Knowledge-to-practice gap in oral microbiome counseling: a mixed-methods study among dental practitioners in Saudi Arabia

Abstract

Background

Evidence links the oral microbiome to systemic diseases, yet its integration into dental practice remains limited, particularly in Saudi Arabia, where non-communicable diseases are prevalent. Equipping dental practitioners with microbiome-related competencies is essential. This study evaluated the knowledge, confidence, and counseling practices of dental practitioners, identifying predictors and barriers to the clinical application of these practices.

Methods

A convergent mixed-methods design involved 286 dental practitioners (general dentists, specialists, academics) across Saudi Arabia. Participants completed a 23-item validated questionnaire (13 assessing objective knowledge, 8 evaluating beliefs, confidence, and barriers, 2 open-ended). Quantitative data were analyzed using descriptive statistics, chi-square tests, and binary logistic regression. Qualitative data from 30 open-ended responses were qualitatively analyzed to explore contextual factors.

Results

Practitioners exhibited moderate-to-high objective knowledge (mean score: 9.14 ± 1.87 out of 13), with 55.9% in the medium category, 28.3% high, and 15.7% low. Confidence in counseling was moderate, with 39.6% reporting high or very high confidence. Prior microbiome training (OR = 3.21, 95% CI: 1.82–5.65, p < 0.001), frequent participation in Continuing Professional Development (CPD), and journal use (OR = 2.15, 95% CI: 1.25–3.70, p = 0.006) predicted higher confidence. Barriers included lack of formal training (52.6%), time constraints (17.9%), and patient disinterest (29.5%). Social media was a key knowledge source (24.2%), while dental curricula were underutilized (14.4%). Qualitative themes reinforced barriers and highlighted conditional motivation linked to patient risk factors.

Conclusions

A notable knowledge-to-practice gap persists in oral microbiome counseling. We propose integrating microbiome science into dental curricula and utilizing mobile Continuing Professional Development (CPD) tools to enhance confidence and increase counseling frequency, thereby addressing training gaps and infrequent updates. Additionally, Electronic Health Record (EHR) prompts are recommended to overcome time constraints and patient disinterest, aligning with Saudi Vision 2030’s goals for preventive care.

Introduction

The oral microbiome, comprising over 700 bacterial species, fungi, viruses, and archaea, plays a crucial role in both oral and systemic health [1, 2]. Dysbiosis in this ecosystem drives dental caries, periodontitis, and oral cancer, with broader implications for systemic conditions such as cardiovascular disease, diabetes, adverse pregnancy outcomes, and Alzheimer’s disease through hematogenous dissemination of pathogens like Porphyromonas gingivalis [3,4,5]. The oral-gut axis further links oral dysbiosis to gastrointestinal inflammation and metabolic dysfunction, amplifying the microbiome’s systemic impact [6, 7]. In Saudi Arabia, where the prevalence of diabetes exceeds 18.7% and cardiovascular disease accounts for 42% of mortality, these oral-systemic connections underscore the critical need for microbiome-informed dental practice to address public health challenges [8].

Despite robust evidence, the integration of microbiome science into clinical dental practice remains limited. Nationwide surveys in Saudi Arabia indicate that while most dental practitioners recognize the term “microbiome,” only a small fraction fully understand its systemic implications, revealing a significant knowledge-to-practice gap [9]. This gap is driven by educational curricula that prioritize technical skills over microbial ecology, limited interprofessional collaboration despite established links between periodontitis and systemic diseases, and insufficient access to updated microbiome training [9,10,11,12]. Moreover, healthcare students, including dental professionals, often lack familiarity with evidence-based practice terminology, further hindering the adoption of microbiome science [13]. Educational interventions have proven effective in addressing similar gaps. For example, a five-year reform of the oral microbiology curriculum at Wuhan University increased the percentage of A-grade achievements from 60% to over 80%, thereby enhancing knowledge retention [14]. Similarly, a systematic review found that interactive continuing professional development (CPD) programs, incorporating workshops and self-reflection, were more effective than passive methods in driving behavioral change among dental professionals ([15].

