2021 Duncan Macmillan Essay Prize competition: Winners announced

The Institute runs an annual 1,000 word essay prize competition named after psychiatrist Duncan Macmillan who helped pioneer a community-centred approach to mental health.

The competition is held in partnership with The Royal College of Psychiatrists and promotes the expertise and knowledge of psychiatry trainees nationwide.

The 2021 competition was held at the end of last year and we’re delighted to announce this year’s winner is Leigh Townsend, an NIHR Academic Clinical Fellow at Newcastle University and a CT1 Psychiatry at Cumbria, Northumberland, Tyne and Wear NHS Foundation Trust. Leigh’s winning entry answered the competition essay question “What’s the next big thing in psychiatry” by exploring “Network Biomarkers and Deep Brain Stimulation – a shock to the system”.

Second prize in the competition was awarded to Natalie Kirby, ST4 Child and Adolescent Psychiatry at Tees, Esk & Wear Valleys NHS Foundation Trust for her essay exploring “A better understanding of trauma-informed care”.

Read both of the winning entries below.

FIRST PRIZE: Network Biomarkers and Deep Brain Stimulation – a shock to the system

Dr Leigh Townsend (NIHR Academic Clinical Fellow Newcastle University CT1 Psychiatry Cumbria, Northumberland, Tyne and Wear NHS Foundation Trust)

Introduction

For psychiatrists, assessing response to psychotropic medications relies upon clinical judgements which may not accurately reflect their neurophysiological effects. Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) allow measurement of signalling between brain regions (brain network biomarkers), offering potential for better prediction of treatment response and more personalised understanding of how medications affect brain function. However, psychotropic medications may have inherent limitations when targeting these networks. Deep brain stimulation (DBS) offers advantages in terms of spatial and temporal specificity, allowing more nuanced modulation of network function. Alone, advances in understanding brain networks constitute a major development; however, the combination of measurement of network biomarkers with DBS will be the ‘next big thing in psychiatry research’.

Network biomarkers

Brain networks are collections of brain regions which show functional connectivity (FC) (temporal association of activity in distinct regions, derived from statistical analysis of neuronal activation measures). 1,2 Psychiatric disorders are increasingly understood to arise from the dynamic interactions of distributed brain areas operating in large-scale brain networks. 2–4 Brain network abnormalities have been reported across the neuropsychiatric spectrum, in schizophrenia, 5–7 major depressive disorder (MDD)8,9 and dementia. 13,14 In schizophrenia, salience network (SN) abnormalities appear to be of particular pathophysiological importance. 6,15 In MDD, studies point to the amygdala, 8,16 anterior cingulate and dorsolateral prefrontal cortices8,16 as important hubs in an extended brain circuit.

Supekar et al.6 demonstrate that SN-centred network patterns can distinguish schizophrenia patients from controls, with an accuracy of 78-80%, similar to the diagnostic accuracy of first-rank symptoms. 17 Hadley et al.18 observe that patterns of aberrant functional network organisation are modulated by antipsychotics in treatment-responsive patients, but not in treatment nonresponders. Using network-based EEG analysis, Hill et al.19 identify widespread changes in spontaneous neural activity following electroconvulsive therapy for treatment resistant MDD (TRMDD); while Mehraram et al. use weighted EEG network measures to discriminate between dementia sub-types.20

FC analysis has the potential to facilitate better clinical decision-making, improving patient identification and monitoring of treatment response and disease progression; however, there are caveats which have slowed its clinical implementation. fMRI requires large, expensive equipment, while the markers and statistical analyses employed in EEG and fMRI are diverse, complex and experimental. Consequently, there is significant heterogeneity in methods and results. Despite these issues, FC analysis is already employed clinically in functional neurosurgery21 and this experience has led to exciting work demonstrating the use of brain network biomarkers in combination with DBS to treat neuropsychiatric conditions.

