Unravelling the influence of affective stimulation on functional neurological symptoms: a pilot experiment examining potential mechanisms.

BACKGROUND: Differences in affective processing have previously been shown in functional neurological disorder (FND); however, the mechanistic relevance is uncertain. We tested the hypotheses that highly arousing affective stimulation would result in elevated subjective functional neurological symptoms (FNS), and this would be associated with elevated autonomic reactivity. The possible influence of cognitive detachment was also explored. METHOD: Individuals diagnosed with FND (motor symptoms/seizures; n=14) and healthy controls (n=14) viewed Positive, Negative and Neutral images in blocks, while passively observing the stimuli ('Watch') or detaching themselves ('Distance'). The FND group rated their primary FNS, and all participants rated subjective physical (arousal, pain, fatigue) and psychological states (positive/negative affect, dissociation), immediately after each block. Skin conductance (SC) and heart rate (HR) were monitored continuously. RESULTS: FNS ratings were higher after Negative compared with Positive and Neutral blocks in the FND group (p=0.002, ηp 2=0.386); however, this effect was diminished in the Distance condition relative to the Watch condition (p=0.018, ηp 2=0.267). SC and/or HR correlated with FNS ratings in the Negative-Watch and Neutral-Distance conditions (r values=0.527-0.672, p values=0.006-0.035). The groups did not differ in subjective affect or perceived arousal (p values=0.541-0.919, ηp 2=<0.001-0.015). CONCLUSIONS: Emotionally significant events may exert an influence on FNS which is related to autonomic activation rather than altered subjective affect or perceived arousal. This influence may be modulated by cognitive detachment. Further work is needed to determine the relevance and neural bases of these processes in specific FND phenotypes.

Long term mortality trends in people with severe mental illnesses and how COVID-19, ethnicity and other chronic mental health comorbidities contributed: a retrospective cohort study.

BACKGROUND: People with schizophrenia-spectrum and bipolar disorders (severe mental illnesses; 'SMI') experience excess mortality. Our aim was to explore longer-term trends in mortality, including the COVID-19 pandemic period, with a focus on additional vulnerabilities (psychiatric comorbidities and race/ ethnicity) in SMI. METHODS: Retrospective cohort study using electronic health records from secondary mental healthcare, covering a UK region of 1.3 million people. Mortality trends spanning fourteen years, including the COVID-19 pandemic, were assessed in adults with clinician-ascribed ICD-10 diagnoses for schizophrenia-spectrum and bipolar disorders. RESULTS: The sample comprised 22 361 people with SMI with median follow-up of 10.6 years. Standardized mortality ratios were more than double the population average pre-pandemic, increasing further during the pandemic, particularly in those with SMI and psychiatric comorbidities. Mortality risk increased steadily among people with SMI and comorbid depression, dementia, substance use disorders and anxiety over 13-years, increasing further during the pandemic. COVID-19 mortality was elevated in people with SMI and comorbid depression (sub-Hazard Ratio: 1.48 [95% CI 1.03-2.13]), dementia (sHR:1.96, 1.26-3.04) and learning disabilities (sHR:2.30, 1.30-4.06), compared to people with only SMI. COVID-19 mortality risk was similar for minority ethnic groups and White British people with SMI. Elevated all-cause mortality was evident in Black Caribbean (adjusted Rate Ratio: 1.40, 1.11-1.77) and Black African people with SMI (aRR: 1.59, 1.07-2.37) during the pandemic relative to earlier years. CONCLUSIONS: Mortality has increased over time in people with SMI. The pandemic exacerbated pre-existing trends. Actionable solutions are needed which address wider social determinants and address disease silos.

Interventions targeting social determinants of mental disorders and the Sustainable Development Goals: a systematic review of reviews.

Globally, mental disorders account for almost 20% of disease burden and there is growing evidence that mental disorders are socially determined. Tackling the United Nations Sustainable Development Goals (UN SDGs), which address social determinants of mental disorders, may be an effective way to reduce the global burden of mental disorders. We conducted a systematic review of reviews to examine the evidence base for interventions that map onto the UN SDGs and seek to improve mental health through targeting known social determinants of mental disorders. We included 101 reviews in the final review, covering demographic, economic, environmental events, neighborhood, and sociocultural domains. This review presents interventions with the strongest evidence base for the prevention of mental disorders and highlights synergies where addressing the UN SDGs can be beneficial for mental health.

