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Dissertation Proposal and Dissertation Manuscript
Version: March 2019
© Northcentral University, 2019

Adoption of Telehealth Technology among Primary Care Providers Using TAM
Dissertation Proposal
Submitted to Northcentral University
School of Technology
in Partial Fulfillment of the
Requirements for the Degree of
DOCTOR OF PHILOSOPHY IN TECHNOLOGY AND INNOVATION MANAGEMENT
by
WENDY K. COLE-REED
San Diego, California
October, 2019
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Abstract
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Acknowledgements
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Table of Contents
Chapter 1: Introduction....................................................................................................................1
Statement of the Problem...........................................................................................................1
Purpose of the Study..................................................................................................................2
Theoretical or Conceptual Framework......................................................................................3
Nature of the Study....................................................................................................................3
Research Questions....................................................................................................................4
Hypotheses ................................................................................................................................4
Significance of the Study...........................................................................................................5
Definitions of Key Terms..........................................................................................................5
Summary....................................................................................................................................6
Chapter 2: Literature Review...........................................................................................................7
Theoretical/Conceptual Framework..........................................................................................7
Theme or Subtopic ....................................................................................................................8
Theme or Subtopic ....................................................................................................................8
Theme or Subtopic ....................................................................................................................8
Theme or Subtopic ....................................................................................................................8
Summary....................................................................................................................................8
Chapter 3: Research Method.........................................................................................................10
Research Methodology and Design.........................................................................................10
Population and Sample............................................................................................................10
Materials or Instrumentation....................................................................................................11
Operational Definitions of Variables ......................................................................................12
Study Procedures.....................................................................................................................12
Data Collection and Analysis..................................................................................................13
Assumptions ...........................................................................................................................14
Limitations...............................................................................................................................14
Delimitations............................................................................................................................14
Ethical Assurances...................................................................................................................14
Summary..................................................................................................................................15
Chapter 4: Findings........................................................................................................................16
XXX of the Data......................................................................................................................16
Results......................................................................................................................................17
Research question 1/hypothesis. Text…..................................................................................17
Evaluation of the Findings.......................................................................................................18
Summary..................................................................................................................................18
Chapter 5: Implications, Recommendations, and Conclusions.....................................................19
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Implications.............................................................................................................................19
Recommendations for Practice................................................................................................19
Recommendations for Future Research...................................................................................20
Conclusions..............................................................................................................................20
References......................................................................................................................................21
Appendices....................................................................................................................................22
Appendix A: XXX.........................................................................................................................23
Appendix B: XXX.........................................................................................................................24
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List of Tables
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List of Figures
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Chapter 1: Introduction
The delivery of healthcare has evolved in the 21st century to include and integrate
mainstream technology. U.S. hospitals are constantly acquiring technology to help improve their
patients’ outcomes. The American Hospital Association (AHA) reported over 36 million hospital
admissions in a 2017 survey (AHA, 2019). During a patient’s hospital stay, technology is
incorporated in their care in some way or another. Examples of technology currently in use in
hospitals are diagnostic technologies, surgical robots, Radio Frequency Identification (RFID) for
automatic data collection, patient safety preventive technology, documentation software, such as
electronic health records, inter-facility communication technologies, data acquisition, medical
devices, and mobile technology. These technologies allow access to patient records while not
physically at the facility, that assist primary care providers in making decisions on the most
appropriate intervention to prescribe to their patient (Alotaibi & Federico, 2017; Hemmat,
Ayatollahi, Maleki, & Saghafi, 2017; Caroline Free et al., 2013;Wen, Chao-Hsien, & Zang,
2010). Individually, these technologies offer significant improvement for the purpose of which
they were created. Collectively, they provide a primary care provider everything they need to
perform a complete assessment of their patients. Telehealth is comprised of a multitude of
technologies used in the hospital setting, but also includes smart clothing, education, patient
assessment tools, and patient portals. Without the use of such advanced technologies so easily
accessible, primary care providers would spend a vast amount of time searching for notes,
diagnostic results, executed interventions, and making decisions without necessary information
about their patients.
Community hospitals that utilize telehealth technology provides their local patient
population with a variety of health-related option. Some patients rely heavily on their community

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hospital to provide a holistic approach towards their healthcare because it is the only access they
have to healthcare (Bhatt & Bathija, 2018). Patients experience a number of issues when
attempting to seek medical attention. According to Taber, Leyva, & Persoskie (2015), patients
avoid medical care in part due to limited access to healthcare, not enough time to stop and seek
medical assistance, inconvenient clinic hours, transportation and distance issues, costs, failure to
see the provider, no or limited available childcare or eldercare, long wait times, issues with
making appointments, and not wanting to be around other sick people. These barriers lead to
declining conditions in the patients’ health. Strategists from AHA Task Force are continually
seeking ways to overcome these barriers in an attempt to improve patient outcomes (Bhatt &
Bathija, 2018).
To meet the needs of the community, it is vital to consider the adoption of virtual care (Bhatt &
Bathija, 2018). Telehealth addresses the barriers patients are burdened with that causes them to
avoid medical care (Bullen, Marshall, & Hughes, 2017). With all of the advantages that
telehealth provides, the rate of its implementation in U.S. hospitals remains low (Scott Kruse et
al., 2018; Spitzer, 2018). Due to multiple external barriers, such as healthcare laws, the
complexity of the technology, reimbursement of services rendered, and low community
reception of telehealth (Scott Kruse et al., 2018), providers are grappling with the adoption of
telehealth (Dinesen et al., 2016; Tuckson, Edmunds, & Hodgkins, 2017). Although
administrators of U.S. hospitals may undergo the costs to acquire the telehealth technology,
prescribing providers have not improved the rate of implementation of the technology. Adoption
of telehealth technology among providers may be influenced by several factors such as the high
cost of the technology, security concerns (Scott Kruse et al., 2018), the time it takes to learn and
integrate the new technology, and lack of organizational support (Yarbrough & Smith, 2007).

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The adoption of telehealth and telemedicine technology among physicians that intend to use the
technology is often studied through the use of the Technology Acceptance Model (TAM)
(Yarbrough & Smith, 2007; Gagnon et al., 2005; Gagnon et al., 2003; Hu et al., 1999). The use
of the TAM for this investigation will predict those factors that impact the adoption of telehealth
among primary care providers. Investigating what factors have a relationship to the adoption of
telehealth technology among prescribing providers may encourage hospital administrators to
create a successful program that addresses those factors (Gagnon et al., 2005).
Statement of the Problem
The implementation rates of the telehealth technology among primary care providers
depends on several factors, such as access to complete patient records, knowledge of how to use
telehealth technology, acceptance of telehealth technology, and amount of reimbursement of
services delivered through telehealth, with acceptance being one of the top factors (Gao, Li, &
Luo, 2015; Kramer, Kinn, & Mishkind, 2015; Schwamm, 2015). Telehealth allows patients
quick and easy access to medical care and has enabled primary care providers the chance to treat
their patients without a physical face-to-face interaction. The pace of the implementation of
telehealth has not been slow. Between the years 2013 and 2017, the American Hospital
Association (AHA) (2019) reported a mere 6% average yearly increase of telehealth
implementation among U.S. hospitals. Primary care providers’ reluctance to adopt telehealth was
noted as one of the attributing barriers of the low implementation rates of telehealth in U.S.
hospitals (Adler-Milstein, Kvedar, & Bates, 2014).
The slow acceptance of the technology among primary care providers may have a direct
effect on the future delivery of healthcare. As Davis, Bagozzi, & Warshaw (1989) pointed out,
user acceptance is key to manufacturers developing advanced technology, as the users have not

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yet experienced the use of the product. Primary care providers struggle more with acceptance of
the technology than with the delivery of healthcare used with telehealth technology (Neville,
2018). As a result, the recipients of the technology do not get the possible benefits of the
innovative technology, leading to undesirable outcomes such as extended hospital stays,
increased hospital costs, and increased complications related to delays in seeking medical
attention (Ramsey, Lord, Torrey, Marsch, & Lardiere, 2016; Thimbleby, 2013). The specific
problem this research will address is the low acceptance rate of telehealth technologies among
primary care providers that work in a community hospital setting within the United States (Harst,
Lantzsch, & Scheibe, 2019; Ford, Hesse, & Huerta, 2016; Lee & Coughlin, 2015).

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Purpose of the Study
The purpose of this quantitative correlational study is to identify the factors that influence
the low acceptance rate of telehealth technologies among primary care providers that work in
community hospitals within the United States. Quantitative studies are used to determine if a
relationship exists between variables and outcomes; assessing the correlation implies the use of
statistical determination (Rutberg & Bouikidis, 2018). The population of this study includes
primary care providers within the United States, which includes medical professionals who can
diagnose patients and provide a treatment plan like medical physicians, physicians’ assistant, and
nurse practitioners, as well as primary care providers that work in a medical facility, and actively
practice in the United States of America. Convenience sampling and Google Forms will be used
for the collection of structured data. The Excel spreadsheet program will be used to organize,
retain, and export the data to a statistical analytics software, SPSS. The appropriate sample size
of 74 was obtained using G*Power software (Faul, Erdfelder, Buchner, & Lang, 2009). The
dependent variable in this study is the behavioral intention to use telehealth technology. The
independent variables are defined as perceived usefulness, perceived ease of use, and
organizational support for telehealth training. SPSS v25 will be utilized to complete the analysis
of the collected data. The aim of the study is to provide insights into the low acceptance of
telehealth among primary care providers. The results of the research study aim to provide
community hospitals within the United States an understanding of the factors associated with the
acceptance of telehealth among primary care providers, which affect the implementation rates of
telehealth within the community hospital (Yarbrough & Smith, 2007).
Theoretical Framework

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Part of the reason for the slow implementation rate of telehealth in hospitals in the United
States is low levels of acceptance among end users and their resistance to accept telehealth
technology (Loera, 2008). Past research studies, such as those done by Rawstorne, Jayasuriya, &
Caputi, (2000) and Davis et al. (1989), have identified that the failure to accept technology is a
barrier to the acceptance of technology among general end users. Hu, Chau, Sheng, & Tam
(1999) identified that the failure to accept technology is a barrier to the acceptance of telehealth
among physicians. The acceptance of technology is frequently used as the basis for the
theoretical framework in many healthcare research studies regarding the adoption of technology
(Bettiga, Lamberti, & Lettieri, 2019; Lemay, Morin, Bazelais, & Doleck, 2018; Tubaishat, 2018;
Neo, Park, Lee, Soh, & Oh, 2015). Users have struggled with their intention to use new
technology based on a variety of contributing factors such as performance acceptance, effort
expectancy, which is the degree of ease associated with the use of the system (Venkatesh et al.,
2003), social influence, and facilitating conditions, such as the amount of guidance or instruction
provided by an organization or specific training for a specific technology, as explained by
Venkatesh et al. (2003). Studies regarding the investigation of the relationship of the attitudes of
end users towards acceptance of healthcare-related technology to the intent to use technology
have been successful in creating useful adoption of technology models (Cruz-Benito, Sánchez-
Prieto, Therón, García-Peñalvo, 2019; Poellhuber, Fournier St-Laurent, & Roy, 2018; Weng, F.,
Yang, R., Ho, H., & Su, H., 2018). TAM (Technology Acceptance Model) was introduced in
1989 by Davis et al. The model focused on the introduction of new technology to end users and
their preparedness to accept the new technology. The model included two factors that affected
the acceptance of new technology among end users; perceived usefulness (PU) and perceived
ease-of-use (PEOU). PU explains the belief the user has about how useful the technology would

