Factors Furthering Public Compliance with Preventive Health Behavior in Taiwan

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Volume 37 Issue 6 Article 8

2023

Factors Furthering Public Compliance with Preventive Health Factors Furthering Public Compliance with Preventive Health Behavior in Taiwan

Behavior in Taiwan

LEE Shan-Ying

Institute of Public Affairs Management, National Sun Yat-sen University, Kaohsiung, Taiwan YEH Jennifer Shu-Chuan

Department of Business Management, National Sun Yat-Sen University, Kaohsiung, Taiwan WU Wei-Ning

Institute of Public Affairs Management, National Sun Yat-sen University, Kaohsiung, Taiwan

Follow this and additional works at: https://digital.car.chula.ac.th/jhr

2586-940X/© 2023 The Authors. Published by College of Public Health Sciences, Chulalongkorn University. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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Factors Furthering Public Compliance with Preventive Health Behavior in Taiwan

Shan-Ying Lee

^a,

*, Shu-Chuan Jennifer Yeh

^b

, Wei-Ning Wu

^a

aInstitute of Public Affairs Management, National Sun Yat-sen University, Kaohsiung, Taiwan

bDepartment of Business Management, National Sun Yat-Sen University, Kaohsiung, Taiwan

Abstract

Background:Individual health behaviors are important for restraining the spread of inﬂuenza. It is crucial to explore what makes individuals take protective measures against infectious diseases. This study aimed to explore factors associated with the public's intention to take protective measures during the inﬂuenza pandemic.

Method:This cross-sectional study was based on the 2013 Taiwan Social Change Survey, with a nationally representative sample. The health belief model constructs and public trust effects (government action, political support, and trust level) were examined using multivariable logistic regression. This study investigated the independent predictors of four personal preventive behaviors: wearing face masks, washing hands frequently, receiving an inﬂuenza vaccine, and keeping away from public places.

Results:77% of the 2005 participants agreed to follow preventive measures. Multiple regression analysis showed that perceived susceptibility, perceived severity, perceived beneﬁts, trust level, living area, and marital status were signiﬁcant predictors of behaviors. While using the four protective behaviors separately as dependent variables, the models showed that the trust level was the strongest driving factor for vaccination. Married people were more likely to avoid public places. Highly educated individuals were more willing to wear masks. Regular exercise also increased the frequency of hand washing during pandemics.

Conclusion:Thefindings confirm that health preventive factors can predict Taiwanese individuals’intentions against influenza contagion, and considering public trust can increase the predictive capacity of health behavior.

Keywords:Health belief model, Inﬂuenza, Pandemic, Preventive behavior, Public trust

1. Introduction

P

andemic outbreaks are a major threat to the world. Such crises occur with increasing frequency, intensity, and duration. New infectious diseases have spread in recent years, resulting in excessive mortality. This has altered the global economy and lifestyles and challenged the health governance of governments.

Personal protective measures are useful for mitigating epidemics of respiratory viruses [1,2]. Besides vaccination, non-pharmaceutical measures are accessible interventions for communities. Govern- ments and health organizations also provide recommendations and guidelines for wearing masks, maintaining good hygiene, and avoiding crowds in

response to inﬂuenza pandemics [3,4]. However, individual perceptions and cooperation are key to implementation. Individuals unwilling to accept restrictions or distrustful of the protective effect may refuse advice. For example, during the coronavirus pandemic, anti-vaccine and face mask mandate protesters persisted, although it was at a mortality peak. Hence, exploring what makes individuals take protective measures against infectious diseases is crucial.

The health belief model (HBM) is one of the most widely used models to explain individual decision- making regarding recommended actions during infectious disease outbreaks. The HBM hypothe- sizes that behavior depends mainly on two variables: (1) the desire to avoid illness and (2) the belief that a speciﬁc health action will prevent illness. It

Received 29 September 2022; revised 12 December 2022; accepted 15 December 2022.

Available online 6 June 2023

*Corresponding author.

