Validity and Reliability of the Revised Dental Beliefs Survey in Iranian Young Adults

Saboohi, Z.; Rostami Varnousfaderani, M.; Rostami Varnousfaderani, M.; Khohsnazar, Z.; Khoshnazar, Z.; Rashidi, F.; Yarmohammadi, S.; Safari-Moradabadi, A.; Hosseini Koukamari, P.

doi:10.58209/hehp.13.2.405

Validity and Reliability of the Revised Dental Beliefs Survey in Iranian Young Adults

Authors

Z. Saboohi ¹

M. Rostami Varnousfaderani ²

Z. Khohsnazar ²

Z. Khoshnazar ²

F. Rashidi ³

S. Yarmohammadi ⁴

A. Safari-Moradabadi ⁵

P. Hosseini Koukamari ⁶

¹ Department of Health Services, School of Public Health, Iran University of Medical Sciences, Tehran, Iran

² Student Research Committee, Shahid Beheshti University of Medical Sciences, Tehran, Iran

³ Student Research Committee, Saveh University of Medical Sciences, Saveh, Iran

⁴ Trauma Research Center, Kashan University of Medical Sciences, Kashan, Iran

⁵ Department of Health Promotion and Education, School of Health, Alborz University of Medical Sciences, Alborz, Iran

⁶ Social Determinants of Health Research Center, Saveh University of Medical Sciences, Saveh, Iran

https://doi.org/10.58209/hehp.13.2.405

Abstract

Aims: Negative views of dentists contribute to dental anxiety and reduced visits, worsening oral health. In Iran, where oral diseases are common and preventive care is low, understanding dental beliefs is essential. This study evaluated the psychometric properties of the Persian Dental Beliefs Survey-Revised to support dental health awareness and behavior change.

Instrument & Methods: This cross-sectional psychometric study was conducted in 2024, involving 400 students at Saveh University of Medical Sciences, selected via convenience sampling. The original Dental Beliefs Survey-Revised was translated from English to Persian using the forward-backward translation method. Face and content validity were confirmed through qualitative assessment. Structural validity was examined using exploratory and confirmatory factor analyses. Internal consistency and reliability were measured by Cronbach’s alpha, McDonald’s omega, and Composite Reliability. Convergent and discriminant validity were assessed through average variance extracted, maximum shared variance, and Fornell-Larcker criteria. Statistical analyses were conducted using SPSS 21 and AMOS 18.

Findings: The Persian Dental Beliefs Survey-Revised identified four factors (ethics (8 items), communication (6 items), control (4 items), and trust (6 items)) explaining 56.8% of the total variance. Goodness-of-fit indices from confirmatory factor analysis confirmed a satisfactory model fit. All reliability indices were strong, and both convergent and discriminant validity were found to be acceptable.

Conclusion: The Persian version of the DBS-R demonstrates strong psychometric properties and is suitable for use in academic, clinical, and public health research within Persian-speaking populations.

Keywords

Anxiety

Questionnaire

Psychometric

Oral health

Young Adult

Subjects

Oral Health Education/Promotion

Introduction
Oral health and hygiene are widely recognized as significant public health concerns in many countries worldwide. Although the World Health Organization (WHO) has highlighted the importance of oral health and its considerable impact on people’s daily lives, the lack of focus on oral health and related diseases has had a detrimental effect on more than 5.3 billion people globally ^{[1, 2]}. Dental decay is the most common dental disease, affecting 60 to 90% of schoolchildren and 100% of adults worldwide. Additionally, nearly 30% of individuals aged 65 to 74 do not have their natural teeth ^[3]. According to a meta-analysis, the overall prevalence of dental decay among the Iranian population is 72.8% ^[4]. Research findings indicate that poor oral health and clinical indicators, such as decayed, missing, and filled teeth, are associated with irregular dental care ^{[5, 6]}.
The presence and utilization of dental services in Iran are lower and more irregular than in other countries ^[6-8]. An important factor influencing the utilization of dental services in a community is the beliefs and perceptions about dentistry among different population groups ^[9]. Dental beliefs refer to patients’ mental perceptions regarding dentists and dental treatment ^[10]. These beliefs reflect the patient’s understanding of the behavior of dental health professionals, which influences their dental fear and anxiety. They also help in understanding the reasons for not using dental health services in a community ^[9]. Karibe et al. showed that negative beliefs about dentists are strongly associated with higher rates of frequent cancellations and missed appointments with dentists ^[11]. Additionally, negative behavior from dentists and staff, as well as a lack of trust, are essential factors that trigger anxiety and discourage people from visiting the dentist ^[12].
Beliefs about dentists were first reported through a questionnaire called the Dental Beliefs Survey (DBS), developed and evaluated by Milgrom ^[13]. The purpose of the DBS is to determine the extent to which a patient perceives the behavior of dental professionals as helpful in alleviating their fear or anxiety. The DBS questionnaire consists of 28 questions, designed in English, and includes three subscales: professionalism/ethics, communication, and control ^[14]. Subsequently, Kvale et al. analyzed the factorial structure of the DBS-R and noted that factor analysis of the data indicates the presence of a fourth dimension represented by the concept of Trust. This new domain includes items 4 and 10 (initially categorized under professionalism/ethics) and items 24-27 (originally placed in the control/lack of control domain) ^[15]. It has been suggested that the shorter version be used more often when researchers are interested in assessing trust in dentists ^[14].
The questionnaire has been examined in different cultures ^{[11, 14, 16-18]} and target groups, including patients ^[19], adults ^[14], and students ^[20]. Students exhibit relatively similar characteristics but have diverse experiences ^[21]. They undergo behavioral changes and lifestyle variations, which may intersect with general health standards ^[22] and oral health ^[23]. Young adulthood is a critical period for shaping long-term health behaviors, including those related to oral health. Promoting positive oral health beliefs during this stage can lead to improved oral health outcomes and enhanced oral health-related quality of life ^[24]. For example, a study showed that students and younger individuals have a more negative attitude toward dentistry compared to other patients and dental visitors ^[16]. Furthermore, a study conducted among university students in southern Brazil indicated that 19.5% of students had not visited a dentist, and 53.5% reported delaying dental visits ^[25]. According to WHO estimates, personal lifestyle and health behaviors account for approximately 65% of overall health and quality of life ^[26]. These findings underscore the need for valid and reliable tools to assess oral health beliefs and behaviors in this age group. Given that universities provide direct access to this population, they represent a strategic setting for such assessments.
As far as we know, a scale for measuring beliefs regarding dentistry is currently not available in Persian. Such a scale would enable the assessment of attitudes and beliefs toward dentistry in a Persian-speaking population and would also be beneficial for cross-cultural studies. As nations strive to attain world-class educational standards and measure their progress against others, allowing individuals to take these assessments in their preferred languages becomes increasingly vital. This approach fosters fairness and ensures that language barriers do not obstruct the accurate evaluation of individuals’ abilities ^[27]. This study aimed to translate and validate the 24-item Dental Beliefs Scale-Revised (DBS-R) to allow for a more accurate assessment of dental beliefs among university students in Iran. This work can serve as a foundation for future research and interventions to improve oral health and enhance dental care.