Deep brain stimulation

Current drug treatments may significantly alter the functioning of brain networks18,22–24 but the temporal and anatomical specificity of medication effects is limited by route of administration. As medication is typically administered indirectly to the brain by mouth, muscle or blood, the entire brain, indeed the whole body, is exposed. DBS offers an alternative. 25

DBS involves reversible, stereotactically-guided implantation of electrodes to stimulate specific brain regions.25 DBS is increasingly used in the management of conditions such as Parkinson’s Disease (PD), when drug therapy has failed.26 Evidence for alterations in psychiatric symptom domains, e.g. mood changes between ON and OFF conditions in PD-DBS patients, has led to interest in the use of DBS in disorders such as MDD or schizophrenia. 27,28

A recent case report by Scangos et al. presents a striking example of this. 29 For a patient with TRMDD, the authors use intracranial EEG (iEEG) to develop a personalised map of her emotional network, containing regions including the amygdala and ventral capsule/ventral striatum (VC/VS). 30 They correlated brain network states with affective state (based on clinical questionnaires) over a 10-day period and identified consistent phenomenological responses to stimulation of network hubs e.g. “‘tingles of pleasure’ with 100-Hz VC/VS stimulation.”29 They identified that gamma power (an EEG signal measure) within the amygdalae bilaterally allowed detection of a high symptom severity state whilst right VC/VS stimulation led to consistent, sustained and dose-dependent symptom improvement. After further testing, they implanted dual-purpose, sensing/stimulating electrodes in the right amydala and VC/VS which could be configured remotely to detect prespecified patterns of activity and automatically deliver short bursts of stimulation. Once configured, the authors reportedly observed rapid and sustained improvement in depressive symptoms associated with the ON condition.

This case report should be considered with caution. The results may not be generalisable both due to the single-patient sample and the personalised nature of the network characterisation and target localisation. Further, though the patient was blinded to ON/OFF condition, clinician knowledge of stimulation condition or cues from stimulation sensations may have resulted in placebo effects. This work should also be considered as an elegant illustration of the potential utility of network biomarkers. The authors use multimodal techniques including iEEG, fMRI, diffusion tensor imaging and DBS to develop a clinically informative neurophysiological map of depression-specific symptoms and then implement an anatomically localised treatment, sensitive and responsive to transient changes in depression-associated brain network function. This approach appears to achieve a significant treatment response in a patient that was heretofore treatment resistant.

Conclusions

Scangos et al. note that their network mapping strategy is routinely utilised in epilepsy to map seizure foci but has not been performed previously in psychiatric conditions. There are conceivable barriers to use of such techniques in psychiatric practice: invasive iEEG and stimulation techniques, poor access to expensive MRI machines, stigma around the use of neurosurgical techniques in psychiatry. These are important, not insurmountable issues. Surface EEG and non-invasive stimulation techniques (such as transcranial magnetic stimulation) 31 may reduce the need for more invasive tools until absolutely required. MRI scanners are undoubtedly expensive, but this cost must be balanced against costs engendered by untreated or untreatable psychiatric disorders. Stigma against ‘psychosurgery’ may be historically justified, 33 thus the onus is on clinicians and researchers to ensure modern techniques can be implemented effectively and responsibly.

The principle of neurophysiological characterisation of psychiatric symptoms is scientifically sound and could be clinically transformative. While DBS may not be a panacea, psychiatrists should embrace its potential, compare the risks and benefits to those of current treatments and strive to support developments in this field to achieve better outcomes for patients.

