Learning, Accessing, and Choosing Cone Beam Computed Tomography: A Survey of Endodontists and Endodontic Specialty Students

Learning, Accessing, and Choosing Cone Beam Computed Tomography: A Survey of Endodontists and Endodontic Specialty Students | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Learning, Accessing, and Choosing Cone Beam Computed Tomography: A Survey of Endodontists and Endodontic Specialty Students Raziye Esra Kayta, Damla Kırıcı, Çiğdem Apaydın This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8520727/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective: This study aims to examine the views of endodontic specialists and postgraduate students in endodontics practicing in Turkey on the use of Cone Beam Computed Tomography (CBCT). Methods: A total of 172 participants completed the CBCT-ASAU scale, which includes six factors: use in complicated cases (A1), measurement of proximity to adjacent anatomy and trauma assessment (A2), diagnostic and treatment planning (A3), ideal imaging (A4), access to CBCT (A5), and use according to lesion size (A6). Data were analyzed based on gender, CBCT training, professional experience, academic title, institution type, geographic region, and CBCT usage, using t-tests, Kruskal-Wallis, and Mann-Whitney U tests. Results: Gender, academic title, institution type, and professional seniority did not show significant effects on CBCT attitudes (p > 0.05). CBCT training significantly influenced A2 and A6 scores (p < 0.05). CBCT users scored significantly higher than non-users in most factors (A1, A2, A3, A5, A6; p < 0.05). Overall, training, experience and actual CBCT use were associated with more positive attitudes and higher reported use. Conclusion: The findings indicate that CBCT education and practical experience play key roles in endodontists’ and trainees’ attitudes toward CBCT use. The CBCT-ASAU tool shows potential for assessing clinical adoption and guiding educational strategies in endodontics. Health sciences/Diseases Health sciences/Health care Health sciences/Medical research Cone-Beam Computed Tomography (CBCT) Endodontics CBCT Knowledge and Attitudes Specialty Training Figures Figure 1 Introductıon Successful endodontic treatment depends on a good clinical and radiographic examination. Radiographic examination in endodontics is one of the important steps in diagnosis and treatment planning. Panoramic and periapical radiographs are the most commonly used imaging modalities for diagnosis and treatment planning. Although intraoral radiographs are fundamental for diagnosis and treatment planning in endodontics, the resulting two-dimensional image offers a limited perspective. Conventional radiographs have limitations such as geometric distortions, anatomical region superpositions, inadequate diagnosis of small periapical lesions, lack of standardization in the radiographs taken and inadequate in cases where proper placement of the film in the mouth is not possible. (1-4) In recent years, three-dimensional imaging methods have been used in the field of health with the development of technology. Radiographic examination in endodontics is one of the important steps in diagnosis and treatment planning. Computed tomography (CT), which is now routinely used in medicine, has made it possible to overcome the inadequacies of conventional two-dimensional (2D) film technology.(5) However, the most important problems of CT systems are their high cost, the need for a large area and the high patient radiation dose. In the early 2000s, CT scanners with a smaller footprint and lower doses began to be produced for use in dentistry. These devices use a conical shaped x-ray with a two-dimensional sensor and are called "Cone Beam Computed Tomography" (CIBT)(6) Cone-beam computed tomography (CIBT) is a contemporary digital imaging technology that provides undistorted, three-dimensional information of teeth and surrounding tissues to aid the diagnostic procedure and clarify clinical decision-making. Cone-beam computed tomographic imaging provides a more detailed three-dimensional image that can influence treatment recommendations and can be used in all phases of treatment, including diagnosis, treatment planning, during the treatment phase and post-treatment evaluation and follow-up. It is superior to conventional radiography by reducing or avoiding superposition of surrounding tissues on each other. Structures that cannot be observed in conventional periapical radiography can be observed with sections taken in axial, coronal and sagittal planes between 0.125-2 mm. (7) Previous studies have primarily focused on assessing knowledge and attitudes toward CBCT among dental students or general dentists.(8,9,10) However, limited data are available regarding how endodontic specialists and endodontic specialty/doctoral students utilize CBCT in clinical decision-making, how they acquire CBCT-related knowledge, and how training influences their usage patterns. Understanding these factors is essential for identifying educational gaps, optimizing specialty training curricula, and promoting appropriate CBCT use aligned with current recommendations. Therefore, the aim of this study was to evaluate the current status of CBCT use among endodontic specialists and endodontic specialty/doctoral students in Turkey. Specifically, the study aimed to assess participants’ training in CBCT, access to the technology, tendencies to use CBCT in case-specific diagnosis and treatment planning, its role in identifying endodontic complications and evaluating treatment outcomes, and their overall perceptions regarding CBCT use. By exploring these aspects, the study seeks to provide insight into educational needs and usage behaviors that may inform future training strategies and guideline-based clinical practice. Research Problem and Sub-Problems The primary research question guiding this investigation is: "What are the views of endodontists and endodontic specialty/doctoral students on the accessibility and use of Cone Beam Computed Tomography (CBCT)?" To address this central question, the following sub-problems are formulated to examine whether significant differences exist in participants' views based on the following variables: a) Gender b) Academic title c) Years of professional experience d) Type of institution of employment e) Current CBCT usage status f) Receiving training in CBCT usage Materials-Method This section includes the research model, population and sample, data collection tools and data analysis. Research Model The study employs a survey model as it aims to describe an existing phenomenon in its current state. Survey research provides the quantitative analysis of trends, attitudes, or opinions within a defined population by examining data collected from a representative sample. The researcher can make generalizations about the population based on this sample (11). Working Group The working group consists of endodontists and endodontic specialty/doctoral students working in Turkey (n = 172). A power analysis was conducted using the G* Power 3.1 program to determine whether the total sample size of 172 participants was sufficient to achieve the required statistical power for the analyses.(12) The G * Power power analysis indicated that, based on the parameters of medium effect size (f = 0.25), α = 0.05, and 1–β = 0.95, the required minimum sample size for the ANOVA design was 132. Since the sample size in the present study (172 participants) exceeds this value, it provides sufficient statistical power for the parametric analyses. Furthermore, the 172-participant sample size is also adequate for applying non-parametric tests such as the Mann–Whitney U and Kruskal–Wallis tests . A convenience sampling method was employed to select participants. This sampling technique involves gathering data from individuals who are readily accessible to the researcher (13). Table 1 provides demographic information regarding the participants. Preparation of the Survey Form The survey instrument was developed based on a review of previous studies conducted on similar topics. The items in these studies were revised through expert consensus and new items were created to prepare a survey form comprising 39 items. The items were articulated in clear and accessible language. Research data were collected through an anonymous online survey. Participants were informed about the purpose of the study, the researchers’ contact information, and the voluntary nature of participation, and informed consent was obtained from all participants by their agreement to proceed with the survey. The survey consists of two sections: Part 1 included 8 items on demographic information (gender, professional title, professional experience, institution and city) as well as questions related to CBCT usage, educational background and education tool. Part 2 comprised 31 items that evaluated participants’ opinions on CBCT usage and cases they have used. After ethical approval was obtained, the finalized survey was administered online using Google Forms. Ethics Committee Approval This study was conducted in accordance with international ethical standards and the World Health Organization Helsinki Declaration at Akdeniz University Faculty of Dentistry, Department of Endodontics. This study was approved by the Clinical Research Ethics Committee of the Faculty of Medicine, Akdeniz University (418/2023). Data Collection Process The finalized survey was