Psychometric evaluation of the near activity visual questionnaire presbyopia (NAVQ-P) and additional patient-reported outcome items.

BACKGROUND: The Near Visual Acuity Questionnaire Presbyopia (NAVQ-P) is a patient-reported outcome (PRO) measure that was developed in a phakic presbyopia population to assess near vision function impacts. The study refined and explored the psychometric properties and score interpretability of the NAVQ-P and additional PRO items assessing near vision correction independence (NVCI), near vision satisfaction (NVS), and near vision correction preference (NVCP). METHODS: This was a psychometric validation study conducted using PRO data collected as part of a Phase IIb clinical trial (CUN8R44 A2202) consisting of 235 randomized adults with presbyopia from the US, Japan, Australia, and Canada. Data collected at baseline, week 2, and months 1, 2, and 3 during the 3-month trial treatment period were included in the analyses to assess item (question) properties, NAVQ-P dimensionality and scoring, reliability, validity, and score interpretation. RESULTS: Item responses were distributed across the full response scale for most NAVQ-P and additional PRO items. Confirmatory factor analysis supported the pre-defined unidimensional structure and calculation of a NAVQ-P total score as a measure of near vision function. Item deletion informed by item response distributions, dimensionality analyses, item response theory, and previous qualitative findings, including clinical input, supported retention of 14 NAVQ-P items. The 14-item NAVQ-P total score had excellent internal consistency (α = 0.979) and high test-retest reliability (Intraclass Correlation Coefficients > = 0.898). There was good evidence of construct-related validity for all PROs supported by strong correlations with concurrent measures. Excellent results for known-groups validity and ability to detect change analyses were also demonstrated. Anchor-based and distribution-based methods supported interpretation of scores through generation of group-level and within-individual estimates of meaningful change thresholds. A meaningful within-patient change in the range of 8-15-point improvement on the NAVQ-P total score (score range 0-42) was recommended, including a more specific responder definition of 10-point improvement. CONCLUSIONS: The NAVQ-P, NVCI, and NVS are valid and reliable instruments which have the ability to detect change over time. Findings strongly support the use of these measures as outcome assessments in clinical/research studies and in clinical practice in the presbyopia population.

Evidence of Hypothalamic-Pituitary-Adrenal and -Gonadal Dysfunction in Cocaine-Addicted Men.

INTRODUCTION: Regular cocaine use has been associated with hormonal dysfunction including hypogonadism, which can lead to fatigue, reduced stamina, sexual dysfunction, and impaired quality of life. However, cocaine's endocrine effects are largely under-reported in the scientific addiction literature and, in many cases, are not addressed within treatment services. The low profile of these adverse effects might be attributable to a lack of awareness and linkage with cocaine use, such that they are recognized only when an acute/emergency problem arises. METHODS: We assessed endocrine diurnal function (adrenocorticotrophic hormone [ACTH], cortisol, and testosterone) in 26 healthy and 27 cocaine-dependent men and examined changes in hormone levels in response to a single 40 mg dose of the noradrenaline re-uptake inhibitor atomoxetine in a double-blind, placebo-controlled experimental medicine study. RESULTS: When compared with healthy controls, diurnal and atomoxetine-induced changes in ACTH and cortisol showed greater variability in cocaine-dependent men. Interestingly, despite an exaggerated rise in ACTH following atomoxetine, an attenuated cortisol response was observed, and one-third of cocaine-dependent men had subnormal testosterone levels. CONCLUSION: Our findings point to a potential disconnection between the pituitary and adrenal responses in cocaine-dependent men, a higher rate of hypogonadism, and a pressing need for more research into the endocrine effects of cocaine and their clinical implications.

Cost-effectiveness of providing university students with a mindfulness-based intervention to reduce psychological distress: economic evaluation of a pragmatic randomised controlled trial.

