Peer Coaches to Improve Diabetes Outcomes in Rural Alabama: A Cluster Randomized Trial

Abstract

Purpose: It is unclear whether peer coaching is effective in minority populations living with diabetes in hard-to-reach, under-resourced areas such as the rural South. We examined the effect of an innovative peer-coaching intervention plus brief education vs brief education alone on diabetes outcomes.

Methods: This was a community-engaged, cluster-randomized, controlled trial with primary care practices and their surrounding communities serving as clusters. The trial enrolled 424 participants, with 360 completing baseline and follow-up data collection (84.9% retention). The primary outcomes were change in glycated hemoglobin (HbA1c), systolic blood pressure (BP), low density lipoprotein cholesterol (LDL-C), body mass index (BMI), and quality of life, with diabetes distress and patient activation as secondary outcomes. Peer coaches were trained for 2 days in community settings; the training emphasized motivational interviewing skills, diabetes basics, and goal setting. All participants received a 1-hour diabetes education class and a personalized diabetes report card at baseline. Intervention arm participants were also paired with peer coaches; the protocol called for telephone interactions weekly for the first 8 weeks, then monthly for a total of 10 months.

Results: Due to real-world constraints, follow-up was protracted, and intervention effects varied over time. The analysis that included the 68% of participants followed up by 15 months showed only a significant increase in patient activation in the intervention group. The analysis that included all participants who eventually completed follow-up revealed that intervention arm participants had significant differences in changes in systolic BP (P = .047), BMI (P = .02), quality of life (P = .003), diabetes distress (P = .004), and patient activation (P = .03), but not in HbA1c (P = .14) or LDL-C (P = .97).

Conclusion: Telephone-delivered peer coaching holds promise to improve health for individuals with diabetes living in under-resourced areas.

Keywords: Peer health coaching; diabetes; primary care; self-management support.

Figure 1

Consort diagram. Note: For purposes of analysis, the terms “practices” and “communities” are used interchangeably. As detailed in Andreae, et al, we initially recruited at the participating practices but had to expand into the surrounding communities to meet recruitment targets. Each community in the study corresponded to a single recruited practice, but participants living in that community could have a doctor in any primary care practice, not just the practices recruited for the study. As can be seen in the figure, not all primary care practices we approached agreed to participate. ^a1 practice had 0 participants enrolled.

Figure 2

A–E. Control-intervention arm differences in change in primary outcome measures for all study participants, showing raw change scores (top of each panel) and change scores from generalized additive models adjusting for differences in time from baseline to follow-up, season, baseline value, clustering, education, and race. Note: In each panel, the top graph presents the raw change scores for each participant, with circles and solid lines signifying control arm and triangles and dotted lines signifying intervention arm. The x axis shows the time in days between baseline and follow-up. Vertical lines show the 12 and 15-month follow-up points. The bottom graph in each panel presents the differences between intervention and control change scores from generalized additive mixed models with p-values from tests of statistical significance of the difference between control and intervention arms. See the article text as well. BMI = body mass index; BP = blood pressure; EDF = estimated degrees of freedom; GAMM = generalized additive mixed models; LDL-C = low density lipoprotein cholesterol.

Figure 2

A–E. Control-intervention arm differences in change in primary outcome measures for all study participants, showing raw change scores (top of each panel) and change scores from generalized additive models adjusting for differences in time from baseline to follow-up, season, baseline value, clustering, education, and race. Note: In each panel, the top graph presents the raw change scores for each participant, with circles and solid lines signifying control arm and triangles and dotted lines signifying intervention arm. The x axis shows the time in days between baseline and follow-up. Vertical lines show the 12 and 15-month follow-up points. The bottom graph in each panel presents the differences between intervention and control change scores from generalized additive mixed models with p-values from tests of statistical significance of the difference between control and intervention arms. See the article text as well. BMI = body mass index; BP = blood pressure; EDF = estimated degrees of freedom; GAMM = generalized additive mixed models; LDL-C = low density lipoprotein cholesterol.