Frequency of Consumption of Food Groups and Cardio-Metabolic Risk Factors: A Genetically Informative Twin Study in Sri Lanka.

Low- and middle-income countries (LMICs) globally have undergone rapid urbanisation, and changes in demography and health behaviours. In Sri Lanka, cardio-vascular disease and diabetes are now leading causes of mortality. High prevalence of their risk factors, including hypertension, dysglycaemia and obesity have also been observed. Diet is a key modifiable risk factor for both cardio-vascular disease and diabetes as well as their risk factors. Although typically thought of as an environmental risk factor, dietary choice has been shown to be genetically influenced, and genes associated with this behaviour correlate with metabolic risk indicators. We used Structural Equation Model fitting to investigate the aetiology of dietary choices and cardio-metabolic phenotypes in COTASS, a population-based twin and singleton sample in Colombo, Sri Lanka. Participants completed a Food Frequency Questionnaire (N = 3934) which assessed frequency of intake of 14 food groups including meat, vegetables and dessert or sweet snacks. Anthropometric (N = 3675) and cardio-metabolic (N = 3477) phenotypes were also collected including weight, blood pressure, cholesterol, fasting plasma glucose and triglycerides. Frequency of consumption of most food items was found to be largely environmental in origin with both the shared and non-shared environmental influences indicated. Modest genetic influences were observed for some food groups (e.g. fruits and leafy greens). Cardio-metabolic phenotypes showed moderate genetic influences with some shared environmental influence for Body Mass Index, blood pressure and triglycerides. Overall, it seemed that shared environmental effects were more important for both dietary choices and cardio-metabolic phenotypes compared to populations in the Global North.

A wearable device perspective on the standard definitions of disability progression in multiple sclerosis.

INTRODUCTION: Multiple sclerosis (MS) is a leading cause of disability among young adults, but standard clinical scales may not accurately detect subtle changes in disability occurring between visits. This study aims to explore whether wearable device data provides more granular and objective measures of disability progression in MS. METHODS: Remote Assessment of Disease and Relapse in Central Nervous System Disorders (RADAR-CNS) is a longitudinal multicenter observational study in which 400 MS patients have been recruited since June 2018 and prospectively followed up for 24 months. Monitoring of patients included standard clinical visits with assessment of disability through use of the Expanded Disability Status Scale (EDSS), 6-minute walking test (6MWT) and timed 25-foot walk (T25FW), as well as remote monitoring through the use of a Fitbit. RESULTS: Among the 306 patients who completed the study (mean age, 45.6 years; females 67%), confirmed disability progression defined by the EDSS was observed in 74 patients, who had approximately 1392 fewer daily steps than patients without disability progression. However, the decrease in the number of steps experienced over time by patients with EDSS progression and stable patients was not significantly different. Similar results were obtained with disability progression defined by the 6MWT and the T25FW. CONCLUSION: The use of continuous activity monitoring holds great promise as a sensitive and ecologically valid measure of disability progression in MS.

Etiological Factors and Symptom Triggers in Functional Motor Symptoms and Functional Seizures: A Pilot Investigation.

OBJECTIVE: This study examined etiological factors and symptom triggers of functional motor symptoms (FMS) or functional seizures (FS) and assessed potential relationships with relevant clinical features (i.e., functional symptoms, quality of life, and general functioning). METHODS: Seventeen participants with FMS or FS and 17 healthy control participants underwent an in-depth clinical interview and completed questionnaires assessing adverse life events, psychological and physical symptoms, alexithymia, autistic traits, illness perceptions, health-related quality of life (HRQoL), and work and social functioning. RESULTS: Participants with FMS or FS perceived various causes of the disorder, including physical symptoms (65%), emotional problems (53%), adverse life events (47%), and work-related factors (29%). Triggers of FMS and FS included physical activity or exertion (59%), stress and emotions (59%), sensory experiences (47%), and fatigue (41%). Compared with healthy control participants, participants with FMS or FS reported more adverse events during adolescence and higher levels of alexithymia, somatoform dissociation, psychological dissociation (disengagement, depersonalization, and derealization), anxiety, depression, and physical symptoms. Participants with FMS or FS had worse HRQoL than healthy control participants and impaired work and social functioning. There were inverse associations between HRQoL scores and somatoform dissociation, anxiety, and adverse life events. CONCLUSIONS: Participants with FMS or FS reported diverse biopsychosocial etiological factors and symptom triggers. Ongoing psychological symptoms and lifetime adverse experiences were associated with worse HRQoL. Future studies will examine these factors in larger samples of individuals with FMS or FS to better understand their shared and distinct etiological underpinnings.

