Color vision alterations in dental students: a potential limiting factor in prosthodontic education

Color vision alterations in dental students: a potential limiting factor in prosthodontic education | 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 Research Article Color vision alterations in dental students: a potential limiting factor in prosthodontic education sergi torné-Durán This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8503312/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 Background Tooth color selection is a complex process that relies on the interaction between dental tissues and visual perception. Accurate shade matching is essential for aesthetic success in restorative dentistry; however, color vision deficiencies may compromise this process in clinical practice. Objective To evaluate the prevalence of color vision alterations among dental students and to assess their potential influence on prosthetic shade selection. Methods A descriptive cross-sectional study was conducted involving 80 fourth- and fifth-year dental students at the University of Barcelona. Color vision was assessed using the Ishihara test. Shade-matching ability was evaluated by matching two Chromascop shade guides and by selecting the shade of a dental crown. Statistical analysis was performed using chi-square and Fisher’s exact tests. Results Of the participants, 33.75% were male and 66.25% female. Color vision deficiency was detected in 2.5% of the sample. A significant association was observed between the presence of ophthalmological alterations and the number of errors in shade-matching tasks. Students with less clinical experience made fewer errors. No significant differences were found between gender and shade-matching performance. Conclusions Although the prevalence of color vision deficiency was low, visual alterations were associated with increased errors in shade selection. These findings highlight the importance of awareness, early detection, and educational support strategies to improve shade-matching accuracy during dental training. Color vision deficiency Color perception Shade selection Dental students Prosthodontics Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 INTRODUCTION The human visual system is an organized network of specialized cells responsible for encoding and interpreting visual stimuli. Tooth color perception depends on the interaction between polychromatic hard and soft dental tissues and incident light reaching the retina. However, this process may be influenced by optical phenomena such as metamerism. Shade selection is a critical step in prosthetic dentistry and remains one of the main challenges in achieving aesthetic dental restorations. This process relies on human color perception, which is trichromatic and influenced by the interaction between illumination conditions, the observer, and the optical characteristics of dental tissues.¹ , 2 . Successful tooth shade selection and reproduction are essential clinical steps in restorative dentistry and play a decisive role in aesthetic outcomes and patient satisfaction. The increasing importance of dental aesthetics has emphasized the need for accurate color matching, which remains a complex and often unpredictable process³–⁵. In recent decades, portable colorimeters, spectrophotometers, and digital imaging systems have been introduced to assist clinicians in shade selection⁶. There is substantial evidence that color vision deficiency represents a relevant problem in medical practice⁷. In dentistry, visual alterations may affect the ability to accurately select tooth color. For this reason, evaluating the influence of color vision alterations on shade selection is of clinical interest. Visual assessment using standardized tests and practical shade-matching tasks allows the identification of potential limitations related to color perception. Color is a visual perception generated in the brain through the interpretation of neural signals transmitted by retinal photoreceptors. When an object is illuminated, part of the electromagnetic spectrum is absorbed while the remaining wavelengths are reflected and interpreted as color⁸. The retina contains rods and cones, which convert light stimuli into neural signals and enable chromatic vision through cone cells sensitive to different wavelengths ¹ , ⁹. Because of the complexity of the visual system, multiple functional alterations may occur¹⁰. Visible light corresponds to wavelengths ranging from approximately 360 to 760 nm. Objects reflect specific wavelengths that determine perceived color, making vision dependent on adequate illumination ⁸ , ⁹. Color classification systems, such as the Munsell system, were developed to describe color in three dimensions¹¹. Although widely used in dentistry, limitations in perceptual uniformity led to the adoption of the CIELAB system by the Commission Internationale de l’Éclairage⁸ , ⁹. The color of natural teeth results from the interaction of light reflected from enamel and light scattered and reflected by dentin, which is the primary source of tooth color¹². Variations in enamel thickness, translucency, and surrounding environmental factors further influence perceived color. The harmony of color in dental restorations is therefore one of the main determinants of patient satisfaction¹²–¹ 5 . Color perception is influenced by multiple external and individual factors, including illumination, observer position, visual fatigue, and psychological variables⁵ , ¹² , ¹⁶. Differences related to age, gender, and experience have been reported, although findings remain inconsistent⁵ , ¹⁷–¹⁹. Overall, interindividual variability in color perception is widely acknowledged⁸ , ⁹ , ²⁰. In clinical practice, appropriate lighting conditions and standardized observation protocols are essential for accurate shade selection. Metamerism represents an additional challenge, as materials may appear identical under one light source but differ under another² , ⁷ , ⁹ , ²⁰. Both visual and instrumental methods are used for shade determination, with conventional color guides remaining the most common despite their inherent subjectivity and limitations ⁹ , ¹² , ² 0_22 . ( Fig. 1 ) Normal color vision depends on the coordinated function of cone photoreceptors. When one or more cone systems are absent or altered, color vision deficiency occurs¹. Color blindness affects up to 8% of men and 0.5% of women, and a significant proportion of affected individuals are unaware of their condition²³. Color vision deficiencies may be congenital or acquired and can vary in severity and clinical relevance. Numerous tests have been developed to identify color vision alterations, including pseudoisochromatic plates and color discrimination tests² 4 –² 6 . Among these, the Ishihara test is widely used due to its simplicity and effectiveness in detecting red–green deficiencies² , 27 . Despite the recognized importance of color perception in restorative dentistry, limited attention has been given to the impact of color vision alterations during undergraduate dental education. Most studies focus on experienced clinicians, whereas data on dental students remain scarce. Understanding whether visual alterations influence shade selection during early clinical training may help improve educational strategies and reduce avoidable aesthetic errors. Therefore, the aim of this study was to evaluate the prevalence of color vision alterations among dental students and to assess their potential influence on prosthetic shade selection. OBJECTIVES AND HYPOTHESIS OF THE STUDY: The primary objective of this study was to determine the prevalence of color vision alterations among undergraduate dental students. Secondary objectives were: To evaluate the presence of color vision alterations using a standardized visual test. To assess shade-matching performance using paired Chromascop shade guides. To evaluate the ability to select the correct shade of a dental crown. The study was conducted among fourth- and fifth-year dental students at the University of Barcelona. The null hypothesis was that the prevalence of color vision alterations among dental students is similar to that of the general population and that these alterations do not influence shade selection accuracy. The alternative hypothesis was that color vision alterations affect the ability to correctly select dental shades in undergraduate dental students with limited clinical experience. MATERIALS AND METHOD: Study design A descriptive cross-sectional study was conducted involving 80 fourth- and fifth-year dental students at the University of Barcelona. Inclusion and exclusion criteria Inclusion criteria Fourth- and fifth-year dental students at the University of Barcelona. Completion of the dental prosthetics course. Exclusion criteria Students not enrolled in the fourth or fifth year. Students who declined participation. Individuals with visual impairments preventing adequate vision. Dental prosthetic technicians. Students with professional experience as dental assistants or hygienists. Sample size calculation Sample size was calculated using G*Power 3.1 software. If 10% of participants would present color vision alterations and that 80% of these individuals would be unable to correctly order the color scale, the following parameters were applied: Inability to order the scale in participants without alterations: 30% α error probability: 0.05 β error probability: 0.02 Based on these parameters, a total sample size of 80 participants was determined. Materials Ishihara test Twenty-four pseudoisochromatic plates were used to detect color vision alterations. Each plate consists of a pattern of colored dots forming a number that may be perceived differently depending on the presence of a color vision deficiency. Chromascop shade guide (Ivoclar Vivadent) The guide consists of 20 ceramic shades arranged into five color families, each including four intensity levels from darkest to lightest. Two identical guides were used, one with the identification