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Impact of COVID-19 Risk Perception on Residents’ Behavioural Intention towards Forest Therapy Tourism

sustainability

Article

Impact of COVID-19 Risk Perception on Residents’ Behavioural

Intention towards Forest Therapy Tourism

Yanjing Gao * and Lijun Chen

School of Geography and Tourism, Huanggang Normal University, Huanggang 438000, China

* Correspondence: gyjxiong@126.com; Tel.: +86-187-7251-9953

Abstract: Risk perception has an important inﬂuence on tourism decision-making behaviour. Based

on the extended Theory of Planned Behaviour, we examine the effect of COVID-19 risk perception

on tourists’ behavioural intentions towards forest therapy tourism. A questionnaire survey was

conducted during the pandemic. Based on structural equation modelling (SEM), our evidence shows

that cognitive risk perception positively and signiﬁcantly inﬂuenced subjective norms, while affec-

tive risk perception positively and signiﬁcantly inﬂuenced attitudes. Subjective norms mediated

perceived risk perception and behavioural intentions, while attitudes mediated emotional risk per-

ception and behavioural intentions. Gender partially moderated perceived behavioural control and

behavioural intentions. Finally, this study proposes corresponding management countermeasures of

great practical importance in promoting the development of forest recreation tourism.

Keywords: the extended theory of planned behaviour; COVID-19; risk perception; forest therapy tourism

Citation: Gao, Y.; Chen, L. Impact of

COVID-19 Risk Perception on

Residents’ Behavioural Intention

towards Forest Therapy Tourism.

Sustainability 2022, 14, 11590. https://

doi.org/10.3390/su141811590

Academic Editor: Anna Mazzi

Received: 26 July 2022

Accepted: 13 September 2022

Published: 15 September 2022

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4.0/).

1. Introduction

The study of the relationship between risk perception and tourism behaviour has been

one of the hot topics in tourism behaviour research in recent years [1–5]. Risk perception

has an important inﬂuence on individuals’ attitudes and behaviours; with high perceived

risk, individuals may adopt a conservative avoidance attitude and avoid certain risky

behaviours, and conversely, will tend to certain attitudes and behaviours [6–10]. The

current COVID-19 epidemic is still a global pandemic, and people’s awareness of risk

avoidance and health awareness is increasing [11]. Relevant supply companies are also

actively taking safety measures to avoid the risks associated with the epidemic and to

facilitate rapid consumer decision-making [12,13]. The epidemic has prompted a change in

people’s preferences for transportation modes and travel destination choices [14–19], with

low-density travel options such as close-in suburban tourism, rural tourism, ecotourism,

and forest therapy tourism being favoured [20–25].

Forest therapy has been a very popular health experience model in recent years,

which is a business model for integrating forestry and wellness with good physiological

and psychological relaxation effects [26]. Currently, research on forest therapy tourism

focuses on the value and therapeutic effects of forest therapy tourism [27–30], forest therapy

tourism base construction [31,32], product development [33], potential evaluation [34], and

forest therapy tourism behaviour [35,36]. According to the health belief model, people

who perceive their health to be at high risk tend to increase their participation in health-

protective behaviours to cope with the risk [37–39]. There are no studies on whether

perceived risk perceptions and emotional risk perceptions of COVID-19 affect potential

tourists’ willingness to engage in forest therapy tourism during an epidemic, and this study

attempts to explore this issue.

The objectives of this study are to construct a model of the relationship between

COVID-19 risk perception and behavioural intention for forest therapy tourism and to

explore whether COVID-19 risk perception can facilitate potential tourists’ behavioural

Sustainability 2022, 14, 11590. https://doi.org/10.3390/su141811590

https://www.mdpi.com/journal/sustainability

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intention for forest therapy tourism. We also aim to test whether attitudes, subjective

norms, and perceptual behavioural control mediate the relationship between COVID-19

risk perception and potential tourists’ behavioural intention. The results of this study will

extend the theoretical model of planned behaviour by introducing cognitive risk perception

and affective risk perception to better understand potential tourists’ risk perception of

COVID-19 and how it affects their behavioural intention, thus enriching the research related

to behavioural intention towards forest therapy tourism. The results also provide useful

hints for destinations to strengthen risk management of epidemic prevention and control,

establish a good safety image, and do a good job of promotion and marketing.

This article is structured as follows: ﬁrst, we conducted a literature review on forest

therapy tourism, theory of planned behaviour, and risk perception, as well as proposed

relevant hypotheses for this study and constructed a conceptual model. Second, the data

sources, sample collection, and research instruments of this study are presented. We

validated the model using Amos 24.0 software of IBM(New York, NY, USA) discussed the

results, and presented the theoretical and practical insights of this study. Finally, we discuss

the shortcomings and provide directions for future in-depth research.

2. Theoretical Framework and Research Hypotheses

2.1. Forest Therapy Tourism

According to Mueller and Kaufmann, therapy tourism consists of the effort to obtain

health through a series of tourism activities [40]. There have been many studies on forest

therapy tourism, and these studies have focused on therapy effects [41–43], potential assess-

ment [34,44], products [45,46], behaviorsbehaviours [35,36], and base construction [47]. The

vast majority of scholars understand the connotation of forest therapy from two perspec-

tives: ﬁrst, the therapeutic perspective, which focuses on the treatment of diseases [48,49];

and second, the therapy perspective, which focuses on relaxation, leisure, and escape from

the routine [50,51]. Li Jiren et al., constructed an index system and used hierarchical analysis

and a fuzzy comprehensive evaluation method to evaluate the development potential [52].