Behavioral science offers insights into the barriers that prevent knowledge translation. Bandura’s self-efficacy theory posits that clinicians’ confidence in applying knowledge is essential for practice change, yet inadequate training undermines this confidence [16]. Knowles’ adult learning principles emphasize the importance of relevant, reinforced education, but Saudi practitioners frequently cite time constraints, perceived patient disinterest, and limited institutional support as obstacles [17]. These challenges are particularly pressing in Saudi Arabia, where Vision 2030 prioritizes a preventive, value-based healthcare model that integrates oral health to mitigate systemic disease burdens [18, 19]. The lack of microbiome-focused education and practical tools, such as structured counseling protocols, limits practitioners’ ability to provide effective patient counseling, perpetuating the knowledge-to-practice gap and hindering alignment with national health objectives.

This study aims to assess the knowledge, confidence, and counseling practices of dental practitioners in Saudi Arabia regarding the oral microbiome, using a 23-item questionnaire (13 items for objective knowledge, 8 for self-rated knowledge, confidence, and barriers, and 2 open-ended), to identify predictors and barriers to its clinical application. By integrating quantitative data and qualitative factors, it aims to characterize implementation barriers and propose actionable strategies for microbiome-informed dental practice, thereby supporting Saudi Arabia’s Vision 2030 objectives for preventive healthcare.

Methodology

Study design and setting

This study employed a convergent mixed-methods design to examine knowledge, confidence, and counseling practices related to the oral microbiome among dental professionals in Saudi Arabia. Quantitative and qualitative data were collected simultaneously and analyzed in parallel to provide complementary insights. The design integrated survey responses with qualitative insights from two open-ended questions (Q22, Q23), aligning with established mixed-methods approaches [20], despite the absence of interviews or focus groups.

Participants and recruitment

A total of 286 licensed dental practitioners, including general dentists, specialists, and academic faculty, participated from multiple regions of Saudi Arabia. Recruitment occurred through professional dental networks, educational institutions, and continuing professional development forums. Exclusion criteria included dental students, unlicensed individuals, inactive practitioners, and those residing outside the country. The purposive sample reflects a diverse cross-section of active dental practitioners, enhancing external validity despite not being statistically representative of the entire population.

Sample size and sampling technique

The target sample size was 384 (95% confidence level, 5% margin of error), calculated using a standard formula for proportions in a finite population. A purposive sampling strategy ensured representation across professional roles and regions. However, 286 practitioners were recruited, with one case excluded due to missing data (N = 285 for most analyses), which was deemed sufficient based on a post-hoc power analysis (> 0.80) for key statistical tests.

Data collection tool and procedure

Data were collected using a validated 23-item questionnaire (Supplementary File S1), comprising sections on demographics, knowledge assessment, self-perceived knowledge, clinical application, predictive variables, and open-ended responses. The English-language tool was distributed electronically via Google Forms and pilot-tested with 20 practitioners, yielding a Cronbach’s alpha of 0.81, which aligns with best practices for scale development (Boateng et al., 2018) [21]. It included: (1) demographic variables (age, gender, years of experience, specialization, workplace); (2) objective knowledge assessment (13 multiple-choice items, Q1–Q13, adapted from Parveen et al., 2024) [9]; (3) self-rated knowledge and confidence (Likert-scale items); (4) clinical application and counseling practices; (5) perceived barriers and facilitators; (6) open-ended qualitative questions (Q22–Q23).

Qualitative analysis

Qualitative data from two open-ended questions (Q22: challenges/motivators; Q23: training needs) were analyzed using inductive content analysis. Thirty substantive responses were coded independently by two researchers, with discrepancies resolved through discussion. Emergent codes were organized into four content categories: professional barriers, time and workflow constraints, patient-related barriers, and conditional motivation. Saturation was achieved at the category level, with no new concepts emerging beyond 30 responses.