distributed to endodontists and postgraduate (specialization/doctoral) students across Turkey via e-mail and through social media platforms using an online survey link. The survey remained open for 3 months. Stevens' (14) criterion of at least 5 to 20 participants per independent variable was taken into account in determining the sample size. Given the 31-item scale developed by the researchers, the minimum required sample size was calculated as 31 × 5 = 155. However, considering the potential of incorrect data, the sample size was accepted as at least 170. Development of the Attitude Scale on the Accessibility and Use of Cone Beam Computed Tomography (CBCT-ASAU) The scale was developed following the steps proposed by Carpenter (15). The following section details the systematic process undertaken in the scale’s development. Item Pool Creation Stage In line with the intended purpose of the measurement tool, the target population was defined as endodontists practicing in Turkey and postgraduate students specializing in endodontics. Literature review on the subject was conducted, encompassing books, theses and articles. An initial pool of survey items was created in light of the information gained from these sources. The stage of seeking expert feedback The purpose of seeking expert guidance is to ensure the content and face validity of the scale. Content validity evaluates how well the items represent the construct being measured (16) . Following this, face validity was evaluated to determine whether the survey items were clearly relevant to the research topic and accurately captured the intended construct (17).The 31-item draft scale was evaluated by two faculty members from the Department of Dentistry, three different faculty members from the same department, a faculty member specialized in measurement, and a language expert who had completed doctoral studies to assess linguistic appropriateness in Turkish. Based on their feedback, the scale was revised with targeted additions and deletions to improve clarity and alignment with the construct. A five-point Likert-type rating (5=completely agree, 1=completely disagree) was used in the scale. SPSS 25.0 package program was used to assess the construct validity of the scale. Before applying factor analysis, the suitability of the data for this procedure was evaluated. Specifically, corrected total correlations of the items were examined and no items were identified to have values equal to or less than 0.25. Given that the instrument was newly developed and had no pre-existing validation, EFA was applied to the items to ensure the construct validity of the scale. To understand the suitability of the scale for factor analysis, the Kaiser-Meyer-Olkin (KMO) coefficient and the Bartlett test were calculated. In this regard, the KMO test measurement result should be .60 and above, and the Bartlett sphericity test result should be statistically significant (18) To clarify the factor structure of the scale, varimax (vertical) rotation was used during exploratory factor analysis (EFA). Item loadings of 0.50 or greater were considered acceptable for inclusion in a factor. The Principal Component Analysis extraction method was employed in EFA. The KMO value of 0.88 suggested that the sample size is sufficient (19); the data structure obtained from the Barlett sphericity test was also identified as suitable for EFA (χ2 = 2305.012, p < .001). Items exhibiting high loadings on two factors simultaneously, with differences of 0.10 or less between loadings, were considered overlapping. In this context, 7 items (I6, I9, I10, I4, I25, I21, I28) were removed due to factor loadings below 0.50, cross-loading, or lack of semantic coherence within their respective factors. As a result, the final scale consisted of 24 items. The factor loadings and explained variance of items in the factors are displayed in Table 2. CBCT-ASAU is a multidimensional scale. As in Table 2, the factor loadings of the items across the six factors of CBCT-ASAU are above 0.50. The exploratory factor analysis revealed that the scale explains approximately 65% of the total variance. Specifically, the variance explained by each factor is as follows: 17.83% for the use of CBCT in complicated cases (A1), 11.66% for the measurement of proximity to adjacent anatomy and use of CBCT in dental trauma (A2), 10.15% for the use of CBCT in diagnosis and treatment planning (A3), 9.67% for the use of CBCT for ideal imaging (A4), 8.41% for the ease of access to CBCT (A5), and 7.37% for the use of CBCT according to the size of the lesion (A6). The total reliability of the scale is αtotal = .82. The reliability coefficients of the six subfactors are also satisfactory: α A1 = .90, α A2 = .82, α A3 = .80, α A4 = .76, α A5 = .71 and α A6 = .78, indicating strong internal consistency in accordance with established guidelines (20). Descriptive statistics suggested that the mean score for the factors A6 ( = 3.74) is higher than those of the other factors. Hence, it is most probable that the participants demonstrate a high tendency to use the CBCT tool according to the lesion size. Descriptive Statistics, Reliability, and Inter-Construct Correlations of the CBCT Scale The Pearson correlation coefficient was used to examine relationships between factors, with values interpreted as high (0.70–1.00), moderate (0.30–0.69), and low (<0.29) (21) Table 3 displays the descriptive statistics, reliability coefficients, and inter-variable correlations among the five factors of the CBCT scale. Inter-item correlations indicate significant positive relationships among most items within the same factor (p < 0.01). For instance, A1 correlated with A2 (r = 0.574), A3 (r = 0.515), A4 (r = 0.509), A5 (r = 0.336), and A6 (r = 0.547). Similarly, A2 correlated with A3 (r = 0.540), A4 (r = 0.403), and A6 (r = 0.451), while A3 correlated with A4 (r = 0.362), A5 (r = 0.229), and A6 (r = 0.319). Correlations for A4 and A5 were lower with some items (A4–A5: r = 0.049; A5–A6: r = 0.024), suggesting that these items, while part of the scale, capture slightly distinct aspects of the constructs. Overall, the pattern of correlations demonstrates that the items are sufficiently related to measure their respective factors while maintaining discriminant properties between factors, supporting both convergent and discriminant validity (22). These findings indicate that the scale is psychometrically robust and appropriate for further analyses, including factor-based or structural modeling approaches. The internal consistency, composite reliability, average variance extracted, and inter-itemcorrelations for the scale factors are presented in Table 3. Cronbach’s alpha values ranged from 0.71 to 0.90, indicating satisfactory internal consistency for all factors (23). Composite reliability (CR) values varied between 0.74 and 0.89, and average variance extracted (AVE) values ranged from 0.45 to 0.65, suggesting acceptable convergent validity across the factors (24). Discriminant Validity Discriminant validity was examined to assess whether the subdimensions of the scale are conceptually distinct from each other, using the Fornell–Larcker criterion and the correlation matrix. As shown in Table 4, the √AVE values of all factors exceed their correlations with other constructs. According to Fornell and Larcker (24), if the √AVE of a construct is greater than its correlations with other constructs, discriminant validity is established. In addition, since all inter-construct correlations are below .574, the HTMT values are also expected to be below the recommended threshold (HTMT < .85;(25)). Therefore, discriminant validity among the subdimensions of the scale is satisfactory according to both the Fornell–Larcker criterion and the correlation structure. Table 4 presents a comparison between the √AVE values and the highest correlations for each construct. Confirmatory Factor Analysis AMOS 16 program was used for confirmatory factor analysis (CFA). The results yielded χ 2 = 466.184, df=245, χ 2 / df = 1.90, RMSEA = 0.07 (90% CI = 0.063, 0.083) values. The fit indices of the scale were examined, and it was observed that the single-factor model demonstrated acceptable fit: AGFI (Adjusted Goodness of Fit Index) = 0.76, GFI (Goodness of Fit Index) = 0.81, NFI (Normed Fit Index) = 0.79, CFI (Comparative Fit Index) = 0.89, SRMR (Standardized Root Mean Square Residual) = 0.09, TLI (Tucker-Lewis Index) = 0.87, and RMR (Root Mean Square Residual) = 0.13 (26). These values indicate that the model fit indices fall within the acceptable range. The fit indices of the scale were examined and that the fit statistics of the single-factor model were within the acceptable range (26). Examination of fit indices demonstrated that the six-factor structure showed a good fit (Figure 1). Data Analysis SPSS 25 and AMOS 16 statistical package programs were used for data analysis. The statistical significance level was set at p <0.05. Data analysis proceeded in two stages. Initially, descriptive statistics were obtained for the key variables. Subsequently, EFA and CFA were conducted to assess the scale’s validity. The maximum likelihood estimation method was employed to estimate model parameters in CFA. Model fit was evaluated using multiple indices, including RMSEA (root means square error of approximation), RMR (root means square residual), GFI (goodness of fit index), CFI (comparative fit index), AGFI (adjusted goodness of fit index), NFI (normed fit index), χ²/df = CMIN/DF (chi-square / degrees of freedom) and p (level of significance). For the suitability of DFA and model fit indexes (values), the values presented in Table 5 below were considered (26) To test whether participants’ responses to the scale items differed significantly according to independent variables, Levene’s Test of Homogeneity of Variances was first conducted to assess variance equality. For variances meeting the homogeneity assumption, t-test was applied for the 'gender' variable, Mann-Whitney U test for the variables of education status and KIBT usage status, one-way variance (ANOVA) for the seniority variable, and Kruskal Wallis analysis for the variables of title, institution of employment and region. Based on ANOVA analysis results, the Least Significant Difference (LSD) post hoc test was used to identify the source of any significant differences. Results Gender: Participants’ views on the CBCT-ASAU scale factors did not differ significantly by gender (p > 0.05). Female participants reported higher mean scores in factors A1, A2, and A6, while male participants reported higher mean scores in factors A3, A4, and A5. These findings indicate that gender does not significantly influence overall opinions on CBCT usage, although there may be differences in experience in certain areas. The results are depicted in Table 6. CBCT training in CBCT status Participants who received training scored significantly higher in factors A2 (proximity to adjacent anatomy and trauma) and A6 (usage according to lesion size) (p < 0.05). Although no statistically significant differences were found in other factors, training generally had a positive impact on attitudes toward CBCT usage. Table 7 presents the results. Professional Experience Professional seniority did not result in statistically significant differences in views on CBCT-ASAU factors (p > 0.05). However, more experienced participants reported higher mean scores in complex case usage (A1) and CBCT accessibility (A5). (Table 8) Academic Title Participants’ academic titles did not significantly affect their opinions on CBCT usage (p > 0.05). Nevertheless, Assistant and Associate Professors showed a greater tendency to integrate CBCT into their clinical decision-making processes.(Table 9) Type of Institution No significant differences were found in CBCT-ASAU factors based on the type of institution (university hospital, private clinic, oral and dental health center) (p > 0.05). University hospital staff generally demonstrated higher usage tendencies, while private clinic staff reported lower scores. (Table 10) CBCT usage status Participants who used CBCT scored significantly higher than non-users in factors A1, A2, A3, A5, and A6 (p < 0.05). These findings suggest that CBCT usage is particularly influential in areas such as managing complex cases, trauma assessment, diagnosis, lesion evaluation, and accessibility.(Table 11) Discussion The present study aimed to develop and preliminarily validate a scale designed to assess CBCT-related decision-making behaviors, educational exposure, and access patterns among endodontists and endodontic specialty/doctoral students in Turkey. Unlike diagnostic accuracy studies,( 1 – 4 ) the primary objective of this instrument is not to directly improve clinical outcomes but to evaluate how CBCT is perceived, selected, and utilized in routine and complex endodontic scenarios. In this context, the scale should be considered a behavioral and educational assessment tool rather than a clinical decision-support system. Although CBCT-related attitude and knowledge scales have been reported previously, most existing instruments target undergraduate students, general dentists, or mixed professional groups. The present scale specifically focuses on endodontists and endodontic specialty/doctoral students and emphasizes case-based CBCT utilization, access, and training-related dimensions.( 8 – 10 ) Given the differences in CBCT accessibility, referral systems, and educational structures across countries, the development of a context-specific instrument addressing national practice patterns represents a necessary step toward meaningful assessment rather than mere duplication of existing tools. The domains included in the scale were structured in accordance with current CBCT guidelines and commonly encountered endodontic decision points. International recommendations from the American Association of Endodontists (AAE) and the American Academy of Oral and Maxillofacial Radiology (AAOMR) emphasize selective CBCT use, particularly in complex cases involving trauma, resorptive defects, complex root anatomy, and proximity to critical anatomical structures.( 27 ) Accordingly, the scale dimensions were designed to reflect these clinically relevant scenarios, allowing indirect evaluation of guideline adherence and clinical reasoning patterns. In this study, the age criterion is not included in the demographic information. The age criterion was not included in the demographic information because it was thought that the duration of professional experience and seniority level, rather than age itself, could make a difference in the use of CBCT.( 28 ) In our study, expert training emerged as the primary source of knowledge for CBCT interpretation, followed by scientific articles and publications, professional courses, congresses, undergraduate education, and social media, respectively. In a separate survey conducted among undergraduate and postgraduate students in the Indian population, the majority of participants (74.19%) reported learning about CBCT during their undergraduate education, while 25.16% gained knowledge through seminars, 29.67% via the internet, and 5% through conferences. Most participants (69.68%) believed that their faculties provided sufficient CBCT training; however, 20% considered the training inadequate, primarily due to limited opportunities for practical, case-based learning. Furthermore, 74.84% of respondents indicated that CBCT education should be delivered during the clinical period, whereas only a small proportion felt it should be included in the pre-clinical curriculum. Overall, it was emphasized that undergraduate students receive relatively limited CBCT training, while postgraduate students acquire more comprehensive knowledge through seminars and professional courses.( 29 ) No significant associations were found between professional experience and CBCT utilization patterns. This finding aligns with previous study( 30 ) reporting that increased availability of CBCT systems and widespread technological integration have reduced experience-based disparities in imaging preferences. Moreover, the lack of significant gender-based differences supports existing evidence that CBCT usage is driven more by clinical indication and training than by demographic factors.( 8 , 31 ) Studies in the literature indicate clear differences between undergraduate and postgraduate education regarding both the level and timing of CBCT training. In a study conducted by Kamburoğlu et al.( 9 ), postgraduate students were reported to have a higher level of CBCT awareness compared with undergraduate students; postgraduate students primarily acquired their CBCT knowledge through seminars, whereas undergraduate students learned mainly through faculty-based courses. Nevertheless, the majority of participants stated that they intended to use CBCT technology in the future, and a substantial proportion of dentists considered the CBCT training received during undergraduate education to be insufficient. Similarly, another survey study revealed that undergraduate students demanded CBCT education to be delivered during the clinical period and in a practical manner, emphasizing the integration of theoretical knowledge with hands-on training. In the study by Parashar et al.( 32 ), it was reported that advanced CBCT training in dental schools in the United States, the United Kingdom, and Australia was predominantly provided within postgraduate programs, while remaining limited in undergraduate curricula. The authors emphasized that if general dental practitioners are to be authorized to use CBCT, CBCT education must be formally integrated into undergraduate dental training. Consistent with these findings, the results of our study showed that undergraduate education ranked low as a source of CBCT interpretation knowledge. This suggests that theoretical CBCT instruction alone at the undergraduate level is insufficient and should be supported by case-based and practical training to improve students’ image interpretation skills. The findings demonstrate that CBCT training significantly influences case-based utilization, particularly in trauma-related cases, large lesions, and proximity assessment to adjacent anatomy. This highlights the role of structured education in shaping appropriate CBCT usage behaviors. Conversely, the absence of significant differences in some domains suggests that mere access to CBCT does not guarantee optimal utilization, reinforcing the importance of targeted educational interventions. In this respect, the scale may serve as a useful tool for identifying educational gaps and guiding curriculum development in undergraduate and specialty training programs. The majority of participants were affiliated with university hospitals, where CBCT availability is typically higher due to referral-based workflows and educational responsibilities. However, the