For therapy resources, scholars have explored the evaluation system and methods for the

suitability of forest therapy resources based on therapy functions and therapy services.

Liu Panyang et al., constructed an index system for calculating the evaluation value of

four types of therapy activities, such as physiological health maintenance, psychological

regulation, sports and ﬁtness, and science education [53]. Due to the different resource

endowments of forest therapy tourism, there is no ﬁxed model for development, and the

exploration of forest therapy tourism products is mainly based on the analysis of speciﬁc

cases and problems to propose the corresponding development model or construction

path [54]. Exploring the factors and mechanisms affecting forest therapy tourism behaviour

is important for constructing forest therapy tourism bases and improving the diversity

of destination product supply. Zhao J & An Y. found that the perceived beneﬁts of forest

therapy tourism and the perceived severity of COVID-19 had a positive effect on the be-

havioural meaning of forest therapy tourism and attitudes mediated health beliefs and

behavioural intentions, while perceived barriers to forest therapy tourism and perceived

susceptibility to COVID-19 were not signiﬁcant factors [35].

Risk perception originates from the category of psychology and refers to the psycho-

logical feelings and perceptions of individuals about various objective risks [55]. People’s

perceptions of risk inﬂuence their behavioural decisions to adopt risk-averse measures or

behaviours [56], and therefore, risk is an important antecedent for tourists when making

destination choices. The COVID-19 epidemic has brought many uncertain risk factors to

society, prompting people to re-examine their lifestyles and travel styles. People are more

interested in health tourism forms such as medical tourism, contact-free tourism, and nature

tourism [23,57–59]. Does COVID-19 risk perception affect residents’ intention toward forest

therapy tourism, and what are the pathways? This study focuses on these questions.

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2.2. Theory of Planned Behaviour

The theory of Planned Behavior was proposed by Icek Ajzen [60] as an extension

and complement to the Theory of Reasoned Action (TRA) [61]. Ajzen found that human

behaviour is not 100% voluntary but is controlled. The model consists of ﬁve elements:

attitudes; subjective norms; perceived behaviour control; behavioural intentions; and be-

haviour. Ajzen argues that all factors that may inﬂuence behaviour are indirectly inﬂuenced

by behavioural intentions. Behavioural intentions are inﬂuenced by three related factors:

the individual’s attitudes, i.e., their “Attitude” toward adopting a particular behaviour;

external “subjective norms,” i.e., “subjective norms” that affect the individual’s ability to

adopt a particular behaviour; and the last is derived from “perceived behavioural control”.

In general, the more positive an individual’s attitude toward a behaviour, the stronger

the individual’s behavioural intention, and the more positive the subjective norm for be-

haviour, the stronger the individual’s behavioural intention. The more positive the attitude

and subjective norm and the stronger the perceived behavioural control, the stronger the

individual’s behavioural intention will be.

The theory of planned behaviour has been widely used in various disciplines, such as

education, psychology, consumer behaviour, and tourism [62–66]. In the ﬁeld of tourism,

it is mainly applied to behavioural research aspects, such as tourists’ environmentally

responsible behaviour, low-carbon tourism behaviour, rural tourism behaviour, ecotourism

behaviour and study tour behaviour [67–69]. Many scholars have added other variables to

obtain better explanatory power. For example, variables such as tourism experience, epi-

demic effects and environmental beliefs have been added to the model to better understand

virtual tourism behaviour [70].

Behavioural intention towards forest therapy tourism is the degree of effort that

tourists are willing to make to realise forest therapy tourism after learning about it. Atti-

tudes towards forest therapy tourism are positive or negative, i.e., attitudes conceptualised

by individuals in evaluating forest therapy tourism. Subjective norms refer to the social

pressures tourists feel when deciding whether to participate in forest therapy tourism,

which may come from family, peers, friends, etc. The stronger the positive subjective

norms, the stronger the intention to engage in certain behaviours. Perceived behavioural

control refers to the inﬂuence of the traveller’s past experiences and anticipated future

obstacles on their behavioural intentions, such as the time, money, and hardware facili-

ties for forest therapy that the traveller possesses. The more resources the traveller has

and the fewer the anticipated barriers, the greater the perceived behavioural control and

the stronger the motivation for behavioural intentions. Based on the above analysis, we

propose the following hypothesis.

Hypothesis H1 (H1). Attitude has a signiﬁcant positive effect on behavioural intentions towards

forest therapy tourism.

Hypothesis H2 (H2). Subjective norms have a signiﬁcant positive effect on behavioural intentions

towards forest therapy tourism.

Hypothesis H3 (H3). Perceived behavioural control has a signiﬁcant positive effect on behavioural

intentions towards forest therapy tourism.

2.3. Risk Perception

Risk perception originates in psychology and refers to an individual’s psychological

perception of various objective risks. The existence of objective risks in the external envi-

ronment is complex and varied, and the forms of risk perception are necessarily complex

and varied when ﬁltered through the subjectivity of individuals. Hence there are also

diverse perspectives on the study of risk perceptions [71–75]. For example, Kaplan & Ja-

coby classiﬁed consumers’ perceived risk into ﬁve categories: ﬁnancial risk, functional risk,

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physical risk, psychosocial risk and social risk [76]. Other scholars have further validated

the existence of six types of risk dimensions, such as ﬁnancial risk and functional risk [77].

