In total, 132 individuals of the 384 respondents were women (34.4%) and 252 (65.6%) were men. In terms of marital status, 131 respondents were single (34.1%) and 253 were married (65.9%). The highest frequency in family size was four (33.3%) and the lowest was seven (2.1%). In terms of employment status, those who worked full time had the highest number amounting to 176 people (45.8%) and retirees had the lowest frequency of 13 people (3.4%) (Table 4).
Table 4. Distribution of wellness tourists in terms of gender, marital status, family size, and employment status
Variables
|
Categories
|
Frequency
|
Percent
|
Mode
|
Gender
|
Male
|
252
|
65.6
|
Male
|
Female
|
132
|
34.3
|
Marital status
|
Married
|
253
|
65.9
|
Married
|
Single
|
131
|
34.1
|
Family size
|
1
|
20
|
5.2
|
4
|
2
|
50
|
15.4
|
3
|
79
|
20.6
|
4
|
128
|
33.3
|
5
|
66
|
17.2
|
6
|
24
|
6.3
|
7
|
8
|
2.1
|
Employment status
|
Full-time job
|
176
|
45.8
|
Full-time job
|
Part-time job
|
50
|
13
|
Unemployed
|
25
|
6.5
|
Housewife
|
51
|
13.3
|
Retired
|
13
|
3.4
|
Student
|
69
|
18
|
Source: Research Findings
According to the results, the average age of the tourists was about 35-36 years. Most tourists were younger than 34 years (54.2%). In terms of educational level, the highest frequency was 131 people (34.1%) in the period of 17-12 years of schooling. In terms of annual income, 243 people (63.3%) had an annual income of less than US$ 2000 (Table 5).
Table 5. Frequency distribution of health tourists in terms of age, level of education, and annual income
Variables
|
Categories
|
Frequency
|
Percent
|
Cumulative Percent
|
Mean
|
Age
Max:60
Min:16
|
34≥X
34<X ≥52
X > 52
|
208
132
44
|
54.2
34.4
11.5
|
54.2
88.5
100
|
35.47
|
Years of schooling
Max:22
Min:2
|
7≥X
7<X ≥12
12<X ≥17
X > 17
|
60
126
131
67
|
15.6
32.8
34.1
17.4
|
15.6
48.4
82.6
100
|
12.74
|
Annual income (US$)
Max: 8000
Min: 0
|
2000≥X
2000 <X ≥4000
4000<X ≥6000
X > 6000
|
243
85
29
27
|
63.3
22.1
7.6
7
|
63.3
85.4
93
100
|
1733.33$
|
Source: Research Findings
4.1 Status of the wellness components
The means of physical, individual, and interaction components of wellness tourism were 4.13, 3.64, and 3.38, respectively. The Friedman test showed a significant difference among the different components of wellness tourism at the 1% level. It should be mentioned that among different items in physical components, “feeling refreshed and relieved of physical fatigue” and “feeling the relief of physical pain” had the highest scores. In the items of the individual component, “rest and relaxation” and “feeling of inner peace and stress relief” had the best status, and in the interaction component, “establishing friendly and supportive relationships” and “spending time with family/friends” had the greatest scores (Table 6; Figure 5).
Table 6: The status of the wellness tourism components
Components of
Dependent variable
|
Mean
rank
|
Mean
|
Sig
|
Physical
|
2.99
|
4.13
|
0.000
|
Individual
|
1.68
|
3.64
|
Interaction
|
1.33
|
3.58
|
Source: Research Findings
4.2 Status of factors affecting choosing the wellness- base destination
The results revealed that among different factors affecting choosing the destination, satisfaction had the greatest score with a mean of 3.12 that is above the medium. In this component, “security of the environment” and “environmental cleanliness” were ranked first and second and “satisfaction with access to city buses and taxis” had the lowest rating. About the three remaining factors, place, marketing-price and quality-facilities, with averages of 2.92, 2.52 and 2.41, respectively, are below the medium, respectively. “Direct international and national flights to the nearest airport”, “providing recreational and wellness packages to tourists” and “a wide variety of recreational and health facilities” had the least scores in each component. Also, the results of the Friedman test showed a significant difference between the current statuses of various factors affecting wellness tourism at the 1% level (table 7 & figure6).
