Juliane Menting

Web-based cognitive behavioural therapy blended with face-to-face sessions for chronic fatigue in type 1 diabetes: a multicentre randomised controlled trial

BACKGROUND Fatigue in type 1 diabetes is prevalent and persistent, but so far, no evidence-based treatments are available. We aimed to investigate the efficacy of cognitive behavioural therapy (CBT) in reducing fatigue severity in patients with type 1 diabetes. METHODS We did a multicentre randomised controlled trial at one university medical centre and four large teaching hospitals in the Netherlands. Eligible patients were aged 18-70 years and had type 1 diabetes for at least 1 year and chronic fatigue for at least 6 months. We randomly assigned patients (1:1) to CBT or waiting list using computer-generated blocked randomisation, stratified by type of enrolment. The CBT intervention (Dia-Fit) was given for 5 months in blended form, consisting of face-to-face and web-based sessions. The primary outcome was fatigue severity assessed 5 months after randomisation, directly after the intervention or waiting list period, with the Checklist Individual Strength fatigue severity subscale. Secondary outcomes were functional impairment (assessed with the total score of the Sickness Impact Profile-8), glycaemic control (HbA1c), and glucose variability. Analyses were done by intention to treat. This trial is registered with the Nederlands Trial Register, number NTR4312. FINDINGS Between Feb 6, 2014, and March 24, 2016, we randomly assigned 120 eligible patients to either CBT (n=60) or waiting list (n=60), all of whom were included in the intention-to-treat analyses. Compared with patients in the waiting list group, those in the CBT group had significantly lower fatigue severity scores (mean difference 13·8, 95% CI 10·0-17·5; p<0·0001) and significantly lower scores for functional impairment (mean difference 513, 95% CI 340-686; p<0·0001) after 5 months. HbA1c and glucose variability did not change after treatment and there was no difference between groups. Five patients in the CBT group and seven in the waiting list group reported adverse events; none were deemed to be related to the study intervention. INTERPRETATION Although our findings need to be confirmed in larger and longer-term studies, they suggest that CBT can effectively reduce fatigue severity and functional impairment in type 1 diabetes. FUNDING Dutch Diabetes Research Foundation (Diabetes Fonds).

Severe fatigue in type 1 diabetes: Exploring its course, predictors and relationship with HbA1c in a prospective study

AIMS To prospectively identify the course of severe fatigue, its predictors and the relationship with HbA1c in patients with type 1 diabetes. METHODS 214 adult patients completed questionnaires on fatigue severity and fatigue-related factors at baseline. HbA1c was retrieved from medical records. After 43months, fatigue severity and HbA1c were reassessed in 194 patients. A logistic regression analysis was used to determine predictors of severe fatigue at follow-up with various cognitive-behavioral and clinical factors as potential predictors. The relationship between fatigue and HbA1c was investigated in a sub-analysis by differentiating between patients with suboptimal glucose control [HbA1c>7% (53mmol/mol)] and optimal glucose control [HbA1c⩽7% (53mmol/mol)]. RESULTS The prevalence of severe fatigue was 40% at baseline and 42% at follow-up. In three out of four severely fatigued patients at baseline (76%), severe fatigue persisted over time. More depressive symptoms, more pain, sleep disturbances, lower self-efficacy concerning fatigue, less confidence in diabetes self-care, more fatigue severity at baseline and more diabetes complications predicted severe fatigue at follow-up. Over time, HbA1c at baseline was positively associated with fatigue severity at follow-up in both groups (suboptimal glucose control: r=.18, p<.05; optimal glucose control: r=.09, p<.05). CONCLUSIONS About three quarters of fatigued[corrected] patients with type 1 diabetes suffer from persistent fatigue. Aside from the number of diabetes complications, no clinical factors explained the persistence of fatigue. HbA1c and fatigue were weakly associated in a sub-analysis. Since the strongest predictors of severe fatigue were cognitive-behavioral factors, behavioral interventions might be effective in decreasing fatigue.