E-mail address:[email protected](S.-Y. Lee).

https://doi.org/10.56808/2586-940X.1046

2586-940X/©2023 The Authors. Published by College of Public Health Sciences, Chulalongkorn University. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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comprises the following dimensions: perceived susceptibility, perceived severity, perceived bene- ﬁts, perceived barriers, self-efﬁcacy to engage in a behavior, and cues to action [5e7]. However, one major limitation of this model is the low predictive capacity of existing variables, coupled with the small effect size of individual variables. This suggests that there are other important variables that determine healthy behavior that the HBM did not consider [8].

Trust in authorities, such as experts, national leadership, and the healthcare system, was an important determinant of citizens' compliance with public health policies, restrictions and guidelines. It may inﬂuence individuals' decisions to adopt recommended protective actions [9e12]. However, the relationship remains largely unknown. Therefore, we introduced the public trust variable comprising government action, political support, and trust level as possible contributors to healthy behavior, and provided empirical evidence to verify it.

Taiwan is an example of how a society can respond quickly to a crisis and protect its citizens’

interests [13]. After several pandemic outbreaks in recent years, from SARS to H7N9, H1N1, and dengue. Thus, the government has learned from its experiences, adopting and adapting many World Health Organization recommendations, and thereby implementing “best practices” in many aspects of pandemic preparedness and response [14].

This study investigated the prevalence and factors associated with preventative behavior among Taiwa- nese individuals. This result is conducive to understanding why some individuals are more willing to follow recommended preventive measures while others are not. By highlighting these crucial factors, the government and health agencies can enhance their ability and public cooperation in the future.

2. Methods

2.1. Study design and data collection

This cross-sectional study was based on the 2013 Taiwan Social Change Survey (Round 4, Year 6: Risk Society) dataset, performed by Academia Sinica, with a nationally representative sample. All adults aged above 18 were amongst the eligible targeted popula- tion. It adopted a 3-stage probability proportional to size sampling method. Township, village, and individual were the three sampling units. Interpersonal interviews were conducted by using structured ques- tionnaires [15]. This study used the special investigation theme of infectious diseases and risk-related questions for analysis objects. A total of 2005 participants were included in the study.

2.2. Measurement

To measure health behavior, we selected four activities as dependent variables: wearing face masks, washing hands frequently, receiving the influenza vaccine, and keeping away from public places. Re- sponses to the question: “When a novel influenza epidemic occurs in Taiwan, would you take actions to prevent it?” ranged from definitely yes (1) to definitely no (5). The sum of the intention to adopt each of the four protective behaviors was used as the preventative behavior score (Cronbach's alpha¼0.72) in linear regression. Thereafter, each protective behavior was treated separately as a dependent variable in the logistic analysis.

There were three independent variables: modifying factors, health belief dimensions, and public trust.

Participant characteristics were described using sociodemographic factors (age, sex, marital status, educa- tional level, living areas) and other potential components (individual income, social status, and self- reported health status). The self-reported individual income was divided into three levels using“2013 Family Income and Expenditure Statistics”conducted by the Directorate-General of Budget, Accounting and Statis- tics, Executive Yuan, Taiwan. The average monthly disposable income per person below $700 (close to the minimum wage) was low, and over $2000 was high.

Variables pertinent to the HBM were perceived susceptibility to influenza (two items), perceived severity (four items), perceived benefit (perception that preventative behavior could reduce the risk of influenza and be effective, two items), and cues to action (three items). Three scales were used to measure public trust.

Thefirst was trust level in authorities (the central government, local government, township administrative office, large-scale organizations, and experts separately). Other items included government action (three items) and political support (two items). (See Appen- dix.) Data were ranked using afive-point Likert scale (1¼strongly agree to 5 ¼strongly disagree). Higher scores indicated greater disagreement and distrust. A positive relationship between beliefs, trust, and preventative behavior was proposed. Those who are conscious of high health risks or fear serious consequences once infected and believe that diseases can be prevented through individual behaviors and trust in government and other authorities had a positive cor- relation with the scores of health behaviors. SPSS 21 was adopted to conduct statistical analyses.

