Abstract
Purpose:
This study aims to examine the relationship between Google Trends (GT) data on orthodontics and oral hygiene terms from 2019, 2020, and 2021 and the gross domestic product (GDP) and population of cities in the Marmara Region.
Materials and methods:
GDP, population, and GDP per capita data for Turkiye and the Marmara Region were collected. Using GT, searches for orthodontics, brackets, clear aligners, orthodontic toothbrush, toothpaste, and tooth decay were analyzed for 2019–2021. GT values for Turkiye and Marmara cities were recorded. The Kruskal-Wallis test was used for group comparisons, followed by Dunn's test for identifying significant differences. Spearman's rho correlation analysis assessed relationships between parameters.
Results:
In 2021, the GT score for toothpaste was significantly higher than in 2019–2020 (p < 0.05). In 2019, clear aligner and tooth decay GT scores showed a positive, significant correlation with GDP (p < 0.05). In 2020 and 2021, braces, clear aligner, and tooth decay GT scores also correlated positively with GDP (p < 0.05). A consistent positive correlation between clear aligner and dental caries was observed across all three years (p < 0.05).
Conclusion:
GT data demonstrate its potential as a valuable tool for epidemiological research, digital data management, and evidence-based analysis. Findings suggest that individuals in higher GDP provinces are more likely to search for advanced orthodontic treatment, particularly clear aligners.
Keywords: Orthodontics, oral hygiene, dental caries, internet, population
Introduction
The correlation between orthodontic treatment and oral hygiene is significant, as maintaining proper oral hygiene plays a crucial role in the success and efficacy of orthodontic treatments (1). Orthodontic appliances, such as brackets or clear aligners, are used to align and straighten teeth. However, these appliances can also lead to an increased accumulation of plaque around the teeth, which can contribute to the build-up of pathogenic bacteria, raising the risk of tooth decay and periodontal diseases (2, 3). White spot lesions, an early sign of demineralization, may appear on tooth surfaces around orthodontic appliances, particularly in areas where oral hygiene is poor and plaque accumulates (4). Maintaining strict oral hygiene practices is essential during orthodontic treatment to minimize plaque accumulation and prevent oral health issues. Orthodontists can support their patients by recommending special oral care products, suchas orthodontic toothbrushes, dental floss, mouthwash, and fluoride-based toothpaste to ensure effective hygiene (5, 6, 7).
Access to oral health services, including orthodontic care, can be significantly influenced by an individual’s socioeconomic status. Those with higher income levels generally have greater access to costly dental procedures, including orthodontic treatments, while individuals with lower socioeconomic status may encounter challenges in receiving similar care (8). Socioeconomic factors such as income, education, and awareness of oral health often shape a person’s decision to pursue orthodontic treatment (9). Additionally, aesthetic concerns play a role in the choice of orthodontic method, with some patients preferring more discreet treatment options.
Among these treatment options, clear aligners have gained popularity due to their aesthetic appeal, as they are nearly invisible compared to traditional braces (10, 11). Clear aligners are customized to fit each patient’s unique dental structure and are designed to achieve the same goals as conventional orthodontic appliances. However, they often require a greater financial investment due to their individualized nature and shorter treatment time (10,12). While clear aligners offer advantages in comfort and discretion, the financial implications may limit accessibility for some patients.
Also, the use of special orthodontic and interdental toothbrushes in patients undergoing orthodontic treatment statistically considerably lowered the plaque index, according to the literature review (13). Proper oral hygiene and the use of fluoride toothpaste are the most important factors in the prevention of dental caries. Current studies revealed that those with lower levels of education or occupational status, as well as lower incomes, exhibited an increased susceptibility to caries lesions or dental decay (2, 3,5, 6). Also, previous studies have reported that people with lower socioeconomic status have poorer oral health than individuals with higher socioeconomic status. Socioeconomic status can be determined based on factors such as an individual’s degree of education, income, and place of residence (8, 9).