Data Visualization Preferences in Remote Measurement Technology for Individuals Living With Depression, Epilepsy, and Multiple Sclerosis: Qualitative Study.

BACKGROUND: Remote measurement technology (RMT) involves the use of wearable devices and smartphone apps to measure health outcomes in everyday life. RMT with feedback in the form of data visual representations can facilitate self-management of chronic health conditions, promote health care engagement, and present opportunities for intervention. Studies to date focus broadly on multiple dimensions of service users' design preferences and RMT user experiences (eg, health variables of perceived importance and perceived quality of medical advice provided) as opposed to data visualization preferences. OBJECTIVE: This study aims to explore data visualization preferences and priorities in RMT, with individuals living with depression, those with epilepsy, and those with multiple sclerosis (MS). METHODS: A triangulated qualitative study comparing and thematically synthesizing focus group discussions with user reviews of existing self-management apps and a systematic review of RMT data visualization preferences. A total of 45 people participated in 6 focus groups across the 3 health conditions (depression, n=17; epilepsy, n=11; and MS, n=17). RESULTS: Thematic analysis validated a major theme around design preferences and recommendations and identified a further four minor themes: (1) data reporting, (2) impact of visualization, (3) moderators of visualization preferences, and (4) system-related factors and features. CONCLUSIONS: When used effectively, data visualizations are valuable, engaging components of RMT. Easy to use and intuitive data visualization design was lauded by individuals with neurological and psychiatric conditions. Apps design needs to consider the unique requirements of service users. Overall, this study offers RMT developers a comprehensive outline of the data visualization preferences of individuals living with depression, epilepsy, and MS.

Longitudinal Assessment of Seasonal Impacts and Depression Associations on Circadian Rhythm Using Multimodal Wearable Sensing: Retrospective Analysis.

BACKGROUND: Previous mobile health (mHealth) studies have revealed significant links between depression and circadian rhythm features measured via wearables. However, the comprehensive impact of seasonal variations was not fully considered in these studies, potentially biasing interpretations in real-world settings. OBJECTIVE: This study aims to explore the associations between depression severity and wearable-measured circadian rhythms while accounting for seasonal impacts. METHODS: Data were sourced from a large longitudinal mHealth study, wherein participants' depression severity was assessed biweekly using the 8-item Patient Health Questionnaire (PHQ-8), and participants' behaviors, including sleep, step count, and heart rate (HR), were tracked via Fitbit devices for up to 2 years. We extracted 12 circadian rhythm features from the 14-day Fitbit data preceding each PHQ-8 assessment, including cosinor variables, such as HR peak timing (HR acrophase), and nonparametric features, such as the onset of the most active continuous 10-hour period (M10 onset). To investigate the association between depression severity and circadian rhythms while also assessing the seasonal impacts, we used three nested linear mixed-effects models for each circadian rhythm feature: (1) incorporating the PHQ-8 score as an independent variable, (2) adding seasonality, and (3) adding an interaction term between season and the PHQ-8 score. RESULTS: Analyzing 10,018 PHQ-8 records alongside Fitbit data from 543 participants (n=414, 76.2% female; median age 48, IQR 32-58 years), we found that after adjusting for seasonal effects, higher PHQ-8 scores were associated with reduced daily steps (ß=-93.61, P<.001), increased sleep variability (ß=0.96, P<.001), and delayed circadian rhythms (ie, sleep onset: ß=0.55, P=.001; sleep offset: ß=1.12, P<.001; M10 onset: ß=0.73, P=.003; HR acrophase: ß=0.71, P=.001). Notably, the negative association with daily steps was more pronounced in spring (ß of PHQ-8 × spring = -31.51, P=.002) and summer (ß of PHQ-8 × summer = -42.61, P<.001) compared with winter. Additionally, the significant correlation with delayed M10 onset was observed solely in summer (ß of PHQ-8 × summer = 1.06, P=.008). Moreover, compared with winter, participants experienced a shorter sleep duration by 16.6 minutes, an increase in daily steps by 394.5, a delay in M10 onset by 20.5 minutes, and a delay in HR peak time by 67.9 minutes during summer. CONCLUSIONS: Our findings highlight significant seasonal influences on human circadian rhythms and their associations with depression, underscoring the importance of considering seasonal variations in mHealth research for real-world applications. This study also indicates the potential of wearable-measured circadian rhythms as digital biomarkers for depression.