absence of significant institutional differences suggests that technological infrastructure in private clinics and public oral health centers has improved over time. This reflects a broader shift toward more uniform access to advanced imaging modalities. This study has several limitations. The use of convenience sampling and a relatively limited sample size restricts generalizability and precludes definitive validation of the instrument. Additionally, the scale validation process represents a preliminary step, focusing primarily on factor structure rather than comprehensive psychometric evaluation. Future studies should aim to include larger and more diverse samples, incorporate test–retest reliability, internal consistency, convergent and discriminant validity assessments, and examine the predictive value of the scale in relation to actual clinical behavior. Within the limitations of this study, the proposed scale provides a preliminary, context-specific instrument for assessing CBCT-related decision-making behaviors, educational exposure, and access among endodontists and endodontic specialty/doctoral students. Although the scale does not directly measure diagnostic or therapeutic outcomes, it offers potential value as an educational and quality-assessment tool by identifying usage patterns, training-related differences, and areas of inconsistency with established CBCT guidelines. The instrument may be used to evaluate the effectiveness of CBCT education, monitor guideline adherence, and inform curriculum development in endodontic training programs. Further validation studies with larger samples and expanded psychometric analyses are required before widespread clinical or educational implementation. Nonetheless, the present findings contribute to understanding CBCT utilization behaviors in a national context and provide a foundation for future research aimed at optimizing CBCT use in endodontic practice. Declarations Disclosure: The authors report no conflicts of interest Funding: Not applicable Author Contribution E. K. conducted the data collection. Ç. A. performed the data analysis. D.K.wrote the manuscript. All authors reviewed and edited the manuscript Data Availability All data are available upon reasonable request to the corresponding author. References Forsberg J, Halse A. Radiographic simulation of a periapical lesion comparing the paralleling and the bisecting-angle techniques. Int Endod J. 1994;27(3):133-8. T yndall DA, Clifton TL, Webber RL, Ludlow JB, Horton RA. TACT imaging of primary caries. 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Use of cone beam computed tomography in endodontics 2015 update. Oral Surg Oral Med Oral Pathol Oral Radiol 2015;120:508–12. 28. Mathew AI, Lee SC, Ha WN, Rossi-Fedele G, Dogramaci EJ. Cone-beam co uted tomography Predictors and characteristics of usage in Australia and New Zealand, a multifactorial analysis. Aust Endod J. 2023;49(2):247-55.mp Shah PH, Venkatesh R. Dental students' knowledge and attitude towards cone-beam computed tomography: An Indian scenario. Indian J Dent Res. 2016;27(6):581-5. Krug R, Connert T, Beinicke A, Soliman S, Schubert A, Kiefner P, et al. When and how endodontic specialists use cone-beam computed tomography? Aust Endod J. 2019;45(3):365-72. Shah PH, Venkatesh R. Dental students' knowledge and attitude towards cone-beam computed t tomography: An Indian scenario. Indian J Dent Res. 2016;27(6):581-5. Parashar V, Whaites E, Monsour P, Chaudhry J, Geist JR. Cone beam computed tomography in dental education: a survey of US, UK, and Australian dental schools. J Dent Educ. 2012;76(11):1443-7. Tables Tables 1 to 11 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table1.docx Table2.docx Table3new.docx Table4new.docx Table5.docx Table6.docx table7.docx table8.docx Table9.docx Table10.docx Table11.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8520727","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":581894636,"identity":"ccb71558-149a-429e-9008-96bf79837223","order_by":0,"name":"Raziye Esra Kayta","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Raziye","middleName":"Esra","lastName":"Kayta","suffix":""},{"id":581894637,"identity":"20034530-5b3c-4ec7-afc2-ea0e76b317fa","order_by":1,"name":"Damla 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10:18:21","extension":"docx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":21422,"visible":true,"origin":"","legend":"","description":"","filename":"Table10.docx","url":"https://assets-eu.researchsquare.com/files/rs-8520727/v1/2e7bd22c33c92d7bad2af8e2.docx"},{"id":101439897,"identity":"27880d2d-610e-44aa-b0d6-018e7bdf7450","added_by":"auto","created_at":"2026-01-29 16:50:54","extension":"docx","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":21611,"visible":true,"origin":"","legend":"","description":"","filename":"Table11.docx","url":"https://assets-eu.researchsquare.com/files/rs-8520727/v1/64020360f9497d23066ca18a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Learning, Accessing, and Choosing Cone Beam Computed Tomography: A Survey of Endodontists and Endodontic Specialty Students","fulltext":[{"header":"Introductıon","content":"\u003cp\u003eSuccessful endodontic treatment depends on a good clinical and radiographic examination. Radiographic examination in endodontics is one of the important steps in diagnosis and treatment planning. Panoramic and periapical radiographs are the most commonly used imaging modalities for diagnosis and treatment planning. Although intraoral radiographs are fundamental for diagnosis and treatment planning in endodontics, the resulting two-dimensional image offers a limited perspective. Conventional radiographs have limitations such as geometric distortions, anatomical region superpositions, inadequate diagnosis of small periapical lesions, lack of standardization in the radiographs taken and inadequate in cases where proper placement of the film in the mouth is not possible.\u003csup\u003e \u003c/sup\u003e(1-4)\u003c/p\u003e\n\u003cp\u003eIn recent years, three-dimensional imaging methods have been used in the field of health with the development of technology. Radiographic examination in endodontics is one of the important steps in diagnosis and treatment planning. Computed tomography (CT), which is now routinely used in medicine, has made it possible to overcome the inadequacies of conventional two-dimensional (2D) film technology.(5) However, the most important problems of CT systems are their high cost, the need for a large area and the high patient radiation dose. In the early 2000s, CT scanners with a smaller footprint and lower doses began to be produced for use in dentistry. These devices use a conical shaped x-ray with a two-dimensional sensor and are called \u0026quot;Cone Beam Computed Tomography\u0026quot; (CIBT)(6) Cone-beam computed tomography (CIBT) is a contemporary digital imaging technology that provides undistorted, three-dimensional information of teeth and surrounding tissues to aid the diagnostic procedure and clarify clinical decision-making. Cone-beam computed tomographic imaging provides a more detailed three-dimensional image that can influence treatment recommendations and can be used in all phases of treatment, including diagnosis, treatment planning, during the treatment phase and post-treatment evaluation and follow-up. It is superior to conventional radiography by reducing or avoiding superposition of surrounding tissues on each other. Structures that cannot be observed in conventional periapical radiography can be observed with sections taken in axial, coronal and sagittal planes between 0.125-2 mm. (7)\u003c/p\u003e\n\u003cp\u003ePrevious studies have primarily focused on assessing knowledge and attitudes toward CBCT among dental students or general dentists.(8,9,10) However, limited data are available regarding how endodontic specialists and endodontic specialty/doctoral students utilize CBCT in clinical decision-making, how they acquire CBCT-related knowledge, and how training influences their usage patterns. Understanding these factors is essential for identifying educational gaps, optimizing specialty training curricula, and promoting appropriate CBCT use aligned with current recommendations.\u003c/p\u003e\n\u003cp\u003eTherefore, the aim of this study was to evaluate the current status of CBCT use among endodontic specialists and endodontic specialty/doctoral students in Turkey. Specifically, the study aimed to assess participants\u0026rsquo; training in CBCT, access to the technology, tendencies to use CBCT in case-specific diagnosis and treatment planning, its role in identifying endodontic complications and evaluating treatment outcomes, and their overall perceptions regarding CBCT use. By exploring these aspects, the study seeks to provide insight into educational needs and usage behaviors that may inform future training strategies and guideline-based clinical practice.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResearch Problem and Sub-Problems\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe primary research question guiding this investigation is: \u0026quot;What are the views of endodontists and endodontic specialty/doctoral students on the accessibility and use of Cone Beam Computed Tomography (CBCT)?