Co-design of 'Ways of Being', a web-based experience to optimise online arts and culture for mental health in young people

AIMS AND METHOD

We aimed to co-design an intervention optimising the benefits of online arts and culture for mental health in young people for subsequent testing in a trial. Co-design followed the double diamond phases of design, discover, define, develop and deliver.

RESULTS

Navigating the views of all co-designers to produce a testable resource demanded in-depth understanding, and frequent iterations in multiple modalities of the theoretical basis of the intervention, amplification of youth voice and commitment to a common goal.

CLINICAL IMPLICATIONS

Co-design with a broad range of collaborators with a shared vision was valued by young co-designers and produced an effective intervention. Co-design allowed the theoretical basis to be followed and refined to create an engaging, practical and testable web experience, aiming to optimise the mental health benefits of online arts and culture for young people in a randomised controlled trial.

Count Me In: an inclusive approach towards patient recruitment for clinical research studies in the NHS

BACKGROUND

Participation in clinical research is associated with better patient outcomes and higher staff retention and satisfaction rates. Nevertheless, patient recruitment to mental health studies is challenging due to a reliance on clinician or patient referrals (standard approach). To empower patients and make healthcare research more equitable, we explored a novel researcher-led approach, called 'Count Me In' (CMI).

OBJECTIVE

To evaluate a 12-month implementation of CMI in a routine clinical setting.

METHODS

CMI was launched in August 2021 in a mental health National Health Service (NHS) Trust in England. Patients (aged 18+) learnt about CMI at their initial clinical appointment. Unless they opted out, they became contactable for research (via research informatics searches).

FINDINGS

After 12 months, 368 patients opted out and 22 741 became contactable through CMI, including 2716 through the standard approach and 20 025 through electronic searches (637% increase). Of those identified via electronic searches, 738 were contacted about specific studies and 270 consented to participate. Five themes were identified based on patient and staff experiences of CMI: 'level of awareness and accessibility of CMI', 'perceptions of research and perceived engagement with CMI', 'inclusive research practice', 'engagement and incentives for research participation', and 'relationships between clinical and research settings'.

CONCLUSIONS

CMI (vs standard) led to a larger and diverse patient cohort and was favoured by patients and staff. Yet a shift in the NHS research culture is needed to ensure that this diversity translates to actual research participation.

CLINICAL IMPLICATIONS

Through collaboration with other NHS Trusts and services, key funders (National Institute for Health and Care Research) and new national initiatives (Office for Life Sciences Mental Health Mission), CMI has the potential to address recruitment challenges through rapid patient recruitment into time-sensitive country-wide studies.

User perspectives on long-term remote active electronic self-monitoring of mood symptoms in bipolar spectrum disorders

BACKGROUND

User feedback is crucial in the development of electronic self-monitoring tools for bipolar spectrum disorders (BSD). Previous studies have examined user experiences in small samples self-monitoring over relatively short time periods. We aimed to explore the experiences of a large sample of individuals with BSD engaged in long-term remote active electronic self-monitoring.

METHODS

An online survey, containing closed and open questions, was sent to participants with BSD enrolled on the Bipolar Disorder Research Network (BDRN) True Colours mood-monitoring system. Questions related to experiences of using True Colours, including viewing mood graphs, and sharing data with healthcare professionals (HCPs) and/or family/friends.

RESULTS

Response rate was 62.7 % (n = 362). 88.4 % reported finding using True Colours helpful. Commonly reported benefits were having a visual record of mood changes, patterns/triggers and identifying early warning signs. Limitations included questions not being comprehensive or revealing anything new. One third had shared their graphs, with 89.9 % finding it helpful to share with HCPs and 78.7 % helpful to share with family/friends. Perceived benefits included aiding communication and limitations included lack of interest/understanding from others.

LIMITATIONS

Responder bias may be present. Findings may not be generalisable to all research cohorts.

CONCLUSIONS

The majority of participants valued long-term self-monitoring. Personalisation and ease of use were important. A potential challenge is continued use when mood is long-term stable, highlighting the need for measures to be sensitive to small changes. Sharing self-monitoring data with HCPs may enhance communication of the lived experience of those with BSD. Future research should examine HCPs' perspectives.

Setting national research priorities for difficult-to-treat depression in the UK between 2021-2026

Background

Difficult-to-treat depression (DTD) presents a substantial health care challenge, with around one-third of people diagnosed with a depressive episode in the UK finding that their symptoms persist following treatment. This study aimed to identify priority research questions (RQs) that could inform the development of new and improved treatments, interventions, and support for people with DTD.

Methods

Using an adapted Child Health and Nutrition Research Initiative (CHNRI) method, this national prioritisation exercise engaged 60 leading researchers and health care professionals in the UK, as well as 25 wider stakeholders with relevant lived experience to produce a ranked list of priority RQs in DTD. The final list of 99 distinct RQs was independently scored by 42 individuals against a list of five criteria: answerability, effectiveness, impact on health, deliverability, and equity.

Results

Highly ranked RQs covered a range of novel and existing treatments. The three highest scoring RQs included evaluation of psychological and pharmacological therapies (eg, behavioural activation, and augmentation therapies), as well as social interventions to reduce loneliness or increase support for people with DTD.

