Forecasting population need for mental health care: a Bayesian methodology applied to the epidemiology of psychotic disorders in England

Background: Mental health service policymakers require evidence-based information to optimise effective care provision based on local need, but tools are unavailable. We developed and validated a population-level prediction model to forecast need for early intervention in psychosis [EIP] services in England up to 2025.Methods: We fitted six candidate Bayesian Poisson regression models, combining epidemiological data on psychosis risk, to predict new annual caseload of referrals, assessed, treated, and probable first episode psychosis [FEP] cases in EIP services, aged 16-64 years at small-area level. Models were validated against observed NHS Mental Health Services Data Set [MHSDS] data at Clinical Commissioning Group [CCG] and national levels for 2017. Projections were made up to 2025, based on small-area demographic forecasts. Outcome: In 2017, our best-fitting model predicted 8,112 (95% interval: 7,623 to 8,597) individuals with probable FEP in England, compared with 8,038 observed in the MHSDS (difference: n=+74; +0·92%), after accounting for psychosis risk by age, sex, ethnicity, small area-level deprivation, social fragmentation and regional cannabis use. In 2020, this model forecasted 9,066 new treated FEP cases (8,485 to 9,618), rising 1% annually up to 2025. For every ten treated cases, we forecasted that 23 and 21 people would be referred to and assessed by EIP services, respectively, for “suspected FEP”. Interpretation: Our methodology provides an accurate, validated toolkit to inform planners, commissioners and providers about future population need for psychosis care at different stages of the referral pathway, based on local determinants of need.Funding: Wellcome Trust, Royal Society, National Institute for Health Research

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O1.3. BACK TO THE FUTURE: PREDICTING POPULATION NEED FOR PSYCHOSIS CARE BASED ON THE EPIDEMIOLOGY OF PSYCHOTIC DISORDERS IN ENGLAND, AN APPLIED BAYESIAN METHODOLOGY

Schizophrenia Bulletin ◽

10.1093/schbul/sbaa028.002 ◽

2020 ◽

Vol 46 (Supplement_1) ◽

pp. S1-S2

Author(s):

Keltie McDonald ◽

Tao Ding ◽

Rebecca Dliwayo ◽

David Osborn ◽

Pia Wohland ◽

...

Keyword(s):

Mental Health ◽

Early Intervention ◽

Small Area ◽

Psychotic Disorders ◽

Population Projections ◽

First Episode ◽

Evidence Based ◽

Psychosis Risk ◽

Small Area Level ◽

Early Intervention In Psychosis

Abstract Background Providing timely, adequate and appropriately-resourced care to people experiencing their first episode of psychosis needs to be informed by evidence-based models of future need in the population. We sought to develop a validated prediction model of need for provision of early intervention in psychosis [EIP] services at the small area level in England up to 2025, based on current epidemiological evidence and demographic projections of the at-risk population. Methods We developed a Bayesian population-level prediction tool. First, we obtained small area incidence data on first episode psychoses, aged 16–64 years, from three major empirical studies of psychosis risk (ÆSOP, ELFEP and SEPEA). Second, we identified suitable prior information from the published literature on variation in psychosis risk by age, sex, ethnicity, deprivation and cannabis use. Third, we combined this empirical data with prior beliefs in six Bayesian Poisson regression models to obtain a full characterisation of the underlying uncertainty in the form of suitable posterior distributions for the relative risks for different permutations of covariate data. Fourth, model coefficients were applied to population projections for 2017 to predict the expected incidence of psychotic disorders, aggregated to Commissioning Group [CCG] and national levels. Fifth, we compared these predictions to observed national FEP data from the NHS Mental Health Services Data Set in 2017 to establish the most valid model. Sixth, we used the best-fitting model to predict three nested indicators of need for psychosis care: (i) total annual referrals to early intervention in psychosis [EIP] for “suspected” FEP (ii) total annual cases accepted onto EIP service caseloads, and (iii) total annual new cases of probable FEP in England up until 2025, using small area population projections. Results A model with an age-sex interaction, ethnicity, small area-level deprivation, social fragmentation and regional cannabis use provided best internal and apparent validity, predicting 8112 (95% Credible Interval 7623 to 8597) individuals with FEP in England in 2017, compared with 8038 observed cases (difference: n=74; 0.94%). Apparent validity was acceptable at CCG level, and by sex and ethnicity, although we observed greater-than-expected need before 35 years old. Predicted new referrals, caseloads and probable incidences of FEP rose over the forecast period by 6.2% to 25,782, 23,187 and 9,541 new cases in 2025, respectively. Discussion Our translational epidemiological tool provides an accurate, validated method to inform planners, commissioners and providers about future population need for psychosis care at different stages of the referral pathway, based on individual and small area level determinants of need. Such tools can be used to underpin evidence-based decision-making in public mental health and resource allocation in mental health systems.

