DNP 750 Week 3 Summary of the Evidence Supporting the Intervention Example

Seven Sources, Three Questions: Appraising the Evidence That Diabetes Distress Can Be Found With Two Items, Matters for Glycemic Control and Responds to Structured Follow-Up

[Student Name]

University of Phoenix

DNP/750: DNP Applied Project I

Week 3 Assignment

[Instructor Name]

[Date]

The health center and figures are composites written for a model paper.

The question guiding the project, written last week in PICOT form, concerns a brief distress screen at diabetes visits, a longer questionnaire for anyone who scores high and nurse follow-up, measured over 12 weeks at our site. This paper summarizes and appraises the evidence behind that intervention. It describes the search, organizes the sources around three questions, rates each source and states what the evidence as a whole supports.

Search Strategy

I searched CINAHL, PubMed and PsycINFO for English-language sources from 2005 to 2025, using combinations of diabetes distress, Diabetes Distress Scale, DDS2, screening, primary care, type 2 diabetes, care management and intervention. In all, 412 records came back. After dropping duplicates, I read titles and abstracts and kept those relevant to adults with type 2 diabetes and to detection, significance or treatment of distress, 38 full texts were read. Seven sources were retained as the strongest and most relevant. Each was leveled with the Johns Hopkins evidence hierarchy and rated for quality as high, good or low.

Question 1: Can Distress Be Detected Reliably and Briefly?

Polonsky et al. (2005) started from 28 candidate items, tested them with patients at four clinical sites and kept 17. Factor analysis produced four consistent domains using 17 items, with internal reliability above .87 and expected associations with depressive symptoms, self-care and A1C. This is a psychometric study, level III, good quality; its limitation is that samples were drawn from specialty and primary care settings with limited ethnic and income diversity.

Fisher et al. (2008) then selected the scale items most closely correlated with the total score and tested two-, three- and four-item versions. The two-item DDS2 identified patients whose full-scale score indicated moderate or higher distress with a sensitivity of .95 and a specificity of .85. This is level III, good quality. For a primary care workflow, a two-item screen with high sensitivity is the right tool: it misses few patients with distress, and the longer scale can then sort out false positives and show what the distress is about. Its limitation is that the cut point was derived and tested in the same kind of sample, not validated separately in a low-income population.

Question 2: Does Distress Matter for Outcomes?

Perrin et al. (2017) pooled 55 studies with 36,998 people with type 2 diabetes and estimated distress prevalence at 36%, higher where samples had more women and more depressive symptoms. This systematic review and meta-analysis is level III under the hierarchy because the studies it pools are nonexperimental, high quality; heterogeneity across measures is its main limitation.

In a longitudinal cohort, Fisher et al. (2010) set side by side major depression, depressive symptoms and diabetes distress as correlates of A1C. Only distress was associated with A1C, both at one time point and in time-concordant change. This cohort study is level III, good quality; as an observational design it cannot show that distress causes higher A1C.

Fisher et al. (2012) examined the shape of the relationship between distress scores and A1C, self-efficacy, diet and physical activity in two samples and found curvilinear links beginning at low levels. They proposed three groups by mean item score: under 2.0 as little or none, 2.0 through 2.9 as moderate, and 3.0 or more as high. This is level III, good quality, and gives the project its reporting categories.

Question 3: Does Anything Reduce Distress Once It Is Found?

Fisher et al. (2013) reported REDEEM, a pragmatic randomized trial enrolling adults who had type 2 diabetes and elevated distress, comparing a computer-assisted self-management program, the same program with a distress-focused problem-solving component and an educational control. Distress and self-management improved significantly in all three arms, with no overall difference between them; patients with high regimen distress improved more in the distress-focused arm. This is level I, high quality. Its message for the project is that structured contact of several kinds reduces distress, while patients with the highest regimen distress may need a component aimed directly at it.

Tricco et al. (2012) meta-analyzed 142 trials of quality improvement strategies for diabetes care and found an average A1C reduction of 0.37 percentage points, with case management and team changes among the effective strategies and larger effects when baseline A1C was above 8%. Level I, high quality. It supports using registered nurse care managers as the vehicle for follow-up, although it does not measure distress.

National Standards

Standards from the American Diabetes Association Professional Practice Committee (2025) recommend routine monitoring for diabetes distress, especially when treatment goals are not met, and addressing it through education, problem solving or referral. Standards are level IV evidence, but they confirm that the intervention is consistent with current expectations for diabetes care.