Ethical considerations

Ethical approval was obtained from the Standing Committee for Scientific Research Ethics, Jazan University (REC-45/05/894, HAPO-10-Z-001) . All participants provided informed consent, and confidentiality was assured.

Statistical analysis

Quantitative data were analyzed using SPSS v27. Descriptive statistics (frequencies, percentages, means, and standard deviations) were presented for all variables before conducting inferential tests. Chi-square tests and logistic regression were used to assess the associations between predictors and counseling confidence. For regression, a binary outcome (Q20_high) was defined: scores ≥ 4 on the 5-point Likert scale were coded as high confidence. This threshold was selected based on its alignment with practical readiness for patient counseling, where scores of 4 and 5 indicate a willingness and perceived ability to engage, consistent with Wilkes et al. (2017) [22], who used a similar cutoff to assess provider confidence in genetic counseling.

Results

Participant characteristics

A total of 286 licensed dental practitioners from across Saudi Arabia participated, extending the previously published national dataset [9] by adding respondents and new variables on counseling confidence, clinical application, and perceived barriers. The sample was predominantly female (54.2%) and comprised a mix of general dentists, specialists, and academic faculty, with the majority working in government institutions (41.3%). Years of experience varied widely, from less than 5 years to over 20 years. Refer to Table 1 for the complete demographic profile.

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Descriptive outcomes

Objective knowledge (Q1–Q13)

The mean objective knowledge score, based on 13 validated multiple-choice questions assessing the oral microbiome, was 9.14 ± 1.87 (range 2–12; N = 285, one missing). The distribution of scores is presented in Fig. 1.

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Conceptual beliefs and clinical application (Q15–Q17)

Most respondents (73.3%) agreed that nutritional counseling influences the oral microbiome (Q15), with 63.2% recognizing the clinical relevance of the oral–gut axis (Q16). A strong preference for formal microbiome training was reported, with 85.7% in agreement (Q17).

Sources of learning (Q18)

The primary sources of learning about the oral microbiome (N = 285) included journals (30.5%), social media (24.2%), workshops/CPD (23.5%), dental curriculum (14.4%), and no formal source (7.4%).

Updating Microbiome knowledge frequency (Q19)

Most participants (89.1%) updated their microbiome knowledge occasionally (monthly or less), while 10.2% updated it frequently (weekly or more), and 0.7% never, as presented in Table 2 and illustrated in Supplementary Fig. 1 (Q15-Q19).

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Self-Reported confidence in counseling (Q20)

Self-reported confidence in counseling patients about the oral microbiome, measured on a 5-point Likert scale, showed the highest proportion (30.8%) with moderate confidence, followed by 25.2% with high confidence and 14.4% with very high confidence. Lower confidence levels were reported by 19.6% (low) and 9.8% (not at all confident), as shown in Fig. 2. For regression analysis, a binary variable (Q20_high) was defined as 1 for scores of 4 or higher and 0 for all other scores.

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Relationships among knowledge, confidence, and barriers (Q1–Q13, Q20, Q21)

The interplay between objective knowledge, confidence in counseling, and reported barriers highlights potential correlations that may influence counseling practices. Confidence increased with objective knowledge (Spearman’s ρ ≈ 0.70, p < 0.001). Confidence profiles differed across knowledge groups (3 × 5 distribution). A heatmap visualization is provided in Fig. 3.

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Barriers to counseling (Q21)

The primary barriers to counseling patients about the oral microbiome were lack of formal training (52.6%), patient disinterest (29.5%), and lack of time (17.9%), as summarized in Fig. 4; Table 2. These barriers indicate significant challenges in applying microbiome knowledge in a clinical setting.