codes concealed. Dental crown A ceramic crown with shade 2B according to the Chromascop guide was used for the shade selection test. Procedure All measurements were performed by the same examiner. After signing informed consent, participants first completed the Ishihara test. Subsequently, they were asked to match 10 shades using two unordered Chromascop guides, one of which had the identification codes covered. Finally, participants were asked to select the shade of the ceramic crown using an unordered Chromascop guide with visible codes. The study workflow is summarized in Fig. 2 . All tests were performed under standardized dental chair lighting conditions. The time required to complete each test was recorded. Data collection All collected data were recorded in a Microsoft Excel spreadsheet. Variables included age, sex, presence of color vision alterations, presence of other visual impairments, time required to complete each test, and number of errors made. Statistical analysis A descriptive statistical analysis was performed. Student’s t-test, one-way ANOVA, Pearson’s chi-square test, and Fisher’s exact test were used when appropriate. Statistical analysis was conducted using SPSS software. Ethical approval Written informed consent to participate was obtained from all participants prior to their inclusion in the study. The study was approved by the Ethics Committee of the Dental Hospital of the University of Barcelona (CEIC HOUB, approval code 2017-17) and was conducted in accordance with the principles of the Declaration of Helsinki. RESULTS A descriptive and bivariate statistical analysis was performed using SPSS software (version 15.0; SPSS Inc., Chicago, USA). Student’s t -test for independent samples was used for continuous variables, and Pearson’s chi-square test or Fisher’s exact test was applied for categorical variables, as appropriate. A p- value < 0.05 was considered statistically significant. Sample characteristics Eighty dental students participated in the study. Of these, 33.75% were male and 66.25% were female. Forty percent were fourth-year students and 60% were fifth-year students. The prevalence of ophthalmological disorders among participants is presented in Table 1 and Figure 3. A statistically significant association was observed between the presence of ophthalmological disorders and a higher number of errors in the study tests (Table 2).\ Table 1. Distribution of ophthalmological alterations according to academic year and sex. Ophthalmologic alteration 4th year 5th year % Women Men No alteration 18.75% 21.25% 40% 20% 20% Myopia 13.75% 15% 28.75% 21.25% 7.5% Myopia and astigmatism 5% 15% 20% 17.5% 2.5% Hypermetropia 0% 3.75% 3.75% 3.75% 0% Hypermetropia and astigmatism 2.5% 2.5% 5% 2.5% 2.5% Other alterations 0% 2.5% 2.5% 1.25% 1.25% Table 2. Relationship between ophthalmological alterations and number of errors in the study tests. Variable t df p-value Ophthalmological alteration −1.72 48.65 0.023 Number of errors −1.07 39.61 0.011 Ishihara test Errors in the Ishihara test were observed in 28.75% of participants. In all but two cases, these errors were considered clinically non-relevant. The most frequent errors are shown in Table 3. Although no statistically significant differences were found, participants who failed more than two Ishihara plates tended to make a higher number of errors in both shade-matching tests. The percentage of failures for each Ishihara plate is presented in Table 4, with plates 17 and 22 being the most frequently failed (16.25% and 12.5%, respectively). Based on the Ishihara test results, 2.5% of participants were identified as having color blindness. Additionally, nine students (11.25%) failed specific plates suggestive of a possible red–green (protan) color vision deficiency. Table 3. Number of errors in the Ishihara test according to academic year and sex. NUMBER OF ERRORS MADE IN THE ISHIHARA TEST 4 year 5 year % women men 0 errors 30.25% 42.5% 72.75% 53.75% 19% 1 error 5% 8.75% 13.75% 7.5% 6.25% 2 errors 2.5% 5% 7.50% 5% 2.5% 3 errors 1.25% 2.5% 3.75% 1.25% 2.5% >5 errors 1.25% 1.25% 2.25% 0% 2.5% Table 4. Percentage of errors for each Ishihara test plate. Ishihara Test Plate % of Times Mistaken Ishihara Test Plate % of Times Mistaken Plate 1 0% Plate 13 12.5% Plate 2 4.16% Plate 14 8.33% Plate 3 8.33% Plate 15 4.16% Plate 4 8.33% Plate 16 0% Plate 5 8.33% Plate 17 12% Plate 6 8.33% Plate 18 20.83% Plate 7 12.5% Plate 19 0% Plate 8 8.33% Plate 20 20.83% Plate 9 8.33% Plate 21 4.16% Plate 10 8.33% Plate 22 41.66% Plate 11 8.33% Plate 23 4.16% Plate 12 16.66% Plate 24 4.16% Shade guide pairing test The mean time required to match the two Chromascop shade guides was 6.50 minutes. Participants who made a higher number of errors required more time to complete the task; however, this difference was not statistically significant (Table 5). The percentage of errors in shade guide pairing is presented in Table 6 and Figure 4. The colors that were most frequently mismatched are shown in Table 7 and Figure 5, while the most commonly confused tones are summarized in Table 8 and Figure 6. Table 5. Relationship between time required for shade selection and number of errors. Variable t df p-value Time −1.39 78 0.170 Number of errors −1.03 78 0.307 Table 6. Percentage of errors in Chromascop shade guide pairing according to academic year and sex. No. of Errors 4th Year 5th Year % Total Women Men 0 errors 0% 0% 0% 0% 0% 1 error 2.5% 0% 2.5% 2.5% 0% 2 errors 3.75% 3.75% 7.5% 6.25% 1.25% 3 errors 6.25% 3.75% 10% 6.25% 3.75% 4 errors 8.75% 13.75% 22.5% 13.75% 8.75% >5 errors 18.75% 38.75% 57.5% 37.5% 20% Table 7. Percentage of the most difficult-to-match shades in the Chromascop guide. Chromascop Shade Guide Code % Most Confusing 4B 75% 6B 72.5% 2A 66.25% 1C 63.75% 6C 63.75% 4A 51.25% 4C 43.75% 01 23.75% 2C 16.25% 4D 1.25% Table 8. Distribution of the most frequently confused tones during Chromascop guide pairing. Chromascop Shade Tone % Error A 37.5% B 58.75% C 40% D 1.25% Crown shade selection test The mean time required to select the shade of the crown was 1.50 minutes. Participants who selected the correct shade (25%) required a mean time of 1.30 minutes, whereas those who made errors (75%) required a mean time of 2.20 minutes. Although this trend suggests that longer completion times were associated with a higher probability of error, the differences were not statistically significant. The most frequently selected shades are presented in Table 9 and Figure 7. Table 9. Distribution of the most frequently selected incorrect shades during crown shade selection. Crown Color % Chosen 3A 31.25% 2B 25% 4B 1.25% 5B 6.25% 6B 1.25% 1C 2.50% 2C 1.25% 4C 6.25% 1D 6.25% 6D 5% 1E 6.25% 2E 7.50% Academic year, sex, and error distribution Among fourth-year students, 55% failed the crown shade selection test, and 55% made four or more errors in the shade guide pairing test. Forty percent failed both tests simultaneously (Figure 8). Among fifth-year students, 61.6% failed the crown shade selection test, 68.3% made four or more errors in the shade guide pairing test, and 56.6% failed both tests (Figure 9). A statistically significant difference between groups was observed (F(1,78) = 4.70, p = 0.033). (Table 10). No statistically significant differences were observed between academic year and crown shade selection errors (Table 11). Regarding sex, no statistically significant differences were observed between male and female participants in either the shade guide pairing test (Table 12) or the crown shade selection test (Table 13). Table 10. Relationship between academic year and number of errors in Chromascop guide pairing. Comparison F (df) p-value Between groups 4.70 (1, 78) 0.033 Table 11 . Relationship between academic year and errors in crown shade selection. Factor F (df) p-value Academic year 1.10 (1, 78) 0.298 T able 12. Relationship between sex and number of errors in Chromascop guide pairing. Comparison F (df) p-value Between groups 2.01 (1, 77) 0.161 Table 13. Relationship between sex and errors in crown shade selection. Comparison F (df) p-value Between groups 1.21 (1, 77) 0.274 Discussion Color perception plays a fundamental role in restorative dentistry, as achieving natural and aesthetically pleasing outcomes remains a primary clinical objective. Patient dissatisfaction related to tooth color has been widely reported, with previous studies indicating dissatisfaction rates ranging from 12% to over 30%, underscoring the clinical relevance of accurate shade selection¹³ , 28 . Human color perception is influenced by multiple factors, including lighting conditions, physiological variables, environmental context, and interobserver variability² , ⁵ , ⁸ , ⁹ , ¹² , ¹⁶, ¹⁷ , ¹⁹ , ²⁴. The difficulty of accurately measuring tooth color in the oral environment has also been emphasized, given the influence of tooth morphology, surface texture, translucency, and surrounding structures ⁷ , ¹² , ¹⁴ , ²⁰. In the present study, shade selection was performed outside the oral cavity, which may partially explain why some environmental factors described in previous investigations could not be directly confirmed. A high degree of interobserver variability was observed, in agreement with previous studies reporting limited agreement among clinicians during shade selection⁸ , ¹⁷ , ²⁴. Differences in lighting conditions across dental units may have contributed to this variability, as supported by earlier investigations highlighting the influence of illumination on color perception⁹ , ¹⁹. Although the combined use of visual and instrumental methods has been recommended to improve shade-matching accuracy¹⁵, the present study relied exclusively on the Chromascop shade guide, which remains one of the most commonly used systems in clinical practice⁹ , ¹² , ¹⁶. This approach reflects routine clinical conditions and allows for comparison with other studies using conventional shade guides. The Ishihara test was used to identify color vision alterations, acknowledging its limitation in grading