Travel Distance Research Articles

Dental care access for children in the United States.

To evaluate access to dental care for children in the United States. The study population included children in 48 states and the District of Columbia. Using multiple data sources, dental care access was estimated at the community level by matching dental care supply and demand using mathematical modeling accounting for access constraints. Outcome measures included percent-met demand, travel distance, and percentage of underserved and unserved communities. Multiple scenarios to improve Medicaid/CHIP participation of dentists were evaluated. Medicaid-insured and CHIP-insured children exhibited lower access compared to those privately insured. The percent-met demand was lower than 50% for Medicaid-insured children and CHIP-insured children for 42 and 34 states, respectively. Percent-met demand was higher than 50% for private-insured children except for Texas and West Virginia. Increasing Medicaid/CHIP participation of dentists resulted in improving access for public-insured children. At 100% Medicaid/CHIP participation, all states exhibited different degrees of percent-met demand increase for publicly insured children, from 7% to 46%. The percent-met demand across all children ranged in 23.8%-82.9% under 70% participation rate versus 22%-83% under 100% participation rate. No single participation rate improved access for all children uniformly across all states. This study found that dental care access was lower for children with public insurance than those with private access across all states, although states responded differently to changes in Medicaid/CHIP participation. Increasing access for children with public insurance would reduce disparities, but overall children's access to dental care would be better improved by expanding the oral health workforce.

Optimization of 3D Printing While Traveling En Route to Extend Range of Unmanned Aircraft Systems for Multilocation Mission Scenarios

Abstract The nexus of two relatively recent technologies, additive manufacturing and unmanned aircraft systems (UAS), has enabled new and unique capabilities that have only started to be realized in integrated systems. This article explores and quantifies the impact of 3D printing parts for UAS, or entire UAS systems, on an agent platform, while this agent travels to multiple locations as part of a mission objective. The fully printed or enhanced UAS can then be released at launch points farther away from the goal locations. This, in turn, can accelerate mission completion times and reduce travel costs depending upon the ratio between vehicle speed and 3D printing rate. Thousands of scenarios are optimized across the design space to minimize the travel path length for the agent platform as a result of 3D printing en route to the locations of interest. Results indicate that based on the print capability and agent travel speed, an exponential decay in the amount of travel distance of the agent platform occurs. For unity ratios of print speed and agent speed in the considered design space, a decrease of 55% in the total required distance of our agent is observed. This reduction in total travel distance can reduce time, fuel, cost, and other aspects including other environmental and social impacts. A generalized optimization formulation is also presented at the end to enable similar analyses with other en route range-extending technology such as battery charging.

Barriers and Attitudes towards Mental Health Services in Nigeria: A Systematic Review

Mental health services in Nigeria consists mainly of large government psychiatric hospitals. There are eight Neuropsychiatric hospitals and a similar number of teaching hospital psychiatric departments for a population of 200 million people. There is only one private community residential facility available with ten beds in Lagos State and it is administered by a religious organization for rehabilitation of persons with drug problems.In Nigeria, an estimated 20-30%of the population are believed to suffer from mental disorders.MEDLINE EntrezPubmed search was done in November, 2018. Studies conducted on mental health and mental health services in Nigeria done from 2009 till date were selected for review. The studies were grouped into two categories according to the key words used in the search. Category 1: Keywords used in the search: mental health,Nigeria.This search yielded a total of one thousand and fifty (1,051) publications. Category 2: Keywords used in the search: mental health services,Nigeria. Lack of incentives for health care workers and inadequate workforce were identified as some of the barriers against the use of mental health services in Nigeria. Other major barriers identified were- poor education, ignorance, and stigmatization. Absence of services in rural communities, waiting time at the facilities, bureaucracy in treatment and poor information management, high cost of service, travel distance, feelings of shame and loss of productive income were the barriers identified in some other studies conducted in Nigeria.

Municipal street‐sweeping area generation with route optimization

AbstractStreet sweeping is used in urban municipalities worldwide but requires a great deal of planning for large‐scale implementation. Municipalities typically make use of the macro‐ and microapproach by using operational areas in which routes are assigned, but creating operational areas without an understanding of the expected workload, number of routes, and the travel distance to and from the depot may lead to increased statistics. In this paper, a combination of heuristic approaches is used to assign street‐sweeping areas on the macroscale and generate street‐sweeping routes on the microscale. For the area assignment, a two‐stage cluster approach is proposed, making use of the weighted k‐means algorithm and differential evolution. For the route optimization, a three‐phase augment merge algorithm is used to create initial solutions, the u‐turns are minimized with a modified version of Hierholzer's algorithm and tabu search, and the remaining u‐turns are removed using a forward‐searching ant colony optimization. A case study in The City of Oshawa, Canada, was used to verify the proposed methodology, and all metrics were theoretically improved.

