Community Health Workers in Diabetes Care: A Systematic Review of Randomized Controlled Trials.
Keywords: chronic illness, community health workers, diabetes, type II diabetes
Consideration of nontraditional approaches in Type 2 diabetes (T2D) care is needed as patients continue to struggle with the intense and often complex responsibilities of managing this chronic illness. Many patients fail to achieve optimal outcomes (e.g., metabolic control, healthy weight, good dietary and exercise practices; Ali et al., 2013), which places them at increased risk for serious and potentially fatal disease-related complications. A major barrier to effective disease management is access to care (Carolan-Olah, Cassar, Quiazon, & Lynch, 2013; Chowdhury, Horsley, Zhang, & Satterfield, 2006). This is exacerbated by the fact that many patients also have mental health concerns and/or lack insurance coverage or adequate finances to cover out-of-pocket costs (National Institute of Mental Health, 2011; Santos-Longhurst, 2014; Zgibor & Songer, 2001).
Involving community health workers (CHWs) in patient care is a rapidly developing and innovative approach for extending the reach of the health care system (Perry, Zulliger, & Rogers, 2014). The United States Department of Labor (2015) outlined the role of CHWs as encompassing the conduct of outreach to promote individual- and community- health through the provision of resources, social support, informal counseling, and advocacy. CHWs bridge together patients/communities and medical providers/health care systems in an effort to reduce barriers that can interfere with the achievement of desired health outcomes.
The purpose of this review was to examine the effectiveness of CHW interventions for patients with T2D. Several other reviews that have included CHWs have been conducted (e.g., Chowdhury et al., 2006; Little, Wang, Castro, Jimenez, & Rosal, 2014), but these have included multiple professional types (e.g., "lay health worker", "peer counselors") and/or team-based interventions (e.g., nurse care manager + CHW team; pharmacist + CHW team). This review focuses specifically on CHWs evaluated within randomized controlled trials (RCTs). Such designs are well suited to test intervention effectiveness, as they require an unbiased comparison of treatment groups (Navaneethan, Palmer, Smith, Johnson, & Strippoli, 2010; Rosen, Manor, Engelhard, & Zucker, 2006). Anticipated outcomes of this review include efforts toward a more comprehensive approach to health care and future research that investigates types and methods of--and mechanisms for change within--CHW interventions that target diabetes.
Studies included in this review tested an intervention using CHWs in the care of adults with T2D. Inclusion criteria were: participants diagnosed with T2D, CHW-delivered intervention, intervention results presented, RCT design, and English language. CHWs were either the sole focus of the intervention under study (e.g., comparing the effectiveness of a CHW vs. a control group) or one component of a multi-component intervention (e.g., comparing the effectiveness of a peer leader vs. a CHW). Exclusion criteria were: non-CHW personnel (e.g., "peer supporters" or "lay educators" with different training backgrounds), team-based interventions, and unavailable full texts. To isolate the effects of the CHW, those delivered by teams of providers (e.g., CHW + Nurse Case Manager) were also excluded.
Using Medical Subjects Headings and text words, including diabetes mellitus, Type II, Non-insulin dependent diabetes mellitus, community health workers, community health worker (*), community health work (*), community health services, and health auxiliary, the following electronic databases were searched for peer-reviewed articles from the dates first indicated until August 2016: CINAHL (1937), EMBASE (1947), Google Scholar (date range not reported), MEDLINE (1946), and PubMed (1946). A total of 17 articles were identified that met aforementioned inclusion criteria (Figure 1).
For each study included in this review, the authors examined sample characteristics, inclusion of theory, CHW training, intervention design, outcome variables, and study results.
Studies in this review were published between 1997 and 2016. The majority of them were conducted in the United States, with the exception of McDermott et al.'s (2015) investigation in Australia. Sample sizes ranged from 107 to 360 participants (M = 173). Study samples were most commonly made up of middleaged female patients (mean of sample Ms = 53.8 years old) with less than a high school education and low annual household income. Several studies reported targeting populations in rural communities or minority populations (e.g., Babamoto et al., 2009; McDermott et al., 2015; Prezio et al., 2013; Rothschild et al., 2014). Interventions were conducted in primary care clinics, participants' homes, grocery stores, an outpatient department of a clinical research center, and via telephone. Studies varied in the degree to which they described characteristics of the CHWs and/or their prior training and experience. For example, Batts et al. (2001) did not report any descriptions, whereas Corkery et al. (1997) provided significant detail about the CHW's heritage, location at the time of the study, past volunteer experience, and concomitant skills (e.g., translator).
Six of the articles included in this review explicitly identified a guiding theory, model, or framework (see Table 1). Discussion of researchers' use of theory is pertinent to fully understanding their investigative processes, from early conceptualizations of research design to interpreting findings (Kelly, 2010). Further, explicit identification of the theories) helps to avoids alternate interpretations of findings that do not align with authors' intentions.
It is noteworthy that several studies grounded their research in the stages-of-change model by Prochaska and Velicer (1997). This transtheoretical model assesses participants' readiness to adapt new (healthier) behaviors and outlines principles and processes of change at each stage to lower resistance, assist progress, and prevent or respond to relapse (Prochaska, Redding, & Evers, 2002). A diagnosis of T2D often demands immediate and significant behavior changes and then, later, continuous monitoring and adaptation of said changes.
Community Health Worker Intervention
To evaluate and compare CHW interventions across studies, CHW training, intervention topics, intervention dose (intensity and duration), attrition (total and within the CHW intervention group), and participant recruitment strategies were analyzed (see Table 2). Commonalities found across studies include intervention foci and recruitment strategies. Limitations and/or areas of discrepancy included a lack of reported experience and evaluation within CHW training, considerable variation in intervention dose, and high attrition rates.