severity² , ²⁶ , ²⁹. Previous reports indicate that individuals with normal trichromatic vision should not commit errors on the test⁶, whereas deuteranopes generally make fewer errors than protanopes due to genetic and photopigment-related differences³ , ⁴ , ⁸. The findings of the present study are consistent with this pattern, as 2.5% of participants were identified as protanopes, and 11.25% failed specific plates suggestive of red–green color vision deficiency. Despite being classified as normal trichromats, 28.75% of participants made up to three errors on the Ishihara test, which are considered poor readings. Although these results were not statistically significant, a tendency was observed whereby participants who failed more than two Ishihara plates also committed a higher number of errors in the shade-matching tasks. Regarding the shade guide pairing test, no previous studies using the Chromascop system were identified. Therefore, comparisons were made with studies using the Vita shade guide. Certain shade confusions reported in the literature differ considerably among studies, and no clear consensus exists regarding which hues are most frequently mismatched⁵ , ¹⁷ , ¹⁹. The present findings also revealed discrepancies in confused tones, reinforcing the notion that shade matching remains highly subjective and influenced by multiple variables. Time required for shade selection has been associated with visual fatigue and increased error rates⁹. In the present study, participants who required more time tended to make more errors in both the guide pairing and crown shade selection tests. Although these differences did not reach statistical significance, the observed trend supports previous recommendations advocating for rapid shade selection to minimize visual fatigue. The influence of sex, age, and experience on shade-matching ability remains controversial. Some studies suggest that younger or more experienced female clinicians perform better⁵ , ¹² , ¹³. whereas others report no significant differences² , ¹⁷ , ³⁰ , ³ 1 . In the present study, no statistically significant differences were found between male and female participants, supporting studies that report no sex-related influence on shade selection accuracy. About clinical experience, a statistically significant association was found between academic year and errors in the shade guide pairing test. Interestingly, fourth-year students committed fewer errors than fifth-year students, contradicting findings that associate greater experience with improved color matching⁹ , ³ 2 . This unexpected result may be explained by increased confidence, reduced attention to detail, or cumulative visual fatigue among more advanced students. The presence of ophthalmological alterations was significantly associated with a higher number of shade selection errors, in agreement with previous reports linking visual impairments to reduced color discrimination ability³² , ⁴ , ⁵ , ²³ , ²⁴ , ³ 3, ³ 4 . However, the influence of visual correction methods was not evaluated and should be addressed in future studies. Due to the low number of participants diagnosed with color vision deficiency, it was not possible to conclusively confirm the second hypothesis of the study. Nevertheless, the results suggest that shade selection errors are not limited exclusively to individuals with diagnosed color blindness. Therefore, assistance during shade selection may be beneficial not only for color-deficient individuals but also for dental students and clinicians with normal color vision. Conclusion No statistically significant association was observed between the number of errors on the Ishihara plates and the number of errors in the shade guide pairing test. No statistically significant relationship was found between errors on the Ishihara test and crown shade selection. The most frequently mismatched Chromascop shade families were B (58.75%), followed by C (40%), A (37.5%), and D (1.25%). A statistically significant association was identified between the presence of ophthalmological disorders and errors in crown shade selection. Although not statistically significant, a trend was observed between increased time required for shade selection and a higher number of errors. Statistically significant differences were found between academic year and the number of errors in the shade guide pairing test, with fourth-year students making fewer errors. No significant association was observed between sex and shade selection errors. Further studies with larger sample sizes are recommended to better clarify the influence of visual factors on dental shade selection. Abbreviations Not applicable. Declarations Ethics approval and consent to participate The study was approved by the Ethics Committee of the Dental Hospital of the University of Barcelona (CEIC HOUB, approval code 2017-17) and was conducted in accordance with the principles of the Declaration of Helsinki. Written informed consent to participate was obtained from all participants prior to their inclusion in the study. Consent for publication Not applicable. Availability of data and materials The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request. Competing Interests The authors declare that they have no competing interests. Funding This research received no external funding. Authors’ contributions S.T.-D. conceived and designed the study, collected the data, performed the statistical analysis, and drafted the manuscript. The author read and approved the final version of the manuscript. Acknowledgements The author would like to thank the dental students who voluntarily participated in this study. References Rabin JC, Kryder AC, Lam D. Diagnosis of normal and abnormal color vision with cone-specific VEPs. Transl Vis Sci Technol. 2016;5(1):8. Simunovic MP. Acquired color vision deficiency. 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Advice for medical students and practitioners with color vision deficiency: a website resource. Clin Exp Optom. 2010;93:39–41. Klemetti E, Matela AM, Haag P, Kononen M. Shade selection performed by novice dental professionals and colorimeter. J Oral Rehabil. 2006;33:31–5. Additional Declarations No competing interests reported. Supplementary Files Dadescolor.zip Estadistica1.zip Estadistica2.zip Estadistica.zip 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. 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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-8503312","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":582005150,"identity":"2dc827e9-03bc-4395-8408-018ca180ed6d","order_by":0,"name":"sergi 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10:19:19","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":289715,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic representation of metamerism observed by the same observer under different illumination conditions.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8503312/v1/2fb06769d3689c00ee266b91.png"},{"id":101437039,"identity":"b8cdd48f-4154-4b5b-88b2-3cc7f61303d3","added_by":"auto","created_at":"2026-01-29 16:27:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":75350,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of the study procedure, including informed consent, Ishihara test, Chromascop shade guide pairing, and crown shade selection.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8503312/v1/bc65fa5972b0efaea39420d7.png"},{"id":101437044,"identity":"a8f67acc-2aed-452e-88a1-59fd72262cb3","added_by":"auto","created_at":"2026-01-29 16:27:09","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":816118,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of participants according to the presence of ophthalmological alterations.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8503312/v1/f0ace16d85a4dfbd0c59af3a.png"},{"id":101437046,"identity":"db39c61b-d358-429a-b617-3f8eaa9fa29f","added_by":"auto","created_at":"2026-01-29 16:27:09","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":31861,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of total errors in the shade guide pairing task.\u003c/p\u003e","description":"","filename":"4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8503312/v1/d202bc71d439f6038a9a457a.jpeg"},{"id":101437041,"identity":"f8cc7547-f3a6-46ca-9166-058f7b016a6e","added_by":"auto","created_at":"2026-01-29 16:27:09","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":25091,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of the most frequently mismatched shades during the shade guide pairing task.\u003c/p\u003e","description":"","filename":"5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8503312/v1/879ce2fc258cd359b1cccc4e.jpeg"},{"id":101437045,"identity":"5d66bb32-f017-4d8b-a64b-235e4cb7ef83","added_by":"auto","created_at":"2026-01-29 16:27:09","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":23345,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of the most frequently confused shades during the crown \u0026nbsp;shade selection task\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8503312/v1/8f25a64556f07fef6d2a1f66.jpeg"},{"id":101751900,"identity":"48af9bcb-776e-48f8-bfb6-4c2e1d724b1a","added_by":"auto","created_at":"2026-02-03 10:24:20","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":37640,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of selected shades during the crown shade selection task.\u003c/p\u003e","description":"","filename":"7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8503312/v1/3cde56253e6c0a59de6a2bf3.jpeg"},{"id":101751898,"identity":"c5d1e286-aeb2-4f78-83f1-c7a28846b9f3","added_by":"auto","created_at":"2026-02-03 10:24:20","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":52408,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of fourth-year dental students according to errors in the shade guide pairing test, crown shade selection, and combined errors in both tests.