Views and opinions of patients with glaucoma and age-related macular degeneration on vision home-monitoring: a UK-based focus group study

ObjectiveTo investigate the views, hopes and concerns of patients living with glaucoma and age-related macular degeneration (AMD) regarding vision home-monitoring.DesignQualitative study using focus groups and questionnaires. Participants were given three...

Spatial Analysis of Advanced Air Mobility in Rural Healthcare Logistics

The transportation of patients in emergency medical situations, particularly in rural areas, often faces significant challenges due to long travel distances and limited access to healthcare facilities. These challenges can result in critical delays in medical care, adversely affecting patient outcomes. Addressing this issue is essential for improving survival rates and health outcomes in underserved regions. This study explored the potential of advanced air mobility to enhance emergency medical services by reducing patient transport times through the strategic placement of vertiports. Using North Dakota as a case study, the research developed a GIS-based optimization workflow to identify optimal vertiport locations that maximize time savings. The study highlighted the benefits of strategic vertiport placement at existing airports and hospital heliports to minimize community disruption and leverage underutilized infrastructure. A key finding was that the optimized mixed-mode routes could reduce patient transport times by up to 21.8 min compared with drive-only routes, significantly impacting emergency response efficiency. Additionally, the study revealed that more than 45% of the populated areas experienced reduced ground travel times due to the integration of vertiports, highlighting the strategic importance of vertiport placement in optimizing emergency medical services. The research also demonstrated the replicability of the GIS-based optimization model for other regions, offering valuable insights for policymakers and stakeholders in enhancing EMS through advanced air mobility solutions.

Optimizing the location of vaccination sites to stop a zoonotic epidemic

Mass vaccinations are crucial public health interventions for curbing infectious diseases. Canine rabies control relies on mass dog vaccination campaigns (MDVCs) that are held annually across the globe. Dog owners must bring their pets to fixed vaccination sites, but sometimes target coverage is not achieved due to low participation. Travel distance to vaccination sites is an important barrier to participation. We aimed to increase MDVC participation in silico by optimally placing fixed-point vaccination locations. We quantified participation probability based on walking distance to the nearest vaccination site using regression models fit to participation data collected over 4 years. We used computational recursive interchange techniques to optimally place fixed-point vaccination sites and compared predicted participation with these optimally placed vaccination sites to actual locations used in previous campaigns. Algorithms that minimized average walking distance or maximized expected participation provided the best solutions. Optimal vaccination placement is expected to increase participation by 7% and improve spatial evenness of coverage, resulting in fewer under-vaccinated pockets. However, unevenness in workload across sites remained. Our data-driven algorithm optimally places limited resources to increase overall vaccination participation and equity. Field evaluations are essential to assess effectiveness and evaluate potentially longer waiting queues resulting from increased participation.

Access to clinical genetic services: An evaluation of patient referral characteristics and identifying barriers in Michigan.

The utilization of genetics in medical care has enhanced the utility of precision medicine and hence increased the need for clinical genetic services. These services have reduced the costs and expanded the availability of genetic testing, but their use is limited in certain populations. This study explores the access to clinical genetic services for Michigan patients referred to a genetics clinic on the western side of the state. Factors included the travel distance (miles), wait time for appointment (days from the referral date to the date of first appointment), population demographics, and cultural characteristics. A retrospective record review of all aged patients (n = 568) referred to a genetics clinic in 2018 demonstrated that all patients were insured (100%), of which majority were white-non-Hispanic (90.7%), more than half were < 10 years of age at referral (53.3%), and most of them kept their first appointment (93.5%). Our analysis showed that the wait time was associated with referral non-compliance, p < 0.01. Adjusting for all variables, for each additional day in wait time, patients had 1% increased risk of not seeking clinical genetic services (OR = 1.01, 90% CI [1.01, 1.02]). Policies to encourage genetic service utilization and improve equitable access to precision health are needed. An opportunity exists for strategies that broaden and add diverse populations to those receiving genetic services.

