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Oral health literacy and behaviors among Chinese university students: a comparative study of medical and non-medical students

BMC Oral Health volume 25, Article number: 683 (2025) Cite this article

Abstract

Background

Oral health literacy (OHL) plays a crucial role in improving oral health outcomes. Due to their academic background, medical students are presumed to have higher OHL levels than students in other disciplines. However, few studies have directly compared OHL and oral health behaviors between medical and non-medical students.

Methods

This cross-sectional study recruited undergraduate students from seven universities in Shandong, China. A total of 2,695 students completed an online survey between August and September 2024. The questionnaire collected information on demographic characteristics, OHL, and oral health-related behaviors. OHL was measured using the validated Chinese version of the short-form Dental Health Literacy Scale (HeLD-14). Data were analyzed using t-tests, chi-square tests, and mediation analysis conducted with the PROCESS macro in SPSS.

Results

Among the participants, 1,572 (58.3%) were medical students. Medical students scored significantly higher on the HeLD-14 total score than non-medical students (56.96 ± 11.04 vs. 54.59 ± 11.24, P < 0.001), with consistently higher scores across all dimensions. In terms of oral health behaviors, medical students were more likely to brush after late-night snacks, use fluoride toothpaste, and floss regularly compared to non-medical students (all P < 0.05). Mediation analysis showed that OHL partially mediated the relationship between academic major and these oral health behaviors.

Conclusion

Medical students exhibit higher OHL and healthier oral health behaviors compared to non-medical students. Enhancing OHL among non-medical students may foster better oral health behaviors and improve overall oral health outcomes.

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Introduction

Health literacy refers to an individual’s ability to acquire, understand, and apply health-related information to make informed decisions about their well-being [1]. Within the domain of oral health, oral health literacy (OHL) specifically encompasses the skills necessary to process and utilize oral health information to maintain and improve oral health, which has emerged as a critical research focus in the field of dental public health [2]. It encompasses multiple competencies, including reading, comprehension, decision-making, and the ability to navigate healthcare systems [3]. The World Health Organization (WHO) identifies health literacy as a fundamental determinant of public health, and within the field of oral health, OHL has been identified as a critical factor influencing both oral health behaviors and clinical outcomes [4, 5].

A growing body of research suggests that higher OHL levels are positively associated with improved oral health behaviors such as regular tooth brushing, flossing, reducing sugar intake, and routine dental check-ups [6, 7]. Conversely, individuals with low OHL have been found to engage in poorer oral health behaviors, which may contribute to adverse oral health outcomes [4, 8]. However, the relationship between OHL and oral conditions remains complex. While some studies support a positive association between OHL and oral health status, a recent systematic review indicated a weak and inconsistent association between OHL and dental caries, periodontal disease, and other oral conditions, with considerable heterogeneity among studies [2]. This indicates that other factors, such as self-efficacy, financial constraints, and social influences, may also play a role [9, 10]. These inconsistencies highlight the need for further research, particularly in specific populations such as university students, to better understand how OHL varies across different academic backgrounds and whether it translates into behavioral differences [11].

University students represent a key demographic for oral health promotion, as they form a significant portion of young adults and are in a transitional stage of developing lifelong health habits. Prior studies have shown that university students often exhibit suboptimal OHL and behaviors, and limited awareness of preventive care [12]. If left unaddressed, these patterns may contribute to long-term oral health risks. Research from various countries has highlighted that OHL levels among university students vary across academic disciplines, with medical students generally presumed to have higher OHL due to their structured curriculum and exposure to health-related knowledge [13, 14]. However, empirical evidence supporting this assumption remains limited, and whether higher OHL among medical students translates into better oral health behaviors has not been fully established [15]. Additionally, the extent to which OHL mediates the relationship between academic major and oral health behaviors remains unclear.

