Childhood adversity, combat experiences, and military sexual trauma: a test and extension of the stress sensitization hypothesis.

BACKGROUND: U.S. veterans report high rates of traumatic experiences and mental health symptomology [e.g. posttraumatic stress disorder (PTSD)]. The stress sensitization hypothesis posits experiences of adversity sensitize individuals to stress reactions which can lead to greater psychiatric problems. We extend this hypothesis by exploring how multiple adversities such as early childhood adversity, combat-related trauma, and military sexual trauma related to heterogeneity in stress over time and, subsequently, greater risk for PTSD. METHODS: 1230 veterans were recruited for an observational, longitudinal study. Veterans responded to questionnaires on PTSD, stress, and traumatic experiences five times over an 18-month study period. We used latent transition analysis to understand how heterogeneity in adverse experiences is related to transition into stress trajectory classes. We also explored how transition patterns related to PTSD symptomology. RESULTS: Across all models, we found support for stress sensitization. In general, combat trauma in combinations with other types of adverse experiences, namely early childhood adversity and military sexual trauma, imposed a greater probability of transitioning into higher risk stress profiles. We also showed differential effects of early childhood and military-specific adversity on PTSD symptomology. CONCLUSION: The present study rigorously integrates both military-specific and early life adversity into analysis on stress sensitivity, and is the first to examine how sensitivity might affect trajectories of stress over time. Our study provides a nuanced, and specific, look at who is risk for sensitization to stress based on previous traumatic experiences as well as what transition patterns are associated with greater PTSD symptomology.

Military veterans and civilians' mental health diagnoses: an analysis of secondary mental health services.

PURPOSE: Healthcare provision in the United Kingdom (UK) falls primarily to the National Health Service (NHS) which is free at the point of access. In the UK, there is currently no national marker to identify military veterans in electronic health records, nor a requirement to record it. This study aimed to compare the sociodemographic characteristics and recorded mental health diagnoses of a sample of veterans and civilians accessing secondary mental health services. METHODS: The Military Service Identification Tool, a machine learning computer tool, was employed to identify veterans and civilians from electronic health records. This study compared the sociodemographic characteristics and recorded mental health diagnoses of veterans and civilians accessing secondary mental health care from South London and Maudsley NHS Foundation Trust, UK. Data from 2,576 patients were analysed; 1288 civilians and 1288 veterans matched on age and gender. RESULTS: Depressive disorder was the most prevalent across both groups in the sample (26.2% veterans, 15.5% civilians). The present sample of veterans accessing support for mental health conditions were significantly more likely to have diagnoses of anxiety, depressive, psychosis, personality, and stress disorders (AORs ranging 1.41-2.84) but less likely to have a drug disorder (AOR = 0.51) than age- and gender-matched civilians. CONCLUSION: Veterans accessing secondary mental health services in South London had higher risks for many mental health problems than civilians accessing the same services. Findings suggest that military career history is a key consideration for probable prognosis and treatment, but this needs corroborating in other geographical areas including national population-based studies in the UK.

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.

Recruiting Military Veterans into Alcohol Misuse Research: The Role of Social Media and Facebook Advertising.

Background: The use of digital technology within health care service delivery, monitoring, and research is becoming progressively popular, particularly given the ongoing COVID-19 pandemic. Mobile health (m-health) apps, one form of digital technology, are increasingly being used to promote positive health related behavior change. Therefore, it is important to conduct research to understand the efficacy of m-health apps. The process of participant recruitment is an essential component in producing strong research evidence, along with ensuring an adequately powered sample to conduct meaningful analyses and draw robust conclusions. Methods: In this work we outline and reflect on the strategies used to recruit help-seeking military veterans into an intervention study, which aimed to evaluate the efficacy of an app (Drinks:Ration) to modify behavior in alcohol misusers. Recruitment strategies included through (1) partner organizations and (2) social media and Facebook advertising (ads). Results: Facebook ads were live for a period of 88 days and were viewed by a total audience of 29,416 people. In total 168 military veterans were recruited across all recruitment strategies, meaning that Drinks:Ration exceeded its recruitment targets. Half of the sample (n = 84) were recruited through social media, including Facebook ads. Conclusions: The current article highlighted that targeted Facebook ads were an efficient strategy to recruit military veterans into a digital intervention trial aiming to reduce alcohol consumption because they reduced the amount of time and resources required to contact a large number of potentially eligible individuals for our study. This article acts as a starting point for other researchers to evaluate their recruitment pathways for recruiting military veterans into alcohol misuse research.