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be for them and PEOU explains the belief the user has about the least amount of effort required
to use the technology (Davis 1989). The TAM is the theoretical framework used for this study to
statistically determine the factors that affect primary care providers’ decision to adopt telehealth
technology in hospitals in the United States.
Nature of the Study
This research study involves investigating the factors that influence the adoption of
telehealth technology among primary care providers that are employed by community hospitals
in the United States. The identification of predicting factors is done by ascertaining if there is a
statistical significant relationship between variables to explain human behavior (Wicherts et al.,
2016). In alignment with the purpose of this study, the quantitative methodology was selected
because it entails the testing of a theory and involves the use of surveys to provide statistical
answers to the research questions (Salvador, 2016; Williams, 2007). A correlational design was
selected to determine the factors that influence the acceptance of telehealth technology among
primary care providers in community hospitals within the U.S. The proposed correlational
research design involves testing hypotheses using numerical data and establishing the degree of
their relationship (Quaranta, 2017). Correlation analysis is useful when seeking to investigate the
relationship between variables (Hummel-Rossi, McIlwain, & Mattis, Academic, 2006). The
design will identify the factors that most strongly predict the intent to use telehealth technology
among primary care providers. The use of TAM has been mentioned as a good model to use to
determine the relationship of factors that impact primary care providers’ behavioral intent to use
telehealth technology (Rho, Choi, & Lee, 2014; Chau & Hu, 2002).
An online survey administration app (Google Forms) will be used to collect survey
completed by primary care providers within the United States. The population of this study

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includes primary care providers that are employed by community hospitals within the United
States. The questions on the survey that are used to identify the acceptance of telehealth
technology among the primary care providers are derived from the original TAM instrument
used in Davis’ 1989 study. The survey instrument has been successfully used in other studies that
sought to investigate physicians’ acceptance of telehealth technology (Yarbrough & Smith, 2007;
Whitten, Doolittle, & Mackert, 2005).
Research Questions
This study aimed to identify the factors influencing U.S. community hospital primary
care providers’ adoption of telehealth technology. The following research questions were based
on the Technology Acceptance (TAM) Framework, which includes the users’ perceived
usefulness and perceived ease of use and organizational support, with a focus on training,
obtained from Marler, Liang, and Dulebohn’s 2006 study:
RQ1. Is there a statistically significant association between perceived ease of use of
telehealth technology, perceived usefulness, and organizational support for training of telehealth
technology and the intent to use telehealth technology among primary care providers that work in
community hospitals within the United States?
Hypotheses
H10. There is no statistically significant association between perceived ease of use of
telehealth technology, perceived usefulness, and organizational support for training of telehealth
technology and the intent to use telehealth technology among primary care providers that work in
community hospitals within the United States.

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H1a. There is a statistically significant association between perceived ease of use of
telehealth technology, perceived usefulness, and organizational support for training of telehealth
technology and the intent to use telehealth technology among primary care providers that work in
community hospitals within the United States.
Significance of the Study
Community hospitals are attempting to implement telehealth technology within their
facilities, but are finding that their primary care providers are reluctant to adopt the technology
(Yarbrough & Smith, 2007). The significance of this study could be to increase the use of
telehealth within community hospitals by helping hospital decision-makers to identify those
factors that create pause to the acceptance of telehealth technology by their primary care
providers (Yarbrough & Smith, 2007). When primary care providers have a positive view of
telehealth technology, their acceptance can improve the overall use of telehealth which can have
an effect on the positive outcomes of patient care (Rho, Yoon, Kim, & Choi, 2015). The use of
the TAM for this study, will further support the claim that TAM is a good model to use when
investigating the acceptance of telehealth technology among primary care providers.
According to Serper and Volk (2018), providers are key to helping to control hospital costs
because they are ultimately responsible for the cost of care of patients. The use of telehealth
technology can reduce the cost of care (Neville, 2018).The impact of primary care providers
accepting telehealth technology could improve opportunities for enhanced documentation in
patient records and immediate access to diagnostic results which means the application of timely
and appropriate interventions, which results in improved patient outcomes (Alvandi, 2017).
Lawmakers could use the result of the study to assist with the creation of laws that give leeway
to providers’ increased use of telehealth technology (Doarn et al., 2014). The study could

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provide hospital decision makers with future studies could expand to include all providers that
specialize in an area of focus.
Definitions of Key Terms
Community hospital. A hospital, generally less than 550 beds, that serves a population
of its immediate geographical location (Beckers Review, 2015).
Intent to use. How the user accepts the technology (Portz et al., 2019)
Perceived ease of use (PEU) The perception an individual has about the amount of effort
it takes to use technology (Davis, 1989).
Perceived usefulness (PU) The perception an individual has about how applicable
technology might be to them (Davis, 1989).
Primary care provider. A healthcare licensed physician, nurse practitioner, or physician
assistant that provides assessment and treatment to individuals with common health issues (U.S.
National Library of Medicine, 2019).
Telehealth technology. The combination of tools and services that provide the electronic
exchange of patients’ health information (Tuckson, Edmunds, & Hodgkins, 2017).

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Summary
Telehealth technology allows patients to receive healthcare that through traditional means,
would be next to impossible, provides a convenience ,as there is little stress related to
transportation, and reduces family stress of having to accommodate schedules to assure a loved
one receives the proper medical attention (George, Daniels, & Fioratou, 2018; Taber, Leyva, &
Persoskie, 2015). Hospitals in the United States have begun to implement telehealth technologies
that will help to provide improved patient outcomes, however, the implementation rate is lower
than expected (AHA, 2019). Adler-Milstein et al. (2014) suggested that primary care providers’
reluctance to adopt telehealth was the most impactful reason for the low implementation rates of
telehealth technology in U.S. hospitals. Investigating the factors that contribute to primary care
providers’ reluctance to adopt the telehealth technology could provide hospital decision makers
with the tools needed to assist primary care providers in accepting telehealth technology
(Gagnon et al., 2005). This proposed study will seek to provide those factors that have a
statistical significance of the primary care providers’ behaviors towards telehealth technology.
Through the use of the TAM as the theoretical framework for this study, factors that affect the
intent of use of telehealth technology among primary care providers that work in U.S. hospitals
can be statistically evaluated and identified (Cruz-Benito et al., 2019; Poellhuber, et al., 2018;
Weng et al., 2018). Using the quantitative method and correlational design for this study will
support the use of TAM by determining the relationship of the factors through the data collected
via an online survey app., Google Forms. The results of the study could help hospital
administrators strategically plan for interventions to take for successful telehealth
implementations and help primary care providers recognize what factors act as barriers in their
adoption of telehealth technology within community hospitals (Gagnon et al., 2005).

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Chapter 2: Literature Review
The purpose of this correlational, quantitative study is to investigate the factors that
influence the decision of primary care providers that work in community hospitals within the
United States, to accept telehealth technologies. TAM has been identified as an acceptable model
to use to predict factors that affect the adoption of technology (Al-Rahmi et al., 2019; Min, So, &
Jeong, 2019; Rahman, Yunus, & Hashim, 2019; Riantini, Vional, & Aries, Aug 2018;
Teeroovengadum, Heeraman, & Jugurnath, 2017). Using TAM as the theoretical framework, this
study seeks to provide answers to the presented research question regarding variables that align
with telehealth technology adoption by primary care providers. The variables include perceived
ease of use, perceived usefulness, and organizational support. An all-encompassing discussion on
telehealth provides insight into the many facets of telehealth technology.
The literature reviewed in this chapter were retrieved following searches through the
Northcentral University (NCU) Library, PubMed, and Google Scholar search engine. Databases
located within the NCU Library included EBSCOhost Discovery Service (EDS), Medline, and
Business Source Complete, government websites and publications, and reputable organizations,
such as American Heart Association (AHA). 1,188 articles related to the adoption of telehealth
among primary providers were located, but only 72 articles remained after removing exclusions.
Research articles on physician acceptance of telehealth, telemedicine, and e-health were
reviewed. Keywords for the queries included “adoption of telehealth and physicians,” “adoption
of telehealth and hospitals,” “acceptance of telehealth and hospitals,” “factors of telehealth
acceptance,” “barriers to telehealth,” “technology training,” “challenges to telehealth,” “end user
technology raining,” “Technology Acceptance Model (TAM),” and studies where TAM was
used in conjunction with another model. Other keywords utilized were “healthcare settings”,

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“hospitals,” “predictive factors of telehealth”, “primary care providers in telehealth”, “nurse
practitioners in telehealth”, “physician assistants in telehealth”, “benefits and barriers to
telehealth”, and “acceptance of telehealth”. Because telehealth is sometimes used
interchangeably with telemedicine and e-health (Wernhart, Gahbauer, & Haluz, 2019; Tuckson,
Edmunds, & Hodgkins, 2017). Articles that included other clinician roles, such as medical
students, nurses and respiratory therapists, patients, other hospital technologies, other
technologies in the hospital setting, such as those regarding electronic healthcare records (EHR),
those specific to an area of practice, such as orthopedics dialysis, other healthcare facilities, such
as military facilities and long-term care facilities, unpublished dissertations, and literature not of
the English language, were all excluded., unless the study included information regarding
perceptions of telehealth. All quantitative and qualitative articles were screened for information
contained within the studies that were relevant to support the research of the selected theoretical
framework, physician and telehealth adoption, and implementation and adoption of telehealth for
hospitals. The majority of articles were published since 2015 to ensure current practices and that
the research is accounted for. Later publications were considered to provide a base level of
understanding and a historical account of the research in the field.
The literature reviewed in this chapter presents a comprehensive collection of published research
articles that have been critically analyzed to identify the gap of the low adoption rate of
telehealth among primar providers in the U.S. (Cuellar, 2019). The following first section
discusses the theoretical framework and how the study. The following theoretical framework
section describes TAM and how the constructs help to shape this study. A section regarding
telehealth’s past, present, and future and the benefits and challenges follows theoretical
framework. A discussion about primary care providers and their role in telehealth adoption is

