Exploring the Use of Digital Interventions by People with Severe Mental Illness to Support Their Physical Health: A Mixed Methods Study.

People with severe mental illness (SMI) are more likely to experience physical health conditions than the general population. Little is known about the experience of people with SMI using digital health interventions (DHIs) to support their physical health. We explored how people with SMI use DHIs to support their physical health, the acceptability, factors affecting use, and impact on physical health. This was a three-stage mixed methods study (1) online survey of people with SMI; (2) interviews with a subsample of participants from Stage 1; (3) stakeholder workshops. Participants were generally satisfied with the DHIs they used. The most popular DHIs were targeted at diet, exercise, and weight management. Factors that encouraged use included simplicity and data-linkage. Concerns included costs, data security, and reliability of information. Positive impacts included accountability and tangible physical health benefits. Mental health impacted engagement with DHIs. DHIs were seen as a useful tool to monitor physical health but could not replace contact with clinical services. DHIs were considered useful and acceptable by people with SMI and may be used as an extension of clinical care. The specific needs and priorities of people with SMI should be considered both in developing and recommending interventions.

The prevalence of autism spectrum disorder traits and diagnosis in adults and young people with personality disorders: A systematic review.

OBJECTIVES: Autism spectrum disorders and personality disorders are spectrum conditions with shared clinical features. Despite similarities, previous attempts to synthesise literature on co-existing prevalence and shared traits have employed a unidirectional focus, assessing personality characteristics of individuals with an autism spectrum disorder diagnosis. Here, we assess the prevalence of autism spectrum disorder diagnosis and/or traits among persons diagnosed with a personality disorder. METHODS: We systematically reviewed the English-language literature following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, according to a pre-registered protocol (PROSPERO: CRD 42021264106). Peer-reviewed quantitative studies reporting the prevalence of autism spectrum disorder diagnosis or traits in persons with an established personality disorder diagnosis were included. Studies were critically appraised using the Appraisal tool for Cross-Sectional Studies. RESULTS: Fifteen studies were identified, including 72,902 participants (median: 48, interquartile range: 30-77). Diagnoses included borderline, schizotypal and obsessive-compulsive personality disorders, and cohorts with unspecified personality disorder diagnoses. There was significant heterogeneity in diagnostic methodology and assessment tools used. We identified preliminary evidence of an increased prevalence of co-existing autism spectrum disorder diagnosis and traits among those diagnosed with a personality disorder, although significant limitations of the literature were identified. CONCLUSION: Our research suggests clinicians should consider conducting a careful developmental assessment when assessing service-users with possible or confirmed personality disorder. Future research directions may include larger studies featuring clinical control groups, an exploration of shared and differentiating behavioural-cognitive features of the two conditions, and investigation into potentially shared aetiological factors. Research investigating demographic factors that may contribute to potential diagnostic overshadowing would also be welcomed.

Advance decisions in dementia: when the past conflicts with the present.

As the prevalence of dementia increases across the Western world, there is a growing interest in advance care planning, by which patients may make decisions on behalf of their future selves. Under which ethical principles is this practice justified? I assess the justification for advance care planning put forward by the philosopher Ronald Dworkin, which he rationalises through an integrity-based conception of autonomy. I suggest his judgement is misguided by arguing in favour of two claims. First, that patients with dementia qualify for some right to contemporary autonomy conceptualised under the 'sense of liberty' it provides. Second, that respecting precedent autonomy, such as an advance care plan, is not essential to Dworkin's integrity-based account of autonomy. Together, my claims problematise the practice of using advance decisions in the context of dementia.

Pink and blue: the role of gender in psychiatric diagnosis.

Why are the diagnostic criteria of some psychiatric disorders standardised by gender while others are not? Why standardise symptom questionnaires by gender but not other personal characteristics such as ethnicity, socioeconomic class or sexual orientation? And how might our changing attitudes towards gender, born from scientific research and changing societal narratives, alter our opinion of these questions? This paper approaches these dilemmas by assessing the concept of diagnosis in psychiatry itself, before analysing two common approaches to the study of psychiatric diagnosis; the naturalist and constructivist views. The paper assesses the relative merits and significance of each, before turning its attention to the nature of gender and its relevance to psychiatry. The paper introduces a framework to approach gender-based diagnostic bias and concludes by drawing a distinction between qualitative and quantitative standardisation, arguing that gender standardisation of psychiatric diagnoses is ethically justified in the former but not the latter.

