Multivariate Approaches

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Multivariate Approaches Aylin Estrada College of Humanities and Social Sciences, Grand Canyon University CNL-540: Research Methods and Program Evalution Dr. Lucas June 14, 2023 1

Multivariate Approaches Examining and understanding the different models and methodologies used by counseling researchers is important for future counselors to understand in order to get the most out of a scholarly article. The design of a study is the foundation for establishing the extent of differences that may or may not exist between groups. Particular attention must be paid to the procedures counseling researchers use to establish that the differences found between groups are valid (Balkin & Kleist, 2022). The article "Telebehavioral Health (TBH) Use Among Rural Medicaid Beneficiaries: Relationships With Telehealth Policies" explores the relationship between telehealth policies and the use of telebehavioral health (TBH) services among rural Medicaid beneficiaries. This analysis aims to evaluate the methodology employed in the study, shedding light on the data collection, statistical analysis, and potential limitations that affect the reliability and validity of the findings. Key Variables In the article, researchers examine the utilization of telebehavioral health (TBH) services among rural Medicaid beneficiaries and its association with telehealth policies. The study investigates how policy factors, such as reimbursement, coverage, and network adequacy, influence the adoption and use of TBH services in rural areas. The researchers conducted a multivariate analysis using Medicaid claims data from rural areas in the United States. They assessed the telehealth policies of each state and analyzed the relationship between these policies and TBH service utilization among Medicaid beneficiaries (Talbot et al., 2020). The key variables of the article include telebehavioral health use, rural Medicaid beneficiaries, telehealth policies, reimbursement rates, coverage policies, and network adequacy. In the study, TBH usage represents the utilization of telebehavioral health services among rural Medicaid beneficiaries. It 2

indicates the extent to which individuals in rural areas are accessing mental health care through telehealth technologies. Rural Medicaid beneficiaries refer to individuals who are enrolled in the Medicaid program and reside in rural areas. The study focuses on this specific population to understand their utilization patterns and access to TBH services. Telehealth policies encompass various policy factors that influence the adoption and use of TBH services. It includes reimbursement rates for telehealth services, coverage policies related to TBH, and network adequacy measures. These policies vary across states and can impact the availability and accessibility of TBH services. The reimbursement rates variable reflects the financial incentives provided to healthcare providers for delivering TBH services. It measures the amount of reimbursement or payment that providers receive for telehealth consultations, which can influence their willingness to offer TBH services. Coverage policies relates to the extent of insurance coverage provided for TBH services. It examines whether telebehavioral health is included in the covered services under Medicaid and the specific conditions or limitations associated with coverage. Lastly, network adequacy assesses the sufficiency and availability of healthcare providers who offer TBH services within a specific geographic area. It measures whether there are enough providers in the network to meet the demand for telebehavioral health services (Talbot et al., 2020). Assessing Validity and Reliability of Reported Statistics Validity refers to the extent to which a study measures what it intends to measure. In the context of reported statistics, it would involve ensuring that the data collected accurately represents the variables being studied. Reliability, on the other hand, refers to the consistency and stability of the measurements or data collected. It assesses whether the results would be 3

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consistent if the study were to be repeated under similar conditions. Researchers establish reliability by using standardized measurement instruments, employing consistent data collection procedures, and conducting statistical analyses to assess the consistency of the results (Balkin & Kleist, 2022). Researchers gathered the data used within the study by accessing Medicaid claims data. When analyzing the statistical data provided by the study, it’s important to take into account the use of administrative data. The use of administrative data offers a comprehensive view of actual healthcare utilization, reducing recall bias associated with self-reported data. However, the study is dependent on the accuracy and completeness of the claims data, and potential biases or errors in documentation could impact the validity of the findings. Although the study employs statistical analyses to assess the relationship between telehealth policies and TBH utilization, the authors of the paper do not explicitly mention any form of statistical techniques used to take into account confounding variables within the study. It’s important to consider the appropriateness of the statistical methods used, including potential confounding variables and control measures, to establish the robustness of the relationships observed. Threats to Internal Validity Potential threats to internal validity within the study include factors such as selection bias, unaccounted for confounding variables, and measurement bias. In regards to selection bias, there may be a potential bias in the selection of participants, such as Medicaid beneficiaries in rural areas. If the sample is not representative of the target population, the generalizability of the findings may be limited. As previously mentioned, there could be uncontrolled or unaccounted confounding variables that influence both the telehealth policies and the utilization of TBH services. These variables can lead to spurious relationships and impact the internal validity of the 4

study. Lastly, measurement bias could result in the lack of accuracy and reliability of the measures used to assess TBH use and other relevant variables, which could affect internal validity (Popovic & Huecker, 2022). Strengths and Limitations of Multivariate Models The strengths of the study lay in its utilization of a large sample of Medicaid claims data from rural areas, allowing for a comprehensive analysis of TBH utilization patterns. Additionally, the inclusion of multiple telehealth policy factors and their associations with TBH utilization enhances the understanding of the complex relationships between policy and service utilization. However, limitations include potential biases in the claims data and lack of statistical techniques used to account for confounding variables, which could impact the internal validity of the study and restrict causal interpretations. Conclusion The article "Telebehavioral Health (TBH) Use Among Rural Medicaid Beneficiaries: Relationships With Telehealth Policies" utilizes a multivariate analysis of Medicaid claims data to explore the relationship between telehealth policies and TBH utilization. While the methodology has notable strengths, including the use of real-world utilization data, it also faces limitations in terms of potential biases in the claims data. Future research should consider addressing these limitations to further enhance the validity and reliability of the findings. 5

References Balkin, R., & Kleist, D. (2022). Counseling research: A practitioner-scholar approach. Wiley. Popovic, A., & Huecker, M. R. (2022). Study bias . PubMed; StatPearls Publishing. https://www.ncbi.nlm.nih.gov/books/NBK574513/ 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). https://doi.org/10.1037/rmh0000160 6

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