OBJECTIVE: Increasing numbers of young people attending university has raised concerns about the capacity of student mental health services to support them. We conducted a randomised controlled trial (RCT) to explore whether provision of an 8 week mindfulness course adapted for university students (Mindfulness Skills for Students-MSS), compared with university mental health support as usual (SAU), reduced psychological distress during the examination period. Here, we conduct an economic evaluation of MSS+SAU compared with SAU. DESIGN AND SETTING: Economic evaluation conducted alongside a pragmatic, parallel, single-blinded RCT comparing provision of MSS+SAU to SAU. PARTICIPANTS: 616 university students randomised. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary economic evaluation assessed the cost per quality-adjusted life year (QALY) gained from the perspective of the university counselling service. Costs relate to staff time required to deliver counselling service offerings. QALYs were derived from the Clinical Outcomes in Routine Evaluation Dimension 6 Dimension (CORE-6D) preference based tool, which uses responses to six items of the Clinical Outcomes in Routine Evaluation Outcome Measure (CORE-OM; primary clinical outcome measure). Primary follow-up duration was 5 and 7 months for the two recruitment cohorts. RESULTS: It was estimated to cost £1584 (2022 prices) to deliver an MSS course to 30 students, £52.82 per student. Both costs (adjusted mean difference: £48, 95% CI £40-£56) and QALYs (adjusted mean difference: 0.014, 95% CI 0.008 to 0.021) were significantly higher in the MSS arm compared with SAU. The incremental cost-effectiveness ratio (ICER) was £3355, with a very high (99.99%) probability of being cost-effective at a willingness-to-pay threshold of £20 000 per QALY. CONCLUSIONS: MSS leads to significantly improved outcomes at a moderate additional cost. The ICER of £3355 per QALY suggests that MSS is cost-effective when compared with the UK's National Institute for Health and Care Excellence thresholds of £20 000 per QALY. TRIAL REGISTRATION NUMBER: Australian and New Zealand Clinical Trials Registry, ACTRN12615001160527.

Identifying the neurodevelopmental and psychiatric signatures of genomic disorders associated with intellectual disability: a machine learning approach.

BACKGROUND: Genomic conditions can be associated with developmental delay, intellectual disability, autism spectrum disorder, and physical and mental health symptoms. They are individually rare and highly variable in presentation, which limits the use of standard clinical guidelines for diagnosis and treatment. A simple screening tool to identify young people with genomic conditions associated with neurodevelopmental disorders (ND-GCs) who could benefit from further support would be of considerable value. We used machine learning approaches to address this question. METHOD: A total of 493 individuals were included: 389 with a ND-GC, mean age = 9.01, 66% male) and 104 siblings without known genomic conditions (controls, mean age = 10.23, 53% male). Primary carers completed assessments of behavioural, neurodevelopmental and psychiatric symptoms and physical health and development. Machine learning techniques (penalised logistic regression, random forests, support vector machines and artificial neural networks) were used to develop classifiers of ND-GC status and identified limited sets of variables that gave the best classification performance. Exploratory graph analysis was used to understand associations within the final variable set. RESULTS: All machine learning methods identified variable sets giving high classification accuracy (AUROC between 0.883 and 0.915). We identified a subset of 30 variables best discriminating between individuals with ND-GCs and controls which formed 5 dimensions: conduct, separation anxiety, situational anxiety, communication and motor development. LIMITATIONS: This study used cross-sectional data from a cohort study which was imbalanced with respect to ND-GC status. Our model requires validation in independent datasets and with longitudinal follow-up data for validation before clinical application. CONCLUSIONS: In this study, we developed models that identified a compact set of psychiatric and physical health measures that differentiate individuals with a ND-GC from controls and highlight higher-order structure within these measures. This work is a step towards developing a screening instrument to identify young people with ND-GCs who might benefit from further specialist assessment.

Stratification of adolescents across mental phenomena emphasizes the importance of transdiagnostic distress: a replication in two general population cohorts.