A web-based cognitive behaviour therapy for chronic fatigue in type 1 diabetes (Dia-Fit): study protocol for a randomised controlled trial

BackgroundFatigue is frequently reported by patients with type 1 diabetes mellitus. A recent study showed that 40 % of patients experienced severe fatigue that lasted for more than six months and was accompanied by substantial impairments in daily functioning. Currently, there is no effective treatment available for chronic fatigue in patients with type 1 diabetes. Cognitive behaviour therapy aimed at cognitions and behaviours that perpetuate fatigue is effective in reducing fatigue in other chronic diseases. Recent research showed that these cognitions and behaviours are also potential determinants of fatigue in type 1 diabetes. We designed Dia-Fit, a web-based cognitive behaviour therapy for severe and chronic fatigue in patients with type 1 diabetes. This patient-tailored intervention is aimed at reducing fatigue by changing cognitions and behaviours assumed to maintain fatigue. The efficacy of Dia-Fit will be investigated in this study.Methods/designA randomised controlled trial will be conducted in 120 patients with type 1 diabetes who are chronically and severely fatigued. Patients will be randomised to a treatment or waiting list group. The treatment group will receive Dia-Fit, a blended care therapy consisting of up to eight internet modules and face-to-face sessions with a therapist during a five-month period. The treatment will be tailored to the fatigue-maintaining cognitions and behaviours that are relevant for the patient and are determined at baseline. The waiting list group will receive Dia-Fit after a waiting period of five months. The primary outcome measure is fatigue severity. Secondary outcome measures are functional impairment and glucose control determined by haemoglobin A1c and blood glucose variability.DiscussionTo our knowledge, this is the first study investigating the efficacy of a cognitive behavioural intervention for chronic fatigue in patients with type 1 diabetes.Trial registrationDutch trial register NTR4312 (10 December 2013).

Is the Eating Disorder Questionnaire-Online (EDQ-O) a valid diagnostic instrument for the DSM-IV-TR classification of eating disorders?

BACKGROUND The Eating Disorder Questionnaire-Online (EDQ-O) is an online self-report questionnaire, which was developed specifically to provide a DSM-IV-TR classification of anorexia nervosa (AN), bulimia nervosa (BN), binge-eating disorder (BED), and eating disorder not otherwise specified (EDNOS), without using a face-to-face clinical interview. OBJECTIVE The purpose of the present study was to examine the psychometric quality of the EDQ-O. METHODS The validity of the EDQ-O was determined by examining the agreement with the diagnoses obtained from the Longitudinal, Expert, and All DATA (LEAD) standard. Participants included 134 new patients of a specialist center for eating disorders located in the Netherlands. RESULTS Assessment of the validity of the EDQ-O yielded acceptable to good AUC (area under the receiver operating characteristic curve) values with a range from 0.72 to 0.83. Most other diagnostic efficiency statistics were also good except for a low sensitivity for AN (0.44), a low positive predictive value for BN (0.50), and a relatively low sensitivity for BED (0.66). CONCLUSION The results of the present study suggest that the EDQ-O performs acceptably as a diagnostic instrument for all DSM-IV-TR eating disorder classifications. However, suggestions are made to further improve the validity of the EDQ-O.

Prevalence and correlates of pain in fatigued patients with type 1 diabetes

OBJECTIVE To investigate the prevalence, location and severity of pain, as well as its association with psychosocial and clinical variables and its impact on functional impairment in fatigued patients with type 1 diabetes. METHODS 120 severely fatigued patients with type 1 diabetes completed questionnaires on pain (McGill Pain Questionnaire, MPQ; Short Form Health Survey subscale bodily pain, SF-36), fatigue severity (Checklist Individual Strength subscale fatigue severity, CIS), depressive symptoms (Beck Depression Inventory Primary Care, BDI-PC) and functional impairment (Sickness Impact Profile-8, SIP-8). HbA1c and diabetes-related complications were assessed, and physical activity was measured using actigraphy. RESULTS 72% of patients reported pain. Muscle, joint and back pain, and headache were most common. Patients with pain were more often female (69 vs. 44%, p=0.013), reported more complications (mean number: 0.7 vs. 0.3, p=0.009) and scored higher on the BDI-PC measuring depressive symptoms (mean score: 3.8 vs. 2.3, p=0.002), compared to patients without pain. Pain was associated with diabetes duration, the number of complications, fatigue severity, depressive symptoms and functional impairment, but not with HbA1c or physical activity. Of patients with pain, 26% reported a high impact of pain. Both pain (β=-0.31, t(117)=-3.39, p=0.001) and fatigue severity (β=0.18, t(117)=2.04, p=0.044) contributed to functional impairment. CONCLUSION Pain was highly prevalent in fatigued patients with type 1 diabetes, although pain impact and severity were relatively low, and the location of some pain symptoms was similar to the location of those in the general population. As pain is related to fatigue and contributes independently to functional impairment, fatigue interventions should address pain.