\u0026quot; To address this central question, the following sub-problems are formulated to examine whether significant differences exist in participants\u0026apos; views based on the following variables:\u003c/p\u003e\n\u003cp\u003ea) Gender\u003c/p\u003e\n\u003cp\u003eb) Academic title\u003c/p\u003e\n\u003cp\u003ec) Years of professional experience \u003c/p\u003e\n\u003cp\u003ed) Type of institution of employment\u003c/p\u003e\n\u003cp\u003ee) Current CBCT usage status\u003c/p\u003e\n\u003cp\u003ef) Receiving training in CBCT usage\u003c/p\u003e"},{"header":"Materials-Method","content":"\u003cp\u003eThis section includes the research model, population and sample, data collection tools and data analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResearch Model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study employs a survey model as it aims to describe an existing phenomenon in its current state. Survey research provides the quantitative analysis of trends, attitudes, or opinions within a defined population by examining data collected from a representative sample. The researcher can make generalizations about the population based on this sample (11).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWorking Group\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe working group consists of endodontists and endodontic specialty/doctoral students working in Turkey (n = 172). A power analysis was conducted using the \u003cem\u003eG*\u003cem\u003ePower 3.1 program to determine whether the total sample size of 172 participants was sufficient to achieve the required statistical power for the analyses.(12) The G\u003c/em\u003e\u003c/em\u003e\u003cem\u003e*\u003c/em\u003ePower power analysis indicated that, based on the parameters of medium effect size (f = 0.25), \u0026alpha; = 0.05, and 1\u0026ndash;\u0026beta; = 0.95, the required minimum sample size for the ANOVA design was 132. Since the sample size in the present study (172 participants) exceeds this value, it provides sufficient statistical power for the parametric analyses. Furthermore, the 172-participant sample size is also adequate for applying non-parametric tests such as the Mann\u0026ndash;Whitney U and Kruskal\u0026ndash;Wallis tests\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eA convenience sampling method was employed to select participants. This sampling technique involves gathering data from individuals who are readily accessible to the researcher (13). Table 1 provides demographic information regarding the participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePreparation of the Survey Form\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe survey instrument was developed based on a review of previous studies conducted on similar topics. The items in these studies were revised through expert consensus and new items were created to prepare a survey form comprising 39 items. The items were articulated in clear and accessible language.\u0026nbsp;Research data were collected through an anonymous online survey. Participants were informed about the purpose of the study, the researchers\u0026rsquo; contact information, and the voluntary nature of participation, and informed consent was obtained from all participants by their agreement to proceed with the survey.\u0026nbsp;The survey consists of two sections: Part 1 included 8 items on demographic information (gender, professional title, professional experience, institution and city) as well as questions related to CBCT usage, educational background and education tool. Part 2 comprised 31 items that evaluated participants\u0026rsquo; opinions on CBCT usage and cases they have used. After ethical approval was obtained, the finalized survey was administered online using Google Forms.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Committee Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with international ethical standards and the World Health Organization Helsinki Declaration at Akdeniz University Faculty of Dentistry, Department of Endodontics. This study was approved by the Clinical Research Ethics Committee of the Faculty of Medicine, Akdeniz University (418/2023).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eData Collection Process\u003c/p\u003e\n\u003cp\u003eThe finalized survey was distributed to endodontists and postgraduate (specialization/doctoral) students across Turkey via e-mail and through social media platforms using an online survey link. The survey remained open for 3 months. Stevens\u0026apos; (14) criterion of at least 5 to 20 participants per independent variable was taken into account in determining the sample size. Given the 31-item scale developed by the researchers, the minimum required sample size was calculated as 31 \u0026times; 5 = 155. However, considering the potential of incorrect data, the sample size was accepted as at least 170.\u003c/p\u003e\n\u003cp\u003eDevelopment of the Attitude Scale on the Accessibility and Use of Cone Beam Computed Tomography (CBCT-ASAU)\u003c/p\u003e\n\u003cp\u003eThe scale was developed following the steps proposed by Carpenter (15). The following section details the systematic process undertaken in the scale\u0026rsquo;s development.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eItem Pool Creation Stage\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn line with the intended purpose of the measurement tool, the target population was defined as endodontists practicing in Turkey and postgraduate students specializing in endodontics. Literature review on the subject was conducted, encompassing books, theses and articles. An initial pool of survey items was created in light of the information gained from these sources.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe stage of seeking expert feedback\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe purpose of seeking expert guidance is to ensure the content and face validity of the scale. Content validity evaluates how well the items represent the construct being measured (16) . Following this, face validity was evaluated to determine whether the survey items were clearly relevant to the research topic and accurately captured the intended construct (17).The 31-item draft scale was evaluated by two faculty members from the Department of Dentistry, three different faculty members from the same department, a faculty member specialized in measurement, and a language expert who had completed doctoral studies to assess linguistic appropriateness in Turkish. Based on their feedback, the scale was revised with targeted additions and deletions to improve clarity and alignment with the construct. A five-point Likert-type rating (5=completely agree, 1=completely disagree) was used in the scale.\u003c/p\u003e\n\u003cp\u003eSPSS 25.0 package program was used to assess the construct validity of the scale. Before applying factor analysis, the suitability of the data for this procedure was evaluated. Specifically, corrected total correlations of the items were examined and no items were identified to have values equal to or less than 0.25. Given that the instrument was newly developed and had no pre-existing validation, EFA was applied to the items to ensure the construct validity of the scale.\u003c/p\u003e\n\u003cp\u003eTo understand the suitability of the scale for factor analysis, the Kaiser-Meyer-Olkin (KMO) coefficient and the Bartlett test were calculated. In this regard, the KMO test measurement result should be .60 and above, and the Bartlett sphericity test result should be statistically significant (18) To clarify the factor structure of the scale, varimax (vertical) rotation was used during exploratory factor analysis (EFA). Item loadings of 0.50 or greater were considered acceptable for inclusion in a factor. The Principal Component Analysis extraction method was employed in EFA.\u003c/p\u003e\n\u003cp\u003eThe KMO value of 0.88 suggested that the sample size is sufficient (19); the data structure obtained from the Barlett sphericity test was also identified as suitable for EFA (\u0026chi;2 = 2305.012, p \u0026lt; .001). Items exhibiting high loadings on two factors simultaneously, with differences of 0.10 or less between loadings, were considered overlapping. In this context, 7 items (I6, I9, I10, I4, I25, I21, I28) were removed due to factor loadings below 0.50, cross-loading, or lack of semantic coherence within their respective factors. As a result, the final scale consisted of 24 items. The factor loadings and explained variance of items in the factors are displayed in Table 2.\u003c/p\u003e\n\u003cp\u003eCBCT-ASAU is a multidimensional scale. As in Table 2, the factor loadings of the items across the six factors of CBCT-ASAU are above 0.50. The exploratory factor analysis revealed that the scale explains approximately 65% of the total variance. Specifically, the variance explained by each factor is as follows: 17.83% for the use of CBCT in complicated cases (A1), 11.66% for the measurement of proximity to adjacent anatomy and use of CBCT in dental trauma (A2), 10.15% for the use of CBCT in diagnosis and treatment planning (A3), 9.67% for the use of CBCT for ideal imaging (A4), 8.41% for the ease of access to CBCT (A5), and 7.37% for the use of CBCT according to the size of the lesion (A6). The total reliability of the scale is \u0026alpha;total = .82. The reliability coefficients of the six subfactors are also satisfactory: \u0026alpha;\u003csub\u003eA1\u003c/sub\u003e = .90, \u0026alpha;\u003csub\u003eA2\u003c/sub\u003e = .82, \u0026alpha;\u003csub\u003eA3\u003c/sub\u003e = .80, \u0026alpha;\u003csub\u003eA4\u003c/sub\u003e = .76, \u0026alpha;\u003csub\u003eA5\u003c/sub\u003e = .71 and \u0026alpha;\u003csub\u003eA6\u003c/sub\u003e = .78, indicating strong internal consistency in accordance with established guidelines (20). Descriptive statistics suggested that the mean score for the factors A6 ( = 3.74) is higher than those of the other factors. Hence, it is most probable that the participants demonstrate a high tendency to use the CBCT tool according to the lesion size.