An Integrated Psychosomatic Treatment Program for People with Diabetes (psy-PAD)

Results of a Randomized Controlled Trial

Background: Many people with diabetes have permanently elevated blood sugar concentrations and a high level of diabetes-related psychological stress, also called “diabetes distress.” In clinical practice, diabetes distress is often an impediment to successful self-management. psy-PAD is a psychodynamically oriented short-term therapy program whose goal is to reduce diabetes distress and improve glycemic control.

Methods: A randomized controlled trial was conducted with 143 patients with either type 1 or type 2 diabetes who were being treated in eleven specialized diabetological practices. psy-PAD in the intervention group (eight sessions) was compared with optimized standard care as the control condition. The inclusion criteria were HbA1c ≥ 7.5% combined with diabetes distress (PAID >35, or doctor’s determination). The primary endpoint was the HbA1c at six months (t₁). Diabetes-related distress (PAID), depressive symptoms (HADS-D, PHQ-9), anxiety symptoms (HADS-A), health-related quality of life (SF-36), panic (short form of the PHQ-D), body mass index (BMI), and triglyceride levels were secondary endpoints. Follow-ups were conducted at six (t₁) and 12 months (t₂) (trial registration: DRKS00003247).

Results: The intergroup comparison at t₁ revealed a significant, clinically relevant reduction of HbA1c by −0.53 percentage points (95% confidence interval [−0.89; −0.16], p = 0.005). The secondary analyses revealed relevant differences in the point estimators for diabetes distress at t₁ and t₂, depressive symptoms at t₂ and BMI at t₁.

Conclusion: For people with diabetes and diabetes distress who do not achieve satisfactory glycemic control despite intensive treatment in specialized diabetological practices, integrated psychosomatic-psychotherapeutic treatment can lower blood sugar levels over the intermediate term and also reduce diabetes distress and depressive symptoms over a one-year period.

With rising prevalences, more than 8 million people were diagnosed with type 2 diabetes mellitus in Germany in 2020. To this figure one can add approximately 32,000 children and adolescents, as well as around 340,000 adults, diagnosed with type 1 diabetes (1). Acute metabolic crises in the form of severe hyperglycemia, life-threatening hypoglycemia, and the development of micro-/macrovascular complications contribute to the increased risk of mortality compared with the normal population (2, 3, 4, 5). Therefore, one of the primary treatment goals of diabetes therapy is to achieve balanced blood sugar metabolism control in order to prevent the risk of acute crises and the development of diabetic complications. Despite intensive health policy efforts, for example in the form of disease management programs (DMPs) or specific diabetes education/training programs, unsatisfactory metabolic control is still found in a relevant proportion of patients. For example, according to the North Rhine DMP report, 58.4% of all people with type 1 diabetes and 40.4% with type 2 diabetes fail to achieve the blood sugar target levels agreed upon (usually < 7.5%) (6).

Patients’ self-management behavior plays a central role in blood sugar control. Reasons for unfavorable self-management behavior can be patient-related, practitioner-related, or environment-related. Against this backdrop, psychosomatic aspects increasingly come to the fore. Many people with diabetes experience a high level of diabetes-related psychological stress, also referred to as “diabetes distress,” (type 1: ~ 44%; type 2: ~ 25  % [7]), as well as comorbid mental illnesses, such as depressive disorders (type 1 ~ 6% [8]; type 2 ~ 15% [9]) and anxiety disorders (type 1: ~ 8% [8]; type 2: ~ 7  % [10]). These result not only in impediments to diabetes self-management and reduced quality of life but also in poorer glycemic control (11, 12), an increased risk of complications (13) and mortality (2, 3, 4, 5), as well as significantly increased costs (14). By focusing psychosocial treatment approaches on reducing diabetes distress, it may be possible to help affected individuals reduce impediments to treatment and, thus, also achieve improvements in their glycemic control. On an international level, integrated treatment approaches enabling access to structured interdisciplinary care concepts that are integrated in primary care have been shown to be effective, with heterogeneous results seen in terms of HbA1c improvement (15, 16).

This study evaluates a cross-sectoral, psychodynamically oriented, integrated psychosocial and psychosomatic treatment program for patients with diabetes (psy-PAD), which is implemented in a collaboration between psychosomatic outpatient clinics and diabetologists in specialized practices. The assumption is that psy-PAD can achieve a significant improvement in glycemic control (HbA1c) compared to optimized standard care. Reductions in diabetes distress, depressive symptoms, and anxiety, as well as an increase in health-related quality of life, were also anticipated.