In today’s digital age, the Internet has become a vital resource for patients seeking information about orthodontic treatments. Dental professionals, including orthodontists, provide a wealth of educational materials via personal websites and health platforms, helping patients make informed decisions about their care (14, 15, 16). One tool that enables the monitoring of public interest in orthodontic and oral health-related topics is Google Trends (GT), a service provided by Google (U.S.). GT provides data on the quantity and frequency of searches conducted on Google for specific keywords or concepts (17). Users can observe the prevalence of a keyword in various areas, over different time periods, and on various devices. GT data can be filtered by time frame or geographical location, making it useful for analyzing patterns related to specific events or recurring trends (18, 19). In addition, GT provides information on keywords associated with a given search term, helping users explore related topics. This freely accessible service can be viewed via the website www.google.com/trends. GT allows users to track the popularity of specific keywords over time, providing valuable insights into public behavior and interest. It offers graphical representations and comparisons of search trends, helping researchers and clinicians analyze patterns in online searches (20, 21).
The null hypothesis of this study is that there is no significant correlation between Google Trends data on orthodontic and oral hygiene-related terms and socioeconomic indicators, including GDP, GDP per capita, and population values, in the Marmara Region for the years 2019, 2020, and 2021. This hypothesis assumes that public interest, as measured by online search behavior for these terms, is not influenced by the socioeconomic characteristics of the region. The study aims to examine the relationship between GT data for terms related to orthodontics and oral hygiene—including orthodontics, brackets, clear aligners, orthodontic toothbrush, toothpaste, and tooth decay—and socioeconomic indicators such as GDP, GDP per capita, and population values of cities in the Marmara Region for the years 2019, 2020, and 2021.
Materials and methods
Ethical statement
Only publicly available information was used in this study; therefore, ethics committee approval was not required.
Data collection
Google Trends data for this study was accessed on August 31, 2023. The pertinent search terms (orthodontics, brackets, clear aligners, orthodontic toothbrush, toothpaste, and tooth decay) were entered into the GT explore section. The region ‘Turkiye’ was selected, and this procedure was repeated for each word by selecting the years 2019, 2020, and 2021 in the custom dated search section.
Relative Search Volume (RSV) measures relative popularity on a scale from 0 to 100, with 100 representing the maximum relative popularity. Based on the search results, values were recorded for the whole of Turkiye and for each province in the Marmara Region (Istanbul, Tekirdag, Edirne, Kirklareli, Balikesir, Canakkale, Bursa, Bilecik, Sakarya, and Kocaeli). During the process of word search, it was determined that in some cities, this topic was not trending and had no value. These communities’ data were recorded as zero.
The socioeconomic data based on the GDP, population, and GDP per capita of Turkiye and the provinces in the Marmara region for the years 2019, 2020, and 2021 were obtained from the Turkish Statistical Institute’s official website (https:///data. tuik.gov. tr/bulten/index). It is important to note that the most recent GDP data available for this analysis was from 2019- 2021. Therefore, all socioeconomic comparisons and correlations in the study are based on the data from 2019-2021.
Statistical analysis
The statistical analyses in this study were performed using IBM SPSS Statistics 22 (IBM Corp., Armonk, NY, USA). Normality was assessed with the Kolmogorov-Smirnov test, which indicated that the parameters did not follow a normal distribution. For intergroup comparisons, the Kruskal-Wallis test was applied, and Dunn’s test was used to determine the specific group responsible for significant differences. Spearman’s rho correlation analysis was conducted to evaluate associations among the parameters. A p-value of <0.05 was considered statistically significant.