The effectiveness of digital health technologies for reducing substance use among young people: a systematic review & meta-analysis.

BACKGROUND: Substance use amongst young people poses developmental and clinical challenges, necessitating early detection and treatment. Considering the widespread use of technology in young people, delivering interventions digitally may help to reduce and monitor their substance use. AIMS: We conducted a systematic review and two meta-analyses to assess the effectiveness of digital interventions for reducing substance use (alcohol, smoking, and other substances) among young people aged 10 to 24 years old. METHOD: Embase, Global Health, Medline, PsychINFO, Web of Science and reference lists of relevant papers were searched in November 2020. Studies were included if they quantitatively evaluated the effectiveness of digital health technologies for treating substance use. A narrative synthesis and meta-analysis were conducted. RESULTS: Forty-two studies were included in the systematic review and 18 in the meta-analyses. Digital interventions showed small, but statistically significant reductions in weekly alcohol consumption compared to controls (SMD= -0.12, 95% CI= -0.17 to -0.06, I2=0%), but no overall effect was seen on 30-day smoking abstinence (OR = 1.12, 95% CI = 0.70 to 1.80, I2=81%). The effectiveness of digital interventions for reducing substance use is generally weak, however, promising results such as reducing alcohol use were seen. Large-scale studies should investigate the viability of digital interventions, collect user feedback, and determine cost-effectiveness. PRISMA/PROSPERO: This systematic review was conducted following Cochrane methodology PRISMA guidelines. The review was registered with PROSPERO in November 2020 (CRD42020218442).

Trajectories of mental health among UK university staff and postgraduate students during the pandemic.

OBJECTIVES: The COVID-19 pandemic has disrupted the social and working lives of many. Past studies have highlighted worsening mental health during the pandemic, but often rely on small samples or infrequent follow-up. This study draws on fortnightly assessments from a large occupational cohort to describe differing trajectories of mental health between April 2020 and April 2021 and individual characteristics associated with these trajectory types. METHODS: King's College London Coronavirus Health and Experiences of Colleagues at King's is an occupational cohort study at a large university in London, UK. Participants (n=2241) completed online questionnaires fortnightly between April 2020 and April 2021. Symptoms of anxiety and depression were assessed using Generalised Anxiety Disorder (GAD-7) and Patient Health Questionnaire (PHQ-9). RESULTS: On average, participants reported low levels of anxiety and depression (GAD-7 and PHQ-9 scores of 0-9, consistent with 'none', 'minimal' or 'mild' symptoms) throughout the year, with symptoms highest in April 2020 and decreasing over the summer months when no lockdown measures were in place. However, we observed more severe and variable symptoms among subgroups of participants. Four trajectory types for anxiety and depression were identified: 'persistent high severity' (6%-7% of participants), 'varying symptoms, opposing national cases' (4%-8%), 'varying symptoms, consistent with national cases' (6%-11%) and 'persistent low severity' (74%-84%). Younger age, female gender, caring responsibilities and shielding were associated with higher severity trajectory types. CONCLUSIONS: These data highlight differing individual responses to the pandemic and underscore the need to consider individual circumstances when assessing and treating mental health. Aggregate trends in anxiety and depression may hide greater variation and symptom severity among subgroups.

Mental health among UK university staff and postgraduate students in the early stages of the COVID-19 pandemic.