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Using epidemiological evidence to forecast population need for early treatment programmes in mental health: a generalisable Bayesian prediction methodology applied to and validated for first-episode psychosis in England

The British Journal of Psychiatry ◽

10.1192/bjp.2021.18 ◽

2021 ◽

pp. 1-9

Author(s):

Keltie McDonald ◽

Tao Ding ◽

Hannah Ker ◽

Thandiwe Rebecca Dliwayo ◽

David P.J. Osborn ◽

...

Keyword(s):

Mental Health ◽

Small Area ◽

First Episode Psychosis ◽

Initial Assessment ◽

First Episode ◽

Evidence Based ◽

Epidemiological Evidence ◽

Episode Psychosis ◽

Small Area Level ◽

Early Intervention In Psychosis

Background Mental health policy makers require evidence-based information to optimise effective care provision based on local need, but tools are unavailable. Aims To develop and validate a population-level prediction model for need for early intervention in psychosis (EIP) care for first-episode psychosis (FEP) in England up to 2025, based on epidemiological evidence and demographic projections. Method We used Bayesian Poisson regression to model small-area-level variation in FEP incidence for people aged 16–64 years. We compared six candidate models, validated against observed National Health Service FEP data in 2017. Our best-fitting model predicted annual incidence case-loads for EIP services in England up to 2025, for probable FEP, treatment in EIP services, initial assessment by EIP services and referral to EIP services for ‘suspected psychosis’. Forecasts were stratified by gender, age and ethnicity, at national and Clinical Commissioning Group levels. Results A model with age, gender, ethnicity, small-area-level deprivation, social fragmentation and regional cannabis use provided best fit to observed new FEP cases at national and Clinical Commissioning Group levels in 2017 (predicted 8112, 95% CI 7623–8597; observed 8038, difference of 74 [0.92%]). By 2025, the model forecasted 11 067 new treated cases per annum (95% CI 10 383–11 740). For every 10 new treated cases, 21 and 23 people would be assessed by and referred to EIP services for suspected psychosis, respectively. Conclusions Our evidence-based methodology provides an accurate, validated tool to inform clinical provision of EIP services about future population need for care, based on local variation of major social determinants of psychosis.

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Cost-effectiveness of early intervention in psychosis: systematic review

The British Journal of Psychiatry ◽

10.1192/bjp.2018.298 ◽

2019 ◽

Vol 215 (01) ◽

pp. 388-394 ◽

Cited By ~ 13

Author(s):

David Aceituno ◽

Norha Vera ◽

A. Matthew Prina ◽

Paul McCrone

Keyword(s):

Mental Health ◽

Early Intervention ◽

Cost Effectiveness ◽

Health Systems ◽

Psychotic Disorders ◽

First Episode ◽

Economic Evaluations ◽

Eligibility Criteria ◽

The Cost ◽

Early Intervention In Psychosis

BackgroundEarly intervention in psychosis (EIP) has been developed as an approach to improve the prognosis of people with psychotic disorders and it has been claimed to be a more efficient model of care. However, the evidence is not definitive and doubts have spread regard to the economic outcomes of EIP services amid the usually restricted mental health budget.AimsWe aimed to review the cost-effectiveness evidence of EIP services worldwide.MethodWe systematically reviewed the economic literature about EIP following the Preferred Reporting Items for Systematic reviews and Meta-Analyses statement guidelines. Studies were selected according to previously stated criteria and analysed with standardised critical appraisal tools for trial-based economic evaluations and modelling studies.ResultsA total of 16 studies were selected after applying the eligibility criteria. Most of them were economic evaluations alongside clinical trials. The overall evidence was consistent in the cost-effectiveness of EIP compared with standard care for first episode of psychosis and the Clinical High Risk for Psychosis paradigm. Such evidence was replicated among different health systems, but mainly in high-income countries. The methodological quality of such evidence, however, was moderate and heterogeneity was significant across the studies.ConclusionsThere is consistent evidence that the implementation of EIP services might be a cost-effective alternative across different health systems. Such evidence, nevertheless, derives from heterogeneous and sometimes methodologically flawed studies, reducing the certainty of such statement. More efforts must be done to rigorously assess the value of this intervention, before expanding it among systems where mental health budgets are more constrained.Declaration of interestNone.