The association of travel burden with prenatal care utilization, what happens after provider-selection

BackgroundBirthing people in the United States face numerous challenges when accessing adequate prenatal care (PNC), with transportation being a significant obstacle. Nevertheless, previous studies that relied solely on the distance to the nearest provider cannot differentiate the effects of travel burden on provider selection and care utilization. These may exaggerate the degree of inequality in access and fail to capture perceived travel burden. This study investigated whether travel distances to the initially visited provider, to the predominant PNC provider, and perceived travel burden (measured by the travel disadvantage index (TDI)) are associated with PNC utilization.MethodsA retrospective cohort of people with live births were identified from South Carolina Medicaid claims files in 2015–2018. Travel distances were calculated using Google Maps. The estimated TDI was derived from local pilot survey data. PNC utilization was measured by PNC initiation and frequency. Repeated measure logistic regression test was utilized for categorical variables and one-way repeated measures ANOVA for continuous variables. Unadjusted and adjusted ordinal logistic regressions with repeated measure were utilized to examine the association of travel burdens with PNC usage.ResultsFor 25,801 pregnancies among those continuously enrolled in Medicaid, birthing people traveled an average of 24.9 and 24.2 miles to their initial and predominant provider, respectively, with an average TDI of -11.4 (SD, 8.5). Of these pregnancies, 60% initiated PNC in the first trimester, with an average of 8 total visits. Compared to the specialties of initial providers, predominant providers were more likely to be OBGYN-related specialists (81.6% vs. 87.9%, p < .001) and midwives (3.5% vs. 4.3%, p < .001). Multiple regression analysis revealed that every doubling of travel distance was associated with less likelihood to initiate timely PNC (OR: 0.95, p < .001) and a lower visit frequency (OR: 0.85, p < .001), and every doubling of TDI was associated with less likelihood to initiate timely PNC (OR: 0.94, p = .04).ConclusionsFindings suggest that the association between travel burden and PNC utilization was statistically significant but of limited practical significance.

Nonlinear Relationship of Multi-Source Land Use Features with Temporal Travel Distances at Subway Station Level: Empirical Study from Xi’an City

The operation of the subway system necessitates a comprehensive understanding of passenger flow characteristics at station locations, as well as a keen awareness of the average travel distances at these stations. Moreover, the travel distances at the station level bear a direct relationship with the built environment composed of land use characteristics within the station’s catchment area. To this end, we selected the land use features within an 800 m radius of the station (land use area, distribution of points of interest, and the surrounding living environment) as the influencing factors, with the travel distances at peak hours on the subway network in Xi’an as the research subject. An improved SSA-XGBOOST-SHAP interpretable machine learning framework was established. The research findings demonstrate that the proposed enhanced model outperforms traditional machine learning or linear regression methods in terms of R-squared, MAE, and RMSE. Furthermore, the distance from the city center, road network density, the number of public transit routes, and the land use mix have a pronounced influence on travel distances, reflecting the significant impact that mature built environments can have on passenger attraction. Additionally, the analysis reveals a notable nonlinear relationship and threshold effect between the built environment variables comprising land use and the travel distances during peak hours. The research results provide data-driven support for operational strategy management and line capacity optimization, as well as theoretical underpinnings for enhancing the efficiency and sustainability of the entire subway system.

Efficiency enhancement in waste management through GIS-based route optimization

Due to rapid urbanization and uncontrolled population growth, solid waste management has become a rising issue in developing nations like Bangladesh. Khulna ranks third among Bangladesh's metropolitan cities. The existing system of Khulna City for transporting municipal solid waste lacks route planning and depends exclusively on the driver's expertise. Hence, this study aims to minimize the length of the present travel paths and assess the advantages of using optimized routes. Secondary datasets like a list of vehicles, financial information, and a list of secondary transfer stations have been collected from the municipality. A field survey was conducted to capture the coordinates of secondary transfer stations. Multiple GPS devices have been installed for monitoring the current paths, stops, and travel time of 31 waste collector vehicles for 10 months. A network database has been prepared and modified by integrating driver's perceptions and field inspection. Network analysis of ArcGIS Pro has been used for finding the optimized routes. The optimized route minimizes the travel distance by 9.40%. By following the optimized routes, about 11.6% of fuel costs can be reduced. This research has the potential to make a significant contribution to the waste management of Khulna City and beyond.