Severe mental illness, race/ethnicity, multimorbidity and mortality following COVID-19 infection: nationally representative cohort study.

BACKGROUND: The association of COVID-19 with death in people with severe mental illness (SMI), and associations with multimorbidity and ethnicity, are unclear. AIMS: To determine all-cause mortality in people with SMI following COVID-19 infection, and assess whether excess mortality is affected by multimorbidity or ethnicity. METHOD: This was a retrospective cohort study using primary care data from the Clinical Practice Research Database, from February 2020 to April 2021. Cox proportional hazards regression was used to estimate the effect of SMI on all-cause mortality during the first two waves of the COVID-19 pandemic. RESULTS: Among 7146 people with SMI (56% female), there was a higher prevalence of multimorbidity compared with the non-SMI control group (n = 653 024, 55% female). Following COVID-19 infection, the SMI group experienced a greater risk of death compared with controls (adjusted hazard ratio (aHR) 1.53, 95% CI 1.39-1.68). Black Caribbean/Black African people were more likely to die from COVID-19 compared with White people (aHR = 1.22, 95% CI 1.12-1.34), with similar associations in the SMI group and non-SMI group (P for interaction = 0.73). Following infection with COVID-19, for every additional multimorbidity condition, the aHR for death was 1.06 (95% CI 1.01-1.10) in the SMI stratum and 1.16 (95% CI 1.15-1.17) in the non-SMI stratum (P for interaction = 0.001). CONCLUSIONS: Following COVID-19 infection, patients with SMI were at an elevated risk of death, further magnified by multimorbidity. Black Caribbean/Black African people had a higher risk of death from COVID-19 than White people, and this inequity was similar for the SMI group and the control group.

Ethnic differences in physical and mental multimorbidity in working age adults with a history of depression and/or anxiety.

BACKGROUND: The current study used data from an ethnically diverse population from South London to examine ethnic differences in physical and mental multimorbidity among working age (18-64 years) adults in the context of depression and anxiety. METHOD: The study included 44 506 patients who had previously attended Improving Access to Psychological Therapies services in the London Borough of Lambeth. Multinomial logistic regression examined cross-sectional associations between ethnicity with physical and mental multimorbidity. Patterns of multimorbidity were identified using hierarchical cluster analysis. RESULTS: Within 44 056 working age adults with a history of depression or anxiety from South London there were notable ethnic differences in physical multimorbidity. Adults of Black Caribbean ethnicity were more likely to have physical multimorbidity [adjusted relative risk ratio (aRRR) = 1.25, 95% confidence interval (CI) 1.15-1.36] compared to adults of White ethnicity. Relative to adults of White ethnicity, adults of Asian ethnicity were more likely to have physical multimorbidity at higher thresholds only (e.g. 4 + conditions; aRRR = 1.53, 95% CI 1.17-2.00). Three physical (atopic, cardiometabolic, mixed) and three mental (alcohol/substance use, common/severe mental illnesses, personality disorder) multimorbidity clusters emerged. Ethnic minority groups with multimorbidity had a higher probability of belonging to the cardiometabolic cluster. CONCLUSION: In an ethnically diverse population with a history of common mental health disorders, we found substantial between- and within-ethnicity variation in rates of physical, but not mental, multimorbidity. The findings emphasised the value of more granular definitions of ethnicity when examining the burden of physical and mental multimorbidity.

Risk and protective factors for new-onset binge eating, low weight, and self-harm symptoms in >35,000 individuals in the UK during the COVID-19 pandemic.