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presented afterwards. In the last part of this chapter, community hospitals and their connection
with the implementation of telehealth technologies are discussed.
Theoretical Framework
To investigate the low adoption of telehealth technology among primary care providers in
community hospitals, TAM is used as the theoretical framework for this study. In the late 1980s,
Davis (1989) created a set of measures that could explain system acceptance or rejection.
According to Chutter (2009), Davis named this model the technology acceptance model. The
conceptual model included a stimulus, which was the system’s features and capabilities that
encouraged the user’s motivation to use the technology. Motivation was noted as the predictor of
actual system use (Chuttur, 2009). Chuttur (2009) also explained that while Davis created the
TAM, it was Ashbein and Ajzens’ (1975) research of the theory of reasoned action (TRA) that
was used as the foundation for the TAM.
TRA explains how a persons’ actual behavior can be determined by considering his or her
prior intention along with whether the person cares what others think about the behavior they
exhibit (Huang, Luo, & Peng, 2017). In later years, Davis collaborated with Venkatesh to
enhance the technology acceptance model and created TAM2. In this model, they included the
experience of the user with similar technology and two input processes: “the social influence
processes (subjective norm, voluntariness, and Image) and the cognitive instrumental processes
(job relevance, output quality, result demonstrability” (Tong,Wong, & Lee, 2015; Wu, Chou,
Weng, & Huang, 2008). Looking at both the acceptance and rejection aspects of technology
behavior, Davis and Venkatesh added subjective norm from TRA, which looks at whether an
end-user is required to use the technology, or if it is just something they decided to do of their
own free will, without the pressure of trying to please another individual, and if the end-user

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believes that using the technology will improve an organization (Wu et al., 2008). In the
cognitive instrumental process, Wu et al. (2008) described the components of the process that
included perceived usefulness made up of job relevance, output quality, result demonstrability,
and perceived ease of use. The authors go on to explain the cognitive instrumental process in
detail. Job relevance is a crucial component of the matching process in which a potential user
judges the effects of using a particular system on his/her job. Output quality is described as the
user preconceptions about what the technology is supposed to accomplish. If the technology
behaved as the end-user initially thought it would, it provides demonstrability; this would mean
the user will have a positive perception, and perceived ease of use (Wu et al. 2008). TAM2 is a
regrouping of the original technology acceptance model by taking a step back and looking more
at the individual user.
In 2008, Venkatesh and Bala introduced TAM3. According to Venkatesh and Bala (2008),
TAM3 is a reflection of TAM and TAM2, only more focused on administration as a group and
those that make executive decisions. Venkatesh and Bala explained that while they have
identified acceptance of technology on an individual level, those that make decisions for an
organization seem to lack an understanding of the subject and process, and referenced significant
information technology failures of large companies that cost them millions of dollars because of
this inability to identify and intervene on the acceptance of technology. The two authors
suggested that “experience will moderate the relationships between (i) perceived ease of use and
perceived usefulness; (ii) computer anxiety and perceived ease of use; and (iii) perceived ease of
use and behavioral intention” (Venkatesh & Bala, 2008). TAM3 emphasized that the experience
of the user helps to link perceived ease of use and perceived usefulness, computer anxiety and
perceived ease of use, and perceived ease of use and behavior a little clearer and easier to relate.

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TAM and TRA are just two of a handful of adoption models used in studies that investigate
the adoption of technology. An extension from TAM, TAM2, and TAM3 is the unified theory of
acceptance and use of technology (UTAUT) model. UTAUT, as presented by Venkatesh, Morris,
Davis, F. and Davis, G. (2003) and cited by Lai (2017), contains all of the variables from the
previous models but has four added independent variables, performance expectancy, effort
expectancy, social influence and facilitating conditions, and four dependent variables, gender,
age, voluntariness, models, and experience of the user. Performance expectancy include
perceived usefulness, extrinsic motivation, job-fit, relative advantage and outcome expectations
constructs; while effort expectancy includes perceived ease of use and complexity constructs
(Lai, 2017). According to Venkatesh and Bala (2008) “Social influence captures various social
processes and mechanisms that guide individuals to formulate perceptions of various aspects of
an IT and facilitating conditions represent organizational support that facilitates the use of an
IT.” Chao’s (2019) study used the extended TAM, UTAUT, because the TAM model was not
fully capable of predicting technology acceptance on an individual basis if trust and management
support constructs were added. Chao indicated that the UTAUT model needed extended
variables to make it more useful for the individual identification of factors that affect adoption.
Although the current study focuses on behavioral intention, as the UTAUT model is used for, the
study does not delve into that depth of the individual determinants of behavioral intention. In
1995, Taylor and Todd presented the theory of planned behavior (TPB), an extension of TRA,
which included perceived behavioral control as one of the determinants of behavioral intention to
use technology. Perceived behavioral control (PBC) was explained by Taylor and Todd as a
representation of access to resources and self-efficacy. According to Taylor and Todd (1995),
there is a relationship between PBC and behavioral intent, however, TPB includes subjective

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norms, which focuses on the social expectation to determine behavioral intent to use, not just for
technology, but any new application of an evidence-based practice (Burgess, Chang, Nakamura,
Izmirian, & Okamura, 2017). The current study’s intent does not focus on social aspects; thus, it
was not a good fit for this study. Rogers’ 1995 theory of diffusion of innovations (DOI), also
known as diffusion of innovations theory (DIT), explained how innovations are disseminated in
time and are dependent upon the message the individual is willing to pass on to the next
individual (Lai, 2017). According to Dearing and Cox (2018), the DOI encompasses how the
adoption of technology will be accepted through communication and social acceptance.
Innovative technology that surfaces will either gain momentum in acceptance if the social group
as a whole accepts the technology or loses momentum for acceptance if the social group as a
whole declines to accept the technology (Dearing & Cox, 2018). Studies that use DOI tend to
look beyond the acceptance stage of adoption, but also seek to investigate factors that may affect
the sustainment of the technology over time (Aizstrauta, Ginters, & Eroles, 2015). Trahan (2019)
cited Everett Rogers’ 1962 book regarding the DOI theory, that adoption depends on previous
interaction with the technology, the level of complexity of the technology, how the technology
meets the current needs of the user, the ability to test the technology out before full use; adopters
are categorized according to the timing of their adoption of the technology, from immediate to
very lengthy time frame; and occurs in four stages, knowledge of the technology, persuasion of
the use of the technology, the decision to commit to using the technology, implementation of the
technology, and confirmation that the technology provides positive outcomes. The use of DOI is
beyond the scope of this study, as this study’s quest is to identify factors that have an impact on
the acceptance of technology of the users and does not focus on post-adoption factors.

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This study will use TAM as the theoretical research framework to investigate the
relationship of factors that predict primary care provider’s intent to use telehealth technology.
TAM is about the beliefs about the technology, individually or as a group. Still, the model does
not take into account that people may be affected by external factors between the intent to accept
and adopt the technology and the actual adoption of the technology when it comes to making
decisions nor does it give a guide on how to make the technology useful (Chuttur, 2009).
According to Holden and Karsh, (2010), when used in healthcare, the generic form of TAM may
not be the best model because “it may not capture…unique contextual features of electronic
health care delivery” (p.4). The article went on to explain that, after their review and analysis of
several articles that used TAM for healthcare IT-related adoption, the TAM model adequately
explained intention to use and the relationship to PU when investigating the adoption of
information technology in the healthcare setting, but added that TAM may require modification
when used in healthcare. Because the current study only seeks to understand the primary care
providers’ behavior towards intent to use telehealth technology, by using external variables and
does not include the providers’ personal goals of performance while at work, nor does it focus on
administration decisions, TAM was selected for this study (Tong, Wong, & Lee, 2015).
Telehealth
Telehealth is also referred to as telemedicine, e-health, electronic health, and telecare
(McClellan, Florell, Palmer, & Kidder, 2020; Wernhart et al., 2019; Kruse, 2018; Lin et al.,
2018; Kruse et al., 2017; Polinski et al, 2016; Sabesan, 2015; Adler-Milstein, 2014; LeRouge &
Garfield, 2013; Hendy et al., 2012). Although Tuckson et al. (2017) explained that telehealth
technology is the combination of tools and services that provide the electronic exchange of
patients’ health information through a network, there are other definitions found in the literature.

19
The most cited explanation is from The World Health Organization (WHO) where telehealth is
defined as the “use of telecommunications and virtual technology to deliver health care outside
of traditional health-care facilities “ (WHO, 2016)(Centers for Disease Control (CDC), 2019;
Kissi et al., 2019; Bagchi, Melamed, Yeniyurt, Holzemer, & Reyes, 2018; Mahar et al., 2018;
Serper & Volk, 2018; Shelton & Reimer, 2018; Kruse et at., 2017; Ryu, 2010). Other researchers
have simply stated that telehealth involves the remote monitoring of a patient’s health (Orlando,
Beard, & Kumar, 2019; Bertoncello, Colucci, Baldovin, Buja, & Baldo, 2018; Neville, 2018;
Alvandi, 2017; Adler-Milstein et al., 2014).
Telehealth first appeared in 1878 with the use of the telephone for physicians making calls
to their patients to check on them according to Bashur et al. (2009), as cited by Dinsen et al.
(2016). Mahar et al. (2018) noted that in the 1920s, radio consultation centers existed. Today,
telehealth has grown in part because of the increase of innovative technologies that allow for
improved communication for the delivery of healthcare (Adler-Milstein et al., 2014).
Telehealth technology has allowed the advancement of the healthcare industry and changed
patient outcomes from poor to improved (Alotaibi & Federico, 2017; Foisey, 2017; McMahon,
2002). Today, patients can be assessed, diagnosed, and treated with physicians and providers
from different states. Patients with chronic diseases are managed better with the use of telehealth
(Haghi, Thurow, & Stoll, 2017). Improving outcomes of patients has always been the objective
when abnormal health issues are identified (HHS Office, 2019; Nagykaldi, Tange, & De
Maeseneer, 2018; Mold, 2017). Innovative medical devices used in healthcare, such as the
electronic healthcare record, diagnostic and monitoring devices, surveillance tools, analytics
software, wearable devices, and surgical assisted devices collect massive amounts of useful
patient data and disrupt the normal way healthcare is delivered. All of this technology will

20
undoubtedly continue to disrupt the healthcare market (Yang et al., 2015), but just how far the
level of disruption will go remains unknown. Several aspects affect whether or not patients will
have better outcomes. Patient outcomes are affected by laws, geographical location and
economical status of neighborhoods and communities, financial burden, the advancement of
technology and its level of acceptance by uers. An in-depth review of these factors will help to
define the technology landscape of healthcare in the future (Singh & Sittig, 2016; Bowles,
Dykes, & Demiris, 2015; McCullough, Casey, Moscovice, & Prasad, 2010).
Telehealth Technology. Hah, Goldin, and Ha (2019) explained that telehealth
technologies includes “a number of electronic information and communication technologies
(ICTs) to facilitate long-distance clinical care, patient and professional health-related education,
and public health administration.” Technology in the telehealth category is gaining recognition
as an effective practical, useful, and convenient tool to deliver healthcare. Because telehealth
technologies offer convenience for primary care providers, it is more favorable to utilize
advanced technology for the delivery of healthcare (Kruse, 2017).
In the article presented by Harwood et al. (2011), the authors identified some of the most
utilized technology in the psychology healthcare field and how clinicians utilize them in the
community. Technology-assisted therapies are not intended to take the place of human
interaction altogether, only as a supportive measure to psychotherapists (Harwood et al., 2011).
Common ethical issues remain with the introduction of technology, and the patient must be at a
certain comfort level with the use of telehealth technology (Harwood et al., 2011). Langarizadeh,
Moghbeli, and Aliabadi (2017) described some of the ethical concerns including the risk of
patient’s information being stolen either through carelessness of the clinician or unsecure

