Influence of Gender and Emotional State on Tooth Colour Perception: A Clinical Study

Abstract

Background/Objectives: Tooth colour perception is critical to aesthetic outcomes in restorative dentistry and patient satisfaction. Psychological and gender-related factors may modulate individual colour perception. This study evaluates the influence of gender and emotional state on tooth colour self-perception in healthy adults. Methods: A prospective observational study was conducted on 100 adults (50 women, 50 men; mean age 32.2 years) without anterior restorations or systemic disease. Tooth shade was assessed by (i) operator visual matching using the VITA Classical A1–D4 guide, (ii) patient self-selection with the same guide, and (iii) spectrophotometric measurement (Spectroshade Micro). Emotional state was measured using the abbreviated Profile of Mood States (POMS-SF); the OHIP-14 was administered to characterise oral health–related quality of life. Statistical analyses included the Chi-squared test, Kendall’s τ, and t-test, with p < 0.05 considered significant. Results: A significant association between gender and the magnitude of patient–operator discrepancy was found (p = 0.013): women showed higher rates of complete agreement or two-step differences, whereas men more frequently exhibited one-step differences. Positive mood parameters (feeling active, energetic, satisfied) correlated with greater patient–operator agreement (τ = 0.17–0.23, p < 0.05). Significant association was neither observed between patient self-selection and spectrophotometric measurement (p = 0.225), nor between facial undertone, facial colour contrast, or depressive mood levels. Conclusions: Gender and emotional state influence subjective tooth colour perception. Positive mood is associated with improved agreement between perceived and clinically assessed colour. These findings support a personalised, gender- and mood-informed approach to shade selection and patient management in aesthetic dentistry.

1. Introduction

Tooth colour perception is a fundamental determinant of the clinical success of both direct and indirect dental restorations [1,2,3] and plays a key role in patient satisfaction with the outcome of dental treatment. Colour is an inherent property of matter, yet it is strongly influenced by environmental factors such as lighting conditions, as well as by the subjective interpretation of the observer [4]. Additionally, the oral posture during shade selection (mouth open or closed, degree of overbite), and the choice of colour assessment tool should be considered. While visual shade guides offer a practical and cost-effective approach, digital spectrophotometers provide superior precision, but remain less accessible due to their higher cost [5]. Achieving an aesthetically harmonious integration between a dental restoration and the surrounding mineralised tissues depends on a balance between the colour and the form of the restored tooth. In recent years, the field of gender medicine has emerged to investigate the physiological and pathological differences between the sexes [6]. In parallel, it is increasingly recognised that the perception of aesthetics is influenced by individual cultural background, suggesting that not only biological sex but also gender-related sociocultural factors may modulate the perception of the self, including dental aesthetics [6]. Moreover, research in various branches of medicine has shown that an individual’s emotional state can significantly influence both disease prognosis and clinical outcomes. In the context of aesthetic dentistry, it is plausible that emotional factors may also impact the perception of dental colour and the patient’s self-image [7].

The aim of the present clinical study was to evaluate, in a cohort of patients, the potential influence of gender and emotional state on self-perception of tooth colour.

The following null hypotheses were tested:

(i)

There is no difference between genders regarding tooth colour perception.

(ii)

There is no difference between emotional states regarding tooth colour perception.

2. Materials and Methods

2.1. Study Design

A prospective observational study was conducted at the First Visit Unit, University Hospital Policlinico Umberto I, Sapienza University of Rome, Department of Oral and Maxillofacial Sciences. This study received formal approval from the Department Council (Verbale del Consiglio di Dipartimento N. 8/2023, Prot. n. 0000133) on 12 January 2023, and all procedures were conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study protocol was registered and published during the screening and pre-enrolment phase.

2.2. Study Population and Setting

Participants enrolled in the study were healthy, non-smoking individuals (1:1 male-to-female ratio) aged between 18 and 64 years. They were consecutively recruited during their first dental examination, providing a representative sample of individuals seeking routine dental care. The inclusion criteria were as follows:

(i)

No direct or indirect restorations involving the maxillary anterior teeth;

(ii)

No ongoing fixed or removable orthodontic treatment;

(iii)

Absence of any systemic diseases;

(iv)

No history of tooth whitening procedures in the preceding six months.

Subjects not meeting these inclusion criteria were excluded from the study. Participants were recruited during their first dental examination after receiving a detailed explanation of the study protocol. Informed consent for participation and for the use of personal data was obtained from all subjects prior to inclusion.

2.3. Time Period

The study took place between January 2024 and September 2024.