2.3. Ethical consideration

Secondary data originally available from the Sur- vey Research Data Archive in Academia Sinica,

JOURNAL OF HEALTH RESEARCH 2023;37:430e438 431

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Taiwan, was used in the analyses. The dataset was publicly accessible for researchers after registration.

The survey protocol and informed consent were approved by the institutional review board.

3. Results

3.1. Participant descriptive statistics

About half of participants were men (50.9%), married (60.8%), had an education level of high school or below (52.1%), and lived in six municipalities or urban

areas. The mean age of the participants was 47 years.

More than half (59.5%) of the respondents reported good health but no routine exercise (56.8%). Among them, 71.0% and 47.6% had middle social status and middle income (Table 1).

The overall intention of all personal protective measures was between “sure” and “should do.”

Approximately 93.5% of participants implemented hand hygiene, 89.1% wore masks, and 85.8% said they would avoid public places where many people are gathered. Although getting the ﬂu vaccine was the least popular method, 77% agreed to take it (Table 2).

The HBM independent variables indicated that most respondents perceived they had a low infection probability (the average score of perceived susceptibility was 3.69). However, a higher number were concerned about the serious consequences once they became infected and would comply with the quarantine restriction (the perceived severity score averaged 1.7). In the perceived benefits variable, respondents attributed influenza to preventable behaviors that individuals should be responsible for (by delivering 2.84 points). For the cues to action variable, the moderate score (3.03) showed that they did not worry about being blamed for getting sick. Similarly, the government action dimension was middle-grade (3.23). For public trust factors, individuals were in a neutral po- sition toward government responsiveness and information sufficiency. Approximately 60% of the participants showed trust in the government, experts, and large-scale organizations. Among the different government levels, 71% had strong confidence in the township-level agencies. The proportion decreased to 43.1% in central government and was approximately equal to distrust.

3.2. Multiple linear regression model

To achieve a comprehensive understanding, we aggregated the four preventive behavior scores into a dependent variable and summed the ﬁve different trust object scores as a trust level variable. The multiple linear regression analysis indicated that perceived susceptibility, perceived severity, perceived beneﬁts, and trust level were predictable factors and remained positively correlated with taking action. Among these four variables, perceived severity had the largest

Table 1. Descriptive statistics (n¼2005).

Variables Number %

Sex Male 1020 50.9

Female 985 49.1

Age (years) 20 49 2.4

21e40 745 37.2

41e64 875 43.6

65 336 16.8

Education High School or below 990 52.1

College 769 40.5

Graduate School or above 140 7.4

Marriage Married 1217 60.8

Single 786 39.2

Living Area Six Municipalities (Urban) 1448 72.2

Others 557 27.8

Social Status High 70 3.6

Medium 1380 71.0

Low 495 25.4

Health Good 1201 59.5

General 582 29.1

Not good 229 11.4

Exercise Yes 846 42.6

No 1139 56.8

Individual Income High 222 11.7

Medium 905 47.6

Low 776 40.8

Trust in Central Gov Yes 772 43.1

Neutral 242 13.5

No 778 43.4

Trust in Local Gov Yes 1102 60.8

Neutral 237 13.1

No 474 26.1

Trust in Township Yes 1294 71.0

Neutral 243 13.3

No 286 15.7

Trust in Large Scale Organization

Yes 1193 68.3

Neutral 222 12.7

No 331 19.0

Trust in Experts Yes 912 55.8

Neutral 300 18.3

No 423 25.9

Table 2. Participants’protective measures during a pandemic.

Number Sure Should Uncertainty Rarely Never

Vaccination 1970 805 (40.9) 711 (36.1) 34 (1.7) 305 (15.5) 115 (5.8)

Mask-wearing 1995 1159 (58.1) 627 (31.4) 28 (1.4) 140 (7.0) 41 (2.1)

Hand hygiene 1996 1248 (62.5) 627 (31.4) 47 (2.4) 66 (3.3) 8 (0.4)

Avoid public place 1994 972 (48.7) 747 (37.5) 73 (3.7) 171 (8.6) 31 (1.6)

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standardized coefﬁcient value with precautions, followed by trust level (Table 3).