OBJECTIVES: To characterise the baseline King's College London Coronavirus Health and Experiences of Colleagues at King's cohort and describe patterns of probable depression and anxiety among staff and postgraduate research students at a large UK university in April/May 2020. METHODS: An online survey was sent to current staff and postgraduate research students via email in April 2020 (n=2590). Primary outcomes were probable depression and anxiety, measured with the Patient Health Questionnaire-9 and Generalised Anxiety Disorder-7, respectively. Secondary outcomes were alcohol use and perceived change in mental health. Outcomes were described using summary statistics and multivariable Poisson regression was used to explore associations with six groups of predictors: demographics and prior mental health, living arrangements, caring roles, healthcare, occupational factors and COVID-19 infection. All analyses were weighted to account for differences between the sample and target population in terms of age, gender, and ethnicity. RESULTS: Around 20% of staff members and 30% of postgraduate research students met thresholds for probable depression or anxiety on the questionnaires. This doubled to around 40% among younger respondents aged <25. Other factors associated with probable depression and anxiety included female gender, belonging to an ethnic minority group, caregiving responsibilities and shielding or isolating. Around 20% of participants were found to reach cut-off for hazardous drinking on Alcohol Use Disorders Identification Test, while 30% were drinking more than before the pandemic. CONCLUSIONS: Our study shows worrying levels of symptoms of depression, anxiety and alcohol use disorder in an occupational sample from a large UK university in the months following the outbreak of the COVID-19 pandemic.

Remote Assessment of Disease and Relapse in Major Depressive Disorder (RADAR-MDD): recruitment, retention, and data availability in a longitudinal remote measurement study.

BACKGROUND: Major Depressive Disorder (MDD) is prevalent, often chronic, and requires ongoing monitoring of symptoms to track response to treatment and identify early indicators of relapse. Remote Measurement Technologies (RMT) provide an opportunity to transform the measurement and management of MDD, via data collected from inbuilt smartphone sensors and wearable devices alongside app-based questionnaires and tasks. A key question for the field is the extent to which participants can adhere to research protocols and the completeness of data collected. We aimed to describe drop out and data completeness in a naturalistic multimodal longitudinal RMT study, in people with a history of recurrent MDD. We further aimed to determine whether those experiencing a depressive relapse at baseline contributed less complete data. METHODS: Remote Assessment of Disease and Relapse - Major Depressive Disorder (RADAR-MDD) is a multi-centre, prospective observational cohort study conducted as part of the Remote Assessment of Disease and Relapse - Central Nervous System (RADAR-CNS) program. People with a history of MDD were provided with a wrist-worn wearable device, and smartphone apps designed to: a) collect data from smartphone sensors; and b) deliver questionnaires, speech tasks, and cognitive assessments. Participants were followed-up for a minimum of 11 months and maximum of 24 months. RESULTS: Individuals with a history of MDD (n = 623) were enrolled in the study,. We report 80% completion rates for primary outcome assessments across all follow-up timepoints. 79.8% of people participated for the maximum amount of time available and 20.2% withdrew prematurely. We found no evidence of an association between the severity of depression symptoms at baseline and the availability of data. In total, 110 participants had > 50% data available across all data types. CONCLUSIONS: RADAR-MDD is the largest multimodal RMT study in the field of mental health. Here, we have shown that collecting RMT data from a clinical population is feasible. We found comparable levels of data availability in active and passive forms of data collection, demonstrating that both are feasible in this patient group.

Indicators of recent COVID-19 infection status: findings from a large occupational cohort of staff and postgraduate research students from a UK university.