Methods

The study was conducted as a two-armed randomized controlled trial (RCT). In contrast to the data held by the German Registry of Clinical Trials (DRKS), the HbA1c at t₂ that was erroneously filed there does not represent a primary endpoint; this also applies to all prospectively submitted documents, such as the ethics application and the application to the German Medical Association (Bundesärztekammer, BÄK) for funding. Due to the complexity of practical implementation in routine care in specialized diabetological practices, and in contrast to the original study protocol, the inclusion criterion “significant distress in the management of diabetes” was not evaluated by means of PAID alone, but also by the clinical impression of the treating diabetologists. Therefore, inclusion criteria included diagnosed type 1/type 2 diabetes, age between 18–70 years, previous completion of diabetes training, HbA1c ≥ 7.5%, and significant diabetes distress (determined by PAID > 35 or identified by the treating diabetologist). Exclusion criteria included severe comorbid physical illness (for example, oncological disease), dementia, severe mental illness (for example, severe depressive episode, psychosis, addiction disorder), as well as insufficient knowledge of the German language. Recruitment was carried out in 11 specialized diabetological practices by means of informed consent.

In addition to standard care, patients in the intervention group (IG) received the short intervention psy-PAD. This is based on a low-threshold, psychodynamically oriented short-term therapy program, the goal of which is to achieve a reduction in psychosocial impediments to treatment and diabetes distress, thereby also improving metabolic control. In terms of content, it integrates elements from self-management therapy and solution-oriented psychotherapy in four phases (see also Köhler and Kruse [17] as well as eMethods Section 1). The psy-PAD program comprised eight individual sessions, which were initially held weekly (4 ×) and later monthly (4 ×) by psychotherapists from the psychosomatic outpatient department, Gießen, Germany, in the specialized practice. Patients in the control group (CG) received standard care in the specialized practices and also received a consultation in the psychosomatic outpatient department at baseline, as well as brief verbal contact with the psychosomatic department at 6 and 12 months. If, as part of this, any evidence of mental illness came to light, the patients were informed about treatment options. The treating diabetologist was also accordingly informed (= optimized standard care).

Data collection was conducted at three measurement time points, t₀ (= pre-intervention), t₁ (= 6 months post intervention), and t₂ (= 12 months post intervention). The primary outcome was HbA1c at t₁ (Bio-Rad VARIANT II; centralized determination at the certified laboratory of the German Diabetes Center, Düsseldorf). Secondary outcomes included body mass index (BMI) and triglyceride levels, as well as diabetes-related distress (PAID) (18, 19, 20), anxiety and depressive symptoms (HADS) (21), health-related quality of life (SF-36) (22), and panic and depressive symptoms (PHQ-D and PHQ-9, respectively) (23), as recorded using questionnaires. Screening to exclude dementia and severe depressive episodes was performed using DemTect (24) and SCID-I (25). Further details on the instruments used are provided in the eMethods Section 2. Information on sample size, power, randomization, and blinding can be found in eMethods Section 3.

Statistical analyses

The analysis was performed according to the intention-to-treat (ITT) principle. All participants that had taken part in the first follow-up at t₁ were selected as the study population. Baseline characteristics were described separately for the intervention and control groups by frequency distributions, means (M) ± standard deviations (SD), and, for triglyceride levels, by geometric means (GM)*/: standard deviation factors (SDF). Normal distributions were assumed for the primary outcome HbA1c and the (continuous) secondary outcomes, while a log-normal distribution was assumed for the triglyceride levels distributed with a right skew. In accordance with the sample size determination, individual HbA1c differences (Delta t₁–t₀) between the intervention and control groups were compared using the independent groups t-test. In addition, sensitivity analyses using last observation carried forward (LOCF) analysis were performed based on the ITT population for the primary parameter of difference in HbA1c between t₀ and t₁ with group comparison by means of t-test. Here, in accordance with LOCF, the HbA1c difference value of 0 was imputed between t₀ and t₁. Secondary analyses were performed using linear mixed models with adjustment for baseline values at t₀ and for dependencies arising from repeated measures in both groups. For adjustment following repeated measures, the general covariance structure was selected. Analyses were performed using SAS Version 9.4 (STAT 15.2).

Results

Of the N = 213 patients screened in the specialized diabetological practices, n = 178 met the inclusion or exclusion criteria and were randomized to one of the two study conditions (see the Figure for details on patient flow and drop-out reasons). The sensitivity analysis for the primary outcome HbA1c at t₁ was based on the ITT population (N = 177), which also included the n = 34 (IG: n = 18; CG: n = 16) patients hitherto not included, for which no data regarding HbA1c at t₀ or t₁ were available. There was also no baseline value at t₀ for n = 4 patients in the IG and n = 5 patients in the CG.

Figure

Flowchart on inclusion and course of study

Overall, data on t₀ and t₁ were available for n = 143 individuals, meaning that these were included in the evaluations (IG: n = 69; CG: n = 74, drop-out rate 19.7%). There were no patients for whom data were available at t₂ but not at t₁. Patient recruitment took place between February 2010 and June 2014. Tables 1 and 2 provide an overview of sociodemographics as well as information on mental health at t₀. A representation of sociodemographics stratified according to diabetes type can be viewed in eTable 1.