References

  1. Friston, K. Functional and effective connectivity: a review. Brain Connect. 1, 13–36 (2011).
  2. Bressler, S. & Menon, V. Large-scale brain networks in cognition: emerging methods and principles. Trends Cogn. Sci. 14, 277–290 (2010).
  3. Goodkind, M. et al. Identification of a common neurobiological substrate for mental illness. JAMA Psychiatry 72, 305–15 (2015).
  4. McTeague, L. et al. Identification of Common Neural Circuit Disruptions in Cognitive Control Across Psychiatric Disorders. Am. J. Psychiatry 174, 676–685 (2017).
  5. Palaniyappan, L., Simmonite, M., White, T., Liddle, E. & Liddle, P. Neural primacy of the salience processing system in schizophrenia. Neuron 79, 814–828 (2013).
  6. Supekar, K., Cai, W., Krishnadas, R., Palaniyappan, L. & Menon, V. Dysregulated brain dynamics in a triple-network saliency model of schizophrenia and its relation to psychosis. Biol. Psychiatry 85, 60–69 (2019).
  7. Li, P. et al. Altered Brain Network Connectivity as a Potential Endophenotype of Schizophrenia. Sci. Rep. 7, (2017).
  8. Price, J. & Drevets, W. Neurocircuitry of mood disorders. Neuropsychopharmacology 35, 192– 216 (2009).
  9. Taylor, J., Kurt, H. & Anand, A. Resting State Functional Connectivity Biomarkers of Treatment Response in Mood Disorders: A Review. Front. Psychiatry 12, (2021).
  10. Moreira da Silva, N., Cowie, C., Blamire, A., Forsyth, R. & Taylor, P. Investigating Brain Network Changes and Their Association With Cognitive Recovery After Traumatic Brain Injury: A Longitudinal Analysis. Front. Neurol. 11, (2020).
  11. Kasahara, M. et al. Traumatic brain injury alters the functional brain network mediating working memory. Brain Inj. 25, 1170–87 (2011).
  12. Caeyenberghs, K. et al. Graph analysis of functional brain networks for cognitive control of action in traumatic brain injury. Brain 135, 1293–1307 (2012).
  13. Hsu, T.-W. et al. Disrupted metabolic connectivity in dopaminergic and cholinergic networks at different stages of dementia from 18F‐FDG PET brain persistent homology network. Sci. Rep. 11, (2021).
  14. Zhang, Y., Jiang, X., Qiao, L. & Liu, M. Modularity-Guided Functional Brain Network Analysis for Early-Stage Dementia Identification. Front. Neurosci. 15, (2021).
  15. McCutcheon, R., Pillinger, T., Rogdaki, M., Bustillo, J. & Howes, O. Glutamate connectivity associations converge upon the salience network in schizophrenia and healthy controls. Transl. Psychiatry 11, 322 (2021).
  16. Kirkby, L. et al. An Amygdala-Hippocampus Subnetwork that Encodes Variation in Human Mood. Cell 175, 1688–1700 (2018).
  17. Townsend, L. & De Giorgi, R. The tail wagging the dog: The diagnostic accuracy of first rank symptoms: COMMENTARY ON… COCHRANE CORNER. BJPsych Adv. 25, 337–341 (2019).
  18. Hadley, J. et al. Change in brain network topology as a function of treatment response in schizophrenia: a longitudinal resting-state fMRI study using graph theory. NPJ Schizophr. 27, 16014 (2016).
  19. Hill, A. et al. Modulation of functional network properties in major depressive disorder following electroconvulsive therapy (ECT): a resting-state EEG analysis. Sci. Rep. 10, (2020).
  20. Mehraram, R. et al. Weighted network measures reveal differences between dementia types: An EEG study. Hum. Brain Mapp. 41, 1573–1590 (2020).
  21. Sisterson, N., Wozny, T., Kokkinos, V., Constantino, A. & Richardson, R. Closed-Loop Brain Stimulation for Drug-Resistant Epilepsy: Towards an Evidence-Based Approach to Personalized Medicine. Neurotherapeutics 16, 119–127 (2019).
  22. Madsen, M. et al. Psilocybin-induced changes in brain network integrity and segregation correlate with plasma psilocin level and psychedelic experience. Eur. Neuropsychopharmacol. 50, 121–132 (2021).
  23. Abdallah, C. et al. Ketamine Treatment and Global Brain Connectivity in Major Depression. Neuropsychopharmacology 42, 1210–1219 (2017).
  24. Maximo, J., Kraguljac, N., Rountree, B. & Lahti, A. Structural and Functional Default Mode Network Connectivity and Antipsychotic Treatment Response in Medication-Naïve First Episode Psychosis Patients. Schizophr. Bull. Open 2, (2021).
  25. Krauss, J. et al. Technology of deep brain stimulation: current status and future directions. Nat. Rev. Neurol. 17, 75–87 (2020).
  26. Hartmann, C., Fliegen, S., Groiss, S., Wojtecki, L. & Schnitzler, A. An update on best practice of deep brain stimulation in Parkinson’s disease. Ther. Adv. Neurol. Disord. 12, (2019).
  27. Bouthour, W. et al. Biomarkers for closed-loop deep brain stimulation in Parkinson disease and beyond. Nat. Rev. Neurol. 15, 343–352 (2019).
  28. Gault, J. et al. Approaches to neuromodulation for schizophrenia. J. Neurol. Neurosurg. Psychiatry 89, 777–787 (2018).
  29. Scangos, K. et al. Closed-loop neuromodulation in an individual with treatment-resistant depression. Nat. Med. 27, 1696–1700 (2021).
  30. Scangos, K., Makhoul, G., Sugrue, L., Chang, E. & Krystal, A. State-dependent responses to intracranial brain stimulation in a patient with depression. Nat. Med. 27, 229–231 (2021).
  31. Tracy, D. & David, A. Clinical neuromodulation in psychiatry: the state of the art or an art in a state? BJPsych Adv. 21, 396–404 (2015).
  32. Hilton, C. Parity of esteem for mental and physical healthcare in England: a hundred years war? J. R. Soc. Med. 109, 133–136 (2016).
  33. Faria, M. Violence, mental illness, and the brain – A brief history of psychosurgery: Part 1 – From trephination to lobotomy. Surg. Neurol. Int. 4, (2013). 

