In a cross-sectional study conducted from August to December 2022, a total of 500 participants were included in the study using multi-stage sampling. The participants were chosen from all 30 health centers in Shiraz, the capital of Fars province in southern Iran. The mean age of the participants was 38.53 ± 10.92 years, ranging from 14 to 74 years. The majority of participants (65.7%) were male. In terms of education, the majority of participants were university graduates (69%), followed by those with secondary education (22%) and postgraduate studies (7%). The majority of participants (87%) came from urban areas. In relation to employment, 76.9% of individuals were employed, 7.9% were students, and the remaining were unemployed. The assessment of the content validity index (CVI) for the initial questions revealed that three questions (2, 4, and 7) had an index of 0.77. After revising and correcting the wording of the questions, and re-evaluating the CVI index, the content was found to be valid and in accordance with the conceptual framework (CVI range between 0.9 to 1.00). The average content validity index scale (S-CVI/Ave) of the questionnaire was 0.98. Additionally, the content validity of all questions in the questionnaire has been confirmed based on the minimum acceptable content validity ratio (CVR) index, as determined by a panel of experts. The CVR index ranges from 0.83 to 1. Once the content validity and face validity of the questionnaire were confirmed, the pilot questionnaire was administered to a group of 50 participants to assess its internal consistency. The Cronbach's alpha coefficient was computed for four factors: professional dental care, appearance and health, flossing, and the retention of natural teeth. The findings indicated that the subscales exhibited a coefficient above 0.70, while all 12 items demonstrated a coefficient of 0.82. The results of the intra-cluster correlation index (ICC) test indicated a significant agreement between the scores of the first and second tests (P < 0.001), confirming the repeatability of the subscales (ranging between 0.97 and 0.98) and the entire questionnaire (0.98), demonstrating high stability in the OHVS questionnaire. Factor analysis to assess the adequacy of the data and sample, Bartlett and KMO tests were utilized. After identifying the factors, the contribution of each factor to the total variance explanation was determined. The Varimax (orthogonal) method was employed for factor rotation, resulting in the formation of a matrix of rotated factors. Based on the correlation of each question with the factor (factor load) in this matrix, the questions were categorized into components. An exploratory factor analysis was performed on a set of 12 sentences using the principal components method. The KMO value obtained was 0.817, indicating that the data is suitable for factor analysis. Furthermore, Bartlett's sphericity test resulted in a significant outcome of 938.5884 at the 0.001 level, providing justification for using factor analysis based on the correlation matrix derived from the sample being studied.
The KMO index evaluation yielded a value of 0.75, demonstrating that the data is appropriate for factor analysis as it surpasses the recommended threshold of 0.7. Additionally, Bartlett's Test of Sphericity showed a non-significant result (Χ2(66) = 1121.276, p < 0.001), which indicates that there is an acceptable correlation between the variables, a prerequisite for conducting factor analysis. Table 1 presents the Communality results for each variable in regards to the main and extracted components.
Table 1
Communality sharing results related to main and extractive components
Communalities
|
---|
items
|
Initial
|
Extraction
|
---|
My smile is an important part of my appearance.
|
1.000
|
0.492
|
I think it is important that my teeth and gums are a source of pride.
|
1.000
|
0.540
|
The condition of my teeth and gums is an important part of my overall health.
|
1.000
|
0.603
|
Going to a dentist is not worth the cost to me
|
1.000
|
0.554
|
If I have a toothache, I prefer to wait and see if it will go away on its own before seeing a dentist
|
1.000
|
0.645
|
Going to the dentist is only important if my teeth or gums are bothering me.
|
1.000
|
0.697
|
Flossing my teeth every day is a high priority for me.
|
1.000
|
572/0
|
t is okay for me to miss a day or two of flossing when I am busy
|
1.000
|
0.433
|
I make sure I have dental floss available with me so I have it when I need it
|
1.000
|
0.597
|
It is important to me to keep my natural teeth
|
1.000
|
0.527
|
would rather get dentures than spend money to treat cavities or gum disease
|
1.000
|
0.796
|
I would not mind if I had to have a false tooth or dentures
|
1.000
|
0.620
|
The main components' solutions indicate that all variables have a communality value of 1, signifying that the variances associated with each variable have been adequately explained. Furthermore, the extracted components demonstrate that none of the variables have a low extracted share, ensuring that none of them were excluded from the analysis. Table 2 displays the amount of variance explained by each component.