21
devices, inadequate guidelines and standards, and a lack of a trustworthy doctor-patient
relationship.
Meetoo et al. (2018), explained the expansion of telehealth in healthcare through the use
of mobile devices. There are several types of mobile devices used in mobile telehealth, like
smartphones, electronic healthrecords, and digital devices (Harvey & Powell, 2019; Meetoo et
al., 2018). Exploring the impact and the effect that technology in telehealth has on society now
and in the future, Meetoo et al. (2018) investigated the usefulness of patient data obtained
through mobile devices and the impact that mobile telehealth technologies makes on the quality
of patient care. Zhao, Ni, & Zhou (2018) explained that mobile devices provide a positive impact
on the quality of care delivered when they are used in telehealth. According to Kashgary,
Alsolaimani, Mosli, & Faraj (2017), the doctor-patient communication is improved through the
use of mobile devices, which also has a positive impact on the delivery of quality of patitent
care. Harvey and Powell (2019) also noted that mobile devices support the delivery of quality of
patient care because it simplifies clinician’s workflow and provides clinicians access to patient
records at the point-of-care. Mobile devices present a few challenges for the clinicians that utlize
them that influence their acceptance of the technology (Harvey & Powell, 2019; Li, Wu, Gao, &
Shi, 2016). Meetoo et al. (2018) explained that while mobile technologies offer positive
outcomes, there is also the possibility the technology will have adverse consequences, such as
violations of privacy and confidentiality. Although there are useful advances in mobile
telehealth, the use of mobile telehealth devices in healthcare will not gain momentum until
healthcare professionals begin to trust both the mobile devices and the patient data that the
devices collect (Meetoo et al., 2018).

22
Wearable Technology in Telehealth. Smartphones and apps have encouraged the
increased use of wearable technology in telehealth (Meetoo, Rylance, and Abuhaimid, 2018).
Apps with the ability to communicate with biometric sensors, which are embedded in clothing,
bracelets, watches, and skin patches, collect data and transfer the data to an interface where
providers can analyze and assess the collected information (Meetoo et al., 2018). Other types of
digital devices that allow the collection of data and transfer of the data include lab chips, where
the bodily fluid is collected on chips, implantable, which are sensors ingested or placed on a
person, and ingestible sensors, which are swallowed (Meetoo et al., 2018). The collected data
measures certain specific biometric levels, which are then sent to the provider, which can allow
clinicians access to all aspects of a patient’s information (Meetoo et al., 2018). The
sophistication behind the analysis of the collected data through algorithms helps to monitor a
patient’s health status and allows providers to identify useful patterns in the patient’s data
(Banaee, Ahmed, & Loutfi, 2013). The research on wearable technology is increasing due to the
reports that they have a positive impact on the monitoring and management of chronic diseases,
such as diabetes and cancer (Gao et al., 2015). Wearable technology can help to reduce the cost
of prevention of eventful adverse outcomes and monitoring of patient’s health-related (Haghi et
al., 2017). It is expected that more wearable technology with telehealth applications will surface
in the future (Ajami & Teimouri, 2015).
Telehealth Video Visits. Visiting patients through telehealth includes the use of video to
communicate and visually assess signs and gather symptoms of illnesses and changes with
chronic diseases (Powell, Stone, & Hollander, 2018). Video visits, also known as face-to-face
real-time visits, video conferencing, and virtual visits, are not only convenient for saving time for
the patient but also allows patients access to medical care where there is a shortage of providers

23
in their area (Donelan et al., 2019; Powell et al., 2018; Powell, Henstenburg, Cooper, Hollander,
& Rising, 2017; Tuckson et al., 2017). Video visits, used in a variety of settings, have a wide
range of usefulness, including assessment of dermatological conditions, genetic counseling, and
pain management (Powell et al., 2018). Studies have shown that patients prefer video visits
versus actual physical face-to-face visits and are satisfied with their video visits (Donelan et al.,
2019; Powell et al., 2018). Patients expressed concern about privacy and confidentiality due to
conversations that could be overheard, their images could be seen by those other than their
provider, and information being intercepted when transmitted (Powell et al., 2017). Other issues
with the use of video visits include poor sound quality, poor video quality, and a patient’s
misrepresentation of signs and symptoms that may lead to missed or incorrect diagnoses (Powell
et al., 2018; Tuckson et al., 2017). Medicare reimburses for the use of video-visits, however,
with stipulations to setting and provider availability. Tuckson et al. (2017) encouraged future
research on every aspect of video visits, including interaction with specialists, applied
interventions such as medications and management of diseases, hospital-based services,
technology used in conjunction with telehealth such as smartphone, and secure transmission of
images and data (Powell et al., 2017; Kaufman et al., 2009).
Privacy and Security. According to Grood, Raissi, Kwon, and Santana (2016) and
Bashur et al. (2014), privacy and confidentiality are real concerns among physicians. Kissi et al.
(2019), reported that because of security and privacy issues, some physicians have chosen to
avoid the use of telehealth technology. Heightened concern for the risks to privacy and
confidentiality with the use of telehealth technologies, as explained by Chaet, Clearfield, Sabin,
and Skimming (2017) includes the use of third parties who may sometimes send patient
information to other parties through codes embedded in the softare that direct specific collected

24
data to another party or through other means. Telehealth-based health care services have had 938
data breaches between 2005 and 2013 (Angst, Block, D’Arcy, & Kelley, 2017); suggesting
telehealth providers perform telehealth privacy and security self-assessment to identify
vulnerabilities in the telehealth system they may use (Zhou, Thieret, Watzlaf, Dealmeida, &
Parmanto, 2019). While confidentiality concerns include the integration of patient records from
one system to another and privacy concerns include the possibility of hacked records, due to
flaws in systems security, there are processes in place to prevent such issues, such as laws like
the Health Insurance Portability and Accountability Act Privacy Rule, HIPAA, codes of conduct,
consent forms, and improved levels of security (Grood et al., 2016). Hall and McGraw (2014)
suggested that Congress should focus on directing the Federal Trade Commission (FTC) on
creating privacy and security laws and policies that are federally mandated in lieu of relying on
individual states to develop their regulations. Hall and McGraw (2014) also posited that any
threats to the privacy and security of patient health information must be identified and addressed
as soon as possible. In their 2017 article, Chaet et al. identified that physicians have a moral
responsibility to respect their patient’s privacy and act accordingly to provide a high level of
confidentiality for their patient’s health records and patient information, which includes assuring
privacy policies exist on the websites that exchange patient data. Chaet et al. (2017) also noted
that physicians have a responsibility to assure that the audio during telehealth interactions are
also provided in a way that protects patient information. Although privacy and confidentiality are
identified by the literature as barriers to the adoption of telehealth among primary care providers.
Telehealth in the Community. The adoption rate of telehealth in the community has a
combination of challenges and barriers. Alverson (2012) noted a lack of broadband connectivity
and access as a major challenge of telehealth in the community. As Sitton-Kent, Humphreys, and

25
Miller (2018) pointed out in their article, three applications could increase the adoption of
telehealth in the community: mobile access to digital care records, digital imaging, and remote
face-to-face consultations. Sitton-Kent et al.’s article presented the financial and positive
outcomes as benefits of telehealth and the implementation of telehealth in the community as
complex but doable.
It is important to know how the community will receive the telehealth process and
technology. Knowing that each telehealth program will be different and will need to cover the
needs of each respective community, telehealth may be readily accepted or may be shunned.
Courtney et al. (2010) assessed the feasibility of telehealth in the community. The study explored
the relationship between the benefits of telehealth and the attitudes of older adults. The authors
used a qualitative descriptive method with a sample of a population of adults who were more
than 70 years of age and had a self-reported chronic health conditions. It was identified that
perceptions on the use of blood pressure monitoring was positive and the end users connected the
use of the kiosk, a free-standing interactive computer used to collect or provide information, to a
reduction in financial burden and doctor visits.
Flickinger et al.’s 2017 article reviewed how individuals in the community that
have HIV could get assistance through the use of telehealth support app. 74% of the participants
thought that self-monitoring via the tool was a benefit along with keeping track of meds and
65.45% identified technical issues with the application as a barrier (Flickinger et al., 2017).
Cost-Effectiveness of the use of Telehealth. According to Agha, Schapira, and Maker
(2002), “Cost effectiveness of telemedicine is related to three major factors: cost sharing, i.e.,
adequate patient volume and sharing of telemedicine infrastructure amongst various clinical
users; effectiveness of telemedicine in terms of patient utility and successful clinical

26
consultations; and indirect cost savings accrued by decreasing cost of patients' lost productivity.”
While telehealth is slowly gaining popularity, the financial ramifications are still being assessed.
A study completed in 2014 by Yamamoto, for Red Quill Consulting Inc, found that while a
telehealth visit may cost between $40-$50, an in-person visit with a provider can cost between
$136-$176. A comparison study was completed by Grustam et al. in 2018 that looked at the cost
of telehealth versus non-telehealth delivery care methods, as it pertains to chronic heart failure.
The results revealed that the use of telemonitoring and nurse telephone support was more cost-
effective than the standard delivery of care as well as an increase in the rate of survival by as
much as 20% (Grustam et al., 2018). Just the impact of chronic health conditions on a patient’s
activities of daily living can equal financial devastation, beginning with expensive treatments,
which can lead to worsening conditions (Henderson et al., 2013).
The military could also benefit financially from the use of telehealth, especially in the
field of mental health., Authors Jones, Etherage, Harmon, and Okiishi (2012) presented
information regarding the many aspects of using mobile telehealth technology, including the
cost-effectiveness of using the technology, to address mental health needs. Chakrabarti (2018)
inquired about whether the use of telehealth was efficient and cost-effective or not. The study
identified that telehealth reduced costs and noted a negative association between cost and
telehealth services (Chakrabarti, 2018).
Telehealth Adoption Among Primary Care Providers
The acceptance of telehealth among primary care providers is crucial to the future
delivery of healthcare and the management of patients’ chronic diseases (Mahar, Rosencrance, &
Rasmussen, 2018). Patients now can have some of their medical issues addressed in real-time, or
at least without considerable delay, and with little impact on the routine of their daily lives. A