Conclusions

This exercise identified and prioritised 99 RQs that could inform future research and funding decisions over the next five years. The results of this research could improve treatment and support for people affected by DTD. It also serves as an example of ways in which the CHNRI method can be adapted in a collaborative manner to provide a more active role for patients, carers, and health care professionals.

Mental health prior to and during the COVID-19 pandemic in individuals with bipolar disorder: Insights from prospective longitudinal data

OBJECTIVES

Many studies have examined the impact of COVID-19 on the mental health of the public, but few have focused on individuals with existing severe mental illness with longitudinal data before and during the pandemic.

AIMS

To investigate the impact of the COVID-19 pandemic on the mental health of people with bipolar disorder (BD).

METHODS

In an ongoing study of people with BD who used an online mood monitoring tool, True Colours, 356 participants provided weekly data on their mental health. Symptoms of depression, mania, insomnia, and suicidal thoughts were compared in 2019 and 2020. From May 2020, participants also provided weekly data on the effect of the COVID-19 pandemic on anxiety, coping strategies, access to care, and medications.

RESULTS

On average, symptoms of depression, mania, insomnia, and suicidal thoughts did not significantly differ in 2020 compared to 2019, but there was evidence of heterogeneity. There were high rates of anxiety about the pandemic and its impact on coping strategies, which increased to over 70% of responders in January 2021. A significant proportion of participants reported difficulty accessing routine care (27%) and medications (21%).

CONCLUSIONS

Although mood symptoms did not significantly increase during the pandemic overall, we observed heterogeneity among our BD sample and other impacted areas. Individuals' unique histories and psychosocial circumstances are key and should be explored in future qualitative studies. The significant impacts of the pandemic may take time to manifest, particularly among those who are socioeconomically disadvantaged, highlighting the need for further long-term prospective studies.

Patient-reported Outcomes: the ICHOM Standard Set for Inflammatory Bowel Disease in Real-life Practice Helps Quantify Deficits in Current Care

BACKGROUND

Patient-reported outcome measures [PROMs] are key to documenting outcomes that matter most to patients and are increasingly important to commissioners of health care seeking value. We report the first series of the ICHOM Standard Set for Inflammatory Bowel Disease [IBD].

METHODS

Patients treated for ulcerative colitis [UC] or Crohn's disease [CD] in our centre were offered enrolment into the web-based TrueColours-IBD programme. Through this programme, e-mail prompts linking to validated questionnaires were sent for symptoms, quality of life, and ICHOM IBD outcomes.

RESULTS

The first 1299 consecutive patients enrolled [779 UC, 520 CD] were studied with median 270 days of follow-up (interquartile range [IQR] 116, 504). 671 [52%] were female, mean age 42 years (standard deviation [sd] 16), mean body mass index [BMI] 26 [sd 5.3]. At registration, 483 [37%] were using advanced therapies. Median adherence to fortnightly quality of life reporting and quarterly outcomes was 100% [IQR 48, 100%] and 100% [IQR 75, 100%], respectively. In the previous 12 months, prednisolone use was reported by 229 [29%] patients with UC vs 81 [16%] with CD, p <0.001; 202 [16%] for <3 months; and 108 [8%] for >3 months. An IBD-related intervention was reported by 174 [13%] patients, and 80 [6%] reported an unplanned hospital admission. There were high rates of fatigue [50%] and mood disturbance [23%].

CONCLUSIONS

Outcomes reported by patients illustrate the scale of the therapeutic deficit in current care. Proof of principle is demonstrated that PROM data can be collected continuously with little burden on health care professionals. This may become a metric for quality improvement programmes or to compare outcomes.

Psychosocial markers of age at onset in bipolar disorder: a machine learning approach

BACKGROUND

Bipolar disorder is a chronic and severe mental health disorder. Early stratification of individuals into subgroups based on age at onset (AAO) has the potential to inform diagnosis and early intervention. Yet, the psychosocial predictors associated with AAO are unknown.

AIMS

We aim to identify psychosocial factors associated with bipolar disorder AAO.

METHOD

Using data from the Bipolar Disorder Research Network UK, we employed least absolute shrinkage and selection operator regression to identify psychosocial factors associated with bipolar disorder AAO. Twenty-eight factors were entered into our model, with AAO as our outcome measure.

RESULTS

We included 1022 participants with bipolar disorder (μ = 23.0, s.d. ± 9.86) in our model. Six variables predicted an earlier AAO: childhood abuse (β = -0.2855), regular cannabis use in the year before onset (β = -0.2765), death of a close family friend or relative in the 6 months before onset (β = -0.2435), family history of suicide (β = -0.1385), schizotypal personality traits (β = -0.1055) and irritable temperament (β = -0.0685). Five predicted a later AAO: the average number of alcohol units consumed per week in the year before onset (β = 0.1385); birth of a child in the 6 months before onset (β = 0.2755); death of parent, partner, child or sibling in the 6 months before onset (β = 0.3125); seeking work without success for 1 month or more in the 6 months before onset (β = 0.3505) and a major financial crisis in the 6 months before onset (β = 0.4575).

CONCLUSIONS

The identified predictor variables have the potential to help stratify high-risk individuals into likely AAO groups, to inform treatment provision and early intervention.