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDescriptive Statistics, Reliability, and Inter-Construct Correlations of the CBCT Scale\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe \u003cstrong\u003ePearson correlation coefficient\u003c/strong\u003e was used to examine relationships between factors, with values interpreted as high (0.70\u0026ndash;1.00), moderate (0.30\u0026ndash;0.69), and low (\u0026lt;0.29) (21) Table 3 displays the descriptive statistics, reliability coefficients, and inter-variable correlations among the five factors of the CBCT scale. Inter-item correlations indicate significant positive relationships among most items within the same factor (p \u0026lt; 0.01). For instance, A1 correlated with A2 (r = 0.574), A3 (r = 0.515), A4 (r = 0.509), A5 (r = 0.336), and A6 (r = 0.547). Similarly, A2 correlated with A3 (r = 0.540), A4 (r = 0.403), and A6 (r = 0.451), while A3 correlated with A4 (r = 0.362), A5 (r = 0.229), and A6 (r = 0.319). Correlations for A4 and A5 were lower with some items (A4\u0026ndash;A5: r = 0.049; A5\u0026ndash;A6: r = 0.024), suggesting that these items, while part of the scale, capture slightly distinct aspects of the constructs. Overall, the pattern of correlations demonstrates that the items are sufficiently related to measure their respective factors while maintaining discriminant properties between factors, supporting both convergent and discriminant validity (22). These findings indicate that the scale is psychometrically robust and appropriate for further analyses, including factor-based or structural modeling approaches. The internal consistency, composite reliability, average variance extracted, and inter-itemcorrelations for the scale factors are presented in Table 3. Cronbach\u0026rsquo;s alpha values ranged from 0.71 to 0.90, indicating satisfactory internal consistency for all factors (23). Composite reliability (CR) values varied between 0.74 and 0.89, and average variance extracted (AVE) values ranged from 0.45 to 0.65, suggesting acceptable convergent validity across the factors (24).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiscriminant Validity\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiscriminant validity\u003c/strong\u003e was examined to assess whether the subdimensions of the scale are conceptually distinct from each other, using the Fornell\u0026ndash;Larcker criterion and the correlation matrix. As shown in Table 4, the \u0026radic;AVE values of all factors exceed their correlations with other constructs. According to Fornell and Larcker (24), if the \u0026radic;AVE of a construct is greater than its correlations with other constructs, discriminant validity is established. In addition, since all inter-construct correlations are below .574, the HTMT values are also expected to be below the recommended threshold (HTMT \u0026lt; .85;(25)). Therefore, discriminant validity among the subdimensions of the scale is satisfactory according to both the Fornell\u0026ndash;Larcker criterion and the correlation structure. Table 4 presents a comparison between the \u0026radic;AVE values and the highest correlations for each construct.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConfirmatory Factor Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAMOS 16 program was used for confirmatory factor analysis (CFA). The results yielded \u0026chi; 2 = 466.184, df=245, \u0026chi; 2 / df = 1.90, RMSEA = 0.07 (90% CI = 0.063, 0.083) values. The fit indices of the scale were examined, and it was observed that the single-factor model demonstrated acceptable fit: AGFI (Adjusted Goodness of Fit Index) = 0.76, GFI (Goodness of Fit Index) = 0.81, NFI (Normed Fit Index) = 0.79, CFI (Comparative Fit Index) = 0.89, SRMR (Standardized Root Mean Square Residual) = 0.09, TLI (Tucker-Lewis Index) = 0.87, and RMR (Root Mean Square Residual) = 0.13 (26). These values indicate that the model fit indices fall within the acceptable range. The fit indices of the scale were examined and that the fit statistics of the single-factor model were within the acceptable range (26). Examination of fit indices demonstrated that the six-factor structure showed a good fit (Figure 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSPSS 25 and AMOS 16 statistical package programs were used for data analysis. The statistical significance level was set at p \u0026lt;0.05. Data analysis proceeded in two stages. Initially, descriptive statistics were obtained for the key variables. Subsequently, EFA and CFA were conducted to assess the scale\u0026rsquo;s validity. The maximum likelihood estimation method was employed to estimate model parameters in CFA. Model fit was evaluated using multiple indices, including RMSEA (root means square error of approximation), RMR (root means square residual), GFI (goodness of fit index), CFI (comparative fit index), AGFI (adjusted goodness of fit index), NFI (normed fit index), \u0026chi;\u0026sup2;/df = CMIN/DF (chi-square / degrees of freedom) and p (level of significance). For the suitability of DFA and model fit indexes (values), the values presented in Table 5 below were considered (26)\u003c/p\u003e\n\u003cp\u003eTo test whether participants\u0026rsquo; responses to the scale items differed significantly according to independent variables, Levene\u0026rsquo;s Test of Homogeneity of Variances was first conducted to assess variance equality. For variances meeting the homogeneity assumption, t-test was applied for the \u0026apos;gender\u0026apos; variable, Mann-Whitney U test for the variables of education status and KIBT usage status, one-way variance (ANOVA) for the seniority variable, and Kruskal Wallis analysis for the variables of title, institution of employment and region. Based on ANOVA analysis results, the Least Significant Difference (LSD) post hoc test was used to identify the source of any significant differences.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eGender:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants\u0026rsquo; views on the CBCT-ASAU scale factors did not differ significantly by gender (p \u0026gt; 0.05). Female participants reported higher mean scores in factors A1, A2, and A6, while male participants reported higher mean scores in factors A3, A4, and A5. These findings indicate that gender does not significantly influence overall opinions on CBCT usage, although there may be differences in experience in certain areas. The results are depicted in Table 6.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCBCT training in CBCT status\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants who received training scored significantly higher in factors A2 (proximity to adjacent anatomy and trauma) and A6 (usage according to lesion size) (p \u0026lt; 0.05). Although no statistically significant differences were found in other factors, training generally had a positive impact on attitudes toward CBCT usage. Table 7 presents the results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProfessional Experience\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eProfessional seniority did not result in statistically significant differences in views on CBCT-ASAU factors (p \u0026gt; 0.05). However, more experienced participants reported higher mean scores in complex case usage (A1) and CBCT accessibility (A5). \u0026nbsp;(Table 8)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcademic Title\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants\u0026rsquo; academic titles did not significantly affect their opinions on CBCT usage (p \u0026gt; 0.05). Nevertheless, Assistant and Associate Professors showed a greater tendency to integrate CBCT into their clinical decision-making processes.(Table 9)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eType of Institution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo significant differences were found in CBCT-ASAU factors based on the type of institution (university hospital, private clinic, oral and dental health center) (p \u0026gt; 0.05). University hospital staff generally demonstrated higher usage tendencies, while private clinic staff reported lower scores. (Table 10)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCBCT usage status\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants who used CBCT scored significantly higher than non-users in factors A1, A2, A3, A5, and A6 (p \u0026lt; 0.05). These findings suggest that CBCT usage is particularly influential in areas such as managing complex cases, trauma assessment, diagnosis, lesion evaluation, and accessibility.(Table 11)\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study aimed to develop and preliminarily validate a scale designed to assess CBCT-related decision-making behaviors, educational exposure, and access patterns among endodontists and endodontic specialty/doctoral students in Turkey. Unlike diagnostic accuracy studies,(\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) the primary objective of this instrument is not to directly improve clinical outcomes but to evaluate how CBCT is perceived, selected, and utilized in routine and complex endodontic scenarios. In this context, the scale should be considered a behavioral and educational assessment tool rather than a clinical decision-support system.