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Qualitative insights (open-ended responses)

Section F of the questionnaire included two optional open-ended questions (Q22 and Q23) to capture perspectives beyond structured survey items. Q22 asked respondents to describe, in their own words, the challenges or motivators affecting their ability to counsel patients about the oral microbiome, while Q23 explored what additional training or support would help them apply microbiome knowledge more effectively. Thirty participants provided substantive responses, with brief or blank entries excluded. This qualitative strand complements the convergent mixed-methods design, providing deeper insight into the contextual and professional factors that shape counseling behavior. Four main categories emerged from Q22: Professional barriers, Time and workflow constraints, Patient-related barriers, and Conditional motivation. These findings align with and expand on quantitative results in Table 3, particularly the barriers of lack of formal training, limited time, and patient disinterest. Illustrative excerpts are presented in Table 3.

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Discussion

This mixed-methods study reveals a significant knowledge-to-practice gap in oral microbiome counseling among dental practitioners in Saudi Arabia, consistent with global trends where scientific knowledge often fails to translate into clinical practice [9, 23, 24]. Despite moderate-to-high objective knowledge of the oral microbiome (mean score: 9.1 ± 1.9 out of 13), only 25.2% of participants reported high confidence and 14.7% very high confidence in patient counseling (Q20, N = 285), highlighting a disconnect driven by educational, practical, and perceptual barriers. These findings underscore the urgent need for targeted strategies to integrate microbiome science into routine dental care, particularly in Saudi Arabia, where the high prevalence of systemic diseases, such as diabetes (18.7%) and cardiovascular disease (accounting for 42% of mortality), amplifies the relevance of oral-systemic health linkages [7, 8].

The survey results indicate strong recognition of the oral microbiome’s clinical relevance, with 73.3% of practitioners agreeing that nutritional counseling influences the oral microbiome (Q15) and 63.2% acknowledging the role of the oral-gut axis in diagnosis and treatment planning (Q16). Additionally, 85.7% supported formal microbiome training (Q17), reflecting a desire for enhanced education. However, reliance on informal knowledge sources, such as social media (24.2%, Q18), over dental curricula (14.4%, Q18), and infrequent knowledge updates (89.1% updating monthly or less, Q19), suggest educational gaps that limit clinical application. These findings align with prior studies that have noted insufficient microbiome integration in dental education [9].

The association between higher knowledge levels and greater counseling confidence (Spearman’s ρ ≈ 0.70, p < 0.001) supports Bandura’s self-efficacy theory, which posits that competence fosters confidence [16]. This finding aligns with those of Wilkes et al. (2017) [22], who reported that primary care providers with formal genetics training exhibited greater counseling confidence. However, our study indicates that knowledge alone is insufficient, as systemic barriers—such as limited formal training (52.6%, Q21) and reliance on informal sources like social media (24.2%, Q18)—hinder clinical translation. This reliance on social media, while reflecting modern learning trends, raises concerns about information reliability, consistent with Hamasha et al. (2019) [25], who noted variable quality in online dental education resources.

Qualitative insights further contextualize these barriers, aligning with global challenges in dental practice. The lack of structured microbiome training, reported by 52.6% of participants (Q21), echoes Taşdemir and Alkan (2015) [26], who found that over 70% of Turkish physicians did not apply oral-systemic knowledge due to educational gaps. Time constraints, cited by 17.9% (Q21), reflect broader challenges in dental practice, where procedural priorities often overshadow preventive counseling [27]. Perceived patient disinterest (29.5%, Q21) suggests a need for improved patient education strategies, as low public awareness of oral-systemic links may undermine counseling efforts [28]. These barriers form a self-reinforcing cycle that limits counseling, despite strong practitioner recognition of microbiome relevance (Q15, Q16).

The findings are particularly significant in Saudi Arabia, where Vision 2030 emphasizes the importance of preventive healthcare [18, 19]. Integrating microbiome-informed counseling could enhance preventive care, especially for patients with systemic conditions. Unlike prior studies focusing solely on knowledge gaps, our mixed-methods approach combines quantitative predictors (e.g., initial training, OR = 3.21, 95% CI: 1.82–5.65, p < 0.001) with qualitative barriers, providing a robust foundation for educational and practice reforms.