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-8503312/v1/e105f2c80067704e736f3541.png"},{"id":101437042,"identity":"3f147e62-5646-4c93-88bc-4cb966e6c7d0","added_by":"auto","created_at":"2026-01-29 16:27:09","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":51596,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of fifth-year dental students according to errors in the shade guide pairing test, crown shade selection, and combined errors in both tests.\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-8503312/v1/07f06343e7919cb89dbb16f1.png"},{"id":103718805,"identity":"6b636fa3-684e-4f33-a1ed-45e7db687315","added_by":"auto","created_at":"2026-03-02 06:41:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2261737,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8503312/v1/6c3363f6-fabb-46cf-b956-1ad8874b416a.pdf"},{"id":101751237,"identity":"a8807fc1-85c9-4e2c-9c9c-7c12a88623de","added_by":"auto","created_at":"2026-02-03 10:18:33","extension":"zip","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":39140,"visible":true,"origin":"","legend":"","description":"","filename":"Dadescolor.zip","url":"https://assets-eu.researchsquare.com/files/rs-8503312/v1/3d041f065b96ad2580d643ed.zip"},{"id":101751387,"identity":"dd7f951c-dfc0-4919-b1a9-4cac77bb9f8a","added_by":"auto","created_at":"2026-02-03 10:19:55","extension":"zip","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":75717,"visible":true,"origin":"","legend":"","description":"","filename":"Estadistica1.zip","url":"https://assets-eu.researchsquare.com/files/rs-8503312/v1/bb343e5b5840833ef0a4cbd0.zip"},{"id":101437038,"identity":"8e8a9754-ae31-42a5-a504-8eea1b06fb99","added_by":"auto","created_at":"2026-01-29 16:27:09","extension":"zip","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":38827,"visible":true,"origin":"","legend":"","description":"","filename":"Estadistica2.zip","url":"https://assets-eu.researchsquare.com/files/rs-8503312/v1/b4470556f24d5015c723365c.zip"},{"id":101437035,"identity":"aa691408-595e-40b3-b18d-98d2224d3f23","added_by":"auto","created_at":"2026-01-29 16:27:09","extension":"zip","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":44913,"visible":true,"origin":"","legend":"","description":"","filename":"Estadistica.zip","url":"https://assets-eu.researchsquare.com/files/rs-8503312/v1/170e6ef64671f57471eb6047.zip"}],"financialInterests":"No competing interests reported.","formattedTitle":"Color vision alterations in dental students: a potential limiting factor in prosthodontic education","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThe human visual system is an organized network of specialized cells responsible for encoding and interpreting visual stimuli. Tooth color perception depends on the interaction between polychromatic hard and soft dental tissues and incident light reaching the retina. However, this process may be influenced by optical phenomena such as metamerism.\u003c/p\u003e \u003cp\u003eShade selection is a critical step in prosthetic dentistry and remains one of the main challenges in achieving aesthetic dental restorations. This process relies on human color perception, which is trichromatic and influenced by the interaction between illumination conditions, the observer, and the optical characteristics of dental tissues.\u0026sup1;\u003csup\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSuccessful tooth shade selection and reproduction are essential clinical steps in restorative dentistry and play a decisive role in aesthetic outcomes and patient satisfaction. The increasing importance of dental aesthetics has emphasized the need for accurate color matching, which remains a complex and often unpredictable process\u0026sup3;\u0026ndash;⁵. In recent decades, portable colorimeters, spectrophotometers, and digital imaging systems have been introduced to assist clinicians in shade selection⁶.\u003c/p\u003e \u003cp\u003eThere is substantial evidence that color vision deficiency represents a relevant problem in medical practice⁷. In dentistry, visual alterations may affect the ability to accurately select tooth color. For this reason, evaluating the influence of color vision alterations on shade selection is of clinical interest. Visual assessment using standardized tests and practical shade-matching tasks allows the identification of potential limitations related to color perception.\u003c/p\u003e \u003cp\u003eColor is a visual perception generated in the brain through the interpretation of neural signals transmitted by retinal photoreceptors. When an object is illuminated, part of the electromagnetic spectrum is absorbed while the remaining wavelengths are reflected and interpreted as color⁸. The retina contains rods and cones, which convert light stimuli into neural signals and enable chromatic vision through cone cells sensitive to different wavelengths \u0026sup1;\u003csup\u003e,\u003c/sup\u003e ⁹. Because of the complexity of the visual system, multiple functional alterations may occur\u0026sup1;⁰.\u003c/p\u003e \u003cp\u003eVisible light corresponds to wavelengths ranging from approximately 360 to 760 nm. Objects reflect specific wavelengths that determine perceived color, making vision dependent on adequate illumination ⁸\u003csup\u003e,\u003c/sup\u003e ⁹. Color classification systems, such as the Munsell system, were developed to describe color in three dimensions\u0026sup1;\u0026sup1;. Although widely used in dentistry, limitations in perceptual uniformity led to the adoption of the CIELAB system by the Commission Internationale de l\u0026rsquo;\u0026Eacute;clairage⁸\u003csup\u003e,\u003c/sup\u003e ⁹.\u003c/p\u003e \u003cp\u003eThe color of natural teeth results from the interaction of light reflected from enamel and light scattered and reflected by dentin, which is the primary source of tooth color\u0026sup1;\u0026sup2;. Variations in enamel thickness, translucency, and surrounding environmental factors further influence perceived color. The harmony of color in dental restorations is therefore one of the main determinants of patient satisfaction\u0026sup1;\u0026sup2;\u0026ndash;\u0026sup1;\u003csup\u003e5\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eColor perception is influenced by multiple external and individual factors, including illumination, observer position, visual fatigue, and psychological variables⁵\u003csup\u003e,\u003c/sup\u003e \u0026sup1;\u0026sup2;\u003csup\u003e,\u003c/sup\u003e \u0026sup1;⁶. Differences related to age, gender, and experience have been reported, although findings remain inconsistent⁵\u003csup\u003e,\u003c/sup\u003e \u0026sup1;⁷\u0026ndash;\u0026sup1;⁹. Overall, interindividual variability in color perception is widely acknowledged⁸\u003csup\u003e,\u003c/sup\u003e ⁹\u003csup\u003e,\u003c/sup\u003e \u0026sup2;⁰.\u003c/p\u003e \u003cp\u003eIn clinical practice, appropriate lighting conditions and standardized observation protocols are essential for accurate shade selection. Metamerism represents an additional challenge, as materials may appear identical under one light source but differ under another\u0026sup2;\u003csup\u003e,\u003c/sup\u003e ⁷\u003csup\u003e,\u003c/sup\u003e ⁹\u003csup\u003e,\u003c/sup\u003e \u0026sup2;⁰. Both visual and instrumental methods are used for shade determination, with conventional color guides remaining the most common despite their inherent subjectivity and limitations ⁹\u003csup\u003e,\u003c/sup\u003e \u0026sup1;\u0026sup2;\u003csup\u003e,\u003c/sup\u003e \u0026sup2;\u003csup\u003e0_22\u003c/sup\u003e. ( Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eNormal color vision depends on the coordinated function of cone photoreceptors. When one or more cone systems are absent or altered, color vision deficiency occurs\u0026sup1;. Color blindness affects up to 8% of men and 0.5% of women, and a significant proportion of affected individuals are unaware of their condition\u0026sup2;\u0026sup3;. Color vision deficiencies may be congenital or acquired and can vary in severity and clinical relevance.\u003c/p\u003e \u003cp\u003eNumerous tests have been developed to identify color vision alterations, including pseudoisochromatic plates and color discrimination tests\u0026sup2;\u003csup\u003e4\u003c/sup\u003e\u0026ndash;\u0026sup2;\u003csup\u003e6\u003c/sup\u003e. Among these, the Ishihara test is widely used due to its simplicity and effectiveness in detecting red\u0026ndash;green deficiencies\u0026sup2;\u003csup\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eDespite the recognized importance of color perception in restorative dentistry, limited attention has been given to the impact of color vision alterations during undergraduate dental education. Most studies focus on experienced clinicians, whereas data on dental students remain scarce. Understanding whether visual alterations influence shade selection during early clinical training may help improve educational strategies and reduce avoidable aesthetic errors. Therefore, the aim of this study was to evaluate the prevalence of color vision alterations among dental students and to assess their potential influence on prosthetic shade selection.\u003c/p\u003e"},{"header":"OBJECTIVES AND HYPOTHESIS OF THE STUDY:","content":"\u003cp\u003eThe primary objective of this study was to determine the prevalence of color vision alterations among undergraduate dental students.\u003c/p\u003e \u003cp\u003eSecondary objectives were:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eTo evaluate the presence of color vision alterations using a standardized visual test.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTo assess shade-matching performance using paired Chromascop shade guides.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTo evaluate the ability to select the correct shade of a dental crown.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThe study was conducted among fourth- and fifth-year dental students at the University of Barcelona.\u003c/p\u003e \u003cp\u003eThe null hypothesis was that the prevalence of color vision alterations among dental students is similar to that of the general population and that these alterations do not influence shade selection accuracy.