\u003c/p\u003e \u003cp\u003eAlthough CBCT-related attitude and knowledge scales have been reported previously, most existing instruments target undergraduate students, general dentists, or mixed professional groups. The present scale specifically focuses on endodontists and endodontic specialty/doctoral students and emphasizes case-based CBCT utilization, access, and training-related dimensions.(\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) Given the differences in CBCT accessibility, referral systems, and educational structures across countries, the development of a context-specific instrument addressing national practice patterns represents a necessary step toward meaningful assessment rather than mere duplication of existing tools.\u003c/p\u003e \u003cp\u003e The domains included in the scale were structured in accordance with current CBCT guidelines and commonly encountered endodontic decision points. International recommendations from the American Association of Endodontists (AAE) and the American Academy of Oral and Maxillofacial Radiology (AAOMR) emphasize selective CBCT use, particularly in complex cases involving trauma, resorptive defects, complex root anatomy, and proximity to critical anatomical structures.(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e) Accordingly, the scale dimensions were designed to reflect these clinically relevant scenarios, allowing indirect evaluation of guideline adherence and clinical reasoning patterns.\u003c/p\u003e \u003cp\u003eIn this study, the age criterion is not included in the demographic information. The age criterion was not included in the demographic information because it was thought that the duration of professional experience and seniority level, rather than age itself, could make a difference in the use of CBCT.(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eIn our study, expert training emerged as the primary source of knowledge for CBCT interpretation, followed by scientific articles and publications, professional courses, congresses, undergraduate education, and social media, respectively. In a separate survey conducted among undergraduate and postgraduate students in the Indian population, the majority of participants (74.19%) reported learning about CBCT during their undergraduate education, while 25.16% gained knowledge through seminars, 29.67% via the internet, and 5% through conferences. Most participants (69.68%) believed that their faculties provided sufficient CBCT training; however, 20% considered the training inadequate, primarily due to limited opportunities for practical, case-based learning. Furthermore, 74.84% of respondents indicated that CBCT education should be delivered during the clinical period, whereas only a small proportion felt it should be included in the pre-clinical curriculum. Overall, it was emphasized that undergraduate students receive relatively limited CBCT training, while postgraduate students acquire more comprehensive knowledge through seminars and professional courses.(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eNo significant associations were found between professional experience and CBCT utilization patterns. This finding aligns with previous study(\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e) reporting that increased availability of CBCT systems and widespread technological integration have reduced experience-based disparities in imaging preferences. Moreover, the lack of significant gender-based differences supports existing evidence that CBCT usage is driven more by clinical indication and training than by demographic factors.(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eStudies in the literature indicate clear differences between undergraduate and postgraduate education regarding both the level and timing of CBCT training. In a study conducted by Kamburoğlu et al.(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e), postgraduate students were reported to have a higher level of CBCT awareness compared with undergraduate students; postgraduate students primarily acquired their CBCT knowledge through seminars, whereas undergraduate students learned mainly through faculty-based courses. Nevertheless, the majority of participants stated that they intended to use CBCT technology in the future, and a substantial proportion of dentists considered the CBCT training received during undergraduate education to be insufficient. Similarly, another survey study revealed that undergraduate students demanded CBCT education to be delivered during the clinical period and in a practical manner, emphasizing the integration of theoretical knowledge with hands-on training. In the study by Parashar et al.(\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), it was reported that advanced CBCT training in dental schools in the United States, the United Kingdom, and Australia was predominantly provided within postgraduate programs, while remaining limited in undergraduate curricula. The authors emphasized that if general dental practitioners are to be authorized to use CBCT, CBCT education must be formally integrated into undergraduate dental training. Consistent with these findings, the results of our study showed that undergraduate education ranked low as a source of CBCT interpretation knowledge. This suggests that theoretical CBCT instruction alone at the undergraduate level is insufficient and should be supported by case-based and practical training to improve students\u0026rsquo; image interpretation skills.\u003c/p\u003e \u003cp\u003eThe findings demonstrate that CBCT training significantly influences case-based utilization, particularly in trauma-related cases, large lesions, and proximity assessment to adjacent anatomy. This highlights the role of structured education in shaping appropriate CBCT usage behaviors. Conversely, the absence of significant differences in some domains suggests that mere access to CBCT does not guarantee optimal utilization, reinforcing the importance of targeted educational interventions. In this respect, the scale may serve as a useful tool for identifying educational gaps and guiding curriculum development in undergraduate and specialty training programs.\u003c/p\u003e \u003cp\u003eThe majority of participants were affiliated with university hospitals, where CBCT availability is typically higher due to referral-based workflows and educational responsibilities. However, the absence of significant institutional differences suggests that technological infrastructure in private clinics and public oral health centers has improved over time. This reflects a broader shift toward more uniform access to advanced imaging modalities.\u003c/p\u003e \u003cp\u003eThis study has several limitations. The use of convenience sampling and a relatively limited sample size restricts generalizability and precludes definitive validation of the instrument. Additionally, the scale validation process represents a preliminary step, focusing primarily on factor structure rather than comprehensive psychometric evaluation. Future studies should aim to include larger and more diverse samples, incorporate test\u0026ndash;retest reliability, internal consistency, convergent and discriminant validity assessments, and examine the predictive value of the scale in relation to actual clinical behavior.\u003c/p\u003e \u003cp\u003eWithin the limitations of this study, the proposed scale provides a preliminary, context-specific instrument for assessing CBCT-related decision-making behaviors, educational exposure, and access among endodontists and endodontic specialty/doctoral students. Although the scale does not directly measure diagnostic or therapeutic outcomes, it offers potential value as an educational and quality-assessment tool by identifying usage patterns, training-related differences, and areas of inconsistency with established CBCT guidelines.\u003c/p\u003e \u003cp\u003e The instrument may be used to evaluate the effectiveness of CBCT education, monitor guideline adherence, and inform curriculum development in endodontic training programs. Further validation studies with larger samples and expanded psychometric analyses are required before widespread clinical or educational implementation. Nonetheless, the present findings contribute to understanding CBCT utilization behaviors in a national context and provide a foundation for future research aimed at optimizing CBCT use in endodontic practice.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eDisclosure:\u003c/h2\u003e\n\u003cp\u003eThe authors report no conflicts of interest\u003c/p\u003e\n\u003ch2\u003eFunding:\u003c/h2\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eE. K. conducted the data collection. \u0026Ccedil;. A. performed the data analysis. D.K.wrote the manuscript. All authors reviewed and edited the manuscript\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eAll data are available upon reasonable request to the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eForsberg J, Halse A. Radiographic simulation of a periapical lesion comparing the paralleling and the bisecting-angle techniques. Int Endod J. 1994;27(3):133-8.