Instrument and Methods
Study design and participants
This cross-sectional study involving 400 university students at Saveh University of Medical Sciences, Iran, examined the psychometric properties of the dental beliefs survey.
Sampling procedure
Participants were selected using a convenience sampling technique based on the inclusion criteria of having prior experience visiting a dentist and providing informed consent to participate in the study. Upon the recommendation of MacCallum et al., we invited 400 individuals for our research, as they suggested a minimum sample size of 200 cases for psychometric studies ^[28]. This was necessary to ensure the availability of two separate samples to assess structural validity. After a comprehensive explanation of the study’s goals, participants were provided with questionnaires to complete. The researcher personally collected the questionnaires, explained the study, and invited individuals to participate voluntarily. Sampling and data collection for psychometric tests (factorial validity and reliability) were conducted between October 2023 and January 2024.
Research tools
The demographic characteristics, including marital status, age, and sex, and a history of toothache, were collected using a demographic data form.
The original version of the Revised Dental Beliefs Survey
This survey was initially developed in English. The DBS comprises 28 items categorized into three subscales. The professionalism/ethics subscale evaluates the dentist’s technical competency and integrity ^[29]. The communication subscale assesses the quality of interaction between the dentist and the patient, as well as the dentist’s demeanor. The lack of control subscale measures patients’ perceived sense of control during dental appointments. The primary objective of this questionnaire is to provide insights into the patient-dentist relationship from the patient’s perspective. In a study by Kvale et al., a four-factor solution was proposed for categorizing specific attributes. The identified factors were ethics (8 items), communication (6 items), control (4 items), and trust (6 items) ^[15]. The trust subscale reflects the perception that the dentist may not empathize with the patient’s experience of pain. We used the Kvale version ^[15] to adapt it for Iranians. Participants rated the items using a 5-point Likert-type scale, with scores ranging from 1 for “not at all” to 5 for “very much.” The total scores ranged from 24 to 114, with higher scores indicating more negative perceptions or beliefs.
Validity procedure
The psychometric properties of the DBS-R were evaluated in stages, including translation, face and content validity examination, structural validity analysis, convergent and discriminant validity testing, and reliability assessment.
Translation
Beaton et al.'s guidelines ^[30] were followed to translate the English version of the DBS-R into Persian. Initially, two experts, one in psychology and the other in Persian, independently translated the questionnaire. Subsequently, the translators and the primary researcher compared the translations, resolved any discrepancies, and synthesized the Persian version. The next step involved back-translating the questionnaire by a native English speaker who was unaware of the original version. An expert committee, consisting of all translators and the primary researcher, reviewed and approved the final Persian version after addressing any disparities.
Content and face validity
The necessity for quantitative evaluations of content and face validity of standard questionnaires was considered unnecessary ^[27]. Therefore, only qualitative methods were employed to assess face and content validity. Twenty participants who met the inclusion criteria completed the questionnaire and provided feedback on item clarity, relevance, and difficulty. All participants reported that the items were clear and easy to understand. In the next step, ten experts in dentistry, public health, psychology, and epidemiology were invited to review the questionnaire in terms of grammar, wording, item allocation, and scaling. Based on their constructive feedback, several items were revised to improve the overall quality of the instrument.
Structural validity
Structural validity assessment involved applying exploratory factor analysis (EFA) followed by confirmatory factor analysis (CFA). EFA serves to summarize the data by grouping correlated parameters, while CFA tests pre-existing hypotheses concerning the structure of the parameters^[31]. Establishing the optimal sample size for factor analysis can be complex. Following the recommendation by MacCallum et al., which suggested a minimum sample size of 200 individuals for psychometric studies ^[28], the suitability of the data for factor analysis in EFA was evaluated using the Kaiser-Meyer-Olkin (KMO) criterion and Bartlett’s sphericity test ^[32]. The KMO test assesses the extent of variance among parameters attributed to underlying factors, with a value between 0.8 and 1 indicating adequate sampling for factor analysis ^[33]. In contrast, a value below 0.7 suggests insufficient sampling, necessitating corrective actions. Bartlett’s sphericity test is a commonly used method to determine the appropriateness of data for factor analysis, where statistical significance indicates the data’s suitability for this analysis ^[34]. Maximum likelihood with Promax rotation was utilized to extract factors. The number of factors was determined based on the literature supporting four factors and the Eigenvalue >1 criterion. Our analysis established a minimum factor loading of 0.4 as the threshold for factor extraction.
First- and second-order factor analyses based on the maximum likelihood approach were employed to estimate the fit indices pattern. The model fit was assessed according to the root mean square error of approximation (RMSEA), normed fit index (NFI), comparative fit index (CFI), goodness of fit index (GFI), chi-square (χ²) value, incremental fit index (IFI), Tucker-Lewis index (TLI), and CMIN/DF index. CFI, GFI, NFI, TLI, and IFI values greater than 0.90, along with RMSEA values less than or equal to 0.08 and CMIN/DF values less than or equal to 3, indicate a good model fit ^[35]. In the second-order factor analysis, researchers assumed that the latent parameters identified earlier were present. This analysis aimed to uncover higher-level concepts, offering a deeper understanding of the data’s structure. Examining these upper-level factors shows how the previously identified parameters are interconnected, forming broader theoretical constructs. The original dataset consisted of 400 participants, randomly divided into two separate datasets: EFA with 200 participants and CFA with 200 participants.
Convergent and discriminant validity
The evaluation of the DBS-R involved an assessment of its convergent and discriminant validity. Convergent validity was confirmed using the average variance extracted (AVE) and composite reliability (CR) values. Additionally, discriminant validity was established by examining maximum shared variance (MSV) and average shared variance (ASV), as well as using Fornell and Larcker’s method. Convergent validity is deemed to be present when the AVE exceeds 0.5 and the CR surpasses the AVE. Regarding discriminant validity, it is necessary for the AVE values of the study constructs to exceed the values of both the ASV and the MSV ^[36].
Reliability assessment
The internal consistency and construct reliability assessment utilized Cronbach’s alpha, McDonald’s omega, and CR. An alpha value exceeding 0.7 indicates acceptable internal consistency ^[37]. Composite reliability values between 0.7 and 0.9 are regarded as satisfactory, while values greater than 0.90 are considered appropriate for exploratory research ^[38].
Data analysis
Various statistical measures were employed in the data analysis to evaluate normal distribution, outliers, and missing data. Skewness and kurtosis were used to assess univariate and multivariate data distributions separately. Furthermore, the Mardia coefficient of multivariate kurtosis was applied to examine multivariate normality, while Mahalanobis D-squared was employed to detect multivariate outliers in this study. The research utilized SPSS 21 and AMOS 18 software from IBM Corp.