Joint patient and clinician priority setting to identify 10 key research questions regarding the long-term sequelae of COVID-19

Given the large numbers of people infected and high rates of ongoing morbidity, research is clearly required to address the needs of adult survivors of COVID-19 living with ongoing symptoms (long COVID). To help direct resource and research efforts, we completed a research prioritisation process incorporating views from adults with ongoing symptoms of COVID-19, carers, clinicians and clinical researchers. The final top 10 research questions were agreed at an independently mediated workshop and included: identifying underlying mechanisms of long COVID, establishing diagnostic tools, understanding trajectory of recovery and evaluating the role of interventions both during the acute and persistent phases of the illness.

Automated virtual reality therapy to treat agoraphobic avoidance and distress in patients with psychosis (gameChange): a multicentre, parallel-group, single-blind, randomised, controlled trial in England with mediation and moderation analyses

BACKGROUND

Automated delivery of psychological therapy using immersive technologies such as virtual reality (VR) might greatly increase the availability of effective help for patients. We aimed to evaluate the efficacy of an automated VR cognitive therapy (gameChange) to treat avoidance and distress in patients with psychosis, and to analyse how and in whom it might work.

METHODS

We did a parallel-group, single-blind, randomised, controlled trial across nine National Health Service trusts in England. Eligible patients were aged 16 years or older, with a clinical diagnosis of a schizophrenia spectrum disorder or an affective diagnosis with psychotic symptoms, and had self-reported difficulties going outside due to anxiety. Patients were randomly assigned (1:1) to either gameChange VR therapy plus usual care or usual care alone, using a permuted blocks algorithm with randomly varying block size, stratified by study site and service type. gameChange VR therapy was provided in approximately six sessions over 6 weeks. Trial assessors were masked to group allocation. Outcomes were assessed at 0, 6 (primary endpoint), and 26 weeks after randomisation. The primary outcome was avoidance of, and distress in, everyday situations, assessed using the self-reported Oxford Agoraphobic Avoidance Scale (O-AS). Outcome analyses were done in the intention-to-treat population (ie, all participants who were assigned to a study group for whom data were available). We performed planned mediation and moderation analyses to test the effects of gameChange VR therapy when added to usual care. This trial is registered with the ISRCTN registry, 17308399.

FINDINGS

Between July 25, 2019, and May 7, 2021 (with a pause in recruitment from March 16, 2020, to Sept 14, 2020, due to COVID-19 pandemic restrictions), 551 patients were assessed for eligibility and 346 were enrolled. 231 (67%) patients were men and 111 (32%) were women, 294 (85%) were White, and the mean age was 37·2 years (SD 12·5). 174 patients were randomly assigned to the gameChange VR therapy group and 172 to the usual care alone group. Compared with the usual care alone group, the gameChange VR therapy group had significant reductions in agoraphobic avoidance (O-AS adjusted mean difference -0·47, 95% CI -0·88 to -0·06; n=320; Cohen's d -0·18; p=0·026) and distress (-4·33, -7·78 to -0·87; n=322; -0·26; p=0·014) at 6 weeks. Reductions in threat cognitions and within-situation defence behaviours mediated treatment outcomes. The greater the severity of anxious fears and avoidance, the greater the treatment benefits. There was no significant difference in the occurrence of serious adverse events between the gameChange VR therapy group (12 events in nine patients) and the usual care alone group (eight events in seven patients; p=0·37).

INTERPRETATION

Automated VR therapy led to significant reductions in anxious avoidance of, and distress in, everyday situations compared with usual care alone. The mediation analysis indicated that the VR therapy worked in accordance with the cognitive model by reducing anxious thoughts and associated protective behaviours. The moderation analysis indicated that the VR therapy particularly benefited patients with severe agoraphobic avoidance, such as not being able to leave the home unaccompanied. gameChange VR therapy has the potential to increase the provision of effective psychological therapy for psychosis, particularly for patients who find it difficult to leave their home, visit local amenities, or use public transport.

FUNDING

National Institute of Health Research Invention for Innovation programme, National Institute of Health Research Oxford Health Biomedical Research Centre.

Clinical- and cost-effectiveness of a technology-supported and solution-focused intervention (DIALOG+) in treatment of patients with chronic depression-study protocol for a multi-site, cluster randomised controlled trial [TACK]

Background

Many with an acute depressive disorder go on to develop chronic depression, despite ongoing care. There are few specifically designed interventions to treat chronic depression. DIALOG+, a technology-assisted intervention based on the principles of solution-focused therapy, may be beneficial. It has been shown to be effective as a treatment for patients with psychotic disorders, especially in regards to increasing quality of life. DIALOG+ was designed to be flexibly applied and not diagnosis-specific, aiming to structure communication and generate a personally-tailored care plan. This cluster randomised controlled trial (RCT) is part of a programme of research to adapt and test DIALOG+ for patients with chronic depression.

Methods

Patients will be eligible for the trial, if they have exhibited symptoms of depression or non-psychotic low mood for at least 2 years, have regular contact with a clinician and have a low subjective quality of life and moderate depressive symptoms. Clinicians, who routinely see eligible patients, will be recruited from a number of sites across NHS England. Clusters will have between 1 and 6 patients per clinician and will be randomised in a 1:1 ratio to either the intervention (DIALOG+) or active control group (treatment as usual + DIALOG scale). Clinicians in the intervention group are trained and asked to deliver the intervention regularly for 12 months. Active control participants receive treatment as usual and are asked to rate their satisfaction with areas of life and treatment on the DIALOG scale at the end of the clinical session. Approximately 112 clinician clusters will be recruited to reach a total patient sample size of 376. Clinical and social outcomes including costs are assessed at baseline and 3, 6 and 12 months post randomisation. The primary outcome will be subjective quality of life at 12 months.