Although studies have explored OHL among university students in different regions, research on Chinese university students remains scarce. Given the high prevalence of oral health problems among young adults in China [16,17,18] and the low rates of regular dental check-ups [19], investigating the OHL and behaviors of university students is of great public health significance. University settings provide a structured environment where health education and targeted interventions can be effectively implemented, making this population an ideal focus for oral health promotion efforts [20]. This study aims to compare OHL and oral health behaviors between medical and non-medical students in China and explore the mediating role of OHL in the association between academic major and oral health behaviors.

Methods

Study design and ethical approval

This study was a cross-sectional survey conducted from August to September 2024 in Shandong Province, eastern China. The study aimed to assess OHL and behaviors among university students from diverse academic backgrounds. The study was approved by the Ethics Committee of Jinan Stomatological Hospital (Approval Number: JNSKQYY-2024-026). All participants provided informed consent before completing the survey. The consent process involved presenting an electronic informed consent form on the first page of the questionnaire, which clearly outlined the study’s objectives, the voluntary nature of participation, and the anonymity of the data collected. Participants were required to click the “Agree” button to proceed with the survey. No personal identifiable information was collected, and all data were securely stored on a cloud platform accessible only to the principal investigators, ensuring strict confidentiality.

Participants and sample size calculation

The study population comprised undergraduate students from diverse academic backgrounds, including one comprehensive university (encompassing both medical and non-medical disciplines), three medical universities, and three non-medical universities in Shandong Province. There were no restrictions based on student’s academic disciplines or year of study; all enrolled undergraduate students were eligible for inclusion. An online questionnaire was distributed via the “WenJuanXing” platform to facilitate data collection.

Since the main measurement of this study was OHL, we determined the required sample size based on the two-sample mean comparison formula using the short-form Health Literacy in Dentistry Scale (HeLD-14). Previous studies employing the HeLD-14 scale with a 5-point Likert system reported an average OHL score of 57.75 with a standard deviation of 12.60 among parents of preschool children [21]. Assuming this score reflects the average OHL level of medical students and hypothesizing that non-medical students would have an OHL level 95% that of medical students, we estimated the required sample size using the formula: N = 2⋅σ2⋅(Zα/2​+Zβ​)2​/Δ2. We set the significance level (α) at 0.05, corresponding to a Zα/2 value of 1.96, and a statistical power (1 − β) of 0.80, corresponding to a Zβ value of 0.84. The expected mean difference (Δ) was defined as 5% of the assumed medical student OHL score. Based on these parameters, the estimated minimum required sample size for each group was approximately 299. This survey ultimately included over 2,600 participants, exceeding the minimum sample size requirement.

Survey questionnaire

This study utilized a self-administered questionnaire to collect data (Supplementary material S1). The questionnaire consisted of single-choice questions and fill-in-the-blank items (e.g., age). It was designed by our research team and included three main sections: (1) Demographic information: gender, age, year of study, family residence, and parents’ educational levels; (2) OHL: measured using the Chinese version of the HeLD-14 scale [21, 22]; (3) Oral health behaviors: including brushing habits, the use of toothpaste, dental floss, and mouthwash, as well as dental visits, professional scaling, dental check-ups, orthodontics, and other dental procedures.

The HeLD-14 scale was chosen for its comprehensive assessment of OHL across seven dimensions: access, understanding, support, economic barriers, seeking care, communication, and application [22]. Each dimension contains two items rated on a 5-point Likert scale, where 1 represents “no difficulty” and 5 represents “unable to do.” To ensure higher scores reflect better OHL, the scale was reverse-scored accordingly. The Chinese version of HeLD-14 has been validated in prior studies, demonstrating strong reliability and validity for assessing OHL in Chinese populations [21]. Additionally, HeLD-14 has been widely adopted in previous OHL research in China [21, 23, 24], allowing for comparability across studies and ensuring methodological consistency, particularly in sample size estimation, where previous findings were referenced. Another advantage of this scale is its concise format, containing only 14 items, which reduces respondent burden and enhances feasibility for large-scale surveys.