Tourism risk is deﬁned as the possibility that a traveller will suffer various misfortunes

during the journey or at the tourist destination [78]. Tourism services are riskier than

physical goods and therefore perceived risk is persuasive in explaining consumer travel

behaviour and is an important factor inﬂuencing travel decisions. Many scholars have

dissected the dimensions of tourism risk perception; for example, Cui, F. et al. argue that

tourism risk perception includes subjective and objective factors. Subjective factors refer to

physical characteristics and mental processes, while objective factors include physical risk,

economic risk, equipment risk, social risk, psychological risk, time risk, and opportunity

loss [79]. Roehl et al. identiﬁed three different risk groups. They summarised seven

dimensions of perceived tourism risk, namely facility risk, ﬁnancial risk, psychological risk,

satisfaction risk, time risk, psychological risk, and social risk [80]. Xu Hui et al., found that

the consumer tourism risk perception dimensions included nine dimensions of physical

risk, functional risk, ﬁnancial risk, communication risk, psychological risk, social risk,

service risk, facility risk, and communication risk [81].

Most of the above studies understand risk perception in terms of the cognitive risk

dimension, while fewer studies understand risk in terms of emotional risk [82,83]. Cogni-

tive risk perception refers to an individual’s perception of the susceptibility to a particular

risk and the severity of the infection [84]. In contrast, affective risk perception refers to

the concern, anxiety or fear that the risk will cause harm to the individual [85]. Some

scholars have usefully explored cognitive and affective risk perceptions. For example,

Minsun Shim & Myoungsoon You examined the intention to consume food associated with

an outbreak in terms of both cognitive risk perception and affective risk perception, both

independently and jointly predicted [86]. COVID-19 is a global public health event, with

daily announcements of the number of conﬁrmed diagnoses and deaths, leading the public

to form an overall risk perception rather than speciﬁc risk dimensions. Emotional percep-

tions of risk, such as worry, anxiety and fear, may often lead to behaviours different from

perceived risk perceptions [87]. The impact of emotional risk perceptions may be greater

than the impact of cognitive risk perceptions, especially when the risk type is classiﬁed as

high fear risk [88]. Due to the highly contagious nature of COVID-19 and measures such

as isolation following illness, individuals will experience more emotions such as worry,

anxiety and fear about the infectious disease, which may lead to behavioural changes in

individuals. Therefore, this study will explore the perceived risk of COVID-19 among

travellers along two dimensions: cognitive risk perception and affective risk perception.

The level of risk perception directly inﬂuences the choice of destination; the higher

the perceived risk of a destination, the more likely travellers will avoid it. The higher

the level of anxiety and risk among travellers, the more likely they will feel that the

environment is unsafe and evacuate [22]. According to previous research on health belief

models, risk perceptions can promote increased health protective attitudes and behavioural

intentions [89,90]. Therefore, individuals’ attitudes and behavioural intentions toward

healthy forms of tourism, such as rural tourism and forest therapy tourism, increase in the

context of the COVID-19 pandemic [91,92]. In addition, the improvement of forest therapy

tourism facilities has contributed to the possibility that tourists may be willing to give more

time and resources to participate because of the impact of the epidemic. In summary, the

following hypotheses are proposed.

Hypothesis H4a (H4a). Cognitive risk perception has a signiﬁcant positive impact on attitudes

towards forest therapy tourism.

Hypothesis H4b (H4b). Affective risk perception has a signiﬁcant positive impact on attitudes

towards forest therapy tourism.

Hypothesis H5a (H5a). Cognitive risk perception has a significant positive effect on subjective norms.

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Hypothesis H5b (H5b). Affective risk perception has a significant positive effect on subjective norms.

Hypothesis H6a (H6a). Cognitive risk perception has a signiﬁcant positive effect on perceptual

behavioural control.

Hypothesis H6b (H6b). Affective risk perception has a signiﬁcant positive effect on perceptual

behavioural control.

Hypothesis H7a (H7a). Cognitive risk perception has a signiﬁcant positive effect on behavioural

intentions for forest therapy tourism.

Hypothesis H7b (H7b). Affective risk perception has a signiﬁcant positive effect on behavioural

intentions for forest therapy tourism.

2.4. Analysis of Mediating Effects and Cohort Differences

Previous studies have shown that attitudes, subjective norms and perceived be-

havioural control mediate between variables [93–96]. In China, due to the persistence

of COVID-19, people are paying more attention to health tourism, and more and more

people are joining forest therapy tourism. The atmosphere may promote more people to

participate. The government has introduced various policies and measures to promote

the development of forest therapy tourism. Relevant enterprises are actively improving

the supply of forest therapy tourism, making more products available to tourists and

participation easier. Against this background, we put forward the following hypothesis.

Hypothesis H8 (H8). Attitude mediates risk perception (cognitive/emotional) and behavioural

intentions towards forest therapy tourism.

Hypothesis H9 (H9). Subjective norms mediate risk perception (cognitive/emotional) and be-

havioural intentions towards forest therapy tourism.

