Using digital tools in clinical, health and social care research: a mixed-methods study of UK stakeholders.

OBJECTIVE: The COVID-19 pandemic accelerated changes to clinical research methodology, with clinical studies being carried out via online/remote means. This mixed-methods study aimed to identify which digital tools are currently used across all stages of clinical research by stakeholders in clinical, health and social care research and investigate their experience using digital tools. DESIGN: Two online surveys followed by semistructured interviews were conducted. Interviews were audiorecorded, transcribed and analysed thematically. SETTING, PARTICIPANTS: To explore the digital tools used since the pandemic, survey participants (researchers and related staff (n=41), research and development staff (n=25)), needed to have worked on clinical, health or social care research studies over the past 2 years (2020-2022) in an employing organisation based in the West Midlands region of England (due to funding from a regional clinical research network (CRN)). Survey participants had the opportunity to participate in an online qualitative interview to explore their experiences of digital tools in greater depth (n=8). RESULTS: Six themes were identified in the qualitative interviews: 'definition of a digital tool in clinical research'; 'impact of the COVID-19 pandemic'; 'perceived benefits/drawbacks of digital tools'; 'selection of a digital tool'; 'barriers and overcoming barriers' and 'future digital tool use'. The context of each theme is discussed, based on the interview results. CONCLUSIONS: Findings demonstrate how digital tools are becoming embedded in clinical research, as well as the breadth of tools used across different research stages. The majority of participants viewed the tools positively, noting their ability to enhance research efficiency. Several considerations were highlighted; concerns about digital exclusion; need for collaboration with digital expertise/clinical staff, research on tool effectiveness and recommendations to aid future tool selection. There is a need for the development of resources to help optimise the selection and use of appropriate digital tools for clinical research staff and participants.

Evidence for feasibility of implementing online brief cognitive-behavioral therapy for eating disorder pathology in the workplace.

OBJECTIVE: CBT-T is a brief (10-week) cognitive-behavioral therapy for non-underweight eating disorders. This report describes the findings from a single center, single group, feasibility trial of online CBT-T in the workplace as an alternative to health service settings. METHOD: This trial was approved by the Biomedical and Scientific Research Ethics committee, University of Warwick, UK (reference 125/20-21) and was registered with ISRCTN (reference number: ISRCTN45943700). Recruitment was based on self-reported eating and weight concerns rather than diagnosis, potentially enabling access to treatment for employees who have not previously sought help and for those with sub-threshold eating disorder symptoms. Assessments took place at baseline, mid-treatment (week 4), post-treatment (week 10), and follow-up (1 and 3 months post-treatment). Participant experiences following treatment were assessed using quantitative and qualitative approaches. RESULTS: For the primary outcomes, pre-determined benchmarks of high feasibility and acceptability were met, based on recruiting >40 participants (N = 47), low attrition (38%), and a high attendance rate (98%) over the course of the therapy. Participant experiences revealed low previous help-seeking for eating disorder concerns (21%). Qualitative findings indicated a wide range of positive impacts of the therapy and the workplace as the therapeutic setting. Analysis of secondary outcomes for participants with clinical and sub-threshold eating disorder symptoms showed strong effect sizes for eating pathology, anxiety and depression, and moderate effect sizes for work outcomes. DISCUSSION: These pilot findings provide a strong rationale for a fully powered randomized controlled trial to determine the effectiveness of CBT-T in the workplace. PUBLIC SIGNIFICANCE: This study demonstrates the feasibility of implementing an eating disorders intervention (online CBT-T) in the workplace as an alternative to traditional healthcare settings. Recruitment was based on self-reported eating and weight concerns rather than diagnosis, potentially enabling access to treatment for employees who had not previously sought help. The data also provide insights into recruitment, acceptability, effectiveness, and future viability of CBT-T in the workplace.

Machine learning models to detect anxiety and depression through social media: A scoping review.

Despite improvement in detection rates, the prevalence of mental health disorders such as anxiety and depression are on the rise especially since the outbreak of the COVID-19 pandemic. Symptoms of mental health disorders have been noted and observed on social media forums such Facebook. We explored machine learning models used to detect anxiety and depression through social media. Six bibliographic databases were searched for conducting the review following PRISMA-ScR protocol. We included 54 of 2219 retrieved studies. Users suffering from anxiety or depression were identified in the reviewed studies by screening their online presence and their sharing of diagnosis by patterns in their language and online activity. Majority of the studies (70%, 38/54) were conducted at the peak of the COVID-19 pandemic (2019-2020). The studies made use of social media data from a variety of different platforms to develop predictive models for the detection of depression or anxiety. These included Twitter, Facebook, Instagram, Reddit, Sina Weibo, and a combination of different social sites posts. We report the most common Machine Learning models identified. Identification of those suffering from anxiety and depression disorders may be achieved using prediction models to detect user's language on social media and has the potential to complimenting traditional screening. Such analysis could also provide insights into the mental health of the public especially so when access to health professionals can be restricted due to lockdowns and temporary closure of services such as we saw during the peak of the COVID-19 pandemic.

