31.8–39.8) | 398/1054 | 36.3 (32.3–40.5) | |||
| >20,000 (>616 USD) | 219/1045 | 19.0 (16.1–22.3) | 353/1045 | 33.7 (30.0–37.6) | 473/1045 | 47.3 (43.2–51.4) | |||
| Reimbursement scheme | |||||||||
| Government/state enterprises | 112/539 | 20.3 (15.9–25.5) | 0.404 | 157/539 | 30.7 (25.4–36.5) | 0.116 | 270/539 | 49.0 (43.1–55.0) | 0.025 |
| Universal coverage scheme | 346/1329 | 26.1 (22.8–29.7) | 466/1329 | 36.6 (32.9–40.5) | 517/1329 | 37.3 (33.6–41.1) | |||
| Social security scheme | 284/1161 | 23.8 (20.6–27.4) | 402/1161 | 36.3 (32.6–40.1) | 475/1161 | 39.9 (36.1–43.8) | |||
| Self-payment/others | 241/975 | 24.7 (21.2–28.6) | 339/975 | 36.3 (32.3–40.6) | 395/975 | 39.0 (34.9–43.2) | |||
| History of mental illness | |||||||||
| No | 875/3645 | 23.7 (21.8–25.7) | 0.527 | 1249/3645 | 35.5 (33.3–37.7) | 0.394 | 1521/3645 | 40.8 (38.6–43.1) | 0.158 |
| Yes | 108/359 | 30.3 (24.2–37.2) | 115/359 | 35.4 (28.6–42.7) | 136/359 | 34.4 (28.0–41.3) | |||
| History of chronic NCDs ‡ | |||||||||
| No | 861/3405 | 25.2 (23.2–27.3) | 0.010 | 1187/3405 | 36.2 (34.0–38.6) | 0.114 | 1357/3405 | 38.6 (36.3–40.9) | <0.001 |
| Yes | 122/599 | 18.4 (14.6–23.1) | 177/599 | 30.9 (25.9–36.4) | 300/599 | 50.6 (44.9–56.3) | |||
| Income loss during the COVID-19 pandemic | |||||||||
| No | 585/2340 | 23.9 (21.5–26.4) | 0.433 | 825/2340 | 36.2 (33.5–39.0) | 0.060 | 930/2340 | 39.9 (37.1–42.7) | 0.125 |
| Yes | 398/1664 | 24.8 (21.9–27.9) | 539/1664 | 34.4 (31.2–37.7) | 727/1664 | 40.8 (37.6–44.2) | |||
| Financial problems during the COVID-19 pandemic | |||||||||
| No | 498/1992 | 24.4 (21.8–27.1) | 0.511 | 713/1992 | 37.3 (34.3–40.3) | 0.218 | 781/1992 | 38.3 (35.4–41.4) | 0.540 |
| Yes | 485/2012 | 23.1 (21.5–26.9) | 651/2012 | 33.8 (30.9–36.8) | 876/2012 | 42.1 (39.1–45.2) | |||
| Information exposure during the COVID-19 pandemic | |||||||||
| <1 h/day | 408/1481 | 27.0 (23.9–30.4) | <0.001 | 503/1481 | 35.5 (32.1–39.1) | 0.726 | 570/1481 | 37.4 (34.0–40.9) | 0.128 |
| 1–2 h/day | 391/1644 | 22.9 (20.2–25.9) | 571/1644 | 35.9 (32.7–39.3) | 682/1644 | 41.1 (37.8–44.5) | |||
| ≥3 h/day | 184/879 | 43.5 (38.9–48.3) | 290/879 | 34.6 (30.2–39.2) | 405/879 | 43.5 (38.9–48.3) | |||
| Confirmed cases in the community | |||||||||
| No | 637/2562 | 25.1 (22.7–27.7) | 0.808 | 871/2562 | 35.2 (32.5–38.0) | 0.775 | 1054/2562 | 39.7 (37.0–42.5) | 0.025 |
| Yes | 136/641 | 20.2 (16.5–24.6) | 215/641 | 33.1 (28.6–37.9) | 290/641 | 46.6 (41.7–51.6) | |||
| Not known | 210/801 | 25.1 (21.4–29.2) | 278/801 | 38.7 (34.1–43.4) | 313/801 | 36.3 (31.9–40.9) | |||
| Quarantine status | |||||||||