27
diabetic patient can test their blood sugar levels and have them uploaded and sent to their
primary care provider’s office, along with any documented signs and symptoms of low or high
blood sugar. If there is a trend that causes concern on behalf of the provider, the provider can
intervene with a video call, order prescriptions to the patient’s nearest pharmacy, and update the
patients’ medical record, or choose to schedule a face-to-face assessment (Rho, Choi, & Lee,
2012). This remote monitoring decreases the risk of the patient’s chronic disease from falling
into a worsened state that might lead to a costly hospital admission (Sherling & Sherling, 2017).
Studies have indicated that hospital admissions are decreased when telehealth technology is
implemented, such as the results from the Veteran’s Administrations’ 2003 program, Care
Coordination/Home Telehealth (CCHT), which proclaimed a 19% decrease in hospital
admissions. Partners Healthcare decreased their cardiac admissions by more than 50%, and
Centura Health was able to reduce hospital readmissions for their cardiac, pulmonary, and
diabetic patients (Connecticut General Assembly (CGA), 2015; Kulshreshtha, Kvedar, Goyal,
Halpern, & Watson, 2010; Darkins et al., 2008; Darkins, 2006). Telehealth was used in a variety
of situations in the part, such as in NASA’s monitoring of astronauts’ physiological
measurements, the use of the radio to provide medical advice to those on ships, and the US
Department of Veterans Affairs (VA) for the purpose of treating behavioral health issues (Mahar
et al., 2018; Dinesen et al., 2016). Telehealth technology provides patients with the opportunity
to receive timely medical attention. Patients may have geographical and transportation barriers
that may prevent them from being seen by a provider. Just the impact of chronic health
conditions on a patient’s activities of daily living can result in financial challenges, beginning
with expensive treatments, which can lead to worsening conditions (Henderson et al., 2013).
Telehealth improves the delivery of healthcare by giving providers access to patients’ charts,

28
assisting providers with the management of their patients’ chronic diseases, and by keeping costs
down at healthcare delivery facilities, such as hospitals (Neville, 2018; Dinesen et al., 2016; de la
Torre-Díez, López-Coronado, Vaca, Aguado, & de Castro, 2015; Wootton, 2012). Because
telehealth includes a variety of innovative technology applications, integrated to achieve the
common goal of improved patient outcomes, there are many categories underneath its umbrella
(Tuckson et al., 2017) including telerehabilitation, telepsychiatry, teleradiology, teledentistry,
teleaudiology, telenursing, and tele-ICU or e-ICU (Maresca et al., 2019; Balenton, & Chiappelli,
2017; Bashshur, Krupinski, Thrall, & Bashshur, 2016; Becker, Frishman, & Scurlock, 2016;
Singh, Pichora-Fuller, Malkowski, Boretzki, & Launer, 2014; Stec, Tomblin, & Coustasse, 2013;
Patel & Antonarakis, 2013).
Hospitals that have implemented telehealth technologies successfully, have noted a
reduction in the rates of hospital admissions, which has positively impacted their costs (Serper &
Volk, 2018; Holland, 2013). There has been an increase in the number of hospitals that have
implemented telehealth into their healthcare delivery system in recent years, but it is still lower
than expected (AHA, 2019a). Some research articles have contributed the low implementation
rate of telehealth technology in hospitals to low acceptance among its end users, including and
especially physicians (Adler-Milstein et al., 2014; Gagnon et al., 2008; Gagnon et al., 2006;
Gagnon et al., 2004). According to Gagnon et al. (2005), the adoption of telehealth in hospitals is
directly impacted by physicians’ acceptance within their facilities. Discovering the barriers to
acceptance of the telehealth technology that is needed to overcome the adoption of telehealth will
positively impact the hospitals’ operational and cost-efficiency.
On an individual level, primary care providers are met with a variety of internal and
external barriers that decrease their acceptance and adoption of telehealth technology. Internal

29
barriers include low levels of knowledge of telehealth, willingness to operate telehealth
technology, perception of decreased quality of care and efficiency of the delivery of care, and
resistance to change (Albarrak et al., 2019; Scott Kruse et al., 2018; Sherling & Sherling, 2017 )
LeRouge & Garfield, 2013: Rho, Choi, & Lee, 2012). External barriers include the risk of
breach of patient privacy, lack of organizational-provided training, issues with times of non-
functional information communication technology, lack of adequate telehealth-related governing
laws, questionable quality of care, and the amount of time it takes to use the technology
(Albarrak et al., 2019; Scott Kruse et al., 2018; Sherling & Sherling, 2017; Rheuban. Shanahan,
& Wilson, 2014; LeRouge & Garfield, 2013; Rho, Choi, & Lee, 2014). A systematic review by
Scott et al. (2018) considered six countries and the barriers of the slow implementation rate of
telemedicine. The problems identified in the study was the challenges and barriers that are
present for implementing telemedicine. The researchers reviewed 30 international and USA
articles and found 33 barriers with the most prevalent barrier being issues with technically
challenged staff at slightly over 10%. Preferred Reporting Items for Systematic Reviews and
Meta-Analyses (PRISMA) guidelines was utilized in the study. The article identified barriers to
telehealth technology among physicians and non-physcians, but identified barriers specific to
physicians. The top barriers for physicians were state licensing limitations, knowledge of
technology, and resistance to change. Barriers to telehealth adoption among countries, including
the USA, and by organizations were also identified by the researchers. While the type of
organizations was not specified, organizational barriers included those relating to cost and
reimbursement, legal issues, and privacy and security. The authors noted that overcoming the
barriers could be done through training, change-management, and an alternating cycle of
technology and person-to-person interaction.

30
Adler- Milstein et al. (2014) investigated telehealth adoption factors from the perspective of
US hospitals. Using empirical research, the researchers sent surveys to 2,891 hospital CEOs to
disperse accordingly. Although the study also focused on hospital level telehealth adoption
factors, it also included market and state-level telehealth adoption factors. The results highlighted
restricted reimbursement, licensing restrictions, limited amounts of current technology, and non-
teaching facilities as factors associated with low implementation rates and adoption. As each
state was assessed for adoption status, it was found that of the total number of hospitals in each
state, Alaska has the broadest (75%) and Rhode Island had the least, (0%) of hospitals within the
state where telehealth was implemented. The authors also ultimately noted that improving
policies would improve hospital adoption of telehealth.
Kissi et al. ‘s (2019) study was based on physicians that were affiliated with government
health institutions in Ghana. The problem that the study addressed was the slow adoption of
telemedicine in healthcare settings. The authors used TAM as their theoretical framework in an
attempt to identify factors physicians’ satisfaction with the use of telemedicine. The survey
results were from 543 respondents- mix of “nurses, physician assistants, physicians, healthcare
administrators, and telemedicine service providers” (Kissi et al, 2019)- and the only separated
results for physicians was in regard to their satisfaction that was influenced by actual use of
telemedicine. The researchers suggested a future study that could include a larger number of
respondents and with a focus on a specific telemedicine type. While this study did not focus on a
specific type of telemedicine, it did focus on a large number of respondents from a broader
geographical area. de Grood, Raissi, Kwon, and Santana’s (2016) literature review of studies
from several different countries encompassed 74 reviewed articles. The authors investigated the
barriers to adoption of telehealth among physicians, though no specific setting was mentioned.

31
The results were presented by groups. The first group listed was design and technical concerns
that showed physicians’ system incompatibility of telehealth system with current systems and
unintuitive telehealth technologies . The concerns of whether their patient’s records would
remain confidential and private contributed to their security barriers. With respect to cost and
liability, the study showed physicians’ fear of not being reimbursed for services and increased
medical malpractice issues. Physicians also expressed loss of productivity concerns due to
having to spend more time documenting and learning how to navigate within the system.
Physicians reported a decreased, or loss of, social interaction with their patients and a limited
knowledge of the telehealth technology system being utilized. Physicians in this study reported
that their workload was too heavy to be disrupted by trying to build the necessary knowledge and
skills to adequately use telehealth technology, while some physicians reported that their usual
workflows would have to be changed and that they were resistant to change. The inability of
some telehealth technology systems to provide alerts from imbedded analysis was also reported
as a barrier. The lack of previous interaction with telehealth technology and facility provided
training were also noted barriers to the adoption of telehealth technology among physicians.
Finally, the size of their practice and the ownership of the practice was an identified factor.
Although the article mentions e-telehealth, its primary focus was on electronic medical records
(EMRs) and not telehealth technology in its totality. de Grood et al. (2016) indicated that further
research could include drilling down the various barriers to adoption among physicians from
different specialties and address limited resources and issues related to using the system.
In 2014, Rho et al. used TAM to discover the predictive factors that influence the
willingness of physicians to use telemedicine technology; the study also included accessibility of
medical records, self-efficacy, and regulatory factors (perceived incentives) as additional

32
constructs to TAM. The ultimate goal of the study was to create a model specifically aimed at
telemedicine acceptance by physicians. In total, 183 physicians were surveyed from medical
centers and hospitals in South Korea. The results showed support that perceived usefulness, the
perceived ease of use, self-efficacy, accessibility of medical records, and perceived incentives
were all contributory factors in the acceptance of technology among physicians, but specifically
for telemedicine services. The article provided strategies for stakeholders, hospitals and
administration, to assist them with the the acceptance of telemedicine technology, but did not
provide insight on organizational factors.
The Challenges and Barriers Experienced by Primary Care Providers
Primary care providers include any healthcare licensed physician, nurse practitioner, or
physician assistant that provides assessment and treatment to individuals with common health
issues (U.S. National Library of Medicine, 2019). Ellner & Phillips (2017), who cited
Donaldson, Vanselow, and Yordy (1994), explained primary care providers as clinicians that
practice in the community, develop a relationship with their patients, and are mainly accountable
for a vast majority of their patient’s health concerns. Among the vast amount of literature
regarding primary care providers, the mutual statement is in regards to the shortage of primary
care providers available to deliver care to the population in multiple communities (Kissi et al.,
2019; Ellner & Phillips, 2017; Bashur et al., 2016; Fodeman & Factor, 2015; LeRouge &
Garfield, 2013; Bodenheimer & Smith, 2013; Okie, 2012; Bodenheimer & Pham, 2010). This
shortage is imparted to several reimbursement concerns, such as with providing sub-standard
quality care, increase in the amount of documentation required, and learning new technology
which could lead to decreased level of skill-sets needed to successfully diagnose and manage
patient’s illnesses and diseases (Kissi et al., 2019; Bashur et al., 2016; Fodeman & Factor, 2015;

33
LeRouge & Garfield, 2013; Bodenheimer & Smith, 2013; Okie, 2012; Bodenheimer & Pham,
2010).
Primary care providers are faced with an increase in patients with chronic illnesses and life
expectancy, gaps in the quality of the delivery of healthcare services, and associated costs of
healthcare, which challenges their ability to provide quality healthcare services (Naylor &
Kurtzman, 2010). The negative impact on patient care, as a result of primary care providers
exiting from their careers, could lead to extensive and long term issues, such as increased chronic
diseases and increased healthcare costs (Bodenheimer & Sinsky, 2014). Telehealth has increased
in the market due to the inability of primary care providers to adequately meet the healthcare
needs of patients (Ellner & Phillips, 2017). Telehealth technology could meet the challenges
faced by primary care providers (Moore et al., 2017).
With all of the reported benefits that telehealth provides, including chronic disease
management (Bashur et al., 2014), physicians are having difficulty accepting telehealth
technology impart to the complexity of the technology (Shadangi et al., 2018). Several barriers
stall the adoption of telehealth technology among primary care providers, and research studies
have identified several key factors that have a relationship with the barriers that influence
acceptance of telehealth technology (Harst et al., 2019; Kissi et al., 2019; Ladan et al., 2018;
Rahimi et al., 2018; Shadangi, Kar et al., 2018; Abdekhoda et al., 2015; Rho et al., 2014;
Dünnebeil et al., 2012; Kim et al., 2010; Wu et al., 2008; Yarbrough & Smith, 2007; Marler et
al., 2006, Hu et al., 2002; Hu, Chau et al., 1999). Kamal, Shafiq, & Kakria (2020) noted that the
importance of analyzing the factors that influence end-users’ attitudes would significantly affect
the acceptance of telehealth technologies. A systematic review of literature completed and
presented by Kruse et al. (2018) provided findings that the majority of the barriers identified