\u003c/p\u003e \u003cp\u003eThe alternative hypothesis was that color vision alterations affect the ability to correctly select dental shades in undergraduate dental students with limited clinical experience.\u003c/p\u003e"},{"header":"MATERIALS AND METHOD:","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eA descriptive cross-sectional study was conducted involving 80 fourth- and fifth-year dental students at the University of Barcelona.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eInclusion and exclusion criteria\u003c/h3\u003e\n\u003cp\u003eInclusion criteria\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eFourth- and fifth-year dental students at the University of Barcelona.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eCompletion of the dental prosthetics course.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eExclusion criteria\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eStudents not enrolled in the fourth or fifth year.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eStudents who declined participation.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eIndividuals with visual impairments preventing adequate vision.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eDental prosthetic technicians.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eStudents with professional experience as dental assistants or hygienists.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eSample size calculation\u003c/p\u003e \u003cp\u003eSample size was calculated using G*Power 3.1 software. If 10% of participants would present color vision alterations and that 80% of these individuals would be unable to correctly order the color scale, the following parameters were applied:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eInability to order the scale in participants without alterations: 30%\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eα error probability: 0.05\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eβ error probability: 0.02\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eBased on these parameters, a total sample size of 80 participants was determined.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMaterials\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eIshihara test\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eTwenty-four pseudoisochromatic plates were used to detect color vision alterations. Each plate consists of a pattern of colored dots forming a number that may be perceived differently depending on the presence of a color vision deficiency.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eChromascop shade guide (Ivoclar Vivadent)\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe guide consists of 20 ceramic shades arranged into five color families, each including four intensity levels from darkest to lightest. Two identical guides were used, one with the identification codes concealed.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eDental crown\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eA ceramic crown with shade 2B according to the Chromascop guide was used for the shade selection test.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e\n\u003ch3\u003eProcedure\u003c/h3\u003e\n\u003cp\u003eAll measurements were performed by the same examiner. After signing informed consent, participants first completed the Ishihara test. Subsequently, they were asked to match 10 shades using two unordered Chromascop guides, one of which had the identification codes covered. Finally, participants were asked to select the shade of the ceramic crown using an unordered Chromascop guide with visible codes. The study workflow is summarized in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eAll tests were performed under standardized dental chair lighting conditions. The time required to complete each test was recorded.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eAll collected data were recorded in a Microsoft Excel spreadsheet. Variables included age, sex, presence of color vision alterations, presence of other visual impairments, time required to complete each test, and number of errors made.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eA descriptive statistical analysis was performed. Student\u0026rsquo;s t-test, one-way ANOVA, Pearson\u0026rsquo;s chi-square test, and Fisher\u0026rsquo;s exact test were used when appropriate. Statistical analysis was conducted using SPSS software.\u003c/p\u003e \u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWritten informed consent to participate was obtained from all participants prior to their inclusion in the study.\u003c/p\u003e\u003cp\u003eThe study was approved by the Ethics Committee of the Dental Hospital of the University of Barcelona (CEIC HOUB, approval code 2017-17) and was conducted in accordance with the principles of the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eA descriptive and bivariate statistical analysis was performed using SPSS software (version 15.0; SPSS Inc., Chicago, USA). Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-test for independent samples was used for continuous variables, and Pearson\u0026rsquo;s chi-square test or Fisher\u0026rsquo;s exact test was applied for categorical variables, as appropriate. A \u003cem\u003ep-\u003c/em\u003evalue \u0026lt; 0.05 was considered statistically significant.\u003c/p\u003e\n\u003ch3\u003eSample characteristics\u003c/h3\u003e\n\u003cp\u003eEighty dental students participated in the study. Of these, 33.75% were male and 66.25% were female. Forty percent were fourth-year students and 60% were fifth-year students. The prevalence of ophthalmological disorders among participants is presented in Table 1 and Figure 3. A statistically significant association was observed between the presence of ophthalmological disorders and a higher number of errors in the study tests (Table 2).\\\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Distribution of ophthalmological alterations according to academic year and sex.\u003c/p\u003e\n\u003ctable\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eOphthalmologic alteration\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e4th year\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e5th year\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eWomen\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMen\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNo alteration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18.75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e40%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMyopia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13.75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e28.75%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMyopia and astigmatism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e20%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHypermetropia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e3.75%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHypermetropia and astigmatism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e5%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOther alterations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e2.5%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Relationship between ophthalmological alterations and number of errors in the study tests.\u003c/p\u003e\n\u003ctable width=\"573\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003et\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003edf\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOphthalmological alteration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;1.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e48.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNumber of errors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eIshihara test\u003c/h3\u003e\n\u003cp\u003eErrors in the Ishihara test were observed in 28.75% of participants. In all but two cases, these errors were considered clinically non-relevant. The most frequent errors are shown in Table 3. Although no statistically significant differences were found, participants who failed more than two Ishihara plates tended to make a higher number of errors in both shade-matching tests. The percentage of failures for each Ishihara plate is presented in Table 4, with plates 17 and 22 being the most frequently failed (16.25% and 12.5%, respectively).\u003c/p\u003e\n\u003cp\u003eBased on the Ishihara test results, 2.5% of participants were identified as having color blindness. Additionally, nine students (11.25%) failed specific plates suggestive of a possible red\u0026ndash;green (protan) color vision deficiency.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Number of errors in the Ishihara test according to academic year and sex.\u0026nbsp;\u003c/p\u003e\n\u003ctable width=\"622\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNUMBER OF ERRORS MADE IN THE ISHIHARA TEST\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4 year\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5 year\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ewomen\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003emen\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 196px;\"\u003e\n \u003cp\u003e0 errors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e30.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e42.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e72.75%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e53.75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e19%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 196px;\"\u003e\n \u003cp\u003e1 error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e8.75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e13.75%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e7.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e6.