Abstract
Introduction
Teledentistry is an innovative health care delivery platform that can potentially improve oral health access and outcomes. The purpose of this study was to predict teledentistry utilization intentions of U.S. adults using the Unified Theory of Acceptance and Use of Technology (UTAUT) as a framework.
Methods
This mixed-method, cross-sectional study surveyed 899 participants from two independent samples in August and September 2021. Convenience samples of Minnesota State Fair attendees and ResearchMatch volunteers completed electronic surveys to identify the behavioral intention (BI) for teledentistry use within the next 6 months. Independent variables were the UTAUT constructs of performance expectancy (PE), effort expectancy (EE), social influence (SI), and facilitating conditions (FC). Data were analyzed using univariate analysis and multiple linear regression adjusting for age, gender and educational level. Qualitative analysis used thematic analysis using UTAUT as a coding framework.
Results
Univariate analysis showed statistical significance between each construct with BI (P < 0.0001). Adjusted multiple linear regression revealed statistical significance between PE and SI with BI (P < 0.0001). Qualitative responses corroborated quantitative results and revealed a lack of teledentistry knowledge.
Conclusion
The majority of participants indicated an intention not to use teledentistry within the next 6 months. The lack of prior experience of telehealth or teledentistry use in addition to lack of knowledge regarding teledentistry may contribute to these results. Future interventions to improve the BI to use teledentistry may benefit from focusing on PE and SI constructs for educational and marketing strategies.
Keywords
Introduction
Telehealth is playing an increasing role in health care delivery as it continues to make significant contributions to health care advancements, enhanced communication between patients and providers, and the expansion of care to previously unassisted populations.1–3 Telehealth became critical during the COVID-19 pandemic as health care systems were challenged to create innovative solutions for providing care, triggering an expansion of related services including teledentistry.1,4–6 Teledentistry has the capability to expedite patient care for services such as risk assessments, triage, treatment planning, and remote management for dental care delivery.7,8 Providing dental care via teledentistry in dental health professional shortage areas (DPHSAs) holds promise for reaching patients who experience barriers to dental care access. However, accessing health care services virtually is not without barriers as technology use and acceptance have been identified for both telehealth and teledentistry services.4,7,9–14
Research conducted to explain factors affecting technology acceptance specific to users’ behavioral intent to use telehealth have applied the Unified Theory of Acceptance and Use of Technology (UTAUT). This theory posits that behavioral intent (BI) is impacted by four constructs: performance expectancy (PE), effort expectancy (EE), social influence (SI), and facilitating conditions (FC).15–17 The following operational definitions were used to define the constructs: PE is the degree to which a participant believes that using the teledentistry system will help the individual attain gains in job performance; EE is the degree to which a participant believes that ease is associated with use of a teledentistry system; SI is the degree to which a participant perceives that others (e.g. physician, dentist, specialist) believe he/she/they should use the teledentistry system; FC is the degree to which a participant believes that the organizational and technical infrastructures exist to support using a teledentistry system; BI is the degree to which a participant intends to use a teledentistry system; and teledentistry was defined as the use of telecommunication devices (e.g. video calls on a cell phone or computer) to facilitate dental exams and services when the patient is in one location and the dentist is in another location.1,15
Measuring patients’ intent to use teledentistry is important for designing targeted interventions to address barriers to this new model of oral health care access. As few studies have measured the behavioral intent of patients to use teledentistry, the purpose of this study was to identify the intention of United States adults to use teledentistry within a 6-month period using the UTAUT as a framework.
Methods
This cross-sectional study was approved by the University of Minnesota Institutional Review Board (STUDY00012797).
Sample
Convenience sampling was used to recruit participants from two sources: Minnesota State Fair adult attendees and ResearchMatch, an online healthy volunteer resource. Inclusion criteria for study participation were age 18 years or older, ability to provide consent, and the ability to complete the survey in English. Data were collected during August and September 2021. Face-to-face recruitment was used at the 2021 Minnesota State Fair at the University of Minnesota Driven to Discover (D2D) research facility. Participants entering the facility and verbally agreeing to complete the survey were provided an electronic tablet containing the informed consent document and survey. Recruitment via ResearchMatch differed as initial contact was through an email to enrollees expressing willingness to participate in online research studies. Interested participants were then sent a link to the survey instrument that included an informed consent document.