34
were due to challenges of the telehealth technology (11%), resistance to change and cost were
second, ( 8%), and concerns with reimbursement was third (5%). Other researchers have
confirmed their findings but also noted the lack of adequate training and support, legal barriers,
and privacy and confidentiality concerns as factors that affect physician acceptance of telehealth
technology (Meetoo et al., 2018; Neville, 2018; de Grood et al., 2016). Acceptance of telehealth
technology among primary care providers could improve the future state of healthcare delivery
(Schreiweis et al., 2019).
Laws, Regulations, and Policies. Due to the many challenges that patients incur when
attempting to receive medical attention through the usual face-to-face primary care provider visit
and patient’s demand for telehealth has lead to new telehealth-related laws, regulations, and
policies on all levels; federal, state, cities, and institutions (Welch, Harvey, O'Connell, &
McElligott, 2017; Dorsey & Topol, 2016). Becker, C. D., Dandy, K., Gaujean, M., Fusaro, M., &
Scurlock, C. (2019). The Food and Drug Administration Safety and Innovation Act was created
in 2012 and included a section that tasks Food and Drug Administration (FDA), the Federal
Communications Commission (FCC), and the Office of the National Coordinator for Health
Information Technology (ONC) with developing new innovations in technology as well as
protect patient safety (Marcoux and Vogenberg, 2016). According to The Center for Connected
Health Policy(CCHP) (2019), although Medicaid is a federally funded program that provides
medical assistance to low-income persons, each state is allowed set their own by laws. All states
reimburses for live-video, but only 14 states allow for store-and-forward-type telehealth (CCHP,
2019). Telehealth technology can be a vehicle for deception and theft. The Federal Trade
Commission (FTC), which ensures that telehealth technology are effective, protects consumers
from false claims (Marcoux and Vogenberg, 2016). The Health Insurance Portability and

35
Accountability Act (HIPAA) protects patient’s health data and information that pass through
electronic communication (Zhou et al., 2019; Schwamm, et al., 2017; Marcoux and Vogenberg,
2016)
Marcoux and Vogenberg (2016) outlined what is necessary to move forward with
telehealth and how laws impact its growth, their focus, however, was on the value of telehealth
as it relates to pharmaceutical care. The article denoted that some of the legal barriers faced in
telehealth relate to limitations of licensing of primary caregivers, the lag on reimbursements for
telehealthcare, and the lack of interconnectivity between providers for the benefit of patient care.
Adler-Milstein et al.’s 2014 study echoed similar information as the previous article;
however, the delivery of the article lays the attention on the policies that are related to improved
adoption of telehealth. The authors surveyed CEOs of 10 hospitals from the District of Columbia
area for qualitative data and data from the Information Technology (IT) Supplement to the
American Hospital Association (AHA) 2012 Annual Survey of Hospitals, which included 2,891
acute care, nonfederal hospitals in the fifty states, for quantitative data (Adler-Milstein, Kvedar,
& Bates). Slightly less than 50% of the hospitals already had telehealth, with 30% using HIMSS
Analytics data. Hospitals that had a cardiac ICU and larger system hospitals had a higher chance
of having telehealth adopted (Adler-Milstein, Kvedar, & Bates, 2014). The study identified states
that had the broadest adoption (Alaska was at the top) as well as no effect from hospitals that
were in identified areas where there was a shortage of primary caregivers (Adler-Milstein et al.,
2014). The study magnifies the need for states to improve their hospital adoption rates of
telehealth to focus more on reimbursement through legislation.
Most of the laws related to telehealth have to deal with reimbursement, but those laws vary
from state to state. It is difficult to get an overall understanding on reimbursement with telehealth

36
because no database exists (Trout, Rampa, Wilson, & Stimpson, 2017). Trout, Rampa, Wilson,
and Stimpson (2017) set out to gain a better understanding by creating a database of state-level
policies and their reimbursement laws for telehealth. It was discovered that Mississippi had the
most robust laws when it comes to reimbursement because they allow reimbursement from all
three types of telehealth: live video transmission, store-and-forward, and remote patient
monitoring. However, most of the states reimburse for only live video transmission, with the
majority of the policies being created between 2012 and 2015 (Trout, Rampa et al., 2017).
Government representatives continue to work to try to improve laws, regulations, and policies
that will encourage the use of telehealth technology, increase adoption among primary care
providers, and provide patients with quality of care and cost savings (Marcoux and Vogenberg,
2016).
Community Hospitals and Telehealth Technologies
A community hospital is a healthcare facility with wards that provides a place for
healing; the concept goes back as far as the late 1800s (Kisacky, 2019). According to Liu and
Kelz (2018), community hospitals may provide an array of care types, from general to
specialized care. While community hospitals provide care to anyone within the community,
providing adequate care to all those within the community can be a challenge. Due to the aging
population and an increase in the number of chronic conditions, hospital costs are on the rise
(Steiner & Friedman, 2013). Hospitals are looking for alternative ways to provide better care and
improved outcomes for their patients as well as having their primary care providers become more
knowledgeable about their patient’s health (Adler-Milstein et al., 2014). Telehealth provides a
form of delivery of healthcare that reduces gaps in the patient continuum of care, often brought
on by several factors such as business challenges, appointment scheduling, transportation issues,

37
after hour’s access for care, and primary care provider shortages (Tuckson et a., 2017). But
hospital implementations of telehealth technologies are met with primary care providers that
have difficulty accepting telehealth technology, which limits the implementation of telehealth
within their organization (Tuckson et al., 2017). When organizations train their end users on the
technology to be implemented, they can also provide support through providing additional
available training and informational resources (Marler et al., 2006). Some telehealth applications
that broaden the ability to meet the continuum of careare tele-ICU, tele-operation, teleradiology,
teleophthalmology, teleoncology, Tele-ECG (electrocardiogram), and telepsychiatry (Ozkan,
Ozhan, Karadana, Gulcu, Macit, & Husain, 2020; Ishida & Matsumoto, 2019; Özgüç &
Tanrıverdi, 2019; Ayatollahi, Nourani, Khodaveisi, Aghaei, & Mohammadpour, 2017; Bashur et
al., 2016; Gatti, Pravettoni, & Capello, 2015). With the identified factors that affect the adoption
of telehealth technology among physicians in community hospitals in the US, community
hospital administrators, stakeholders, and telehealth technology manufacturers will be able to
create a strategy that improves the effectiveness of the delivery of healthcare services, which
ultimately provides improved patient outcomes (de Grood et al., 2016).
Training and Support. In Yarbrough and Smith’s 2007 systematic review research
study, regarding technology acceptance among physicians, one of the barriers identified was
organizational issues. The main category under organizational issues was organizational support,
which included training physicians on the technology. The authors note that physicians require
more focused training as compared to other industries. Due to its complexity, adequate training is
a key to their successful use during their usual workflow, as it allows them to create new and
improved workflow patterns will reduce the amount of time they have to spend in the system
documenting (Edirippulige & Armfield, 2017; Moore, Coffman, Jetty, Petterson, & Bazemore,

38
2016; Yarbrough & Smith, 2007; Marler et al., 2006). The study by Yarbrough and Smith (2007)
reviewed several technology types used by physicians, but telemedicine was also included. The
researchers concluded their research, by adding physician acceptance of telehealth technology,
can affect the implementation of telehealth technology in healthcare organizations. Effective
training of telehealth technology has a positive effect on the attitudes and acceptance of the
technology among primary care providers (Hah & Goldin, 2019). In organizations, inadequate
end user training on the implemented technology has a direct impact on the failure of the
implemented technology (Marler et al., 2006). Marler et al.(2006) indicated that it is imperative
that end users within organizations have an “opportunity and an intention to use” the new
technology. In 2017, researchers Slovensky, Malvey, and Neigel explained that it is imperative
for physicians to proficiently utilize innovative technology in healthcare, including telemedicine,
to provide adequate care. Slovensky et al. (2017) also noted that the United States does not do a
good job of training physicians on the use of telemedicine and that organizations are an essential
piece to providing training in the job setting. Providing the primary care providers with adequate
training on telehealth technologies that are used within the organization could improve physician
productivity, the quality of healthcare delivered, and decrease medical errors related to the lack
of knowledge and skill of the telehealth technology (Edirippulige & Armfield, 2017; Slovensky
et al., 2017: Moore et al., 2016; DeJong, Lucey, & Dudley, 2015). As one of the barriers to the
acceptance of telehealth technology among primary care providers, it is noted in the literature
that there is a limited number of research that covers training of telehealth among primary care
providers (Edirippulige & Armfield, 2017). This paper includes organizational support, mainly
through training, but also includes an extension of the relationship of the organization’s support
of their primary care provider’s transition to the telehealth technology purchased by the hospital.

39
Summary
This chapter discussed an explanation of the organization of the literature review and
theoretical framework that addresses topics related to the adoption of telehealth technology
among primary care providers. Key aspects of telehealth and the challenges and barriers of
adoption of telehealth among primary care providers were briefly discussed. Community
hospitals and the the role primary providers play in the implementation of telehealth technology
within the institution were also discussed.
Telehealth technology has the potential to meet the many challenges faced in the
delivery of healthcare. Telehealth, often referred to as telemedicine and e-health, is the use of
communication tools that enable the remote assessment and treatment of patients by their
providers for the management of diseases and illnesses (McClellan, Florell, Palmer, & Kidder,
2020; Wernhart et al., 2019; Kruse, 2018; Lin et al., 2018; Kruse et al., 2017; Tuckson et al.,
2017; Polinski et al., 2016). Telehealth presents with solutions to patient’s transportations and
geographical issues, as well as physical limitations and family obligations, such as difficulty
finding someone to care for their dependent loved ones while they seek medical care (Dorsey et
al, 2016). Telehealth also improving the quality of the delivery of healthcare, as the technology
can be used to manage chronic diseases and mental illnesses (Meetoo et al., 2018; Dorsey et al.,
2016). Inadequate telehealth-related laws and policies, increasing security breaches in
organizations, complicated telehealth systems, and insufficient organizational training and
support of implemented telehealth systems reflect the barriers to the adoption of telehealth
technology among primary care providers (Edirippulige & Armfield, 2017; de Grood et al.,
2016; Moore et al., 2016). Community hospitals see the benefit of incorporating the use of
telehealth technology and have begun to implement and integrate its use (Singh & Sittig, 2016;

40
Bowles, Dykes, & Demiris, 2015). Physicians are the reason for the low implementation rate of
telehealth technology within community hospitals (Neville, 2018; Tuckson et al., 2017; Adler-
Milstein et al., 2014). There is a lack of studies regarding the adoption of telehealth technology
among primary care providers that work within community hospitals (Harst et al., 2019; Kissi et
al., 2019; Ladan et al., 2018; Rahimi et al., 2018; Shadangi, Kar et al., 2018; Abdekhoda et al.,
2015). The use of TAM and the constructs, along with organizational support constructs, with a
focus on training and support, could help to identify factors that have a relationship with primary
care providers’ decision to accept or reject telehealth technology (Yarbrough & Smith, 2007;
Marler et al., 2006; Gagnon et al., 2005; Gagnon et al., 2003; Hu et al., 1999). The number of
practicing primary care providers are decreasing and accepting telehealth technology will help to
ease some of their frustrations experienced with feeling overloaded (Kissi et al., 2019; Bashur et
al., 2016; Fodeman & Factor, 2015). Community hospitals that have higher rates of primary care
providers that accept telehealth technology have better outcomes for the patients as compared to
hospitals with lower rates (Adler- Milstein et al., 2014). This study will seek to find a statistical
relationship between the intent to use telehealth technology among primary care providers in the
U.S.

