Abstract
Introduction:
In recent years, patient preferences and attitudes have become crucial in shaping dental treatment choices and service utilization. Understanding these preferences is crucial for improving service delivery and patient satisfaction.
Aim:
This study aims to comprehensively analyze the factors influencing these preferences, focusing on demographic, socio-economic, and behavioral variables, and the growing role of social media in healthcare decisions.
Methodology:
A cross-sectional survey using an online questionnaire was conducted among Indian individuals aged 18 years and above, yielding 231 responses. The data were analyzed using descriptive statistics, Chi-square tests, and ANOVA to assess associations and significant differences among variables. Factor analysis was used to determine factors influencing the selection of dental care services.
Results:
The findings suggest that younger adults (76.6% aged 18–43 years) and females (65.8%) are more engaged in digital consultations and dental care decisions. Key factors influencing dental care choices include previous experience, painless treatment, and availability. Trust in social media for dental information is low, with 72.7% expressing doubts about its accuracy. Factor analysis identified four key dimensions affecting dental care choices which were grouped as patient-centric dental service quality, external validation and assurance, experience and cost-driven decisions, and professional competence.
Conclusion:
The study underscores the importance of maintaining high-quality service, effective communication, and leveraging professional referrals and online reviews to enhance patient trust and satisfaction. Despite social media’s rising role, direct professional advice remains the preferred source for dental care decisions.
Keywords: Dental care decision-making, dental care utilization, dental treatment choices, patient attitudes, social media influence
Résumé
Introduction:
Les préférences et attitudes des patients influencent de plus en plus les choix de traitement dentaire et l’utilisation des services de santé. Comprendre ces préférences est essentiel pour améliorer la qualité des services et la satisfaction des patients.
Objectif:
Cette étude vise à analyser les facteurs influençant ces préférences, en se concentrant sur les variables démographiques, socio-économiques et comportementales, ainsi que sur l’impact des réseaux sociaux dans les décisions de santé.
Méthodologie:
Une enquête transversale en ligne a été menée auprès d’Indiens âgés de 18 ans et plus, recueillant 231 réponses. Des statistiques descriptives, des tests du chi-carré et l’ANOVA ont été utilisés pour évaluer les associations et les différences significatives, tandis qu’une analyse factorielle a permis d’identifier les principaux facteurs influençant le choix des services de soins dentaires.
Résultats:
Les résultats indiquent que les jeunes adultes (76,6 % âgés de 18 à 43 ans) et les femmes (65,8 %) participent davantage aux consultations numériques et à la prise de décisions en matière de soins dentaires. Les principaux facteurs influençant le choix des soins dentaires comprennent les expériences antérieures, la prise en charge indolore et la disponibilité des services. La confiance dans les réseaux sociaux pour obtenir des informations dentaires est faible, avec 72,7 % exprimant des doutes quant à leur exactitude. L’analyse factorielle a identifié quatre principales dimensions influençant les choix dentaires : qualité de service centrée sur le patient, validation et assurance externes, décisions basées sur l’expérience et les coûts, et compétence professionnelle.
Conclusion:
L’étude souligne l’importance de maintenir des services de haute qualité, une communication efficace, et de tirer parti des recommandations professionnelles et des avis en ligne pour renforcer la confiance et la satisfaction des patients. Bien que les réseaux sociaux jouent un rôle croissant, le conseil direct des professionnels reste la source préférée pour les décisions en matière de soins dentaires.
Mots-clés: Prise de décision en matière de soins dentaires, utilisation des soins dentaires, choix de traitements dentaires, attitudes des patients, influence des médias sociaux
INTRODUCTION
Dentistry, as an essential component of overall health, has seen similar trends, where patient preferences and attitudes play a critical role in shaping their choices of dental treatments and facilities. The sector of dental care decision-making has evolved significantly in recent years, with patients becoming increasingly proactive in selecting their treatment options and care providers. Various factors, including demographic, behavioral, socioeconomic, cultural, and epidemiological influences, contribute to individuals’ decisions to either forgo care or seek professional assistance for dental problems.[1] Understanding these preferences is crucial for dental practitioners and policymakers aiming to improve service delivery and patient satisfaction.