Figure 2

A–E. Control-intervention arm differences in change in primary outcome measures for all study participants, showing raw change scores (top of each panel) and change scores from generalized additive models adjusting for differences in time from baseline to follow-up, season, baseline value, clustering, education, and race. Note: In each panel, the top graph presents the raw change scores for each participant, with circles and solid lines signifying control arm and triangles and dotted lines signifying intervention arm. The x axis shows the time in days between baseline and follow-up. Vertical lines show the 12 and 15-month follow-up points. The bottom graph in each panel presents the differences between intervention and control change scores from generalized additive mixed models with p-values from tests of statistical significance of the difference between control and intervention arms. See the article text as well. BMI = body mass index; BP = blood pressure; EDF = estimated degrees of freedom; GAMM = generalized additive mixed models; LDL-C = low density lipoprotein cholesterol.

Figure 2

A–E. Control-intervention arm differences in change in primary outcome measures for all study participants, showing raw change scores (top of each panel) and change scores from generalized additive models adjusting for differences in time from baseline to follow-up, season, baseline value, clustering, education, and race. Note: In each panel, the top graph presents the raw change scores for each participant, with circles and solid lines signifying control arm and triangles and dotted lines signifying intervention arm. The x axis shows the time in days between baseline and follow-up. Vertical lines show the 12 and 15-month follow-up points. The bottom graph in each panel presents the differences between intervention and control change scores from generalized additive mixed models with p-values from tests of statistical significance of the difference between control and intervention arms. See the article text as well. BMI = body mass index; BP = blood pressure; EDF = estimated degrees of freedom; GAMM = generalized additive mixed models; LDL-C = low density lipoprotein cholesterol.

Figure 2

A–E. Control-intervention arm differences in change in primary outcome measures for all study participants, showing raw change scores (top of each panel) and change scores from generalized additive models adjusting for differences in time from baseline to follow-up, season, baseline value, clustering, education, and race. Note: In each panel, the top graph presents the raw change scores for each participant, with circles and solid lines signifying control arm and triangles and dotted lines signifying intervention arm. The x axis shows the time in days between baseline and follow-up. Vertical lines show the 12 and 15-month follow-up points. The bottom graph in each panel presents the differences between intervention and control change scores from generalized additive mixed models with p-values from tests of statistical significance of the difference between control and intervention arms. See the article text as well. BMI = body mass index; BP = blood pressure; EDF = estimated degrees of freedom; GAMM = generalized additive mixed models; LDL-C = low density lipoprotein cholesterol.

Figure 3

A and B. Control-intervention arm differences in change in secondary outcome measures for all study participants by study arm showing raw change scores (top of each panel) and change scores from generalized additive models adjusting for differences in time from baseline to follow-up, season, baseline value, clustering, education, and race. EDF= estimated degrees of freedom; GAMM = generalized additive mixed models. In each panel, the top graph presents the raw change scores for each participant with circles and solid lines signifying control arm and triangles and dotted lines signifying intervention arm. The x axis shows the time in days between baseline and follow-up. Vertical lines show the 12 and 15-month follow-up points. The bottom graph in each panel presents the differences between intervention and control change scores from generalized additive models with p-values from tests of statistical significance between control and intervention arms. See the article text as well.

Figure 3

A and B. Control-intervention arm differences in change in secondary outcome measures for all study participants by study arm showing raw change scores (top of each panel) and change scores from generalized additive models adjusting for differences in time from baseline to follow-up, season, baseline value, clustering, education, and race. EDF= estimated degrees of freedom; GAMM = generalized additive mixed models. In each panel, the top graph presents the raw change scores for each participant with circles and solid lines signifying control arm and triangles and dotted lines signifying intervention arm. The x axis shows the time in days between baseline and follow-up. Vertical lines show the 12 and 15-month follow-up points. The bottom graph in each panel presents the differences between intervention and control change scores from generalized additive models with p-values from tests of statistical significance between control and intervention arms. See the article text as well.