Findings
The mean age of the students was 22.23±4.96 years. The majority of participants were single (n=356, 89.4%). Additionally, 30% had experienced tooth extraction, 64.3% had at least one filled tooth, and 53% had a decayed tooth.
Maximum likelihood exploratory factor analysis
All items followed a normal distribution. Moreover, the Mardia coefficient of multivariate kurtosis was below 8. Additionally, no significant multivariate outliers were detected based on the Mahalanobis D-squared test (p<0.001). MLEFA with Promax rotation and Kaiser normalization was conducted on the first random dataset (n=200). The KMO measure of sampling adequacy was 0.91. Bartlett’s test of sphericity was also significant (χ²=3774.59; df=276; p<0.001). The four-factor solution explained 56.8% of the total variance.
Confirmatory factor analysis
The four factors, which were subsequently examined through CFA across three models. Model 1 initially assumed a single latent factor; however, it did not exhibit an acceptable fit with the observed indicators. Model 2 was then tested, incorporating four latent factors. A second-order factor analysis was conducted to determine whether all the identified factors aligned with the overarching construct of “Dental Beliefs” (Figures 1).

Figure 1. Factor structure model of the Revised Dental Beliefs Survey (DBS-R) based on confirmatory factor analysis (CFA)

All factor loadings of the latent parameters were statistically significant at the 99% confidence level. The model exhibited acceptable goodness-of-fit. The chi-square to degrees of freedom ratio (χ2/dF) was 2.11 (p<0.001); both the TLI and the CFI exceeded 0.9, and the RMSEA was 0.06. Collectively, these indices validated the model’s overall adequacy and supported its construct validity (Table 1).

Table 1. The model fit indicators (χ²/df: Chi-Squared Test/Degree of Freedom; NFI: Normed Fit Index; RMSEA: Root-Mean-Square Error of Approximation; GFI: Goodness of Fit Index, AGFI: Adjusted Goodness of Fit Index; IFI: Incremental Fit Index; CFI: Comparative Fit Index;; TLI: Tucker-Lewis index) of the revised dental beliefs survey

Convergent and discriminant validity
The total mean score of the DBS-R was 68.55±21.08. Regarding the subscales, the mean scores were as follows: trust=13.73±6.29, ethics=18.78±7.17, communication=13.38±5.22, and control= 0.89±3.56. There were robust convergent validity for all four factors. The correlation coefficients among the factors were lower than the square roots of the AVE values, which further substantiated the acceptable level of discriminant validity. Cronbach’s alpha and McDonald’s omega values for ethics, communication, control, and trust were all high (Table 2).