Table 7: The status of factors affecting choosing the destination
Independent variables
|
Mean
rank
|
Mean
|
Sig
|
Satisfaction
|
3.50
|
3.12
|
0.000
|
Place
|
3.01
|
2.94
|
Marketing-price
|
1.93
|
2.52
|
Quality -Facilities
|
1.56
|
2.41
|
Source: Research Findings
4.3 Correlation coefficients between variables
The results of the Pearson correlation test (Table 8) showed a positive and significant (P < 0.01) relationship between place, satisfaction, marketing-price, and quality-facilities with wellness.
Table 8: The Pearson correlation results between research variables
Variable 1
(Independent )
|
Variable 2
(Dependent)
|
r
|
Sig
|
Place
|
Wellness
|
0.569
|
0.000
|
Satisfaction
|
0.379
|
0.000
|
Marketing-price
|
0.350
|
0.000
|
Quality-facilities
|
0.315
|
0.000
|
Source: Research Findings
4.4 Structural equation model of the research
The structural model of the research, which is, in fact, the general model of the research, indicates causal relationships between latent internal and external variables and expresses causal effects and the extent of the explained variance. The general research model examined the effect of each of the independent variables (place, satisfaction, marketing-price, and quality-facilities) on the dependent variable (wellness). Given that the overall research model had good diagnostic validity and reliability, the general model was tested using the goodness of fit index (GFI), adjusted goodness of fit index (AGFI), normed fit index (NFI), the Tucker-Lewis index (TLI), the comparative fit index (CFI), and the root mean square error of approximation (RMSEA). Also, the results of the remaining covariance and variance analysis indicators in the data context, which include CMIN/D and GFI, show that the covariance and error variance are well controlled. Regarding the indicators of the alternative model review, including IFI, TLI, NFI, GFI, it was also shown that the values of these indicators for the model were higher than 0.9, which is an acceptable value. Eventually, the RMSEA index showed that the model had the goodness of fit. According to the fit indicators and the amount of variance explained by independent variables, it was determined that four external latent variables (satisfaction, place, marketing-price, and quality-facilities) accounted for 62% of the wellness variance (Table 9; Figure 7).
Table 9: The results of the overall measurement model compliance with the fit indicators
Fit index
|
Suggested criterion *
|
Results in research **
|
Result
|
CMIN/DF
|
Less than 3
|
2.171
|
Significant
|
CFI
|
> 0.9
|
0.988
|
Significant
|
GFI
|
> 0.9
|
0.982
|
Significant
|
NFI
|
> 0.9
|
0.987
|
Significant
|
TLI
|
> 0.9
|
0.982
|
Significant
|
IFI
|
> 0.9
|
0.982
|
Significant
|
RMSEA
|
X ≥0.08
|
0.055
|
Significant
|
* Source: (Kalantari, 2013; Maccallam et al., 1996)
** Source: Research Findings
Table (10) shows the total effects of the independent variables on wellness, with the most significant effects being observed in place (0.825) and satisfaction (0.579), respectively. Other variables that affect destination choosing were marketing-price (0.545) and quality-facilities (0.391), respectively. In the following regression equation, all the variables that affect wellness destination choosing are included along with their path coefficients.
Wellness =28.22+ 1.112* Place+ 0.280* Satisfaction+ 0.221* Marketing-Price+ 0.211* Quality-Facilities
Table 10: The total effect of independent variables on the dependent variable
Independent variables
|
Dependent variable
|
Total effect
|
Place
|
Wellness
|
0.825
|
Satisfaction
|
0.579
|
Marketing-Price
|
0.545
|
Quality-Facilities
|
0.391
|
** Source: Research Findings