Incentives for State Fair participants included a backpack containing oral health products. ResearchMatch participants had the option to enter a lottery for one of three $50 internet gift cards. Patient identification information was stored separately from survey data in the university-approved cloud-based duo-authenticated storage system.
Instrument
The survey instrument was distributed via REDCap software using REDCap electronic data capture tools hosted at the University of Minnesota 18 and provided definitions of telehealth and teledentistry. The initial questions assessed familiarity with telehealth and teledentistry, and whether teledentistry had been utilized in the past 12 months. For those with teledentistry experience, branching logic directed participants to two additional questions: intention to use the services again and rating their experience on a 5-point Likert scale, ranging from Strongly Negative = 1 to Strongly Positive = 5.
The survey then proceeded to the UTAUT items, with 17 items addressing the five constructs in relation to teledentistry: four items asking about predicted perceptions of PE, three items for EE, three items for SI, four items for FC, and three items asking about predicted behavioral intent to use teledentistry (BI). For each of the 17 UTAUT items, possible answers were based on a 5-point Likert scale, ranging from Strongly Disagree = 1 to Strongly Agree = 5.
Four demographic items were also included: participant age in years, gender identification, education level, and zip code.
Theoretical framework
PE, EE, SI, and FC were considered independent variables, and behavioral intent (BI) to use teledentistry within the next 6 months was assigned as the dependent variable.
Modifications to the UTAUT construct items were made to reflect the methodology of the UTAUT questionnaire as suggested by Khatun et al. and to address telehealth and teledentistry as a whole, rather than on any specific telehealth platform(s).15,19 As the UTAUT items were modified from “telehealth” to “teledentistry,” the survey was piloted among a representative sample of 10 participants, including two University of Minnesota School of Dentistry faculty members and several individuals who are representative of the population of interest. Several small modifications were made based on participant feedback prior to finalizing the survey.
The null hypothesis tested was that there is no association between United States adults’ behavioral intent (BI) to use teledentistry services in the next 6 months and each of the UTAUT constructs of PE, EE, SI, and FC controlling for age, gender, and education level.
Data analysis
A power analysis determined a sample size of at least 776 participants assuming a small effect size (0.02 using Cohens’ F2) at 90% power with an alpha of P = 0.05. 20 Descriptive statistics for each sample and the total sample are reported using counts and proportions for categorical variables and means and standard deviations for continuous variables. Unadjusted univariate analysis compared the dependent variable (BI) with each of the four UTAUT constructs (PE, EE, SI and FC) as independent variables. Multiple linear regression was conducted controlling for the confounders of age, gender, educational level, and cohort (ResearchMatch or State Fair). A two-sided P-value < 0.05 was considered statistically significant. All quantitative analyses were conducted using R, version 4.1.1. 21
Qualitative analyses of open-ended items were conducted using thematic analysis within the UTAUT framework. Responses coded outside the framework generated potential new themes.
Results
The State Fair recruited 484 participants and ResearchMatch yielded 432 initiated surveys. After removing surveys that were incomplete, 483 remained from State Fair participants, and 416 from ResearchMatch, totaling 899 surveys available for analysis.
Table 1 shows participant demographics for each sample and total results. The mean age of the State Fair participants was almost 2 years older than ResearchMatch participants. The majority of participants identified as female with a greater proportion in the ResearchMatch group. The highest completed level of education was similar between the two samples, with most participants responding, “college degree or technical school graduation.”
Demographic characteristics of participants from State Fair and ResearchMatch (RM) samples.
Zip codes of all participants were mapped to indicate residence by state and county (Figures 1 and 2). All but six states were represented in the United States between the two samples, with the majority of participants residing in Minnesota. Further descriptive analyses of Minnesotan participants were mapped by county, with the majority of respondents residing within the seven-county Twin Cities metropolitan area (Figure 3) where the State Fair is located.
Number of participants by state for the total sample.
Number of participants by U.S. country for the total sample.
Number of participants by Minnesota county for the total sample.