Hypothesis H10 (H10). Perceived behavioural control is a signiﬁcant mediator between risk

perception (cognitive/emotional) and behavioural intentions for forest recreation.

Previous studies have shown that demographic characteristics have a signiﬁcant rela-

tionship with consumer risk perceptions, inﬂuencing their behavioural intentions [82]. In

particular, gender is often used as a meaningful variable inﬂuencing the way tourists obtain

information as well as their travel preferences, travel spending, and other behaviours [97].

COVID-19 has also been studied by several scholars to examine the behavioural patterns

of residents of different genders. For example, the ﬁndings of Vincenzo Galasso et al. on

Gender differences in COVID-19 attitudes and behavior showed that women are more

likely to perceive COVID-19 as a very serious health problem, to agree to restrictive public

policy measures, and to comply with them [98]. Therefore, we hypothesised that gender

had a moderating role in the constructed relationship.

Hypothesis H11 (H11). Male and female participants differ in the relationships between risk

perception, attitudes, subjective norms, perceived behavioural control and behavioural intentions

towards forest therapy tourism.

2.5. Theoretical Framework

This study adds COVID-19 risk perception into the eTPB to construct a model of the

inﬂuence mechanism of behavioural intention towards forest therapy tourism (Figure 1).

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Figure 1. Proposed research framework.

3. Methodology

3.1. Research Instrument and Data Collection

The population of this study is adults aged 20 years and above, mainly because this

group has better ﬁnancial means to undertake tourism. The data are from ﬁeld research

conducted by the subject team in Hubei from October 2021. The main reasons for selecting

Hubei Province were, ﬁrst, because the COVID-19 epidemic ﬁrst started in Hubei, which

suffered a substantial loss of life and economic loss due to the limited knowledge of

COVID-19 and local medical conditions at the time. Second, all 17 prefecture-level cities

(directly administered counties) in Hubei Province had cases of COVID-19. Third, Hubei

Province has one of the better government policies on epidemic prevention and residents’

awareness of personal protection in the country, making it more likely to engage in a

healthy and ecological approach to tourism. Fourth, Hubei Province is uniquely positioned

for forest recreation, which allows residents to choose this form of tourism.

The survey used random sampling and convenience sampling methods. Three cities

were randomly selected from 17 cities in Hubei Province. Three researchers in each city

randomly distributed 210 questionnaires in city parks and shopping malls. A total of

427 valid questionnaires were obtained after eliminating invalid questionnaires, such as

those completed for too short a period and those with the same answers for two consecutive

variables, according to the research theme and relevant indicators.

The design of the scale drew on the ﬁndings of Bae, S.Y. and Chang, P.J. [59]. During

the scale design process, preresearch questionnaires were distributed in September 2021 to

ensure quality, accuracy, and applicability. Questions that were ambiguous or not clearly

expressed were corrected through analysis of the preresearch questionnaire. The ofﬁcial

questionnaire was designed using a 5-point Likert scale, with a scale of 1–5 representing

‘strongly disagree’ to ‘strongly agree’. The questionnaire consists of two parts, one with

basic information about the respondent and the other with COVID-19 risk perceptions and

items related to attitudes, subjective norms, perceptual behavioural control, and intentions

towards forest recreation tourism.

Using covariance-based structural equation modelling (CB-SEM), we aimed to test

the effect of COVID-19 risk perception on intention to travel for forest recreation and

whether there is a mediating effect of certain variables, and to explore differences between

gender groups.

We used IBM SPSS 23.0 and Amos 24.0 software to analyse the data (IBM, New York,

NY, USA). To examine the quality and structure of the variables, exploratory factor anal-

ysis, conﬁrmatory factor analysis (CFA), and structural equation modelling (SEM) were

implemented to examine the causal relationships between the constructs. A bootstrapping

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approach was then used to test the mediating role of attitudes, subjective planning and

perceived behavioural control. Finally, differences between gender cohorts were examined.

3.2. Data Analysis (CB-SEM)

Structural equation modelling is widely used in a variety of disciplines, particularly in

the social sciences [99]. Structural equation modelling allows the researcher to statistically

examine “whether a hypothesised model is consistent with the data collected to reﬂect

[the] theory” [100] (p. 34). Structural models include covariance-based SEM (CB-SEM)

and variance-based SEM (PLS-SEM) [101]. CB-SEM emphasises total ﬁtness, mainly by

testing the applicability of the theory, and is suitable for the testing of theoretical models

(validation). PLS-SEM, the PLS component, designed primarily to explain variance (de-

tecting whether causality is signiﬁcantly related), is suitable for performing theoretical

model building (exploratory) and can be used to validate the inferred causal relationships

explored. Given that this study is primarily a validation based on an existing model,

CB-SEM was used.

4. Results

4.1. The Social-Demographic Characteristics of the Respondents

Table 1 displays the demographic information of the participants. Among the recov-

ered samples, 253 were female, accounting for 59.3%. The sample covered age groups above

20 years old, with 56.2% of respondents aged 31–50 and 29.3% unmarried, representing

125 full-time college students. The majority of the respondents had attained a high school

degree or above, with a proportion of 80.6%. Approximately 73.5% of the respondents’

monthly average income was above 3000 RMB (approximately 472 USD).

Table 1. Demographic information (n = 427).