| Never | 486/1781 | 27.6 (24.6–30.7) | <0.001 | 567/1781 | 32.3 (29.3–35.5) | 0.059 | 728/1781 | 40.1 (36.8–43.4) | 0.456 |
| Past | 359/1575 | 22.6 (19.9–25.6) | 563/1575 | 36.5 (33.2–39.8) | 653/1575 | 40.9 (37.6–44.3) | |||
| Current | 138/648 | 20.1 (16.2–24.5) | 234/648 | 40.8 (35.4–46.3) | 276/648 | 39.2 (34.1–44.6) | |||
| Working from home | |||||||||
| No | 209/865 | 23.9 (20.1–28.1) | 0.764 | 293/865 | 34.1 (29.9–38.5) | 0.892 | 363/865 | 42.1 (37.6–46.7) | 0.695 |
| Yes | 774/3139 | 24.3 (22.2–26.5) | 1071/3139 | 35.8 (33.5–38.3) | 1294/3139 | 39.8 (37.4–42.3) | |||
| Perceived social support | |||||||||
| Low perceived support | 59/226 | 32.9 (24.6–42.6) | <0.001 | 69/226 | 33.7 (25.8–42.6) | 0.137 | 98/226 | 33.4 (26.3–41.3) | 0.653 |
| Moderate perceived support | 501/1833 | 27.1 (24.4–30.1) | 574/1833 | 32.7 (29.7–35.8) | 758/1833 | 40.2 (37.1–43.4) | |||
| High perceived support | 423/1945 | 20.5 (18.1–23.2) | 721/1945 | 38.4 (35.3–41.6) | 801/1945 | 41.1 (38.0–44.3) | |||
| Resilient coping | |||||||||
| Low resilient copers | 425/1756 | 23.9 (21.2–26.8) | 0.815 | 605/1756 | 36.8 (33.7–40.1) | 0.864 | 726/1756 | 39.3 (36.2–42.4) | 0.969 |
| Medium resilient copers | 393/1570 | 25.2 (22.1–28.5) | 525/1570 | 34.2 (30.9–37.6) | 652/1570 | 40.6 (37.2–44.2) | |||
| High resilient copers | 165/678 | 23.1 (18.9–27.8) | 234/678 | 34.7 (29.7–40.1) | 279/678 | 42.2 (36.9–47.8) | |||
| Fear of COVID-19 | |||||||||
| No/minimal | 169/200 | 82.9 (74.2–89.0) | <0.001 | 29/200 | 16.4 (10.3–25.1) | <0.001 | 2/200 | 0.7 (0.2–2.9) | <0.001 |
| Moderate | 662/1698 | 38.7 (35.4–42.0) | 754/1698 | 45.8 (42.4–49.2) | 282/1698 | 15.5 (13.3–18.1) | |||
| Severe | 152/2106 | 8.1 (6.5–9.9) | 581/2106 | 28.9 (26.2–31.8) | 1373/2106 | 63.0 (60.0–65.9) | |||
| Perceived risk of COVID-19 infection | |||||||||
| Low perceived risk | 584/767 | 74.5 (69.8–78.7) | <0.001 | 171/767 | 23.8 (19.7–28.5) | <0.001 | 12/767 | 1.7 (0.8–3.7) | <0.001 |
| Medium perceived risk | 385/1997 | 19.9 (17.5–22.5) | 990/1997 | 51.6 (48.5–54.6) | 622/1997 | 28.6 (25.9–31.4) | |||
| High perceived risk | 14/1240 | 1.0 (0.4–2.2) | 203/1240 | 16.7 (13.9–19.9) | 1023/1240 | 82.3 (79.1–85.2) | |||
| Overall | 983/4004 | 24.2 (22.2–26.2) | 1364/4004 | 35.5 (33.4–37.6) | 1657/4004 | 40.3 (38.2–42.4) | |||
† Prevalence is presented as weighted. ‡ To includes diabetes mellitus, hypertension, dyslipidemia, stroke and heart disease, chronic kidney disease, chronic lung disease, and cancer. § The currency exchange on the survey period was 1 USD = 32.5 Baht. Abbreviations: CI, confidence interval; COVID-19, coronavirus disease-2019; COVID-PSS, coronavirus disease-2019 Public Stigma Scale; NCDs, non-communicable diseases.
