Using Interactive 3D Visualisations in Neuropsychiatric Education.

Obsessive compulsive disorder (OCD) is a neuropsychiatric disorder with a global prevalence of 2-3%. OCD can have an enormous impact on the lives of those with the disorder, with some studies suggesting suicidal ideation is present in over 50% of individuals with OCD, and other data showing a significant number of individuals attempt suicide. It is therefore important that individuals with OCD receive the best possible treatment. A greater understanding of the underlying pathophysiology of neuropsychiatric disorders among professionals and future clinicians can lead to improved treatment. However, data suggests that many students and clinicians experience "neurophobia", a lack of knowledge or confidence in cases involving the nervous system. In addition, research suggests that the relationship many students have with neurological conditions deteriorates over time, and can persist into practice.If individuals living with conditions such as OCD are to receive the best possible treatment, it is crucial that those administering care are equipped with a thorough understanding of such disorders. While research has shown that the use of interactive 3D models can improve anatomy education and more specifically neurology education, the efficacy of using of such models to engage with neuropsychiatric conditions, specifically OCD, has not been assessed. This study seeks to address this gap.In this study an interactive application for Android devices was designed using standardised software engineering methods in order to improve neuropsychiatry literacy by empowering self-pace learning through interactive 3D visualisations and animations of the neural circuitry involved in OCD. A pilot test and a usability assessment were conducted among five postgraduate life science students. Findings relating to user experience were promising, and pre-test vs. post-test evaluation suggested encouraging outcomes regarding the effectiveness of the application in improving the knowledge and understanding of OCD. In short, this study suggests that interactive 3D visualisations can improve neuropsychiatry education. For this reason, more efforts should be made to construct similar applications in order to ensure patients always receive the best possible care. Fig. 2.1 A diagrammatic representation of the CSTC circuit, based on a similar diagram by Robertson et al. (2017).

Physical health indicators in major mental illness: data from the Quality and Outcome Framework in the UK.

BACKGROUND: In the UK, the Quality and Outcome Framework (QOF) has specific targets for general practictioners to record body-mass index (BMI) and blood pressure (BP) in major mental illness, diabetes, and chronic kidney disease. Although incentives are given for aspects of major mental illness (schizophrenia, bipolar disorder, and related psychoses), barriers to care can occur. Our aim was to compare recording of specific targets for BP and BMI in individuals with major mental illness relative to diabetes and chronic kidney disease across the UK. METHODS: Using 2012 and 2013 QOF data from 9731 general practices across all four countries in the UK, we calculated median payment, population achievement, and exception rates for BP indicators in major mental illness and chronic kidney disease and BMI indicators in major mental illness and diabetes. Differences in unweighted rates between practices in the same UK country were tested with a sign test. Differences in population achievement rate between practices in different countries were compared with those in England by use of a quantile regression analysis. FINDINGS: UK payment and population achievement rates for BMI recording in major mental illness were significantly lower than were those in diabetes (payment 92·7% vs 95·5% and population achievement 84·0% vs 92·5%, p<0·0001) and exception rates were higher (8·1% vs 2·0%, p<0·0001). For BP recording, UK payment and population achievement rates were significantly lower for major mental illness than for chronic kidney disease (94·1% vs 97·8% and 87·0% vs 97·1%, p<0·0001), whereas exception rate was higher (6·5% vs 0·0%, p<0·0001). This difference was observed for all UK countries. Median population achievement rates for BMI and BP recording in major mental illness were significantly lower in Scotland than in England (for BMI -1·5%, 99% CI -2·7 to -0·3, and for BP -1·8%, -2·7 to -0·9; p<0·0001 for both). There were no cross-jurisdiction differences for chronic kidney disease and diabetes. INTERPRETATION: We found lower payment rates, higher exception rates, and lower population achievement rates for BMI and BP recording in major mental illness than in diabetes and chronic kidney disease throughout the UK. We also found variation in these rates between countries. This finding is probably multifactorial, reflecting a combination of patient, clinician, and wider organisational factors; however, it might also suggest inequality in access to certain aspects of health care for people with major mental illness. FUNDING: None.

Impact of socioeconomic deprivation on rate and cause of death in severe mental illness.