Gender

male

female

174

40.7

253

59.3

20–30

132

30.9

31–40

19.9

Age

41–50

155

36.3

51–60

10.1

60 above

2.8

middle school below

19.4

high school and secondary school

134

31.4

Education

college and undergraduate

175

41.0

master’s degree and above

8.2

Marital status

married

single

302

70.7

125

29.3

Monthly average

income (RMB)

3000 and below

3001–5000

5001–8000

8001–10,000

10,001 and above

Note: RMB = Renminbi, USD1 = 6.354 RMB.

113

26.5

158

37.0

22.2

6.3

8.0

4.2. Reliability and Validity Test

Quality and structural analysis of variables refer mainly to the testing of the reliability

and validity of variables to determine whether the sample data are reliable and valid.

4.2.1. Exploratory Factor Analysis

Before conducting exploratory factor analysis, the KMO value and Bartlett’s sphericity

test should also be calculated for the sample data to determine whether the data are suitable

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for factor analysis. The results show that the KMO is 0.859, the approximate chi-square

is 5004.167, the degrees of freedom is 231, and the probability of signiﬁcant value is less

than 0.001, indicating that the data are suitable for exploratory factor analysis. Using the

principal component analysis method to extract the common factors and the maximum

variance method for factor rotation, the results of the exploratory factor analysis for each

variable were calculated, as shown in Table 2. The six extracted principal components

explained 71.248% of the cumulative total variance of all variables. Based on the content

and signiﬁcance of the question items contained in each component, combined with the

analysis of relevant literature above, the six principal components were named as cognitive

risk perception, affective risk perception, attitude subjective norms, perceived behavioural

control, and behavioural intention.

Table 2. Total Variance Explained and Rotated Component Matrix.

Constructs

Items

CR1

Cognitive risk perception

CR2

CR3

AR1

AR2

Affective risk perception

AR3

AR4

AR5

Attitude

Subjective norms

Perceived behavioural control

behavioural intention

Cumulative Total Variance Explained

0.822

0.870

0.800

0.724

0.734

15.407

0.782

0.765

0.764

0.766

29.053

0.775

0.806

0.809

0.701

42.165

0.757

0.865

0.826

53.409

0.860

0.837

0.643

62.826

0.558

0.839

0.875

71.248

4.2.2. Conﬁrmatory Factor Analysis

Before conducting the conﬁrmatory factor analysis, the model ﬁt was ﬁrst tested to

ensure that the model had a good overall ﬁt. The overall ﬁt of the model showed a good ﬁt

with χ2 = 488.882, df = 196, p < 0.001, χ2/df = 2.494, RMSEA = 0.059, CFI = 0.940, IFI = 0.940,

TLI = 0.929. The results showed that the Cronbach’s for each question item lay between

0.666–0.882, which was greater than the acceptable value of 0.6. The combined reliability

CR values were all greater than 0.7, and the average extracted variance (AVE) values were

largely greater than 0.45, thus providing good reliability (Table 3). The discriminant test for

differential validity between the variables followed Fornell and Larcker’s recommendation

that the square root of the AVE value for each latent variable should be greater than

the correlation coefﬁcient between the variables [102]. The square roots of the AVEs

were all greater than the correlation coefﬁcients between the variables, and therefore, the

discriminant validity between the latent variables was good (Table 4).

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Table 3. Results of conﬁrmatory factor analysis.

Constructs

Cognitive risk

perception

Affective risk

perception

Attitude

Subjective norms

Perceived

behavioural

control

behavioural

intention

Items

Std. Factor

Overall, the likelihood of having a

COVID-19 infection was high

There is a high chance of COVID-19 infection

compared to other diseases

There is a high chance of dying from COVID-19

0.821

0.83

0.585

I was afraid that I would get infected

I worry about infecting my family and friends

I fear that COVID-19 will happen in my area

I am concerned that COVID-19 will

become a health issue

I fear that COVID-19 hits every year

0.808

0.852

0.765

0.683

0.67

Forest health care tourism is an

active and healthy way of tourism

Forest health tourism can effectively relax

It is pleasant to participate in forest

health care and tourism activities

0.75

0.903

0.884

Many people are doing forest

health care tourism now

The government supports

forest health care tourism

The media is promoting forest health care tourism

Important relatives and friends

around me also support me in participating

in the forest health care tourism

0.776

0.859

0.843

0.758

At present, it is difﬁcult to ﬁnd the right forest

health care base for tourism

I do not have enough time to carry out forest

health care tourism at present

I have no good economic conditions to carry out

forest health care tourism at present

0.545

0.653

0.806

I am willing to participate in the forest

health care tourism

I am willing to spend more money for the services

or projects in the forest health care tourism base

I will encourage other relatives and friends to

participate in the forest health care tourism

I am willing to actively promote

forest health care tourism

0.811

0.715

0.863

0.769

Note: CFI = 0.940, IFI = 0.940, TLI = 0.929, RMSEA = 0.059.

Cronbach’s α

0.777

0.865

0.877

0.882

0.666

0.866

0.794

0.871

0.884

0.712

0.870

AVE

0.568

0.576

0.720

0.656

0.458

0.626

Table 4. Correlation and discriminant validity analysis of the main variables.