Discussion

This definitive multi-site, cluster RCT aims to evaluate the clinical- and cost-effectiveness of DIALOG+ for people with chronic depression. If shown to be effective for this patient population it could be used to improve outcomes of mental health care on a larger scale, ensuring that patients with complex and co-morbid diagnoses can benefit.

Trial registration

ISRCTN11301686. Registered on 13 Jun 2019.

Cervical lymph nodes and ovarian teratomas as germinal centres in NMDA receptor-antibody encephalitis

Autoantibodies against the extracellular domain of the N-methyl-d-aspartate receptor (NMDAR) NR1 subunit cause a severe and common form of encephalitis. To better understand their generation, we aimed to characterize and identify human germinal centres actively participating in NMDAR-specific autoimmunization by sampling patient blood, CSF, ovarian teratoma tissue and, directly from the putative site of human CNS lymphatic drainage, cervical lymph nodes. From serum, both NR1-IgA and NR1-IgM were detected more frequently in NMDAR-antibody encephalitis patients versus controls (both P < 0.0001). Within patients, ovarian teratoma status was associated with a higher frequency of NR1-IgA positivity in serum (OR = 3.1; P < 0.0001) and CSF (OR = 3.8, P = 0.047), particularly early in disease and before ovarian teratoma resection. Consistent with this immunoglobulin class bias, ovarian teratoma samples showed intratumoral production of both NR1-IgG and NR1-IgA and, by single cell RNA sequencing, contained expanded highly-mutated IgA clones with an ovarian teratoma-restricted B cell population. Multiplex histology suggested tertiary lymphoid architectures in ovarian teratomas with dense B cell foci expressing the germinal centre marker BCL6, CD21+ follicular dendritic cells, and the NR1 subunit, alongside lymphatic vessels and high endothelial vasculature. Cultured teratoma explants and dissociated intratumoral B cells secreted NR1-IgGs in culture. Hence, ovarian teratomas showed structural and functional evidence of NR1-specific germinal centres. On exploring classical secondary lymphoid organs, B cells cultured from cervical lymph nodes of patients with NMDAR-antibody encephalitis produced NR1-IgG in 3/7 cultures, from patients with the highest serum NR1-IgG levels (P < 0.05). By contrast, NR1-IgG secretion was observed neither from cervical lymph nodes in disease controls nor in patients with adequately resected ovarian teratomas. Our multimodal evaluations provide convergent anatomical and functional evidence of NMDAR-autoantibody production from active germinal centres within both intratumoral tertiary lymphoid structures and traditional secondary lymphoid organs, the cervical lymph nodes. Furthermore, we develop a cervical lymph node sampling protocol that can be used to directly explore immune activity in health and disease at this emerging neuroimmune interface.

Commercial Use of Emotion Artificial Intelligence (AI): Implications for Psychiatry

PURPOSE OF REVIEW

Emotion artificial intelligence (AI) is technology for emotion detection and recognition. Emotion AI is expanding rapidly in commercial and government settings outside of medicine, and will increasingly become a routine part of daily life. The goal of this narrative review is to increase awareness both of the widespread use of emotion AI, and of the concerns with commercial use of emotion AI in relation to people with mental illness.

RECENT FINDINGS

This paper discusses emotion AI fundamentals, a general overview of commercial emotion AI outside of medicine, and examples of the use of emotion AI in employee hiring and workplace monitoring. The successful re-integration of patients with mental illness into society must recognize the increasing commercial use of emotion AI. There are concerns that commercial use of emotion AI will increase stigma and discrimination, and have negative consequences in daily life for people with mental illness. Commercial emotion AI algorithm predictions about mental illness should not be treated as medical fact.

Expectations for Artificial Intelligence (AI) in Psychiatry

PURPOSE OF REVIEW

Artificial intelligence (AI) is often presented as a transformative technology for clinical medicine even though the current technology maturity of AI is low. The purpose of this narrative review is to describe the complex reasons for the low technology maturity and set realistic expectations for the safe, routine use of AI in clinical medicine.

RECENT FINDINGS

For AI to be productive in clinical medicine, many diverse factors that contribute to the low maturity level need to be addressed. These include technical problems such as data quality, dataset shift, black-box opacity, validation and regulatory challenges, and human factors such as a lack of education in AI, workflow changes, automation bias, and deskilling. There will also be new and unanticipated safety risks with the introduction of AI. The solutions to these issues are complex and will take time to discover, develop, validate, and implement. However, addressing the many problems in a methodical manner will expedite the safe and beneficial use of AI to augment medical decision making in psychiatry.

Pharmacological treatment for psychotic depression

BACKGROUND

Evidence is limited regarding the most effective pharmacological treatment for psychotic depression: monotherapy with an antidepressant, monotherapy with an antipsychotic, another treatment (e.g. mifepristone), or combination of an antidepressant plus an antipsychotic. This is an update of a review first published in 2005 and last updated in 2015.

OBJECTIVES

1. To compare the clinical efficacy of pharmacological treatments for patients with an acute psychotic depression: antidepressant monotherapy, antipsychotic monotherapy, mifepristone monotherapy, and the combination of an antidepressant plus an antipsychotic versus placebo and/or each other. 2. To assess whether differences in response to treatment in the current episode are related to non-response to prior treatment.