Multi-strategy cooperative scheduling for airport specialized vehicles based on digital twins

Efficient specialized vehicle cooperative scheduling is significant for airport operations, particularly during times of high traffic, which reduces the risk of flight delays and increases customer satisfaction. In this paper,we construct a multi-type vehicles collaborative scheduling model with the objectives of minimizing vehicle travel distance and vehicle waiting time. Additionally, a three-layer genetic algorithm is designed, and the crossover and mutation operations are enhanced to address the scheduling model. Due to the numerous uncertainties and stochastic interferences in airport operations, conventional scheduling methods unable to effectively address these challenges, this paper combines improved genetic algorithm, simulation algorithm, and digital twins technology, proposing a multi-strategy scheduling framework for specialized vehicles based on digital twins. The scheduling framework utilises digital twins to capture dynamic data from the airport and continuously adjusts the scheduling plan through the scheduling strategy to ensure robust scheduling for specialized vehicles. In the event of severe delays at the airport, fast and efficient re-scheduling can be achieved. Finally, the effectiveness of the proposed scheduling framework is validated using domestic flight data, and extensive experiments and analyses are conducted in different scenarios. This research contributes to addressing the optimization problem of cooperative scheduling for multi-type vehicles at airports.

A two-stage game-theoretical framework for Pricing & Management problem of shared mobility in a competitive market

ABSTRACT With the global proliferation of shared mobility systems, the vehicle-sharing market has witnessed an influx of companies and investors, thereby intensifying competition and potentially leading to suboptimal decision-making. Consequently, there is a pressing need for a modelling framework that specifically addresses operational and strategic-level policy design for multiple vehicle-sharing companies in a competitive market. In this study, we develop a two-stage game-theoretical framework to simulate the competitive process between multiple vehicle-sharing companies, facilitating their business decisions regarding pricing and management (P&M) problem, where management mainly include service area design, vehicle deployment, redirecting, and rebalancing. In the first stage of the framework, two companies operating under the same shared mobility service form a strategic alliance to compete against another vehicle-sharing service. Subsequently, in the second stage, these two companies engage in competition to maximise their individual profits. Based on the factors such as generalised travel cost, average acceptance level and vehicle availability, the competition process of each stage is formulated as a generalised Nash equilibrium problem. A linearisation method is employed for solving the equilibrium solution. Finally, we apply our proposed models to various vehicle-sharing systems and application scenarios to demonstrate their applicability. The numerical results illustrate that our model assists companies in making rational management decisions amidst intense competition while also revealing market competition landscape of vehicle-sharing systems based on different travel distances in the shared mobility market.

Social and built environmental factors associated with adult asthma hospital admission in the North Central Texas

Asthma, one of the most common chronic diseases of adults and children, is an important public health concern. The cause of asthma is thought to be a combination of genetic and environmental factors, and a growing body of research has investigated the possible geographic and contextual factors that contribute to asthma prevalence. However, few studies have incorporated geographic and environmental variables into their designs, despite evidence that geography is associated with asthma exacerbation. Additionally, studies of asthma exacerbations among adults are limited. The situation regarding asthma is particularly concerning in North Central Texas (NCT) compared to the national context. In light of this, we analyzed the geographic variation of approximately 12,000 adult patients hospitalized for asthma in the North Central Texas Region, and their association with built environmental features such as land use types, dwelling characteristics, exposure to traffic parameters at the Census Block Group (CBG) level, and pollutant concentrations in the relevant counties for the year 2014. We applied the Hierarchical Linear Model (HLM), and our analysis indicates that there are significant health disparities in the region. We found that the adult asthma hospitalization rate is significantly higher in low-income, low-education neighborhoods with a significant Black population. Furthermore, factors such as increased travel distance to work and substandard dwelling conditions have been found to trigger an increase in hospital visits for asthma patients. Conversely, the presence of greenspace in the surrounding area has been found to help reduce the frequency of asthma-related hospital visits. It is worth noting that both indoor and outdoor environmental quality contribute to adult asthma hospitalizations. Overall, our study highlights the importance of considering geographic and environmental factors in understanding the prevalence and exacerbation of asthma. Our findings suggest that targeted interventions, such as improving indoor and outdoor environmental quality and increasing access to greenspace, may help reduce the burden of asthma in high-risk communities.