Intervention focus. There was a great deal of overlap across studies with respect to the focus of the CHW interventions. These foci can be classified into four types of service: The first type involved patient education. For example, Perez-Escamilla and colleagues (2015) trained CHWs on T2D pathophysiology, risk factors, and lifestyle strategies for glycemic control (nutrition, physical activity, blood glucose monitoring, medications, etc.). The second type involved patient care and health management (e.g., Heisler et al., 2014; Palmas et al., 2014). This type of service included developing self-management skills, creating goals and action plans, identifying potential barriers, and problem solving. The third type of service involved care coordination (e.g., McDermott et al., 2015; Spencer et al., 2011). In this role, CHWs reinforced instructions from participants' primary care providers, facilitated appointment- and referral-scheduling, and so forth The fourth type of service involved providing support regarding patients' mental, emotional, and social health and well-being (e.g., Rothschild et al., 2014; Tang, Brown, Funnell, & Anderson, 2014). For example, CHWs evaluated by Rothschild and colleagues (2014) provided social support that targeted stress management.
Recruitment strategy. The primary recruitment strategy used in eight of the 17 studies was a medical chart review. The second most common approach, and frequently used to supplement efforts done via medical chart review, was recruitment during routine medical visits (e.g., Palmas et al., 2014; Wagner et al., 2015). Rothschild et al. (2014) recruited via direct mailings, outreach efforts, and through partnerships with primary care clinics. Four studies did not report their recruitment strategy.
CHW training. The majority of studies reported the training and education provided for their respective CHWs; however, few reported receiving any formal evaluation of their delivery of the intervention during their training. This information is critical to evaluating the quality of CHW interventions. Several researchers (e.g., Tang et al., 2014) reported using CHWs who had previously received rigorous training and had several years of prior experience prior experience, whereas other researchers (e.g., Corkery et al., 1997) reported little to no information regarding CHW training or prior experience.
Intervention dose. The documented dose intensity (i.e., how many total contacts participants had CHWs) ranged from three to 36 contacts, not including additional phone calls (made on an as-needed basis). The documented dose duration (i.e., how long participants met with CHWs) ranged from 8-10 weeks to 24 months, with two studies that had varied durations (Corkery et al., 1997; Wagner et al., 2015). The average length of time per meeting was not routinely reported. The majority of studies did not report a set intervention frequency (i.e., how often CHWs had contact with participants). The most common frequency noted was approximately one contact per month, but this did not account for additional phone calls. This variation in intervention dose across studies makes it difficult to compare study outcomes. An additional challenge presents itself in comparing dose intensity and duration across studies: secondary to differences in reporting, some studies reported the mean dose (e.g., Prezio et al., 2013) whereas others only reported goals set for the desired dose (e.g., Tang et al., 2014).
Attrition. Reporting attrition in RCTs is critical, as loss to follow-up can diminish the strength of a trial's findings (Dumville, Torgerson, & Hewitt, 2006). Further, high attrition can introduce bias if the characteristics of participants who left the study differ from those who stayed in the intervention and control groups (Fewtrell et al., 2008). Therefore, it is important to report the attrition rate for both the total sample and the respective intervention group(s). Of the 17 studies reviewed, nine reported both the total and intervention attrition rates. Five reported either the total or the intervention attrition rate, but not both. Three failed to report either attrition rate. Of the total rates reported, attrition ranged from 6% to 41%. Of the intervention rates reported, attrition ranged from 8% to 42.8%. According to Lyles et al. (2007), best-evidence behavioral interventions require attrition rates of 30% or less in each randomized group for the intervention outcomes to be considered seriously. There were three studies that reported a total sample attrition rate over 30% (Babamoto et al., 2009; Corkery et al., 1997; Tang et al., 2014), and one study that reported an intervention group attrition rate (Tang et al., 2014) over that threshold.
Outcome variables can be categorized by self-care behavior-, knowledge-, mental health and well-being-, physical health-, and other- outcomes not otherwise categorized (see Table 3). Data on self-care behaviors were provided in 13 studies; however, there was little consistency in the specific outcome variables measured and instruments used. The most commonly assessed variable was diabetes self-care practices. It should be noted that other studies, such as Kollannoor-Samuel et al. (2016), examined other such behaviors (e.g., physical activity, healthy eating) that would fall under a larger umbrella of self-care practices. Data about diabetes knowledge were presented in nine studies; the most common variable assessed was global diabetes knowledge. Data about mental health and well-being outcomes were provided in nine studies. The most common outcome variable assessed was diabetes distress. Data about physical health were provided in all studies; the most common outcome variables assessed were Alc and blood pressure. Noncategorized outcomes included diabetes care priorities, needs related to diabetes and nondiabetes care, quality of diabetes care, collaborative relationships with health providers, and therapeutic cohesion and alliance. Three of the 17 studies investigated these outcomes with no overlaps between them. Due to the limited presence of these outcomes in this literature, it is difficult to make informed conclusions regarding patients' experiences.
Results of the CHW interventions are presented in Table 4. Additionally, the following main foci across studies' results are presented below:
Physical health. The majority of studies reported a significant reduction in Alc levels for participants receiving a CHW intervention (see Table 5). This indicator is a hallmark gauge of long-term glycemic control (Mayo Foundation for Medical Education and Research, 2016). There was inconsistency in findings regarding the sustainability of improvements in Alc, however. Perez-Escamilla et al. (2015) reported improvements over 18 months; Prezio et al. (2013) found improvements ongoing for the duration of the study with greater improvements after the first six months; Rothschild et al. (2014) reported maintained improvements over two years; Tang et al. (2014) demonstrated improved Alc at 6-months post intervention, but these improvements were diminished at 18 months.
Food label use and diet quality were also found to mediate the relationship between a CHW intervention and improvements in glycemic control (Kollannoor-Samuel et al., 2016). Patients using food labels as a dietary tool and who reported a higher quality diet experienced a significant improvement in metabolic control. Additional physiological risk factors positively impacted by CHW interventions included reduced blood pressure (Gary et al., 2003), waist circumference (Tang et al., 2014), and weight (Rothschild et al., 2014).
Diabetes knowledge. Findings from the studies reviewed commonly concluded that CHW interventions had significant impacts on patients' diabetes knowledge (e.g., Babamoto et al., 2009; Corkery et al., 1997; Wagner et al., 2015). However, while Corkery et al. (1997) reported significant improvements upon completion of the diabetes education program in diabetes knowledge scores, they could not prove that the improved outcomes were a result of the CHW intervention per se.
