key: cord-0991090-99dh7gpa
authors: Chang, Kun-Chia; Strong, Carol; Pakpour, Amir H.; Griffiths, Mark D.; Lin, Chung-Ying
title: Factors related to preventive COVID-19 infection behaviors among people with mental illness
date: 2020-07-29
journal: J Formos Med Assoc
DOI: 10.1016/j.jfma.2020.07.032
sha: 9c570bc5389f924315b8e8ee91cbc78875031836
doc_id: 991090
cord_uid: 99dh7gpa

Abstract Background Because of the spread of novel coronavirus disease 2019 (COVID-2019), preventive COVID-19 infection behaviors become important for individuals, especially those who are vulnerable. The present study proposes a model to explain the preventive COVID-19 infection behaviors among people with mental illness in Taiwan. Methods A cross-sectional design was carried and 414 patients with mental illness (230 males [55.6%]; mean age = 46.32 [SD = 10.86]) agreed to participate in the study. All the participants completed the Preventive COVID-19 Infection Behaviors Scale, Self-Stigma Scale-Short, Believing COVID-19 Information Scale, Fear of COVID-19 Scale, and Depression Anxiety Stress Scale-21. Regression models and structural equation modeling (SEM) were applied to examine the factors associated with preventive COVID-19 infection behaviors. Results Both regression models and SEM showed that trust in COVID-19 information sources (standardized coefficient [β] = 0.211 in regression; β = 0.194 in SEM) and fear of COVID-19 (β = -0.128 in regression; β = -0.223 in SEM) significantly explained preventive behaviors among individuals with mental illness. The SEM further showed that fear of COVID-19 was significantly explained by trust in COVID-19 information sources (β = 0.220) and self-stigma (β = 0.454). Conclusions Based on the results, healthcare providers should help individuals with mental illness reduce self-stigma and fear of COVID-19 which would consequently improve their preventive COVID-19 infection behaviors. Moreover, improving trust in COVID-19 information sources for individuals with mental illness may be another method to improve their preventive behaviors.

With the spread of novel coronavirus disease 2019 (COVID- 19) worldwide, health 27 behaviors -especially preventive behaviors by individuals -has become crucial. More 28 specifically, with the awareness and practice of preventive behaviors, the transmission rate of 29 infectious disease can be reduced. [1] [2] [3] Shaw et al. 2 based on their beliefs). 1, 2 For instance, spatial distancing has been implemented in many 34 countries to avoid the possibility of infection transmission. 4 Such policies appear to be 35 effective because COVID-19 infection rates were lower in countries that applied early 36 preventive policies such as quarantine and closure of non-essential shops and schools. 2,5 37 However, reliance on government action alone is insufficient to totally control COVID- 19 38 infection and the World Health Organization (WHO) 6 proposed a number of personal 39 preventive behaviors for individuals to engage in to control COVID-19 infection. Therefore, 40 understanding the factors that associated with individuals' preventive behaviors is an 41 important topic during the COVID-19 pandemic. 42 information may increase individuals' good practice in preventive behaviors. Although 48 misconceptions concerning COVID-19 have been found in social media, 9 many authorities 49 have used different methods (e.g., penalties for those who distribute misinformation) to 50 prevent such misinformation. Taiwan (where the present study was carried out) has 51 effectively prevented such misinformation. 8 Nevertheless, some accurate COVID- 19 52 information (e.g., the death rate and numbers of confirmed cases) may trigger an individual's 53 fear of COVID-19 and induce psychological distress. 10 Therefore, trust in COVID-19 54 information sources may improve individuals' prevention behaviors but jeopardize their 55 mental health, including the increase in the fear of COVID-19 and psychological distress. 56

Several theories, including the Health Belief Model, 11 the Fear Drive Model, 12 and the 57 Protection Motivation Theory, 13 manipulate fear to facilitate an individual in practicing 58 preventive behaviors to avoid infection. However, extreme fear (for individuals who cannot 59 handle the fear they perceive) may lead to irrational thinking 14 and subsequently inhibit 60 practicing preventive behaviors. Moreover, fear of COVID-19 may induce individuals to 61 perform inappropriate behaviors, such as panic purchase, discrimination, and even 62 suicide. [15] [16] [17] Indeed, a meta-analysis showed that when individuals cannot control fear, they 63 defensively resist preventive behaviors. 18 Therefore, individuals with mental illness may have 64 difficulties in controlling fear and resist engaging in preventive COVID-19 infection behavior. 65