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Potential value of the current mental health monitoring of children in state care in England

BJPsych Open ◽

10.1192/bjo.2018.70 ◽

2018 ◽

Vol 4 (6) ◽

pp. 486-491 ◽

Cited By ~ 3

Author(s):

Christine Cocker ◽

Helen Minnis ◽

Helen Sweeting

Keyword(s):

Mental Health ◽

Missing Data ◽

Mental Health Problems ◽

Population Level ◽

Cross Sectional ◽

Data Set ◽

Looked After Children ◽

Education Data ◽

Sample Attrition ◽

Aggregate Population

BackgroundRoutine screening to identify mental health problems in English looked-after children has been conducted since 2009 using the Strengths and Difficulties Questionnaire (SDQ).AimsTo investigate the degree to which data collection achieves screening aims (identifying scale of problem, having an impact on mental health) and the potential analytic value of the data set.MethodDepartment for Education data (2009–2017) were used to examine: aggregate, population-level trends in SDQ scores in 4/5- to 16/17-year-olds; representativeness of the SDQ sample; attrition in this sample.ResultsMean SDQ scores (around 50% ‘abnormal’ or ‘borderline’) were stable over 9 years. Levels of missing data were high (25–30%), as was attrition (28% retained for 4 years). Cross-sectional SDQ samples were not representative and longitudinal samples were biased.ConclusionsMental health screening appears justified and the data set has research potential, but the English screening programme falls short because of missing data and inadequate referral routes for those with difficulties.Declaration of interestNone.

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Reddit Users’ Experiences of Suicidal Thoughts During the COVID-19 Pandemic: A Qualitative Analysis of r/Covid19_support Posts (Preprint)

10.2196/preprints.28891 ◽

2021 ◽

Author(s):

Allie Slemon ◽

Corey McAuliffe ◽

Trevor Goodyear ◽

Liza McGuinness ◽

Elizabeth Shaffer ◽

...

Keyword(s):

Mental Health ◽

Qualitative Research ◽

Social Media ◽

Coping Strategies ◽

Health Resources ◽

Population Level ◽

Epidemiological Data ◽

Qualitative Inquiry ◽

Search Term ◽

Suicidal Thoughts

BACKGROUND The COVID-19 pandemic is having considerable impacts on population-level mental health, with research illustrating an increased prevalence in suicidal thoughts due to pandemic stressors. While the drivers of suicidal thoughts amid the pandemic are poorly understood, qualitative research holds great potential for expanding upon projections from pre-pandemic work and contextualizing emerging epidemiological data. Despite calls for qualitative inquiry, there is a paucity of qualitative research examining experiences of suicidality related to COVID-19. The use of publicly available data from social media offers timely and pertinent information into ongoing pandemic-related mental health, including individual experiences of suicidal thoughts. OBJECTIVE The objective of this paper is to examine online posts that discuss suicidal thoughts within one Reddit community r/COVID19_support with the aim to identify contributing stressors and coping strategies related to the COVID-19 pandemic. METHODS This study draws on online posts from within the Reddit community r/COVID19_support that describe users’ suicidal thoughts during and related to the COVID-19 pandemic. Data were collected from creation of this subreddit on February 12, 2020 until December 31, 2020. Using the search term “suicide”, we used the NCapture add-on tool, hosted by NVivo, to conduct our investigation. A qualitative thematic analysis, as described by Braun and Clarke, was conducted to generate themes reflecting users’ experiences of suicidal thoughts. RESULTS A total of 83 posts from 57 users were included in the analysis. Reddit posts described a range of users’ lived experiences of suicidal thoughts related to the pandemic, including deterioration in mental health, complex emotions associated with suicidal thinking, and concern that suicidal thoughts may progress to action. Seven prominent and compounding stressors were identified as contributing to Reddit users’ suicidal thoughts, including social isolation, employment and finances, virus exposure and COVID-19 illness, uncertain timeline of the pandemic, news and social media, pre-existing mental health conditions, and lack of access to mental health resources. Some users described individual coping strategies used in attempt to manage suicidal thoughts, however these were recognized as insufficient for addressing the multilevel stressors of the pandemic. CONCLUSIONS Multiple and intersecting stressors have contributed to individuals’ experiences of suicidal thoughts in the context of the COVID-19 pandemic, requiring thoughtful and complex public health and policy responses. While ongoing challenges exist with self-disclosure of mental health challenges on social media, Reddit and other online platforms may a supportive space for users to share suicidal thoughts and discuss potential coping strategies.