Self-care behaviors. Several studies reported significant improvements in patients' medication adherence (Babamoto et al., 2009; Batts et al., 2001; Heisler et al., 2014), dietary adherence (i.e., fruit and vegetable intake; Babamoto et al., 2009; Batts et al., 2001; Kollannoor-Samuel et al., 2016; Rothschild et al., 2014), and physical activity (Batts et al., 2001; Gary et al., 2003; Rothschild et al., 2014; Spencer et al., 2011). Corkery et al. (1997) noted significant changes in reported self-care behaviors at the end of the study, but a causal relationship between the CHW intervention and these behaviors was not supported. Additionally, Kenya, Lebron, Reyes Arrechea, Li (2014) found a discrepancy between patient reports of glucometer use and their blood glucose self-monitoring (BGSM) reports, concluding that the CHW intervention may improve glycemic control without demonstrating a change in BGSM practices.
Mental health and well-being. Five of the studies reviewed reported significant findings in participants' mental health and well-being. Heisler et al. (2014) found improvements in patients' self-efficacy and diabetes distress when the CHW used an e-Health tool as compared to print materials in providing decision-making support. Spencer et al. (2013) noted no impact from the intervention on PHQ-9 scores, but PHQ-2 scores did drop when researchers used the "average intervention effect" (i.e., combining the preintervention to postintervention effects for the immediate and delayed groups) and adjusted for demographics (gender, age, and education). Further, these researchers found diabetes-related emotional distress scores were reduced even further within the immediate intervention group from six to 12 months. Tang et al. (2014) also found improvements in diabetes distress at 18-month follow-up. Testing a CHW-delivered stress management intervention, Wagner et al. (2016) maintained that diabetes education was associated with significant improvements in depression and anxiety, and that increased attendance in said education was associated with greater improvements in both Alc and disease-related stress. Finally, Rothschild et al. (2014) evaluated a CHW-delivered intervention on self-management training; they found that self-efficacy increased significantly during the study in both intervention and control groups (with no significant between-groups differences).
This systematic review highlights several important findings within the RCTs that have been conducted studying the effectiveness of CHW-delivered interventions on T2D care. Our results have implications for both clinical practice and future research. Implications for clinical practice are discussed on a more global level regarding the larger shift in health care toward a more comprehensive approach. Additionally, more specific implications are also presented with respect to the design and implementation of CHW-led diabetes interventions.
The Triple Aim of health care--improving patients' experiences of care, improving the health of populations, and reducing per capita costs of care--should be at the heart of comprehensive care (Katon & Uniitzer, 2013). The findings of this review highlighted psychological and social factors often contributing to patients' T2D management. While one response to boost comprehensiveness is to layer-on an abundance of screenings and tests, this effort fails in respect to the third aim of reducing costs and would likely hurt patients' care experience (s). Medical providers, mental health providers, and the larger health care system are tasked to be knowledgeable about the primary concerns research has highlighted for the population being served (e.g., patients with T2D), and must be strategic in their delivery of screenings and interventions that have demonstrated effectiveness.
With the growing need to provide comprehensive health care, more research investigating nontraditional approaches that simultaneously enhance patient care and boost cost savings is warranted. Further investigation targeting the mechanisms of change in the delivery of a CHW intervention (e.g., optimal dosage) would advance these aims. Furthermore, three of the 17 studies reviewed addressed the social contributions and/or complications to patients' management of diabetes. Managing T2D is a social issue. Spousal and family support and involvement can be the biggest predictor of treatment adherence (Tang et al., 2008; Whittemore, Melkus, & Gray, 2005); conversely, it can present major obstacles, such as difficult changes in family roles and responsibilities (Batts et al., 2001). There is a need to evaluate the social impact of this disease on the patient as well as on the patient's social network. Consideration of the bidirectional impact between the patient and his or her social network is supported by foundational theories/models in the field (e.g., biopsychosocial model of health, symbolic interactionism theory, social networks and social support model). CHWs are uniquely positioned as a bridge between the patient and medical system to assist patients in improving the social support received and managing implications of their disease on their social network (McEwen, Pasvogel, Gallegos, & Barrera, 2010).
An additional direction for future research geared toward improving patient care and cost savings is to further examine the impact of CHWs on emergency department (ED) or hospital admissions. In the studies reviewed, there was very limited attention to this type of resource utilization, and in the few studies that examined it there was a discrepancy in findings. As alternative approaches to support patient care for T2D and other chronic conditions continue to gain momentum, examining their impact(s) on outcomes such as ED and hospital admissions provide valuable information about potential changes in the physical and psychological/social health of patients.
Strengths and Limitations
The studies included in this review were strengthened by their robust research designs (i.e., RCTs), which served to maximize internal validity and provide objective information about the effectiveness of CHWs. Focusing solely on CHWs allowed us to tease out the effectiveness of CHW-delivered interventions, also increasing internal validity. Additionally, researchers tested the effectiveness of a CHW intervention on patients' physiological outcomes, mental health outcomes, and knowledge and behaviors, which provided valuable data about the interconnectedness of the mind and the body.
There are also important limitations of this review. The impact of the intervention is dependent on its delivery. In failing to report information about CHW training and evaluation, confidence in some of the results is weakened. This is primarily due to the consumer not knowing how closely the CHW adhered to the study protocol and design. Further, in working toward streamlining the process of using CHWs in patients' care and determining the minimum dose needed to produce the desired patient health outcomes, consistency in intervention dose reporting is needed. Our reporting and assessment of RCTs was limited to published data; therefore, the results of evaluations done by health departments, community programs, or private health care organizations that were not published were not included in this review, potentially limiting its scope. We also did not include studies referring to this work by another name (e.g., lay health workers) and studies including other team members as a part of the intervention to provide a more focused assessment of the effectiveness of CHWs in particular. This potentially limited the scope, but not the specificity, of this review.
As T2D continues to increase in prevalence, an assessment of the effectiveness of alternative approaches to patient care is needed. Literature evaluating the impacts of CHW interventions has reported positive findings on patients' bio-psychosocial health outcomes; however, research has not gotten to the point yet where the most important and effective methods of CHW training and intervention foci and dosages are well understood. The advancement of comprehensive health care alongside future research that evaluates social factors and resource utilization will further inform and advance our efforts.
