Personal independence payments among people who access mental health services: results from a novel data linkage.

BACKGROUND: Personal independence payment (PIP) is a benefit that covers additional daily living costs people may incur from a long-term health condition or disability. Little is known about PIP receipt and associated factors among people who access mental health services, and trends over time. Individual-level data linking healthcare records with administrative records on benefits receipt have been non-existent in the UK. AIMS: To explore how PIP receipt varies over time, including PIP type, and its association with sociodemographic and diagnostic patient characteristics among people who access mental health services. METHOD: A data-set was established by linking electronic mental health records from the South London and Maudsley NHS Foundation Trust with administrative records from the Department for Work and Pensions. RESULTS: Of 143 714 working-age patients, 37 120 (25.8%) had received PIP between 2013 and 2019, with PIP receipt steadily increasing over time. Two in three patients (63.2%) had received both the daily living and mobility component. PIP receipt increased with age. Those in more deprived areas were more likely to receive PIP. The likelihood of PIP receipt varied by ethnicity. Patients diagnosed with a severe mental illness had 1.48 odds (95% CI 1.42-1.53) of having received PIP, compared with those with a different psychiatric diagnosis. CONCLUSIONS: One in four people who accessed mental health services had received PIP, with higher levels seen among those most likely in need, as indicated by a severe mental illness diagnosis. Future research using this data-set could explore the average duration of PIP receipt in people who access mental health services, and re-assessment patterns by psychiatric diagnosis.

A framework for remotely enabled co-design with young people: its development and application with neurodiverse children and their caregivers.

Introduction: This paper describes an innovative Framework for Remotely Enabled Co-Design with Young people (FREDY), which details an adaptable four-stage process for generating design concepts with children and other key stakeholders in a naturalistic and inclusive way. Methods: Recommendations from existing patient engagement and design methodologies were combined to provide research teams with procedures to capture and analyse end-user requirements rapidly. Resulting insights were applied through iterative design cycles to achieve accelerated and user-driven innovation. Results: Applying this framework with neurodiverse children within the context of healthcare, shows how creative design methods can give rise to new opportunities for co-creating across diverse geographies, abilities, and backgrounds as well as strengthen co-designer approval of the co-design process and resulting product. Discussion: We summarise key learnings and principles for fostering trust and sustaining participation with remote activities, and facilitating stakeholder design input through continuous collaboration, as well as highlight the potential benefits and challenges of utilising FREDY with neurotypical populations.

Attention-deficit/hyperactivity disorder (ADHD) in cultural context II: a comparison of the links between ADHD symptoms and waiting-related responses in Hong Kong and UK.

The concept of attention-deficit/hyperactivity disorder (ADHD) is considered to have cross-cultural validity, but direct comparisons of its psychological characteristics across cultures are limited. This study investigates whether preschool children's ADHD symptoms expressed in two cultures with different views about child behaviour and parenting, Hong Kong and the UK, show the same pattern of associations with their waiting-related abilities and reactions, an important marker of early self-regulation. A community sample of 112 preschoolers (mean age = 46.22 months; 55 from UK, 57 from HK) completed three tasks measuring different waiting elements - waiting for rewards, choosing the amount of time to wait, and having to wait unexpectedly when a task is interrupted. Participants' waiting-related behavioural and emotional reactions were coded. Parents rated their children's ADHD symptoms and delay aversion. Our findings revealed that the associations between ADHD symptoms and waiting-related responses were comparable in both UK and HK samples. This suggests that the core psychological characteristics of ADHD, particularly in relation to waiting behaviours, may exhibit similarity across cultural contexts. Future research can extend this cross-cultural analysis to other ADHD-related psychological domains and explore additional cultural settings.

Editorial: "What say you?" The promise and potential pitfalls of using automated and passive monitoring approaches to assess parenting behaviours from verbal and written communication.

Rates of mental health problems in adolescence are rising as highlighted in this current issue of the Journal. It is therefore increasingly important to identify children who may be at risk so that preventive interventions can be deployed before they reach adolescence. Adverse parenting has long been considered a risk factor for poor mental health in adolescence, but the methods traditionally used to assess this are laborious, burdensome and costly. Recently, passive monitoring and automated approaches to collecting and analysing spoken and written forms of parental communication have been proposed. This editorial examines the promise of such technological advances for assessing parenting and provides words of caution from parents and young people that should be heeded before rolling these approaches out at scale.