SEARCH METHODS

A search of the Cochrane Central Register of Controlled Trials (CENTRAL), in the Cochrane Library; the Cochrane Common Mental Disorders Controlled Trials Register (CCMDCTR); Ovid MEDLINE (1950-); Embase (1974-); and PsycINFO (1960-) was conducted on 21 February 2020. Reference lists of all included studies and related reviews were screened and key study authors contacted.

SELECTION CRITERIA

All randomised controlled trials (RCTs) that included participants with acute major depression with psychotic features, as well as RCTs consisting of participants with acute major depression with or without psychotic features, that reported separately on the subgroup of participants with psychotic features.

DATA COLLECTION AND ANALYSIS

Two review authors independently extracted data and assessed risk of bias in the included studies, according to criteria from the Cochrane Handbook for Systematic Reviews of Interventions. Data were entered into RevMan 5.1. We used intention-to-treat data. Primary outcomes were clinical response for efficacy and overall dropout rate for harm/tolerance. Secondary outcome were remission of depression, change from baseline severity score, quality of life, and dropout rate due to adverse effects. For dichotomous efficacy outcomes (i.e. response and overall dropout), risk ratios (RRs) with 95% confidence intervals (CIs) were calculated.  Regarding the primary outcome of harm, only overall dropout rates were available for all studies. If the study did not report any of the response criteria as defined above, remission as defined here could be used as an alternative. For continuously distributed outcomes, it was not possible to extract data from the RCTs.  MAIN RESULTS: The search identified 3947 abstracts, but only 12 RCTs with a total of 929 participants could be included in the review. Because of clinical heterogeneity, few meta-analyses were possible. The main outcome was reduction in severity (response) of depression, not of psychosis. For depression response, we found no evidence of a difference between antidepressant and placebo (RR 8.40, 95% CI 0.50 to 142.27; participants = 27, studies = 1; very low-certainty evidence) or between antipsychotic and placebo (RR 1.13, 95% CI 0.74 to 1.73; participants = 201, studies = 2; very low-certainty evidence). Furthermore, we found no evidence of a difference in overall dropouts with antidepressant (RR 1.24, 95% CI 0.34 to 4.51; participants = 27, studies = 1; very low-certainty evidence) or antipsychotic monotherapy (RR 0.79, 95% CI 0.57 to 1.08; participants = 201, studies = 2; very low-certainty evidence). No evidence suggests a difference in depression response (RR 2.09, 95% CI 0.64 to 6.82; participants = 36, studies = 1; very low-certainty evidence) or overall dropouts (RR 1.79, 95% CI 0.18 to 18.02; participants = 36, studies = 1; very low-certainty evidence) between antidepressant and antipsychotic. For depression response, low- to very low-certainty evidence suggests that the combination of an antidepressant plus an antipsychotic may be more effective than antipsychotic monotherapy (RR 1.83, 95% CI 1.40 to 2.38; participants = 447, studies = 4), more effective than antidepressant monotherapy (RR 1.42, 95% CI 1.11 to 1.80; participants = 245, studies = 5), and more effective than placebo (RR 1.86, 95% CI 1.23 to 2.82; participants = 148, studies = 2). Very low-certainty evidence suggests no difference in overall dropouts between the combination of an antidepressant plus an antipsychotic versus antipsychotic monotherapy (RR 0.79, 95% CI 0.63 to 1.01; participants = 447, studies = 4), antidepressant monotherapy (RR 0.91, 95% CI 0.55 to 1.50; participants = 245, studies = 5), or placebo alone (RR 0.75, 95% CI 0.48 to 1.18; participants = 148, studies = 2). No study measured change in depression severity from baseline, quality of life, or dropouts due to adverse events. We found no RCTs with mifepristone that fulfilled our inclusion criteria. Risk of bias is considerable: we noted differences between studies with regards to diagnosis, uncertainties around randomisation and allocation concealment, treatment interventions (pharmacological differences between various antidepressants and antipsychotics), and outcome criteria.

AUTHORS' CONCLUSIONS

Psychotic depression is heavily under-studied, limiting confidence in the conclusions drawn. Some evidence indicates that combination therapy with an antidepressant plus an antipsychotic is more effective than either treatment alone or placebo. Evidence is limited for treatment with an antidepressant alone or with an antipsychotic alone. Evidence for efficacy of mifepristone is lacking.

PAX-D: study protocol for a randomised placebo-controlled trial evaluating the efficacy and mechanism of pramipexole as add-on treatment for people with treatment resistant depression

Introduction

Clinical depression is usually treated in primary care with psychological therapies and antidepressant medication. However, when patients do not respond to at least two or more antidepressants within a depressive episode, they are considered to have treatment resistant depression (TRD). Previous small randomised controlled trials suggested that pramipexole, a dopamine D2/3 receptor agonist, may be effective for treating patients with unipolar and bipolar depression as it is known to influence motivational drive and reward processing. PAX-D will compare the effects of pramipexole vs placebo when added to current antidepressant medication for people with TRD. Additionally, PAX-D will investigate the mechanistic effect of pramipexole on reward sensitivity using a probabilistic decision-making task.