Social media has emerged as a significant source of healthcare information and patients often turn to these platforms to gather information about dental treatments, compare facilities, and read about the experiences of others.[2] This shift toward digital consultation highlights the need for dental care providers to understand the dynamics of social media influence and its implications for patient engagement and service delivery.
This paper aims to explore how demographic factors, socioeconomic status, and the prevalence of digital literacy influence patient preferences and attitudes. By analyzing these variables, the study seeks to offer a comprehensive understanding of how patients choose their dental treatments and the extent to which social media affects these choices.
METHODOLOGY
Study participants and survey
This study employed a cross-sectional survey design using an online questionnaire distributed through Google Forms. A judgmental sampling technique was used, where participants are selected based on the researcher’s professional judgment. The survey was circulated through social media platforms - Facebook and WhatsApp and through direct interviews among acquaintances. The target population included Indian individuals aged 18 years and above who have access to social media or can be reached through WhatsApp and direct interviews. The data were collected after taking informed consent from participants, using a structured questionnaire developed following consultation with subject experts. Participants’ anonymity and confidentiality were maintained.
The questionnaire consisted of the following sections:
Demographic information
Dental visit history
Factors influencing dental care service selection: Participants’ ratings of various factors influencing their choice of dental care services, for which responses were collected on a 5-point Likert scale (strongly agree to strongly disagree)
Social media usage for dental care: Participants’ practices related to using social media for dental care information
Perceptions toward dental advertisements on social media: Ratings were done on a Likert scale (strongly agree to not at all agree).
Statistical analysis
The data were exported from Google Forms to a spreadsheet for preliminary review and cleaning. Statistical analysis was conducted using the Statistical Package for the Social Sciences (SPSS) for Windows (version 23; SPSS Inc., Chicago IL, USA). Descriptive statistics (e.g., frequencies, percentages, and means) were used to summarize the data. Chi-square tests were used to assess associations between demographic variables and responses. Likert scale responses were analyzed using ANOVA to identify significant differences. P < 0.05 was considered statistically significant.
RESULTS
A total of 231 responses were obtained from 412 individuals, giving a response rate of 56%. A significant portion of the respondents are young adults, with 76.6% aged between 18 and 43 years, suggesting that youngsters are more engaged or accessible through online surveys. There is a higher participation rate among females (65.8%) compared to males (34.2%). The baseline characteristics of the study population are summarized in Table 1.
Table 1.
Baseline characteristics of the survey participants
| Category | Particulars | Frequency (%) |
|---|---|---|
| Age group (years) | 18–30 | 85 (36.8) |
| 31–43 | 92 (39.8) | |
| 44–56 | 36 (15.6) | |
| >56 | 18 (7.8) | |
| Gender | Male | 79 (34.2) |
| Female | 152 (65.8) | |
| Education group | Up to 10th class | 11 (4.8) |
| Up to 12th class | 34 (14.7) | |
| Undergraduate | 131 (56.7) | |
| Postgraduate | 55 (23.8) | |
| Occupation group | Self employed | 6 (2.6) |
| Government employee | 49 (21.2) | |
| Private sector employee | 81 (35.1) | |
| Professional | 43 (18.6) | |
| Student | 20 (8.7) | |
| Unemployed | 32 (13.9) | |
| Income group | Up to Rs. 5000 | 57 (24.7) |
| Rs. 5001–20,000 | 70 (30.3) | |
| Rs. 20,001–50,000 | 31 (13.4) | |
| Rs. 50,001–75,000 | 21 (9.1) | |
| More than Rs. 75,000 | 52 (22.5) | |
| Dental visit history | None in the last 2 years | 54 (23.4) |
| Once in the last 2 years | 107 (46.3) | |
| More than once in the last 2 years | 70 (30.3) | |
| Type of dental setting visited | Government | 39 (16.9) |
| Private | 104 (45.0) | |
| Both | 88 (38.1) |
Source: Survey data
The frequency of dental visits is significantly related to the age of the participants, education, occupation, and monthly income, and there is no significant gender difference related to the variable. The type of dental setting visited is significantly influenced by income, education, and occupation of the participants.
However, on ANOVA analysis, there were no significant differences for dental visit history among the various income groups of respondents (P > 0.05), but among various age groups (P = 0.009), education (P = 0.003), and occupation (P = 0.002) categories of respondents [Table 2].