Cognitive risk

perception

Affective risk

perception

Attitude

Subjective norms

Cognitive Risk Affective Risk

Perception

Attitude

0.754

0.494

0.184

0.287

0.759

0.253

0.113

0.849

0.619

Subjective

Norms

Perceived

Behavioural

Control

Behavioural

Intention

0.810

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Table 4. Cont.

Perceived

behavioural control

Behavioural intention

Cognitive Risk Affective Risk

Perception

Attitude

Subjective

Norms

Perceived

Behavioural

Control

0.097

0.123

0.170

0.138

0.166

0.090

0.545

0.735

Note: The bold numbers on the diagonal are the square root of the AVE.

0.677

0.197

Behavioural

Intention

0.791

4.3. Path Analysis

Next, SEM was used to conduct veriﬁcation (Figure 2). The model ﬁt indices for the

structural model were RMSEA = 0.072, CFI = 0.909, NFI = 0.874, TLI = 0.894, demonstrating

a good ﬁt to the data. Cognitive risk perception exhibited a signiﬁcantly positive inﬂuence

on subjective norms (β = 0.320, p < 0.001), supporting H5a, but it did not show signiﬁcant

effects on attitude and perceived behavioural control, rejecting H4a and H6a. Affective

risk perception exhibited a signiﬁcantly positive inﬂuence on attitude (β = 0.188, p < 0.01),

supporting H4b, whereas it did not affect subjective norms and perceived behavioural

control, rejecting H5b and H6b. Both cognitive risk perception and affective risk perception

had no signiﬁca-nt positive inﬂuence on behavioural intention, rejecting H7a and H7b.

Attitude, subjective norms and perceived behavioural control had positive inﬂuences

on behavioural intention (β = 0.204, p < 0.001; β = 0.678, p < 0.001; β = 0.103, p < 0.05),

supporting H5, H6, and H7 (Figure 2).

Figure 2. Standard estimates of structural equation model path analysis. CFI = 0.909, NFI = 0.874,

TLI = 0.894, RMSEA = 0.072; * p < 0.05, ** p < 0.01, *** p < 0.001.

4.4. Mediation Test

After the model was established, this study used bootstrapping to evaluate the medi-

ating role of attitude and subjective norms, setting a replicate sample of 5000 and using

maximum likelihood estimation with ﬁxed conﬁdence intervals (PC) and bias-corrected

conﬁdence intervals (BC) of 95%. Table 5 indicates that among the associations in affective

risk perception, cognitive risk perception, attitude, subjective norms, and intention, no

zero existed between the lower and upper bounds of the indirect effect. Additionally,

estimates of the indirect effect were not zero. Therefore, attitude exhibited a mediating

effect on the relationship between affective risk perception and behavioural intention,

partially supporting H8. In addition, subjective norms also acted as a signiﬁcant mediator

between cognitive risk perception and behavioural intention, partially supporting H9. But

Sustainability 2022, 14, 11590

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perceived behavioural control was not a signiﬁcant mediator between risk perception and

behavioural intention, rejecting H10.

Table 5. Bootstrapping effects and 95% conﬁdence intervals (CI).

Pathways

Estimates

Affective risk perception→Attitude→behavioural intention

Cognitive risk perception→subjective norms→behavioural intention

0.058

0.150

0.025

0.035

Bis-Corrected 95%CI

Lower Upper

0.019

0.092

0.123

0.23

0.008

0.000

subjective norms

Attitude

behavioural intention

4.5. Multi-Group Analysis

To examine the potential moderating effect of gender, multi-group analyses were con-

ducted to compare differences in the coefﬁcients of the corresponding structural paths for

males and females using the CR (Critical ratios for differences between parameters) value.

When the CR value > 1.96, there is a signiﬁcant difference between the two groups [62].

The comparison of results by gender, reported in Table 6, indicates that the path

coefﬁcients from perceived behavioural control to behavioural intention were signiﬁcantly

different between males and females. The impact of perceived behavioural control on

behavioural intention among female participants was much stronger than among males.

Thus, H11 was partially conﬁrmed.

Table 6. Critical Ratios for Differences between Parameters (Measurement weights).

Male

Estimate

Female

Estimate

CR Value

<—

Cognitive risk perception

0.398

<—

Affective risk perception

0.254

<—

Attitude

0.153

<—

subjective norms

0.779

<—

Perceived behavioural control

−0.069

0.206

0.263

0.197

0.591

0.178

−1.776

−0.661

0.508

−1.547

2.37

5. Discussion

Based on the theory of planned behaviour, this study examines the inﬂuence of

risk perception on behavioural intentions towards forest therapy tourism during the

COVID-19 pandemic.

First, the results showed that attitudes towards forest therapy tourism were positively

but nonsigniﬁcantly associated with perceptions of cognitive risk, while they were sig-

niﬁcantly and positively associated with perceptions of emotional risk. That is, positive

attitudes towards forest therapy tourism were not based on the threat of disease but on

personal concerns about contracting COVID-19 for themselves and their families. This

result is consistent with Vindegaard N & Benros M E [103], who found that the epidemic

increased the population’s suspected psychological disorders and had important emotional

effects, producing anxiety, depression, or more severe mental disorders, among other out-

comes. These psychological disorders may not stem from actual infection or death but from

the individual’s fear of possible social stigma, discrimination, etc. During the epidemic,

Chinese people became anxious, probably not because of the harm caused by the disease

itself but from the psychological changes brought about by disclosing personal information

and comments from society. Thus, the COVID-19 pandemic caused individuals who had

not considered forest therapy tourism to change their attitudes, possibly due to emotional

concerns in this context.