Table 2. Validity (AVE: Average Variance Extracted; MSV: Maximum Shared Squared Variance; ASV: Average Shared Variance) and reliability (α: Cronbach’s alpha; Ω: McDonald’s omega; CR: Composite Reliability) analysis of the Revised Dental Beliefs Survey structure

Discussion
The present study aimed to translate and evaluate the psychometric properties of the Persian version of the DBS-R in Iranian university students.
The Persian version demonstrated four different constructs. Four factors explained 56.80% of the variance based on the exploratory factor analysis. All aspects were loaded appropriately based on their respective factors. According to the original study by Kvale et al. ^[15], these four factors explain 63.9% of the variance. According to the CFA, five models were investigated, and the 24-item version with four domains improved upon the original. Furthermore, a global factor that included all of these items was identified. Following the original study, we conducted CFA in three models. In Model 1, the DBS-R was considered one global factor; however, we did not find acceptable fit indicators. We then tested the model at two levels; one with four domains and another with the DBS-R as one domain. Both of these models demonstrated acceptable values. Convergent and discriminant validity were satisfied, as indicated by AVE values greater than 0.5 and CR values exceeding the AVE during the assessment.
The Fornell-Larcker test confirmed the discriminant validity of the Persian version, which was a significant validation. This finding aligns with the study by Kvale et al., which found strong convergent validity between DBS-R scores and related constructs, such as dental anxiety and desire for control. They also reported strong discriminant validity by comparing DBS-R scores between a clinical sample of individuals with injection phobia and a non-clinical sample of students ^[15]. All reliability indices, such as Cronbach’s alpha and CR, were excellent for these four subscales, further reinforcing the robustness of the Persian version. The reliability of the scales in Kvale et al.'s study ranged from 0.88 to 0.90. Furthermore, Milgrom examined the psychometric properties of the DBS-R among students and patients with dental phobia. Their findings showed strong convergent validity with moderate correlations between this questionnaire and dental anxiety measures, consistent with expectations ^[20].
Different versions of the DBS-R, consisting of 22, 24, 25, and 28 items, have previously been psychometrically evaluated in Spain, Turkey, China, and Sweden. In the Swedish version, 550 adults were compared, including students, general dental patients, 105 periodontal patients, and 62 patients on a waiting list for dental fear treatment. According to the results, the DBS-R exhibited strong internal consistency across all study groups. The findings indicate that the DBS-R is a trustworthy and valid measure for evaluating attitudes toward dentists within diverse Swedish patient and non-clinical groups ^[16].
In another study by Balgiu et al., EFA and CFA revealed a four-factor model with dimensions of professionalism, comfort, communication, and not feeling involved (χ²/df=2.02; CFI=0.91; RMSEA=0.072). Cronbach’s alpha for the subscales ranged from 0.90 to 0.63. Test-retest reliability for the total score was considered acceptable (r=0.63). Correlations between the DBS-R, DASS-21R, and DFS were positive but moderate, indicating good convergent validity ^[19].
The findings from the Turkish version, based on EFA, indicated that the DBS-R comprises three factors encompassing 22 items. Upon conducting a CFA, it was determined that the 22-item three-factor version demonstrated a better fit for the data than the original 28-item English language four-factor structure model proposed. The internal reliability of the Turkish version of the DBS-R was substantiated by a Cronbach’s alpha value of 0.88. Furthermore, the correlation coefficient between the Turkish version of the DBS-R and the Modified Dental Anxiety Scale (MDAS) was observed to be 0.29 ^[18].
The psychometric properties of the short and long Chinese versions of the DBS-R exhibit similar results. Both versions demonstrate good reliability and validity. The internal consistency in both versions is high (0.93-0.94), with alpha levels matching those found in studies involving clinical and non-clinical samples ^{[16, 17, 20]}. Moreover, all subscales exhibit internal consistency. Test-retest data revealed that the CDBS-R remains stable over two weeks. The findings for the Chinese version suggest that the items on the CDBS-R measure a single underlying construct that remains stable outside the dental setting ^[14]. Additionally, in the Spanish version, the internal reliability is 0.96 (95% CI=0.94-0.97), and the test-retest reliability is 0.86 (95% CI=0.64-0.94) ^[17].
Regarding factor averages in the Persian version, ethics, trust, communication, and control had the highest to lowest averages, respectively. In the 24-item Chinese version, the averages correspond to ethics, communication, trust, and power in that order ^[14]. Based on our averages, the highest negative attitude toward the target group was found in the ethics factor among the subscales. Our results are similar to those of Wu & Buchanan ^[14]. These observations indicate that Iranian students strongly emphasize ethics in their perceptions of dentistry. This finding is significant as it highlights the importance of instilling ethical principles and values in future dental professionals. Patients’ concerns about the moral behavior of dental professionals played a crucial role in shaping their overall understanding of healthcare experiences. The items in the ethics factor, primarily “I am concerned that dentists may recommend procedures that are not necessary” and “I am concerned that dentists may not provide me with all the necessary information for good decision-making,” highlighted fundamental aspects of trust. Transparency in the dentist-patient relationship and the fear that dentists may recommend unnecessary procedures underscore the core of patients’ trust in healthcare providers.
This indicates concerns about potential overtreatment or the exploitation of patients for financial gain. Such worries impact the economic well-being of patients and erode their trust in dentists’ professional judgment and honesty. Similarly, concerns about dentists withholding necessary information for informed decision-making emphasize the importance of transparency and patient autonomy in healthcare delivery. Patients expect clear and comprehensive explanations about treatment options, potential risks, and choices. When they perceive a lack of transparency or feel that information is being withheld, it can lead to feelings of vulnerability and weaken their trust in the treatment process ^[19]. In the studies by Kuhl et al. ^{[15, 16]}, as well as in the Turkish-translated version ^[18], control had the highest mean; however, in our study, control had the lowest mean. The ability to control conditions can play a determining role in individuals’ anxiety regarding treatment ^{[39, 40]}.
Based on the tell-show-do model, which is a behavior-shaping technique that enhances predictability in the clinical setting ^[41], behavioral control can be increased among patients. Behavioral control allows patients to feel that they have some control over the treatment process. This sense of control also increases trust in the dentist ^[40]. The average communication structure was 38.13, compared to 7.73 in Turkish and 19 in Chinese. A good relationship between patient and physician is crucial for managing anxiety. Dentists can establish a good relationship with patients and increase trust by providing comprehensive information about the problem description, treatment options, and preventive measures ^[42].
Our study’s strengths include examining the psychometric properties of the DBS-R scale for the first time in Iran, utilizing the forward-backward method according to the Beaton protocol for the translation process, and achieving convergent and discriminant validity. However, the present study also had some limitations that need to be acknowledged. First, there was potential bias due to a tendency to provide desired responses with self-reported measures, and the study did not assess test-retest reliability.
The Persian version of the DBS-R has appropriate psychometric properties for evaluating beliefs and attitudes toward dentists among Iranian young people. This suggests that healthcare providers can use it for potential implications in developing effective oral health interventions focused on health beliefs, which refer to individuals’ perceptions of their well-being, including their views on health, factors influencing illness, and strategies for disease prevention and recovery. Furthermore, health policymakers should pay special attention to beliefs, particularly among the young. A study showed that students have more critical attitudes and higher expectations regarding dental services than other age groups, such as adults and patients. In other studies, it is recommended that the tool’s validity be investigated among patients and individuals with dental phobias to compare results across different groups and obtain the best version. In the current study, a 24-item version has been validated; researchers can validate a 28-item version in Persian and compare it with the current version.