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 196px;\"\u003e\n \u003cp\u003e2 errors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e2.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7.50%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e2.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 196px;\"\u003e\n \u003cp\u003e3 errors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e2.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.75%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e2.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 196px;\"\u003e\n \u003cp\u003e\u0026gt;5 errors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.25%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e2.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u003c/strong\u003e Percentage of errors for each Ishihara test plate.\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003eIshihara Test Plate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e% of Times Mistaken\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003eIshihara Test Plate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e% of Times Mistaken\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003ePlate 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003ePlate 13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e12.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003ePlate 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e4.16%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003ePlate 14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e8.33%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003ePlate 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e8.33%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003ePlate 15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e4.16%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003ePlate 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e8.33%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003ePlate 16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003ePlate 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e8.33%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003ePlate 17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e12%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003ePlate 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e8.33%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003ePlate 18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e20.83%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003ePlate 7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e12.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003ePlate 19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003ePlate 8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e8.33%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003ePlate 20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e20.83%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003ePlate 9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e8.33%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003ePlate 21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e4.16%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003ePlate 10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e8.33%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003ePlate 22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e41.66%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003ePlate 11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e8.33%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003ePlate 23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e4.16%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003ePlate 12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e16.66%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003ePlate 24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e4.16%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eShade guide pairing test\u003c/h3\u003e\n\u003cp\u003eThe mean time required to match the two Chromascop shade guides was 6.50 minutes. Participants who made a higher number of errors required more time to complete the task; however, this difference was not statistically significant (Table 5). The percentage of errors in shade guide pairing is presented in Table 6 and Figure 4. The colors that were most frequently mismatched are shown in Table 7 and Figure 5, while the most commonly confused tones are summarized in Table 8 and Figure 6.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5.\u0026nbsp;\u003c/strong\u003eRelationship between time required for shade selection and number of errors.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable width=\"506\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003et\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003edf\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.170\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNumber of errors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.307\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6.\u003c/strong\u003e Percentage of errors in Chromascop shade guide pairing according to academic year and sex.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eNo. of Errors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e4th Year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e5th Year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e% Total\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eMen\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0 errors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e1 error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e2.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e2.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e2.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e2 errors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e3.75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e3.75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e7.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e6.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e1.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e3 errors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e6.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e3.75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e6.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e3.75%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e4 errors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e8.75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e13.75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e22.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e13.75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e8.75%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026gt;5 errors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e18.75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e38.75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e57.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e37.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e20%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 7.\u003c/strong\u003e Percentage of the most difficult-to-match shades in the Chromascop guide.\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003eChromascop Shade Guide Code\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e% Most Confusing\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e4B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e75%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e6B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e72.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e2A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e66.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e1C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e63.75%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e6C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e63.75%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e4A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e51.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e4C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e43.75%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e23.75%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e2C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e16.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e4D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e1.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 8.\u003c/strong\u003e Distribution of the most frequently confused tones during Chromascop guide pairing.\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003eChromascop Shade Tone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e% Error\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e37.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e58.75%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e40%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003eD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e1.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eCrown shade selection test\u003c/h3\u003e\n\u003cp\u003eThe mean time required to select the shade of the crown was 1.50 minutes. Participants who selected the correct shade (25%) required a mean time of 1.30 minutes, whereas those who made errors (75%) required a mean time of 2.20 minutes. Although this trend suggests that longer completion times were associated with a higher probability of error, the differences were not statistically significant. The most frequently selected shades are presented in Table 9 and Figure 7.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 9.\u003c/strong\u003e Distribution of the most frequently selected incorrect shades during crown shade selection.\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003eCrown Color\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e% Chosen\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e3A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e31.