OBJECTIVE: The disruption caused by the COVID-19 pandemic has been associated with poor mental health, including increases in eating disorders and self-harm symptoms. We investigated risk and protective factors for the new onset of these symptoms during the pandemic. METHOD: Data were from the COVID-19 Psychiatry and Neurological Genetics study and the Repeated Assessment of Mental health in Pandemics Study (n = 36,715). Exposures were socio-demographic characteristics, lifetime psychiatric disorder, and COVID-related variables, including SARS-CoV-2 infection/illness with COVID-19. We identified four subsamples of participants without pre-pandemic experience of our outcomes: binge eating (n = 24,211), low weight (n = 24,364), suicidal and/or self-harm ideation (n = 18,040), and self-harm (n = 29,948). Participants reported on our outcomes at frequent intervals (fortnightly to monthly). We fitted multiple logistic regression models to identify factors associated with the new onset of our outcomes. RESULTS: Within each subsample, new onset was reported by: 21% for binge eating, 10.8% for low weight, 23.5% for suicidal and/or self-harm ideation, and 3.5% for self-harm. Shared risk factors included having a lifetime psychiatric disorder, not being in paid employment, higher pandemic worry scores, and being racially minoritized. Conversely, infection with SARS-CoV-2/illness with COVID-19 was linked to lower odds of binge eating, low weight, and suicidal and/or self-harm ideation. DISCUSSION: Overall, we detected shared risk factors that may drive the comorbidity between eating disorders and self-harm. Subgroups of individuals with these risk factors may require more frequent monitoring during future pandemics. PUBLIC SIGNIFICANCE: In a sample of 35,000 UK residents, people who had a psychiatric disorder, identified as being part of a racially minoritized group, were not in paid employment, or were more worried about the pandemic were more likely to experience binge eating, low weight, suicidal and/or self-harm ideation, and self-harm for the first time during the pandemic. People with these risk factors may need particular attention during future pandemics to enable early identification of new psychiatric symptoms.

The United Kingdom Eating Disorders Genetics Initiative.

OBJECTIVE: The United Kingdom Eating Disorders Genetics Initiative (EDGI UK), part of the National Institute for Health and Care Research (NIHR) Mental Health BioResource, aims to deepen our understanding of the environmental and genetic etiology of eating disorders. EDGI UK launched in February 2020 and is partnered with the UK eating disorders charity, Beat. Multiple EDGI branches exist worldwide. This article serves the dual function of providing an in-depth description of our study protocol and of describing our initial sample including demographics, diagnoses, and physical and psychiatric comorbidities. METHOD: EDGI UK recruits via media and clinical services. Anyone living in England, at least 16 years old, with a lifetime probable or clinical eating disorder is eligible to sign up online: edgiuk.org. Participants complete online questionnaires, donate a saliva sample for genetic analysis, and consent to medical record linkage and recontact for future studies. RESULTS: As of September 2022, EDGI UK recruited 7435 survey participants: 98% female, 93.1% white, 97.8% cisgender, 65.9% heterosexual, and 52.1% have a university degree. Over half (57.8%) of these participants have returned their saliva DNA kit. The most common diagnoses are anorexia nervosa (48.3%), purging disorder (37.8%), bulimia nervosa (37.5%), binge-eating disorder (15.8%), and atypical anorexia nervosa (7.8%). CONCLUSION: EDGI UK is the largest UK eating disorders study and efforts to increase its diversity are underway. It offers a unique opportunity to accelerate eating disorder research. Researchers and participants with lived experience can collaborate on projects with unparalleled sample size. PUBLIC SIGNIFICANCE STATEMENT: Eating disorders are debilitating and costly for society but are under-researched due to underfunding. EDGI UK is one of the largest eating disorder studies worldwide with ongoing recruitment. The collected data constitute a resource for secondary analysis. We will combine data from all international EDGI branches and the NIHR BioResource to facilitate research that improves our understanding of eating disorders and their comorbidities.

Sociodemographic, mental health, and physical health factors associated with participation within re-contactable mental health cohorts: an investigation of the GLAD Study.