The oral health behavior questionnaire was adapted from previous studies on oral health behaviors in China and refined based on the current study’s objectives and context [24, 25]. While no dedicated pilot study was conducted, these questions have been widely used in similar populations, reinforcing their validity and applicability. Given that our study focuses on university students, we tailored the questionnaire to reflect their specific oral health habits and behavioral patterns, ensuring relevance and accuracy in assessing their oral health practices.

Data collection

After obtaining ethical approval, the research team-initiated data collection. To ensure representativeness and diversity of the sample, an online survey was distributed through the Wenjuanxing platform. Recruitment was promoted via multiple channels, including campus broadcasts, WeChat public accounts, and invitations through various social media platforms (WeChat, QQ, Sina Weibo, Xiaohongshu). Participants were encouraged to share the survey to maximize reach and participation among eligible university students.

To avoid duplicate responses, each questionnaire could only be submitted once per internet protocol (IP) address. Two investigators reviewed the completed questionnaires to identify and exclude invalid responses, such as those with logical inconsistencies, missing items exceeding 20%, incomplete demographic information, or submission times shorter than 2 min.

Data analysis

After data collection, responses were imported into Excel and analyzed using SPSS version 25.0. Prior to analysis, data cleaning procedures were performed. Quantitative data were presented as mean ± standard deviation (SD), and comparisons between groups were conducted using independent-sample t-tests if normality was met; otherwise, Mann-Whitney U tests were used. Categorical data were expressed as percentages, with group comparisons performed using chi-square tests or Fisher’s exact test when necessary. The internal consistency reliability of the HeLD-14 scale was evaluated using Cronbach’s α coefficient, with values above 0.8 indicating good reliability. To explore whether OHL mediates the association between students’ majors (medical vs. non-medical) and their oral health behaviors, mediation analysis was conducted using the PROCESS macro in SPSS (Model 4). A nonparametric bootstrap approach with 5000 resamples was used to generate bias-corrected confidence intervals (CIs) for the indirect effect. If the 95% CI did not include zero, the mediation effect was considered statistically significant. All mediation models were adjusted for potential confounders, including gender, age, academic year, parental education level, and residential background. All statistical tests were two-sided, with P-values less than 0.05 considered statistically significant.

Results

Questionnaire response

A total of 2,805 questionnaires were distributed, and 2,695 valid responses were collected after excluding incomplete questionnaires, resulting in a response rate of 96.1%.

Basic information of participants

The included university students were aged 17–25 years, with a mean age of 18.99 ± 1.15 years. There was no significant difference in gender or age between medical and non-medical students. However, medical students were more likely to reside in urban areas and had parents with higher education levels compared to non-medical students (Table 1).

Table 1 Comparison of sociodemographic characteristics between medical and non-medical students
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Reliability of the HeLD-14 scale

The Cronbach’s α coefficient for the Chinese version of the HeLD-14 scale was 0.939. The Cronbach’s α for its seven dimensions—concerning, understanding, supporting, financial burden, medical treatment, communication, and application—were 0.876, 0.915, 0.723, 0.963, 0.895, 0.931, and 0.962, respectively.

OHL performance among Chinese university students

In terms of OHL, both medical and non-medical students showed relatively low scores in the financial burden dimension but performed better in the communication and application dimensions (Fig. 1). Comparing the HeLD-14 scores between the two groups, medical students had a significantly higher mean total score (56.96 ± 11.04) than non-medical students (54.59 ± 11.24, P < 0.001). Medical students also scored higher across all dimensions of the HeLD-14 scale (Table 2).

Fig. 1
figure 1

Distribution of OHL scores among medical students (A) and non-medical students (B). The bars, from left to right, represent the proportions of students with low (1–2 points), moderate (3 points), and high (4–5 points) OHL scores

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Table 2 Comparison of oral health literacy between medical and non-medical students
Full size table

To further explore whether exposure to oral health-related coursework influences OHL, we conducted a subgroup analysis comparing OHL scores across different academic years among medical students. The results showed that OHL scores increased with academic progression, with higher-year students demonstrating better OHL than lower-year students across most dimensions (Table S1). However, no significant differences were observed in the financial burden dimension or in the second item of the support dimension (“When you go to the dentist, do you ask other people to go with you?“).