SECOND PRIZE:  A better understanding of trauma-informed care

Natalie Kirby, ST4 Child and Adolescent Psychiatry at Tees, Esk & Wear Valleys NHS Foundation Trust

As the field of psychiatry continues to develop its knowledge and understanding of childhood trauma, viewed by some as psychiatry’s ‘greatest public health challenge’1, it is imperative that mental health services adapt and respond appropriately. With the economic cost of adverse experiences in childhood estimated to be approximately £42.8 billion per year in England and Wales2, there is a strong argument for trauma to be at the top of the agenda in terms of clinical and academic priorities.

Trauma can be described as a ‘set of circumstances…experienced by an individual as physically or emotionally harmful or life threatening and that has lasting adverse effects on the individual’s functioning and mental, physical, social, emotional, or spiritual well-being’3. The landmark Adverse Childhood Experiences (ACEs) study led by Vincent Felitti in the USA demonstrated that childhood adverse experiences are widespread in the general population4 . In England, almost half of the adult population have experienced at least one ACE, and 9% have experienced four or more ACEs5. The ACEs research demonstrated that a higher number of adversities in childhood predicted long-term negative impacts in many areas of health including physical health, mental illness, sexual and reproductive health, and substance misuse4. Such findings have been echoed in a number of further studies6,7 and a recent meta-analysis identified that having four or more ACEs was strongly correlated with anxiety, depression and suicide attempts8. The ACE-attributable cost of mental illness in England and Wales is estimated to be approximately £11.2 billion per year9.

Given the widespread prevalence of trauma, and the subsequent effects on health and wellbeing, it is understandable that a large proportion of those who require support from mental health services have experienced trauma at some point in their lives10. It is imperative, therefore, that services are organised in a way that supports the understanding of, and response to, trauma and its impact on mental health. However, this does not appear to be widely practised within current mental health systems, with research emerging regarding the possible iatrogenic harms related to institutional re-traumatisation within mental health systems10,11. For example, studies have indicated that acute psychiatric inpatient admissions may actually be experienced as counter-therapeutic and re-traumatising for many individuals6. Re-traumatisation, although unintentional, is likely to occur where mental health systems fail to understand or recognise behaviours in the context of trauma; the use of authoritarian and ‘power over’ dynamics is likely to lead to experiences of fear, unsafety and associated behaviours such as aggression11. A trauma informed approach is, therefore, vital in terms of supporting the wellbeing of service users and staff, and facilitating recovery6, 10. 

So, what is a Trauma Informed Approach (TIA)? As described by Clement (2015), TIAs are ‘based on the understanding that most people in contact with human services have experienced trauma, and this understanding needs to permeate service relationships and delivery’11. TIAs are strengths based, whereby behaviours are reframed in terms of their function in maintaining a sense of safety for the individual; this entails a shift from thinking “what is wrong with you” to “what happened to you”12. In comparison to trauma-specific interventions designed to treat symptoms of trauma, TIAs require organisational changes at the whole systems level12 based on the key principles of prioritising safety, collaboration, transparency and preventing re-traumatisation10,11.