Apart from the potential negative association between fear of COVID-19 and preventive 66 COVID-19 infection behavior, fear of COVID-19 has been found to be associated with 67 psychological distress in studies carried out in different countries. [19] [20] [21] Therefore, it is likely 68 that psychological distress also has a negative association with preventive COVID-19 69 infection behaviors. 70

Although trust in COVID-19 information sources, fear of COVID-19, and psychological 71 distress have been identified among the general population during the COVID-19 pandemic, 72 it is not known how these factors influence vulnerable populations. Therefore, the present 73 study specifically investigated a vulnerable population (i.e., individuals with mental illness). 74

Such individuals are an especially vulnerable during the current pandemic. For example, they 6 may not have ability to distinguish good from bad COVID-19 information, 22 and they may 76 have more difficulties than general population in handling their mood. 22 77 Moreover, individuals with mental illness often have self-stigma issues that prevent 78 them from performing health behaviors such as treatment compliance. 23 Individuals with 79 mental illness and self-stigma are reluctant to adhere to treatment because they have high 80 levels of psychological distress and lower levels of self-esteem. 24 The present study investigated the potential factors explaining preventive COVID-19 89 infection behaviors among individuals with mental illness in Taiwan. The following 90 hypotheses were formulated based on the aforementioned literature: H 1 -self-stigma will be 91 negatively associated with preventive COVID-19 infection behaviors; H 2 -trust in 92 COVID-19 information sources will be positively associated with preventive COVID-19 93 infection behaviors; H 3 -fear of COVID-19 will be negatively associated with preventive 94 COVID-19 infection behaviors; H 4 -psychological distress will be negatively associated 95 with preventive COVID-19 infection behaviors; H 5 self-stigma will be positively associated 96 with psychological distress; H 6 -trust in COVID-19 information sources will be positively 97 associated with psychological distress; H 7 -fear of COVID-19 will be positively associated 98 with psychological distress; H 8 -self-stigma will be positively associated with fear of 99 COVID-19; and H 9 -trust in COVID-19 information sources will be positively associated 100 with fear of COVID-19 ( Figure 1 ). 101

Study design, participants, and recruitment procedure 103

The present study adopted a cross-sectional design and commenced after the Taiwan 104 government had already tightened the regulations for many hospitals and clinics to avoid 105 unnecessary contact between different personnel, including medical staff, patients, and Measures 133

Considering the five preventive behaviors recommended by the WHO, 6 the five-item 135 PCIBS was developed using a five-point Likert scale to quantify how an individual regularly 136 performs preventive behaviors. More specifically, the five-point Likert scale scores from 1 137 (almost never) to 5 (almost always) with a higher PCIBS score indicating a higher frequency 138 in performing preventive behaviors. "I stay home more when I feel unwell" is an example 139 item in the PCIBS. The PCIBS has demonstrated moderate correlations with psychological 140 distress in a recent study, and reported satisfactory concurrent validity. 26 The present study's 141 data showed that the PCIBS had very good internal consistency (α=.77). 142

Considering stereotypes, emotional responses, and behaviors induced by self-endorsed 144 misconception of mental illness, the nine-item SSS-S was developed using a four-point Likert 145 scale to assess self-stigma. More specifically, the four-point Likert scale scores from 1 146 (strongly disagree) to 4 (strongly agree) with a higher SSS-S score indicating a greater level 147 of self-stigma. "I feel uncomfortable because I have a mental illness" is an example item in 148 the SSS-S. The SSS-S has demonstrated satisfactory psychometric properties, including 149 internal consistency and construct validity, in samples of Taiwanese individuals with mental 9 illness. 27, 28 The present study showed that the SSS-S had excellent internal consistency 151 (α=.95). 152

Considering commonly used social media among Taiwanese individuals, 6 construct validity, in a large sample of general Iranian population. 29 Moreover, the Chinese 168 FCV-19S was found to be psychometrically sound recently 6, 30 The present study's data 169

showed that the FCV-19S had excellent internal consistency (α=.92). 170

Considering the symptoms of different types of psychological distress, the 21-item 172 DASS-21 was developed using a four-point Likert scale to assess how an individual suffers 173 from depression (seven items), anxiety (seven items), and stress (seven items). More 174 specifically, the four-point Likert scale scores from 0 (never) to 3 (almost always) with higher 175 DASS-21 total scores indicating a greater level of psychological distress. "I felt that I was 176 close to panic" is an example item in the DASS-21. The DASS-21 has demonstrated 177 satisfactory psychometric properties, including internal consistency and construct validity, in 178

Korean samples with and without mental illness. 31 The present study's data showed that the 179 DASS-21 had excellent internal consistency (α=.96). 180