Table 2.
Multinomial logistic regression model results of factors associated with COVID-19-related public stigma (n = 4004).
Table 2.
Multinomial logistic regression model results of factors associated with COVID-19-related public stigma (n = 4004).
| Factors | Moderate vs. No/Minimal | High vs. No/Minimal | ||||||
|---|---|---|---|---|---|---|---|---|
| Unadjusted OR (95% CI) † | p-Value | Adjusted OR (95% CI) † | p-Value | Unadjusted OR (95% CI) † | p-Value | Adjusted OR (95% CI) † | p-Value | |
| Age, year | ||||||||
| ≤30 | Reference (1.00) | Reference (1.00) | Reference (1.00) | Reference (1.00) | ||||
| 31–50 | 0.99 (0.76–1.29) | 0.927 | 1.59 (1.08–2.34) | 0.018 | 1.26 (0.97–1.63) | 0.083 | 2.22 (1.36–3.62) | 0.001 |
| ≥51 | 2.19 (1.11–4.35) | 0.024 | 4.34 (1.49–12.64) | 0.007 | 5.84 (3.14–10.83) | <0.001 | 10.31 (3.13–34.01) | <0.001 |
| Sexual identity | ||||||||
| Female | Reference (1.00) | Reference (1.00) | Reference (1.00) | Reference (1.00) | ||||
| Male | 1.34 (1.03–1.75) | 0.028 | 1.68 (1.21–2.33) | 0.002 | 1.51 (1.17–1.95) | 0.001 | 2.35 (1.58–3.49) | <0.001 |
| Others | 0.72 (0.40–1.28) | 0.256 | 1.00 (0.50–2.03) | 0.992 | 0.59 (0.33–1.08) | 0.088 | 1.00 (0.42–2.37) | 0.993 |
| Marital status | ||||||||
| Single | Reference (1.00) | Reference (1.00) | Reference (1.00) | Reference (1.00) | ||||
| Married/domestic partnership | 0.93 (0.65–1.33) | 0.690 | 0.88 (0.52–1.49) | 0.627 | 2.42 (1.75–3.36) | <0.001 | 1.97 (1.07–3.64) | 0.030 |
| Divorced/widowed/separated | 5.24 (2.36–11.64) | <0.001 | 3.88 (1.42–10.55) | 0.008 | 6.64 (3.16–13.99) | <0.001 | 3.69 (1.00–13.60) | 0.050 |
| Education level | ||||||||
| Illiterate/primary school/junior high school | Reference (1.00) | Reference (1.00) | ||||||
| Senior high school/diploma/high vocational | 0.85 (0.40–1.79) | 0.655 | 0.73 (0.36–1.49) | 0.387 | ||||
| Bachelor’s degree/higher education | 0.88 (0.42–1.85) | 0.736 | 0.89 (0.44–1.82) | 0.748 | ||||
| Occupation | ||||||||
| Unemployed/retried | Reference (1.00) | Reference (1.00) | ||||||
| Employed | 0.82 (0.55–1.23) | 0.340 | 1.09 (0.75–1.60) | 0.645 | ||||
| College student | 0.96 (0.64–1.44) | 0.833 | 0.94 (0.64–1.38) | 0.747 | ||||
| Religion | ||||||||
| Irreligion | Reference (1.00) | Reference (1.00) | Reference (1.00) | |||||
| Buddhist | 1.29 (0.90–1.85) | 0.159 | 2.14 (1.47–3.11) | <0.001 | 2.11 (1.22–3.63) | 0.007 | ||
| Christian/Muslim/Others | 0.86 (0.47–1.59) | 0.632 | 1.69 (0.95–3.01) | 0.073 | 1.41 (0.59–3.35) | 0.439 | ||
| Region of residence | ||||||||
| Capital city and its environs | Reference (1.00) | Reference (1.00) | ||||||
| Non-capital city and its environs | 1.29 (1.06–1.57) | 0.012 | 1.45 (1.20–1.76) | <0.001 | 1.45 (1.08–1.95) | 0.013 | ||
| Living status | ||||||||
| Alone | Reference (1.00) | Reference (1.00) | ||||||
| With family | 1.11 (0.80–1.54) | 0.523 | 1.31 (0.94–1.83) | 0.114 | ||||
| With others | 0.85 (0.50–1.46) | 0.564 | 0.89 (0.52–1.54) | 0.676 | ||||