BACKGROUND: Researchers conducting cohort studies may wish to investigate the effect of episodes of COVID-19 illness on participants. A definitive diagnosis of COVID-19 is not always available, so studies have to rely on proxy indicators. This paper seeks to contribute evidence that may assist the use and interpretation of these COVID-indicators. METHODS: We described five potential COVID-indicators: self-reported core symptoms, a symptom algorithm; self-reported suspicion of COVID-19; self-reported external results; and home antibody testing based on a 'lateral flow' antibody (IgG/IgM) test cassette. Included were staff and postgraduate research students at a large London university who volunteered for the study and were living in the UK in June 2020. Excluded were those who did not return a valid antibody test result. We provide descriptive statistics of prevalence and overlap of the five indicators. RESULTS: Core symptoms were the most common COVID-indicator (770/1882 participants positive, 41%), followed by suspicion of COVID-19 (n = 509/1882, 27%), a positive symptom algorithm (n = 298/1882, 16%), study antibody lateral flow positive (n = 124/1882, 7%) and a positive external test result (n = 39/1882, 2%), thus a 20-fold difference between least and most common. Meeting any one indicator increased the likelihood of all others, with concordance between 65 and 94%. Report of a low suspicion of having had COVID-19 predicted a negative antibody test in 98%, but positive suspicion predicted a positive antibody test in only 20%. Those who reported previous external antibody tests were more likely to have received a positive result from the external test (24%) than the study test (15%). CONCLUSIONS: Our results support the use of proxy indicators of past COVID-19, with the caveat that none is perfect. Differences from previous antibody studies, most significantly in lower proportions of participants positive for antibodies, may be partly due to a decline in antibody detection over time. Subsequent to our study, vaccination may have further complicated the interpretation of COVID-indicators, only strengthening the need to critically evaluate what criteria should be used to define COVID-19 cases when designing studies and interpreting study results.

Smartphone-based alcohol interventions: A systematic review on the role of notifications in changing behaviors toward alcohol.

Background: Smartphone-based interventions are increasingly being used to facilitate positive behavior change, including reducing alcohol consumption. However, less is known about the effects of notifications to support this change, including intervention engagement and adherence. The aim of this review was to assess the role of notifications in smartphone-based interventions designed to support, manage, or reduce alcohol consumption. Methods: Five electronic databases were searched to identify studies meeting inclusion criteria: (1) studies using a smartphone-based alcohol intervention, (2) the intervention used notifications, and (3) published between 1st January 2007 and 30th April 2021 in English. PROSPERO was searched to identify any completed, ongoing, or planned systematic reviews and meta-analyses of relevance. The reference lists of all included studies were searched. Results: Overall, 14 papers were identified, reporting on 10 different interventions. The strength of the evidence regarding the role and utility of notifications in changing behavior toward alcohol of the reviewed interventions was inconclusive. Only one study drew distinct conclusions about the relationships between notifications and app engagement, and notifications and behavior change. Conclusions: Although there are many smartphone-based interventions to support alcohol reduction, this review highlights a lack of evidence to support the use of notifications (such as push notifications, alerts, prompts, and nudges) used within smartphone interventions for alcohol management aiming to promote positive behavior change. Included studies were limited due to small sample sizes and insufficient follow-up. Evidence for the benefits of smartphone-based alcohol interventions remains promising, but the efficacy of using notifications, especially personalized notifications, within these interventions remain unproven.

Psychosocial impact of the COVID-19 pandemic on 4378 UK healthcare workers and ancillary staff: initial baseline data from a cohort study collected during the first wave of the pandemic.