Background information of the participants were obtained from self-reports, including 182 age, gender, educational year, and marital status. Moreover, diagnoses of the participants' 183 mental illness were retrieved from their medical records. 184

In addition to the descriptive statistics that illustrate the participants' characteristics, 186

Pearson correlation was carried out to understand the associations between the studied 187 variables. Following this, two regression models were constructed to understand the factors 188 Tucker-Lewis index (TLI) > .9, root mean square error of approximation (RMSEA) < .08; and 207 standardized root mean square residual (SRMR) < .08 were thus adopted to indicate good 208 fit. 32, 33 Given that there were five missing values (~1.2%) in the present study, full 209 information maximum likelihood method was applied to impute the missing information. All 210 the data analyses were performed using IBM SPSS Statistics for Windows, Version 24.0 211 (IBM corp., Armonk, NY), except for the SEM model, which was analyzed using lavaan 212 package in the R software. 213

Among the 414 participants, more than half were males (n = 230; 55.6%), the majority 215 were single (n = 208; 50.2%), and the most common major diagnosis was schizophrenia (n = 216 197; 47.6%). The mean age of the participants was 46.32 (SD = 10.86) years and their mean 217 years of education was 10.89 years (SD = 3.25). Table 1 also presents the participants' scores 218 on each measure. Moreover, the associations between the studied variables are presented in 219 Table 2 , where significantly moderate associations were observed between self-stigma, fear 220 of COVID-19, and psychological distress (r = .339 to .494; all p-values < .001). Furthermore, 221 trust in COVID-19 information sources was significantly correlated with fear of COVID-19 222 (r = .215; p<.001) and preventive behavior (r =.176; p<.001). 223

The regression models showed that trust in COVID-19 information sources 224 also showed that higher trust in health information sources concerning cigarette was 248 associated with healthier behavior. 34 Trust in information sources is an important part of 249 evaluation for monitoring in how individuals perceive risk and cope with stress differently 250 13 during the COVID-19 pandemic. 35 Individuals with lower socioeconomic status have been 251 found to trust less legitimate sources such as television, social media, or friends more than 252 healthcare professionals. 36 The present study showed that higher trust in COVID-19 information sources was 260 associated with increased fear of COVID-19 among individuals living with mental illness. 261

Higher trust in COVID-19 information sources may indicate higher exposure and acceptance 262 of COVID-19 information. It is likely that the more individuals living with mental illness are 263 exposed to COVID-19 information, the more fear generated because their lack of 264 understanding of such a new health issue with no effective treatment. This finding is 265 consistent with the Heuristic-Systematic Model, which highlights that individuals with prior 266 knowledge about a topic have lower impact of fear arousal from fear appeals messages of 267 health campaigns. 37 Public health campaigns or governments should balance the fact that fear 268 may be an unexpected consequence resulted from providing COVID-19 messages daily via 269 multiple channels. For individuals who do not have resources to filter out useful information 270 or to evaluate their personal risk, additional reassurance for their safety or interpretation of 271 messages from the government on social media and broadcast media may help individuals 272 lower the fear. 273

As hypothesized, the present study found that more fear of COVID-19 was associated 274 with less preventive COVID-19 infection behaviors but more psychological distress. Fear 275 may promote individuals to engage in preventive behaviors because fear of COVID-19 may 276 motivate individuals to engage in behaviors that prevent them from infection. [11] [12] [13] [14] Indeed, 277

Harper et al. 38 Although self-stigma was not associated with COVID-19 preventive behaviors in the 290 present study, self-stigma was associated with fear of COVID-19 and psychological distress. 291 A possible reason for the nonsignificant association between self-stigma and preventive 292 behaviors is that self-stigma does not directly associate with preventive behaviors. Rather, the 293 association between self-stigma and preventive behaviors was via fear of COVID-19. Indeed, 294 self-stigma was found to be highly associated with fear of COVID-19, and fear of COVID-19 295 was associated with COVID-19 preventive behaviors. When individuals with mental illness 296 have self-stigma, they may feel incompetence and are afraid of disclosing their illness 297 identity. 23 Therefore, individuals with mental illness may have an elevated fear of COVID-19 298 because they may disclose their mental illness identity if they are affected by That is, they have to visit a physician for COVID-19 treatment and discuss their mental 300 illness. Another explanation is that individuals with mental illness who have self-stigma may 301 worry that healthcare providers may provide poorer quality service and/or have more 302 negative attitudes to them compared with people with no mental illness if they have 303 COVID-19. More specifically, one route for individuals with mental illness to develop 304 self-stigma is through uncomfortable previous experiences (e.g., being laughed and/or not 305 being respected). 27 Such experiences may also induce their fear of COVID-19. Moreover, the 306 association between self-stigma and psychological distress found in the present study concurs 307 with prior findings. 24,25 308 There are some limitations in the present study. First, the study adopted a cross-sectional 309 design and as such the findings are unable to determine any causal relationship, although the 310 model proposes potential directions among the studied variables. Second, all the measures 311 used in the present study were self-report (or with the assistance of an assistant researcher). 312 Therefore, the associations found in the present study might be influenced by common 313 variance bias. Moreover, other biases such as recall bias and social desirability bias might 314 exit using self-report methods. Nevertheless, using self-reports in the present study had the 315 benefits of low-cost and rapid data collection that can respond in a timely fashion to the need 316 of reaction toward COVID-19 during the pandemic. However, future studies may consider 317 using other types of measurement method (e.g., actually observing preventive behaviors) to 318 corroborate the present study's findings. Third, the participants were in stable condition 319 during the study period. Therefore, the present study's findings may not be generalized to 320 those with a severe mental illness. Fourth, the participants were recruited solely from one 321 institution in Taiwan Table 3 Regression models explaining preventive behaviors among individuals with mental illness B (SE)/ β (95% CI) Trust in COVID-19 information