Methods and analysis

PAX-D will assess effectiveness in the short- term (during the first 12 weeks) and in the longer-term (48 weeks) in patients with TRD from the UK. The primary outcome will be change in self-reported depressive symptoms from baseline to week 12 post-randomisation measured using the Quick Inventory of Depressive Symptomatology Self-Report (QIDS-SR16). Performance on the decision-making task will be measured at week 0, week 2 and week 12. Secondary outcomes include anhedonia, anxiety and health economic measures including quality of life, capability, well-being and costs. PAX-D will also assess the adverse effects of pramipexole including impulse control difficulties.

Discussion

Pramipexole is a promising augmentation agent for TRD and may be a useful addition to existing treatment regimes. PAX-D will assess its effectiveness and test for a potential mechanism of action in patients with TRD.

Trial registration number

ISRCTN84666271

Ketamine and other glutamate receptor modulators for depression in adults with bipolar disorder

BACKGROUND

Glutamergic system dysfunction has been implicated in the pathophysiology of bipolar depression. This is an update of the 2015 Cochrane Review for the use of glutamate receptor modulators for depression in bipolar disorder.

OBJECTIVES

1. To assess the effects of ketamine and other glutamate receptor modulators in alleviating the acute symptoms of depression in people with bipolar disorder. 2. To review the acceptability of ketamine and other glutamate receptor modulators in people with bipolar disorder who are experiencing depressive symptoms.

SEARCH METHODS

We searched the Cochrane Central Register of Controlled Trials (CENTRAL), Ovid MEDLINE, Embase and PsycINFO all years to July 2020.  We did not apply any restrictions to date, language or publication status.

SELECTION CRITERIA

RCTs comparing ketamine or other glutamate receptor modulators with other active psychotropic drugs or saline placebo in adults with bipolar depression.

DATA COLLECTION AND ANALYSIS

Two review authors independently selected studies for inclusion, assessed trial quality and extracted data. Primary outcomes were response rate and adverse events. Secondary outcomes included remission rate, depression severity change scores, suicidality, cognition, quality of life, and dropout rate. The GRADE framework was used to assess the certainty of the evidence.

MAIN RESULTS

Ten studies (647 participants) were included in this review (an additional five studies compared to the 2015 review). There were no additional studies added to the comparisons identified in the 2015 Cochrane review on ketamine, memantine and cytidine versus placebo. However, three new comparisons were found: ketamine versus midazolam, N-acetylcysteine versus placebo, and riluzole versus placebo. The glutamate receptor modulators studied were ketamine (three trials), memantine (two), cytidine (one), N-acetylcysteine (three), and riluzole (one). Eight of these studies were placebo-controlled and two-armed. In seven trials the glutamate receptor modulators had been used as add-on drugs to mood stabilisers. Only one trial compared ketamine with an active comparator, midazolam. The treatment period ranged from a single intravenous administration (all ketamine studies), to repeated administration for riluzole, memantine, cytidine, and N-acetylcysteine (with a follow-up of eight weeks, 8 to 12 weeks, 12 weeks, and 16 to 20 weeks, respectively). Six of the studies included sites in the USA, one in Taiwan, one in Denmark, one in Australia, and in one study the location was unclear. All participants had a primary diagnosis of bipolar disorder and were experiencing an acute bipolar depressive episode, diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders fourth edition (IV) or fourth edition text revision (IV-TR). Among all glutamate receptor modulators included in this review, only ketamine appeared to be more efficacious than placebo 24 hours after infusion for response rate (odds ratio (OR) 11.61, 95% confidence interval (CI) 1.25 to 107.74; P = 0.03; participants = 33; studies = 2; I² = 0%, low-certainty evidence). Ketamine seemed to be more effective in reducing depression rating scale scores (MD -11.81, 95% CI -20.01 to -3.61; P = 0.005; participants = 32; studies = 2; I² = 0%, very low-certainty evidence). There was no evidence of ketamine's efficacy in producing remission over placebo at 24 hours (OR 5.16, 95% CI 0.51 to 52.30; P = 0.72; participants = 33; studies = 2; I² = 0%, very low-certainty evidence). Evidence on response, remission or depression rating scale scores between ketamine and midazolam was uncertain at 24 hours due to very low-certainty evidence (OR 3.20, 95% CI 0.23 to 45.19). In the one trial assessing ketamine and midazolam, there were no dropouts due to adverse effects or for any reason (very low-certainty evidence). Placebo may have been more effective than N-acetylcysteine in reducing depression rating scale scores at three months, although this was based on very low-certainty evidence (MD 1.28, 95% CI 0.24 to 2.31; participants = 58; studies = 2). Very uncertain evidence found no difference in response at three months (OR 0.82, 95% CI 0.32 to 2.14; participants = 69; studies = 2; very low-certainty evidence). No data were available for remission or acceptability. Extremely limited data were available for riluzole vs placebo, finding only very-low certainty evidence of no difference in dropout rates (OR 2.00, 95% CI 0.31 to 12.84; P = 0.46; participants = 19; studies = 1; I² = 0%).