However, cues to action, government action, and political support were negative and non-signiﬁcant.

Higher individual income and regular exercise did not increase the intention to engage in healthy behaviors. Individuals living in urban areas and married had different health behaviors from those in

Table 3. Multiple linear regression of preventative behavior (n¼2005).

Variables Unstandardized

coefﬁcients

Standardized coefﬁcients 95%CI of B P-value *

B Std. Error b Lower Upper

(Constant) 2.77 0.92 0.98 4.57 0.003 **

HBM

Perceived susceptibility 0.16 0.04 0.10 0.07 0.24 0.001 ***

Perceived severity 0.36 0.04 0.27 0.29 0.43 0.001 ***

Perceived beneﬁts 0.13 0.05 0.08 0.04 0.22 0.003 **

Cues to action 0.01 0.05 0.01 0.09 0.08 0.844

Public Trust

Government action 0.05 0.03 0.04 0.11 0.02 0.134

Political support 0.05 0.04 0.03 0.13 0.04 0.301

Trust level 0.13 0.02 0.15 0.08 0.18 0.001 ***

Demographic

Gender (Male¼ref) 0.22 0.15 0.04 0.52 0.09 0.16

Age (years below 20¼ref)

21e40 0.49 0.43 0.09 0.36 1.34 0.256

41e64 0.40 0.46 0.07 0.51 1.30 0.391

Above 65 0.19 0.51 0.02 0.81 1.19 0.713

Education (High school or below¼ref)

College 0.18 0.17 0.03 0.52 0.16 0.289

Graduate school 0.36 0.30 0.04 0.95 0.22 0.223

Living area (Suburb¼ref) 0.51 0.18 0.08 0.86 0.17 0.004 **

Marriage (Single¼ref) 0.70 0.17 0.13 0.36 0.36 0.001 ***

Individual Income 0.04 0.03 0.05 0.09 0.01 0.123

Regular Exercise (No¼ref) 0.16 0.16 0.03 0.47 0.14 0.292

Notes:*p<0.05,**p<0.01,***p<0.001

R¼0.406, R-square¼0.164, adjusted R-square¼0.152, std. error of the estimate¼2.519, F change¼13.62

Table 4. Multiple logistic regression of four kinds of preventive behavior.

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suburbs and singles. The model identiﬁed only 15.2% of the variance explained by the inputs (adjusted R-square¼0.152).

3.3. Logistic regression model

Logistic regression analyses were used to further explore the associations between each precautionary measure and the constructs of the HBM and trust-related variables (Table 4). We grouped those with neutral and negative positions as reference- dependent and analyzed the respective inﬂuencing factors of the four behaviors.

The four multiple regression analyses showed no consistent outcomes. Three HBM factors and the trust level demonstrated signiﬁcant associations with adherence to at least one precautionary measure in the expected direction, whereas government action and political support showed a non-signiﬁ- cant association.

Perceived susceptibility, perceived severity, and degree of trust were significant predictors of both being vaccinated and wearing face masks. Perceived susceptibility and degree of trust were positively associated with proper handwashing. Perceived benefits showed their influence on avoiding crow- ded public places only.

In stratiﬁcation by each sociodemographic attri- bute, men and adults aged below 20 signiﬁcantly differed from women and minors in vaccination.

Women aged below 20 or above 64, married, with higher education, and living in urban areas had a higher face mask prevalence. Married women living in urban areas showed a stronger intent to stay away from public places compared with single men living in non-metropolitan areas. Individuals exercised regularly duringﬂu pandemics.

4. Discussion

This study examined residents' intention to use precautionary measures against the flu pandemic, one of ten global health threats but preventable diseases [16]. People were accustomed to seasonal influenza, and bore the health risk by voluntary choices of individuals in the past. However, with the COVID-19 spread over the past years, different governance systems have had marked effects on the pandemic responses and performance. The empirical data used in this study had both the intention of taking preventive measures and the assessment of trust. Hence, the comprehensive analysis was beneficial to a deeper understanding of individual health behaviors and insight knowledge of the governments’role.

