CAMBRIDGE, England–(BUSINESS WIRE)–Jun 6, 2022–
ieso, a data-driven AI healthcare company pioneering next-generation digital therapeutics in mental health, announced today study results showing that integrated approaches for mental healthcare in diabetes patients improved mental health outcomes, patient engagement with self-management of diabetes, diabetes distress, and quality of life.
It is estimated that 25% of patients with diabetes have comorbid depression, and 40% have comorbid anxiety. Comorbid mental health problems in patients with diabetes are associated with poorer quality of life, poorer diabetes management and even decreased lifespan. It is estimated that comorbid physical and mental health conditions increase physical healthcare costs by 45% to 75%, and that tailored interventions are associated with substantial savings in healthcare costs 1.
This study, conducted with support from Roche Diabetes Care Limited, enrolled 102 patients and evaluated the effect of a novel online CBT tailored for patients with type 2 diabetes. The intervention was delivered by accredited therapists over the internet, using text, and following a diabetes-specific treatment protocol. The study consisted of up to 10 CBT sessions per person lasting up to 60 minutes each. Each course of online CBT was delivered over a period of approximately 12 weeks.
The online CBT therapy was delivered by therapists that were specially trained to understand the physical symptoms of diabetes and how to manage them. Therapists were also trained to use an innovative form of cognitive behavioral therapy, Acceptance and Commitment Therapy, that allowed for a more personalized approach.
The study results showed that a course of tailored online CBT helped patients adjust emotionally to their diagnosis and also supported the overall management of their diabetes. Patients who received the tailored therapy had reduced levels of distress about having diabetes, increased engagement in managing their condition, and improved quality of life, compared to synthetic control arms derived from real-world health service data to benchmark clinical outcomes. The results also showed that patients had much higher recovery rates in terms of their mood and anxiety symptoms, relative to patients who received standard CBT, that was not tailored to address diabetes related issues.
- The Diabetes Distress Scale (DDS) is a 17-item self-report instrument where each item is rated on a 6-point scale from (1) “not a problem” to (6) “a very significant problem”. Patients in the study started at an average of 3.40, which is above the threshold of 3 for clinically significant diabetes distress 2, and decreased on average by 0.94 points with diabetes-tailored online CBT to 2.46 by the end of treatment.
- On the Audit of Diabetes Dependent Quality of Life (ADDQOL) score, which assesses an individual’s perceptions of the impact of diabetes on their quality of life, patients who received ieso diabetes-tailored online CBT therapy decreased by 0.45 points, which represents a significant improvement in quality of life.
- Patient Activation Measure (PAM) measures a patient’s ability to manage their illness, classifying them into one of four levels, from 1 (disengaged and overwhelmed) to 4 (maintaining behaviours and pushing further). Patients who received diabetes-tailored online CBT showed a significant improvement in self-management of diabetes, with the proportion of patients at the lowest level of activation (Level 1) decreasing from 44.1% to 23.5%, pre- to post-treatment. The proportion of patients at the highest level of activation (Level 4) increased from 1.0% to 17.7% pre- to post-treatment.
- In terms of their mental health symptoms, patients who received diabetes-tailored online CBT showed recovery rates of 76%, compared with 56% for patients with diabetes who received standard online CBT.
“Feelings of being low in mood or worry can have a significant impact on a patient’s ability to manage their diabetes. We’ve now shown that addressing these feelings with tailored online therapy can improve a patient’s physical and emotional wellbeing,” said Andy Blackwell, Chief Science and Strategy Officer, ieso. “We’re excited to announce these results, which show that diabetes-specific online cognitive behavioral therapy can improve patient outcomes in Type 2 diabetes management and care.”
“The study provides evidence that integrated approaches for mental healthcare in patients with diabetes can improve physical wellbeing and patient outcomes, paving the way for further research into other long-term conditions,” added Andy Richards, Chair, ieso. “These results have much wider implications for the role of digital CBT therapy, mental health and its impact on clinical outcomes across a variety of different healthcare conditions. New online tools are needed to improve patient access to quality mental health care, which can significantly impact clinical outcomes and associated costs in chronic diseases such as diabetes.”
ieso’s AI-enabled digital assessment tools and therapeutics for mental health conditions will build on the insights developed from the world’s largest outcomes-linked therapy dataset, which surpasses 530,000 hours. The data encompass insights in the treatment of common mental health conditions including depression and anxiety and those linked with long term conditions such as diabetes.
ieso is a data-driven AI healthcare company pioneering next-generation digital therapeutics to improve mental health outcomes and access to care. The company is developing a pipeline of AI-driven evidence-based mental health assessment tools and solutions to democratize access to mental health therapy at scale. With a network of more than 600 fully qualified therapists, ieso currently provides virtual care (telehealth) serving more than 20 million adults through the UK National Health Service (NHS). ieso’s research has been published in several peer-reviewed journals including the Lancet and JAMA, shaping our understanding of scalable digital mental healthcare solutions. For more information, visit www.iesogroup.com. Connect with us on Twitter @iesogroup and LinkedIn.
2 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). https://doi.org/10.2337/dc11-1572
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PUB: 06/06/2022 08:00 AM/DISC: 06/06/2022 08:03 AM