(*) Indicates articles included in review
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(*) Babamoto, K. S., Sey, K. A., Camilleri, A. J., Karlan, V. J., Catalasan, J., & Morisky, D. E. (2009). Improving diabetes care and health measures among Hispanics using community health workers: Results from a randomized controlled trial. Health Education & Behavior, 36, 113-126. http://dx.doi.org/10.1177/1090198I08325911
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(*) Corkery, E., Palmer, C., Foley, M. E., Schechter, C. B., Frisher, L., & Roman, S. H. (1997). Effect of a bicultural community health worker on completion of diabetes education in a Hispanic population. Diabetes Care, 20, 254-257. http://dx.doi.org/10.2337/diacare.20.3.254
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(*) Kenya, S., Lebron, C., Reyes Arrechea, E., & Li, H. (2014). Glucometer use and glycemic control among Hispanic patients with diabetes in southern Florida. Clinical Therapeutics, 36, 485-493. http://dx.doi.Org/10.1016/j.clinthera.2013.12.009
(*) Kollannoor-Samuel, G., Shebl, F. M Segura-Perez, S., Chhabra, J., Vega-Lopez, S., & Perez-Escamilla, R. (2016). Effects of food label use on diet quality and glycemic control among Latinos with type 2 diabetes in a community health worker-supported intervention. American Journal of Public Health, 106, 1059-1066. http://dx.doi.org/10.2105/AJPH.2016.303091
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(*) McDermott, R. A., Schmidt, B., Preece, C., Owens, V., Taylor, S., Li, M., & Esterman, A. (2015). Community health workers improve diabetes care in remote Australian Indigenous communities: Results of a pragmatic cluster randomized controlled trial. BioMed Central Health Services Research, 15, 68-76. http://dx.doi.org/10.1186/s12913-015-0695-5
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(*) Perez-Escamilla, R., Damio, G., Chhabra, J., Fernandez, M. L., Segura-Perez, S., Vega-Lopez, S., ... D'Agostino, D. (2015). Impact of a community health workers-led structured program on blood glucose control among Latinos with type 2 diabetes: The DIALBEST trial. Diabetes Care, 38, 197-205. http://dx.doi.org/10.2337/dc14-0327
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(*) Wagner, J. A., Bermudez-Millan, A., Damio, G., Segura-Perez, S., Chhabra, J., Vergara, C., ... Perez-Escamilla, R. (2016). A randomized, controlled trial of a stress management intervention for Latinos with type 2 diabetes delivered by community health workers: Outcomes for psychological wellbeing, glycemic control, and Cortisol. Diabetes Research and Clinical Practice, 120, 162-170. http://dx.doi.Org/10.1016/j.diabres.2016.07.022
Whittemore, R., Melkus, G. D., & Grey, M. (2005). Metabolic control, self-management and psychosocial adjustment in women with type 2 diabetes. Journal of Clinical Nursing, 14, 195-203. http://dx.doi.org/10.1111/j.1365-2702.2004.00937.x
Zgibor, J. C., & Songer, T. J. (2001). External barriers to diabetes care: Addressing personal health systems issues. Diabetes Spectrum, 14, 23-28. http://dx.doi.org/10.2337/diaspect.14.L23
Lisa J. Trump, PhD, LMFT, and Tai J. Mendenhall, PhD, LMFT
University of Minnesota, Twin Cities
This article was published Online First June 22, 2017.
Lisa J. Trump, PhD, LMFT, and Tai J. Mendenhall, PhD, LMFT, Department of Family Social Science, University of Minnesota, Twin Cities.
Correspondence concerning this article should be addressed to Lisa J. Trump, PhD, LMFT, or Tai J. Mendenhall, PhD, LMFT, Department of Family Social Science, University of Minnesota, Twin Cities, 1985 Buford Avenue, 290 McNeal Hall, Saint Paul, MN 55108. E-mail: email@example.com or firstname.lastname@example.org
Received January 3, 2017
Revision received March 16, 2017
Accepted May 1, 2017
Table 1 Inclusion of Theory Article Explicit Use 1. Babamoto et al. of Theory (2009) 2. Gary et al. (2003) 3. Perez-Escamilla et al. (2015) 4. Prezio et al. (2013) 5. Spencer et al. (2011); Spencer et al. (2013) Missing 1. Batts et al. (2001) Theory 2. Corkery et al. (1997) 3. Heisler et al. (2014) 4. Kenya et al. (2014) 5. Kollannoor-Samuel et al. (2016) 6. McDermott et al. (2015) 7. Palmas et al. (2014) 8. Rothschild et al. (2014) 9. Tang et al. (2014) 10. Wagner et al. (2016) 11. Wagner et al. (2015) Theories identified Explicit Use 1. Transtheoretical Stages of Change model (Prochaska & of Theory Velicer, 1997) 2. Precede-Proceed model (Green & Kreuter, 1991) 3. Stages of Change model (Prochaska & Velicer, 1997); Motivational Interviewing (Miller & Rollnick, 1991); Chronic Care Model framework (Wagner et al., 2001) 4. Social Cognitive theory (Bandura, 2001) 5. Socioecological model and empowerment theory (Anderson & Funnell, 2005) Missing 1. -- Theory 2. -- 3. -- 4. -- 5. -- 6. -- 7. -- 8. Described elsewhere 9.-- 10.-- 11.-- Table 2 Community Health Worker Intervention Article Training (*) Babamoto et al. Education: 6-week training (2009) curriculum Experience in training: NR Evaluation: NR Batts et al. (2001) Education: NR Experience in training: NR Evaluation: NR Corkery et al. Education: NR (1997) Experience in training: NR Evaluation: NR Gary et al. (2003) Education: NR Experience in training: NR Evaluation: Met bi-weekly with nurse case manager Heisler et al. Education: 80 hours + 4-8 (2014) hours of booster training annually Experience in training: NR Evaluation: NR Kenya et al. (2014) Education: NR Experience in training: NR Evaluation: NR Kollannoor-Samuel Education: Additional training et al. (2016) in unknown amount Experience in training: NR Evaluation: Interviews and educational sessions monitored McDermott et al. Education: 3-week training + 2 (2015) workshops during intervention Experience in training: NR Evaluation: NR Palmas et al. Education: NR (2014) Experience in training: NR Evaluation: NR Perez-Escamilla et