5 powerpoint slides (Group Review Synthesis Project)

Description of the Theories or Conceptual Framework

The theoretical frameworks outlined in this project include the Information Motivation Behavioral Skills Model (IMB), the Health Belief Model (HBM). The IMB construct is defined as an initial prerequisite for enacting a health behavior and it includes not only information on the health-related behavior but also on the cognitively effortless decision-making (Chang, 2014). Motivation is seen as having two components, personal motivation which is about the belief on the intervention outcome and attitudes towards a particular behavior and social support which is the perceived social support for the engaging in the behavior. Behavioral skills are those necessary for performing a particular behavior. The IMB has been used for adherence and compliance to medications for chronic and lifestyle health conditions like hypertension, diabetes, obesity, and HIV/AIDS. This theoretical framework was used by Nelson et al. in 2018 to predict the patients’ self-medication adherence and HbA1c reduction levels.

The Health Belief Model (HBM) suggests that a person’s belief in a personal threat of an illness or disease together with a person’s belief in the effectiveness of the recommended health behavior will predict the likelihood that the person will adopt the behavior (LaMorte, 2019). The HBM emphasizes that an individual’s course of action will be determined by his perception of the benefits and barriers related to the health behavior. The constructs in HBM include perceived susceptibility which is about perceived risk if behavior is not performed, perceived severity referring to severity of consequence of not performing behavior, perceived benefits are rewards expected from performing the behavior, perceived barriers are hindrances to taking the action, cues to action is stimulus or trigger that makes behavior change inevitable like symptoms or complications from the disease, and self-efficacy refers to the level of confidence in ability to make a behavioral change. The HBM was used by Shabibi and colleagues in 2017 for promotion of self-care behaviors in individuals with diabetes especially medication compliance.

Conceptual frameworks within the field of public health are tools to illustrate the relationships between health exposures, and outcomes (Paradies & Stevens, 2005). In this project, the conceptual frameworks used include the investigation on the racial disparities in the providence of quality primary care to American citizens living with Type 2 Diabetes (Hu, 2016). Its objectives are to explore the existence of ethnic disparities, such as access to proper care, compliance, and mortality rate, and equality of diabetes among citizens (Hashimoto, 2019). Others include the effect of patient and medical providers' differing perceptive on non-compliance with medication given (Mayberry, 2016). The relationship between a patient suffering from Type 2 Diabetes and inconsistence to medication (Brundisini, 2015). Other articles focus on inequalities among old people living with Type 2 Diabetes in providing selfcare, the existence of racial inequality on medication compliances among Type 2 Diabetes in the use of mHealth technology for the notification (Nelson, 2015). Another conceptual model used, is the Group-Based Trajectory model, which identifies subgroups of patients with similar patterns of medication refills, to determine adherence within a particular population or group (Lo-Ciganic, 2016). Through application of this conceptual framework, understanding which populations are at risk for poor medical adherence can help to create programs or change policies within different geographical locations.

Methods

The methods used to perform this literature review of whether minorities have reduced medication compliance in patients with Type II Diabetes included systematic literature review, retrospective cohort studies, as well as cross sectional studies.

Systematic literature review was performed in studies by Agarwal et al. (2018), Mayberry et al. (2016), and Adams et al. (2015). Agarwal and colleagues reviewed the literature on care and outcome disparities in young adults in rural and urban areas (2018). Search included collection of articles from Psychological Aspects Journal while the keywords were young adults, type 1 diabetes, type 2 diabetes, health disparities, health outcomes, emerging adult, adolescent. Agarwal et al. concluded that childhood trauma can lead to poor treatment adherence of diabetes in young adults and care utilization may not be different among young adults in both rural and urban settings (2018).

Mayberry et al. (2016) used literature review to synthesize knowledge on current self-care behavior disparities in individuals with diabetes. Search included Medline/Pubmed published on self-care disparities 5 years before start of study and 25 papers were eventually studied. The keywords were type 2 diabetes, African American, Hispanic/Latino, disparities, adherence and self-care. They concluded that SES and geographic location modified the association between race/ethnicity and self-care and self- care disparities persisted in both rural and urban settings in almost the same magnitude. Adams et al. (2015) also used literature review to examine whether diabetes medication adherence is suboptimal among disparities populations. Search included comprehensive search of PubMed database from 2007 to 2014, 38 articles that provided persistent evidence of persistent disparities in compliance were studied. Keywords included diabetes, medication, race, adherence, compliance. Conclusions were race and ethnic differences persist across various settings including geographical location, disparities in medication compliance persist across a broad range of racial, ethnic populations, and addressing disparities in medication compliance for diabetes medications has the potential to reduce disparities in diabetes control and mortality.