Oral health behaviors among students of different majors

Medical students and non-medical students showed no significant difference in brushing frequency or brushing duration (Table 3). However, more medical students brushed after late-night snacks (70.0% vs. 62.8%, P < 0.001) and used fluoride toothpaste (31.8% vs. 25.6%, P < 0.001). Regular dental floss use was higher among medical students (28.9% vs. 23.3%, P = 0.001), while no significant differences were observed in mouthwash use or professional scaling frequency. Medical students were more likely to have regular dental check-ups (31.3% vs. 26.9%, P = 0.013) and undergo orthodontic treatment (20.9% vs. 17.5%, P = 0.025), but no difference was found in dental veneer procedures.

Table 3 Comparison of oral health behaviors between medical and non-medical students
Full size table
Table 4 Mediation analysis of OHL in the association between academic major and behavioral outcomes
Full size table

Mediation effect of OHL on university major and oral health behaviors

To investigate whether OHL mediated the association between university majors and oral health behaviors, we performed a mediation analysis using the PROCESS macro. University major (medical vs. non-medical students) was set as the independent variable, the total score of the HeLD-14 scale as the mediator, and oral health behaviors with significant group differences as the dependent variables. Covariates included gender, age, grade, parental education levels, and residence.

Regression analysis showed that university major was significantly associated with OHL (β = 1.5063, 95% CI: 0.6639–2.3487, P < 0.001), indicating higher OHL levels among medical students. In turn, higher OHL was significantly associated with brushing after a late-night snack (β = 0.0351, 95% CI: 0.0275–0.0428, P < 0.001) and fluoride toothpaste use (β = 0.0308, 95% CI: 0.0227–0.0390, P < 0.001). Mediation analysis (Table 4) showed that OHL accounted for 24.97% of the association between university major and brushing after a late-night snack (indirect effect = 0.0529, 95% CI: 0.0223–0.0878, P < 0.001) and 21.45% of the association with fluoride toothpaste use (indirect effect = 0.0464, 95% CI: 0.0189–0.0776, P < 0.001).

Discussion

To the best of our knowledge, this is the first study to compare OHL and behaviors between medical and non-medical students in China. Our findings reveal that medical students have higher OHL and perform better in specific oral health compared to their non-medical counterparts. Additionally, OHL partially mediates the relationship between university major and oral health behaviors, offering valuable insights for developing strategies to improve oral health behaviors among college students in the future.

Previous studies have assessed OHL and oral health behaviors among university students across different countries, yet the findings remain inconsistent and difficult to compare due to methodological variations. One major reason for this discrepancy is the use of different assessment tools. For instance, a study in Sydney employed the Comprehensive Measure of Oral Health Knowledge (CMOHK) [26], while research in China utilized the Knowledge, Attitude, and Practice (KAP) questionnaire [27]. In contrast, studies conducted in Saudi Arabia and other regions have used variations of the Rapid Estimate of Adult Literacy in Dentistry (REALD), including REALD-30 [12], REALD-40 [28], and REALD-99 [29]. These inconsistencies in measurement tools limit direct comparisons and contribute to variability in reported OHL levels. Additionally, differences in geographic regions, study populations, and whether participants had specific academic backgrounds further influenced the reported OHL levels. For example, a study among undergraduate nursing students at the University of Sydney indicated a generally good level of oral health knowledge [26], whereas a study in Cork, Ireland, found that only 23% of third-year university students had adequate OHL [14]. Moreover, research suggests that exposure to systematic oral health education significantly impacts students’ OHL levels [30]. These findings highlight the complexity of assessing OHL across different populations and emphasize the need for standardized measurement tools to facilitate meaningful cross-study comparisons.