Results
When searching for ‘orthodontics’ in GT, the highest value was determined in Bilecik (100) in 2021. For the search ‘clear aligner’, the highest values were determined in Bursa (100) in 2019 and Istanbul (94) in 2021. The highest values for the search for ‘orthodontic toothbrush’ were determined in Istanbul (100) for all years, while there were no searches in other provinces of the Marmara Region. The search for ‘toothpaste’ was high in all provinces of the Marmara Region for all three years. The search for ‘tooth decay’ was highest in Bursa (100) in 2019, but the proportion of provinces with no searches was quite high (Table 1). There was a statistically significant difference between toothpaste GT scores by year (p<0.05). In 2021, toothpaste GT scores were significantly higher than in 2019 and 2020 (p<0.05). There was no statistically significant difference between 2019 and 2020 (Table 2). In year 2019; a significantly substantial positive correlation (76.8%, p < 0.05) was observed between GDP and the clear aligner. Also, there was a positive, (76.8%) and statistically significant correlation between GDP and tooth decay (p<0.05) (Table 3). There was a positive, (66.4%) and statistically significant correlation between GDP per capita and clear aligner. Also, there was a positive, (66.4%) and statistically significant correlation between GDP per capita and tooth decay (p<0.05) (Table 4). When examining the correlation between dental terminology based on GT data, there was a positive, (100%) and statistically significant correlation only between clear aligner and tooth decay (p<0.05) (Table 4). In year 2020, there was a positive, (68.2%) and statistically significant correlation between GDP and brackets/ clear aligners/tooth decay (p<0.05) (Table 4). When examining the correlation between dental terminology based on GT data, there was a positive, (100%) and statistically significant correlation only between clear aligner and tooth decay (p<0.05) (Table 4). In year 2021, there was a positive, (68.2%) and statistically significant correlation between GDP and brackets/clear aligners/tooth decay (p<0.05) (Table 5). When examining the correlation between dental terminology based on GT data, there was a positive, (64.3%) and statistically significant correlation between clear aligner and orthodontics (p<0.05). Also, there was a positive, (94.5%) and statistically significant correlation between clear aligner and tooth decay (p<0.05) (Table 5).
Table 1.
GDP, population, GDP per capita and GT value data of the provinces in the Marmara Region included in the study. GDP: Gross Domestic Product, GT: Google Trends
| City | Year | Gross Domestic Product (GDP) | Population | GDP per Capita | Orthodontics (GT Value) | Brackets (GT Value) | Clear Aligner (GT Value) | Orthodontic Toothbrush (GT Value) | Toothpaste (GT Value) | Tooth Decay (GT Value) |
|---|---|---|---|---|---|---|---|---|---|---|
| Turkiye | 2019 | 4.311.732.766 | 83.154.997 | 52.213 | 78 | 57 | 51 | 21 | 78 | 63 |
| 2020 | 5.048.220.067 | 83.614.362 | 60.541 | 64 | 62 | 52 | 18 | 82 | 70 | |
| 2021 | 7.248.788.983 | 84.680.273 | 86.144 | 78 | 62 | 56 | 15 | 74 | 70 | |