Table 1

Sociodemographic data at t₀

Table 2

Mental health at t₀

eTable 1

Sociodemographic data at t₀ broken down according to diabetes type

The main analysis of the primary outcome included mean change 6 months post intervention (Delta t₁–t₀). The secondary analyses include mean changes and estimated effects at both 6 months (Delta t₁–t₀) and 12 months (Delta t₂–t₀). Tables 3a and 3b provide a detailed overview of group differences (between-subject effects). Changes over time (within-subject effects) can be found in eTable 2.

Table 3a

Primary analysis: differences between IG and CG

Table 3b

Secondary analyses: differences between the IG and CG

eTable 2

Secondary analyses: differences within the IG and CG (within-subject effects)

Primary analysis: HbA1c at t1

In the primary analysis, HbA1c differences between t₀ and t₁ differed statistically significantly and clinically relevantly from each other between IG (M  = − 0.36 percentage points [SD  =  1.06]) and CG (M  =  0.16 percentage points [SD  =  1.16]) with a group difference of −0.53 percentage points (95% confidence interval: [−0.89; −0.16], p = 0.005).

Likewise in the sensitivity analysis of the ITT population, the reduction in HbA1c in the IG was significantly greater compared to the CG. The mean difference in Delta t₁−t₀ HbA1c values between IG and CG was −0.42 percentage points ([0.72; −0.12], p = 0.006).

Secondary analyses

With a mean change of −0.48 percentage points in HbA1c, the comparison between the IG and the CG at t₁ showed a relevant difference in the point estimators in favor of the IG; however, this difference was no longer evident in the further time course from t₀ to t₂. Since linear mixed models with adjustments were used in the secondary analyses, slight differences emerge in the mean change in HbA1c at t₁ (−0.48 percentage points) compared with the primary analysis (−0.53 percentage points).

For PAID, a relevant difference in point estimators was found in favor of the IG at both measuring time points. At t₁, the mean PAID change between IG and CG was −5.25 points, and at t₂ −5.35 points.

While there was no relevant difference in point estimators regarding depression (HADS-D) in the comparison between the IG and the KG at t₁, a relevant difference was found in favor of the IG (1.25 points) at 12-month follow-up at t₂. The converse was true for the mean difference in BMI: here, with –0.71 BMI points at t₁, a difference in point estimators was found in favor of the IG, but this was no longer evident at t₂.

For PHQ-9, HADS-A, SF-36, and triglyceride levels, a comparison of IG and CG revealed no relevant difference in point estimators at either of the measurement time points.

Discussion

The results on the primary endpoint HbA1c show that individuals with diabetes who had elevated blood sugar levels (HbA1c ≥ 7.5%) and diabetes distress in a specialized diabetology practice were able to achieve clinically relevant improvements in glycemic control through the low-threshold, cross-sector psychodynamically oriented short-term therapy program psy-PAD compared with optimized standard care. With a mean change of −0.53 percentage points in the 6-month mental health follow-up, there was a statistically significant (p = 0.005) and clinically relevant intergroup difference. Secondary analyses also looked at 12-month mental health follow-up. However, with a mean change in HBA1c of −0.29 percentage points, there were no differences in the point estimators. In this context, the effect at 1 year is also very close to the relevance threshold of 0.3 percentage points used by the European Medicines Agency (EMA) to assess a clinically relevant group difference (26). The fact that, despite this, no relevant difference in the point estimators could be achieved may be explained by the fact that sample size determination was primarily geared towards the comparison of HbA1c in the IG and the KG from t₀ to t₁. Although the power for this comparison was sufficient despite the slightly lower number of cases (N = 143 instead of N = 150), it is possible that, at times, this was insufficient to show the t₀−t₂ effect for HbA1c as well as secondary outcomes due to the lower number of cases at t₂.

A significant overall reduction in diabetes distress was seen over the course of the study, thereby making it possible to address one of the therapeutic goals of diabetes treatment. In the group comparison, the reduction was greater in the IG both at 6 months and at 12 months post intervention than under optimized standard care. In addition, the 12-month mental health follow-up revealed a difference with regard to depressive symptoms. This effect was seen even though the intervention was deliberately designed in such as way as to not primarily address depressive symptoms, but instead to focus on diabetes distress and its causes. Thus, the results also provide an indication that depressive symptoms in patients with diabetes are closely linked to diabetes distress. For anxiety, on the other hand, there were no group differences, even though a significant reduction was seen in the IG at both measurement time points. Despite the fact that in the absence of a passive control group (i.e., standard care) it is not possible to make any statements about the effect of an additional psychosomatic outpatient consultation and how the further standard care in the specialized practice would have been affected without such an option, it is reasonable to assume that even a low-threshold option such as a psychosomatic outpatient consultation in the context of dedicated psychotherapeutic consultation hours can be helpful for patients. This is also evident in the fact that there was significant improvement in mental health in the two groups at both the 6-month and 12-month mental health follow-ups.