Table 2.
Correlation between demographic characteristics and dental visit
| Factor | χ 2 | df | P | Sum of squares (between groups) | df (between) | Mean square (between) | F | Significant value |
|---|---|---|---|---|---|---|---|---|
| Dental visit history | ||||||||
| Income | 25.299 | 8 | 0.001 | 4.007 | 4 | 1.002 | 1.904 | 0.111 |
| Education | 48.813 | 6 | 0.000 | 7.294 | 3 | 2.431 | 4.775 | 0.003 |
| Occupation | 25.127 | 10 | 0.005 | 10.130 | 5 | 2.026 | 4.042 | 0.002 |
| Gender | 1.362 | 2 | 0.506 | 0.385 | 1 | 0.385 | 0.719 | 0.397 |
| Age | 22.509 | 6 | 0.001 | 6.063 | 3 | 2.021 | 3.927 | 0.009 |
| Type of dental setting usually visited | ||||||||
| Income | 56.459 | 8 | 0.000 | 2.473 | 4 | 0.618 | 1.224 | 0.301 |
| Education | 48.137 | 6 | 0.000 | 9.237 | 3 | 3.079 | 6.510 | 0.000 |
| Occupation | 47.919 | 10 | 0.000 | 6.474 | 5 | 1.295 | 2.645 | 0.024 |
Source: Survey data
Factors influencing dental care selection
The top three factors are previous experience (94% either strongly agree or agree), painless treatment (86.5% either strongly agree or agree), and availability (93.1% either strongly agree or agree). The reputation of the dentist/clinic, word of mouth, and expertise of the dentist are also highly valued, with over 90% of respondents agreeing or strongly agreeing on their importance. Interpersonal communication skills and staff behavior are similarly important, with around 95% of respondents agreeing or strongly agreeing on their significance. Online reviews have mixed importance, with only 42% agreeing or strongly agreeing. Dental insurance was a decisive factor for only 38% of respondents [Table 3].
Table 3.
Responses regarding factors influencing dental care selection
| Factors | Strongly agree, n (%) | Agree, n (%) | Not sure, n (%) | Disagree, n (%) | Strongly disagree, n (%) |
|---|---|---|---|---|---|
| Reputation about dentist/dental clinic | 124 (53.7) | 87 (37.7) | 7 (3.0) | 13 (5.6) | - |
| Word of mouth | 120 (51.9) | 93 (40.3) | 2 (0.9) | 14 (6.1) | 2 (0.9) |
| Previous experience | 157 (68.0) | 60 (26.0) | 7 (3.0) | 7 (3.0) | - |
| Affordability | 120 (51.9) | 89 (38.5) | 15 (6.5) | 4 (1.7) | 3 (1.3) |
| Expertise of the dentist | 137 (59.3) | 80 (34.6) | 8 (3.5) | 6 (2.6) | - |
| Specialization | 118 (51.1) | 52 (22.5) | 35 (15.2) | 21 (9.1) | 5 (2.2) |
| Interpersonal communication skills | 138 (59.7) | 72 (31.2) | 18 (7.8) | 3 (1.3) | - |
| Staff behavior | 137 (59.3) | 82 (35.5) | 9 (3.9) | 3 (1.3) | - |
| Accessibility | 125 (54.1) | 91 (39.4) | 3 (1.3) | 12 (5.2) | - |
| Availability | 142 (61.5) | 73 (31.6) | 14 (6.1) | 2 (0.9) | - |
| Professional referral | 71 (30.7) | 69 (29.9) | 66 (28.6) | 22 (9.5) | 3 (1.3) |
| Painless treatment | 150 (64.9) | 50 (21.6) | 17 (7.4) | 9 (3.9) | 5 (2.2) |
| Insurance | 62 (26.8) | 27 (11.7) | 74 (32.0) | 37 (16.0) | 31 (13.4) |
| Ambience of the clinic | 102 (44.2) | 98 (42.4) | 15 (6.5) | 10 (4.3) | 6 (2.6) |
| Facilities of the clinic | 106 (45.9) | 89 (38.5) | 22 (9.5) | 9 (3.9) | 5 (2.2) |
| Waiting time | 116 (50.2) | 85 (36.8) | 20 (8.7) | 5 (2.2) | 5 (2.2) |
| Online review | 54 (23.4) | 43 (18.6) | 49 (21.2) | 21 (9.1) | 64 (27.7) |
Source: Survey data
Determining the factors influencing the selection of dental care service using principal component analysis
In this study, we applied the Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy and Bartlett’s test of sphericity to assess the appropriateness of the data for factor analysis. The KMO value was 0.797, indicating good adequacy, and Bartlett’s test of sphericity was highly significant (P < 0.001), confirming that the sample was suitable for factor analysis. In addition, we examined the communalities for each variable by principal component analysis, and the results are summarized in Table 4.