BACKGROUND: The Genetic Links to Anxiety and Depression (GLAD) Study is a large cohort of individuals with lifetime anxiety and/or depression, designed to facilitate re-contact of participants for mental health research. At the start of the pandemic, participants from three cohorts, including the GLAD Study, were invited to join the COVID-19 Psychiatry and Neurological Genetics (COPING) study to monitor mental and neurological health. However, previous research suggests that participation in longitudinal studies follows a systematic, rather than random, process, which can ultimately bias results. Therefore, this study assessed participation biases following the re-contact of GLAD Study participants. METHODS: In April 2020, all current GLAD Study participants (N = 36,770) were invited to the COPING study. Using logistic regression, we investigated whether sociodemographic, mental, and physical health characteristics were associated with participation in the COPING baseline survey (aim one). Subsequently, we used a zero-inflated negative binomial regression to examine whether these factors were also related to participation in the COPING follow-up surveys (aim two). RESULTS: For aim one, older age, female gender identity, non-binary or self-defined gender identities, having one or more physical health disorders, and providing a saliva kit for the GLAD Study were associated with an increased odds of completing the COPING baseline survey. In contrast, lower educational attainment, Asian or Asian British ethnic identity, Black or Black British ethnic identity, higher alcohol consumption at the GLAD sign-up survey, and current or ex-smoking were associated with a reduced odds. For aim two, older age, female gender, and saliva kit provision were associated with greater COPING follow-up survey completion. Lower educational attainment, higher alcohol consumption at the GLAD Study sign-up, ex-smoking, and self-reported attention deficit hyperactivity disorder had negative relationships. CONCLUSIONS: Participation biases surrounding sociodemographic and physical health characteristics were particularly evident when re-contacting the GLAD Study volunteers. Factors associated with participation may vary depending on study design. Researchers should examine the barriers and mechanisms underlying participation bias in order to combat these issues and address recruitment biases in future studies.

A qualitative exploration of the psychosocial needs of people living with long-term conditions and their perspectives on online peer support.

INTRODUCTION: Approximately 20% of people with a long-term condition (LTC) experience depressive symptoms (subthreshold depression [SUBD]). People with SUBD experience depressive symptoms that do not meet the diagnostic criteria for major depressive disorder. However, there is currently no targeted psychological support for people with LTCs also experiencing SUBD. Online peer support is accessible, inexpensive and scalable, and might offer a way of bridging the gap in psychosocial care for LTC patients. This article explores the psychosocial needs of people living with LTCs and investigates their perspectives on online peer support interventions to inform their future design. METHODS: Through a co-produced participatory approach, online focus groups were completed with people with lived experience of LTCs. Focus groups were audio recorded and transcribed verbatim. Reflexive thematic analysis (TA) was conducted adopting a critical-realist approach and an inductive analysis methodology that sought to follow participants' priorities and concerns. RESULTS: Ten people with a range of LTCs participated across three online focus groups, lasting an average of 95 (±10.1) min. The mean age was 57 (±11.4) years and 60% of participants identified as female. The three key emerging themes were: (1) relationship between self and outside world; (2) past experiences of peer support; and (3) philosophy and vision of peer support. Adults living with LTCs shared their past experiences of peer support and explored their perspectives on how future online peer support platforms may support their psychosocial needs. CONCLUSION: Despite the negative impact(s) of having a long-term physical health condition on mental health, physical and mental healthcare are often treated as separate entities. The need for an integrated approach for people with LTCs was clear. Implementation of online peer support to bridge this gap was supported, but there was a clear consensus that these interventions need to be co-produced and carefully designed to ensure they feel safe and not commercialised or prescriptive. Shared explorations of the potential benefits and concerns of these online spaces can shape the philosophy and vision of future platforms. PATIENT OR PUBLIC CONTRIBUTION: This work is set within a wider project which is developing an online peer support platform for those living with LTCs. A participatory, co-produced approach is integral to this work. The initial vision was steered by the experiences of our Patient and Public Involvement (PPI) groups, who emphasised the therapeutic value of peer-to-peer interaction. The focus groups confirmed the importance and potential benefit of this project. This paper represents the perspectives of PPI members who collaborate on research and public engagement at the mental-physical interface. A separate, independent Research Advisory Group (RAG), formed of members also living with LTCs, co-produced study documents, topic guides, and informed key decision-making processes. Finally, our co-investigator with lived experience (E. A.F.) undertook the analysis and write-up alongside colleagues, further strengthening the interpretation and resonance of our work. She shares first joint authorship, and as a core member of the research team, ensures that the conduct of the study is firmly grounded in the experience of people living with LTCs.