Education: 65 hours of al. (2015) training + 25 supplemental hours Experience in training: NR Evaluation: Weekly meetings with field supervisor and health management team Prezio et al. (2013) Education: 27 hours of training Experience in training: NR Evaluation: Competency assessment and clinical observation Rothschild et al. Education: 100 hours of training (2014) Experience in training: NR Evaluation: NR Spencer et al. Education: 80 hours of training (2011) Experience in training: NR Evaluation: NR Spencer et al. Education: 80 hours of training (2013) Experience in training: NR Evaluation: NR Tang et al. (2014) Education: 160 hours of community outreach training + 80 hours of specific training Experience in training: NR Evaluation: NR Wagner et al. Education: NR (2016) Experience in training: NR Evaluation: NR Wagner et al. Education: 150 hours of training (2015) Experience in training: Delivered intervention to pilot cohort Evaluation: Supervision of training experience Article Intervention topics Babamoto et al. Diabetes knowledge (1st role) (2009) Identified problems (2nd role) Goals Level of Progress Barriers and Issues Problem-solving Batts et al. (2001) Healthy eating Physical activity Medication adherence Appointment adherence (3rd role) SMBG (**) Foot care Smoking cessation Corkery et al. Reinforced self-care (1997) instructions Appointment adherence Appointment adherence Gary et al. (2003) Diabetes knowledge Behavior monitoring Adherence to treatment Social support (4th role) Physician Feedback Heisler et al. Diabetes knowledge (2014) Medication adherence Barriers Patient goals Action plans Kenya et al. (2014) BGSM Medication adherence Lifestyle behaviors Kollannoor-Samuel Nutrition knowledge et al. (2016) Physical activity Diabetes knowledge Mental and cardiac health BGSM Medication adherence Appointment adherence McDermott et al. Appointment adherence (2015) Medication knowledge Nutrition Smoking cessation Foot care Self-management skills Palmas et al. Barriers to care (2014) Goal setting Needs assessment Referrals Nutrition and exercise knowledge Perez-Escamilla et Diabetes knowledge al. (2015) Healthy lifestyle behaviors Nutrition BGSM Medication adherence Appointment adherence Mental health Prezio et al. (2013) BC.SM Nutrition Medication adherence Smoking cessation Physical activity Diabetes knowledge Referrals Rothschild et al. Diabetes knowledge (2014) Diabetes management skills Goal setting Problem-solving skills Modifying home environment to support behavior change Social support Stress management Spencer et al. Diabetes knowledge (2011) Diabetes management skills Communication skills with medical providers Referrals Spencer et al. Stress reduction (2013) Physical activity Nutrition Goal setting Communication skills with medical providers Referrals Tang et al. (2014) Goal setting Mental health Diabetes self-management skills Action plans Emotional support Resource utilization Wagner et al. Diabetes knowledge (2016) Nutrition Medication adherence Physical activity BGSM Physical relaxation Wagner et al. Nutrition (2015) Physical activity Skills training Relaxation exercise Article Dose (Intensity/Duration) Babamoto et al. 10 individual education sessions + (2009) follow-up phone calls (M = 11 sessions)/6 months Batts et al. (2001) 3 visits/2 years Corkery et al. NR number of clinic visits + NR (1997) number of diabetes education sessions/duration varied Gary et al. (2003) 6 visits + additional contacts as needed (mode = < 3 visits)/2 year Heisler et al. 1-2 hour session + 2 follow-up (2014) calls/2 years Kenya et al. (2014) Visits as needed (M = 8 visits)/1 year Kollannoor-Samuel 17 visits/1 year et al. (2016) McDermott et al. Visits as needed (mean NR)/2 (2015) years Palmas et al. 4 individual visits + 10 group (2014) sessions + 10 follow-up phone calls (medians = 3 visits, 0 group sessions, and 10 phone calls)/l year Perez-Escamilla et 17 sessions/1 year al. (2015) Prezio et al. (2013) 7 sessions (M = 7)/l year Rothschild et al. 36 visits (mode = < 13 visits)/2 (2014) years Spencer et al. 2 home visits per month + 1 (2011) medical visit + 11 education classes (M = 8 classes) + follow-up phone calls every two weeks/6 months Spencer et al. 2 home visits per month + 1 (2013) medical visit + 11 education classes (M = 8 classes) + follow-up phone calls every two weeks/6 months Tang et al. (2014) 11 2-hour group classes in initial 6 months + 2 home visits per month + monthly follow-up phone calls/18 months Wagner et al. 8 group education sessions (M = 5 (2016) sessions)/8-10 weeks Wagner et al. 8 group education sessions (M = 5 (2015) sessions)/varied duration Attrition (% total/% in CHW Article intervention) Participant Recruitment Babamoto et al. 41%/28% Recruited during routine (2009) clinic visits Batts et al. (2001) NR/NR NR Corkery et al. 37%/20% NR (1997) Gary et al. (2003) 16%/NR Medical chart review Heisler et al. 6%/NR Medical chart review (2014) Kenya et al. (2014) NR/NR NR Kollannoor-Samuel 17%/NR Recruited during routine et al. (2016) clinic visits at primary care clinic McDermott et al. 10%/17% Recruited during routine (2015) clinic visits at primary care clinics Palmas et al. 15.5%/18.8% Recruited during routine (2014) clinic visits at primary care clinics Perez-Escamilla et 29%/24.8% Medical chart review al. (2015) Prezio et al. (2013) 14.4%/8% NR Rothschild et al. 16%/20.5% Direct mailings, (2014) outreach at community events and churches, partnerships with primary care clinics, and direct outreach by CHW Spencer et al. 17.7%/18% Medical chart review (2011) Spencer et al. 17.1%/NR Medical chart review (2013) Tang et al. (2014) 41%/42.8% Medical chart review Wagner et al. NR/NR Medical chart review (2016) Wagner et al. NR/22.9% Medical chart review (2015) and recruited during routine clinic visit in a primary care clinic (*) Experience