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Risk of depression in family caregivers: unintended consequence of COVID-19

BJPsych Open ◽

10.1192/bjo.2020.99 ◽

2020 ◽

Vol 6 (6) ◽

Author(s):

Stephen Gallagher ◽

Mark A. Wetherell

Keyword(s):

Mental Health ◽

Family Caregivers ◽

Depressive Symptomatology ◽

Negative Impact ◽

General Health Questionnaire ◽

Population Level ◽

Poor Mental Health ◽

Unintended Consequences ◽

Depression Symptoms ◽

Data Set

Background Coronavirus disease 2019 (COVID-19) is likely to exacerbate the symptoms of poor mental health in family caregivers. Aims To investigate whether rates of depressive symptomatology increased in caregivers during COVID-19 and whether the unintended consequences of health protective measures, i.e., social isolation, exacerbated this risk. Another aim was to see if caregivers accessed any online/phone psychological support during COVID. Method Data (1349 caregivers; 6178 non-caregivers) was extracted from Understanding Society, a UK population-level data-set. The General Health Questionnaire cut-off scores identified those who are likely to have depression. Results After adjustment for confounding caregivers had a higher risk of having depressive symptoms compared with non-caregivers, odds ratio (OR) = 1.22 (95% CI 1.05–1.40, P = 0.008) evidenced by higher levels of depression pre-COVID-19 (16.7% caregivers v. 12.1% non-caregivers) and during the COVID-19 pandemic (21.6% caregivers v. 17.9% non-caregivers), respectively. Further, higher levels of loneliness increased the risk of depression symptoms almost four-fold in caregivers, OR = 3.85 (95% 95% CI 3.08–4.85, P < 0.001), whereas accessing therapy attenuated the risk of depression (43%). A total of 60% of caregivers with depression symptoms reported not accessing any therapeutic support (for example online or face to face) during the COVID-19 pandemic. Conclusions COVID-19 has had a negative impact on family caregivers’ mental health with loneliness a significant contributor to depressive symptomatology. However, despite these detriments in mental health, the majority of caregivers do not access any online or phone psychiatric support. Finally, psychiatric services and healthcare professionals should aim to focus on reducing feelings of loneliness to support at-risk caregivers.

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Impulsivity in early psychosis: A complex link with violent behaviour and a target for intervention

European Psychiatry ◽

10.1016/j.eurpsy.2017.12.003 ◽

2018 ◽

Vol 49 ◽

pp. 30-36 ◽

Cited By ~ 11

Author(s):

V. Moulin ◽

P. Golay ◽

J. Palix ◽

P.S. Baumann ◽

M-M. Gholamrezaeec ◽

...

Keyword(s):

Substance Abuse ◽

Early Intervention ◽

Psychotic Disorders ◽

Interaction Analysis ◽

Early Psychosis ◽

First Episode ◽

Positive Symptoms ◽

Violent Behaviour ◽

Increased Risk ◽

Early Intervention In Psychosis

AbstractBackgroundViolent behaviour (VB) occurs in first episode of schizophrenia and can have devastating impact both on victims and patients themselves. A better knowledge of the underlying mechanisms of VB may pave the way to preventive treatments.Objectives1) To explore the nature of the link between impulsivity and VB in early psychosis (EP) patients; 2) To explore the interactions between impulsivity and substance abuse, insight, and positive symptoms, the main dynamic risk factors of VB described to date.Design and methodsPost hoc analysis of data acquired in the frame of a 36-months EP cohort study. A total of 265 EP patients, aged 18 to 35, treated at TIPP (Treatment and early Intervention in Psychosis Program), at the Department of Psychiatry in Lausanne, Switzerland, were included in the study. Logistic regression analyzes were performed as well as mediation analysis and interaction analysisResultsOur data suggest that impulsivity is a predictor of VB when analyzed independently and as part of a multi-factorial model. Impulsivity continues to differentiate violent patients from non-violent ones at the end of the program. In addition, the relationship between impulsivity and VB is not mediated by substance abuse. Finally, the effect of impulsivity on the probability of VB is potentiated by the interaction of different levels of insight and positive symptoms.ConclusionsEarly intervention strategies in psychotic disorders should include evaluation of impulsivity considering it is linked to increased risk of VB and may respond to treatment.