Conclusion
The research findings indicate that the Persian version of the DBS-R has appropriate psychometric properties for evaluating beliefs and attitudes toward dentists among Iranian young people.

Acknowledgments: We sincerely appreciate the Student Research Committee and the Vice Chancellor for Research and Technology at Saveh University of Medical Sciences for their financial support of this study.
Ethical Permissions: Ethical approval was obtained from the Ethics Committee of the Vice Chancellor for Research and Technology at Saveh University of Medical Sciences, with code IR.SAVEHUMS.REC.1403.029. Informed consent was obtained from all participants before data collection, and their right to withdraw from the study at any time without any consequences was guaranteed.
Conflicts of Interests: The authors declared no conflicts of interests.
Authors' Contribution: Saboohi Z (First Author), Introduction Writer/Methodologist/Main Researcher (25%); Rostami Varnousfaderani M (Second Author), Methodologist/Assistant Researcher (10%); Khohsnazar Z (Third Author), Assistant Researcher/Statistical Analyst (10%); Rashidi F (Fourth Author), data analysis (10%); Yarmohammadi S (Fifth Author), Introduction Writer/Methodologist (10%); Safari-Moradabadi A (Sixth Author), Assistant Researcher (10%); Hosseini Koukamari P (Seventh Author), Methodologist/Statistical Analyst /Discussion Writer (25%)
Funding/Support: This article is based on research (IR.SAVEHUMS.REC.1403.029), which was approved and financially supported by the Vice Chancellor for Research and Technology at Saveh University of Medical Sciences.