When comparing our findings with other research in China, we found that the OHL levels of Chinese university students are generally comparable to those reported among young and middle-aged adults [21], yet remain lower than those observed in healthcare professionals [23] and adult orthodontic patients [31]. Notably, university students scored the lowest in the financial burden dimension of OHL, reflecting their reliance on parental financial support, which aligns with their developmental stage and limited financial independence [32]. While our results suggest that university students performed relatively well in the communication and application dimensions, variations in specific OHL dimensions have been reported in other studies, likely due to differences in study populations, academic backgrounds, and exposure to health-related education. Research on working adults and orthodontic patients has shown that the lowest-scoring OHL dimensions often relate to attention and social support rather than financial constraints [31], suggesting that different populations face distinct challenges in OHL. These findings underscore the importance of designing tailored oral health interventions that address the unique needs of different populations. For university students, strategies could focus on reducing financial barriers to dental care by providing affordable services or subsidies, ensuring that economic limitations do not hinder access to necessary oral health care. Meanwhile, for other populations, such as adult orthodontic patients, interventions may need to emphasize strengthening social support systems and increasing awareness of oral health care. Recognizing these differing challenges can help guide more effective and targeted health literacy programs to improve oral health outcomes across diverse demographic groups.

Our study revealed that medical students demonstrate higher OHL and superior oral health behaviors compared to non-medical students, which aligns with our initial hypothesis. This advantage was consistent across all dimensions of the HeLD-14 scale, reinforcing the role of academic major in shaping OHL. The structured curriculum of medical education, which incorporates systematic exposure to health-related knowledge and preventive care practices, likely contributes to these differences. These findings are consistent with previous research demonstrating that students in medical and healthcare-related disciplines tend to have higher OHL than their counterparts in non-health-related fields [29]. This highlights the impact of formal health education on literacy levels, emphasizing the need for targeted interventions among students in non-health-related fields. Furthermore, research has shown that educational interventions can significantly enhance OHL and oral health behaviors among adolescents and young adults, reinforcing the idea that university settings provide a crucial opportunity to improve oral health outcomes through structured education [33].

Beyond the direct association between academic major and oral health behaviors, our study found that OHL partially mediates this relationship. This mediation suggests that OHL serves as a key mechanism through which academic background influences oral health behaviors. Higher OHL levels may enhance health awareness, improve the ability to interpret and act upon health-related information, and facilitate the adoption of preventive behaviors [34]. For instance, the elevated OHL observed among medical students may enable them to better navigate oral health resources and maintain healthy practices such as brushing after late-night snacks and using fluoride toothpaste. These findings align with broader public health research, which has demonstrated that OHL mediates the relationship between education level and oral health outcomes in adults [35].

Given these findings, improving OHL among non-medical university students presents an opportunity to improve their oral health behaviors and, by extension, their long-term oral health outcomes. Since health literacy is a modifiable factor, targeted interventions could effectively address disparities in OHL and promote healthier behaviors. Incorporating oral health education into non-medical curricula may be a practical approach to equip students with the knowledge and skills necessary for better oral health practices [36]. Health promotion strategies tailored to non-medical students could include structured workshops on brushing techniques, the benefits of fluoride toothpaste, and the use of dental floss. Additionally, leveraging digital tools and e-learning platforms could provide accessible and engaging resources for oral health education, thereby fostering sustainable improvements in OHL and behaviors at the population level [37]. Previous studies have demonstrated the effectiveness of structured educational interventions in improving OHL and promoting healthier behaviors [33], indicating that universities can serve as a suitable setting for scalable public health initiatives.