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e2B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e25%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e4B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e1.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e5B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e6.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e6B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e1.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e1C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e2.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e2C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e1.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e4C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e6.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e1D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e6.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e6D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e1E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e6.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e2E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 288px;\"\u003e\n \u003cp\u003e7.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eAcademic year, sex, and error distribution\u003c/h3\u003e\n\u003cp\u003eAmong fourth-year students, 55% failed the crown shade selection test, and 55% made four or more errors in the shade guide pairing test. Forty percent failed both tests simultaneously (Figure 8). Among fifth-year students, 61.6% failed the crown shade selection test, 68.3% made four or more errors in the shade guide pairing test, and 56.6% failed both tests (Figure 9).\u003c/p\u003e\n\u003cp\u003eA statistically significant difference between groups was observed (F(1,78) = 4.70, p = 0.033). (Table 10). No statistically significant differences were observed between academic year and crown shade selection errors (Table 11).\u003c/p\u003e\n\u003cp\u003eRegarding sex, no statistically significant differences were observed between male and female participants in either the shade guide pairing test (Table 12) or the crown shade selection test (Table 13).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 10.\u003c/strong\u003e Relationship between academic year and number of errors in Chromascop guide pairing.\u0026nbsp;\u003c/p\u003e\n\u003ctable width=\"430\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eComparison\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eF (df)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eBetween groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.70 (1, 78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 11\u003c/strong\u003e. Relationship between academic year and errors in crown shade selection.\u003c/p\u003e\n\u003ctable width=\"441\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eFactor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eF (df)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAcademic year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.10 (1, 78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.298\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eT\u003cstrong\u003eable 12.\u003c/strong\u003e Relationship between sex and number of errors in Chromascop guide pairing.\u003c/p\u003e\n\u003ctable width=\"448\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eComparison\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eF (df)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eBetween groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.01 (1, 77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.161\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 13.\u003c/strong\u003e Relationship between sex and errors in crown shade selection.\u0026nbsp;\u003c/p\u003e\n\u003ctable width=\"459\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eComparison\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eF (df)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eBetween groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.21 (1, 77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.274\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eColor perception plays a fundamental role in restorative dentistry, as achieving natural and aesthetically pleasing outcomes remains a primary clinical objective. Patient dissatisfaction related to tooth color has been widely reported, with previous studies indicating dissatisfaction rates ranging from 12% to over 30%, underscoring the clinical relevance of accurate shade selection\u0026sup1;\u0026sup3;\u003csup\u003e, 28\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eHuman color perception is influenced by multiple factors, including lighting conditions, physiological variables, environmental context, and interobserver variability\u0026sup2;\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e⁵\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e⁸\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e⁹\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u0026sup1;\u0026sup2;\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u0026sup1;⁶, \u0026sup1;⁷\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u0026sup1;⁹\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u0026sup2;⁴. The difficulty of accurately measuring tooth color in the oral environment has also been emphasized, given the influence of tooth morphology, surface texture, translucency, and surrounding structures ⁷\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u0026sup1;\u0026sup2;\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u0026sup1;⁴\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u0026sup2;⁰. In the present study, shade selection was performed outside the oral cavity, which may partially explain why some environmental factors described in previous investigations could not be directly confirmed.\u003c/p\u003e\n\u003cp\u003eA high degree of interobserver variability was observed, in agreement with previous studies reporting limited agreement among clinicians during shade selection⁸\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u0026sup1;⁷\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u0026sup2;⁴. Differences in lighting conditions across dental units may have contributed to this variability, as supported by earlier investigations highlighting the influence of illumination on color perception⁹\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u0026sup1;⁹.\u003c/p\u003e\n\u003cp\u003eAlthough the combined use of visual and instrumental methods has been recommended to improve shade-matching accuracy\u0026sup1;⁵, the present study relied exclusively on the Chromascop shade guide, which remains one of the most commonly used systems in clinical practice⁹\u003csup\u003e,\u003c/sup\u003e \u0026sup1;\u0026sup2;\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u0026sup1;⁶. This approach reflects routine clinical conditions and allows for comparison with other studies using conventional shade guides.\u003c/p\u003e\n\u003cp\u003eThe Ishihara test was used to identify color vision alterations, acknowledging its limitation in grading severity\u0026sup2;\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u0026sup2;⁶\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u0026sup2;⁹. Previous reports indicate that individuals with normal trichromatic vision should not commit errors on the test⁶, whereas deuteranopes generally make fewer errors than protanopes due to genetic and photopigment-related differences\u0026sup3;\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e⁴\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e⁸. The findings of the present study are consistent with this pattern, as 2.5% of participants were identified as protanopes, and 11.25% failed specific plates suggestive of red\u0026ndash;green color vision deficiency.\u003c/p\u003e\n\u003cp\u003eDespite being classified as normal trichromats, 28.75% of participants made up to three errors on the Ishihara test, which are considered poor readings. Although these results were not statistically significant, a tendency was observed whereby participants who failed more than two Ishihara plates also committed a higher number of errors in the shade-matching tasks.\u003c/p\u003e\n\u003cp\u003eRegarding the shade guide pairing test, no previous studies using the Chromascop system were identified. Therefore, comparisons were made with studies using the Vita shade guide. Certain shade confusions reported in the literature differ considerably among studies, and no clear consensus exists regarding which hues are most frequently mismatched⁵\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u0026sup1;⁷\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u0026sup1;⁹. The present findings also revealed discrepancies in confused tones, reinforcing the notion that shade matching remains highly subjective and influenced by multiple variables.\u003c/p\u003e\n\u003cp\u003eTime required for shade selection has been associated with visual fatigue and increased error rates⁹. In the present study, participants who required more time tended to make more errors in both the guide pairing and crown shade selection tests. Although these differences did not reach statistical significance, the observed trend supports previous recommendations advocating for rapid shade selection to minimize visual fatigue.\u003c/p\u003e\n\u003cp\u003eThe influence of sex, age, and experience on shade-matching ability remains controversial. Some studies suggest that younger or more experienced female clinicians perform better⁵\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u0026sup1;\u0026sup2;\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u0026sup1;\u0026sup3;. whereas others report no significant differences\u0026sup2;\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u0026sup1;⁷\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u0026sup3;⁰\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u0026sup3;\u003csup\u003e1\u003c/sup\u003e. In the present study, no statistically significant differences were found between male and female participants, supporting studies that report no sex-related influence on shade selection accuracy.