Retrospective cohort analysis was used by Patel et al. (2016), Blumberg & Warren (2014), and Buja et al. (2014). Patel and colleagues (2015) employed retrospective study using MarketScan Multi-State Medicaid Database to examine the racial health disparities in medication compliance and medication persistence developmentally disabled adults with type 2 diabetes enrolled in Medicaid. Chronic disease conditions were diagnosed by ICD-9-CM, medication adherence was measured by Medication Procession Ratio (MPRm), and medication persistence was measured from initiation to discontinuation of therapy. There was no difference regarding geographical location in terms of medical compliance in patients having developmental disability (DD) with T2DM.

Blumberg and Warren (2014) used retrospective cohort to examine factors contributing to disparate healing and amputation rates of diabetic foot ulcers in a study involving 234 patients newly diagnosed of diabetes foot ulcer at geographically adjacent but independent public, private, and Veteran Hospitals. ICD-9-CM and Current Procedural Terminology codes were used to identify patients with diabetes, foot ulcers, and lower extremity amputations while healing was measured by skin closure and lower extremity amputation (LEA). VA hospitals had highest amputation rate (23.5%), much older patients, presented advanced degree of diabetes foot ulcer progression. Public hospitals had most poorly controlled diabetic patients, highest healing rate. Private hospital patients had lowest amputation rate, shortest time to amputation, malnourished, had the largest wound area presentation. The findings are devoid of differences in geographical location.

Buja et al. in 2014 conducted a retrospective cohort study involving diabetic 105,987 participants. Data obtained from Valore datasets using algorithms prepared by Tuscany Regional Public Health Agency. Compliance with standards of care was assessed on the basis of adherence to at least one HbA1c test a year, screening for nephropathy at least one year, and at least one LDL cholesterol test a year. Adherence to these requirements was estimated from administrative databases regarding drug prescriptions and diagnostic service usage. Adherence to all management indicators for diabetes was slightly better for females than males with the female gender having 10% higher odds of undergoing renal function tests. There was no such difference between the urban and rural dwellers regarding treatment adherence.

Cross-sectional study method was used by Nelson et al. (2018). It was a study of 237 diabetic participants being followed to identify barriers to adherence to management. Information-Motivational-Behavioral skills model (IMB) to assess patient-reported barriers to medication adherence. Associations were found between identified barriers and patients characteristics using the IMB constructs. Younger age and lower health literacy were associated with higher barrier scores. IMB barrier constructs explained 44% of variance in diabetes medication adherence. Disparities exist in geographical location in terms of barrier to medication scores.

Strengths and Limitations of Methods

The strength in performing a systematic literature review include pooling of analyses from numerous and similar studies together. It is a high form of evidence which helps experts to form an agreement on a particular subject (MacGill, 2019). When systematic reviews are conducted with a set definition of the research question including population, intervention, exposures and outcomes of interest, bias may be reduced due to the robust nature of the research (Drucker, 2016). It is also helpful to determine whether a certain technique works or not and identifies knowledge gaps for further research. Limitations include difficulty in merging different study designs as researchers may have differ in the number of participants, length of study, and statistical approach.

Retrospective cohort studies like other cohort studies have advantages which include gathering data based on the sequence of events. It can also be used to assess causality. Researchers are able to examine multiple outcomes for a given exposure, investigate rare exposures, and calculate rates of disease in exposed and unexposed individuals over time. These rates include incidence, relative risk, risk difference, and attributable risk percentage (Song & Chung, 2010). Retrospective studies have some limitations. There is usually absence of data on confounding factors and available data on which the study is based may be of poor quality. It may be difficult to identify an appropriate exposed cohort and comparison group. Retrospective studies are susceptible to recall bias or information bias (LaMorte, 2016).

Cross-sectional studies have strengths which include being used to prove or disprove assumptions, they are not costly and does not take time (Rivers, 2018). They also contain multiple variables at the time of the data snapshot and the data can be used for various types of research. Cross sectional studies allow for the selection subjects based on inclusion and exclusion criteria as compared to outcome status within case-control studies or exposure status as in cohort studies (Setia, 2016). Many outcomes and findings can be analyzed to create new theories. Cross-sectional studies are limited in that they cannot be used to analyze behaviors over a period of time and does not help to determine cause and effect. Findings can be flawed or skewed if there is a conflict of interest.