Exploring foundation doctors' self-reported confidence in the assessment and management of mental health conditions.

AIMS AND METHOD: This study assesses newly qualified doctors' confidence in practising clinical skills related to the assessment and management of mental health conditions and how this correlates with other areas of medicine. We conducted a national survey of 1311 Foundation Year 1 doctors in the UK. Survey items assessed confidence recognising mentally unwell patients, conducting a mental state examination, assessing cognition and mental capacity, formulating a psychiatric diagnosis and prescribing psychotropic medications. RESULTS: A substantial proportion of surveyed doctors lacked confidence in their clinical skills related to mental health and prescribing psychotropic medications. Network analysis revealed that items corresponding to mental health were highly correlated, suggesting a potential generalised lack of confidence in mental healthcare. CLINICAL IMPLICATIONS: We identify areas of lack of confidence in some newly qualified doctors' ability to assess and manage mental health conditions. Future research might explore how greater exposure to psychiatry, integrated teaching and clinical simulation might better support medical students for future clinical work.

'Medical clearance' and referral to liaison psychiatry: a national service evaluation.

AIMS AND METHOD: The prevalence of delaying psychiatric care until the patient has received 'medical clearance', and the definitions and understanding of 'medical clearance' terminology by relevant clinicians, are largely unknown. In a service evaluation of adult liaison psychiatry services across England, we explore the prevalence, definitions and understanding of 'medical clearance' terminology in three parallel studies: (a) an analysis of trust policies, (b) a survey of liaison psychiatry services and (c) a survey of referring junior doctors. Content and thematic analyses were performed. RESULTS: 'Medical clearance' terminology was used in the majority of trust policies, reported as a referral criterion by many liaison psychiatry services and had been encountered by most referring doctors. 'Medical clearance' was identified as a common barrier to liaison psychiatry referral. Terms were inconsistently used and poorly defined. CLINICAL IMPLICATIONS: Many liaison psychiatry services seem not to comply with guidance promoting parallel assessment. This may affect parity of physical and mental healthcare provision.

Acute Severe Hyponatremia Following Use of "Detox Tea".

A previously healthy 51-year-old woman presented to the ED with a one-week history of malaise, myalgia, unsteadiness, and an intermittent mild headache. Physical examination revealed neurological signs including a broad-based gait and bilateral low amplitude tremor. Laboratory testing of electrolytes revealed acute severe hyponatremia (115 mmol/L). Further, history-taking revealed increased urinary frequency following regular consumption of an over-the-counter detoxification tea product. The patient made a good recovery following admission to the intensive care unit. We identify similar cases in the literature and explore potential causal mechanisms. This case highlights the importance of enquiring about the use of supplementary health products when taking a history, and specifically identifies a growing number of reports of acute severe hyponatremia following the use of "detox teas".

Sleep and circadian rhythm actigraphy measures, mood instability and impulsivity: A systematic review.

The normal spectrum trait measures of mood instability and impulsivity are implicated in and comprise core symptoms of several psychiatric disorders. A bidirectional relationship between these traits and sleep disturbance and circadian rhythm dysfunction has been hypothesised, although has not been systematically assessed using objective measures in naturalistic settings. We systematically reviewed the literature following PRISMA guidelines, according to a pre-registered protocol (PROSPERO: CRD 42018108213). Peer-reviewed quantitative studies assessing an association between actigraphic variables and any measure of mood instability or impulsivity in participants aged 12-65 years old were included. Studies were critically appraised using the AXIS tool. Twenty-three articles were retained for inclusion. There was significant heterogeneity in the selection and reporting of actigraphic variables and metrics of mood instability and impulsivity. We identified emerging evidence of a positive association between circadian rest-activity pattern disturbance and delayed sleep timing with both mood instability and impulsivity. Evidence for an association with sleep duration, sleep efficiency or sleep quality was inconsistent. Future research should focus on longitudinal intra-individual associations to establish the directionality between these measures and may lead to the development of chronotherapeutic interventions for a number of psychiatric disorders.

Digital Communication Biomarkers of Mood and Diagnosis in Borderline Personality Disorder, Bipolar Disorder, and Healthy Control Populations.