\u003c/p\u003e\n\u003cp\u003eAbout clinical experience, a statistically significant association was found between academic year and errors in the shade guide pairing test. Interestingly, fourth-year students committed fewer errors than fifth-year students, contradicting findings that associate greater experience with improved color matching⁹\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u0026sup3;\u003csup\u003e2\u003c/sup\u003e. This unexpected result may be explained by increased confidence, reduced attention to detail, or cumulative visual fatigue among more advanced students.\u003c/p\u003e\n\u003cp\u003eThe presence of ophthalmological alterations was significantly associated with a higher number of shade selection errors, in agreement with previous reports linking visual impairments to reduced color discrimination ability\u0026sup3;\u0026sup2;\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e⁴\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e⁵\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u0026sup2;\u0026sup3;\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u0026sup2;⁴\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u0026sup3;\u003csup\u003e3,\u0026nbsp;\u003c/sup\u003e\u0026sup3;\u003csup\u003e4\u003c/sup\u003e. However, the influence of visual correction methods was not evaluated and should be addressed in future studies.\u003c/p\u003e\n\u003cp\u003eDue to the low number of participants diagnosed with color vision deficiency, it was not possible to conclusively confirm the second hypothesis of the study. Nevertheless, the results suggest that shade selection errors are not limited exclusively to individuals with diagnosed color blindness. Therefore, assistance during shade selection may be beneficial not only for color-deficient individuals but also for dental students and clinicians with normal color vision.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003col start=\"1\" type=\"1\"\u003e\n \u003cli\u003eNo statistically significant association was observed between the number of errors on the Ishihara plates and the number of errors in the shade guide pairing test.\u003c/li\u003e\n \u003cli\u003eNo statistically significant relationship was found between errors on the Ishihara test and crown shade selection.\u003c/li\u003e\n \u003cli\u003eThe most frequently mismatched Chromascop shade families were B (58.75%), followed by C (40%), A (37.5%), and D (1.25%).\u003c/li\u003e\n \u003cli\u003eA statistically significant association was identified between the presence of ophthalmological disorders and errors in crown shade selection.\u003c/li\u003e\n \u003cli\u003eAlthough not statistically significant, a trend was observed between increased time required for shade selection and a higher number of errors.\u003c/li\u003e\n \u003cli\u003eStatistically significant differences were found between academic year and the number of errors in the shade guide pairing test, with fourth-year students making fewer errors. No significant association was observed between sex and shade selection errors.\u003c/li\u003e\n \u003cli\u003eFurther studies with larger sample sizes are recommended to better clarify the influence of visual factors on dental shade selection.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Ethics Committee of the Dental Hospital of the University of Barcelona (CEIC HOUB, approval code 2017-17) and was conducted in accordance with the principles of the Declaration of Helsinki. Written informed consent to participate was obtained from all participants prior to their inclusion in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eS.T.-D. conceived and designed the study, collected the data, performed the statistical analysis, and drafted the manuscript. The author read and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author would like to thank the dental students who voluntarily participated in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRabin JC, Kryder AC, Lam D. Diagnosis of normal and abnormal color vision with cone-specific VEPs. Transl Vis Sci Technol. 2016;5(1):8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSimunovic MP. Acquired color vision deficiency. Surv Ophthalmol. 2016;61:132\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJordan G, Deeb SS, Bosten JM, Mollon JD. The dimensionality of color vision in carriers of anomalous trichromacy. J Vis. 2010;10(12):1\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavidoff C, Neitz M, Neitz J. Genetic testing as a new standard for clinical diagnosis of color vision deficiencies. Transl Vis Sci Technol. 2016;5(2):2.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGocke HS, Piskin B, Ceyhan D, Gokce SM, Arisan V. Shade matching performance of normal and color vision-deficient dental professionals with standard daylight and tungsten illuminants. J Prosthet Dent. 2010;103:139\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBirch J. Identification of red-green colour deficiency: sensitivity of Ishihara and American Optical Company (Hard, Rand and Rittler) pseudoisochromatic plates to identify slight anomalous trichromatism. Ophthalmic Physiol Opt. 2010;30:667\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDozic A, Kleverlaan CJ, El-Zohairy A, Feilzer AJ, Khashayar G. Performance of five commercially available tooth colour-measuring devices. 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Evaluation of self-shade matching ability of dental students using visual and instrumental means. J Dent. 2012;40:e82\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePoljak-Guberina R, Celebic A, Powers JM, Paravina RD. Colour discrimination of dental professionals and colour-deficient laypersons. J Dent. 2011;39(Suppl 3):e17\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi Q, Wang YN. Comparison of shade matching by visual observation and an intraoral dental colorimeter. J Oral Rehabil. 2007;34:848\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDozic A, Kharbanda AK, Kamell H, Brand HS. European dental students\u0026rsquo; opinions about visual and digital tooth colour determination systems. J Dent. 2011;39(Suppl 3):e23\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeireles SS, Demarco FF, dos Santos IS, Dumith SC, Bona AD. 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J Prosthodont. 2007;16:269\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBorb\u0026eacute;ly J, Vars\u0026aacute;nyi B, Fej\u0026eacute;rdy P, Hermann P, Jakstat HA. Toothguide Trainer tests with color vision deficiency simulation monitor. J Dent. 2010;38(Suppl 2):e41\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSpalding JA, Cole BL, Mir FA. Advice for medical students and practitioners with color vision deficiency: a website resource. Clin Exp Optom. 2010;93:39\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKlemetti E, Matela AM, Haag P, Kononen M. Shade selection performed by novice dental professionals and colorimeter. J Oral Rehabil. 2006;33:31\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003c/ol\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":"Color vision deficiency, Color perception, Shade selection, Dental students, Prosthodontics","lastPublishedDoi":"10.21203/rs.3.rs-8503312/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8503312/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eTooth color selection is a complex process that relies on the interaction between dental tissues and visual perception. Accurate shade matching is essential for aesthetic success in restorative dentistry; however, color vision deficiencies may compromise this process in clinical practice.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo evaluate the prevalence of color vision alterations among dental students and to assess their potential influence on prosthetic shade selection.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA descriptive cross-sectional study was conducted involving 80 fourth- and fifth-year dental students at the University of Barcelona. Color vision was assessed using the Ishihara test. Shade-matching ability was evaluated by matching two Chromascop shade guides and by selecting the shade of a dental crown. Statistical analysis was performed using chi-square and Fisher\u0026rsquo;s exact tests.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf the participants, 33.75% were male and 66.25% female. Color vision deficiency was detected in 2.5% of the sample. A significant association was observed between the presence of ophthalmological alterations and the number of errors in shade-matching tasks. Students with less clinical experience made fewer errors. No significant differences were found between gender and shade-matching performance.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eAlthough the prevalence of color vision deficiency was low, visual alterations were associated with increased errors in shade selection. These findings highlight the importance of awareness, early detection, and educational support strategies to improve shade-matching accuracy during dental training.\u003c/p\u003e","manuscriptTitle":"Color vision alterations in dental students: a potential limiting factor in prosthodontic education","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-29 16:27:04","doi":"10.21203/rs.3.rs-8503312/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":"56ea8c97-850f-4241-aa13-c007d50ec4f2","owner":[],"postedDate":"January 29th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-22T15:15:50+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-29 16:27:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8503312","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8503312","identity":"rs-8503312","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}