OBJECTIVES: This study reports preliminary findings on the prevalence of, and factors associated with, mental health and well-being outcomes of healthcare workers during the early months (April-June) of the COVID-19 pandemic in the UK. METHODS: Preliminary cross-sectional data were analysed from a cohort study (n=4378). Clinical and non-clinical staff of three London-based NHS Trusts, including acute and mental health Trusts, took part in an online baseline survey. The primary outcome measure used is the presence of probable common mental disorders (CMDs), measured by the General Health Questionnaire. Secondary outcomes are probable anxiety (seven-item Generalised Anxiety Disorder), depression (nine-item Patient Health Questionnaire), post-traumatic stress disorder (PTSD) (six-item Post-Traumatic Stress Disorder checklist), suicidal ideation (Clinical Interview Schedule) and alcohol use (Alcohol Use Disorder Identification Test). Moral injury is measured using the Moray Injury Event Scale. RESULTS: Analyses showed substantial levels of probable CMDs (58.9%, 95% CI 58.1 to 60.8) and of PTSD (30.2%, 95% CI 28.1 to 32.5) with lower levels of depression (27.3%, 95% CI 25.3 to 29.4), anxiety (23.2%, 95% CI 21.3 to 25.3) and alcohol misuse (10.5%, 95% CI 9.2 to 11.9). Women, younger staff and nurses tended to have poorer outcomes than other staff, except for alcohol misuse. Higher reported exposure to moral injury (distress resulting from violation of one's moral code) was strongly associated with increased levels of probable CMDs, anxiety, depression, PTSD symptoms and alcohol misuse. CONCLUSIONS: Our findings suggest that mental health support for healthcare workers should consider those demographics and occupations at highest risk. Rigorous longitudinal data are needed in order to respond to the potential long-term mental health impacts of the pandemic.

Investigating the impact of COVID-19 lockdown on adults with a recent history of recurrent major depressive disorder: a multi-Centre study using remote measurement technology.

BACKGROUND: The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes a clinical illness Covid-19, has had a major impact on mental health globally. Those diagnosed with major depressive disorder (MDD) may be negatively impacted by the global pandemic due to social isolation, feelings of loneliness or lack of access to care. This study seeks to assess the impact of the 1st lockdown - pre-, during and post - in adults with a recent history of MDD across multiple centres. METHODS: This study is a secondary analysis of an on-going cohort study, RADAR-MDD project, a multi-centre study examining the use of remote measurement technology (RMT) in monitoring MDD. Self-reported questionnaire and passive data streams were analysed from participants who had joined the project prior to 1st December 2019 and had completed Patient Health and Self-esteem Questionnaires during the pandemic (n = 252). We used mixed models for repeated measures to estimate trajectories of depressive symptoms, self-esteem, and sleep duration. RESULTS: In our sample of 252 participants, 48% (n = 121) had clinically relevant depressive symptoms shortly before the pandemic. For the sample as a whole, we found no evidence that depressive symptoms or self-esteem changed between pre-, during- and post-lockdown. However, we found evidence that mean sleep duration (in minutes) decreased significantly between during- and post- lockdown (- 12.16; 95% CI - 18.39 to - 5.92; p <  0.001). We also found that those experiencing clinically relevant depressive symptoms shortly before the pandemic showed a decrease in depressive symptoms, self-esteem and sleep duration between pre- and during- lockdown (interaction p = 0.047, p = 0.045 and p <  0.001, respectively) as compared to those who were not. CONCLUSIONS: We identified changes in depressive symptoms and sleep duration over the course of lockdown, some of which varied according to whether participants were experiencing clinically relevant depressive symptoms shortly prior to the pandemic. However, the results of this study suggest that those with MDD do not experience a significant worsening in symptoms during the first months of the Covid - 19 pandemic.

The association between paternal psychopathology and adolescent depression and anxiety: A systematic review.

INTRODUCTION: Paternal psychopathology is associated with various adolescent outcomes. With emotional disorders presenting a significant public health concern in the adolescent age group, the aim of this systematic review was to synthesize evidence on the relationship between paternal mental health and adolescent anxiety or depression. METHODS: PubMed, Web of Science, Embase, Ovid MEDLINE, Global Health, and PsycINFO were searched for articles which primarily aimed to investigate the relationship between paternal mental health (exposure) and adolescent anxiety or depression (outcome). Articles were assessed for risk of bias, and findings are presented in a narrative synthesis. The protocol is registered on PROSPERO (CRD42018094076). RESULTS: Findings from the fourteen included studies indicated that paternal depression is associated with adolescent depression and anxiety. Findings relating to other paternal mental health disorders were inconclusive. Results largely suggested that adolescent depression and anxiety is equally associated with paternal and maternal mental health. The included studies were mostly cross-sectional, and the quality of included studies was mixed. Attempts to focus on the 11-17 year age range were hampered by the variability of age ranges included in studies. CONCLUSIONS: Further longitudinal research is needed to clarify the association between paternal mental health disorders other than depression, and adolescent anxiety or depression. Mechanisms in this relationship should also be further explored, and could be informed by existing models on younger children.