| Istanbul | 2019 | 1.324.090.706 | 15.519.267 | 86.579 | 77 | 48 | 83 | 100 | 82 | 83 |
| 2020 | 1.519.194.737 | 15.462.452 | 98.070 | 67 | 91 | 76 | 100 | 94 | 82 | |
| 2021 | 2.202.155.938 | 15.840.900 | 140.698 | 75 | 69 | 94 | 100 | 94 | 60 | |
| Tekirdag | 2019 | 73.774.749 | 1.055.412 | 70.756 | 54 | 33 | 0 | 0 | 43 | 0 |
| 2020 | 90.400.413 | 1.081.065 | 84.626 | 55 | 18 | 0 | 0 | 80 | 0 | |
| 2021 | 145.715.920 | 1.113.400 | 132.803 | 59 | 100 | 0 | 0 | 86 | 0 | |
| Edirne | 2019 | 18.186.660 | 413.903 | 44.066 | 73 | 0 | 0 | 0 | 84 | 0 |
| 2020 | 20.775.119 | 407.763 | 50.568 | 60 | 0 | 0 | 0 | 72 | 0 | |
| 2021 | 28.029.048 | 412.115 | 68.374 | 88 | 0 | 0 | 0 | 92 | 0 | |
| Kırklareli | 2019 | 20.654.402 | 361.836 | 57.159 | 55 | 0 | 0 | 0 | 91 | 0 |
| 2020 | 24.443.902 | 361.737 | 67.564 | 63 | 0 | 0 | 0 | 93 | 0 | |
| 2021 | 35.220.127 | 366.363 | 96.745 | 45 | 0 | 0 | 0 | 95 | 0 | |
| Balıkesir | 2019 | 54.225.630 | 1.228.620 | 44.172 | 67 | 0 | 0 | 0 | 79 | 0 |
| 2020 | 64.548.805 | 1.240.285 | 52.289 | 44 | 0 | 0 | 0 | 78 | 0 | |
| 2021 | 90.054.037 | 1.250.610 | 72.307 | 49 | 0 | 0 | 0 | 90 | 0 | |
| Canakkale | 2019 | 28.985.545 | 542.157 | 53.537 | 37 | 78 | 0 | 0 | 82 | 0 |
| 2020 | 37.575.427 | 541.548 | 69.346 | 64 | 52 | 0 | 0 | 79 | 0 | |
| 2021 | 49.142.315 | 557.276 | 89.445 | 53 | 67 | 0 | 0 | 87 | 0 | |
| Bursa | 2019 | 178.187.158 | 3.056.120 | 58.899 | 64 | 53 | 100 | 0 | 79 | 100 |
| 2020 | 203.645.989 | 3.101.833 | 66.141 | 59 | 81 | 85 | 0 | 77 | 88 | |
| 2021 | 302.120.912 | 3.147.818 | 96.684 | 67 | 67 | 92 | 0 | 87 | 53 | |
| Bilecik | 2019 | 12.610.109 | 219 427 | 56.947 | 92 | 0 | 0 | 0 | 80 | 0 |
| 2020 | 15.488.635 | 218 717 | 70.701 | 53 | 0 | 0 | 0 | 72 | 0 | |
| 2021 | 23.514.663 | 228 334 | 105.199 | 100 | 0 | 0 | 0 | 86 | 0 | |
| Sakarya | 2019 | 50.795.250 | 1.029.650 | 49.791 | 72 | 100 | 0 | 0 | 78 | 0 |
| 2020 | 59.882.221 | 1.042.649 | 57.793 | 56 | 94 | 0 | 0 | 80 | 0 | |
| 2021 | 81.740.233 | 1.060.876 | 77.717 | 44 | 77 | 0 | 0 | 75 | 0 | |
| Kocaeli | 2019 | 156.514.810 | 1.953.035 | 81.108 | 80 | 77 | 89 | 0 | 79 | 93 |
| 2020 | 190.845.001 | 1.997.258 | 49.791 | 79 | 100 | 63 | 0 | 82 | 81 | |
| 2021 | 309.313.454 | 2.033.441 | 43.639 | 80 | 99 | 68 | 0 | 87 | 77 |
Table 2.
Evaluation of GT data related to terms associated with the field of dentistry by analyzing the data over different years. Kruskal Wallis Test, SD: Standard Deviation, *p less than 0.05
| 2019 | 2020 | 2021 | |||||
|---|---|---|---|---|---|---|---|
| Min-Max | Mean±SD (median) | Min-Max | Mean±SD (median) | Min-Max | Mean±SD (median) | p | |
| Orthodontics | 37-92 | 67.1±15.6 (70) | 44-79 | 60±9.3 (59.5) | 44-100 | 66±19.3 (63) | 0.518 |
| Brackets | 0-100 | 38.9±38.1 (41) | 0-100 | 43.6±44.3 (35) | 0-100 | 47.9±42.8 (67) | 0.910 |
| Clear Aligner | 0-100 | 27.2±44 (0) | 0-85 | 22.4±36.4 (0) | 0-94 | 25.4±41.5 (0) | 0.947 |
| Orthodontic Toothbrush | 0-100 | 10±31.6 (0) | 0-100 | 10±31.6 (0) | 0-100 | 10±31.6 (0) | 1.000 |
| Toothpaste | 43-91 | 77.7±12.8 (80) | 72-94 | 80.7±7.5 (80) | 75-95 | 87.9±5.6 (87) | 0.022* |
| Tooth Decay | 0-100 | 27.6±44.6 (0) | 0-88 | 25.1±40.5 (0) | 0-77 | 19±31.1 (0) | 0.867 |
Table 3.