Sex differences in experiences of multiple traumas and mental health problems in the UK Biobank cohort.

PURPOSE: Experiences of reported trauma are common and are associated with a range of mental health problems. Sex differences in how reported traumas are experienced over the life course in relation to mental health require further exploration. METHODS: 157,358 participants contributed data for the UK Biobank Mental Health Questionnaire (MHQ). Stratified Latent Class Analysis (LCA) was used to analyse combinations of reported traumatic experiences in males and females separately, and associations with mental health. RESULTS: In females, five trauma classes were identified: a low-risk class (58.6%), a childhood trauma class (13.5%), an intimate partner violence class (12.9%), a sexual violence class (9.1%), and a high-risk class (5.9%). In males, a three-class solution was preferred: a low-risk class (72.6%), a physical and emotional trauma class (21.9%), and a sexual violence class (5.5%). In comparison to the low-risk class in each sex, all trauma classes were associated with increased odds of current depression, anxiety, and hazardous/harmful alcohol use after adjustment for covariates. The high-risk class in females and the sexual violence class in males produced significantly increased odds for recent psychotic experiences. CONCLUSION: There are sex differences in how reported traumatic experiences co-occur across a lifespan, with females at the greatest risk. However, reporting either sexual violence or multiple types of trauma was associated with increased odds of mental health problems for both males and females. Findings emphasise the public mental health importance of identifying and responding to both men and women's experiences of trauma, including sexual violence.

Challenges in Using mHealth Data From Smartphones and Wearable Devices to Predict Depression Symptom Severity: Retrospective Analysis.

BACKGROUND: Major depressive disorder (MDD) affects millions of people worldwide, but timely treatment is not often received owing in part to inaccurate subjective recall and variability in the symptom course. Objective and frequent MDD monitoring can improve subjective recall and help to guide treatment selection. Attempts have been made, with varying degrees of success, to explore the relationship between the measures of depression and passive digital phenotypes (features) extracted from smartphones and wearables devices to remotely and continuously monitor changes in symptomatology. However, a number of challenges exist for the analysis of these data. These include maintaining participant engagement over extended time periods and therefore understanding what constitutes an acceptable threshold of missing data; distinguishing between the cross-sectional and longitudinal relationships for different features to determine their utility in tracking within-individual longitudinal variation or screening individuals at high risk; and understanding the heterogeneity with which depression manifests itself in behavioral patterns quantified by the passive features. OBJECTIVE: We aimed to address these 3 challenges to inform future work in stratified analyses. METHODS: Using smartphone and wearable data collected from 479 participants with MDD, we extracted 21 features capturing mobility, sleep, and smartphone use. We investigated the impact of the number of days of available data on feature quality using the intraclass correlation coefficient and Bland-Altman analysis. We then examined the nature of the correlation between the 8-item Patient Health Questionnaire (PHQ-8) depression scale (measured every 14 days) and the features using the individual-mean correlation, repeated measures correlation, and linear mixed effects model. Furthermore, we stratified the participants based on their behavioral difference, quantified by the features, between periods of high (depression) and low (no depression) PHQ-8 scores using the Gaussian mixture model. RESULTS: We demonstrated that at least 8 (range 2-12) days were needed for reliable calculation of most of the features in the 14-day time window. We observed that features such as sleep onset time correlated better with PHQ-8 scores cross-sectionally than longitudinally, whereas features such as wakefulness after sleep onset correlated well with PHQ-8 longitudinally but worse cross-sectionally. Finally, we found that participants could be separated into 3 distinct clusters according to their behavioral difference between periods of depression and periods of no depression. CONCLUSIONS: This work contributes to our understanding of how these mobile health-derived features are associated with depression symptom severity to inform future work in stratified analyses.

Physical multimorbidity, depressive symptoms, and social participation in adults over 50 years of age: findings from the English Longitudinal Study of Ageing.