Neither of the study conditions appeared to have an effect on physical health or triglyceride levels. For BMI, on the other hand, the group comparison showed a medium-term reduction in favor of the IG, but this was no longer evident at 12 months. Thus, overall, it cannot be assumed that offering short-term therapy leads to long-term somatic improvements.

Limitations

As a result of study drop-outs, it is not possible to exclude bias. Drop-out analyses showed that the study population (N = 143) had higher scores for weight and physical health-related quality of life and lower scores for depression compared with dropouts between t₀ and t₁ (N = 34). Moreover, patients that dropped out before t₁ were more likely to be married or widowed and less likely to suffer from a panic disorder or a depressive disorder. There were no differences with regard to the primary outcome HbA1c. Secondary sensitivity analysis of the ITT population regarding the primary outcome HbA1c at t₁ verified the result of the primary analysis. A multiple imputation analysis was not performed since the LOCF analysis revealed no evidence of drop-out bias in the results. The psy-PAD study addressed a highly distressed patient population in specialized practices, meaning that it is not possible to readily extrapolate the results to patients in, for example, primary care or with less pronounced symptoms. Moreover, psy-PAD was a cooperation model between diabetology practices and psychosomatic outpatient departments in the Gießen/Marburg/Wetzlar area. An assessment needs to be made as to whether the regional networks and collaborations could similarly be transferred to other regions in Germany, especially rural areas. Furthermore, it should be noted that a comparison was carried out with an active control group that also received a psychosomatic intervention in the form of one consultation. This means that the results are at times more conservative than would have been the case if they had been compared with conventional routine care, which includes virtually no psychosomatic treatment components. In addition, there is no knowledge regarding which other, for example psychotherapeutic, services were used during the study period.

Conclusion

The psy-PAD study showed that an integrated, cross-sectoral, psychodynamically oriented therapy program in people with diabetes and problematic glycemic control as well as increased diabetes distress can achieve a clinically meaningful and statistically significant reduction in HbA1c in the medium term. In addition, the group comparison demonstrated a reduction in diabetes-related distress and depressive symptoms. Future research should investigate the possibilities (medical, psychosocial, and economic) of further networking specialized diabetology practices and psychosomatic outpatient departments to improve care and evaluate the potential of low-threshold psychotherapeutic/psychosomatic programs.

Affiliations

Acknowledgments
We would like to express our sincere thanks to all patients who participated in the study. We would also like to thank our colleagues at the specialized diabetological practices for their support and for the interdisciplinary exchange: Dr. med. M. Brinschwitz (Marburg), Dr. med. A. Csecke (Gießen), Dr. med. M. Eckhard (Bad Nauheim), PD Dr. K. Ehlenz (Gießen), Dr. med. M. Eidenmüller (Marburg), Dr. med. B. Fischer, Dr. med. R. Göbel (Wetzlar), S. Hewel-Hildebrand (Marburg), Dr. med. U. Kajdan (Kirchhhain), Frau Dr. J. Liersch (Gießen), Dr. C. Marck (Gießen-Pohlheim), and F. W. Petry (Wetzlar).

Funding
The study was funded by the BÄK (Project No. 08-62).

Registration
The study was approved by the Ethics Committee of the Justus Liebig University Gießen (Ref. No.: 163/09) and registered with the German Register of Clinical Trials (DRKS): DRKS00003247.

Data sharing statement
Individual, anonymized patient data on which the results of the present article are based will be made available to researchers submitting a methodologically sound analysis proposal. Analysis proposals can be submitted up to 36 months following publication of the article via the contact details for the first author.

Conflict of interest statement
The authors declare that no conflict of interests exists.

Manuscript received on 29 September 2021, revised version accepted on 20 December 2021.

Translated from the original German by Christine Rye.

Corresponding author
Dr. phil. Hanna Kampling
Klinik für Psychosomatik und Psychotherapie
Universitätsklinikum Gießen und Marburg GmbH
Standort Gießen
Ludwigstraße 76
35390 Gießen

Cite this as
Kampling H, Köhler B, Germerott I, Haastert B, Icks A, Kulzer B, Nowotny B, Hermanns N, Kruse J: An integrated psychosomatic treatment program for people with diabetes (psy-PAD)—results of a randomized controlled trial. Dtsch Arztebl Int 2022; 119: 245–52. DOI: 10.3238/arztebl.m2022.0094

►Supplementary material

eReferences eMethods Sections, eTables:
www.aerzteblatt-international.de/m2022.0094

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