Universal Credit receipt among working-age patients who are accessing specialist mental health services: results from a novel data linkage study.

BACKGROUND: In 2013, Universal Credit (UC) was introduced by the UK Government. Understanding of how UC provision is allocated among people with mental disorders, and its intersection with protected characteristics is limited. This study aimed to explore (1) how UC receipt, including UC conditionality regime, varied among users of specialist mental health services between 2013 and 2019 and (2) associations between sociodemographic and diagnostic patient characteristics and UC receipt. METHODS: Working-age individuals who had accessed specialist mental health services were included if they had their mental health record data successfully linked with administrative benefits data. Associations between sociodemographic, diagnostic patient characteristics and UC receipt were explored using logistic regression models. RESULTS: Of the 143 715 patients, 26.9% had received UC between 2013 and 2019. Four in five patients were allocated to the searching for work conditionality regime during their time on UC. Females were less likely to have received UC (adjusted OR (AOR) 0.87, 95% CI 0.85 to 0.89) than males, and UC receipt decreased with age. Black patients (AOR 1.39, 95% CI 1.34 to 1.44) and patients from mixed and multiple ethnic backgrounds (AOR 1.27, 95% CI 1.18 to 1.38) had a higher likelihood of UC receipt than White patients. UC receipt was lower among patients diagnosed with severe mental illness compared with other psychiatric diagnoses (AOR 0.74, 95% CI 0.71 to 0.77). CONCLUSION: One in four specialist mental health service users had received UC and a large majority were subject to conditionality. The temporality of UC conditionality and mental health service presentation needs further exploration.

Impact of inconsistent ethnicity recordings on estimates of inequality in child health and education data: a data linkage study of Child and Adolescent Mental Health Services in South London.

OBJECTIVES: Ethnicity data are critical for identifying inequalities, but previous studies suggest that ethnicity is not consistently recorded between different administrative datasets. With researchers increasingly leveraging cross-domain data linkages, we investigated the completeness and consistency of ethnicity data in two linked health and education datasets. DESIGN: Cohort study. SETTING: South London and Maudsley NHS Foundation Trust deidentified electronic health records, accessed via Clinical Record Interactive Search (CRIS) and the National Pupil Database (NPD) (2007-2013). PARTICIPANTS: N=30 426 children and adolescents referred to local Child and Adolescent Mental Health Services. PRIMARY AND SECONDARY OUTCOME MEASURES: Ethnicity data were compared between CRIS and the NPD. Associations between ethnicity as recorded from each source and key educational and clinical outcomes were explored with risk ratios. RESULTS: Ethnicity data were available for 79.3% from the NPD, 87.0% from CRIS, 97.3% from either source and 69.0% from both sources. Among those who had ethnicity data from both, the two data sources agreed on 87.0% of aggregate ethnicity categorisations overall, but with high levels of disagreement in Mixed and Other ethnic groups. Strengths of associations between ethnicity, educational attainment and neurodevelopmental disorder varied according to which data source was used to code ethnicity. For example, as compared with White pupils, a significantly higher proportion of Asian pupils achieved expected educational attainment thresholds only if ethnicity was coded from the NPD (RR=1.46, 95% CI 1.29 to 1.64), not if ethnicity was coded from CRIS (RR=1.11, 0.98 to 1.26). CONCLUSIONS: Data linkage has the potential to minimise missing ethnicity data, and overlap in ethnicity categorisations between CRIS and the NPD was generally high. However, choosing which data source to primarily code ethnicity from can have implications for analyses of ethnicity, mental health and educational outcomes. Users of linked data should exercise caution in combining and comparing ethnicity between different data sources.

Automatic detection of expressed emotion from Five-Minute Speech Samples: Challenges and opportunities.

Research into clinical applications of speech-based emotion recognition (SER) technologies has been steadily increasing over the past few years. One such potential application is the automatic recognition of expressed emotion (EE) components within family environments. The identification of EE is highly important as they have been linked with a range of adverse life events. Manual coding of these events requires time-consuming specialist training, amplifying the need for automated approaches. Herein we describe an automated machine learning approach for determining the degree of warmth, a key component of EE, from acoustic and text natural language features. Our dataset of 52 recorded interviews is taken from recordings, collected over 20 years ago, from a nationally representative birth cohort of British twin children, and was manually coded for EE by two researchers (inter-rater reliability 0.84-0.90). We demonstrate that the degree of warmth can be predicted with an F1-score of 64.7% despite working with audio recordings of highly variable quality. Our highly promising results suggest that machine learning may be able to assist in the coding of EE in the near future.