Table 4.
Communality values of all variables
| Factor number | Factors | Initial | Extraction |
|---|---|---|---|
| F1 | Reputation about dentist/dental clinic | 1.000 | 0.465 |
| F2 | Word of mouth | 1.000 | 0.482 |
| F3 | Previous experience | 1.000 | 0.668 |
| F4 | Affordability | 1.000 | 0.554 |
| F5 | Expertise of the dentist | 1.000 | 0.745 |
| F6 | Specialization | 1.000 | 0.797 |
| F7 | Interpersonal communication skills of the dentist | 1.000 | 0.723 |
| F8 | Staff behavior | 1.000 | 0.670 |
| F9 | Accessibility | 1.000 | 0.553 |
| F10 | Availability | 1.000 | 0.733 |
| F11 | Professional referral | 1.000 | 0.649 |
| F12 | Painless treatment | 1.000 | 0.628 |
| F13 | Insurance | 1.000 | 0.580 |
| F14 | Ambience of the clinic | 1.000 | 0.704 |
| F15 | Facilities of the clinic | 1.000 | 0.753 |
| F16 | Waiting time | 1.000 | 0.741 |
| F17 | Online review | 1.000 | 0.706 |
Source: Survey data. Extraction method: Principal component analysis
The four factors that accounted for a cumulative variance of 65.603% of the total variance were extracted. The eigenvalues and the percentage of variance explained by each factor are shown in Table 5.
Table 5.
Explanation of total variance
| Component | Initial Eigenvalues |
Extraction sums of squared loadings |
Rotation sums of squared loadings |
||||||
|---|---|---|---|---|---|---|---|---|---|
| Total | Percentage of variance | Cumulative (%) | Total | Percentage of variance | Cumulative (%) | Total | Percentage of variance | Cumulative (%) | |
| F1 | 6.454 | 37.965 | 37.965 | 6.454 | 37.965 | 37.965 | 4.565 | 26.853 | 26.853 |
| F2 | 2.222 | 13.073 | 51.038 | 2.222 | 13.073 | 51.038 | 3.104 | 18.257 | 45.110 |
| F3 | 1.384 | 8.141 | 59.179 | 1.384 | 8.141 | 59.179 | 1.802 | 10.599 | 55.709 |
| F4 | 1.092 | 6.424 | 65.603 | 1.092 | 6.424 | 65.603 | 1.682 | 9.894 | 65.603 |
| F5 | 0.881 | 5.179 | 70.783 | ||||||
| F6 | 0.832 | 4.895 | 75.678 | ||||||
| F7 | 0.765 | 4.503 | 80.181 | ||||||
| F8 | 0.651 | 3.827 | 84.007 | ||||||
| F9 | 0.568 | 3.342 | 87.350 | ||||||
| F10 | 0.469 | 2.762 | 90.111 | ||||||
| F11 | 0.424 | 2.492 | 92.604 | ||||||
| F12 | 0.308 | 1.811 | 94.414 | ||||||
| F13 | 0.280 | 1.644 | 96.058 | ||||||
| F14 | 0.259 | 1.524 | 97.582 | ||||||
| F15 | 0.156 | 0.918 | 98.500 | ||||||
| F16 | 0.148 | 0.869 | 99.369 | ||||||
| F17 | 0.107 | 0.631 | 100.000 | ||||||
Source: Survey data. Extraction method: Principal component analysis
The rotated component matrix, using Varimax rotation, revealed the following loadings for each factor [Table 6]. All the four factors have been given appropriate names on the basis of the variables represented in each case.