1. Aljauid AS, Al-Otaibi AO, Aldawood MM, Mohamed RN, Basha S, Thomali YA. Oral health behavior of medical, dental, and pharmacology students in Taif University: A Cross-sectional Study. Journal of Advanced Oral Research. 2020;11(1):83-92.
2. Kim H-J, Cho Y, Noh Y, Joo J-Y, Park HR. A decision tree to identify the combinations of non-communicable diseases that constitute the highest risk for dental caries experience: A hospital records-based study. Plos one. 2021;16(10):e0257079.
3. Ghanbari Z, Moradi Y, Samiee N, Moradpour F. Dental caries prevalence in relation to the cardiovascular diseases: cross-sectional findings from the Iranian kurdish population. BMC Oral Health. 2024;24(1):509.
4. Soltani MR, Sayadizadeh M, Estabragh SR, Ghannadan K, Malek-Mohammadi M. Dental caries status and its related factors in Iran: a meta-analysis. Journal of Dentistry. 2020;21(3):158.
5. López R. Periodontal disease and adverse pregnancy outcomes. Evidence-Based Dentistry. 2008;9(2):48-.
6. faraji Khiavi F, Ghobadian S, Zakavi F, Golpasand Hagh L. Comparative Study of Dental Care and Dental Services in Iran and Selected Countries. 2018.
7. Pouraskari Z, Yazdani R, Hessari H. Exploring the Challenges in Covering Dental Services through Complementary Insurance in Iran: A Qualitative Study. International Journal of Dentistry. 2024;2024.
8. Rezaei S, Pulok MH, Zahirian Moghadam T, Zandian H. Socioeconomic-related inequalities in dental care utilization in northwestern Iran. Clinical, cosmetic and investigational dentistry. 2020:181-9.
9. Pai M, Rajesh G, Yellapurkar S. Development of modified dental beliefs scale among an adolescent rural population. Journal of International Society of Preventive and Community Dentistry. 2021;11(2):132-7.
10. Kulich KR, Berggren U, Hakeberg M, Gustafsson JE. Factor structure of the Dental Beliefs Survey in a dental phobic population. European journal of oral sciences. 2001;109(4):235-40.
11. Karibe H, Kato Y, Shimazu K, Okamoto A, Heima M. Gender differences in adolescents’ perceptions toward dentists using the Japanese version of the dental beliefs survey: a cross-sectional survey. BMC Oral Health. 2019;19:1-8.
12. Moore R. Trusting the Dentist—Expecting a Leap of Faith vs. a Well-Defined Strategy for Anxious Patients. Dentistry Journal. 2022;10(4):66.
13. Milgrom P, Weinstein P, Kleinknecht R, Getz T. Treating fearful dental patients: a clinical handbook. New York: Appleton. 1985.
14. Wu L, Buchanan H. Translation and validation of the revised dental beliefs survey (DBS-R) in China. Psychology, health & medicine. 2020;25(7):812-23.
15. Kvale G, Milgrom P, Getz T, Weinstein P, Johnsen TB. Beliefs about professional ethics, dentist–patient communication, control and trust among fearful dental patients: the factor structure of the revised Dental Beliefs Survey. Acta Odontologica Scandinavica. 2004;62(1):21-9.
16. Abrahamsson KH, Hakeberg M, Stenman J, Öhrn K. Dental beliefs: evaluation of the Swedish version of the revised Dental Beliefs Survey in different patient groups and in a non‐clinical student sample. European Journal of Oral Sciences. 2006;114(3):209-15.
17. Coolidge T, Hillstead MB, Farjo N, Weinstein P, Coldwell SE. Additional psychometric data for the Spanish Modified Dental Anxiety Scale, and psychometric data for a Spanish version of the Revised Dental Beliefs Survey. BMC oral health. 2010;10:1-8.
18. Erciyas K, Hamamci Z, Buyukozturk S, Erciyas A. Revised dental beliefs survey: reliability and validity of a 22‐item modified Turkish version. Journal of oral rehabilitation. 2009;36(11):831-9.
19. Balgiu BA, Sfeatcu R, Sluşanschi O, Dumitrache MA. Linguistic and cultural validation of the Romanian version of the Revised Dental Beliefs survey. Int J Med Dent. 2020;24:381-9.
20. Coolidge T, Heima M, Coldwell SE, Weinstein P, Milgrom P. Psychometric properties of the revised dental beliefs survey. Community dentistry and oral epidemiology. 2005;33(4):289-97.
21. Chiapetti N, Serbena CA. Uso de álcool, tabaco e drogas por estudantes da área de saúde de uma universidade de Curitiba. Psicologia: Reflexão e Crítica. 2007;20:303-13.
22. Franca Cd, Colares V. Estudo comparativo de condutas de saúde entre universitários no início e no final do curso. Revista de Saúde Pública. 2008;42:420-7.
23. Piqueras JA, Kuhne W, Vera-Villarroel P, Van Straten A, Cuijpers P. Happiness and health behaviours in Chilean college students: a cross-sectional survey. BMC public health. 2011;11:1-10.
24. de Oliveira Cunha R, Leite ICG. Factors associated with recent and regular non-use of dental services by students from a university in southeastern Brazil: a cross-sectional study. BMC Oral Health. 2022;22(1):612.
25. Hambleton RK, Patsula L. Adapting tests for use in multiple languages and cultures. Social indicators research. 1998;45:153-71.
26. MacCallum RC, Widaman KF, Zhang S, Hong S. Sample size in factor analysis. Psychological methods. 1999;4(1):84.
27. Milgrom P. Treating fearful dental patients: a patient management handbook. (No Title). 1995.
28. Beaton DE, Bombardier C, Guillemin F, Ferraz MB. Guidelines for the process of cross-cultural adaptation of self-report measures. Spine. 2000;25(24):3186-91.