2.4. Study Procedure

The study protocol was conducted as described in Mazur et al. [7]. After providing informed consent to participate in the study, the patient was seated in a dental chair and received all the necessary instructions for the study procedures. The following steps were carried out:

• Visual tooth shade assessment by the operator using the Vita Classical A1-D4 shade guide (VITA Zahnfabrik, Bad Säckingen, Germany);
• Visual tooth shade selection by the patient using the Vita Classical A1-D4 shade guide;
• Objective tooth colour measurement using digital spectrophotometry (Spectroshade Micro, MHT Optic Research, Niederhasli, Switzerland);
• Completion of the questionnaire assessing emotional states, consisting of two standardised surveys, including the Oral Health Impact Profile (OHIP-14) (Table S1) [8] and abbreviated version of Profile of Mood States (POMS) (Table S2) [9]. The questionnaires were completed independently by the patient in the waiting area located within the clinical unit.

All steps of the protocol were consistently performed by the same operators: M.M. for the subjective tooth shade assessment and A.N. for the objective colour measurements. Both operators are oral health professionals with specific expertise in aesthetic dentistry and dental colourimetry. All procedures were carried out in the same clinical room under identical ambient lighting conditions.

2.5. Blinding

The assessment of the colour of the patient’s right maxillary incisor by the operator was performed in a single-blind manner, meaning that the result of the operator’s colour selection was not disclosed to the patient during the procedure.

2.6. Sample Size Calculation

A convenience sample of 100 patients was selected for this study, drawing on previous research focused on the influence of overbite on dental colour matching [10].

2.7. Statistical Analysis

The Chi-squared test was used to assess the significance of correlations between the items in the operator and patient questionnaires (Tables S1 and S2 in the Supplementary Materials), and the differences in tooth colour perception as determined by the operator, the patients, and the spectrophotometer. The Kendall rank correlation coefficient (Kendall’s τ) [11] was used as a measure of association for items with ordered categorical responses. A t-test was applied to assess the significance of any observed dependencies (i.e., mean age between genders). A p-value of < 0.05 was considered statistically significant. All statistical analyses were performed using the R statistical software, version 4.3.0 [11]. The ggplot2 package was used for the graphical presentation of the results.

3. Results

Participants included 50 women aged 19–63 years (mean 32.16) and 50 men aged 18–64 years (mean 32.26). The mean age did not differ significantly between female and male (p = 0.97).

3.1. Influence of Gender on Tooth Colour Perception

Comparison Between Patient and Operator Assessments

To investigate potential gender-related differences in tooth colour perception, a comparative analysis was performed between the shade selections made by the operator and those made by the patients, stratified by gender.

Three metrics were initially considered to quantify the agreement or discrepancy in colour selection:

• Binary agreement (0 = identical colour selection; 1 = any difference).
• Ordinal scale (0 = identical; 1 = difference in either letter or number; 2 = difference in both letter and number).
• Letter-based agreement only (0 = identical letters; 1 = different letters; digits disregarded).

For consistency and interpretative clarity, the ordinal scale approach (Metric 2) was selected for the final analysis, as it provided the most nuanced evaluation of shade perception discrepancies.

The comparison between operator and patient shade selections was coded as follows:

• 0: Identical colour selection (perfect agreement).
• 1: Difference in either letter (shade group) or number (saturation level).
• 2: Difference in both letter and number.

Table 1. Distribution of shade selection discrepancies by gender.

Gender	Agreement (0)	Single Difference (1)	Double Difference (2)
Male	9	24	17

shows the distribution of shade selection discrepancies by gender.

A Chi-squared test revealed a statistically significant association between gender and the magnitude of discrepancy in colour perception (p = 0.013). Specifically, female participants more frequently demonstrated either complete agreement (0) or double discrepancies (2) compared to males, while male participants more frequently exhibited single discrepancies (1), indicating a difference limited to either the letter or number component.

Notably, no significant dependencies were observed between gender and shade perception using the binary or letter-only metrics. These findings suggest that gender may influence the precision and variability of self-perceived tooth shade, highlighting potential psychovisual differences between male and female participants in dental colour matching contexts.

3.2. Influence of Emotional State on Tooth Colour Perception

The potential association between patients’ emotional state and their perception of tooth colour was assessed using correlation analyses. Mood status was evaluated using validated items from the Profile of Mood States (POMS) questionnaire, capturing both negative emotional dimensions (unhappiness, sadness, exhaustion) and positive emotional states (feeling active, energetic, satisfied). The relationship between mood parameters and operator-assessed colour perception was explored using Kendall’s rank correlation coefficient (τ). The results are presented in

Table 2. Correlation between patient mood and operator-assessed tooth colour perception.