Identifying probable post-traumatic stress disorder: applying supervised machine learning to data from a UK military cohort.

BACKGROUND: Early identification of probable post-traumatic stress disorder (PTSD) can lead to early intervention and treatment. AIMS: This study aimed to evaluate supervised machine learning (ML) classifiers for the identification of probable PTSD in those who are serving, or have recently served in the United Kingdom (UK) Armed Forces. METHODS: Supervised ML classification techniques were applied to a military cohort of 13,690 serving and ex-serving UK Armed Forces personnel to identify probable PTSD based on self-reported service exposures and a range of validated self-report measures. Data were collected between 2004 and 2009. RESULTS: The predictive performance of supervised ML classifiers to detect cases of probable PTSD were encouraging when compared to a validated measure, demonstrating a capability of supervised ML to detect the cases of probable PTSD. It was possible to identify which variables contributed to the performance, including alcohol misuse, gender and deployment status. A satisfactory sensitivity was obtained across a range of supervised ML classifiers, but sensitivity was low, indicating a potential for false negative diagnoses. CONCLUSIONS: Detection of probable PTSD based on self-reported measurement data is feasible, may greatly reduce the burden on public health and improve operational efficiencies by enabling early intervention, before manifestation of symptoms.

Postural Stability During Standing Balance and Sit-to-Stand in Master Athlete Runners Compared With Nonathletic Old and Young Adults.

The aim of this study was to compare postural sway during a series of static balancing tasks and during five chair rises between healthy young (mean [SEM], age 26 [1] years), healthy old (age 67 [1] years) and master athlete runners (age 67 [1] years; competing and training for the previous 51 [5] years) using the Microsoft Kinect One. The healthy old had more sway than the healthy young in all balance tasks. The master athletes had similar sway to young athletes during two-leg balancing and one-leg standing with eyes open. When balancing on one leg with eyes closed, both the healthy old and the master athletes had around 17-fold more sway than the young athletes. The healthy old and master athletes also had less anterio-posterior movement during chair rising compared with young athletes. These results suggest that masters runners are not spared from the age-associated decline in postural stability and may benefit from specific balance training.

Restore and Rebuild (R&R): a protocol for a phase 2, randomised control trial to compare R&R as a treatment for moral injury-related mental health difficulties in UK military veterans to treatment as usual.

BACKGROUND: Exposure to potentially morally injurious events is increasingly recognised as a concern across a range of occupational groups, including UK military veterans. Moral injury-related mental health difficulties can be challenging for clinicians to treat and there is currently no validated treatment available for UK veterans. We developed Restore and Rebuild (R&R) as a treatment for UK veterans struggling with moral injury-related mental health difficulties. This trial aims to examine whether it is feasible to conduct a pilot randomised controlled trial (RCT) of R&R treatment compared with a treatment-as-usual (TAU) control group. METHODS: We will use a feasibility single-blind, single-site RCT design. The target population will be UK military veterans with moral injury-related mental health difficulties. We will recruit N=46 veteran patients who will be randomly allocated to R&R (n=23) or TAU (n=23). Patients randomised to R&R will receive the 20-session one-to-one treatment, delivered online. Veterans allocated to TAU, as there are currently no manualised treatments for moral injury-related mental health problems available, will receive the one-to-one treatment (online) typically provided to veterans who enter the mental health service for moral injury-related mental health difficulties. We will collect outcome measures of moral injury, post-traumatic stress disorder (PTSD), alcohol misuse, common mental disorders and trauma memory at pretreatment baseline (before randomisation), end of treatment, 12 weeks and 24 weeks post-treatment. The primary outcome will be the proportion of patients who screen positive for PTSD and moral injury-related distress post-treatment. ETHICS AND DISSEMINATION: This trial will establish whether R&R is feasible, well-tolerated and beneficial treatment for veterans with moral injury-related mental health difficulties. If so, the results of the trial will be widely disseminated and R&R may improve access to effective care for those who struggle following moral injury and reduce the associated negative consequences for veterans, their families and wider society. TRIAL REGISTRATION NUMBER: ISRCTN99573523.

