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Regardless of whether it is acute or chronic, the assessment of pain should be simple and practical. Since the intensity of pain is thought to be one of the primary factors that determine its effect on a human's overall function and sense, there are many scales to assess pain. The aim of the current article was to review pain intensity scales that are commonly used in dental and oral and maxillofacial surgery (OMFS). Previous studies demonstrated that multidimensional scales, such as the McGill Pain Questionnaire, Short form of the McGill Pain Questionnaire, and Wisconsin Brief Pain Questionnaire were suitable for assessing chronic pain, while unidimensional scales, like the Visual Analogue Scales (VAS), Verbal descriptor scale, Verbal rating scale, Numerical rating Scale, Faces Pain Scale, Wong-Baker Faces Pain Rating Scale (WBS), and Full Cup Test, were used to evaluate acute pain. The WBS is widely used to assess pain in children and elderly because other scales are often difficult to understand, which could consequently lead to an overestimation of the pain intensity. In dental or OMFS research, the use of the VAS is more common because it is more reliable, valid, sensitive, and appropriate. However, some researchers use NRS to evaluate OMFS pain in adults because this scale is easier to use than VAS and yields relatively similar pain scores. This review only assessed pain scales used for post-operative OMFS or dental pain.

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This study aimed to investigate and compare the reliability and accuracy of tooth shade selection in the model using 30 milled crowns via five methods: (1) digital single-lens reflex (DSLR) camera with twin flash (TF) and polarized filter (DSLR + TF), (2) DSLR camera with a ring flash (RF) and polarized filter (DSLR + RF), (3) smartphone camera with light corrector and polarized filter (SMART), (4) intraoral scanner (IOS), and (5) spectrophotometer (SPEC). These methods were compared with the control group or manufacturer’s shade. The CIE Lab values (L, a, and b values) were obtained from five of the methods to indicate the color of the tooth. Adobe Photoshop was used to generate CIE Lab values from the digital photographs. The reliability was calculated from the intraclass correlation based on two repetitions. The accuracy was calculated from; (a) ΔE calculated by the formula comparing each method to the control group, (b) study and control groups were analyzed by using the Kruskal–Wallis test, and (c) the relationship between study and control groups were calculated using Spearman’s correlation. The reliability of the intraclass correlation of L, a, and b values obtained from the five methods showed satisfactory correlations ranging from 0.732–0.996, 0.887–0.994, and 0.884–0.999, respectively. The ΔE from all groups had statistically significant differences when compared to the border of clinical acceptance (ΔE = 6.8). The ΔE from DSLR + TF, DSLR + RF, SMART, and SPEC were higher than clinical acceptance (ΔE > 6.8), whereas the ΔE from IOS was 5.96 and all of the L, a, and b values were not statistically significantly different from the manufacturer’s shade (p < 0.01). The ΔE of the DSLR + RF group showed the least accuracy (ΔE = 19.98), whereas the ∆E of DSLR + TF, SMART, and SPEC showed similar accuracy ∆E (ΔE = 10.90, 10.57, and 11.57, respectively). The DSLR camera combined with a ring flash system and polarized filter provided the least accuracy. The intraoral scanner provided the highest accuracy. However, tooth shade selection deserves the combination of various techniques and a professional learning curve to establish the most accurate outcome.

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