Synthesis

Taken together, the sources show that diabetes distress is common in type 2 diabetes, is measurable with a validated scale, can be screened for in two items with high sensitivity, is associated with A1C and self-care from modest levels upward, and declines with structured intervention. The evidence for detection and significance is consistent across studies; the evidence for reduction rests mainly on one well-designed trial and on broader evidence that care management improves diabetes outcomes.

Applicability to the Site

Applicability matters as much as strength. The REDEEM sample and most scale studies drew on insured patients in large health systems, while our site serves mainly patients on Medicaid or without insurance. That difference cuts both ways: distress may be more common and more tied to money and time pressures at our site, and patients may have less access to the kinds of follow-up tested in trials. The care manager model reviewed by Tricco et al. (2012), however, was tested across more than a hundred trials in varied settings, and our site already employs care managers. The two-item screen needs no special equipment and can be given on the tablets medical assistants already use. The evidence therefore transfers well for detection and reasonably for follow-up, provided the pathway offers options that fit patients' circumstances, such as phone contact and same-day handoffs rather than weekly sessions.

Gaps

Few studies test distress screening as a routine workflow in safety-net primary care, and none of the retained sources measured whether screening alone changes outcomes. Most samples were English-speaking. These gaps argue for careful measurement at the site rather than against the change.

Strength of the Body of Evidence

Rated as a whole with the Johns Hopkins approach, the body of evidence is good and consistent for detection and significance: several good-quality studies by overlapping research groups, confirmed by a large meta-analysis, point the same way. For reduction of distress, the evidence is good but thinner, resting on one high-quality trial and indirect support from care management research. Consistency across sources, and the absence of any study suggesting harm from screening, support a practice change so long as outcomes are measured at the site.

Recommendation

The evidence is strong enough to implement DDS2 screening, full-scale follow-up for positive screens and a care manager pathway at the site as a quality improvement project, with outcomes measured locally and a plan for Spanish-speaking patients.

Conclusion

Seven sources answer the three questions that the intervention depends on. Detection and significance are well supported; response to follow-up is supported by a pragmatic trial and by care management evidence. Next week I will select the translational framework that will guide implementation.

References

American Diabetes Association Professional Practice Committee. (2025). 5. Facilitating positive health behaviors and well-being to improve health outcomes: Standards of care in diabetes 2025. Diabetes Care, 48(Suppl. 1), S86-S127. https://doi.org/10.2337/dc25-S005

Fisher, L., Glasgow, R. E., Mullan, J. T., Skaff, M. M., & Polonsky, W. H. (2008). Development of a brief diabetes distress screening instrument. Annals of Family Medicine, 6(3), 246-252. https://doi.org/10.1370/afm.842

Fisher, L., Hessler, D., Glasgow, R. E., Arean, P. A., Masharani, U., Naranjo, D., & Strycker, L. A. (2013). REDEEM: A pragmatic trial to reduce diabetes distress. Diabetes Care, 36(9), 2551-2558. https://doi.org/10.2337/dc12-2493

Fisher, L., Hessler, D. M., Polonsky, W. H., & Mullan, J. (2012). When is diabetes distress clinically meaningful? Establishing cut points for the Diabetes Distress Scale. Diabetes Care, 35(2), 259-264. https://doi.org/10.2337/dc11-1572

Fisher, L., Mullan, J. T., Arean, P., Glasgow, R. E., Hessler, D., & Masharani, U. (2010). Diabetes distress but not clinical depression or depressive symptoms is associated with glycemic control in both cross-sectional and longitudinal analyses. Diabetes Care, 33(1), 23-28. https://doi.org/10.2337/dc09-1238

Perrin, N. E., Davies, M. J., Robertson, N., Snoek, F. J., & Khunti, K. (2017). The prevalence of diabetes-specific emotional distress in people with type 2 diabetes: A systematic review and meta-analysis. Diabetic Medicine, 34(11), 1508-1520. https://doi.org/10.1111/dme.13448

Polonsky, W. H., Fisher, L., Earles, J., Dudl, R. J., Lees, J., Mullan, J., & Jackson, R. A. (2005). Assessing psychosocial distress in diabetes: Development of the Diabetes Distress Scale. Diabetes Care, 28(3), 626-631. https://doi.org/10.2337/diacare.28.3.626

Tricco, A. C., Ivers, N. M., Grimshaw, J. M., Moher, D., Turner, L., Galipeau, J., Halperin, I., Vachon, B., Ramsay, T., Manns, B., Tonelli, M., & Shojania, K. (2012). Effectiveness of quality improvement strategies on the management of diabetes: A systematic review and meta-analysis. The Lancet, 379(9833), 2252-2261. https://doi.org/10.1016/S0140-6736(12)60480-2