The performance of artificial intelligence-driven technologies in diagnosing mental disorders: an umbrella review.

Artificial intelligence (AI) has been successfully exploited in diagnosing many mental disorders. Numerous systematic reviews summarize the evidence on the accuracy of AI models in diagnosing different mental disorders. This umbrella review aims to synthesize results of previous systematic reviews on the performance of AI models in diagnosing mental disorders. To identify relevant systematic reviews, we searched 11 electronic databases, checked the reference list of the included reviews, and checked the reviews that cited the included reviews. Two reviewers independently selected the relevant reviews, extracted the data from them, and appraised their quality. We synthesized the extracted data using the narrative approach. We included 15 systematic reviews of 852 citations identified. The included reviews assessed the performance of AI models in diagnosing Alzheimer's disease (n = 7), mild cognitive impairment (n = 6), schizophrenia (n = 3), bipolar disease (n = 2), autism spectrum disorder (n = 1), obsessive-compulsive disorder (n = 1), post-traumatic stress disorder (n = 1), and psychotic disorders (n = 1). The performance of the AI models in diagnosing these mental disorders ranged between 21% and 100%. AI technologies offer great promise in diagnosing mental health disorders. The reported performance metrics paint a vivid picture of a bright future for AI in this field. Healthcare professionals in the field should cautiously and consciously begin to explore the opportunities of AI-based tools for their daily routine. It would also be encouraging to see a greater number of meta-analyses and further systematic reviews on performance of AI models in diagnosing other common mental disorders such as depression and anxiety.

The Effectiveness and Safety of Serious Games for Improving Cognitive Abilities Among Elderly People With Cognitive Impairment: Systematic Review and Meta-Analysis.

BACKGROUND: Cognitive impairment is a mental disorder that commonly affects elderly people. Serious games, which are games that have a purpose other than entertainment, have been used as a nonpharmacological intervention for improving cognitive abilities. The effectiveness and safety of serious games for improving cognitive abilities have been investigated by several systematic reviews; however, they are limited by design and methodological weaknesses. OBJECTIVE: This study aims to assess the effectiveness and safety of serious games for improving cognitive abilities among elderly people with cognitive impairment. METHODS: A systematic review of randomized controlled trials (RCTs) was conducted. The following 8 electronic databases were searched: MEDLINE, Embase, CINAHL, PsycINFO, ACM Digital Library, IEEE Xplore, Scopus, and Google Scholar. We also screened reference lists of the included studies and relevant reviews, as well as checked studies citing our included studies. Two reviewers independently carried out the study selection, data extraction, risk of bias assessment, and quality of evidence appraisal. We used a narrative and statistical approach, as appropriate, to synthesize the results of the included studies. RESULTS: Fifteen studies met the eligibility criteria among 466 citations retrieved. Of those, 14 RCTs were eventually included in the meta-analysis. We found that, regardless of their type, serious games were more effective than no intervention (P=.04) and conventional exercises (P=.002) for improving global cognition among elderly people with cognitive impairment. Further, a subgroup analysis showed that cognitive training games were more effective than no intervention (P=.05) and conventional exercises (P<.001) for improving global cognition among elderly people with cognitive impairment. Another subgroup analysis demonstrated that exergames (a category of serious games that includes physical exercises) are as effective as no intervention and conventional exercises (P=.38) for improving global cognition among elderly people with cognitive impairment. Although some studies found adverse events from using serious games, the number of adverse events (ie, falls and exacerbations of pre-existing arthritis symptoms) was comparable between the serious game and control groups. CONCLUSIONS: Serious games and specifically cognitive training games have the potential to improve global cognition among elderly people with cognitive impairment. However, our findings remain inconclusive because the quality of evidence in all meta-analyses was very low, mainly due to the risk of bias raised in the majority of the included studies, high heterogeneity of the evidence, and imprecision of total effect sizes. Therefore, psychologists, psychiatrists, and patients should consider offering serious games as a complement and not a substitute to existing interventions until further more robust evidence is available. Further studies are needed to assess the effect of exergames, the safety of serious games, and their long-term effects.