Characterizing patterns of mental phenomena in epidemiological studies of adolescents can provide insight into the latent organization of psychiatric disorders. This avoids the biases of chronicity and selection inherent in clinical samples, guides models of shared aetiology within psychiatric disorders and informs the development and implementation of interventions. We applied Gaussian mixture modelling to measures of mental phenomena from two general population cohorts: the Avon Longitudinal Study of Parents and Children (ALSPAC, n = 3018) and the Neuroscience in Psychiatry Network (NSPN, n = 2023). We defined classes according to their patterns of both positive (e.g. wellbeing and self-esteem) and negative (e.g. depression, anxiety, and psychotic experiences) phenomena. Subsequently, we characterized classes by considering the distribution of diagnoses and sex split across classes. Four well-separated classes were identified within each cohort. Classes primarily differed by overall severity of transdiagnostic distress rather than particular patterns of phenomena akin to diagnoses. Further, as overall severity of distress increased, so did within-class variability, the proportion of individuals with operational psychiatric diagnoses. These results suggest that classes of mental phenomena in the general population of adolescents may not be the same as those found in clinical samples. Classes differentiated only by overall severity support the existence of a general, transdiagnostic mental distress factor and have important implications for intervention.

The impact of the initial COVID-19 outbreak on young adults' mental health: a longitudinal study of risk and resilience factors.

Few studies assessing the effects of COVID-19 on mental health include prospective markers of risk and resilience necessary to understand and mitigate the combined impacts of the pandemic, lockdowns, and other societal responses. This population-based study of young adults includes individuals from the Neuroscience in Psychiatry Network (n = 2403) recruited from English primary care services and schools in 2012-2013 when aged 14-24. Participants were followed up three times thereafter, most recently during the initial outbreak of the COVID-19 outbreak when they were aged between 19 and 34. Repeated measures of psychological distress (K6) and mental wellbeing (SWEMWBS) were supplemented at the latest assessment by clinical measures of depression (PHQ-9) and anxiety (GAD-7). A total of 1000 participants, 42% of the original cohort, returned to take part in the COVID-19 follow-up; 737 completed all four assessments [mean age (SD), 25.6 (3.2) years; 65.4% female; 79.1% White]. Our findings show that the pandemic led to pronounced deviations from existing mental health-related trajectories compared to expected levels over approximately seven years. About three-in-ten young adults reported clinically significant depression (28.8%) or anxiety (27.6%) under current NHS guidelines; two-in-ten met clinical cut-offs for both. About 9% reported levels of psychological distress likely to be associated with serious functional impairments that substantially interfere with major life activities; an increase by 3% compared to pre-pandemic levels. Deviations from personal trajectories were not necessarily restricted to conventional risk factors; however, individuals with pre-existing health conditions suffered disproportionately during the initial outbreak of the COVID-19 pandemic. Resilience factors known to support mental health, particularly in response to adverse events, were at best mildly protective of individual psychological responses to the pandemic. Our findings underline the importance of monitoring the long-term effects of the ongoing pandemic on young adults' mental health, an age group at particular risk for the emergence of psychopathologies. Our findings further suggest that maintaining access to mental health care services during future waves, or potential new pandemics, is particularly crucial for those with pre-existing health conditions. Even though resilience factors known to support mental health were only mildly protective during the initial outbreak of the COVID-19 pandemic, it remains to be seen whether these factors facilitate mental health in the long term.

The psychosis metabolic risk calculator (PsyMetRiC) for young people with psychosis: International external validation and site-specific recalibration in two independent European samples.