It makes sense that systems which prioritise the principles of safety, sensitivity and empowerment are likely to be helpful for trauma survivors. As Blecker (2016) notes, ‘for trauma victims/survivors who for so long have had their experiences denied in so many different settings, trauma-informed systems carry incredible potential for good’13. However, there has been little progress from a research perspective in terms of providing an evidence base for TIAs14. A 2016 narrative review found some evidence for the effectiveness of TIAs in terms of reducing post-traumatic and general mental health symptoms, increasing coping skills, shorter inpatient stays, and improved physical health11; however, this was limited by a small number of studies, all of which were conducted in the US. To date, studies have tended to focus on specific trauma-informed interventions15 rather than whole systems approaches.

There are clear barriers to building an evidence base; this is a multifaceted area of research complicated by ambiguities in terminology and a lack of clear consensus regarding the key components of TIAs16. The use of different interventions between studies means it is difficult to pinpoint which specific components are helpful i.e. what are the ‘key active ingredients’ that lead to change11. Further research, including systematic reviews and randomised controlled trials, could certainly help to unpick some of these complexities and to give a fuller picture of the potential impact of TIAs17. Studies testing the efficacy of TIAs in mental health settings, alongside an exploration of service user experiences of TIAs, would be valuable. A key component of this research should be the involvement of trauma survivors from the outset, enabling future service development to be influenced by those for whom it is most pertinent10.  

Given the growing evidence base for the widespread prevalence and burden of trauma, there certainly appears to be a strong case for the implementation of TIAs within healthcare systems. If TIAs were indeed to become the ‘next big thing in psychiatry research’, this could provide the evidence needed to profoundly change how mental health services are organised and delivered in order to optimise service users’ experiences within the healthcare system.  

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References

  1. Grant S, Lappin J. Childhood trauma: psychiatry's greatest public health challenge? The Lancet 2017;2(7):e300-301.
  2. Hughes K, Ford K, Kadel R, et al. Health and financial burden of adverse childhood experiences in England and Wales: a combined primary data study of five surveys. BMJ Open 2020;10:e036374.
  3. National Centre for Trauma-Informed Care (NCTIC) SAMHSA’s Working Concept of Trauma and Framework for a Trauma-Informed Approach. 2014. Substance Abuse and Mental Health Services Administration (SAMHSA), Rockville, MD.
  4. Felitti VJ, Anda RF, Nordenberg D, et al. Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults. The Adverse Childhood Experiences (ACE) study. Am J Prev Med 1998;14:245–58.
  5. Bellis et al. National household survey of adverse childhood experiences and their relationship with resilience to health-harming behaviors in England. BMC Medicine 2014;12:72.
  6. Muskett, C. (2014), Trauma-informed care. Int J Ment Health Nurs, 23: 51-59
  7. Lewis et al. The epidemiology of trauma and post-traumatic stress disorder in a representative cohort of young people in England and Wales. Lancet Psychiatry 2019;6(3):247-256.
  8. Hughes et al. The effect of multiple adverse childhood experiences on health: a systematic review and meta-analysis. Lancet Public Health 2017;2:e356–66.
  9. Hughes K, Ford K, Kadel R, et al. Health and financial burden of adverse childhood experiences in England and Wales: a combined primary data study of five surveys. BMJ Open 2020;10:e036374.  
  10. Sweeney A, Taggart D. (Mis)understanding trauma-informed approaches in mental health. J Ment Health, 2018;27(5); 383-387.
  11. Sweeney A, Clement S, Filson B, Kennedy A. Trauma-informed mental healthcare in the UK: what is it and how can we further its development? Ment Health Rev J 2016;21(3):174-192
  12. Harris M, Fallot R. Using Trauma Theory to Design Service Systems. New Directions for Mental Health Services. 2001. Jossey-Bass, San Francisco, CA
  13. Becker-Blease K. As the world becomes trauma–informed, work to do. J Trauma & Dissociation. 2017;18(2):131-138
  14. Reeves E. A Synthesis of the Literature on Trauma-Informed Care. Issues Ment Health Nurs. 2015;36(9):698-709.
  15. Han H et al. Trauma informed interventions: A systematic review. PLoS ONE 2021;16(6): e0252747.
  16. Maynard B, Farina A, Dell N, Kelly M. Effects of trauma-informed approaches in schools: A systematic review. Campbell Systematic Reviews 2019;15:e1018
  17. Asmussen K, Fischer F, Drayton E, McBride T. Adverse childhood experiences: What we know, what we don’t know, and what should happen next. 2020. Early Intervention Foundation, London, UK.