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The Social Ecological Model (SEM) provides a framework for multilevel factors affecting health behaviors and impacting health behavior change, as well as a theoretical framework for the interactions between persons and groups (Stokol, 1995). Over the past twenty years, there has been an increasing focus upon disease prevention and changing individual health behaviors to avoid chronic diseases (McLeroy et al., 1988). Health promotion programs have led to community-driven efforts to promote fitness, health eating habits, and non-smoking campaigns (McLeroy et al., 1988). The Social Ecological Model (SEM) conceptual framework is determined by the following: intrapersonal factors; interpersonal processes; institutional factors; community factors; and, public policy (McLeroy, et al., 1988). The Conceptual Model – Social Ecological Model (SEM): Medication adherence and type 2 diabetes, as described by SEM will be included in the poster, if accepted.
Results of Literature Synthesis
The SEM for health promotion addresses the individual and social environmental factors for interventions (McLeroy, Bibeau, Steckler, & Glanz, 1998). SEM is defined by: intrapersonal factors, interpersonal processes, institutional factors, community factors, and public policy. Medication adherence and type 2 diabetes primarily had interventions within the intrapersonal and interpersonal domains, as discussed in the following sections.
Intrapersonal factors.
SEM includes “intrapersonal factors include the individual’s characteristics such as, knowledge, attitudes, self-concept, skills, and etcetera” (McLeroy et al., 1998, p. 355). Additionally, developmental history of the individual is included (McLeroy et al., 1998).
Bains & Egede (2011) conducted a survey of one hundred twenty-five adults with diabetes from a primary care clinic to complete a validated survey assessing health literacy, diabetes knowledge, and self-care. The authors reported that health literacy was independently associated with diabetes knowledge but not associated with glycemic control (Bains & Egede (2011). The authors also found that health literacy did not have a direct correlation to glycemic control, but suggest there is possibly an influence through diabetes knowledge (Bains & Egede, 2011). Cohen et al. (2010) found a strong association between medication adherence, as measured by medication possession ratio, for oral glycemic lowering agents (OGLA) and A1C control among insured diabetes patients with poorly controlled A1C, especially those taking two or more OGLA.
Hernandez-Tejada et al. (2012) found an association between diabetes empowerment and increased medication adherence, increased knowledge, and effective self-care behaviors for participants with type 2 diabetes. Hill-Briggs, et al. (2007) found a correlation among higher Diabetes-related Problem Solving (DPSS) scores being related to better medication adherence and more frequent self-monitoring of blood glucose. DPSS scores above the mean were also associated with better A1C levels (Hill-Briggs et al. 2007).
In their study of diabetes health beliefs among the Lumbee Indians living in rural Southeastern North Carolina, Jacobs, Kemppanen, Taylor, & Hadsell (2014) found that study participants did not hold strong beliefs about their ability to understand the nature of diabetes as a chronic disease (Jacobs, Kemppanen, Taylor, & Hadsell, 2014). The authors also discussed participant’s beliefs about ability to control symptoms and lower confidence in efficacy of treatments (Jacobs, Kemppanen, Taylor, & Hadsell, 2014). Parchman, Zeber, & Palmer (2010) conducted an observational study and found that participatory decision making during primary care encounters by patients with type 2 diabetes resulted in improvements in A1C levels and improved medication adherence. Piette, Heisler, Harand, & Juip (2010) sought to understand the differences between African American and White participants in diabetes patient’s medication related beliefs and adherence problems due to cost concerns. The authors found that significant number of diabetes patients endorsed negative beliefs about their medications including: doctors would prescribe fewer medications if they spent more time with patients; most prescriptions were addictive; and negative beliefs were consistently more common among African-American than White patients (Piette, Heisler, Harand, & Juip, 2010).