The correlation between the GDP and GDP per capita with data from the GT dataset focusing on the field of dentistry in the year 2019. Spearman’s rho correlation, test*p less than 0.05, GDP: Gross Domestic Product, GT: Google Trends
| 2019 | GDP | GDP per Capital | Orthodontics (GT Value) | Brackets (GT Value) | Clear Aligner (GT Value) | Orthodontic Toothbrush (GT Value) | Toothpaste (GT Value) | Tooth Decay (GT Value) | |
|---|---|---|---|---|---|---|---|---|---|
| Orthodontics | r | -0.042 | 0.115 | 1.000 | |||||
| p | 0.907 | 0.751 | . | ||||||
| Brackets | r | 0.444 | 0.244 | -0.163 | 1.000 | ||||
| p | 0.199 | 0.497 | 0.654 | . | |||||
| Clear Aligner | r | 0.768 | 0.664 | 0.276 | 0.362 | 1.000 | |||
| p | 0.009* | 0.036* | 0.440 | 0.305 | . | ||||
| Orthodontic Toothbrush | r | 0.522 | 0.522 | 0.290 | 0.060 | 0.357 | 1.000 | ||
| p | 0.122 | 0.122 | 0.416 | 0.870 | 0.311 | . | |||
| Toothpaste | r | -0.425 | -0.154 | 0.049 | -0.413 | -0.129 | 0.236 | 1.000 | |
| p | 0.221 | 0.671 | 0.893 | 0.236 | 0.723 | 0.512 | . | ||
| Tooth Decay | r | 0.768 | 0.664 | 0.276 | 0.362 | 1.000 | 0.357 | -0.129 | |
| p | 0.009* | 0.036* | 0.440 | 0.305 | 0.001* | 0.311 | 0.723 | 1.000 |
Table 4.
The correlation between the GDP and GDP per capita with data from the GT dataset focusing on the field of dentistry in the year 2020. Spearman’s rho correlation test, *p less than 0.05, GDP: Gross Domestic Product, GT: Google Trends
| 2020 | GDP | GDP per Capital | Orthodontics (GT Value) | Brackets (GT Value) | Clear Aligner (GT Value) | Orthodontic Toothbrush (GT Value) | Toothpaste (GT Value) | Tooth Decay (GT Value) | |
|---|---|---|---|---|---|---|---|---|---|
| Orthodontics | r | 0.321 | -0.067 | 1.000 | |||||
| p | 0.365 | 0.855 | . | ||||||
| Brackets | r | 0.682 | -0.088 | 0.544 | 1.000 | ||||
| p | 0.030* | 0.810 | 0.104 | . | |||||
| Clear Aligner | r | 0.798 | 0.022 | 0.485 | 0.608 | 1.000 | |||
| p | 0.006* | 0.951 | 0.156 | 0.062 | . | ||||
| Orthodontic Toothbrush | r | 0.522 | 0.522 | 0.406 | 0.299 | 0.500 | 1.000 | ||
| p | 0.122 | 0.122 | 0.244 | 0.401 | 0.141 | . | |||
| Toothpaste | r | 0.512 | 0.256 | 0.573 | 0.497 | 0.263 | 0.525 | 1.000 | |
| p | 0.130 | 0.475 | 0.083 | 0.144 | 0.464 | 0.119 | . | ||
| Tooth Decay | r | 0,798 | 0.022 | 0.485 | 0.608 | 1.000 | 0.500 | 0.263 | 1.000 |
| p | 0,006* | 0.951 | 0.156 | 0.062 | 0.001* | 0.141 | 0.464 | . |
Table 5.