Evaluating the combined effectiveness of influenza control strategies and human preventive behavior

technology and citizen behavior in pandemic: Lessons from COVID-19 in East Asia

The use of facemasks to prevent respiratory infection: A literature review in the context of the Health Belief Model

The COVID-19 pandemic calls for spatial distancing and social closeness: not for social distancing!

Response to COVID-19 in Taiwan: Big data analytics, new technology, and proactive testing

Psychometric testing of three COVID-19-related scales among people with mental illness

Preventive behaviors conveyed on YouTube to mitigate transmission of COVID-19: Cross-sectional study

How health officials and social media are teaming up to fight the coronavirus "infodemic

Knowledge and perceptions of COVID-19 among the general public in the United States and the United Kingdom: A cross-sectional online survey

Immediate psychological responses and associated factors during the initial stage of the 2019 coronavirus disease (COVID-19) epidemic among the general population in China

Health belief model

The impact of communications on the self-regulation of health beliefs, decisions, and behavior

A Protection Motivation Theory of Fear Appeals and Attitude Change

The fear of COVID-19 and its role in preventive behaviors

COVID-19-related suicides in Bangladesh due to lockdown and economic factors: Case study evidence

Social reaction toward the 2019 novel coronavirus (COVID-19)

Development and initial validation of the COVID Stress Scales

A meta-analysis of fear appeals: Implications for effective public health campaigns

Psychometric validation of the Bangla Fear of COVID-19 Scale: Confirmatory factor analysis and Rasch analysis

Adaptation of the Fear of COVID-19 Scale: Its association with psychological distress and life satisfaction in Turkey

Validation and psychometric evaluation of the Italian version of the Fear

Multidisciplinary research priorities for the COVID-19 pandemic: A call for action for mental health science

Self-stigma of people with schizophrenia as predictor of their adherence to psychosocial treatment

The mediation role of self-esteem for self-stigma on quality of life for people with schizophrenia: A retrospectively longitudinal study

Dynamic changes of self-stigma, quality of life, somatic complaints, and depression among people with schizophrenia: A pilot study applying kernel smoothers

Associations between fear of COVID-19, mental health, and preventive behaviours across pregnant women and husbands: An actor-partner interdependence modelling

Cross-validation of two commonly used self-stigma measures, Taiwan versions of the Internalized Stigma Mental Illness Scale and Self-Stigma Scale-Short, for people with mental illness

Further psychometric evaluation of the Self-Stigma Scale-Short: measurement invariance across mental illness and gender

Fear of COVID-19 Scale: Development and initial validation

Advance online publication

Assessing the fear of COVID-19 among different populations: A response to

The 21-Item and 12-Item Versions of the Depression Anxiety Stress Scales: Psychometric evaluation in a Korean population

Insufficient physical activity and overweight: Does caregiver screen-viewing matter?

Psychometric testing of three Chinese online-related addictive behavior instruments among Hong Kong university students

Isolated and skeptical: social engagement and trust in information sources among smokers

How behavioural science data helps mitigate the COVID-19 crisis

Health literacy and use and trust in health information

Prior knowledge and health messages: An examination of affect as heuristics and information as systematic processing for fear appeals

Functional fear predicts public health compliance in the COVID-19 pandemic

Nature walk decrease the depression by instigating positive mood

Cognitive dysfunction in psychiatric disorders: Characteristics, causes and the quest for improved therapy