We found that Taiwanese individuals highly accepted recommended preventions, irrespective of their social status or income level, compared with those who had negative attitudes toward vaccines and masks in some places [17]. Furthermore, participants were likely to adopt non-pharmaceutical methods. Vaccina- tion was the least preferred of the four measures.

Similar studies indicate that cognition, hygiene, habit, education, or government policy advocates exert a profound inﬂuence, especially in Asian areas [18].

Our analyses highlighted key factors and expla- nations associated with the uptake of individual protective actions against inﬂuenza (Fig. 1).

First, almost all HBM constructs demonstrated sig- niﬁcant differences, except for cues to action.

Perceived susceptibility and severity were the most influential factors. Consistent with the HBM theory and related evidence-based studies, these two threat perceptions show that individuals who believe they are prone to be infected or that such a situation will have dire consequences are more likely to engage in risk-avoiding behaviors [5e7]. Participants who perceived themselves as easily and seriously suscep- tible to influenza were more likely to accept the vaccine and wear face masks. However, we observed a limited but significant event in which the perceived benefits factor influenced individuals only to stay away from public places. This suggests that they avoid crowds based on their belief that they would be readily infected by others. Therefore, acting on personal benefits is better than collectively [19].

Another concern is how public trust affects individual behavior during a pandemic. We examined public trust through political support, government actions, and trust levels. A substantial number of representative surveys show that Taiwanese individuals who expressed high levels of trust in authorities were much more likely to take precautions and support vaccination, facemasks, and hand hygiene restrictions. Trust in government is widely considered a key determinant of citizens' compliance with public health policies, especially in times of crisis [20e22]. Those who focus on health systems and experts show that individuals who have a high level of trust in doctors or nurses are extremely likely to consider vaccines safe and accept them [23].

Regarding political trust, local trust is generally higher than national trust [24]. However, the authorities'trust level was the only significant factor in this dimension. Other factors, which were the government's ability to handle a flu pandemic (government action), reliable information, and risk communication (political support), showed no statistical differences. The diversity of findings might result from limited quantitative evidence, different

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definitions, and objects in trust investigations [25,26]. This study makes an important contribution to this field. The results suggest that local governments play a significant role in promoting the effi- cacy of risk communication and implementing wide-scale intervention strategies to enhance the voluntary adoption of preventive behavior.

Sex, age, education, and other socioeconomic variables might be influential predictors; however, the evidence is inconsistent and probably does not mean that these are the most important variables [19]. This study's results showed that married individuals living in a metropolis had a significantly higher odds ratio of compliance than those who were single and living in the suburbs. However, there were no differences between men and women in preventive measures. Higher education and income did not increase intention. The vulnerable older adult group, who had special offers and free vaccinations, showed no significant inclination toward preventive health behaviors. Furthermore, demographic variables have divergent results on different types of preventive behaviors. With a high proportion of all preventative behaviors, we con- jectured that most Taiwanese individuals have good public health consciousness. Therefore, researchers should focus on variables other than modifying factors and design different incentives to comply with distinct preventive measures practically.

Based on ourﬁndings, Taiwanese adopted different types of precautionary measures even though none of

these measures were enforced by law and no penalty was imposed for noncompliance. It had empirical support to the HBM factors and offered insight to the public trust. Especially after the pandemic panic, authorities also take extreme precautionary measures such as imposing quarantine and test the suspected cases, largely lockdowns instead of public awareness campaigns regarding the adoption of preventive measures. The relevant factors presented in the study help to establish public governance mechanism to prepare for a health crisis with stronger resilience or capacity.

5. Conclusion

Infectious diseases are increasing and pose threats due to the rise in greater global movement and interaction. Individuals who willingly comply with guid- ance to avoid risk can decrease their health burdens.

Hence, understanding the variables associated with preventative behavior would be helpful for governance and management during the pandemic. Inevi- tably, individuals must learn to live with viruses.