| Person income, baht/month § | ||||||||
| ≤10,000 (≤308 USD) | Reference (1.00) | Reference (1.00) | ||||||
| 10,001–20000 (309–616 USD) | 0.88 (0.66–1.15) | 0.342 | 0.83 (0.63–1.08) | 0.169 | ||||
| >20,000 (>616 USD) | 1.22 (0.92–1.62) | 0.174 | 1.59 (1.21–2.09) | 0.001 | ||||
| Reimbursement scheme | ||||||||
| Government/state enterprises | Reference (1.00) | Reference (1.00) | ||||||
| Universal coverage scheme | 0.93 (0.62–1.38) | 0.709 | 0.59 (0.41–0.86) | 0.006 | ||||
| Social security scheme | 1.01 (0.67–1.51) | 0.974 | 0.69 (0.47–1.01) | 0.056 | ||||
| Self-payment/others | 0.97 (0.64–1.47) | 0.892 | 0.65 (0.44–0.96) | 0.030 | ||||
| History of mental illness | ||||||||
| No | Reference (1.00) | Reference (1.00) | ||||||
| Yes | 0.78 (0.53–1.14) | 0.205 | 0.66 (0.46–0.95) | 0.026 | ||||
| History of chronic NCDs ‡ | ||||||||
| No | Reference (1.00) | Reference (1.00) | ||||||
| Yes | 1.17 (0.82–1.65) | 0.383 | 1.79 (1.30–2.48) | <0.001 | ||||
| Income loss during the COVID-19 pandemic | ||||||||
| No | Reference (1.00) | Reference (1.00) | ||||||
| Yes | 0.91 (0.72–1.16) | 0.457 | 0.99 (0.78–1.24) | 0.908 | ||||
| Financial problems during the COVID-19 pandemic | ||||||||
| No | Reference (1.00) | Reference (1.00) | ||||||
| Yes | 0.92 (0.72–1.16) | 0.463 | 1.53 (1.30–1.80) | 0.362 | ||||
| Information exposure during the COVID-19 pandemic | ||||||||
| <1 h/day | Reference (1.00) | Reference (1.00) | Reference (1.00) | |||||
| 1–2 h/day | 1.19 (0.92–1.55) | 0.184 | 1.30 (1.01–1.67) | 0.045 | 1.52 (1.05–2.21) | 0.027 | ||
| ≥3 h/day | 1.20 (0.87–1.66) | 0.261 | 1.44 (1.06–1.96) | 0.021 | 1.32 (0.84–2.07) | 0.232 | ||
| Confirmed cases in the community | ||||||||
| No | Reference (1.00) | Reference (1.00) | ||||||
| Yes | 1.17 (0.85–1.61) | 0.341 | 1.46 (1.07–1.98) | 0.016 | ||||
| Not known | 1.10 (0.83–1.46) | 0.504 | 0.91 (0.69–1.21) | 0.526 | ||||
| Quarantine status | ||||||||
| Never | Reference (1.00) | Reference (1.00) | Reference (1.00) | Reference (1.00) | ||||
| Past | 1.38 (1.07–1.78) | 0.014 | 1.35 (0.99–1.84) | 0.061 | 1.24 (0.97–1.59) | 0.081 | 1.33 (0.92–1.93) | 0.131 |
| Current | 1.73 (1.24–2.43) | 0.001 | 2.08 (1.31–3.33) | 0.002 | 1.34 (0.97–1.87) | 0.076 | 1.75 (1.03–2.97) | 0.039 |
| Working from home | ||||||||
| No | Reference (1.00) | Reference (1.00) | ||||||
| Yes | 0.97 (0.73–1.28) | 0.826 | 1.08 (0.82–1.41) | 0.593 | ||||
| Perceived social support | ||||||||
| Low perceived support | Reference (1.00) | Reference (1.00) | ||||||
| Moderate perceived support | 1.18 (0.71–1.96) | 0.525 | 1.46 (0.92–2.32) | 0.106 | ||||
| High perceived support | 1.83 (1.10–3.04) | 0.020 | 1.98 (1.24–3.16) | 0.004 | ||||
| Resilient coping | ||||||||
| Low resilient copers | Reference (1.00) | Reference (1.00) | ||||||
| Medium resilient copers | 0.90 (0.64–1.27) | 0.546 | 0.88 (0.63–1.23) | 0.450 | ||||
| High resilient copers | 1.02 (0.73–1.43) | 0.890 | 0.90 (0.65–1.24) | 0.511 | ||||