AUTHORS' CONCLUSIONS

It is difficult to draw reliable conclusions from this review due to the certainty of the evidence being low to very low, and the relatively small amount of data usable for analysis in bipolar disorder, which is considerably less than the information available for unipolar depression. Nevertheless, we found uncertain evidence in favour of a single intravenous dose of ketamine (as add-on therapy to mood stabilisers) over placebo in terms of response rate up to 24 hours, however ketamine did not show any better efficacy for remission in bipolar depression. Even though ketamine has the potential to have a rapid and transient antidepressant effect, the efficacy of a single intravenous dose may be limited. We did not find conclusive evidence on adverse events with ketamine, and there was insufficient evidence to draw meaningful conclusions for the remaining glutamate receptor modulators. However, ketamine's psychotomimetic effects (such as delusions or delirium) may have compromised study blinding in some studies, and so we cannot rule out the potential bias introduced by inadequate blinding procedures. To draw more robust conclusions, further methodologically sound RCTs (with adequate blinding) are needed to explore different modes of administration of ketamine, and to study different methods of sustaining antidepressant response, such as repeated administrations.

Impact of COVID-19 on telepsychiatry at the service and individual patient level across two UK NHS mental health Trusts

Background

The effects of COVID-19 on the shift to remote consultations remain to be properly investigated.

Objective

To quantify the extent, nature and clinical impact of the use of telepsychiatry during the COVID-19 pandemic and compare it with the data in the same period of the 2 years before the outbreak.

Methods

We used deidentified electronic health records routinely collected from two UK mental health Foundation Trusts (Oxford Health (OHFT) and Southern Health (SHFT)) between January and September in 2018, 2019 and 2020. We considered three outcomes: (1) service activity, (2) in-person versus remote modalities of consultation and (3) clinical outcomes using Health of the Nation Outcome Scales (HoNOS) data. HoNOS data were collected from two cohorts of patients (cohort 1: patients with ≥1 HoNOS assessment each year in 2018, 2019 and 2020; cohort 2: patients with ≥1 HoNOS assessment each year in 2019 and 2020), and analysed in clusters using superclasses (namely, psychotic, non-psychotic and organic), which are used to assess overall healthcare complexity in the National Health Service. All statistical analyses were done in Python.

Findings

Mental health service activity in 2020 increased in all scheduled community appointments (by 15.4% and 5.6% in OHFT and SHFT, respectively). Remote consultations registered a 3.5-fold to 6-fold increase from February to June 2020 (from 4685 to a peak of 26 245 appointments in OHFT and from 7117 to 24 987 appointments in SHFT), with post-lockdown monthly averages of 23 030 and 22 977 remote appointments/month in OHFT and SHFT, respectively. Video consultations comprised up to one-third of total telepsychiatric services per month from April to September 2020. For patients with dementia, non-attendance rates at in-person appointments were higher than remote appointments (17.2% vs 3.9%). The overall HoNOS cluster value increased only in the organic superclass (clusters 18–21, n=174; p<0.001) from 2019 to 2020, suggesting a specific impact of the COVID-19 pandemic on this population of patients.

Conclusions and clinical implications

The rapid shift to remote service delivery has not reached some groups of patients who may require more tailored management with telepsychiatry.

An Investigation of Levetiracetam in Alzheimer's Disease (ILiAD): a double-blind, placebo-controlled, randomised crossover proof of concept study

BACKGROUND

Although Alzheimer's disease affects around 800,000 people in the UK and costs almost £23 billion per year, currently licenced treatments only offer modest benefit at best. Seizures, which are more common in patients with Alzheimer's disease than age matched controls, may contribute to the loss of nerve cells and abnormal brain discharges can disrupt cognition. This aberrant electrical activity may therefore present potentially important drug targets. The anti-seizure medication levetiracetam can reduce abnormal cortical discharges and reverse memory deficits in a mouse model of Alzheimer's disease. Levetiracetam has also been shown to improve memory difficulties in patients with mild cognitive impairment, a precursor to Alzheimer's disease. Clinical use of levetiracetam is well-established in treatment of epilepsy and extensive safety data are available. Levetiracetam thus has the potential to provide safe and efficacious treatment to help with memory difficulties in Alzheimer's disease.

METHODS

The proposed project is a proof of concept study to test whether levetiracetam can help cognitive function in people with dementia. We plan to recruit thirty patients with mild to moderate Alzheimer's disease with no history of previous seizures or other significant co-morbidity. Participants will be allocated to a double-blind placebo-controlled crossover trial that tests levetiracetam against placebo. Standardised scales to assess cognition and a computer-based touchscreen test that we have developed to better detect subtle improvements in hippocampal function will be used to measure changes in memory. All participants will have an electroencephalogram (EEG) at baseline. The primary outcome measure is a change in the computer-based touchscreen cognitive task while secondary outcomes include the effect of levetiracetam on mood, quality of life and modelling of the EEG, including time series measures and feature-based analysis to see whether the effect of levetiracetam can be predicted. The effect of levetiracetam and placebo will be compared within a given patient using the paired t-test and the analysis of covariance adjusting for baseline values.

DISCUSSION

This is the first study to evaluate if an anti-seizure medication can offer meaningful benefit to patients with Alzheimer's disease. If this study demonstrates at least stabilisation of memory function and/or good tolerability, the next step will be to rapidly progress to a larger study to establish whether levetiracetam may be a useful and cost-effective treatment for patients with Alzheimer's disease.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03489044 . Registered on April 5, 2018.

Bipolar disorder: Trimodal age-at-onset distribution

OBJECTIVE

Bipolar disorder (BD) is a chronic mental health disorder with significant morbidity and mortality. Age at onset (AAO) may be a key variable in delineating more homogeneous subgroups of BD patients. However, no known research has systematically assessed how BD age-at-onset subgroups should be defined.

