Multivariate Approaches

In preparation for this assignment, read the Telebehavioral Health (TBH) Use Among Rural Medicaid Beneficiaries: Relationships With Telehealth Policies article located in the Topic 3 Resources.

Write a 750-1,000-word paper about your selected article. Be sure to include the following in your paper:

A discussion about the key variables in the selected article

Identify the validity and reliability reported statistics for the article

The particular threats to internal validity that were found in the study

The strengths and limitations of the multivariate models used in the selected article

A reference and in-text citations for the selected article as well as one additional reference


Multivariate Approaches

In the article “Telebehavioral Health (TBH) Use Among Rural Medicaid Beneficiaries: Relationships with Telehealth Policies,” Talbot et al. (2020) examined the relationship between Medicaid telehealth policies and telebehavioral health (TBH) use in rural fee-for-service beneficiaries with behavioral health needs. Also, the researchers investigated the association between beneficiaries’ characteristics and telebehavioral health use. It is essential to note that people in rural areas are more susceptible to behavioral health issues such as serious mental illnesses (SMI), suicide, and substance overdose deaths compared to people in urban areas. According to Morales et al. (2020), disparities in mental health among people living in underserved, rural areas emanate from various factors, including limited availability of specialty mental health care services, healthcare professionals’ shortages, and infrastructural deficiencies. Therefore, states perceive Medicaid telehealth policies as profound tools for addressing these inequalities and promoting affordable, convenient, and timely care services. As a result, the study by Talbot et al. (2020) reveals the prevailing interrelationships between Medicaid telehealth policies and telebehavioral health use (TBH), providing opportunities for empirically testing the effectiveness of these policies in addressing mental health inequalities in rural areas.

Variables in the Selected Article

The researchers aimed at investigating the associations between various outcomes and explanatory variables, alongside multiple covariates. According to Tolbat et al. (2020), the principal outcome variable was the telebehavioral health (TBH) use among Medicaid benefits who use outpatient behavioral health services (OP BHS). On the other hand, explanatory variables used in the study were telehealth policies in state Medicaid programs. In this sense, the researchers used the state-level policy information from the Center for Telehealth and e-Health Law (CTeL) to classify Medicaid Beneficiaries based on state Medicaid programs. The classification of beneficiaries consistent with the types of state Medicaid programs yielded a four-level variable containing the following aspects: enrollment for programs with neither policy, an informed consent requirement without a facility fee policy, a facility fee policy without an informed consent requirement, and both policies (Tolbat et al., 2020). Finally, the study included various covariates including individual, country, and state-level variables that influence telebehavioral health use (TBH).

The Validity and Reliability of the Reported Statistics for the Article

The study exhibited multiple aspects that contributed to the validity and reliability of the Reported statistics. Firstly, the researchers utilized chi-square tests to determine the association between TBH use and two Medicaid telehealth policies of interest and the selected covariates. According to Nihan (2020), the chi-square test is a profound statistical approach for revealing any correlation among non-numeric variables. Therefore, applying this statistical method enabled investigators to determine the interplay between explanatory and outcome variables, alongside different covariates. Apart from using chi-square tests to determine the relationship between TBH use and Medicaid telehealth policies of interest, the researchers performed contrast analyses to specify the nature of interactions. Allen (2017) argues that contrast analysis can provide additional insights into group differences and enable researchers to contrast coefficients to determine whether these differences reflect in the data. Undoubtedly, these approaches contributed to the study’s validity and reliability.

Threats to Internal Validity in the Study

Although the study is internally valid, the researchers identified possible threats to internal validity. For instance, one of these threats was the inclusion criteria that excluded people with dual eligibility and Medicaid-managed care. Also, investigators excluded older Medicaid beneficiaries. Therefore, the subsequent findings are not generalizable to rural OP BHS excluded from the study (Talbot et al., 2020, p. 228). Secondly, the researchers used a cross-sectional study design that only established the causal relationships between explanatory variables, covariates, and the major outcome variable (TBH) use. Therefore, the study’s findings do not support definitive conclusions.

The Strengths and Limitations of the Multivariate Models Used in the Article

The multivariate strategies used in demonstrate strengths and weaknesses tool. The most profound strength of the study’s approaches is the ability to produce results consistent with the research hypotheses. According to Mishra et al. (2021), multivariate approaches reduce the probability of type-1 error because they accommodate extra information contained in the associations among variables. Therefore, utilizing these models enhanced the study’s scope. In terms of limitations, the researchers only studied two Medicaid telehealth policies due to the information constraints for the other policies. Secondly, the applied research design only established the causal relationships between explanatory and outcome variables instead of informing a definitive conclusion. Therefore, additional research is necessary to establish the relationships between the unstudied Medicaid telehealth policies and TBH use.


Studying the associations between telebehavioral health use and different state-level Medicaid telehealth policies is essential in determining how these policies influence the utilization of telehealth services among people living in remote, underserved areas. Also, it is an ideal strategy for determining effective policies for addressing health inequalities in rural communities regarding behavioral and mental health. The scholarly article “Telebehavioral Health (TBH) Use Among Rural Medicaid Beneficiaries: Relationships with Telehealth Policies” provides findings from a cross-sectional study conducted to establish the correlations between state Medicaid telehealth policies and TBH use. Although researchers used multivariate models to analyze data and establish coefficients, various limitations hampered the study’s validity and generalizability. Therefore, further research on the topic is necessary to provide more generalizable contentions and definitive conclusions.


Allen, M. (2017). The SAGE encyclopedia of communication research methods (Vols. 1–4). Sage.

Mishra, A., Harichandrakumar, K. T., VS, B., Satheesh, S., & Nair, N. S. (2021). The multivariate approach in analyzing medical data with correlated multiple outcomes: An exploration using ACCORD trial data. Clinical Epidemiology and Global Health, 11, 100785.

Morales, D. A., Barksdale, C. L., & Beckel-Mitchener, A. C. (2020). A call to action to address rural mental health disparities. Journal of Clinical and Translational Science, 4(5), 1–20.

Nihan, S. T. (2020). Karl Pearson’s chi-square tests. Educational Research and Reviews, 15(9), 575–580.

Talbot, J. A., Jonk, Y. C., Burgess, A. R., Thayer, D., Ziller, E., Paluso, N., & Coburn, A. F. (2020). Telebehavioral health (TBH) use among rural Medicaid beneficiaries: Relationships with telehealth policies. Journal of Rural Mental Health, 44(4), 217–231.

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