References

Adams, A. S. Banerjee, S., & Ku, C. J. (2015). Medication adherence and racial differences in diabetes in the USA Diabetes Management 5(2), 79-87. doi:10.2217/DMT.14.55

Agarwal, S., Hilliard, M. & Butler, A. (2018). Disparities in care delivery and outcomes in young adults with diabetes Current Diabetes Reports. 18(65). https://doi.org/10.1007/s.11892-018-1037-x

Baju, A., Gini, R., Visca, M., Damiani, G., Federico, B., …………. Donato, D., (2014) Need and disparities in primary care management of diabetes with diabetes BMC Endocrine Disorders 14(56). https://doi.org/10.1186/1472-6823-14-56

Blumberg, S. N. & Warren, S. M. (2014) Disparities in initial presentation and treatment of diabetic foot ulcers in public, private, Veterans Administration hospital Journal of Diabetes 6, 68-75. doi:10.1111/1753/0407.12050

Brundisini, F., Vanstone, M., Hulan, D., DeJean, D., & Giacomini, M. (2015). Type 2 diabetes patients’ and providers’ differing perspectives on medication nonadherence: a qualitative meta-synthesis. BMC health services research, 15(1), 516.

Drucker, A.M., Fleming, P., Chan, A.W. (2016). Research techniques made simple: assessing

risk of bias in systematic reviews. Journal of Investigative Dermatology. 136(11), 109-114. doi: 10.1016/j.jid.2016.08.021.

Hu, R., Shi, L., Liang, H., Haile, G. P., & Lee, D. C. (2016). Racial/Ethnic Disparities in Primary Care Quality Among Type 2 Diabetes Patients, Medical Expenditure Panel Survey, 2012. Preventing chronic disease, 13, E100-E100. https://www.cdc.gov/pcd/issues/2016/16_0113.htm

LaMorte, W. W. (2019). Health belief model Retrieved from http://sphweb.bumc.bu.edu/otlt/MPH-Modules/SB/BehavioralChangeTheories/BehavioralChangeTheories2.html

Lo-ciganic, W.H., Donohue, J.M., Jones, B.L, Perera, S., Thorpe, J.M., Thorpe, C.T., Marcum,

Z.A., Gellad, W.F. (2016). Trajectories of diabetes medication adherence and hospitalization risk: A retrospective cohort study in a large state Medicaid program. Journal of General Internal Medicine. 31(9), 1052-1060. doi: 10.1007/s11606-061-3747-6

MacGill, M. (2019). What is a systematic review in research? Reviewed from https://www.medicalnewstoday.com/articles/281283.php

Mayberry, L. S., Bergner, E. M., Chakkalakal, R. J., Elasy, T. A., & Osborn, C. Y. (2016). Self-care disparities among adults with type 2 diabetes in the USA. Current diabetes reports, 16(11), 113. https://link.springer.com/article/10.1007/s11892-016-0796-5

Nelson, L. A., Mulvaney, S. A., Gebretsadik, T., Ho, Y. X., Johnson, K. B., & Osborn, C. Y. (2015). Disparities in the use of a mHealth medication adherence promotion intervention for low-income adults with type 2 diabetes. Journal of the American Medical Informatics Association, 23(1), 12-18.

Nelson, L. A., Wallson, K. A., Kripalani, S., LeSteguron, L. M., Williamson, E. M., ……… Mayberry, L. S. (2018). Assessing barriers to diabetes medication adherence using the Information-Medication- Behavioral skills model Diabetes Research and Clinical Practice 142, 374-384. https://doi.org/10.1016/diabres.2018.05.046

Paradies, Y., Stevens, M. (2005). Conceptual diagrams in public health research. Journal of

Epidemiology and Community Health. 59, 1012-1013. doi: 10.1136/jech.2005.036913.

Patel, I., Erickson, S. R., Caldwell, C. H., Woolford, S. J., Bagozi, R. P., …….. Balkrishman, R. (2016). Predictors of medication adherence and persistence in Medicaid enrollees with developmental disabilities and type 2 diabetes Research in Social and Administrative Pharmacy 12, 596-603. http://dx.doi.org/10.1016/j.sapharm.2015.09.008

Rivers, J. (2018). Cross-sectional study defined Retrieved from https://study.com/academy/lesson/cross-sectional-study-definition-advantages-disadvantages-example.html

Setia, M.S. (2016). Methodology series module 3: Cross-sectional studies. Indian Journal of

Dermatology. 61(3), 261-264. doi:10.4103/0019-5154.182410.

Song, J. W. & Chung, K. C. (2010). Observational studies: Cohort and case control studies Plast Reconstr Surg. 126(6), 2234-2242. doi:10.1097/PRS.0b013e3181f44abc