29. Plichta SB, Kelvin EA. Munro’s statistical methods for health care research. 2013.
30. Harerimana A, Mtshali NG. Using exploratory and confirmatory factor analysis to understand the role of technology in nursing education. Nurse Education Today. 2020;92:104490.
31. Hosseini Koukamari P, Naami A, Allahyari T. Confirmatory and exploratory factor analyses of adaptive performance scale: a study among hospital nurses. Iranian Journal of Ergonomics. 2015;3(1):41-9.
32. Black WC, Babin BJ, Anderson RE. Multivariate data analysis: A global perspective: Pearson; 2010.
33. Hair JF, Black WC, Babin BJ, Anderson RE, Tatham RL. Multivariate data analysis 6th Edition. Pearson Prentice Hall. New Jersey. humans: Critique and reformulation …; 2006.
34. Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research. 1981;18(1):39-50.
35. Mayers A. Introduction to statistics and SPSS in psychology. (No Title). 2013.
36. Leguina A. A primer on partial least squares structural equation modeling (PLS-SEM). Taylor & Francis; 2015.
37. Berggren U. Long‐term management of the fearful adult patient using behavior modification and other modalities. Journal of Dental Education. 2001;65(12):1357-68.
38. Appukuttan DP. Strategies to manage patients with dental anxiety and dental phobia: literature review. Clinical, cosmetic and investigational dentistry. 2016:35-50.
39. Allen KD, Stanley R, McPherson K. Evaluation of behavior management technology dissemination in pediatric dentistry. Pediatr Dent. 1990;12(2):79-82.
40. Corah NL. Dental anxiety: assessment, reduction and increasing patient satisfaction. Dental Clinics of North America. 1988;32(4):779-90.
41. Ghaffari M, Esfahani SN, Rakhshanderou S, Koukamari PH. Evaluation of health belief model-based intervention on breast cancer screening behaviors among health volunteers. Journal of Cancer Education. 2019;34(5):904-12.
42. Öhrn K, Hakeberg M, Abrahamsson KH. Dental beliefs, patients’ specific attitudes towards dentists and dental hygienists: a comparative study. International journal of dental hygiene. 2008;6(3):205-13.
Aljauid AS, Al-Otaibi AO, Aldawood MM, Mohamed RN, Basha S, Al Thomal Y. Oral health behavior of medical, dental, and pharmacology students in Taif University: A cross-sectional study. J Adv Oral Res. 2020;11(1):83-92. [Link] [DOI:10.1177/2320206820918746]
Kim HJ, Cho Y, Noh Y, Joo JY, Park HR. A decision tree to identify the combinations of non-communicable diseases that constitute the highest risk for dental caries experience: A hospital records-based study. PLoS One. 2021;16(10):e0257079. [Link] [DOI:10.1371/journal.pone.0257079]
Ghanbari Z, Moradi Y, Samiee N, Moradpour F. Dental caries prevalence in relation to the cardiovascular diseases: cross-sectional findings from the Iranian Kurdish population. BMC Oral Health. 2024;24(1):509. [Link] [DOI:10.1186/s12903-024-04280-z]
Soltani MR, Sayadizadeh M, Raeisi Estabragh S, Ghannadan K, Malek-Mohammadi M. Dental caries status and its related factors in Iran: A meta-analysis. J Dent. 2020;21(3):158-76. [Link]
López R. Periodontal disease and adverse pregnancy outcomes. Evid Based Dent. 2008;9(2):48. [Link] [DOI:10.1038/sj.ebd.6400581]
Faraji Khiavi F, Ghobadian S, Zakavi F, Golpasand Hagh L. Comparative study of dental care and dental services in Iran and selected countries. REVISTA PUBLICANDO. 2018;5(15):95-113. [Link]
Pouraskari Z, Yazdani R, Hessari H. Exploring the challenges in covering dental services through complementary insurance in Iran: A qualitative study. Int J Dent. 2024;2024:6982460. [Link] [DOI:10.1155/2024/6982460]
Rezaei S, Pulok MH, Zahirian Moghadam T, Zandian H. Socioeconomic-related inequalities in dental care utilization in northwestern Iran. Clin Cosmet Investig Dent. 2020;12:181-9. [Link] [DOI:10.2147/CCIDE.S253242]
Pai M, Rajesh G, Yellapurkar S. Development of modified dental beliefs scale among an adolescent rural population. J Int Soc Prev Community Dent. 2021;11(2):132-7. [Link] [DOI:10.4103/jispcd.JISPCD_367_20]
Kulich KR, Berggren U, Hakeberg M, Gustafsson JE. Factor structure of the dental beliefs survey in a dental phobic population. Eur J Oral Sci. 2001;109(4):235-40. [Link] [DOI:10.1034/j.1600-0722.2001.00118.x]
Karibe H, Kato Y, Shimazu K, Okamoto A, Heima M. Gender differences in adolescents' perceptions toward dentists using the Japanese version of the dental beliefs survey: A cross-sectional survey. BMC Oral Health. 2019;19(1):144. [Link] [DOI:10.1186/s12903-019-0845-y]
Moore R. Trusting the dentist-expecting a leap of faith vs. a well-defined strategy for anxious patients. Dent J. 2022;10(4):66. [Link] [DOI:10.3390/dj10040066]
Milgrom P. Treating fearful dental patients: A clinical handbook. New York: Appleton; 1985. [Link]
Wu L, Buchanan H. Translation and validation of the revised dental beliefs survey (DBS-R) in China. Psychol Health Med. 2020;25(7):812-23. [Link] [DOI:10.1080/13548506.2019.1668568]
Kvale G, Milgrom P, Getz T, Weinstein P, Johnsen TB. Beliefs about professional ethics, dentist-patient communication, control and trust among fearful dental patients: The factor structure of the revised dental beliefs survey. Acta Odontol Scand. 2004;62(1):21-9. [Link] [DOI:10.1080/00016350310005780]