| Fear of COVID-19 | ||||||||
| No/minimal | Reference (1.00) | Reference (1.00) | Reference (1.00) | Reference (1.00) | ||||
| Moderate | 5.98 (3.4–10.42) | <0.001 | 3.70 (1.95–7.03) | <0.001 | 45.91 (11.13–189.40) | <0.001 | 20.71 (4.11–104.19) | <0.001 |
| Severe | 18.10 (10.04–32.61) | <0.001 | 6.24 (3.16–12.36) | <0.001 | 891.66 (215.11–3695.96) | <0.001 | 111.70 (21.90–569.63) | <0.001 |
| Perceived risk of COVID-19 infection | ||||||||
| Low perceived risk | Reference (1.00) | Reference (1.00) | Reference (1.00) | Reference (1.00) | ||||
| Medium perceived risk | 8.12 (6.06–10.90) | <0.001 | 7.78 (5.61–10.79) | <0.001 | 63.85 (27.90–146.14) | <0.001 | 60.15 (23.80–152.00) | <0.001 |
| High perceived risk | 52.43 (22.46–122.42) | <0.001 | 41.94 (17.56–100.15) | <0.001 | 3672.46 (1183.11–11399.61) | <0.001 | 2245.43 (667.25–7556.23) | <0.001 |
† The effect estimates are presented weighted. ‡ To includes diabetes mellitus, hypertension, dyslipidemia, stroke and heart disease, chronic kidney disease, chronic lung disease, and cancer. § The currency exchange on the survey period was 1 USD = 32.5 Baht. Abbreviations: CI, confidence interval; COVID-19, coronavirus disease-2019; COVID-PSS, coronavirus disease-2019 Public Stigma Scale; NCDs, non-communicable diseases; OR, odds ratio.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
MDPI and ACS Style
Ruengorn, C.; Awiphan, R.; Phosuya, C.; Ruanta, Y.; Thavorn, K.; Wongpakaran, N.; Wongpakaran, T.; Nochaiwong, S. Disparities and Factors Associated with Coronavirus Disease-2019-Related Public Stigma: A Cross-Sectional Study in Thailand. Int. J. Environ. Res. Public Health 2022, 19, 6436. https://doi.org/10.3390/ijerph19116436
AMA Style
Ruengorn C, Awiphan R, Phosuya C, Ruanta Y, Thavorn K, Wongpakaran N, Wongpakaran T, Nochaiwong S. Disparities and Factors Associated with Coronavirus Disease-2019-Related Public Stigma: A Cross-Sectional Study in Thailand. International Journal of Environmental Research and Public Health. 2022; 19(11):6436. https://doi.org/10.3390/ijerph19116436
Chicago/Turabian StyleRuengorn, Chidchanok, Ratanaporn Awiphan, Chabaphai Phosuya, Yongyuth Ruanta, Kednapa Thavorn, Nahathai Wongpakaran, Tinakon Wongpakaran, and Surapon Nochaiwong. 2022. "Disparities and Factors Associated with Coronavirus Disease-2019-Related Public Stigma: A Cross-Sectional Study in Thailand" International Journal of Environmental Research and Public Health 19, no. 11: 6436. https://doi.org/10.3390/ijerph19116436
APA StyleRuengorn, C., Awiphan, R., Phosuya, C., Ruanta, Y., Thavorn, K., Wongpakaran, N., Wongpakaran, T., & Nochaiwong, S. (2022). Disparities and Factors Associated with Coronavirus Disease-2019-Related Public Stigma: A Cross-Sectional Study in Thailand. International Journal of Environmental Research and Public Health, 19(11), 6436. https://doi.org/10.3390/ijerph19116436
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