in training did not include experience gained prior to the study. (**) BGSM is blood glucose self-management. Table 3 Quantitative Outcome Variables Category Outcome Variable Behavior 1. Behavioral risk factors (Babamoto et al., Outcomes 2009; Kenya et al., 2014; Spencer et al., 2011; Spencer et al., 2013) 2. Medication adherence (Babamoto et al., 2009; Heisler et al., 2014; Rothschild et al., 2014) 3. Health behaviors (Batts et al., 2001) 4. Diabetes self-care practices (Corkery et al., 1997; Gary et al., 2003; Perez-Escamilla et al., 2015; Rothschild et al., 2014; Spencer et al., 2011; Spencer et al., 2013; Wagner et al., 2016) 5. Physical activity (Gary et al., 2003; Kollannoor-Samuel et al., 2016; Spencer et al., 2013) 6. Healthful eating (Gary et al., 2003; Kollannoor-Samuel et al., 2016; Spencer et al., 2013) 7. Self-reported health status (Wagner et al., 2016) 8. Home skills (Wagner et al., 2015) Knowledge 1. Diabetes knowledge (Babamoto et al., 2009; Outcomes Corkery et al., 1997; Kollannoor-Samuel et al., 2016; Perez-Escamilla et al., 2015; Wagner et al., 2015) 2. Medication knowledge and decision-making (Heisler et al., 2014) 3. Health Literacy (McDermott et al., 2015) 4. Diabetes self-management knowledge (Spencer et al., 2011) 5. Medication changes (Prezio et al., 2013) Mental Health and 1. Diabetes self-efficacy (Heisler et al., 2014; Weil-Being Rothschild et al., 2014; Spencer et al., 2011) Outcomes 2. Diabetes distress (Heisler et al., 2014; Spencer et al., 2011; Spencer et al., 2013; Tang et al., 2014; Wagner et al, 2016) 3. Quality of life (McDermott et al., 2015) 4. Acculturation (Perez-Escamilla et al., 2015; Rothschild et al., 2014) 5. Social support (Perez-Escamilla et al., 2015; Rothschild et al., 2014; Tang et al., 2014) 6. Diabetes attitudes (Perez-Escamilla et al., 2015; Spencer et al., 2013) 7. Mental health (Perez-Escamilla et al., 2015) 8. Depression (Rothschild et al., 2014; Spencer et al., 2013) 9. Stress (Rothschild et al., 2014) 10. Anxiety (Rothschild et al., 2014; Wagner et al., 2016) 11. Treatment expectations (Wagner et al., 2015) 12. Affect (Wagner et al., 2015) 13. Treatment satisfaction (Wagner et al., 2015) Physical Health 1. HbAlc (Babamoto et al., 2009; Corkery et Outcomes al., 1997; Gary et al., 2003; Heisler et al., 2014; Kenya et al., 2014; Kollannoor-Samuel et al., 2016; McDermott et al., 2015; Palmas et al., 2014; Perez-Escamilla et al., 2015; Prezio et al., 2013; Rothschild et al., 2014; Spencer et al., 2011; Spencer et al., 2013; Tang et al., 2014; Wagner et al., 2016; Wagner et al., 2015) 2. Weight, height, and/or body mass index (Babamoto et al., 2009; Perez-Escamilla et al., 2015; Prezio et al., 2013; Tang et al., 2014) 3. Blood pressure (Batts et al., 2001; Gary et al., 2003; McDermott et al., 2015; Palmas et al., 2014; Perez-Escamilla et al., 2015; Prezio et al., 2013; Rothschild et al., 2014; Spencer et al., 2011; Tang et al., 2014) 4. Lipid profile (Gary et al., 2003; Perez- Escamilla et al., 2015; Prezio et al., 2013; Tang et al., 2014) 5. Self-monitored blood glucose (Kenya et al.. 2014) 6. Cholesterol (Palmas et al., 2014; Spencer et al., 2011) 7. Hip/waist circumference (Perez-Escamilla et al., 2015; Tang et al., 2014) 8. Diabetes-related complications (Spencer et al., 2013) 9. Urinary Cortisol (Wagner et al., 2016) Non-Categorized 1. Diabetes care priorities (Batts et al., 2001) Outcomes 2. Needs related to diabetes care and non- diabetes care (Batts et al., 2001) 3. Quality of diabetes care (Spencer et al., 2013) 4. Relations with health providers (Spencer et al., 2013) 5. Therapeutic cohesion and alliance (Wagner et al., 2015) Category Instrument (*) Behavior 1. Behavioral Risk Factor Surveillance Outcomes System; Michigan Diabetes Knowledge Scale 2. Morisky Self-Reported Medication Behavior Scale; 4-Item Self-Reported Adherence Measure; MEMS 6 Track Cap 3. NR 4. Patient Self-Reported Behaviors Rating Scale of Diabetes Self-Care Practices; Summary of Diabetes Self- Care Activities Scale 5. Dietary Risk Assessment; ADA guidelines 6. Food Frequency Questionnaire; Food Label Questionnaire, Healthy Eating Index 7. 1-item from National Health Interview Survey 8. Weekly diary entries Knowledge 1. Diabetes Knowledge Questionnaire; Outcomes Diabetes knowledge test developed for Gary et al. (2003); Diabetes- related knowledge survey developed by Kollannoor-Samuel et al. (2016); 10-items from DIALBEST 2. The Diabetes Mellitus Medication Choice Aid; Decisional Conflict Scale; Statin Choice 3. Functional Health Literacy for Adults 4. 1-item validated question 5. Computerized pharmacy records Mental Health and 1. Diabetes Empowerment Scale; Weil-Being Perceived Competence for Diabetes Outcomes Scale 2. Diabetes Distress Scale; Problem Areas in Diabetes Scale 3. Assessment of Quality of Life 4. Marin Instrument to Assess for Acculturation 5. Personal Resource Questionnaire; Diabetes Support Scale 6. NR 7. NR 8. Beck Depression Inventory; Patient Health Questionnaire-9 item; Patient- Health Questionnaire-8 item 9. Perceived Stress Scale; PROMIS Emotional Distress/Anxiety Scale 10. Spielberger State Anxiety Inventory 11. Credibility Expectancy Scale 12. Affect reports 13. Developed for Wagner et al. (2015) Physical Health 1. Clinical data Outcomes 2. Clinical data 3. Clinical data 4. Clinical data 5. Stanford Patient Education Research Center Diabetes Questionnaire 6. Clinical data 7. Clinical data 8. NR 9. Clinical data Non-Categorized 1. Developed for Batts et al. (2001) Outcomes 2. Developed for Batts et al. (2001) 3. NR 4. NR 5. 