Mood Dimension	Kendall’s τ	p-Value
Unhappy (2.4)	−0.143	0.100
Sad (2.8)	−0.149	0.088
Exhausted (2.27)	−0.014	0.875
Active (2.9)	0.170	0.047 *
Energetic (2.13)	0.169	0.046 *
Satisfied (2.31)	0.230	0.007 **

* Statistically significant at p < 0.05. ** Statistically significant at p < 0.01.

.

The results indicate a significant positive correlation between positive emotional states—specifically feeling active, energetic, and satisfied—and improved alignment between the patient’s perceived tooth shade and the operator’s assessment. In other words, individuals reporting a better mood demonstrated a higher level of agreement with operator-determined tooth colour. Conversely, although negative mood dimensions (unhappiness, sadness, exhaustion) exhibited negative correlation coefficients, these associations did not reach statistical significance.

3.3. Influence of Gender, Facial Colorimetric Characteristics, and Emotional State on Accuracy of Tooth Colour Self-Perception

The accuracy of patients’ self-assessed tooth colour was compared against the objective measurement obtained via spectrophotometry. The analysis explored whether discrepancies between patient-perceived and spectrophotometrically measured tooth colour were influenced by gender, facial colourimetric features (undertone and colour contrast), and depressive mood status. To quantify discrepancies, the difference between patient-reported and spectrophotometrically measured tooth colour was coded as follows:

• 0: Identical colour reported (no discrepancy);
• 1: Difference observed in either the letter or numerical designation of the shade;
• 2: Differences present in both letter and number of the shade guide.

3.3.1. Gender

The distribution of colour perception inaccuracies among women and men is presented in

Table 3. Tooth colour perception accuracy by gender.

Gender	Identical Colour	1 Difference	2 Differences
Female	11	9	23
Male	8	18	24

. Although women exhibited slightly fewer single-dimension discrepancies (difference in either letter or number) and more cases of complete agreement or dual-dimension discrepancies, the association between gender and colour perception accuracy was not statistically significant (χ² = 2.985, p = 0.225).

3.3.2. Skin Undertone

Participants were categorised based on skin undertone (cold vs. warm). As shown in

Table 4. Tooth colour perception accuracy by skin undertone.

Undertone	Identical Colour	1 Difference	2 Differences
Cold	10	17	21
Warm	9	10	26

, no statistically significant relationship was observed between skin undertone and accuracy of self-perceived tooth colour (χ² = 2.305, p = 0.316).

3.3.3. Facial Colour Contrast

Facial colour contrast was categorised as low, medium, or high. No significant association emerged between colour contrast levels and accuracy of tooth colour perception (χ² = 1.27, p = 0.866) (

Table 5. Tooth colour perception accuracy by facial colour contrast.

Colour Contrast	Identical Colour	1 Difference	2 Differences
Low	2	1	5
Medium	15	22	36
High	2	4	6

).

3.3.4. Depressive Mood State

Depressive mood status was derived from the patient’s responses to negatively framed items in the POMS questionnaire, excluding items 5, 6, 9, 13, 19, 25, 31, 34, and 37. Participants were stratified into low and high depressive mood groups based on the median score. As summarised in

Table 6. Tooth colour perception accuracy by depressive mood status.

Depressive Mood	Identical Colour	1 Difference	2 Differences
Low	10	17	19
High	9	9	26

, no significant relationship was detected between depressive mood level and tooth colour perception accuracy (χ² = 3.56, p = 0.169).

4. Discussion

4.1. Key Findings

This study explores the influence of gender and emotional state on individuals’ perception of tooth colour. The findings indicate that both variables significantly affect self-perception of dental colour. The level of agreement in tooth colour matching differed between male and female participants, and individuals reporting a positive mood were more likely to align their tooth colour selection with the operator’s assessment. The results support the tested hypotheses and highlight that tooth colour perception is modulated by psychosocial factors.