Abrahamsson KH, Hakeberg M, Stenman J, Ohrn K. Dental beliefs: Evaluation of the Swedish version of the revised dental beliefs survey in different patient groups and in a non-clinical student sample. Eur J Oral Sci. 2006;114(3):209-15. [Link] [DOI:10.1111/j.1600-0722.2006.00358.x]
Coolidge T, Hillstead MB, Farjo N, Weinstein P, Coldwell SE. Additional psychometric data for the Spanish modified dental anxiety scale, and psychometric data for a Spanish version of the revised dental beliefs survey. BMC Oral Health. 2010;10:12. [Link] [DOI:10.1186/1472-6831-10-12]
Erciyas K, Hamamci Z, Buyukozturk S, Erciyas AF. Revised dental beliefs survey: reliability and validity of a 22-item modified Turkish version. J Oral Rehabil. 2009;36(11):831-9. [Link] [DOI:10.1111/j.1365-2842.2009.02001.x]
Balgiu BA, Sfeatcu LR, Slusanschi O, Adina DM. Linguistic and cultural validation of the Romanian version of the revised dental beliefs survey. Int J Med Dent. 2020;24:381-9. [Link]
Coolidge T, Heima M, Coldwell SE, Weinstein P, Milgrom P. Psychometric properties of the revised dental beliefs survey. Community Dent Oral Epidemiol. 2005;33(4):289-97. [Link] [DOI:10.1111/j.1600-0528.2005.00214.x]
Chiapetti N, Serbena CA. Alcohol, tobacco and other drugs used by students of health services from a University in Curitiba. PSICOLOGIA REFLEXÃO E CRÍTICA. 2007;20(2):303-13. [Portuguese] [Link] [DOI:10.1590/S0102-79722007000200017]
Franca CD, Colares V. Comparative study of health behavior among college students at the start and end of their courses. REVISTA DE SAÚDE PÚBLICA. 2008;42(3):420-7. [Portuguese] [Link] [DOI:10.1590/S0034-89102008000300005]
Piqueras JA, Kuhne W, Vera-Villarroel P, Van Straten A, Cuijpers P. Happiness and health behaviours in Chilean college students: A cross-sectional survey. BMC Public Health. 2011;11:443. [Link] [DOI:10.1186/1471-2458-11-443]
Hagman J, Wide U, Werner H, Hakeberg M. Oral health and oral health behavior in young adults with caries disease. BDJ Open. 2021;7(1):28. [Link] [DOI:10.1038/s41405-021-00084-3]
De Oliveira Cunha R, Leite ICG. Factors associated with recent and regular non-use of dental services by students from a university in southeastern Brazil: A cross-sectional study. BMC Oral Health. 2022;22(1):612. [Link] [DOI:10.1186/s12903-022-02648-7]
Saboohi Z, Hoseini Koukamari P, Rohani M, Rawlins J, Karimy M. Health promoting behaviors in Iranian female adolescents during the COVID-19 pandemic. Health Educ Health Promot. 2022;10(2):377-83. [Link]
Hambleton RK, Patsula L. Adapting tests for use in multiple languages and cultures. Soc Indic Res. 1998;45:153-71. [Link] [DOI:10.1023/A:1006941729637]
MacCallum RC, Widaman K, Zhang S, Hong S. Sample size in factor analysis. Psychol Methods. 1999;4(1):84-99. [Link] [DOI:10.1037/1082-989X.4.1.84]
Milgrom P. Treating fearful dental patients: A patient management handbook. Seattle: University of Washington; 1995. [Link]
Beaton DE, Bombardier C, Guillemin F, Ferraz MB. Guidelines for the process of cross-cultural adaptation of self-report measures. Spine (Phila Pa 1976). 2000;25(24):3186-91. [Link] [DOI:10.1097/00007632-200012150-00014]
Kellar SP, Kelvin EA. Munro's statistical methods for health care research. Philadelphia: Lippincott Williams & Wilkins; 2013. [Link]
Harerimana A, Mtshali NG. Using exploratory and confirmatory factor analysis to understand the role of technology in nursing education. Nurse Educ Today. 2020;92:104490. [Link] [DOI:10.1016/j.nedt.2020.104490]
Hosseini Koukamari P, Naami A, Allahyari T. Confirmatory and exploratory factor analyses of adaptive performance scale: A study among hospital nurses. Iran J Ergon. 2015;3(1):41-9. [Persian] [Link]
Hair JF, Black WC, Babin BJ, Anderson RE. Multivariate data analysis: A global perspective. London: Pearson; 2010. [Link]
Hair JF, Black WC, Babin BJ, Anderson RE, Tatham. Multivariate data analysis. 6th ed. New Jersey: Prentice Hall; 2006. [Link]
Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. J Mark Res. 1981;18(1):39-50. [Link] [DOI:10.1177/002224378101800104]
Mayers A. Introduction to statistics and SPSS in psychology. London: Pearson; 2013. [Link]
Leguina A. A primer on partial least squares structural equation modeling (PLS-SEM). Int J Res Method Educ. 2015;38(2):220-1. [Link] [DOI:10.1080/1743727X.2015.1005806]
Berggren U. Long-term management of the fearful adult patient using behavior modification and other modalities. J Dent Educ. 2001;65(12):1357-68. [Link] [DOI:10.1002/j.0022-0337.2001.65.12.tb03495.x]
Appukuttan DP. Strategies to manage patients with dental anxiety and dental phobia: literature review. Clin Cosmet Investig Dent. 2016;8:35-50. [Link] [DOI:10.2147/CCIDE.S63626]
Allen KD, Stanley RT, McPherson K. Evaluation of behavior management technology dissemination in pediatric dentistry. Pediatr Dent. 1990;12(2):79-82. [Link]
Corah NL. Dental anxiety. Assessment, reduction and increasing patient satisfaction. Dent Clin North Am. 1988;32(4):779-90. [Link] [DOI:10.1016/S0011-8532(22)00310-X]