Table 6.
Rotated component matrix
| Factor number | Factors | Component |
|||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | ||
| F10 | Availability | 0.834 | |||
| F8 | Staff behavior | 0.787 | |||
| F12 | Painless treatment | 0.745 | |||
| F7 | Interpersonal communication skills of the dentist | 0.735 | |||
| F16 | Waiting time | 0.707 | |||
| F14 | Ambience of the clinic | 0.683 | |||
| F15 | Facilities of the clinic | 0.664 | |||
| F9 | Accessibility | 0.660 | |||
| F17 | Online review | 0.826 | |||
| F13 | Insurance | 0.725 | |||
| F11 | Professional referral | 0.659 | |||
| F3 | Previous experience | 0.780 | |||
| F4 | Affordability | 0.698 | |||
| F2 | Word of mouth | 0.514 | |||
| F5 | Expertise of the dentist | 0.790 | |||
| F6 | Specialization | 0.697 | |||
Source: Survey data. Extraction method: Principal component analysis. Rotation method: Varimax with Kaiser normalization
Based on the rotated component matrix, the factors were interpreted and named as follows:
Patient-centric dental service quality (Factor 1): Explains 26.853% of the variance availability, staff behavior, painless treatment, interpersonal communication skills of the dentist, waiting time, the ambience of the clinic, facilities of the clinic, and accessibility
External validation and assurance (Factor 2): Explains 18.257% of the variance - online review, insurance, and professional referral
Experience and cost-driven decision (Factor 3): Explains 10.599% of the variance - previous experience, affordability, and word of mouth
Professional competence (Factor 4): Explains 9.894% of the variance - expertise of the dentist and specialization.
Practices related to social media usage for dental care
The study revealed that a significant majority (64.1%) of individuals regularly use social media sites, with 43.3% relying on these platforms to gather information related to dental treatments. However, despite this usage, only 21.2% have considered or opted for a specific dental treatment based on what they saw on social media. There is a notable concern about the accuracy and reliability of dental treatment information on social media, with 72.7% expressing doubts. Furthermore, only 11.3% have discussed social media content with their dentist, suggesting limited influence on professional consultations. Importantly, a large majority (87.4%) prefer to receive dental care recommendations directly from their dentist rather than relying on social media sources [Figure 1].
Figure 1.
Responses on practices related to social media usage for dental care
Perception toward dental advertisements through social media
A significant portion of respondents believe that online reviews and social media presence influence their perception of dentists, with 57.6% interested in exploring online reviews and 42.8% agreeing that a dentist’s social media presence affects their treatment decisions. However, trust in social media for dental care information is low, with 60.2% disagreeing that they trust specific social media platforms or accounts for such information [Table 7].
Table 7.
Responses for patient’s perception toward dental advertisements through social media
| Perceptions | Strongly agree, n (%) | Agree, n (%) | Not sure, n (%) | Disagree, n (%) | Strongly disagree, n (%) |
|---|---|---|---|---|---|
| Helps to increase awareness of the qualifications of dentist | 64 (27.7) | 69 (29.9) | 28 (12.1) | 45 (19.5) | 25 (10.8) |
| Interested in exploring online reviews of dentists and dental clinics | 64 (27.7) | 64 (27.7) | 27 (11.7) | 41 (17.7) | 35 (15.2) |
| A dentist’s social media presence influences my treatment decisions | 65 (28.1) | 34 (14.7) | 35 (15.2) | 61 (26.4) | 36 (15.6) |
| A dental clinic can survive today’s commercial climate without advertising | 44 (19.0) | 57 (24.7) | 54 (23.4) | 50 (21.6) | 26 (11.3) |
| Social media significantly shapes societal beauty standards, including dental esthetics | 59 (25.5) | 65 (28.1) | 26 (11.3) | 47 (20.3) | 34 (14.7) |
| The costs of managing social media would be passed on to patients’ increasing treatment cost | 57 (24.7) | 68 (29.4) | 57 (24.7) | 33 (14.3) | 16 (6.9) |
| I trust specific social media platforms or accounts for dental care information | 39 (16.9) | 26 (11.3) | 27 (11.7) | 45 (19.5) | 94 (40.7) |
Source: Survey data
DISCUSSION
The survey predominantly engaged young adults (76.6% aged 18–43 years), suggesting that younger individuals are more likely to participate in online surveys. This may reflect higher comfort levels with technology and greater online presence among this age group. A higher proportion of female respondents (65.8%) compared to males (34.2%) indicates that females may be more inclined to participate in surveys related to health or possibly have a greater interest in dental health topics. Given the high engagement of young adults and females, digital marketing, social media engagement, and educational content can be specifically designed for these groups. Our results are comparable with previous studies, showing that dental service utilization is higher among females than males and is influenced by sociodemographic factors such as age, education, and occupation.[1,3] With 56.7% undergraduates and 23.8% postgraduates, the respondent pool is highly educated, likely to have a better understanding of dental health, and dental care options, and possibly more critical evaluation of dental information sources. The survey’s diverse income distribution also influenced varying dental care affordability, with higher income respondents having greater access to services and lower income respondents being more cost-conscious. Globally, disparities in dental care utilization and oral health outcomes are influenced by factors such as education, income, occupation, and social class.[4]