A feasibility study of the delivery of online brief cognitive-behavioral therapy (CBT-T) for eating disorder pathology in the workplace.

OBJECTIVE: CBT-T is a brief (10 sessions) version of cognitive behavioral therapy for non-underweight eating disorders. This report describes the protocol for a single center, single group, feasibility trial of online CBT-T in the workplace as an alternative to the health-service setting. By offering mental health services for eating disorders in the workplace, greater accessibility and increased help-seeking behaviors could be achieved. METHOD: Treatment will be delivered online over 10 weeks and offered to employees based on self-referral rather than meeting diagnostic criteria, making treatment available to employees with sub-threshold eating disorder symptoms. RESULTS: Assessments will be conducted at baseline, mid-treatment (week 4), posttreatment (week 10) and at follow-up (1 month and 3 months posttreatment). For the primary outcome, measures will include recruitment, attrition and attendance data using pre-set benchmarks to determine high, medium or low feasibility and acceptability. Qualitative participant experiences data will be analyzed using thematic analysis. Impact on work engagement and effect sizes will be determined from secondary outcome measures; the latter enabling sample size calculations for future study. DISCUSSION: These pilot data will provide insights to recruitment, acceptability, effectiveness and viability of a future fully powered clinical trial of online CBT-T in the workplace. PUBLIC SIGNIFICANCE STATEMENT: This study will present feasibility data from an eating disorders intervention (online CBT-T) using the workplace as an alternative to the healthcare setting to recruit and treat workers. Recruitment will be based on self-reported eating and weight concerns rather than diagnosis potentially enabling treatment to employees who have not previously sought help. The data will also provide insights to recruitment, acceptability, effectiveness, and future viability of CBT-T in the workplace.

Active HHV-6 Infection of Cerebellar Purkinje Cells in Mood Disorders.

Early-life infections and associated neuroinflammation is incriminated in the pathogenesis of various mood disorders. Infection with human roseoloviruses, HHV-6A and HHV-6B, allows viral latency in the central nervous system and other tissues, which can later be activated causing cognitive and behavioral disturbances. Hence, this study was designed to evaluate possible association of HHV-6A and HHV-6B activation with three different groups of psychiatric patients. DNA qPCR, immunofluorescence and FISH studies were carried out in post-mortem posterior cerebellum from 50 cases each of bipolar disorder (BPD), schizophrenia, 15 major depressive disorder (MDD) and 50 appropriate control samples obtained from two well-known brain collections (Stanley Medical Research Institute). HHV-6A and HHV-6B late proteins (indicating active infection) and viral DNA were detected more frequently (p < 0.001 for each virus) in human cerebellum in MDD and BPD relative to controls. These roseolovirus proteins and DNA were found less frequently in schizophrenia cases. Active HHV-6A and HHV-6B infection in cerebellar Purkinje cells were detected frequently in BPD and MDD cases. Furthermore, we found a significant association of HHV-6A infection with reduced Purkinje cell size, suggesting virus-mediated abnormal Purkinje cell function in these disorders. Finally, gene expression analysis of cerebellar tissue revealed changes in pathways reflecting an inflammatory response possibly to HHV-6A infection. Our results provide molecular evidence to support a role for active HHV-6A and HHV-6B infection in BPD and MDD.

Glial fibrillary acidic protein and glutamine synthetase in subregions of prefrontal cortex in schizophrenia and mood disorder.

Several theories of schizophrenia suggest dysfunction in glutamate neurotransmission in higher brain regions such as the prefrontal cortex (PFC). Previous studies have investigated whether astroglial abnormalities could give rise to glutamate dysfunction using glial fibrillary acidic protein (GFAP) immunocytochemistry. We have used quantitative immunoautoradiography to measure glutamine synthetase (GS), the glial enzyme which recycles synaptic glutamate, as a more direct test of glial mechanisms of abnormal glutamate function in schizophrenia. We compared GS with GFAP immunoautoradiography in dorsolateral (area 9) and orbitofrontal (area 11/47) cortex. Optical density measures from film autoradiographs revealed an increase in GFAP immunoreactivity in area 9 in schizophrenia and a decrease in area 11/47 in both schizophrenia and bipolar disorder. The increase in GFAP in area 9 significantly correlated with lifetime antipsychotic drug treatment, whereas the reduction in area 11/47 occurred despite this effect. There were no changes in GS immunoreactivity in any psychiatric disorder. Regional and antigen-specific down-regulation of GFAP protein in OFC in schizophrenia and bipolar disorder may relate to disease mechanisms of psychosis.