One of the key strengths of this study lies in its mixed-methods design, which allowed for a comprehensive exploration of the knowledge-to-practice gap by integrating both quantitative patterns and qualitative insights. By capturing numerical associations alongside practitioners’ lived experiences, the study provides a richer and more nuanced understanding of the barriers to microbiome counseling. The inclusion of a diverse, multi-specialty sample from various regions across Saudi Arabia further enhances the credibility and generalizability of the findings. Rigorous thematic coding and statistical analysis ensured methodological robustness across both strands of data.

Despite its strengths, this study has several limitations that should be acknowledged. The cross-sectional design limits causal inferences about knowledge, confidence, and counseling behaviors. Self-reported data may be subject to social desirability bias, potentially inflating reported confidence (e.g., 47.9% high confidence, Q20) or counseling frequency. Administering the questionnaire in English may have excluded non-fluent practitioners, thereby reducing the inclusivity of the sample. Additionally, the placement of Section D (Clinical Application) after Section C (Self-Perceived Knowledge) may have introduced response bias, as questions about the oral microbiome’s clinical relevance (e.g., Q15–Q17) could have prompted participants with inadequate knowledge to reflect and potentially adjust their responses. Although saturation of factors was achieved with 30 qualitative responses, the small subset limits the depth of contextual insights. Missing data (in one case, N = 285 for most analyses) and the absence of longitudinal follow-up limit insights into behavioral changes over time. Future research should employ longitudinal designs, randomize question order to mitigate response bias, and incorporate patient perspectives to gain a deeper understanding of communication dynamics.

Clinical implications and recommendations

To address the identified barriers, we propose a targeted implementation framework that integrates oral microbiome counseling into dental practice, aligning with Saudi Vision 2030’s preventive health goals. The framework addresses three primary barriers: lack of formal training (52.6%, Q21), time constraints (17.9%, Q21), and perceived patient disinterest (29.5%, Q21). Proposed strategies include:

1. 1.

Curriculum Integration and CPD: Incorporate microbiome science into dental curricula and develop case-based continuing professional development (CPD) modules to enhance knowledge and confidence (OR = 3.21 for training) [29, 30].

2. 2.

Microbiome Moments: Implement brief, 2-minute counseling sessions during routine cleanings, supported by electronic health record (EHR) prompts for high-risk patients, to address time constraints [31].

3. 3.

Patient Engagement: Train auxiliary staff to initiate microbiome discussions and use visual aids to boost patient interest, addressing low awareness [28].

Supportive Tools: Mobile microlearning platforms for just-in-time education and EHR-integrated prompts to streamline counseling.

Expected outcomes

*

Increased practitioner confidence (projected OR = 3.21).

*

40% increase in microbiome-related counseling frequency.

*

Enhanced alignment with Saudi Vision 2030’s preventive care objectives.

These strategies leverage existing infrastructure, such as mobile technology and EHR systems, to create sustainable, scalable solutions for integrating microbiome science into routine dental care.

Conclusion

This mixed-methods study highlights a significant gap between knowledge of the oral microbiome and its clinical application among dental practitioners in Saudi Arabia. Despite widespread recognition of the microbiome’s clinical relevance, limited confidence and infrequent counseling persist, driven by educational gaps, time constraints, and a perceived lack of patient interest. The study’s integration of quantitative and qualitative insights identifies prior training and evidence-based learning as key predictors of practitioner confidence, while underscoring structural barriers that impede clinical integration. To address this divide, a multifaceted strategy is proposed: integrating microbiome science into dental curricula, leveraging mobile microlearning for continuing professional development, and implementing efficient patient engagement tools, such as electronic health record prompts. These interventions align with Saudi Vision 2030’s focus on preventive healthcare, positioning dental professionals as advocates for systemic wellness through microbiome-informed care. Ultimately, bridging the knowledge-to-practice gap requires structured educational reforms, institutional support, and a reimagined role for dentistry in holistic health, enabling dental care in Saudi Arabia to effectively address both oral and systemic health.

Data availability

“The datasets used and/or analysed during the current study are available as supplementary files”.