The correlation between the GDP and GDP per capita with data from the GT dataset focusing on the field of dentistry in the year 2021. Spearman’s rho correlation test, *p less than 0.05, GDP: Gross Domestic Product, GT: Google Trends
| 2021 | GDP | GDP per Capital | Orthodontics (GT Value) | Brackets (GT Value) | Clear Aligner (GT Value) | Orthodontic Toothbrush (GT Value) | Toothpaste (GT Value) | Tooth Decay (GT Value) | |
|---|---|---|---|---|---|---|---|---|---|
| Orthodontics | r | -0.055 | 0.018 | 1.000 | |||||
| p | 0.881 | 0.960 | . | ||||||
| Brackets | r | 0.684 | 0.113 | -0.107 | 1.000 | ||||
| p | 0.029* | 0.756 | 0.769 | . | |||||
| Clear Aligner | r | 0.798 | 0.172 | 0.321 | 0.355 | 1.000 | |||
| p | 0.006* | 0.636 | 0.366 | 0.314 | . | ||||
| Orthodontic Toothbrush | r | 0.522 | 0.522 | 0.174 | 0.180 | 0.643 | 1.000 | ||
| p | 0.122 | 0.122 | 0.631 | 0.618 | 0.045* | . | |||
| Toothpaste | r | 0.068 | 0.012 | 0.025 | -0.481 | 0.250 | 0.412 | 1.000 | |
| p | 0.853 | 0.973 | 0.946 | 0.159 | 0.486 | 0.236 | . | ||
| Tooth Decay | r | 0.798 | -0.037 | 0.365 | 0.440 | 0.945 | 0.500 | 0.189 | 1.000 |
| p | 0.006* | 0.919 | 0.299 | 0.203 | 0.001* | 0.141 | 0.600 | . |
Discussion
The internet has become the primary source for patients seeking health-related information (22). Many individuals research orthodontic treatments, treatment costs, and doctor reviews online. The demand for orthodontic treatments continues to rise (19), prompting people to use search engines for information. In this study, Google Trends (GT) was utilized to track behavioral interests and analyze search volume data.
This study aimed to explore GT data on orthodontics and oral hygiene from 2019 to 2021, examining behavioral changes in the Marmara Region. This region was chosen for its socioeconomic diversity and dense population, encompassing metropolitan cities like Istanbul and smaller, rural provinces. Its economic significance, contributing substantially to Turkiye’s GDP, also made it a relevant study area.
GT data were collected for key search terms related to orthodontics and oral hygiene, including ‘orthodontics,’ ‘brackets,’ ‘clear aligners,’ ‘orthodontic toothbrush,’ ‘toothpaste,’ and ‘dental caries.’ These terms were selected based on their relevance to orthodontic treatment and oral health. Since the GT data did not follow a normal distribution, the Kruskal-Wallis test was applied, followed by Dunn’s post-hoc test to identify specific group differences. Spearman’s rho correlation was used to assess the relationship between GT search behavior and socioeconomic factors, given its suitability for non-normally distributed data and monotonic relationships.
The findings indicate widespread public interest in orthodontic treatment across all Marmara Region provinces, as reflected by searches for ‘orthodontics’ (10,19, 23, 24). The highest GT score for ‘orthodontics’ was recorded in Bilecik in 2021, demonstrating that interest extends to diverse socioeconomic areas.
Searches for ‘clear aligners’ exhibited notable trends, with peak scores in Bursa (2019) and Istanbul (2021). This suggests increasing interest in clear aligners, particularly in wealthier regions, aligning with studies showing that individuals with higher socioeconomic status prefer aesthetic orthodontic solutions due to their higher cost (10,11). Additionally, a significant positive correlation between GDP and clear aligner searches reinforces the influence of socioeconomic status on treatment choices (25). While no correlation was found between ‘orthodontics’ and socioeconomic level, a positive correlation emerged between GDP and searches for ‘braces’ and ‘clear aligners’ in 2020 and 2021. This suggests that as income levels rise in the Marmara Region, individuals tend to become more informed about orthodontic options and conduct more research.