\u003c/li\u003e\n\u003cli\u003eT yndall DA, Clifton TL, Webber RL, Ludlow JB, Horton RA. TACT imaging of primary caries. Oral Surg Oral Med Oral Pathol Oral Radiol Endod. 1997;84(2):214-25.\u003c/li\u003e\n\u003cli\u003eSchwartz SF, Foster JK, Jr. Roentgenographic interpretation of experimentally produced bony lesions. I. Oral Surg Oral Med Oral Pathol. 1971;32(4):606-12.\u003c/li\u003e\n\u003cli\u003ePatel S. New dimensions in endodontic imaging: Part 2. Cone beam computed tomography. Int Endod J. 2009;42(6):463-75.\u003c/li\u003e\n\u003cli\u003eS\u0026Ccedil;. The use of computed tomography in oral and maxillofacial surgery. \u003cem\u003eAtat\u0026uuml;rk University Journal of Faculty of Dentistry\u003c/em\u003e. 2000.\u003c/li\u003e\n\u003cli\u003eK. O. Diş Hekimliğinde konik işınlı bilgisayarlı tomografinin (KIBT) Yeri ve \u0026Ouml;nemi. 7 Tepe Klinik, 3(3):6-17. (2012).\u003c/li\u003e\n\u003cli\u003eLofthag-Hansen S, Huumonen S, Grondahl K, Grondahl HG. Limited cone-beam CT and intraoral radiography for the diagnosis of periapical pathology. Oral Surg Oral Med Oral Pathol Oral Radiol Endod. 2007;103(1):114-9.\u003c/li\u003e\n\u003cli\u003eYalcinkaya SE, Berker YG, Peker S, Basturk FB. Knowledge and attitudes of Turkish endodontists towards digital radiology and cone beam computed tomography. Niger J Clin Pract. 2014;17(4):471-8.\u003c/li\u003e\n\u003cli\u003eKamburoglu K, Kursun S, Akarslan ZZ. Dental students\u0026apos; knowledge and attitudes towards cone beam computed tomography in Turkey. Dentomaxillofac Radiol. 2011;40(7):439-43.\u003c/li\u003e\n\u003cli\u003eFatima A MS. Knowledge and attitudes of dentists and dental students toward cone-beam computed tomography. \u003cem\u003eJournal of Research in Dental and Maxillofacial Sciences\u003c/em\u003e. 2020;5(4):26\u0026ndash;30\u003c/li\u003e\n\u003cli\u003eCreswell, J. W. (2012). \u003cem\u003eEducational Research: Planning, Conducting, and Evaluating Quantitative and Qualitative Research\u003c/em\u003e (4th ed.). Boston: Pearson. \u003c/li\u003e\n\u003cli\u003eKeskin B. Statistical power analysis: an application in the field of social sciences. Master\u0026rsquo;s thesis. Antalya: Akdeniz University, Institute of Social Sciences; 2012\u003c/li\u003e\n\u003cli\u003eRahi, S. (2017). Research design and methods: A systematic review of research paradigms, sampling issues and instruments development. \u003cem\u003eInternational Journal of Economics \u0026amp; Management Sciences\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e(2), 1-5. \u003c/li\u003e\n\u003cli\u003eStevens, J. (1996). Applied multivariate statistics for the social sciences (3rd ed.). Mahwah, NJ: Lawrence Erlbaum \u003c/li\u003e\n\u003cli\u003eSerena S. Carpenter (2018). \u003cem\u003eTen Steps in Scale Development and Reporting: A Guide for Researchers\u003c/em\u003e. \u003cem\u003eCommunication Methods and Measures\u003c/em\u003e, 12(1), 25\u0026ndash;44\u003c/li\u003e\n\u003cli\u003eCohen, R. J., \u0026amp; Swerdlik, M. E. (2018). Psychological testing and assessment: An introduction to tests and measurement (9th ed.). McGraw Hill. \u003c/li\u003e\n\u003cli\u003eKarako\u0026ccedil; AGDFY, D\u0026ouml;nmez L. Basic principles in scale development studies. \u003cem\u003eTıp Eğitimi D\u0026uuml;nyası\u003c/em\u003e. 2014;13(40):39\u0026ndash;49.\u003c/li\u003e\n\u003cli\u003eJeong, J. (2004). Analysis of the factors and the roles of hard in organizational learning styles ıdentified by key informants at selected corporations in the Republic of Korea, Phd Thesis, Texas A\u0026amp;M University, USA\u003c/li\u003e\n\u003cli\u003eTabachnick, B. G., \u0026amp; Fidell, L. S. (2007). \u003cem\u003eExperimental designs using ANOVA\u003c/em\u003e (Vol. 724). Belmont, CA: Thomson/Brooks/Cole.\u003c/li\u003e\n\u003cli\u003eHair, J. F., Anderson, R.E., Tatham, R.L., \u0026amp; Black, W.C. (1998). \u003cem\u003eMultivariate Data Analysis\u003c/em\u003e (5th ed.). New Jersey: Pearson Education. \u003c/li\u003e\n\u003cli\u003eB\u0026uuml;y\u0026uuml;k\u0026ouml;zt\u0026uuml;rk, Ş. (2022). Bilimsel Araştırma Y\u0026ouml;ntemleri. Carpenter, S. (2018). Ten steps in scale development and reporting: A guide for researchers. \u003cem\u003eCommunication methods and measures\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(1), 25\u003c/li\u003e\n\u003cli\u003eHair, J. F., Black, W. C., Babin, B. J., \u0026amp; Anderson, R. E. (2010). \u003cem\u003eMultivariate Data Analysis\u003c/em\u003e(7th,ed.).Prentice Hall.\u003c/li\u003e\n\u003cli\u003eNunnally, J. \u0026amp; Bernstein, I. (1994). \u003cem\u003ePsychometric theory\u003c/em\u003e. New York: McGraw Hill\u003c/li\u003e\n\u003cli\u003eFornell, C., \u0026amp; Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. \u003cem\u003eJournal of Marketing Research, 18\u003c/em\u003e(1), 39\u0026ndash;50. \u003c/li\u003e\n\u003cli\u003eHenseler, J., Ringle, C. M., \u0026amp; Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. \u003cem\u003eJournal of the Academy of Marketing Science, 43\u003c/em\u003e(1), 115\u0026ndash;135. \u003c/li\u003e\n\u003cli\u003eSchermelleh-Engel, K., Moosbrugger, H., \u0026amp; M\u0026uuml;ller, H. (2003). Evaluating the fit of, structural equation models: Tests of significance and descriptive goodness-of-fit measures. \u003cem\u003eMethods of \u003c/em\u003e\u003cem\u003ePsychological Research Online,\u003c/em\u003e 8(2), 23\u0026ndash;74\u003c/li\u003e\n\u003cli\u003eAAE and AAOMR Joint Position Statement. Use of cone beam computed tomography in endodontics 2015 update. Oral Surg Oral Med Oral Pathol Oral Radiol 2015;120:508\u0026ndash;12. 28. \u003c/li\u003e\n\u003cli\u003eMathew AI, Lee SC, Ha WN, Rossi-Fedele G, Dogramaci EJ. Cone-beam co uted tomography Predictors and characteristics of usage in Australia and New Zealand, a multifactorial analysis. Aust Endod J. 2023;49(2):247-55.mp\u003c/li\u003e\n\u003cli\u003eShah PH, Venkatesh R. Dental students\u0026apos; knowledge and attitude towards cone-beam computed tomography: An Indian scenario. Indian J Dent Res. 2016;27(6):581-5.\u003c/li\u003e\n\u003cli\u003eKrug R, Connert T, Beinicke A, Soliman S, Schubert A, Kiefner P, et al. When and how endodontic specialists use cone-beam computed tomography? Aust Endod J. 2019;45(3):365-72.\u003c/li\u003e\n\u003cli\u003eShah PH, Venkatesh R. Dental students\u0026apos; knowledge and attitude towards cone-beam computed t tomography: An Indian scenario. Indian J Dent Res. 2016;27(6):581-5.\u003c/li\u003e\n\u003cli\u003eParashar V, Whaites E, Monsour P, Chaudhry J, Geist JR. Cone beam computed tomography in dental education: a survey of US, UK, and Australian dental schools. J Dent Educ. 2012;76(11):1443-7.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 11 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Cone-Beam Computed Tomography (CBCT), Endodontics, CBCT Knowledge and Attitudes, Specialty Training","lastPublishedDoi":"10.21203/rs.3.rs-8520727/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8520727/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e This study aims to examine the views of endodontic specialists and postgraduate students in endodontics practicing in Turkey on the use of Cone Beam Computed Tomography (CBCT).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A total of 172 participants completed the CBCT-ASAU scale, which includes six factors: use in complicated cases (A1), measurement of proximity to adjacent anatomy and trauma assessment (A2), diagnostic and treatment planning (A3), ideal imaging (A4), access to CBCT (A5), and use according to lesion size (A6). Data were analyzed based on gender, CBCT training, professional experience, academic title, institution type, geographic region, and CBCT usage, using t-tests, Kruskal-Wallis, and Mann-Whitney U tests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Gender, academic title, institution type, and professional seniority did not show significant effects on CBCT attitudes (p \u0026gt; 0.05). CBCT training significantly influenced A2 and A6 scores (p \u0026lt; 0.05). CBCT users scored significantly higher than non-users in most factors (A1, A2, A3, A5, A6; p \u0026lt; 0.05). Overall, training, experience and actual CBCT use were associated with more positive attitudes and higher reported use.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e The findings indicate that CBCT education and practical experience play key roles in endodontists’ and trainees’ attitudes toward CBCT use. The CBCT-ASAU tool shows potential for assessing clinical adoption and guiding educational strategies in endodontics.\u003c/p\u003e","manuscriptTitle":"Learning, Accessing, and Choosing Cone Beam Computed Tomography: A Survey of Endodontists and Endodontic Specialty Students","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-29 16:50:49","doi":"10.21203/rs.3.rs-8520727/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7cb0657b-98b3-459d-82f6-658ea97ee34e","owner":[],"postedDate":"January 29th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":61908863,"name":"Health sciences/Diseases"},{"id":61908864,"name":"Health sciences/Health care"},{"id":61908865,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2026-01-30T12:55:37+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-29 16:50:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8520727","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8520727","identity":"rs-8520727","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}