References

Wade WG. Resilience of the oral Microbiome. Periodontol 2000. 2021;86:113–22. https://doi.org/10.1111/prd.12365.

Dewhirst FE, Chen T, Izard J, Paster BJ, Tanner ACR, Yu W-H, et al. The human oral Microbiome. J Bacteriol. 2010;192:5002–17. https://doi.org/10.1128/JB.00542-10.

Hajishengallis G. Periodontitis: from microbial immune subversion to systemic inflammation. Nat Rev Immunol. 2015;15:30–44. https://doi.org/10.1038/nri3785.

Dominy SS, Lynch C, Ermini F, Benedyk M, Marczyk A, Konradi A, et al. Porphyromonas gingivalis in alzheimer’s disease brains: evidence for disease causation and treatment with small-molecule inhibitors. Sci Adv. 2019;5:eaau3333. https://doi.org/10.1126/sciadv.aau3333.

Parveen S, Qahtani ASA, Halboub E, Hazzazi RAA, Madkhali IAH, Mughals AIH, et al. Periodontal-Systemic disease: A study on medical practitioners’ knowledge and practice. Int Dent J. 2023. https://doi.org/10.1016/j.identj.2023.05.003.

DeGruttola AK, Low D, Mizoguchi A, Mizoguchi E. Current Understanding of dysbiosis in disease in human and animal models. Inflamm Bowel Dis. 2016;22:1137–50. https://doi.org/10.1097/MIB.0000000000000750.

Kitamoto S, Nagao-Kitamoto H, Hein R, Schmidt TM, Kamada N. The bacterial connection between the oral cavity and the gut diseases. J Dent Res. 2020;99:1021–9. https://doi.org/10.1177/0022034520924633.

Alhabeeb W, Elasfar A, Kinsara A, Aljizeeri A, Jelaidan I, Alghalayini K, et al. A Saudi heart association position statement on cardiovascular diseases and diabetes mellitus. J Saudi Heart Association. 2024;36. https://doi.org/10.37616/2212-5043.1407.

Parveen S, Alqahtani AS, Aljabri MY, Bajonaid A, Khan SS, Hassan, AA-HA-A, et al. Nationwide exploration: assessing oral Microbiome knowledge among dental professionals in Saudi Arabia and its implications for oral health care. BMC Oral Health. 2024;24:1028. https://doi.org/10.1186/s12903-024-04770-0.

Tonetti MS, Jepsen S, Jin L, Otomo-Corgel J. Impact of the global burden of periodontal diseases on health, nutrition and wellbeing of mankind: A call for global action. J Clin Periodontol. 2017;44:456–62. https://doi.org/10.1111/jcpe.12732.

Watt RG, Daly B, Allison P, Macpherson LMD, Venturelli R, Listl S, et al. Ending the neglect of global oral health: time for radical action. Lancet. 2019;394:261–72. https://doi.org/10.1016/S0140-6736(19)31133-X.

Bui FQ, Almeida-da-Silva CLC, Huynh B, Trinh A, Liu J, Woodward J, et al. Association between periodontal pathogens and systemic disease. Biomedical J. 2019;42:27–35. https://doi.org/10.1016/j.bj.2018.12.001.

Snibsøer AK, Ciliska D, Yost J, Graverholt B, Nortvedt MW, Riise T, et al. Self-reported and objectively assessed knowledge of evidence-based practice terminology among healthcare students: A cross-sectional study. PLoS ONE. 2018;13:e0200313. https://doi.org/10.1371/journal.pone.0200313.

Nie M, Gao ZY, Wu XY, Jiang CX, Du JH. Evaluation of oral microbiology lab curriculum reform. BMC Med Educ. 2015;15:217. https://doi.org/10.1186/s12909-015-0497-9.

Firmstone VR, Elley KM, Skrybant MT, Fry-Smith A, Bayliss S, Torgerson CJ. Systematic review of the effectiveness of continuing dental professional development on learning, behavior, or patient outcomes. J Dent Educ. 2013;77:300–15.