Table 2
Amount of variances explained by each component
Total Variance Explained
|
---|
Component
|
Initial Eigenvalues
|
Extraction Sums of Squared Loadings
|
Rotation Sums of Squared Loadings
|
---|
Total
|
% of Variance
|
Cumulative %
|
Total
|
% of Variance
|
Cumulative %
|
Total
|
% of Variance
|
Cumulative %
|
---|
1
|
3.207
|
26.724
|
26.724
|
3.207
|
26.724
|
26.724
|
1.990
|
16.587
|
16.587
|
2
|
1.602
|
13.348
|
40.072
|
1.602
|
13.348
|
40.072
|
1.860
|
15.540
|
32.128
|
3
|
1.202
|
10.019
|
50.090
|
1.202
|
10.019
|
50.090
|
1.733
|
14.441
|
46.569
|
4
|
1.065
|
8.873
|
58.936
|
1.065
|
8.873
|
58.963
|
1.487
|
12.394
|
58.963
|
5
|
0.802
|
6.687
|
65.649
| | | | | | |
6
|
0.771
|
6.424
|
72.074
| | | | | | |
7
|
0.704
|
5.863
|
77.937
| | | | | | |
8
|
0.671
|
5.592
|
83.529
| | | | | | |
9
|
0.590
|
4.916
|
88.445
| | | | | | |
10
|
0.582
|
4.849
|
93.924
| | | | | | |
11
|
0.440
|
3.665
|
96.959
| | | | | | |
12
|
0.365
|
3.041
|
100.000
| | | | | | |
It reveals that only four components have eigenvalues greater than 1, collectively accounting for 58.963% of the total variance. Figure 1 portrays the scree plot of the eigenvalues from the principal components analysis.
The graph further validates that the solution's four components provide a better description of the main components. Combining the information from Table 2 and Fig. 1, it can be observed that four components with eigenvalues exceeding one were extracted. These components account for approximately 59% of the total variance related to oral health values. The first component explains around 16% of the variance, while the fourth component has the smallest contribution at about 12%. Table 3 exhibits the factor loadings for each item after Varimax rotation.
Table 3
Matrix of factors rotated by Varimax method (orthogonal)
Rotated Component Matrixa
|
---|
items
|
Component
|
---|
1
|
2
|
3
|
4
|
---|
q6
|
821/0
|
027/0-
|
067/0-
|
131/0-
|
q5
|
794/0
|
074/0-
|
039/0-
|
089/0-
|
q4
|
706/0
|
144/0
|
181/0-
|
048/0-
|
q11
|
147/0
|
880/0
|
011/0-
|
016/0-
|
q12
|
091/0
|
744/0
|
212/0-
|
116/0-
|
q10
|
033/0-
|
594/0-
|
408/0
|
078/0
|
q3
|
113/0-
|
025/0
|
762/0
|
093/0
|
q2
|
028/0-
|
244/0-
|
673/0
|
161/0
|
q1
|
118/0-
|
219/0-
|
652/0
|
070/0-
|
q9
|
109/0-
|
144/0-
|
048/0
|
750/0
|
q7
|
026/0-
|
074/0
|
139/0
|
739/0
|
q8
|
341/0
|
151/0
|
037/0
|
540/0-
|
The table illustrates those questions 4, 5, and 6 have the highest correlation with the first factor, while questions 10, 11, and 12 have the highest correlation with the second factor. Questions 1, 2, and 3 exhibit the highest correlation with the third factor, whereas questions 7, 8, and 9 have the highest correlation with the fourth factor. Question 10 displays a shared correlation between factors 2 and 3 and is categorized under the subgroup of factor 2 due to its stronger correlation with factor 2 compared to factor 3.