BACKGROUND: Socioeconomic status has important associations with disease-specific mortality in the general population. Although individuals with Severe Mental Illnesses (SMI) experience significant premature mortality, the relationship between socioeconomic status and mortality in this group remains under investigated. We aimed to assess the impact of socioeconomic status on rate and cause of death in individuals with SMI (schizophrenia and bipolar disorder) relative to the local (Glasgow) and wider (Scottish) populations. METHODS: Cause and age of death during 2006-2010 inclusive for individuals with schizophrenia or bipolar disorder registered on the Glasgow Psychosis Clinical Information System (PsyCIS) were obtained by linkage to the Scottish General Register Office (GRO). Rate and cause of death by socioeconomic status, measured by Scottish Index of Multiple Deprivation (SIMD), were compared to the Glasgow and Scottish populations. RESULTS: Death rates were higher in people with SMI across all socioeconomic quintiles compared to the Glasgow and Scottish populations, and persisted when suicide was excluded. Differences were largest in the most deprived quintile (794.6 per 10,000 population vs. 274.7 and 252.4 for Glasgow and Scotland respectively). Cause of death varied by socioeconomic status. For those living in the most deprived quintile, higher drug-related deaths occurred in those with SMI compared to local Glasgow and wider Scottish population rates (12.3% vs. 5.9%, p = <0.001 and 5.1% p = 0.002 respectively). A lower proportion of deaths due to cancer in those with SMI living in the most deprived quintile were also observed, relative to the local Glasgow and wider Scottish populations (12.3% vs. 25.1% p = 0.013 and 26.3% p = <0.001). The proportion of suicides was significantly higher in those with SMI living in the more affluent quintiles relative to Glasgow and Scotland (54.6% vs. 5.8%, p = <0.001 and 5.5%, p = <0.001). CONCLUSIONS: Excess mortality in those with SMI occurred across all socioeconomic quintiles compared to the Glasgow and Scottish populations but was most marked in the most deprived quintiles when suicide was excluded as a cause of death. Further work assessing the impact of socioeconomic status on specific causes of premature mortality in SMI is needed.

Identification of novel genome-wide associations for suicidality in UK Biobank, genetic correlation with psychiatric disorders and polygenic association with completed suicide.

BACKGROUND: Suicide is a major issue for global public health. Suicidality describes a broad spectrum of thoughts and behaviours, some of which are common in the general population. Although suicide results from a complex interaction of multiple social and psychological factors, predisposition to suicidality is at least partly genetic. METHODS: Ordinal genome-wide association study of suicidality in the UK Biobank cohort comparing: 'no suicidality' controls (N = 83,557); 'thoughts that life was not worth living' (N = 21,063); 'ever contemplated self-harm' (N = 13,038); 'act of deliberate self-harm in the past' (N = 2498); and 'previous suicide attempt' (N = 2666). OUTCOMES: We identified three novel genome-wide significant loci for suicidality (on chromosomes nine, 11 and 13) and moderate-to-strong genetic correlations between suicidality and a range of psychiatric disorders, most notably depression (rg 0·81). INTERPRETATION: These findings provide new information about genetic variants relating to increased risk of suicidal thoughts and behaviours. Future work should assess the extent to which polygenic risk scores for suicidality, in combination with non-genetic risk factors, may be useful for stratified approaches to suicide prevention at a population level. FUND: UKRI Innovation-HDR-UK Fellowship (MR/S003061/1). MRC Mental Health Data Pathfinder Award (MC_PC_17217). MRC Doctoral Training Programme Studentship at the University of Glasgow (MR/K501335/1). MRC Doctoral Training Programme Studentship at the Universities of Glasgow and Edinburgh. UKRI Innovation Fellowship (MR/R024774/1).

Admission to psychiatric hospital for mental illnesses 2 years prechildbirth and postchildbirth in Scotland: a health informatics approach to assessing mother and child outcomes.