Potential Mechanisms Involved in the Effect of Cognitive Behavioral Therapy on Fatigue Severity in Type 1 Diabetes

Objective: To identify mediators of the beneficial effect of cognitive–behavioral therapy (CBT) on fatigue severity in chronically fatigued patients with Type 1 diabetes. Method: We performed secondary analyses of a randomized controlled trial testing the efficacy of CBT. Primary outcome was fatigue severity assessed with the Checklist Individual Strength, subscale fatigue severity. We used multiple mediation analysis to determine potential mediators of the treatment effect. Proposed mediators were symptom focusing, self-efficacy concerning fatigue and pain, perceived activity, sleep disturbances, confidence in diabetes self-care, diabetes distress and discrepancy regarding social support. Actigraphy was used to assess the level of physical activity. The analysis was repeated with depressive symptoms as potential mediator to test whether this caused a change in the other fatigue-related mediators. Results: The effect of CBT on fatigue severity was partly mediated by a change in symptom focusing (−1.39, 95% CI [−3.32, −0.19]), fear avoidance (−1.10, 95% CI [−2.49, −0.22]), self-efficacy concerning fatigue (−1.95, 95% CI [−4.51, −0.40]), and perceived physical activity (−2.44, 95% CI [−4.53, −1.07]). Depressive symptoms were also a mediator (−1.22, 95% CI [−2.56, −0.38]), but the aforementioned fatigue-perpetuating factors still explained part of the treatment effect. Conclusions: Changes in cognitions about fatigue and activity, and a change in depressive symptoms partly mediated the treatment effect of CBT on fatigue severity in Type 1 diabetes. The mediators found are similar to those explaining the effects of CBT in other chronic diseases. This provides knowledge for the development of more effective and efficient interventions for fatigue.

Is Fatigue a Disease-Specific or Generic Symptom in Chronic Medical Conditions?

Objective: Severe fatigue is highly prevalent in various chronic diseases. Disease-specific fatigue models have been developed, but it is possible that fatigue-related factors in these models are similar across diseases. The purpose of the current study was to determine the amount of variance in fatigue severity explained by: (a) the specific disease, (b) factors associated with fatigue across different chronic diseases (transdiagnostic factors), and (c) the interactions between these factors and specific diseases. Method: Data from 15 studies that included 1696 patients with common chronic diseases and disorders that cause long-term disabilities were analyzed. Linear regression analysis with the generalized least-squares technique was used to determine fatigue-related factors associated with fatigue severity, that is, demographic variables, health-related symptoms and psychosocial variables. Results: Type of chronic disease explained 11% of the variance noted in fatigue severity. The explained variance increased to 55% when the transdiagnostic factors were added to the model. These factors were female sex, age, motivational and concentration problems, pain, sleep disturbances, physical functioning, reduced activity and lower self-efficacy concerning fatigue. The predicted variance increased to 61% when interaction terms were added. Analysis of the interactions revealed that the relationship between fatigue severity and relevant predictors mainly differed in strength, not in direction. Conclusions: Fatigue severity can largely be explained by transdiagnostic factors; the associations vary between chronic diseases in strength and significance. This suggests that severely fatigued patients with different chronic diseases can probably benefit from a transdiagnostic fatigue-approach which focuses on individual patient needs rather than a specific disease.

PS12 - 8. Chronic fatigue is highly prevalent in type 1 diabetes, but not related to glucose variability or hyperglycemia

Fatigue is a presenting symptom of diabetes, but little is known of the course of fatigue. Clinical experience suggests that patients can suffer from chronic fatigue. In this study we investigated the prevalence of chronic fatigue, defined as severe and persistent fatigue lasting for at least six months in a large cohort of patients.