The analysis of factors influencing dental treatment choices reveals several key dimensions that significantly impact patient attitudes and decisions. These dimensions have been categorized based on their correlation and the percentage of variation they explain, providing a comprehensive understanding of what drives patients to choose particular dental services.
Patient-centric dental service quality: This category encompasses factors such as the availability of the dentist, staff behavior, painless treatment, interpersonal communication skills of the dentist, waiting time, clinic ambience, facilities, and accessibility. Collectively, these factors create a holistic patient experience that significantly affects treatment choices. Positive interactions and effective communication between the staff, dentists, and patients help build trust and comfort.[5] A clean, welcoming clinic with modern facilities not only enhances patient satisfaction but also reflects the clinic’s commitment to high-quality care. Accessing dental care in rural and remote regions poses significant challenges, often requiring long-distance travel and substantial time investment. Many studies consistently highlight accessibility and limited availability as primary obstacles to timely oral health care in many areas.[6] Finally, ensuring painless treatment is vital. By reducing pain and discomfort during procedures, dental clinics can significantly improve the patient experience, encouraging regular visits and fostering long-term loyalty.
External validation and assurance factors: This dimension includes factors such as online reviews, insurance coverage, and professional referrals. Positive online reviews and recommendations from trusted professionals[7] can significantly influence a patient’s decision to choose a particular dental service. In addition, having insurance coverage can alleviate financial concerns, making it easier for patients to commit to necessary treatments. Similar to our results, a previous study showed poor awareness regarding the dental benefits covered in health insurance plans, despite a positive attitude toward implementing dental insurance in India.[8]
Experience and cost-driven decision factors: This category covers previous experience, affordability, and word-of-mouth recommendations. One of the most frequently cited reasons for seeking treatment from public hospitals is the affordability of the services.[6] A positive previous experience can lead to repeat visits and referrals, while affordable services ensure that more patients can access necessary care. Word of mouth remains a powerful tool in attracting new patients, as personal stories and recommendations are often deemed highly trustworthy.
Professional competence and specialization: This dimension includes the expertise of the dentist and their specialization. Factors in the professional competence and specialization category are critical in determining patient confidence and trust in the dental care they receive.
The survey results reveal that social media plays a significant role in shaping patient perceptions of dental care. The majority of respondents believe that social media increases awareness of dentists’ qualifications and are interested in online reviews of dental clinics. However, opinions are divided on whether a dentist’s social media presence influences treatment decisions, and there is concern that the costs of managing a social media presence could increase treatment costs. In addition, while many agree that social media shapes societal beauty standards, there is a notable skepticism about the reliability of dental information on these platforms. These insights suggest that while an online presence is important, dental practices should ensure transparency and cost-effectiveness to build trust and maintain patient satisfaction.
CONCLUSION
Despite the prevalent use of social media, there is a clear preference for professional dental advice. Factors such as previous experience, painless treatment, and availability are paramount in dental care selection, whereas online reviews and social media influence are less critical. The findings suggest that dental professionals should focus on maintaining high-quality service and direct patient communication to build trust and influence treatment decisions effectively.
Conflicts of interest
There are no conflicts of interest.
Funding Statement
Nil.
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