Searches for ‘orthodontic toothbrush’ were predominantly from Istanbul, with minimal interest in other provinces. This suggests limited awareness of specialized oral hygiene tools outside urban centers, emphasizing the need for orthodontists to educate patients on proper oral hygiene during treatment (3,13). White spot lesions (WSLs), an early sign of demineralization, can appear within four weeks of fixed orthodontic treatment (25,26). Left untreated, WSLs progress to dental caries, a frequent issue during and after orthodontic treatment in patients with poor oral hygiene (13,27).
A key finding was the significant correlation between GDP and searches for ‘dental caries’ in 2019 and 2020. However, this does not imply a higher prevalence of dental caries in wealthier regions; rather, it reflects greater awareness and proactive information-seeking behavior among individuals with higher socioeconomic status (5, 6). As income levels rise, people tend to prioritize preventive oral health measures, such as regular brushing and flossing, which are crucial in both orthodontic treatment and dental caries prevention (3,28). Orthodontic appliances increase susceptibility to plaque accumulation, necessitating enhanced oral hygiene practices (9,12, 23).
Another significant finding was the positive correlation between GDP and searches for ‘brackets,’ ‘clear aligners,’ and ‘dental caries’ in 2020 and 2021. This underscores the role of socioeconomic status in shaping public interest in orthodontic treatment. Wealthier individuals are more likely to explore advanced treatment options and prioritize oral health during treatment. Across all three years, a significant positive correlation was observed between GDP and clear aligner searches, suggesting that rising income levels drive interest in orthodontic innovations. The demand for orthodontic treatment is expected to grow due to the increasing popularity and affordability of aesthetic and digital orthodontic techniques (23).
Orthodontic treatment is becoming more prevalent among adults compared to children. One of its primary drawbacks is the use of brackets. However, advancements in healthcare technology have addressed concerns related to treatment duration and aesthetics (23). Clear aligners, now a popular alternative, have contributed to increased orthodontic treatment demand among adults (11). While treatment with clear aligners is more expensive than brackets (24), patients researching clear aligners also tend to seek information about dental caries, indicating greater awareness of one of the most critical complications of orthodontic treatment.
A limitation of this study is the continuous updating of internet data, allowing only instantaneous or time-specific assessments. Socioeconomic data were obtained from the Turkish Statistical Institute for reliability, but GT measures relative popularity rather than depth of understanding. The most recent GDP data available were from 2019 to 2021, meaning all socioeconomic comparisons were based on this timeframe. Additionally, this study focused solely on the Marmara Region due to data management constraints. While expanding the study to all of Turkiye is technically possible, it would introduce significant complexity. Future research could benefit from incorporating updated data and analyzing different regions.
Conclusion
This study highlights the potential of Google Trends (GT) data as a valuable tool for analyzing public interest and trends in orthodontics and oral hygiene. However, GT has limitations, as it measures search volumes rather than users’ actual knowledge levels or intent. Despite these constraints, GT offers valuable insights for epidemiological research, digital data analysis, and evidence-based decision-making. The results suggest that individuals in higher GDP provinces are more likely to search for orthodontic advancements, such as clear aligners, indicating a link between socioeconomic status and interest in modern orthodontic treatments. Additionally, enhancing public awareness of orthodontic care and oral hygiene could contribute to improving overall oral health in the population.
Footnotes
Ethics committee approval: Not required.
Informed consent: Not required.
Peer review: Externally peer-reviewed.
Author contributions: HU, MTA participated in designing the study. HU participated in generating the data for the study. HU participated in gathering the data for the study. HU, MTA participated in the analysis of the data. HU wrote the majority of the original draft of the paper. HU participated in writing the paper. HU, MTA has had access to all of the raw data of the study. HU, MTA has reviewed the pertinent raw data on which the results and conclusions of this study are based. HU, MTA have approved the final version of this paper. HU guarantees that all individuals who meet the Journal’s authorship criteria are included as authors of this paper.
Conflict of interest:The authors declared that they have no conflict of interest.
Financial disclosure:The authors declared that they have received no financial support.
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