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Long-term Benzodiazepine Treatment in Patients with Psychotic Disorders Attending a Mental Health Service in Rural Greece

Journal of Neurosciences in Rural Practice ◽

10.4103/0976-3147.196447 ◽

2016 ◽

Vol 07 (S 01) ◽

pp. S026-S030 ◽

Cited By ~ 1

Author(s):

Vaios Peritogiannis ◽

Thiresia Manthopoulou ◽

Venetsanos Mavreas

Keyword(s):

Mental Health ◽

Treatment Regimen ◽

Psychotic Disorders ◽

Population Based ◽

First Episode ◽

Future Research ◽

History Of ◽

The Mean ◽

Mobile Mental Health

ABSTRACT Introduction: Long-term benzodiazepine (BZD) treatment in patients with mental disorders is widespread in clinical practice, and this is also the case of patients with schizophrenia, although the evidence is weak and BZD prescription is discouraged by guidelines and medical authorities. Data on BZD prescription are usually derived from national or regional databases whereas information on the use of BZD by patients with schizophrenia and related psychoses in general population-based samples is limited. Materials and Methods: Information for 77 patients with psychotic disorders who were regularly attending follow-up appointments with the multidisciplinary Mobile Mental Health Unit of the prefectures of Ioannina and Thesprotia, Northwest Greece, during 1-year period (2015) was obtained from our database. Results: From the total of 77 engaged patients, 30 (39%) were regularly prescribed BZDs in the long term, as part of their treatment regimen. Prescribed BZDs were mostly diazepam and lorazepam, in 43.3% of cases each. The mean daily dose of these compounds was 13 mg and 3.77 mg, respectively. Statistical analysis showed a correlation of long-term BZD use with the history of alcohol/substance abuse. Most patients were receiving BZD continuously for several years, and the mean dose was steady within this interval. Conclusions: A large proportion of patients with psychotic disorders were regularly prescribed BZD in long term. It appears that when BZDs are prescribed for some period in the course of a psychotic disorder, their use commonly exceeds the recommended interval and then becomes a regular part of the chronic treatment regimen. Future research should address the factors that may be related to the long-term BZD use by patients with psychotic disorders. Interventions for the reduction of regular BZD prescription should target the primary care setting and all those who treat first episode patients.

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The Nature of Schizophrenia: Signposts to Prevention

Australian & New Zealand Journal of Psychiatry ◽

10.1177/000486740003401s03 ◽

2000 ◽

Vol 34 (1_suppl) ◽

pp. A14-A21 ◽

Cited By ~ 12

Author(s):

Patrick D. McGorry

Keyword(s):

Mental Health ◽

Risk Factors ◽

Primary Prevention ◽

Psychotic Disorders ◽

Early Years ◽

First Episode ◽

Preventive Interventions ◽

Work Settings ◽

The Face ◽

National Mental Health

Objective To describe the characteristics of schizophrenia relevant to conducting indicated preventive interventions. Method A systematic review of the literature informed by experiences at the Personal Assistance and Crisis Evaluation (PACE) clinic. Results Primary prevention requires a sophisticated knowledge of key causal risk factors relevant to the expression of a disorder. The causal risk factors most useful from an intervention standpoint may turn out to be somewhat removed from the neurobiology of the disorder and may even be relatively non-specific, so that tackling them could reduce the risks for a range of mental disorders. The frontier for more specific prevention in schizophrenia and related psychosis is currently represented by indicated preventive interventions for subthreshold symptoms. Again, these may be relatively broad spectrum early in the prepsychotic phase but more proximal to onset, greater treatment specificity can be explored. However, this can be viewed more as preventively orientated treatment rather than primary prevention per se. Early detection of first episode psychosis and optimal intensive treatment of first episodes and the critical early years after diagnosis also represent increasingly attractive preventive foci in psychotic disorders. Conclusion As evidence accumulates, implementation of evidence-based practice in real work settings is a major challenge as it is throughout the mental health service system. The momentum of preventively orientated treatment must be maintained through the 2nd National Mental Health Strategy and in the face of recent misleading polemic regarding the treatability of psychotic disorders, especially schizophrenia. The evidence demonstrates that schizophrenia and related disorders have never been more treatable.

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