Poluektova O, Kappas A, Smith C. Using bandura’s Self-Efficacy theory to explain individual differences in the appraisal of Problem-Focused coping potential. Emot Rev. 2023;15:175407392311643. https://doi.org/10.1177/17540739231164367.

Kamışlı H, Özonur M. The effects of Training – Based on knowles’ adult education Principles – On participants. EURASIA J MATH SCI T. 2017;13. https://doi.org/10.12973/ejmste/80801.

Alkarimi HA, Jawadi A, Tayeb S, Ismail R, AlShareef EJ, Sherbini N. Implementing the child oral health initiative (COHI): improving access to preventive dental care to achieve Saudi vision 2030 healthcare goals. BMJ Open Qual. 2025;14. https://doi.org/10.1136/bmjoq-2024-003070.

Suleiman AK, Ming LC. Transforming healthcare: Saudi arabia’s vision 2030 healthcare model. J Pharm Policy Pract. 18:2449051. https://doi.org/10.1080/20523211.2024.2449051.

Meissner H, Creswell J, Klassen AC, Plano V, Smith KC. Best practices for mixed methods research in the health sciences. 2013. https://doi.org/10.1177/1473325013493540a.

Boateng GO, Neilands TB, Frongillo EA, Melgar-Quiñonez HR, Young SL. Best practices for developing and validating scales for health, social, and behavioral research: A primer. Front Public Health. 2018;6. https://doi.org/10.3389/fpubh.2018.00149.

Wilkes MS, Day FC, Fancher TL, McDermott H, Lehman E, Bell RA, et al. Increasing confidence and changing behaviors in primary care providers engaged in genetic counselling. BMC Med Educ. 2017;17:163. https://doi.org/10.1186/s12909-017-0982-4.

Borreani E, Wright D, Scambler S, Gallagher JE. Minimising barriers to dental care in older people. BMC Oral Health. 2008;8:7. https://doi.org/10.1186/1472-6831-8-7.

Mariño R, Giacaman RA. Patterns of use of oral health care services and barriers to dental care among ambulatory older Chilean. BMC Oral Health. 2017;17:38. https://doi.org/10.1186/s12903-016-0329-2.

Hamasha AA-H, Alghofaili N, Obaid A, Alhamdan M, Alotaibi A, Aleissa M et al. Social media utilization among dental practitioner in riyadh, Saudi Arabia. https://doi.org/10.2174/1874210601913010101.

Taşdemir Z, Alkan BA. Knowledge of medical doctors in Turkey about the relationship between periodontal disease and systemic health. Braz Oral Res. 2015;29:55. https://doi.org/10.1590/1807-3107BOR-2015.vol29.0055.

Manske S. Lifestyle medicine and the microbiome: holistic prevention and treatment. Integr Med (Encinitas). 2024;23:10–4.

Shubayr MA, Kruger E, Tennant M. Oral health providers’ views of oral health promotion in jazan, Saudi arabia: a qualitative study. BMC Health Serv Res. 2023;23:214. https://doi.org/10.1186/s12913-023-09170-8.

Duff J, Cullen L, Hanrahan K, Steelman V. Determinants of an evidence-based practice environment: an interpretive description. Implement Sci Commun. 2020;1:85. https://doi.org/10.1186/s43058-020-00070-0.

Merry L, Castiglione SA, Rouleau G, Létourneau D, Larue C, Deschênes M-F, et al. Continuing professional development (CPD) system development, implementation, evaluation and sustainability for healthcare professionals in low- and lower-middle-income countries: a rapid scoping review. BMC Med Educ. 2023;23:498. https://doi.org/10.1186/s12909-023-04427-6.

Forsetlund L, O’Brien MA, Forsén L, Mwai L, Reinar LM, Okwen MP, et al. Continuing education meetings and workshops: effects on professional practice and healthcare outcomes. Cochrane Database Syst Rev. 2021;2021:CD003030. https://doi.org/10.1002/14651858.CD003030.pub3.