Frequencies of the UTAUT item responses from the survey instrument are reported in Table 2. Similar response trends were noted for the four UTAUT construct items of PE, EE, SI, and FC between the two samples. While the majority of participants “agreed” with most items for the PE, EE, and FC constructs, a large percentage of “neutral” responses were noted for both samples. Two of the three SI construct items found the largest proportion of “neutral” responses for each sample. The number of participants in each sample who did not choose a response for each of the UTAUT items was between 0.0% and 2.3%, and therefore not included in Table 2.
Response frequencies of UTAUT construct items (PE, EE, SI, FC, BI) for State Fair and RM samples.
The largest discrepancy in responses between samples was for the BI construct as the majority of D2D participants responded to the three BI items with “neutral” (36.2%–40.4%) while a majority of ResearchMatch participants responded with “strongly disagree” (37.7%–38.2%).
Unadjusted univariate analysis found that each UTAUT construct reached statistical significance (<0.0001) with the dependent variable, BI (Table 3).
Unadjusted univariate analysis results of UTAUT constructs (PE, EE, SI, FC) with BI for State Fair and ResearchMatch samples.
Hypotheses testing
Table 4 displays multiple regression results controlling for age, gender, and educational level. The null hypothesis was rejected for an association between BI and the constructs of PE and SI, and accepted for the constructs of EE and FC.
Multiple regression analysis of UTAUT constructs (PE, EE, SI, FC) with BI for State Fair and RM samples.
As the survey instrument was altered for this study, Cronbach's alpha was calculated to measure internal consistency for each construct (Table 5). All constructs in the State Fair sample met or exceeded the established acceptable alpha level of 0.70; however, FC in the ResearchMatch sample was questionable (0.7 >
Cronbach's alpha for UTAUT construct items (PE, EE, SI, FC, BI) by study sample.
Qualitative analysis
Three open-ended survey items were included to elicit free-text responses to provide context and clarifying information to the quantitative results. Items were, “Provide any comments regarding your experience and/or concerns in using any form of telehealth or teledentistry for the delivery of your health care,” and the option to select “Other” as part of two multiple choice items, “What benefits do you believe teledentistry services provide?” and “What reason(s) impact why you might not use teledentistry services?”
In the State Fair sample, 59 participants provided a total of 76 responses to the open-response questions: 6 participants responded to two of the three questions, and 3 participants provided answers to all three questions. In the ResearchMatch sample, 137 participants provided a total of 205 responses: 32 of the participants provided responses to two of the questions and 3 participants provided responses to all three questions. Two study staff independently coded each response and indicated whether the response was positive or negative in regards to each UTAUT construct. All five UTAUT constructs were identified in addition to generating a new theme named “lack of knowledge.” Table 6 displays representative quotes for each theme.
Summary of qualitative responses by theme for total sample.
The most predominant theme was PE with responses centering on how the use of teledentistry could assist in consultations and communication with a dentist. Several participants recognized the role teledentistry plays in consultations and providing triage services, but also were concerned with missed dental findings and not as effective as in person associated with teledentistry use. The majority of comments coded as EE focused on the ease of use or convenience of teledentistry. The most infrequent comments were coded as SI, while FC garnered responses highlighting general internet access and reliability issues. Behavioral Intent comments emerged primarily as strong statements expressing either eagerness to no intention to use teledentistry.
The new theme of “lack of knowledge” included a wide scope of comments questioning how they could receive dental treatment remotely. Several responses also expressed uncertainty about the current location and availability of teledentistry offered in their geographic area, or if their dentist provides this service.
In summary, qualitative comments reinforced the quantitative findings in that “lack of knowledge” appeared to coincide with the high proportion of UTAUT items where participants provided a “neutral” response. While the qualitative data were minimal, the information gathered corroborated with the quantitative results.
Discussion
To the authors’ knowledge, this study is the first to report U.S. adults’ perceptions of teledentistry technology and behavioral intentions to utilize teledentistry. The majority of study participants expressed no BI to use teledentistry within the next 6 months as associated with the constructs of PE and SI. Open-ended comments supported the general lack of knowledge about the scope of services provided by teledentistry.