Strengths and limitations

This study benefits from a large sample, the use of a validated OHL assessment tool, and the direct comparison between medical and non-medical students. Additionally, it provides novel insights into the mediating role of OHL in oral health behaviors, highlighting the importance of OHL in shaping preventive behaviors. However, several limitations warrant acknowledgment. First, as a cross-sectional study, causality cannot be established between OHL, university major, and oral health behaviors. Future longitudinal or intervention studies are needed to confirm the causal pathways identified. Second, our sample was limited to university students in a single region of China, which may limit the generalizability of our findings. Expanding the sample to include diverse geographic and cultural contexts would enhance the robustness of our findings. Finally, while the HeLD-14 scale provided a comprehensive assessment of OHL, future research could incorporate additional measures to capture broader dimensions of health literacy, such as digital health literacy. Moreover, our study did not assess whether medical students had received formal oral health education as part of their curriculum, which could be an important factor influencing their OHL and related behaviors. Future research should explore the dynamic changes in OHL throughout medical education and investigate the specific impact of oral health coursework on shaping students’ oral health knowledge and behaviors.

Conclusion

In conclusion, this study demonstrates the higher OHL levels and superior oral health behaviors of medical students compared to non-medical students and highlights the mediating role of OHL in these relationships. These findings emphasize the need to enhance OHL among college students through targeted education and intervention strategies, ultimately contributing to improved oral health outcomes in this population.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

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Acknowledgements

We extend our heartfelt gratitude to all the staff and participants who contributed to the questionnaire survey. We also thank Hiplot (https://hiplot.cn/) for their assistance in visualizing the Likert scale charts.

Funding

This work was supported by grants from the Shandong Province Medical and Health Science and Technology Development Plan Project (202312071011) and Shandong Province Humanities and Social Sciences Research Project (2023-JKZX-11).

Author information

Author notes

  1. Wei Wang, Changjie Xiao and Siyi Li contributed equally to this work.

Authors and Affiliations

  1. Department of Endodontics, Jinan Stomatological Hospital, Jinan, 250001, China

    Wei Wang & Fuju Zheng

  2. Department of VIP Dental Service, Jinan Stomatological Hospital, Jinan, 250001, China

    Changjie Xiao

  3. Department of Pediatric Dentistry, Jinan Stomatological Hospital, Jinan, 250001, China

    Siyi Li

  4. Dezhou Center for Disease Control and Prevention, Dezhou, 253000, China

    Min Li

  5. Department of Cardiology, Shandong Provincial Qianfoshan Hospital, The First Affiliated Hospital of Shandong First Medical University, Jinan, 250014, China

    Luxiang Shang

  6. Medical Science and Technology Innovation Center, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, 250117, China

    Luxiang Shang

  7. Shandong Center for Disease Control and Prevention, No. 16992, Jingshi Road, Lixia District, Jinan, 250014, Shandong, China

    Rui Li

Authors
  1. Wei Wang
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  2. Changjie Xiao
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  3. Siyi Li
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  4. Min Li
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  5. Fuju Zheng
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  6. Luxiang Shang
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  7. Rui Li
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Contributions

W Wang, C Xiao, and S Li were responsible for data collection, statistical analysis, data interpretation, and drafting of the manuscript. M Li assisted with questionnaire design and data validation. F Zheng and L Shang supervised the research process, provided critical feedback on the manuscript, and reviewed and revised it for important intellectual content. R Li conceptualized the study, secured funding, and provided overall project oversight. All authors have read and approved the final manuscript.

Corresponding authors

Correspondence to Fuju Zheng, Luxiang Shang or Rui Li.

Ethics declarations

Ethics approval and consent to participate

This study was performed in line with the principles of the Declaration of Helsinki. The study was approved by the Ethics Committee of Jinan Stomatological Hospital (Approval Number: JNSKQYY-2024-026). All participants provided informed consent before completing the survey.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Clinical trial number

Not applicable.

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Wang, W., Xiao, C., Li, S. et al. Oral health literacy and behaviors among Chinese university students: a comparative study of medical and non-medical students. BMC Oral Health 25, 683 (2025). https://doi.org/10.1186/s12903-025-06030-1

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  • DOI: https://doi.org/10.1186/s12903-025-06030-1

Keywords

BMC Oral Health

ISSN: 1472-6831

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