Shorter communications: Exploring the impact of a brief smartphone-based alcohol intervention app (DrinksRation) on the quality of life of UK military veterans.

Alcohol misuse - defined as consuming more than 14 units of alcohol per week - is a well-established problem among veterans. This study investigated the change in quality of life among help-seeking UK veterans who completed a 28-day brief alcohol intervention delivered via a digital smartphone application (called DrinksRation) and have previously sought clinical help for a mental health disorder. This study was a secondary outcome analysis of data collected during a randomised control trial. In total, 123 UK veterans participated in the study and were randomly allocated to either the intervention or control arm. Participants completed self-report questionnaires regarding their alcohol use and quality of life (WHOQOL-BREF) at baseline, day 28 (end of intervention), day 84, and day 168. At the primary endpoint (day 84), we found significantly greater improvements in the intervention arm compared to the control arm for psychological quality of life (Cohen's d = 0.47), and environmental quality of life (d = 0.34). However, we observed no statistically significant differences between the intervention and control arm for social relationships and physical quality of life. Further, for day 168 we found no significant differences. Findings suggest that DrinksRation can increase quality of life among help-seeking veterans who have previously sought help for a mental health disorder, but the increases were modest and restricted to certain domains. Additional treatment may be needed for long-term and sustained improvements in quality of life.

Engagement With a Remote Symptom-Tracking Platform Among Participants With Major Depressive Disorder: Randomized Controlled Trial.

BACKGROUND: Multiparametric remote measurement technologies (RMTs), which comprise smartphones and wearable devices, have the potential to revolutionize understanding of the etiology and trajectory of major depressive disorder (MDD). Engagement with RMTs in MDD research is of the utmost importance for the validity of predictive analytical methods and long-term use and can be conceptualized as both objective engagement (data availability) and subjective engagement (system usability and experiential factors). Positioning the design of user interfaces within the theoretical framework of the Behavior Change Wheel can help maximize effectiveness. In-app components containing information from credible sources, visual feedback, and access to support provide an opportunity to promote engagement with RMTs while minimizing team resources. Randomized controlled trials are the gold standard in quantifying the effects of in-app components on engagement with RMTs in patients with MDD. OBJECTIVE: This study aims to evaluate whether a multiparametric RMT system with theoretically informed notifications, visual progress tracking, and access to research team contact details could promote engagement with remote symptom tracking over and above the system as usual. We hypothesized that participants using the adapted app (intervention group) would have higher engagement in symptom monitoring, as measured by objective and subjective engagement. METHODS: A 2-arm, parallel-group randomized controlled trial (participant-blinded) with 1:1 randomization was conducted with 100 participants with MDD over 12 weeks. Participants in both arms used the RADAR-base system, comprising a smartphone app for weekly symptom assessments and a wearable Fitbit device for continuous passive tracking. Participants in the intervention arm (n=50, 50%) also had access to additional in-app components. The primary outcome was objective engagement, measured as the percentage of weekly questionnaires completed during follow-up. The secondary outcomes measured subjective engagement (system engagement, system usability, and emotional self-awareness). RESULTS: The levels of completion of the Patient Health Questionnaire-8 (PHQ-8) were similar between the control (67/97, 69%) and intervention (66/97, 68%) arms (P value for the difference between the arms=.83, 95% CI -9.32 to 11.65). The intervention group participants reported slightly higher user engagement (1.93, 95% CI -1.91 to 5.78), emotional self-awareness (1.13, 95% CI -2.93 to 5.19), and system usability (2.29, 95% CI -5.93 to 10.52) scores than the control group participants at follow-up; however, all CIs were wide and included 0. Process evaluation suggested that participants saw the in-app components as helpful in increasing task completion. CONCLUSIONS: The adapted system did not increase objective or subjective engagement in remote symptom tracking in our research cohort. This study provides an important foundation for understanding engagement with RMTs for research and the methodologies by which this work can be replicated in both community and clinical settings. TRIAL REGISTRATION: ClinicalTrials.gov NCT04972474; https://clinicaltrials.gov/ct2/show/NCT04972474. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/32653.