OBJECTIVES: The aim of the current study was to identify specific patterns of physical multimorbidity and examine how these patterns associated with changes in social participation over time. METHODS: We used latent class analysis to identify clusters of physical multimorbidity in 11,391 older adults. Mixed effects regression models were used to assess associations between physical multimorbidity clusters and changes in social participation over 15 years. RESULTS: Four clusters of physical multimorbidity were identified. All physical multimorbidity clusters were associated with a reduction in cultural engagement (e.g. visits to theatre, cinema, museums) over time, with the strongest association seen in the complex/multisystem cluster (ß = -0.26, 95% CI = -0.38 to -0.15). Similar results emerged for leisure activities. Adjusting for depressive symptoms fully attenuated some associations. All physical multimorbidity clusters were associated with an increase in civic participation over time. CONCLUSIONS: Physical multimorbidity reduced some aspects of social participation over time, with specific combinations of conditions having increased risk of reductions.Supplemental data for this article is available online at http://dx.doi.org/10.1080/13607863.2021.2017847.

Automatic Assessment of the 2-Minute Walk Distance for Remote Monitoring of People with Multiple Sclerosis.

The aim of this study was to investigate the feasibility of automatically assessing the 2-Minute Walk Distance (2MWD) for monitoring people with multiple sclerosis (pwMS). For 154 pwMS, MS-related clinical outcomes as well as the 2MWDs as evaluated by clinicians and derived from accelerometer data were collected from a total of 323 periodic clinical visits. Accelerometer data from a wearable device during 100 home-based 2MWD assessments were also acquired. The error in estimating the 2MWD was validated for walk tests performed at hospital, and then the correlation (r) between clinical outcomes and home-based 2MWD assessments was evaluated. Robust performance in estimating the 2MWD from the wearable device was obtained, yielding an error of less than 10% in about two-thirds of clinical visits. Correlation analysis showed that there is a strong association between the actual and the estimated 2MWD obtained either at hospital (r = 0.71) or at home (r = 0.58). Furthermore, the estimated 2MWD exhibits moderate-to-strong correlation with various MS-related clinical outcomes, including disability and fatigue severity scores. Automatic assessment of the 2MWD in pwMS is feasible with the usage of a consumer-friendly wearable device in clinical and non-clinical settings. Wearable devices can also enhance the assessment of MS-related clinical outcomes.

Moral injury and psychological wellbeing in UK healthcare staff.

BACKGROUND: Potentially morally injurious events (PMIEs) can negatively impact mental health. The COVID-19 pandemic may have placed healthcare staff at risk of moral injury. AIM: To examine the impact of PMIE on healthcare staff wellbeing. METHODS: Twelve thousand nine hundred and sixty-five healthcare staff (clinical and non-clinical) were recruited from 18 NHS-England trusts into a survey of PMIE exposure and wellbeing. RESULTS: PMIEs were significantly associated with adverse mental health symptoms across healthcare staff. Specific work factors were significantly associated with experiences of moral injury, including being redeployed, lack of PPE, and having a colleague die of COVID-19. Nurses who reported symptoms of mental disorders were more likely to report all forms of PMIEs than those without symptoms (AOR 2.7; 95% CI 2.2, 3.3). Doctors who reported symptoms were only more likely to report betrayal events, such as breach of trust by colleagues (AOR 2.7, 95% CI 1.5, 4.9). CONCLUSION: A considerable proportion of NHS healthcare staff in both clinical and non-clinical roles report exposure to PMIEs during the COVID-19 pandemic. Prospective research is needed to identify the direction of causation between moral injury and mental disorder as well as continuing to monitor the longer term outcomes of exposure to PMIEs.

Shared goals for mental health research: what, why and when for the 2020s.

Mental health problems bring substantial individual, community and societal costs and the need for innovation to promote good mental health and to prevent and treat mental health problems has never been greater. However, we know that research findings can take up to 20 years to implement. One way to push the pace is to focus researchers and funders on shared, specific goals and targets. We describe a consultation process organised by the Department of Health and Social Care and convened by the Chief Medical Officer to consider high level goals for future research efforts and to begin to identify UK-specific targets to measure research impact. The process took account of new scientific methods and evidence, the UK context with a universal health care system (the NHS) and the embedded research support from the National Institute for Health Research Clinical Research Network, as well as the views of individual service users and service user organisations. The result of the consultation is a set of four overarching goals with the potential to be measured at intervals of three, five or ten years.