The patient journeys of children and adolescents with depression: a study of electronic health records.

In England, children and adolescents with depression can seek treatment from specialist mental health services. We know little about how they journey through these services, or whether healthcare providers collect sufficient data to accurately appraise this. We aimed to summarise the child and adolescent depression pathway for two healthcare providers. This cohort study used de-identified electronic health records extracted from Cambridgeshire and Peterborough NHS Foundation Trust (CPFT) and South London and Maudsley NHS Foundation Trust (SLaM). We identified referrals between 2015 and 2019 during which the referred patient received their first depression diagnosis aged < 18 years. We described patient demographic and clinical characteristics, and features of the referral. In total, n = 296 (CPFT) and n = 2502 (SLaM) patients had a referral which met eligibility criteria. In both sites, patients were more frequently female (CPFT 79.3%; SLaM 69.3%) and White ethnicity (CPFT 88.9%; SLaM 57.9%) as compared to respective population estimates for the Trusts' catchment areas. Patients typically received their first depression diagnosis during adolescence (median ages 16 in CPFT and 15 in SLaM). The most common comorbidity was anxiety disorder. Referrals were usually routine, to community teams specialising in the child age group. Commonly mentioned interventions included antidepressant medication, cognitive behavioural therapy, and dialectical behaviour therapy. However, pathways varied within and between sites, and the quality and consistency of some data was poor. These findings provide an overview of service pathways experienced by children and adolescents with depression, but also highlight that pathways can vary according to individual need and healthcare provider. More systematic collection of some data, and standardisation in record systems used by different providers, would be beneficial.

Identifying features of risk periods for suicide attempts using document frequency and language use in electronic health records.

Background: Individualising mental healthcare at times when a patient is most at risk of suicide involves shifting research emphasis from static risk factors to those that may be modifiable with interventions. Currently, risk assessment is based on a range of extensively reported stable risk factors, but critical to dynamic suicide risk assessment is an understanding of each individual patient's health trajectory over time. The use of electronic health records (EHRs) and analysis using machine learning has the potential to accelerate progress in developing early warning indicators. Setting: EHR data from the South London and Maudsley NHS Foundation Trust (SLaM) which provides secondary mental healthcare for 1.8 million people living in four South London boroughs. Objectives: To determine whether the time window proximal to a hospitalised suicide attempt can be discriminated from a distal period of lower risk by analysing the documentation and mental health clinical free text data from EHRs and (i) investigate whether the rate at which EHR documents are recorded per patient is associated with a suicide attempt; (ii) compare document-level word usage between documents proximal and distal to a suicide attempt; and (iii) compare n-gram frequency related to third-person pronoun use proximal and distal to a suicide attempt using machine learning. Methods: The Clinical Record Interactive Search (CRIS) system allowed access to de-identified information from the EHRs. CRIS has been linked with Hospital Episode Statistics (HES) data for Admitted Patient Care. We analysed document and event data for patients who had at some point between 1 April 2006 and 31 March 2013 been hospitalised with a HES ICD-10 code related to attempted suicide (X60-X84; Y10-Y34; Y87.0/Y87.2). Findings: n = 8,247 patients were identified to have made a hospitalised suicide attempt. Of these, n = 3,167 (39.8%) of patients had at least one document available in their EHR prior to their first suicide attempt. N = 1,424 (45.0%) of these patients had been "monitored" by mental healthcare services in the past 30 days. From 60 days prior to a first suicide attempt, there was a rapid increase in the monitoring level (document recording of the past 30 days) increasing from 35.1 to 45.0%. Documents containing words related to prescribed medications/drugs/overdose/poisoning/addiction had the highest odds of being a risk indicator used proximal to a suicide attempt (OR 1.88; precision 0.91 and recall 0.93), and documents with words citing a care plan were associated with the lowest risk for a suicide attempt (OR 0.22; precision 1.00 and recall 1.00). Function words, word sequence, and pronouns were most common in all three representations (uni-, bi-, and tri-gram). Conclusion: EHR documentation frequency and language use can be used to distinguish periods distal from and proximal to a suicide attempt. However, in our study 55.0% of patients with documentation, prior to their first suicide attempt, did not have a record in the preceding 30 days, meaning that there are a high number who are not seen by services at their most vulnerable point.