Our study results were not supported by other published results as no other studies reported the majority of participants not intending to use telehealth or teledentistry in the future. However, this may be due to sample selection as these studies surveyed groups with prior telehealth experience, and this study's sample consisted of 56% of participants with prior telehealth experience.
Sharma et al. surveyed dysphagia patients after using synchronous telerehabilitation and reported an increase in the intention to use telehealth services in the future. 23 Similarly, Rahman et al. reported 96% of teledentistry users would use it again. 7 It is worth noting that the Rahman et al. and the present study were conducted during the COVID-19 pandemic, which may have increased interest as many elective procedures were postponed and the concern for disease transmission kept many in self-isolation. 7
In partial support of this study's results, Triantafillou et al. found that patients who used synchronous visits for otolaryngology surgery consultations identified the benefit of triage and communication with providers offered with virtual communication but expressed concern with telehealth's appropriateness and effectiveness for a new patient visit. 6
In the present study, a preponderance of qualitative responses associated dentistry with hands-on procedures (e.g. fillings, crowns, dental cleanings) where teledentistry was not seen to have value. However, a small number of qualitative comments did highlight the use of telehealth and teledentistry for consultation purposes, which is supported by a retrospective study conducted by Crummey et al., who surveyed 100 patients following virtual consultation prior to oral surgery. 24 Patients reported high satisfaction rates with the ability to fully discuss and express their concerns. 24 Despite nearly half of these patients experiencing technical difficulties during the consultation, 93.5% reported that they would use a video consultation again. 24
Our results specific to the association of UTAUT constructs found associations between BI and both PE and SI when adjusting for age, gender, and education level. This varies from results reported by Khatun et al. where only FC was associated with BI in a study of patients using a cloud-based primary care service. 15 These differences may be due to the application of the UTAUT model to telehealth and teledentistry. Further studies are needed in both disciplines to elucidate potential differences.
Despite differences in the literature for which UTAUT constructs affect BI, BI has been a good representation of actual behavior.17,19,25 Technology use and acceptance will continue to be pinnacle for telehealth utilization and sustainability. Synchronous visits require that patients have internet capabilities and be able to operate and troubleshoot audiovisual components. While older adults have experienced technology-related issues due to disabilities or inexperience, research has noted that the more telehealth technology was utilized, the more positive patient perceptions were, which could be applied to any age group.26,27 Further studies are required to assess the intention to use teledentistry among participants with prior telehealth and teledentistry experience.
A strength of this study was the sample size that exceeded the minimum required to reach statistical significance. While the geographic location of participants was primarily in Minnesota, study recruitment allowed participation from the U.S. as a whole.
Limitations
Several limitations should be considered when viewing the study's results. Both samples used were convenience samples that limit the generalizability of findings. While participants were residents of most U.S. states, the participation was not representative of the nation as a whole. While the survey instrument used was found to have acceptable construct validity for most constructs, it was adapted from an existing instrument and has not been validated. The UTAUT model was not developed in a health care context but was used in this study and other studies to help explain end-user acceptance and utilization of telehealth platforms, including teledentistry.15–17
Conclusion
Since PE and SI were the strongest predictors of a participant's intention to use teledentistry, these data can be used to further develop teledentistry platforms. With the lack of knowledge identified in this study population, educational initiatives are required to increase the general public's knowledge of what teledentistry offers.
This study provides new directions for further investigation into the relationship between the Unified Theory of Acceptance and Use of Technology constructs and the intention of U.S. adults to use teledentistry services. Further investigation is required among participants with and without teledentistry experience to determine the strength of the UTAUT constructs to predict future intentions to use teledentistry.
Footnotes
Acknowledgements
Special thanks are extended to Dr Susan Buck-Wischmeier for her contributions to instrument development and data collection as well as the following State Fair volunteers: Monika Attia, Mahmoud Mire, Samidha Rajora, Emily Taras, and Aisa Zamani.
The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health's National Center for Advancing Translational Sciences. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Grant-In-Aid of Research, Artistry, and Scholarship program (GIA) from the Office of the Vice President for Research, University of Minnesota.
Declaration of conflicting interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Grant-In-Aid, Office of the Vice President for Research, University of Minnesota and the National Institutes of Health's National Center for Advancing Translational Sciences, grant UL1TR002494.