Cohort profile: The Social media, smartphone use and Self-harm in Young People (3S-YP) study-A prospective, observational cohort study of young people in contact with mental health services.

OBJECTIVES: The Social media, Smartphone use and Self-Harm (3S-YP) study is a prospective observational cohort study to investigate the mechanisms underpinning associations between social media and smartphone use and self-harm in a clinical youth sample. We present here a comprehensive description of the cohort from baseline data and an overview of data available from baseline and follow-up assessments. METHODS: Young people aged 13-25 years were recruited from a mental health trust in England and followed up for 6 months. Self-report data was collected at baseline and monthly during follow-up and linked with electronic health records (EHR) and user-generated data. FINDINGS: A total of 362 young people enrolled and provided baseline questionnaire data. Most participants had a history of self-harm according to clinical (n = 295, 81.5%) and broader definitions (n = 296, 81.8%). At baseline, there were high levels of current moderate/severe anxiety (n = 244; 67.4%), depression (n = 255; 70.4%) and sleep disturbance (n = 171; 47.2%). Over half used social media and smartphones after midnight on weekdays (n = 197, 54.4%; n = 215, 59.4%) and weekends (n = 241, 66.6%; n = 263, 72.7%), and half met the cut-off for problematic smartphone use (n = 177; 48.9%). Of the cohort, we have questionnaire data at month 6 from 230 (63.5%), EHR data from 345 (95.3%), social media data from 110 (30.4%) and smartphone data from 48 (13.3%). CONCLUSION: The 3S-YP study is the first prospective study with a clinical youth sample, for whom to investigate the impact of digital technology on youth mental health using novel data linkages. Baseline findings indicate self-harm, anxiety, depression, sleep disturbance and digital technology overuse are prevalent among clinical youth. Future analyses will explore associations between outcomes and exposures over time and compare self-report with user-generated data in this cohort.

KCL TEST: an open-source inspired asymptomatic SARS-CoV-2 surveillance programme in an academic institution.

Rapid and accessible testing was paramount in the management of the COVID-19 pandemic. Our university established KCL TEST: a SARS-CoV-2 asymptomatic testing programme that enabled sensitive and accessible PCR testing of SARS-CoV-2 RNA in saliva. Here, we describe our learnings and provide our blueprint for launching diagnostic laboratories, particularly in low-resource settings. Between December 2020 and July 2022, we performed 158277 PCRs for our staff, students, and their household contacts, free of charge. Our average turnaround time was 16 h and 37 min from user registration to result delivery. KCL TEST combined open-source automation and in-house non-commercial reagents, which allows for rapid implementation and repurposing. Importantly, our data parallel those of the UK Office for National Statistics, though we detected a lower positive rate and virtually no delta wave. Our observations strongly support regular asymptomatic community testing as an important measure for decreasing outbreaks and providing safe working spaces. Universities can therefore provide agile, resilient, and accurate testing that reflects the infection rate and trend of the general population. Our findings call for the early integration of academic institutions in pandemic preparedness, with capabilities to rapidly deploy highly skilled staff, as well as develop, test, and accommodate efficient low-cost pipelines.