The Lifelong Management (LM) intervention was designed to support patients’ efforts in achieving and sustaining self-management goals in a “real-world” setting. Specifically, the LM intervention followed an empowerment-based approach that was patient-driven and flexible to individual needs, priorities, and life circumstances. This study examined the diabetes-related health impact of the first 6-months of the LM intervention on clinical, self-care, and psychosocial outcomes compared to a 6-month attention-control period with participants serving as their own controls.
While the attention-control condition (i.e., the mailed intervention) was not originally designed as an active intervention, it appeared to serve as a low-intensity intervention that led to modest improvements in diabetes-related health outcomes that were sustained and or further improved during the LM intervention. Following the first 6-months of the attention-control period, participants made significant improvements in DBP and serum cholesterol. They also reported a higher frequency of following a healthy diet, and monitoring blood glucose.
In addition to classic study effects such as volunteer bias and greater motivation at the start of a behavioral intervention, another possible explanation for the health gains associated with the attention-control period is the quality and quantity of “attention” participants received. Immediately following the baseline assessment, clinical results (e.g., A1C, blood pressure, lipid panel) were sent to participants and their diabetes care providers. The feedback given to patients included an explanation of the measure, their results, desired target range, and specific behavioral strategies that could influence the results (e.g., eat less saturated fats). Although we consider this type of feedback to be a standard of care that all patients with diabetes should receive, it is possible that some participants were not receiving this minimal level of care prior to participation in the study. For this reason, the clinical feedback could have prompted providers to make treatment adjustments and/or participants to initiate health-promoting practices. Research has shown that feedback can function as a cue that stimulates behavior change [26
For instance, reductions in DBP and serum cholesterol could be attributed to treatment intensification on the part of providers. In fact, a greater percentage of patients reported taking blood pressure (pre-control 85% vs. post-control 89%) and cholesterol medication (pre-control 66% vs. post-control 72%) at the end of the control period compared to baseline. Consistent with this explanation, Hiss and colleagues [28
] found that, among patients whose clinical values were above normal range, clinical feedback to physicians was associated with improvements in glycemic control, blood pressure and cholesterol at 1-year follow-up.
In addition to clinical feedback, we also mailed weekly newsletters on core self-management topics. These newsletters provided diabetes information, addressed psychosocial concerns, and included strategies to improve self-management practices to an already motivated group. Six out of the 24 newsletters addressed healthy eating and/or blood sugar testing. Consequently, weekly reminders of self-care behaviors coupled with clinical feedback may have contributed to the positive changes patients reported in dietary patterns and blood sugar monitoring. In fact, a study by Anderson and colleagues found that providing diabetes education newsletters on a weekly basis activated behavior change in diet, exercise, glucose monitoring, and weight loss [25
Similar to the attention-control period, participation in the LM intervention was also associated with modest improvements in health outcomes including glycemic control, weight, BMI, and LDL. Compared to the control period, the LM intervention led to a significant reduction in A1C.
In terms of psychosocial outcomes, there were no changes in diabetes-specific quality of life associated with the control or intervention period. It is important to note that, at baseline, the group, on average reported a highly positive diabetes-specific quality of life (mean=32.7, sd=16.7). On a 6-point likert scale with scores ranging from 17 – 102 (lower scores indicate higher quality of life), a baseline mean under 33 leaves a very narrow range for improvement. Therefore, the lack of change in this variable could be partially due to a floor effect.
We also found no within- or between- period differences in diabetes empowerment. This finding is inconsistent with Anderson and colleague’s [6
] study that indicated improvements in diabetes empowerment for the control group and empowerment-based intervention group. While this study and Anderson et al.’s [6
] study used a similar empowerment-based approach to self-management, there were some distinct differences. Anderson et al.’s [6
] intervention consisted of 6 self-management education sessions conducted over a 6-week period with the expectation that participants would attend all 6 sessions. In contrast, the LM intervention consisted of 24 weekly self-management support sessions conducted over a period of 6-months in which participants were encouraged to attend sessions as frequently as needed to obtain support and/or education. It is possible that improvements in diabetes empowerment are most prominent in the short-term, particularly with concentrated and frequent exposure to empowerment-based support. It is equally plausible that this intervention had no impact on diabetes empowerment.
Contrary to other self-management programs, the LM intervention was specifically designed to accommodate individuals with type 2 diabetes living under “real-life” conditions. In other words, given the variability in participants’ support needs, priorities, responsibilities, coping styles, etc., we did not expect the attendance rate to be 100%. In fact, patients were informed that while the sessions would be available weekly, they were invited to attend only as often as they felt it would be helpful for them. Based on our goal to attract at least 15% to 20% (n=12 to 15 participants) of the sample each week, we met our expectation for morning sessions (m=21%; n=16 participants) and fell below our expectation for afternoon sessions (m=10%; n=8 participants). Overall, attendance remained relatively stable over the course of 24 sessions.
It should be noted that 5 out of 48 sessions (10% of total morning and afternoon sessions) attracted a group size of 20–25 participants. While we recognize that a group of this size may not be ideal, our experience was that all participants who came with specific questions or issues were able to discuss them either in the session or afterwards with the facilitators. Our primary goal was to develop and evaluate an innovative model for providing ongoing self-management support that is flexible and can accommodate a large number of participants with different support needs and attendance patterns. Indeed, a disadvantage of this type of intervention is the small chance that sessions may fill over the optimal capacity. Therefore, when implementing this intervention in the future, it would be beneficial to consider adding an additional weekly session contingent on total group size.
Similar to our previous study [18
], the frequency and patterns of attendance varied across individuals. Some participants attended weekly, some attended monthly, and others attended less consistently. Given that frequency of attendance was not related to diabetes-related health outcomes, a possible interpretation is that people, indeed, have the ability to accurately assess the level of support they need and seek this support accordingly.
Several limitations to this study need to be acknowledged. Due to funding constraints, we were unable to use a randomized controlled trial (RCT) design for this study. Instead, we employed a control-intervention time-series design with participants serving as their own controls. Findings suggest that our attention-control condition served as an active intervention that produced improvements, thereby diluting potential control-intervention differences. Moreover, study effects such as greater enthusiasm at the start of a behavioral intervention may have further enhanced the improvements made in the first 6 months of the study (i.e., attention-control condition). These methodological issues underscore the importance of designing the optimal control group particularly for studies where an RCT design is not financially feasible.
As mentioned previously, treatment intensification triggered by clinical feedback may have contributed to improvements associated with the control condition. However, we did not collect detailed documentation of treatment changes (e.g., type of medication or dosage) during the 6-month attention-control period. Therefore, the unique influence of provider behavior cannot be examined. Future investigations should conduct medical chart reviews to monitor and track provider-initiated treatment changes particularly in response to clinical feedback. It is possible that clinical feedback can serve as an effective intervention on its own. In summary, this program complemented and enhanced the treatment these patients were receiving and resulted in modest metabolic improvements.
Alternatively, this study could be conceived as testing an intervention consisting of two phases with phase one: a low-intensity, mailed education and clinical feedback intervention followed by phase two: a high-intensity empowerment-based, weekly self-management support intervention conducted in a group setting. With this perspective, the findings would suggest that participation in a low-intensity education and feedback intervention is associated with improvements in some diabetes-related clinical (e.g., DBP, serum cholesterol) and behavioral (e.g., following a healthy diet, monitoring blood sugar) outcomes with additional clinical improvements (e.g., A1C, weight, BMI, LDL) when followed by a high-intensity, empowerment-based self-management support intervention.