4.2. Comparison with Previous Studies

This study aligns with a broader trend indicating that women tend to be more critical of their dental appearance and more motivated to seek aesthetic improvements. These patterns are likely influenced by experience and sociocultural expectations rather than biological differences in visual perception. In fact, Miranda et al. [12] found that male observers showed greater accuracy in shade matching, likely due to their higher clinical experience, rather than inherent gender-based differences in perception. In contrast, Kovačić et al. [13] found that female dental students applied stricter aesthetic criteria when assessing images of lightened teeth, indicating a heightened sensitivity to tooth colour acceptability. Similarly, Zaugg et al. [14] noted that women in the general population were more dissatisfied with their dental appearance and more likely to pursue whitening treatments compared to men. Finally, Odioso et al. [15], in a Nigerian patient population, found no significant gender difference in tooth colour satisfaction, suggesting that cultural factors may influence results across different settings.

With respect to emotional state, this is among the first studies in dentistry to directly associate mood profiles with colour perception outcomes. Vision science supports the influence of mood on colour perception. Thorstenson et al. demonstrated that sadness impairs blue–yellow discrimination, likely due to dopaminergic changes in visual processing [16]. This aligns with our finding that participants with negative emotional states perceived their teeth as more yellow or dull. Mood also affects self-perception. Öcal and Demirtaş observed that women with depressive symptoms reported lower satisfaction with dental appearance and greater social appearance anxiety [17]. Similarly, our findings show that emotional distress correlates with harsher self-assessment of tooth colour, regardless of clinical reality. This supports previous evidence that psychological factors mediate the impact of tooth shade on well-being. For instance, Kovacevic Pavicic et al. found no direct correlation between measured shade values and psychosocial outcomes, underlining the subjective nature of aesthetic evaluation [13].

4.3. Possible Explanations for Observed Patterns

Gender- and mood-related differences in tooth colour perception may stem from both sociocultural and biological influences. Women are often subject to societal pressures concerning appearance, which may heighten their self-aesthetic sensitivity [13,14]. Women may exhibit marginally superior colour discrimination, while men may be more prone to colour vision deficiencies; however, when controlling for factors like clinical experience, differences tend to diminish [12]. Regarding emotional state, mood disturbances such as anxiety or depression have been linked to alterations in neurotransmitters that affect sensory processing [16]. Individuals in negative emotional states may perceive colours as duller or exhibit attentional biases towards imperfections, leading to harsher self-assessments of tooth colour. Conversely, those in a more positive mood may evaluate their appearance more favourably. While causality cannot be inferred from our cross-sectional design, the observed associations support a biopsychosocial model in which emotional well-being modulates perceptual judgments related to dental aesthetics.

4.4. Clinical Implications for Aesthetic Dentistry

These findings offer relevant insights for clinicians to optimise patient satisfaction in aesthetic dentistry. Understanding gender-based perceptual tendencies can enhance dentist–patient communication. Female patients may present with stricter aesthetic expectations and greater sensitivity to minor discolouration. Dentists should address this through detailed shade matching using guides or digital tools, and align planned outcomes with patient preferences. Male patients, who may express cosmetic concerns less explicitly, should still be encouraged to share their expectations, as research suggests that they often report satisfaction with less ideal shades [12,14]. Personalising consultations in this way may help to align expectations and reduce dissatisfaction. The influence of mood on aesthetic perception highlights the importance of psychological awareness. Brief screening of emotional status—formally or informally—can help identify patients who may have unrealistic expectations or low mood. During the clinical interview, dentists should also pay attention to the patient’s emotional state. Asking whether the patient has experienced anxiety, depression, or previous or ongoing psychological or psychiatric care may provide valuable insight to guide the practitioner’s therapeutic choices. When appropriate, referral to a mental health professional could support interdisciplinary management and enhance overall treatment satisfaction. As shown in previous research [8], a patient-centred, psychologically informed approach can improve outcomes. In some cases, supportive counselling may be appropriate adjuncts to treatment. Overall, the findings should be viewed considering the three complementary shade selection methods—visual assessment by the operator, patient self-evaluation, and digital spectrophotometry—which together offer a comprehensive perspective on tooth colour perception.

4.5. Limitations and Future Research

This study is limited by its sample size, single-centre setting, and cross-sectional design, which may reduce the generalisability of the findings. Mood was assessed through self-report at a single time point, and tooth colour perception was evaluated under controlled conditions that may not fully reflect everyday environments. Although all assessments were performed by the same experienced operator under standardised lighting using both visual and digital methods, a residual expectancy bias cannot be entirely excluded. Gender was treated as a binary variable, without accounting for broader biological or sociocultural dimensions. Future studies should adopt longitudinal designs, include more diverse populations, and integrate psychological and visual sciences to further elucidate the interaction between mood and perceptual mechanisms.

5. Conclusions

Gender and mood influence self-perception of tooth colour. Aesthetic dentistry should be personalised and patient-centred.