41
Chapter 3: Research Method
The problem this research will address is the low acceptance rate of telehealth
technologies among primary care providers that work in a community hospital setting within the
United States (Harst, Lantzsch, & Scheibe, 2019; Ford, Hesse, & Huerta, 2016; Lee & Coughlin,
2015). The purpose of this quantitative correlational study is to identify the factors that influence
the low acceptance rate of telehealth technologies among primary care providers that work in
community hospitals within the United States. TAM will serve as the theoretical framework as it
has been successfully used in a plethora of research studies in the past couple of decades to
determine the factors associated with the acceptance of technology among physicians (Harst,
Lantzsch, & Scheibe, 2019; Kissi et al., 2019; Ladan, Wharrad, & Windle, 2018; Rahimi, Nadri,
Lotfnezhad Afshar, & Timpka, 2018; Shadangi, Kar, Mohanty, & Dash, 2018; Abdekhoda,
Ahmadi, Gohari, & Noruzi, 2015; Rho et al.,, 2014; Dünnebeil, Sunyaev, Blohm, Leimeister, &
Krcmar, 2012; Kim, DelliFraine, Dansky, & McCleary, 2010; Wu, Shen, Lin, Greenes, & Bates,
2008; Yarbrough & Smith, 2007; Hu, Chau, & Sheng, 2002; Hu, Chau, Sheng, & Tam, 1999).
This chapter will provide the details of the proposed research methodology the study. The
research methodology and design will give insight on how the study will be conducted in terms
of data collection, data organization, and data analysis (Abutabenjeh& Jaradat, 2018). The
Population and sample section will introduce the part of the targeted population group that is
being studied (Banerjee & Chaudhury, 2010). Materials or instrumentation will take the reader
through what will be used to gather and analyse the data (Bastos, Duquia, González-Chica,
Mesa, & Bonamigo, 2014). The operational definitions of variables will provide information
about how the abstract concept will be measured. Study procedures will provide the exact steps
that will be used to collect the data. Assumptions, limitations, delimitations sections will explain

42
the three different control aspects of the study (Simon, 2011). Finally, ethical assurances will
discuss the steps taken during the study to protect humans (Vanclay, Baines, & Taylor, 2013). A
summary of the chapter will also be provided.
Research Methodology and Design
This is a correlational and cross-sectional research study that will use the quantitative non-
experimental research design using the methods. As cited in 2017 by Taherdoost Simons’ (2001)
article explained that acceptance of telehealth technology involves the conflict of refusing to use
and deciding to use an innovation and requires an approach that helps readers to understand why
users choose to adopt a technology. Quantitative, non-experimental research design is often used
for studies that focus on the adoption of technology (Chan, Okumus, & Chan, 2020;.Mitzner et
al., 2016; Pedron, Picoto, Dhillon, & Caldeira, 2016;.Teza, Buchele, de Souza, & Aparecida
Dandolini, 2016). Non-experimental, or descriptive research designs are used when subjects will
only be measured one time and the relationship between the variables is sought. Since this
study’s purpose is to identify the factors that influence the low acceptance rate of telehealth
technologies among primary care providers that work in community hospitals within the United
States, constructs will need to be compared, thus the correlational method was chosen.
The correlational design involves testing hypotheses using numerical data and establishing the
degree of their relationship (Quaranta, 2017).
Although the quantitative method was selected for this study, the qualitative or mixed
methods could have also been utilized, however, the quantitative method uses statistics to
analyze the data which improves the reproducibility of the study, can successfully validate and
test previously formulated and assembled theories, and presents facts regarding the presented

43
social phenomena (McLeod, 2019; Zyphur & Pierides, 2019). While qualitative studies could be
appropriate to use for investigating the decision whether an end user will adopt technology or
not, qualitative studies focus on the social aspects of issues and may require more time to
complete since conducting 8 interviews might require less time than collecting 200
questionnaires (McCusker & Gunaydin, 2015). Qualitative methods, according to McLeod
( 2019), do not provide numeric results, rather results that are interpretations of words or
multimedia, and thus would not provide experimental results. Mixed methods, according to
Regnault, Willgoss and Barbic (2017), requires a combination of the quantitative and qualitative
methods along with an experienced researcher, Quantitative research studies include non-
experimental and experimental methods and also quasi-experimental methods. Since
experimental quantitative studies require the application of a treatment to examine the effects of
the treatment (Mertler, 2016), it is not appropriate in this study, since no treatment will be
applied. Non-experimental studies are those in which the researcher cannot manipulate, control
or alter the predictor subjects or variables, rather, relies on observation, interpretation or
interaction to reach a conclusion.
Obsevational techniques are used in qualitative research methods in which the subject or
the target respondent is analyzed and observed in their natural setting. Obersvational reasrch are
mainly applied when other procedures for data ccollection like questionnaires, surveys etc. are
not adequately effective.
Population and Sample
The population of this study includes primary care providers within the United States,
which includes medical professionals who can diagnose patients and provide a treatment plan
like medical physicians, physicians’ assistant, and nurse practitioners, as well as primary care

44
providers that work in a medical facility, and actively practice in the United States of America..
The purpose of this quantitative correlational study is to identify the factors that influence the
low acceptance rate of telehealth technologies among primary care providers that work in
community hospitals within the United States (Harst, Lantzsch, & Scheibe, 2019; Ford, Hesse, &
Huerta, 2016; Lee & Coughlin, 2015).
The participants chosen must indicate that they have received training on the telehealth
technology before using it. The participants must have at least five years of experience of
practicing with their current credential so that they have a greater exposure and experience that
wil beneficial for the study. Both men and women of any ethnicity are elgible. Participants must
have access to a device that has access to the internet (i.e. smartphone, tablet, laptop, or desktop)
in order to fill the survey. The respondents will be needed to provide their consent to take the
survey and wish to give their views on the adoption of telehealth technology.
A sample size estimation of 74 was obtained using G*Power 3.1 software (Faul,
Erdfelder, Buchner, & Lang, 2009). The input parameters were one-tail test- ANOVA, the effect
size was 0.15, alpha error probability was 0.05, power beta error probability was 0.95, and the
number of predictors was 2. An online survey administrator, Google Forms, will be used to
present participants with the survey. Participants will be recruited via e-mail which will include a
link to complete the web-based questionnaire. Sampling will be done after screening the
participants and the whole screening process will be completed in a fairly short amount of time
(Valerio et al., 2016; Bujang et al., 2012). Systematic sampling uses probability sampling, but
requires more time due to reach needed sample size (Bujang et al., 2012). Since this study will
only be one month, the number of respondents desired will need to be reached as soon as
possible.

45
Materials or Instrumentation
An online survey administration app (Google Forms) will be used to collect completed
surveys by primary care providers within the United States. Google Forms offer an unlimited
number of respondents, collects survey answers in an organized manner in a spreadsheet, and is
free (Vasantha & Harinarayana, 2016). Google Forms provides a weblink that can be imbedded
into websites and e-mails (Vasantha & Harinarayana, 2016). The link will be posted The
questions on the survey that are used to identify the acceptance of telehealth technology among
the primary care providers are derived from the original TAM instrument used in Davis’ 1989
study. The TAM survey instrument has been successfully used in other studies that sought to
investigate physicians’ acceptance of telehealth technology (Kissi et al., 2019; Rho et al., 2014;
Yarbrough & Smith, 2007; Whitten, Doolittle, & Mackert, 2005) and assess the perceived ease
of use and perceived usefulness of technology in the healthcare field. Questions in this study that
are from Tam are tailored to apply to telehealth. The questions used to identify organizational
issues, with an emphasis on training, are derived from Marler et al.’s 2006 study. The authors
extended TAM with constructs that included training on technology in organizations with
mandated implementations of technology. Training reactions (TR) and employee resources (ER)
constructs from Marler et al.’s post-training survey are used. TR provides information about the
end users perception of how effective the technology training was; while ER, originally from
Mathieson et al., 2001, provides information on the end users perception of post-training
available effective and useful resources. Marler et al.’s TR constructs have also been used in
other adoption of technology studies since their study (Harris, Mills, Fawson, & Johnson, 2018;
Zumraha, Khalidb, Alic, & Mokhtar, 2016).

46
Rho et al (2014) indicated several respondent characteristics to test for the intent to use, but
only the applicable demographics and descriptive information will be collected such as gender,
age, hospital type, type of medical group, and the regional location of the hospital. All
demographic data are collected at the beginning of the survey. A 5-point Likert scale will be
used to measure the questions. The degree of agreement and organizational support anchors are
used for the responses. The degree of agreement responses range from strongly disagree to
strongly agree (1=Strongly Disagree to 5=Strongly Agree). Several survey questions are
assigned to each category of primary questions. The degree of agreement and organizational
support anchors are used for the responses. The included questions provide a concise
measurement of the question being measured. The amount of time it takes to complete the survey
will be tested by and provided to participants as the average time it takes to complete the online
survey. Revilla & Ochoa (2017) suggested keeping the time it takes to complete an online survey
between 10 and 20 minutes. The timeframe for the survey would be for four weeks. Participants
will be assured that their information will be kept confidential and no personal identifying
information, such as name or address, will be collected (Yip, Han, & Sng, 2016).
Checklist:
☐ Describe the instruments (e.g., tests, questionnaires, observation protocols) that will be
(proposal) or were (manuscript) used, including information on their origin and evidence
of their reliability and validity.
☐ Describe in detail any field testing or pilot testing of instruments to include their
results and any subsequent modifications.
☐ Include evidence permission was granted to use the instrument(s) in an appendix.