OBJECTIVE: To identify factors associated with: admission to a specialist mother and baby unit (MBU) and the impact of perinatal mental illness on early childhood development using a data linkage approach in the 2 years prechildbirth and postchildbirth. METHODS: Scottish maternity records (SMR02) were linked to psychiatric hospital admissions (SMR04). 3290 pregnancy-related psychiatric admissions for 1730 women were assessed. To investigate factors associated with MBU admission, the group of mothers admitted to an MBU were compared with those admitted to general psychiatric wards. To assess the impact of perinatal mental illness on early child development, a pragmatic indicator for 'at potential risk of adversity', defined as a child who was recorded as requiring intensive treatment at any time under the health plan indicators (HPI) and/or who had no record of completing three doses of the 5-in-1 vaccine by 12 months was generated. Logistic regression models were used to describe the association between each variable and the risk of admission between those with a history of prior psychiatric admission and those without. RESULTS: Women admitted to an MBU were significantly more likely to be admitted with non-affective psychosis (OR=1.97, 95% CI 1.22 to 3.18), affective psychosis (OR=2.44, 95% CI 1.37 to 4.33) and non-psychotic depressive episodes (OR=1.93, 95% CI 1.42 to 2.63). They were less likely to come from deprived areas (OR=0.68 95% CI 0.49 to 0.93). Women with a previous history of psychiatric admission were significantly more likely to be located in the two most deprived quintiles. Almost one-third (29%) of children born to mothers with a pregnancy-related psychiatric admission were assessed as 'at potential risk of adversity.' CONCLUSIONS: A health informatics approach has potential for improving understanding of social and clinical factors, which contribute to the outcomes of perinatal mental illness, as well as potential adverse developmental outcomes for offspring.

Standard cardiovascular disease risk algorithms underestimate the risk of cardiovascular disease in schizophrenia: evidence from a national primary care database.

BACKGROUND: Schizophrenia is associated with increased cardiovascular mortality. Although cardiovascular disease (CVD) risk prediction algorithms are widely in the general population, their utility for patients with schizophrenia is unknown. METHODS: A primary care dataset was used to compare CVD risk scores (Joint British Societies (JBS) score), cardiovascular risk factors, rates of pre-existing CVD and age of first diagnosis of CVD for schizophrenia (n=1997) relative to population controls (n=215,165). RESULTS: Pre-existing rates of CVD and the recording of risk factors for those without CVD were higher in the schizophrenia cohort in the younger age groups, for both genders. Those with schizophrenia were more likely to have a first diagnosis of CVD at a younger age, with nearly half of men with schizophrenia plus CVD diagnosed under the age of 55 (schizophrenia men 46.1% vs. control men 34.8%, p<0.001; schizophrenia women 28.9% vs. control women 23.8%, p<0.001). However, despite high rates of CVD risk factors within the schizophrenia group, only a very small percentage (3.2% of men and 7.5% of women) of those with schizophrenia under age 55 were correctly identified as high risk for CVD according to the JBS risk algorithm. CONCLUSION: The JBS2 risk score identified only a small proportion of individuals with schizophrenia under the age of 55 as being at high risk of CVD, despite high rates of risk factors and high rates of first diagnosis of CVD within this age group. The validity of CVD risk prediction algorithms for schizophrenia needs further research.

Physical health indicators in major mental illness: analysis of QOF data across UK general practice.

BACKGROUND: The Quality and Outcomes Framework (QOF) has specific targets for body mass index (BMI) and blood pressure recording in major mental illness (MMI), diabetes, and chronic kidney disease (CKD). Although aspects of MMI (schizophrenia, bipolar disorder, and related psychoses) are incentivised, barriers to care may occur. AIM: To compare payment, population achievement, and exception rates for blood pressure and BMI recording in MMI relative to diabetes and CKD across the UK. DESIGN AND SETTING: Analysis of 2012/2013 QOF data from 9731 UK general practices 2 years after the introduction of the mental health, BMI, and blood pressure QOF indicators. METHOD: Payment, exception, and population achievement rates for the MMI and CKD blood pressure indicators and the MMI and diabetes BMI indicators were calculated and compared. RESULTS: UK payment and population achievement rates for BMI recording for MMI were significantly lower than for diabetes (payment: 92.7% versus 95.5% and population achievement: 84.0% versus 92.5%, P<0.001) and exception rates were higher (8.1% versus 2.0%, P<0.001). For blood pressure recording, UK payment and population achievement rates were significantly lower for MMI than for CKD (94.1% versus 97.8% and 87.0% versus 97.1%, P<0.001), while exception rate was higher (6.5% versus 0.0%, P<0.001). This was observed for all countries. Compared with England, Northern Ireland had higher population achievement rates for both mental health indicators, whereas Scotland and Wales had lower rates. There were no cross-jurisdiction differences for CKD and diabetes. CONCLUSION: Differences in payment, exception, and population achievement rates for blood pressure and BMI recording for MMI relative to CKD and diabetes were observed across the UK. These findings suggest potential inequalities in the monitoring of physical health in MMI within the UK primary care system.