4-item Outcome Alliance Scale (*) The instruments listed only include those that were reported by the authors in their manuscripts. Table 4 CHW Intervention Results Sample Participant mean Article size (N) Region age in years Babamoto et al. 189 Los Angeles, 50 (2009) CA Batts et al. (2001) 119 Baltimore, MD 59 Corkery et al. 64 New York City, 53 (1997) NY Gary et al. (2003) 149 Baltimore, MD 59 Heisler et al. 1 x 8 Detroit, MI 52 (2014) Kenya et al. (2014) 117 Miami, FL 55 Kollannoor-Samuel 203 New Haven, CT 57 et al. (2016) McDermott et al. 213 Adelaide, South 48 (2015) Australia Palmas et al. 360 New York City, 58 (2014) NY Perez-Escamilla et 211 Hartford, CT 56 al. (2015) Prezio et al. (2013) 180 Dallas, TX 46 Rothschild et al. 144 Chicago, IL 54 (2014) Spencer et al. 164 Detroit, MI 50 (intervention). (2011) 55 (control) Spencer et al. 164 Detroit, MI 53 (2013) Tang et al. (2014) 116 Detroit, MI 49 Wagner et al. 107 Hartford, CT 61 (DE), 60 (2016) (SM + DE) Wagner et al. 107 Hartford, CT 60 (2015) Article Sex (% Female) Babamoto et al. 64 (2009) Batts et al. (2001) 75 Corkery et al. 74 (1997) Gary et al. (2003) 77 Heisler et al. 76 (iDecide); 66 (2014) (printed materials) Kenya et al. (2014) 55 Kollannoor-Samuel 73 et al. (2016) McDermott et al. 62 (2015) Palmas et al. 63 (control), (2014) 61 (intervention) Perez-Escamilla et 74 al. (2015) Prezio et al. (2013) 67 (control), 54 (intervention) Rothschild et al. 67 (2014) Spencer et al. 75 (intervention), (2011) 67 (control) Spencer et al. 71 (2013) Tang et al. (2014) 58.6 Wagner et al. 72 (DE), 74 (2016) (SM + DE) Wagner et al. 73 (2015) Significant changes in constructs measured for Article CHW Intervention group Babamoto et al. a. Self-reported health status of "very good" or (2009) "excellent" increased from 5% at baseline to 57% at follow-up b. Intake of fatty foods decreased from 29% at baseline to 16% at follow-up c. Intake of 2 + servings of fresh fruit per day and fresh vegetables per day increased from 47% and 39% at baseline to 73% and 76% at follow-up, respectively d. Exercise 3 + days per week increased from 28% at baseline to 63% at follow-up e. Mean Diabetes Knowledge Scale score increased from 10.6 at baseline to 14.7 at follow-up f. Mean Alc decreased from 8.6% at baseline to 7.2% at follow-up Batts et al. (2001) a. Percentages of needs addressed in first, second, and third visits decreased for healthy eating, physical activity, medication adherence, and insurance Corkery et al. a. Alc levels decreased from 11.7 at baseline to (1997) 9.9 at post-intervention and sustained at 9.5 at follow-up b. Self-reported knowledge scores improved from 74.4% at baseline and 95.4% at post-test c. Improvements from baseline to follow-up in self-reported adherence to the meal plan, carrying a fast-acting sugar, and performing daily foot care Gary et al. (2003) a. A .26-unit increase in leisure-time physical activity from baseline Heisler et al. a. Within-group mean improvements from baseline (2014) to follow-up in medication decisional conflict (11.5, 14.1), knowledge about medications (10.8, 12.8), satisfaction with clarity of medication information (13.0, 22.2), and satisfaction with helpfulness of medication information (10.2, 21.5) for printed materials and iDecide, respectively b. Within-group mean improvements from baseline to follow-up in diabetes self-care efficacy (4.8, 81), medication adherence (5.7, 3.4), and Alc (-.3, -.4) for printed materials and iDecide, respectively c. Within-group mean improvement of 14.1 for iDecide group from baseline to follow-up in diabetes distress d. Between-group differences in improvement found to be greater for iDecide than printed materials for satisfaction with clarity of information on medications and satisfaction with helpfulness of information on medications e. Between-group difference in improvement of 15.7 in mean diabetes distress score for iDecide than printed materials Kenya et al. (2014) a. Alc values decreased from 10.04 at baseline to 8.80 at follow-up Kollannoor-Samuel a. Food label use improved 16.4% from baseline to et al. (2016) follow-up b. Alc levels decreased .52% from baseline to follow-up c. 15% of the decrease in Alc levels from baseline to follow-up was associated with food label use to diet quality path d. Within-individuals, Alc values decreased 12% between baseline and follow-up and with respect to diet quality (.11%) McDermott et al. a. Alc levels decreased from 10.8 at baseline to (2015) 9.8 at follow-up Palmas et al. a. When separated out from in-person contacts, (2014) phone contacts were associated with greater Alc reduction from baseline to follow-up Perez-Escamilla et a. Ale levels decreased .42% from baseline to 3 al. (2015) months, .47% at 6 months, .57% at 12 months, and .55% at 18 months b. An overall group effect of--.51% was found for Alc with the intervention group having lower Ale levels than the control group c. Fasting glucose was lower for the intervention group than the control group Prezio et al. (2013) a. Alc levels decreased .7% from baseline to follow-up. with a greater reduction in Alc for intervention group than the control group Rothschild et al. a. Alc levels decreased .55 points lower for the (2014) intervention group than the control group from baseline to year one (8.35 to 7.87 for intervention group, 8.23 to 8.42 for control group) and .69 points lower from year one to year two (7.87 to 7.64 for intervention group. 