Background: Remote monitoring and digital phenotyping harbor potential to aid clinical diagnosis, predict episode course and recognize early signs of mental health crises. Digital communication metrics, such as phone call and short message service (SMS) use may represent novel biomarkers of mood and diagnosis in Bipolar Disorder (BD) and Borderline Personality Disorder (BPD). Materials and Methods: BD (n = 17), BPD (n = 17) and Healthy Control (HC, n = 21) participants used a smartphone application which monitored phone calls and SMS messaging, alongside self-reported mood. Linear mixed-effects regression models were used to assess the association between digital communications and mood symptoms, mood state, trait-impulsivity, diagnosis and the interaction effect between mood and diagnosis. Results: Transdiagnostically, self-rated manic symptoms and manic state were positively associated with total and outgoing call frequency and cumulative total, incoming and outgoing call duration. Manic symptoms were also associated with total and outgoing SMS frequency. Transdiagnostic depressive symptoms were associated with increased mean incoming call duration. For the different diagnostic groups, BD was associated with increased total call frequency and BPD with increased total and outgoing SMS frequency and length compared to HC. Depression in BD, but not BPD, was associated with decreased total and outgoing call frequency, mean total and outgoing call duration and total and outgoing SMS frequency. Finally, trait-impulsivity was positively associated with total call frequency, total and outgoing SMS frequency and cumulative total and outgoing SMS length. Conclusion: These results identify a general increase in phone call and SMS communications associated with self-reported manic symptoms and a diagnosis-moderated decrease in communications associated with depression in BD, but not BPD, participants. These findings may inform the development of clinical tools to aid diagnosis and remote symptom monitoring, as well as informing understanding of differential psychopathologies in BD and BPD.

A day in the life of a psychiatrist in 2050: where will the algorithm take us?

Digital phenotyping (such as using live data from personal digital devices on sleep, activity and social media interactions) to monitor and interpret people's current mental state is a newly emerging development in psychiatry. This article offers an imaginary insight into its future potential for both psychiatrist and patient.

Severe psychiatric disturbance and attempted suicide in a patient with COVID-19 and no psychiatric history.

A previously fit and well 37-year-old male healthcare worker presented with confusion, psychotic symptoms and a suicide attempt in the context of a new COVID-19 diagnosis. Following surgical interventions and an extended admission to the intensive care unit, he made a good recovery in terms of both his physical and mental health. A number of factors likely contributed to his presentation, including SARS-CoV-2 infection, severe insomnia, worry, healthcare worker-related stress, and the unique social and psychological stressors associated with the COVID-19 pandemic. This case highlights the need to further characterise the specific psychiatric sequelae of COVID-19 in community settings, and should remind general medical clinicians to be mindful of comorbid psychiatric symptoms when assessing patients with newly diagnosed COVID-19.

Predicting treatment effects in unipolar depression: A meta-review.

There is increasing interest in clinical prediction models in psychiatry, which focus on developing multivariate algorithms to guide personalized diagnostic or management decisions. The main target of these models is the prediction of treatment response to different antidepressant therapies. This is because the ability to predict response based on patients' personal data may allow clinicians to make improved treatment decisions, and to provide more efficacious or more tolerable medications to the right patient. We searched the literature for systematic reviews about treatment prediction in the context of existing treatment modalities for adult unipolar depression, until July 2019. Treatment effect is defined broadly to include efficacy, safety, tolerability and acceptability outcomes. We first focused on the identification of individual predictor variables that might predict treatment response, and second, we considered multivariate clinical prediction models. Our meta-review included a total of 10 systematic reviews; seven (from 2014 to 2018) focusing on individual predictor variables and three focusing on clinical prediction models. These identified a number of sociodemographic, phenomenological, clinical, neuroimaging, remote monitoring, genetic and serum marker variables as possible predictor variables for treatment response, alongside statistical and machine-learning approaches to clinical prediction model development. Effect sizes for individual predictor variables were generally small and clinical prediction models had generally not been validated in external populations. There is a need for rigorous model validation in large external data-sets to prove the clinical utility of models. We also discuss potential future avenues in the field of personalized psychiatry, particularly the combination of multiple sources of data and the emerging field of artificial intelligence and digital mental health to identify new individual predictor variables.