In this study, we proposed a solution aimed at addressing these risks as follows: (1) adopted the HBM and tested the validity of variables; (2) extended new variables, public trust, as a possible key determinant of healthy behavior; and (3) exhaustively explored the important predictive factors of perceived susceptibility, perceived severity, trust level, and public trust in the HBM. In

Fig. 1. Interaction effects between HBM constructs and public trust on preventive behaviors.

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summary, the study opens opportunities for devel- oping and enhancing conventional HBM, and ex- tends the concept by introducing the new factor of public trust. It is helpful for the government to take effective action at present.

Nevertheless, there are limitations that ought to be considered while interpreting the results. Firstly, Taiwan has faced unique crises and experiences with SARS, which might have prepared the government and citizens to respond to the pandemic promptly and cautiously. These results may not necessarily be applicable to other countries.

Furthermore, this survey was conducted ten years ago. We recommend more comparative research is needed to determine the differences that develop over time and provide a complete explanation. Also, longitudinal research can be more pertinent to explore public trust proposition.

Funding

This research did not receive any speciﬁc grant from funding agencies in the public, commercial, or not-for-proﬁt sectors.

Conﬂict of interest

The authors declare that there are no conﬂicts of interest.

Acknowledgment None.

Appendix. Questionnaire and related statistics

Domain Constructs Questionnaire Items Mean SD Constructs Mean Constructs SD

Health Belief Perceived Susceptibility

How likely do you think you will get infected with a new type of inﬂuenza?

3.69 0.925 3.69 0.881

How likely do you think it is that you will get infected with a new type of inﬂu- enza when you travel abroad for leisure or business?

3.67 1.267

Perceived Severity

How serious do you think it is to get infected with a new type of inﬂuenza?

1.82 0.85 1.7 0.54

If you have contact with people who get infected with a new type of inﬂu- enza, government ofﬁcials recommend that you stay home for at least 10 days.

Do you think you could do that?

1.67 0.979

Do you agree or disagree that the government should compel the isola- tion of people who get infected with a new type of inﬂuenza to protect people who are healthy?

1.83 0.87

Do you agree or disagree that the government should compel the screening of foreigners who are from the affected region where people get infected with a new type of inﬂuenza?

1.46 0.635

Perceived

Beneﬁts Do you think people who get infected with a new type of inﬂuenza had any ways to prevent getting it?

2.55 1.104 2.84 0.846

(continued on next page)

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(continued )

Do you think people who get infected with a new type of new inﬂuenza are responsible for their infection?

3.11 1.04

Cues to Action

If you get infected with a new type of inﬂuenza, would you let your neighbor know about this fact?

3.63 0.787 3.03 0.594

Do you think people who get infected with a new type of inﬂuenza will be condemned by others?

3.01 1.228

Do you think that media reports on new types of inﬂuenza are exaggerated?

2.42 0.824

Public Trust Government Action

Do you think the government fully informs the public regarding information about a new type of inﬂuenza?

2.87 1.095 3.23 0.808

Do you worry the government might hide any information about a new type of inﬂuenza?

3.78 1.112

If an epidemic of a new type of inﬂuenza occurs in Taiwan, do you think the government has the ability to manage it immediately?

3.02 1.166

Political Support The government mostly consider things (e.g., poli- tics or economy) that are unrelated to the medical profession when man- aging the issue of new types of inﬂuenza. Do you agree that the government can use such perspectives to handle the issue of new types of inﬂuenza?

3.58 1.1 3.48 0.843

Since Taiwan is unable to be a member of the World Health Organization, we cannot get the most updated information about a new type of inﬂu- enza. Because of that, people are more likely to get infected with a new type of inﬂuenza. Do you agree with this statement?

3.39 1.137

Trust Level Overall, how much do you trust each of the following?

Central government

2 0.93 1.66 0.558

The local government (county or municipal)

1.65 0.866

(continued on next page)

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100523.

(continued )

Township (Town, City, District) administrative ofﬁce

1.45 0.749

Large civil organizations or groups

1.51 0.793

Experts or scholars 1.7 0.853

STUDY