METHODS

We systematically searched the following databases: Cochrane Central Register of Controlled Trials, PsycINFO, MEDLINE, Embase, CINAHL, Scopus, Proquest Dissertations and Theses, Google Scholar and BIOSIS Previews. Original quantitative English language studies investigating AAO in BD were sought.

RESULTS

A total of 9454 unique publications were identified. Twenty-one of these were included in data analysis (n = 22981 BD participants). Fourteen of these studies (67%, n = 13626 participants) found a trimodal AAO distribution: early-onset (µ = 17.3, σ = 1.19, 45% of sample), mid-onset (µ = 26.0, σ = 1.72, 35%), and late-onset (µ = 41.9, σ = 6.16, 20%). Five studies (24%, n = 1422 participants) described a bimodal AAO distribution: early-onset (µ = 24.3, σ = 6.57, 66% of sample) and late-onset (µ = 46.3, σ = 14.15, 34%). Two studies investigated cohort effects on BD AAO and found that when the sample was not split by cohort, a trimodal AAO was the winning model, but when separated by cohort a bimodal distribution fit the data better.

CONCLUSIONS

We propose that the field conceptualises bipolar disorder age-at-onset subgroups as referring broadly to life stages. Demarcating BD AAO groups can inform treatment and provide a framework for future research to continue to investigate potential mechanisms of disease onset.

Internet of things issues related to psychiatry

Background

Internet of Things (IoT) devices for remote monitoring, diagnosis, and treatment are widely viewed as an important future direction for medicine, including for bipolar disorder and other mental illness. The number of smart, connected devices is expanding rapidly. IoT devices are being introduced in all aspects of everyday life, including devices in the home and wearables on the body. IoT devices are increasingly used in psychiatric research, and in the future may help to detect emotional reactions, mood states, stress, and cognitive abilities. This narrative review discusses some of the important fundamental issues related to the rapid growth of IoT devices.

Main body

Articles were searched between December 2019 and February 2020. Topics discussed include background on the growth of IoT, the security, safety and privacy issues related to IoT devices, and the new roles in the IoT economy for manufacturers, patients, and healthcare organizations.

Conclusions

The use of IoT devices will increase throughout psychiatry. The scale, complexity and passive nature of data collection with IoT devices presents unique challenges related to security, privacy and personal safety. While the IoT offers many potential benefits, there are risks associated with IoT devices, and from the connectivity between patients, healthcare providers, and device makers. Security, privacy and personal safety issues related to IoT devices are changing the roles of manufacturers, patients, physicians and healthcare IT organizations. Effective and safe use of IoT devices in psychiatry requires an understanding of these changes.

Introducing artificial intelligence in acute psychiatric inpatient care: qualitative study of its use to conduct nursing observations

Background

All patients admitted to an acute inpatient mental health unit must have nursing observations carried out at night either hourly or every 15 minutes, to ascertain that they are safe and breathing. However, while this practice ensures patient safety, it can also disturb patients’ sleep, which in turn can impact negatively on their recovery.

Objective

This article describes the process of introducing artificial intelligence (‘digitally assisted nursing observations’) in an acute mental health inpatient ward, to enable staff to carry out the hourly and the 15 minutes observations, minimising disruption of patients’ sleep while maintaining their safety.

Findings

The preliminary data obtained indicate that the digitally assisted nursing observations agreed with the observations without sensors when both were carried out in parallel and that over an estimated 755 patient nights, the new system has not been associated with any untoward incidents. Preliminary qualitative data suggest that the new technology improves patients’ and staff’s experience at night.

Discussion

This project suggests that the digitally assisted nursing observations could maintain patients’ safety while potentially improving patients’ and staff’s experience in an acute psychiatric ward. The limitations of this study, namely, its narrative character and the fact that patients were not randomised to the new technology, suggest taking the reported findings as qualitative and preliminary.

Clinical implications

These results suggest that the care provided at night in acute inpatient psychiatric units could be substantially improved with this technology. This warrants a more thorough and stringent evaluation.

Increasing Cybercrime Since the Pandemic: Concerns for Psychiatry

PURPOSE OF REVIEW

Since the pandemic, the daily activities of many people occur at home. People connect to the Internet for work, school, shopping, entertainment, and doctor visits, including psychiatrists. Concurrently, cybercrime has surged worldwide. This narrative review examines the changing use of technology, societal impacts of the pandemic, how cybercrime is evolving, individual vulnerabilities to cybercrime, and special concerns for those with mental illness.

RECENT FINDINGS

Human factors are a central component of cybersecurity as individual behaviors, personality traits, online activities, and attitudes to technology impact vulnerability. Mental illness may increase vulnerability to cybercrime. The risks of cybercrime should be recognized as victims experience long-term psychological and financial consequences. Patients with mental illness may not be aware of the dangers of cybercrime, of risky online behaviors, or the measures to mitigate risk. Technology provides powerful tools for psychiatry but technology must be used with the appropriate safety measures. Psychiatrists should be aware of the potential aftermath of cybercrime on mental health, and the increased patient risk since the pandemic, including from online mental health services. As a first step to increase patient awareness of cybercrime, psychiatrists should provide a recommended list of trusted sources that educate consumers on cybersecurity.