Second, perceived risk perceptions positively inﬂuence the subjective norms of forest

therapy tourism. When a particular disease poses a threat to the physical health of residents,

people may perceive that forest therapy tourism will be supported by their group members.

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This attitude is consistent with the ﬁndings of Zhao Jing [35], which conﬁrmed the inﬂuence

of the perceived risk of infectious diseases on residents’ willingness to engage in forest

therapy tourism. In China, the government, businesses and society are actively promoting

forest recreation tourism due to the epidemic, and they may believe that participation in

outdoor forest therapy tourism helps to ensure social safety distances and healthy physical

and mental development, which is in fact the case [104]. Thus, the perceived risk of

COVID-19 has led to more support for forest therapy tourism from respondents.

Third, there was no signiﬁcant effect of COVID-19 risk perception on behavioural

intentions towards forest therapy tourism. This ﬁnding is not entirely consistent with the

ﬁndings of Zhao Jing [35]. The results showed that COVID-19 cognitive risk and emotional

risk perceptions had a negative but nonsigniﬁcant effect on a willingness to engage in

forest therapy tourism. This ﬁnding indicates that forest therapy tourism behaviour is

somewhat inhibited by the COVID-19 epidemic, but not signiﬁcantly. The reason for this

result may be that the irregular outbreaks of the epidemic in scattered locations in China

have increased the risk perception of the population, and coupled with the government’s

tourism control measures, the willingness of the population to travel has been dampened.

However, the Chinese government’s rapid and robust “dynamic zero infection” policy has

given residents some conﬁdence to travel, so the effect is insigniﬁcant.

Fourth, there is a signiﬁcant mediating role of attitude between perceived emotional

risk and behavioural intentions, which is consistent with the ﬁndings of Zhao Li, Wangbing

Liang et al. [105]. Individuals with perceived emotional risk during the ongoing COVID-19

epidemic have increased positive attitudes towards forest therapy tourism, leading to

more behavioural intentions. Currently, COVID-19 outbreaks are scattered irregularly in

China, and the ongoing epidemic has put considerable pressure on the state, companies,

and individuals. Although the demand for tourism has been dampened by government

policies, people have been looking for ways to travel that are stress relieving and relatively

safe, hence the popularity of forest therapy tourism as a form of health tourism and the

ability to maintain some social distance.

Fifth, subjective norms have a signiﬁcant mediating role between risk perception and

behavioural intentions. During the COVID-19 pandemic in China, the government took

strong preventive measures, such as “dynamic zero infection”, wearing masks, keeping

social distance, and limiting the ﬂow of people in scenic spots, which provided protections

that allowed people to travel outside. At the same time, therapyp tourism was used as a

health-promoting approach to travel. The perceived risk of COVID-19, therefore, leads

people to believe that their group members approve of forest therapy tourism, which

encourages people to take part in it.

Finally, attitudes, subjective norms, and perceived behavioural control exerted a

positive inﬂuence on behavioural intentions. This result is consistent with the ﬁndings of

a large body of previous research on the theory of planned behaviour [106]. Individuals’

behavioural intentions towards forest therapy tourism were inﬂuenced by behavioural

attitudes, group members’ approval, and their perceived ability to participate in forest

therapy tourism. Gender had a signiﬁcant moderating effect on the relationship between

perceived behavioural control and behavioural intentions. Perceptual behavioural control

and behavioural intentions were positively correlated for females, indicating that greater

perceptual behavioural control was associated with greater behavioural intentions to engage

in forest therapy tourism, while the correlation was negative in the male group. This ﬁnding

may be related to the fact that women generally show a higher level of knowledge and better

protective behaviour than men in terms of hand hygiene and personal protection [107].

6. Conclusions

The study of the relationship between COVID-19 risk perception and behavioural

intentions for forest therapy tourism is of theoretical and practical importance. It may

help to understand whether and how COVID-19 risk perception inﬂuences behavioural

intentions for forest therapy tourism.

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6.1. Theoretical Contributions

Our research makes two main theoretical contributions to the literature on risk percep-

tion and forest therapy tourism. First, based on the Health Belief Model and the extended

Theory of Planned Behaviour, the study constructs a conceptual model of risk perception

on behavioural intentions towards forest therapy tourism to better understand whether

and how COVID-19 risk perception inﬂuences potential tourists’ forest therapy tourism

behaviour. Cognitive and affective risk perception were incorporated into a theoretical

model of planned behaviour. The empirical results veriﬁed that cognitive and affective

risk perception inﬂuence forest therapy tourism behavioural intentions through subjective

norms and attitudes. The extensions, modiﬁcations and inclusion of new variables to the

TPB model are consistent with previous research [59].

Second, previous tourism risk perceptions have focused on cognitive risk perceptions,

such as physical risk, ﬁnancial risk, social risk, and psychological risk, with less attention

paid to emotional risk perceptions [86]. In this study, emotional perceptions were incorpo-

rated into the model to better match peoples’ emotions such as anxiety, depression, and

fear during the COVID-19 pandemic [108,109], and such emotional perceptions were em-

pirically veriﬁed to have a signiﬁcant positive effect on attitudes, which further inﬂuenced

behavioural intentions towards forest therapy tourism. It suggests that the perception of

emotional risk, such as anxiety and fear brought about by the COVID-19 pandemic, also

has a very important inﬂuence on behavioural intentions.