Powell, Hill, & Clancy (2007) used the Rapid Estimate of Adult Literacy in Medicine (REALM) literacy instrument prior to completing the Diabetes Health Belief Model (DHBM) scale and Diabetes Knowledge Test (DKT) to 68 eligible participants. The participants were recruited from a general internal medicine clinic that cared for low-income, medically underserved population (Powell, Hill, & Clancy, 2007). There was no significant association between the DHBM scale score and literacy level (Powell, Hill, & Clancy, 2007). Ruelas, Roybal, Lu, Goldman, & Peters (2009) conducted a randomized, prospective study in an underserved, Latino area to establish a disease-management program to determine effectiveness. The results included an overall decrease in A1C by 1% and medication adherence was the strongest predictor (Ruelas, Roybal, Lu, Goldman, & Peters, 2009). Knowledge scores also increased in the group that reached the target A1C score (Ruelas, Roybal, Lu, Goldman, & Peters, 2009). Sarkar, Fisher, & Schillinger (2006) performed a randomized, prospective, observational study in which patients enrolled in the type 2 diabetes program and were measuring self-efficacy, health literacy, and self-management behaviors. The study participants were ethnically diverse and 52% had limited health literacy (Sarkar, Fisher, & Schillinger, 2006). Self-efficacy was associated with self-management behaviors across race/ethnicity and health literacy levels (Sarkar, Fisher, & Schillinger, 2006). Walker et al. (2006) conducted a randomized controlled primary prevention study for type 2 diabetes in the continental U.S. and Hawaii. Participants included 2,155 adults with impaired glucose tolerance that were randomly assigned to a metformin treatment arm or placebo treatment arm.
Interpersonal factors.
McLeroy, Bibeau, Steckler, & Glanz (1998) describe interpersonal factors of SEM as “formal and informal social networks and social support systems including the family, work group, and friendship networks” (p. 355). These relationships can have an impact upon health behaviors in people with type 2 diabetes.
Mayberry & Osborn (2012) conducted a mixed methods study and used focus group session to evaluate perceptions of family members’ self-care knowledge, perceptions of family members’ diabetes-specific supportive and non-supportive behaviors, and participant’s diabetes medication adherence and glycemic control. The results indicated that family members who perform more nonsupportive behaviors reported less adherence to diabetes medications, which was associated with less glycemic control (Mayberry & Osborn, 2012). However, there was no association between family members who performed more diabetes-specific supportive behaviors and medication adherence or glycemic control (Mayberry & Osborn, 2012).
Institutional processes.
A third level of SEM focuses upon institutional processes. This level includes such processes as how organizations support behavior changes, the importance of health promotion activities for behavior change; the importance of organizational support (McLeroy, Bibeau, Steckler, & Glanz, 1998). Institutional processes include formal and informal rules and regulations for operation (McLeroy, Bibeau, Steckler, & Glanz, 1998).
While no studies directly addressed institutional processes, there are study outcomes that impact organizations such as public health. Type 2 diabetes, a chronic disease, impacts healthcare costs and this issue is impacting financial decisions.
Community factors.
A forth level of SEM is community factors which includes “relationships among organizations, institutions, and informal networks within defined boundaries” (McLeroy, Bibeau, Steckler, & Glanz, 1998, p. 355). Community can have multiple meanings including mediating structures that embrace families; relationships among organizations such as volunteer agencies; and, community defined in geographical and community terms (McLeroy, Bibeau, Steckler, & Glanz, 1998).
There are direct and indirect community impacts from type 2 diabetes. Ruelas, Roybal, Lu, Goldman, & Peters, 2009, discuss the establishment of a disease-management program in an underserved, Latino area to determine effectiveness of diabetes interventions is an example of community support. The community impact of this program reaches far beyond the participant. Additionally, Mayberry & Osborn (2012) conducted a study about family support and non-support of diabetes-related behaviors. While this study relates to intrapersonal factors, it also applies to the community factors due to the significant contributions of the discussions created within the community. As the participant and family discuss diabetes and new knowledge, there is more opportunity for others to learn.
Public policy.
The final level of SEM is public policy which includes local, state, national laws and policies (McLeroy, Bibeau, Steckler, & Glanz, 1998). The use of public policy has a potential to protect the health of the community through regulatory policies and laws (McLeroy, Bibeau, Steckler, & Glanz, 1998).