The influence of travel time on perceived traveled distance varies by spatiotemporal scale

The influence of travel time on perceived traveled distance has often been studied, but the results are inconsistent regarding the relationship between the two magnitudes. We argue that this is due to differences in the lengths of investigated travel distances and hypothesize that the influence of travel time differs for rather short compared to rather long traveled distances. We tested this hypothesis in a virtual environment presented on a desktop as well as through a head-mounted display. Our results show that, for longer distances, more travel time leads to longer perceived distance, while we do not find an influence of travel time on shorter distances. The presentation through an HMD vs. desktop only influenced distance judgments in the short distance condition. These results are in line with the idea that the influence of travel time varies by the length of the traveled distance, and provide insights on the question of how distance perception in path integration studies is affected by travel time, thereby resolving inconsistencies reported in previous studies.

Understanding the large role of long-distance travel in carbon emissions from passenger travel

Long-distance passenger travel has received rather sparse attention for decarbonization. Here we characterize the long-distance travel pattern in England and explore its importance on carbon emissions from and decarbonization of passenger travel. We find that only 2.7% of a person’s trips are for long distance travel (>50 miles one-way), but they account for 61.3% of the miles and 69.3% of the greenhouse gas (CO2 equivalent) emissions from passenger travel, highlighting its importance for decarbonizing passenger transport. Long-distance travel per person has also been increasing over time, trending in the opposite direction to shorter-distance travel. Flying for leisure and social purposes are the largest contributors to long distance miles and emissions, and these miles are also increasing. Overall, per capita travel emissions have started decreasing slowly from 2007, but are still higher than in 1997. We propose a new metric—emissions reduction sensitivity (% emission reduced/% trips altered)—to understand the efficiency of travel demand related initiatives to reduce greenhouse gas emissions. Long-distance travel—especially flying—can offer orders of magnitude larger emissions reduction sensitivity compared with urban travel, which suggests that a proportionate policy approach is necessary.

An Estimation Method for Passenger Flow Volumes from and to Bus Stops Based on Land Use Elements: An Experimental Study

To unravel the general relationship between bus travel and land use around bus stops and along bus routes and to promote their coordinated development, this paper explores a method to estimate passenger flow volumes from and to bus stops based on land use types, intensities, and spatial distributions around bus stops and along bus routes. Firstly, following the principle of the gravity model, which considers traffic volumes analogous to gravity based on trip generation and distance impedance between traffic analysis zones (TAZs), a gravitational logic estimation method for passenger flow volumes from and to bus stops was constructed with land use elements between bus stop TAZs and the upstream and downstream collections of bus stop TAZs. Building upon this, the passenger flow volumes from and to 38 bus stops in the Xueyuan Square area of Dalian during weekday morning peak hours were taken as the experimental objects. The basic estimation models of two gravity sets corresponding to passenger flow volumes from and to bus stops were constructed using the bus travel generation based on the aggregation of area-based origin unit method and the bus travel distance impedance based on the probability density method. Finally, the reliability of the estimation method of passenger flow volumes from and to bus stops was verified by regression fitting between the surveyed values of passenger flow volume and the estimated values of the basic models. The results indicate that the fuzzy estimation and transformation of bus travel based on land use elements, which serves as a crucial lever for facilitating strategic alignment in transit-oriented development (TOD), can be effectively achieved by using the area-based origin unit method to aggregate bus travel generation and the probability density method to evaluate the bus travel distance impedance.

The impact of travel distance in patient outcomes following revascularization for chronic limb-threatening ischemia