6.2. Practical Contributions

Understanding how COVID-19 risk perceptions act on the behavioural intentions of

forest therapy tourism provides a basis for understanding tourists’ attitudes and behaviours

towards risk perceptions and formulating and improving tourism risk management and

forest therapy development strategies.

First, as COVID-19 cognitive and affective risks positively inﬂuence behavioural inten-

tions in forest therapy tourism through attitudes and subjective norms, there is a need to

strengthen risk management in forest therapy tourism destinations, improve epidemic pre-

vention and control initiatives, positively project an image of destination safety to tourists,

and reduce their perception of COVID-19 risk perception. Destinations should establish

a sound risk management system, especially systems related to epidemic prevention and

control during the epidemic. They should identify a leading group for epidemic prevention

and control; carry out epidemic risk management in terms of the internal environment,

target setting, risk identiﬁcation and assessment, risk factors, areas likely to be affected,

duration, information and communication, emergency management, and preventive mea-

sures, and realise comprehensive risk management in terms of the whole process, factors,

staff, and measures. These measures will improve the safety perception of potential tourists

and provide security for the sustainable development of tourism during the epidemic.

Second, as positive forest therapy tourism attitudes and subjective norms have an

obvious role in promoting behavioural intentions, the government and enterprises should

take relevant measures to actively raise the health awareness of the entire population and

advocate a healthy and sustainable way of tourism. Residents should be actively motivated

to protect forest therapy tourism resources and promote the development of forest therapy

tourism to improve their quality of life [110].

Third, destinations can use news websites, social media, short videos, and other channels

to promote the product features, therapy activities, and facilities to tourists, and actively

promote the destination’s anti-epidemic initiatives and safety image, vigorously publicise

the benefits of forest recreation tourism for human health, and guide residents to reduce the

perceived emotional risk of COVID-19 by de-escalating the adverse emotions such as anxiety,

fear, and depression brought about by COVID-19 through forest therapy tourism.

Fourth, the empirical results show that perceived behavioural control has a positive

impact on behavioural intentions towards forest therapy tourism. Therefore, social stake-

holders should create conditions to reduce the difﬁculties and obstacles for tourists to

Sustainability 2022, 14, 11590

14 of 18

participate in forest therapy tourism by adopting measures such as improving the supply

of forest therapy tourism products and implementing a paid leave system. Speciﬁcally, the

government should scientiﬁcally formulate plans for the forest therapy industry, increase

policy support, vigorously cultivate leading forest therapy enterprises, and implement

a paid leave system to guarantee the leisure time available to tourists. Encourage the

development of the forest therapy industry in poor areas. Strengthen land use protection

and meet the demand for land for the forest therapy industry according to law and regula-

tions. Broaden investment and ﬁnancing channels, and encourage various forestry, health,

pension, Chinese medicine and other industrial funds and social capital to enter the forest

therapy industry in various forms in accordance with the law. Improve the mechanism

of joint construction and sharing, and encourage localities to promote the integrated de-

velopment of forest therapy and health care, elderly care services and Chinese medicine

industries, to achieve mutual promotion and a win-win situation. Forest therapy enter-

prises should improve the accessibility of forest therapy for tourists and reduce obstacles

by improving infrastructure and service facilities and developing forest therapy products

that meet market demand.

6.3. Shortcomings and Outlook

Despite the contributions of this study, there are certain shortcomings. First, with the

cross-sectional data used in this study, whether the behavioural intentions of potential

tourists towards forest recreation tourism have changed after the epidemic needs to be

further explored. Second, due to time and ﬁnancial constraints and the need for epidemic

prevention and control, this study was conducted in Hubei Province, where the epidemic

began. The sample was not nationally representative, so whether the behavioural intentions

in other provinces are the same as those in Hubei needs to be further investigated and

veriﬁed. Third, as risk perceptions are easily inﬂuenced by various factors, such as the

surrounding environment, individuals, and policies, the results of the analysis of the

questionnaire data alone need to be further veriﬁed, and qualitative research methods can

be introduced into the study in the future to verify and enrich the ﬁndings of this study.

Forth, With nearly 60% of respondents being female, our ﬁndings should be interpreted

with caution as this may not reﬂect the overall true picture, which may be related to

our choice of research location. Future research may have to control the gender ratio of

respondents to ensure that it is largely balanced and representative of the overall proﬁle. At

the same time, differences in risk perception decisions can be studied for different groups

of tourists with different attributes to develop more reﬁned risk management strategies.

Author Contributions: Y.G.: conceptualisation, methodology, article structure design, software, data

analysis, writing—original draft; L.C.: supervision, writing—review and editing. All authors have

read and agreed to the published version of the manuscript.

Funding: This research was supported by (1) Science and Technology Research Project of Hubei

Provincial Education Department (Q20202902); (2) Philosophy and Social Science Research Project of

Hubei Provincial Education Department (21D105).

Institutional Review Board Statement: Not applicable.

Informed Consent Statement: Not applicable.

Data Availability Statement: Data connected to this research are available from the corresponding

author under request.

Conﬂicts of Interest: The authors declare no conﬂict of interest.

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