8.42 to 8.33 for control group) b. Glucose self-monitoring increased from baseline to year two for both groups c. Self-efficacy increased a mean of 4.4 units from baseline to year two for both groups d. Weight decreased 4.82 pounds from baseline to year one and 5.02 pounds from year one to year two e. Social support increased 6.7 points from baseline to year one and 12.7 points from year one to year two Spencer et al. a. Mean Alc levels decreased from 8.6 at baseline (2011) to 7.8 at follow-up b. Mean LDL cholesterol levels decreased from 105 at baseline to 95 at follow-up c. Self-management knowledge improved from baseline to follow-up, with improvements seen in self-management score, knowledge about how food affects blood sugar, and how exercise helps blood sugar d. Percent that met guidelines for physical activity increased from 37% at baseline to 53% at follow-up e. Adherence to inspecting the inside of shoes daily increased from 49% at baseline to 77% at follow-up f. Testing blood sugars as recommended improved from 74% at baseline to 87% at follow-up Spencer et al. a. With age and ethnicity added to the model, (2013) problem areas in diabetes decreased 6.5 points from baseline to 6 months, with a total reduction of 12.3 months from baseline to follow-up b. In calculating an "average intervention effect" by combining the immediate and delayed groups, problem areas in diabetes decreased from baseline to follow-up regardless of whether demographics were added to the model c. When problem areas in diabetes analyses were stratified by race/ethnicity, the outcome was only significant for Latino/as d. Depression symptoms decreased by .4 units from baseline to 6 months for the delayed group, with a difference between the immediate and delayed group of .7 e. For Latino/as, depression symptoms decreased 1.0 units from baseline to 6 months f. With the "average intervention effect", a decrease in depression symptoms was seen from baseline to 6 months Tang et al. (2014) a. Alc levels decreased 5.5 units from baseline to 6 months and maintained a decrease of 4.4 units at 12 months b. Waist circumference decreased 1.4 inches from baseline to 6 months and sustained a 1.3 inch reduction at 18 months c. Social support improved .6 units from baseline to 6 months and sustained .4 unit improvement at 12 months and .3 units at 18 months d. High diabetes distress decreased from baseline to 6 months e. Moderate diabetes distress levels decreased from 28.6% at baseline to 14.5% at 6 months, and was sustained at 16.2% at 12 months and at 18.8% at 18 months Wagner et al. a. Depression symptoms increased from 5.3 units (2016) at baseline to 6.2 units at post-treatment for diabetes education (DE) group and decreased from 6.7 units at baseline to 4.7 units at post-treatment for stress management and diabetes education (SM + DE) b. Anxiety symptoms increased froml.8 units at baseline to 2.9 units at post-treatment for DE group and decreased from 1.9 units at baseline to 1.7 units at post-treatment for SM + DE c. Self-reported health worsened from 3.3 units at baseline to 3.4 units at post-treatment for DE group and decreased from 3.5 units at baseline to 3.1 units at post-treatment for SM + DE d. Number of sessions attended was associated with Ale; compared to baseline, at post-treatment each additional session attended was associated with a .21 decrease in Alc and at follow-up was associated with a .19 decrease in Alc e. Compared to baseline, at post-treatment each additional SM session was associated with a .6 point decrease in diabetes distress score Wagner et al. a. Diabetes knowledge scores increased from 62% (2015) correct at baseline to 76% correct at follow-up b. In-session relaxation exercises increased positive affect and decreased negative affect from baseline to follow-up Associated statistical significant (p; respective) Article /Effect size (if reported) Babamoto et al. a. < .05 (2009) b. < .05 c. < .05 d. < .05 e. < .05 f. < .05 Batts et al. (2001) a. < .001; < .001; < .05; < .001 Corkery et al. a. = .004; < .001 (1997) b. < .001 c. = .013; < .001; < .001 Gary et al. (2003) a. < .05 Heisler et al. a. All < .001/< .001 (2014) b. = .002/< .001; < .001/ = .036; = .016/= .001 c. < .001 d. = .03; = .007 e. < .001 Kenya et al. (2014) a. < .001 Kollannoor-Samuel a. < .001 et al. (2016) b. < .05 c. < .01 d. < .01; < .05 McDermott et al. a. = .018 (2015) Palmas et al. a. = .04 (2014) Perez-Escamilla et a. = .043; = .050; al. (2015) = .021; = .009 b. = .002 c. = .002 Prezio et al. (2013) a. = .02; < .001 Rothschild et al. a. = .021; = .005 (2014) b. Significant (p value NR) c. Significant (p value NR) d. = .041; = .036 e. = .015; < .001 Spencer et al. a. < .01 (2011) b. < .05 c. < .01; < .01; < .05, OR = 11.4; < .01, OR = 4.3 d. < .05 e. < .01, OR = 3.3 f. < .05 Spencer et al. a. = .05 (2013) b. < .05 c. .30 effect for African Americans and Latino/ as combined; .53 effect for Latino/as d. < .05; .44 effect e. .53 effect f. .21 effect for everyone; .31 effect for Latino/as Tang et al. (2014) a. = .004; = .011 b. = .0001; = .0001 c. < .0001; = .0001; = .050 d. Significant (p value NR) e. = .013; = .003; = .030 Wagner et al. a. .002, [r.sup.2] = .082 (2016) b. = .005, [r.sup.2] = .077 c. = .023, [r.sup.2] = .048 d. = .002, [r.sup.2] = .092; = .004 e. = .047, [r.sup.2] = .060 Wagner et al. a. = .000 (2015) b. = .001 Note. OR = odds ratio; r = R-squared; effect = Cohen's D effect size; NR = not reported. Table 5 Main Foci in Findings Theme Articles supporting theme Significant impact on physical Corkery et al., 1997; Gary et al., health 2003; Heisler et al., 2014; Kenya et al., 2014; McDermott et al., 2015; Perez-Escamilla et al., 2015; Prezio et al., 2013; Rothschild et al., 2014; Spencer et al., 2011; Tang et al., 2014; & Wagner et al., 2016 Significant impact on diabetes Babamoto et al., 2009; Corkery knowledge et al., 1997; Kenya et al., 2014; & Wagner et al., 2015 Significant impact on self-care Babamoto et al., 2009; Batts et behaviors al., 2001; Corkery et al., 1997; Gary et al., 2003; Heisler et al., 2014; Kollannoor-Samuel et al., 2016; Rothschild et al., 2014; & Spencer et al., 2011 Significant impact on mental health Heisler et al., 2014; Rothschild and well-being et al., 2014; Spencer et al., 2013; Tang et al., 2014; & Wagner et al., 2016
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|Author:||Trump, Lisa J.; Mendenhall, Tai J.|
|Publication:||Families, Systems & Health|
|Date:||Sep 1, 2017|
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