BackgroundPatient travel distance to the hospital is a key metric of individual and social disadvantage and its impact on the management and outcomes following intervention for chronic limb-threatening ischemia (CLTI) is likely underestimated. We sought to evaluate the effect of travel distance on outcomes in patients undergoing first-time lower extremity revascularization at our institution. MethodsWe retrospectively reviewed all consecutive patients undergoing first-time lower extremity revascularization, both endovascular and open, for CLTI from 2005 to 2014. Patients were stratified into 2 groups based on travel distance from home to hospital greater than or less than 30 miles. Outcomes included reintervention, major amputation, restenosis, primary patency, wound healing, length of stay, length of follow-up and mortality. Kaplan-Meier estimates were used to determine event rates. Logistic and cox regression was used to evaluate for an independent association between travel distance and these outcomes. ResultsOf the 1293 patients were identified, 38% traveled >30 miles. Patients with longer travel distances were younger (70 years vs 73 years; P = .001), more likely to undergo open revascularization (65% vs 41%; P < .001), and had similar Wound, Ischemia, foot Infection stages (P = .404). Longer distance travelled was associated with an increase in total hospital length of stay (9.6 days vs 8.6 days; P = .031) and shorter total duration of postoperative follow-up (2.1 years vs 3.0 years; P = .001). At 5 years, there was no definitive difference in the rate of restenosis (hzard ratio [HR], 1.3; 95% confidence interval [CI], 0.91-1.9; P = .155) or reintervention (HR, 1.4; 95% CI, 0.96-2.1; P = .065), but longer travel distance was associated with an increased rate of major amputation (HR, 2.1; 95% CI, 1.2-3.7; P = .011), and death (HR, 1.6; 95% CI, 1.2-2.2; P = .002). Longer travel distance was also associated with higher rate of nonhealing wounds (HR, 2.3; 95% CI, 1.5-3.5; P = .001). ConclusionsLonger patient travel distance was found to be associated with a lower likelihood of limb salvage and survival in patients undergoing first-time lower extremity revascularization for CLTI. Understanding and addressing the barriers to discharge, need for multidisciplinary follow-up, and appropriate postoperative wound care management will be key in improving outcomes at tertiary care regional specialty centers.

Geographic Access to Pediatric Orthopedic Surgeons in the United States: An Analysis of Sociodemographic Factors.

It is unclear how pediatric orthopedic surgeons are geographically distributed relative to their patients. The purpose of this study was to evaluate the geographic distribution of pediatric orthopedic surgeons in the United States. County-level data of actively practicing pediatric orthopedic surgeons were identified by matching several registries and membership logs. Data were used to calculate the distance between counties and nearest surgeon. Counties were categorized as "surgeon clusters" or "surgeon deserts" if the distance to the nearest surgeon was less than or greater than the national average and the average of all neighboring counties, respectively. Cohorts were then compared for differences in population characteristics using data obtained from the 2020 American Community Survey. A total of 1197 unique pediatric orthopedic surgeons were identified. The mean distance to the nearest pediatric orthopedic surgeon for a patient residing in a surgeon desert or a surgeon cluster was 141.9±53.8 miles and 30.9±16.0 miles, respectively. Surgeon deserts were found to have lower median household incomes (P<.001) and greater rates of children without health insurance (P<.001). Multivariate analyses showed that higher Rural-Urban Continuum codes (P<.001), Area Deprivation Index scores (P<.001), and percentage of patients without health insurance (P<.001) all independently required significantly greater travel distances to see a pediatric orthopedic surgeon. Pediatric orthopedic surgeons are not equally distributed in the United States, and many counties are not optimally served. Additional studies are needed to identify the relationship between travel distances and patient outcomes and how geographic inequalities can be minimized. [Orthopedics. 2024;47(4):e204-e210.].

Patient considerations for orthodontists: A comparative study of university students in Malaysia and Taiwan

Background/purposePatients' considerations when choosing an orthodontist are influenced by many factors, including background, ethnicity, and location. Accordingly, this study aimed to identify factors influencing patients’ considerations when selecting an orthodontist in both Malaysia and Taiwan. Materials and methodsIn total, 248 dental students from Taipei Medical University and 110 dental students from Manipal University College Malaysia were selected for this study. Participants' considerations when selecting an orthodontist were assessed using a questionnaire survey. The questionnaire collected data regarding participants’ demographic characteristics and their preferences regarding clinical settings, orthodontist attributes, administrative systems, and the influence of social media. The gathered data were analyzed and compared using independent t-test, ANOVA, and chi-squared for both cohorts. ResultsThe present results revealed significant differences between the Malaysian and Taiwanese participants with several variables, including orthodontist experience, recommendations, pain-free treatment procedures, treatment duration, friendly reception, sources of information about orthodontists, and preferred social media platforms. Notably, among the Taiwanese participants, “person responsible for treatment costs,” was significantly correlated with the orthodontist's age, the orthodontist's work experience, information sources, travel distance, and content posted by orthodontists on social media. By contrast, among the Malaysian participants, this variable was correlated with the work experience of orthodontists. ConclusionSignificant differences were observed between the Malaysian and Taiwanese participants in terms of their considerations when choosing an orthodontist. Participant's gender significantly influenced orthodontist preferences among the Malaysian participants, whereas the individual responsible for treatment costs was identified to be the most crucial factor influencing the Taiwanese participants.