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Ieso - Depression subtypes linked to varying recovery rates, study shows

Ieso - Depression subtypes linked to varying recovery rates, study shows

  • Data from more than 8,000 NHS patients identifies five distinct subtypes of depression
  • Analyses show that distinct subtypes respond differently to treatment
  • Findings published in Depression & Anxiety highlight need to more precisely diagnose mental health conditions so that the most suitable treatments can be accessed

Five subtypes of depression have been identified in new research from the University of Sheffield and Ieso Digital Health1. Patients with each subtype show distinct responses to treatment, a finding that could lead to a more tailored and effective approach to treating depression.

Globally, 264 million people suffer from depression and only half are expected to recover, even after treatment. Depression is characterised by a variety of cognitive (low mood, repetitive negative thoughts, suicidal ideas), affective (loss of pleasure and motivation), and somatic (difficulties with sleep and changes in appetite) symptoms. However, not all patients will experience all of these symptoms.

The wide range of symptoms experienced under the single diagnosis of ‘depression’ are thought to be masking the fact that some treatments are more effective for certain patients. Selecting treatments based on a more precise assessment of a patient’s symptom profile could improve clinical outcomes.

By analysing the type and severity of symptoms experienced by more than 8,000 patients receiving in-person cognitive behavioural therapy (CBT) through the NHS, researchers were able to group patients into five broad depression subtypes: mild, severe, cognitive-affective, somatic and typical.

Further analyses showed that distinct subtypes respond differently to treatment - cognitive-affective patients were more likely to engage, attend more sessions, and attain reliable improvement, compared to the typical and somatic types. Meanwhile, patients with a typical subtype were more likely to drop out of treatment than those with cognitive-affective and somatic subtypes.

Dr Melanie Simmonds-Buckley, University of Sheffield, lead author on the Depression & Anxiety paper, commented:

“Given how different depression can be from one person to the next, a treatment that works for one person may not work as well for another. Our findings have helped to identify how symptom profiles can be grouped into replicable subtypes of depression, showing that not all patients respond to CBT treatment in the same way. We now want to understand which other available treatments work best for patients with each depression subtype to help them to access the most appropriate treatment.”

The results from this study replicated findings from a 2020 published paper which analysed data from nearly 10,000 NHS patients who received internet enabled CBT2.

Dr Ana Catarino, Director of Clinical Science at Ieso, and an author on both papers, added:

“It has been hugely valuable to replicate our original findings from internet-enabled CBT with patients who have received CBT face-to-face. Our hope is that the subtyping algorithm we have developed can be applied more broadly and, ultimately, lead to improved outcomes for patients through a more precise approach to diagnosis and treatment selection. The next step towards this goal will be a clinical trial to uncover the specific treatment types that work best for each subtype.”

The subtyping algorithm developed from these two studies, and now validated with data from more than 18,000 patients, could be applied to the information provided by patients newly diagnosed with depression to identify their subtype. Those with depression subtypes that have higher chances of dropout and lower chances of symptomatic improvement could be identified in their first therapy session and prioritised for clinical supervision. In particular, those with somatic depression, who are also more likely to have other long-term health conditions, may benefit from integrated care from medical and psychological specialists.

1. Simmonds‐Buckley, M., Catarino, A., & Delgadillo, J. (2021). Depression subtypes and their response to cognitive behavioural therapy: A latent transition analysis. Depression and Anxiety, 1– 10.

2. Catarino, A., Fawcett, J., Ewbank, M., Bateup, S., Cummins, R., Tablan, V., & Blackwell, A. (2020). Refining our understanding of depressive states and state transitions in response to cognitive behavioural therapy using latent Markov modelling. Psychological Medicine, 1-10.

About Ieso Digital Health

Ieso delivers world-class online mental healthcare, with reach to over 20 million patients and a clinical network of 650+ fully qualified therapists and psychological wellbeing practitioners (NHS and private) across the UK.

Ieso aims to revolutionise the existing standard of mental healthcare through innovation and new idea generation, maintaining its patient-centric approach to advance treatment for the 1 in 4 adults who will experience at least one diagnosable mental problem in any one year.

Combining collective knowledge and smart technology, Ieso’s data-led clinical insights are enabling the company to develop AI tools to drive better quality and consistency of care. Backed by an experienced and highly motivated leadership team, Ieso delivers flexible and confidential 1:1 psychotherapy delivered in real-time, anytime, anywhere, through its device-agnostic online platform.

Ieso has a track record in improving patient care beyond national targets and has already treated more than 70,000 patients through over 400,000 hours of therapy under the NHS IAPT programme (Improving Access to Psychological Therapies). It is currently available across 49 NHS clinical commissioning groups and 27 NHS providers.

For more information, visit and connect with us on Twitter @IesoHealthLtd and LinkedIn.

About University of Sheffield

With almost 29,000 of the brightest students from over 140 countries, learning alongside over 1,200 of the best academics from across the globe, the University of Sheffield is one of the world's leading universities.
A member of the UK's prestigious Russell Group of leading research-led institutions, Sheffield offers world-class teaching and research excellence across a wide range of disciplines.

Unified by the power of discovery and understanding, staff and students at the university are committed to finding new ways to transform the world we live in.

Sheffield is the only university to feature in The Sunday Times 100 Best Not-For-Profit Organisations to Work For 2018 and for the last eight years has been ranked in the top five UK universities for Student Satisfaction by Times Higher Education.

Sheffield has six Nobel Prize winners among former staff and students and its alumni go on to hold positions of great responsibility and influence all over the world, making significant contributions in their chosen fields.

Global research partners and clients include Boeing, Rolls-Royce, Unilever, AstraZeneca, Glaxo SmithKline, Siemens and Airbus, as well as many UK and overseas government agencies and charitable foundations.

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Tim WatsonPartner