47
Operational Definitions of Variables
The questions on the acceptance of telehealth technology questionnaire related to the
PEU and PU factors of the study within the survey instrument are derived from the initial TAM
instrument (Davis, 1989), and are further supported by previous research studies on the adoption
of telemedicine and telehealth (Yarbrough & Smith, 2007; Whitten, Doolittle, & Mackert, 2005).
XXX. Text…
Checklist:
☐ For quantitative and mixed methods studies, identify how each variable will be
(proposal) or was (manuscript) used in the study. Use terminology appropriate for the
selected statistical test (e.g., independent/dependent, predictor/criterion, mediator,
moderator).
☐ Base the operational definitions on published research and valid and reliable
instruments.
☐ Identify the specific instrument that will be (proposal) or was (manuscript) used to
measure each variable.
☐ Describe the level of measurement of each variable (e.g., nominal, ordinal, interval,
ratio), potential scores for each variable (e.g., the range [0–100] or levels [low, medium,
high]), and data sources. If appropriate, identify what specific scores (e.g., subscale
scores, total scores) will be (proposal) or were (manuscript) included in the analysis and
how they will be (proposal) or were (manuscript) derived (e.g., calculating the sum,
difference, average).

48
Study Procedures
No survey incentives are offered. Each respondent will be assigned a code that begins with a
number preceeded by PPC-. Once the study period ends, the surveys will be collected from the
online surveys.
Checklist:
☐ Describe the exact steps that will be (proposal) or were (manuscript) followed to
collect the data, addressing what data as well as how, when, from where, and from whom
those data will be (proposal) or were (manuscript) collected in enough detail the study
can be replicated.
Data Collection and Analysis
Data collection allows the researchers to explain the phenomenon. The study will include
the collection of data via a Likert-type questionnaire as opposed to the researcher performing an
interview or collecting data via visual observation. The data will only be collected at one single
instance. Using an instrument to collect the data will provide a way to measure the results. Data
collection can be done either through face-to-face interviews or through the presentation of a
self-administered questionnaire, usually in the form of scales (Leeuw, 2008). Instruments are
presented to a sample population over a select period of time and then analyzed. Once the one-
time, questionnaire surveys are completed, SPSS v25 statistical software will be used to provide
one-way ANOVA analysis of the collected data.
Checklist:
☐ Describe the strategies that will be (proposal) or were (manuscript) used to code and/or
analyze the data, and any software that will be (proposal) or was (manuscript) used.

49
☐ Ensure the data that will be (proposal) or were (manuscript) collected and the analysis
can be used to answer the research questions and/or test the hypotheses with the ultimate
goal of addressing the identified problem.
☐ Use proper terminology in association with each design/analysis (e.g., independent
variable and dependent variable for an experimental design, predictor and criterion
variables for regression).
☐ For quantitative studies, describe the analysis that will be (proposal) or was
(manuscript) used to test each hypothesis. Provide evidence the statistical test chosen is
appropriate to test the hypotheses and the data meet the assumptions of the statistical
tests.
☐ For qualitative studies, describe how the data will be (proposal) or were (manuscript)
processed and analyzed, including any triangulation efforts. Explain the role of the
researcher.
☐ For mixed methods studies, include all of the above.
Assumptions
Begin writing here…The participants are liscensed in the state that they represent.
Respondents will answer the survey questionnaire honestly and without bias. The respodents will
not share survey with affiliates and coerce others into providing directed answers. Respondents
are able to comprehend the English language. Respondents will complete the survey in its
entirety.
Checklist:
☐ Discuss the assumptions along with the corresponding rationale underlying them.

50
Limitations
Online surveys offer advantages as well as disadvantages to the research process.
Online surveys offer financial relief as they are often cost effective and easy to generate
participants, but participants may experience access issues, deleted invitational posts to complete
the survey, and incomplete surveys due to interruptions (Wright 2017). Researchers are able to
collect data and perform analysis while assuring the targeted sample size is attained during the
timeframe (Wright, 2017). The structure of research questions may cause participants to have
bias or answer questions that are misleading (Wright, 2017).
Correlational studies, according to Mitchell (1985) do not share the same level of validity as
experimental designs in that the correlational design includes multiple issues with construct
validity (validating measures), issues with the validity of the statistical conclusions, internal, and
external validities. Zaki (2012) indicated that the respondents’ characteristics might have an
effect on the responses to the questions, the environment where the questionnaire is administered
may influence the response, the level of understanding and cultural background may alter the
respondents perception of the understanding of the questions, and bias in the verbiage of the
questionnaire that may lead the respondent to answer a certain way. According to Valerio et al.,
2016, convenience sampling May result in homogeneous sampling frame. Limited
generalizability to broader (
population. Less rigorous if organizations or partners do not follow a process to identify
participants. also the results can only be generalized to a population that is represented by the
convenience sample obtained. by

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Costanza, D. P., Blacksmith, N., & Coats, M. (2015). Convenience Samples and Teaching
Organizational Research Methods. TIP: The Industrial-Organizational Psychologist, 53(1), 137–
140.)
Checklist:
☐ Describe the study limitations.
☐ Discuss the measures taken to mitigate these limitations.
Delimitations
Begin writing here…
Checklist:
☐ Describe the study delimitations along with the corresponding rationale underlying
them.
☐ Explain how these research decisions relate to the existing literature and
theoretical/conceptual framework, problem statement, purpose statement, and research
questions.
Ethical Assurances
Once the Institutional Review Board (IRB) approves the plan for the study, the collection
of the data can begin. Begin writing here…
Checklist:
☐ Confirm in a statement the study will (proposal) or did (manuscript) receive approval
from Northcentral University’s Institutional Review Board (IRB) prior to data collection.
☐ If the risk to participants is greater than minimal, discuss the relevant ethical issues
and how they will be (proposal) or were (manuscript) addressed.

52
☐ Describe how confidentiality or anonymity will be (proposal) or was (manuscript)
achieved.
☐ Identify how the data will be (proposal) or were (manuscript) securely stored in
accordance with IRB requirements.
☐ Describe the role of the researcher in the study. Discuss relevant issues, including
biases as well as personal and professional experiences with the topic, problem, or
context. Present the strategies that will be (proposal) or were (manuscript) used to prevent
these biases and experiences from influencing the analysis or findings.
☐ In the dissertation manuscript only, include the IRB approval letter in an appendix.
Summary
The problem this research will address is the low acceptance rate of telehealth
technologies among primary care providers that work in a community hospital setting within the
United States (Harst, Lantzsch, & Scheibe, 2019; Ford, Hesse, & Huerta, 2016; Lee & Coughlin,
2015). The purpose of this quantitative correlational study is to identify the factors that influence
the low acceptance rate of telehealth technologies among primary care providers that work in
community within the United States.Begin writing here…
Checklist:
☐ Summarize the key points presented in the chapter.
☐ Logically lead the reader to the next chapter on the findings of the study.

53
Chapter 4: Findings
Begin writing here…
Checklist:
☐ Begin with a brief overview of the purpose of the study and the organization of the
chapter.
☐ Organize the entire chapter around the research questions/hypotheses.
XXX of the Data
Begin writing here…
Checklist:
☐ For qualitative studies, clearly identify the means by which the trustworthiness of the
data was established. Discuss credibility (e.g., triangulation, member checks),
transferability (e.g., the extent to which the findings are generalizable to other situations),
dependability (e.g., an in-depth description of the methodology and design to allow the
study to be repeated), and confirmability (e.g., the steps to ensure the data and findings
are not due to participant and/or researcher bias).
☐ For quantitative studies, explain the extent to which the data meet the assumptions of
the statistical test and identify any potential factors that might impact the interpretation of
the findings. Provide evidence of the psychometric soundness (i.e., adequate validity and
reliability) of the instruments from the literature as well as in this study (as appropriate).
Do not merely list and describe all the measures of validity and reliability.
☐ Mixed methods studies should include discussions of the trustworthiness of the data as
well as validity and reliability.

54
Results
Begin writing here…
Checklist:
☐ Briefly discuss the overall study. Organize the presentation of the results by the
research questions/hypotheses.
☐ Objectively report the results of the analysis without discussion, interpretation, or
speculation.
☐ Provide an overview of the demographic information collected. It can be presented in
a table. Ensure no potentially identifying information is reported.
Research question 1/hypothesis. Text…
☐ Report all the results (without discussion) salient to the research question/hypothesis.
Identify common themes or patterns.
☐Use tables and/or figures to report the results as appropriate.
☐ For quantitative studies, report any additional descriptive information as appropriate.
Identify the assumptions of the statistical test and explain how the extent to which the
data met these assumptions was tested. Report any violations and describe how they were
managed as appropriate. Make decisions based on the results of the statistical analysis.
Include relevant test statistics, p values, and effect sizes in accordance with APA
requirements.
☐ For qualitative studies, describe the steps taken to analyze the data to explain how the
themes and categories were generated. Include thick descriptions of the participants’
experiences. Provide a comprehensive and coherent reconstruction of the information
obtained from all the participants.

55
☐ For mixed methods studies, include all of the above.
Evaluation of the Findings
Begin writing here…
Checklist:
☐ Interpret the results in light of the existing research and theoretical or conceptual
framework (as discussed in Chapters 1 and 2). Briefly indicate the extent to which the
results were consistent with existing research and theory.
☐ Organize this discussion by research question/hypothesis.
☐ Do not draw conclusions beyond what can be interpreted directly from the results.
☐ Devote approximately one to two pages to this section.
Summary
Begin writing here…
Checklist:
☐ Summarize the key points presented in the chapter.

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Chapter 5: Implications, Recommendations, and Conclusions
Begin writing here…
Checklist:
☐ Begin with a brief review of the problem statement, purpose statement, methodology,
design, results, and limitations.
☐ Conclude with a brief overview of the chapter.
Implications
Begin writing here…
Checklist:
☐ Organize the discussion around each research question and (when appropriate)
hypothesis individually. Support all the conclusions with one or more findings from the
study.
☐ Discuss any factors that might have influenced the interpretation of the results.
☐ Present the results in the context of the study by describing the extent to which they
address the study problem and purpose and contribute to the existing literature and
framework described in Chapter 2.
☐ Describe the extent to which the results are consistent with existing research and
theory and provide potential explanations for unexpected or divergent results.
Recommendations for Practice
Begin writing here…
Checklist:

57
☐ Discuss recommendations for how the findings of the study can be applied to practice
and/or theory. Support all the recommendations with at least one finding from the study
and frame them in the literature from Chapter 2.
☐ Do not overstate the applicability of the findings.
Recommendations for Future Research
Begin writing here…
Checklist:
☐ Based on the framework, findings, and implications, explain what future researchers
might do to learn from and build upon this study. Justify these explanations.
☐ Discuss how future researchers can improve upon this study, given its limitations.
☐ Explain what the next logical step is in this line of research.
Conclusions
Begin writing here…
Checklist:
☐ Provide a strong, concise conclusion to include a summary of the study, the problem
addressed, and the importance of the study.
☐ Present the “take-home message” of the entire study.
☐ Emphasize what the results of the study mean with respect to previous research and
either theory (PhD studies) or practice (applied studies).

58
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Appendices

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Appendix B: XXX
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