Background: Cardiometabolic dysfunction is common in young people with psychosis. Recently, the Psychosis Metabolic Risk Calculator (PsyMetRiC) was developed and externally validated in the UK, predicting up-to six-year risk of metabolic syndrome (MetS) from routinely collected data. The full-model includes age, sex, ethnicity, body-mass index, smoking status, prescription of metabolically-active antipsychotic medication, high-density lipoprotein, and triglyceride concentrations; the partial-model excludes biochemical predictors. Methods: To move toward a future internationally-useful tool, we externally validated PsyMetRiC in two independent European samples. We used data from the PsyMetab (Lausanne, Switzerland) and PAFIP (Cantabria, Spain) cohorts, including participants aged 16-35y without MetS at baseline who had 1-6y follow-up. Predictive performance was assessed primarily via discrimination (C-statistic), calibration (calibration plots), and decision curve analysis. Site-specific recalibration was considered. Findings: We included 1024 participants (PsyMetab n=558, male=62%, outcome prevalence=19%, mean follow-up=2.48y; PAFIP n=466, male=65%, outcome prevalence=14%, mean follow-up=2.59y). Discrimination was better in the full- compared with partial-model (PsyMetab=full-model C=0.73, 95% C.I., 0.68-0.79, partial-model C=0.68, 95% C.I., 0.62-0.74; PAFIP=full-model C=0.72, 95% C.I., 0.66-0.78; partial-model C=0.66, 95% C.I., 0.60-0.71). As expected, calibration plots revealed varying degrees of miscalibration, which recovered following site-specific recalibration. PsyMetRiC showed net benefit in both new cohorts, more so after recalibration. Interpretation: The study provides evidence of PsyMetRiC's generalizability in Western Europe, although further local and international validation studies are required. In future, PsyMetRiC could help clinicians internationally to identify young people with psychosis who are at higher cardiometabolic risk, so interventions can be directed effectively to reduce long-term morbidity and mortality. Funding: NIHR Cambridge Biomedical Research Centre (BRC-1215-20014); The Wellcome Trust (201486/Z/16/Z); Swiss National Research Foundation (320030-120686, 324730- 144064, and 320030-173211); The Carlos III Health Institute (CM20/00015, FIS00/3095, PI020499, PI050427, and PI060507); IDIVAL (INT/A21/10 and INT/A20/04); The Andalusian Regional Government (A1-0055-2020 and A1-0005-2021); SENY Fundacion Research (2005-0308007); Fundacion Marques de Valdecilla (A/02/07, API07/011); Ministry of Economy and Competitiveness and the European Fund for Regional Development (SAF2016-76046-R and SAF2013-46292-R).For the Spanish and French translation of the abstract see Supplementary Materials section.

Treating common mental disorder including psychotic experiences in the primary care improving access to psychological therapies programme (the TYPPEX study): protocol for a stepped wedge cluster randomised controlled trial with nested economic and process evaluation of a training package for therapists.

INTRODUCTION: At least one in four people treated by the primary care improving access to psychological therapies (IAPT) programme in England experiences distressing psychotic experiences (PE) in addition to common mental disorder (CMD). These individuals are less likely to achieve recovery. IAPT services do not routinely screen for nor offer specific treatments for CMD including PE. The Tailoring evidence-based psychological therapY for People with common mental disorder including Psychotic EXperiences study will evaluate the clinical and cost-effectiveness of an enhanced training for cognitive behavioural therapists that aims to address this clinical gap. METHODS AND ANALYSIS: This is a multisite, stepped-wedge cluster randomised controlled trial. The setting will be IAPT services within three mental health trusts. The participants will be (1) 56-80 qualified IAPT cognitive behavioural therapists and (2) 600 service users who are triaged as appropriate for cognitive behavioural therapy in an IAPT service and have PE according to the Community Assessment of Psychic Experiences-Positive 15-items Scale. IAPT therapists will be grouped into eight study clusters subsequently randomised to the control-intervention sequence. We will obtain pseudonymous clinical outcome data from IAPT clinical records for eligible service users. We will invite service users to complete health economic measures at baseline, 3, 6, 9 and 12-month follow-up. The primary outcome will be the proportion of patients with common mental disorder psychotic experiences who have recovered by the end of treatment as measured by the official IAPT measure for recovery. ETHICS AND DISSEMINATION: The study received the following approvals: South Central-Berkshire Research Ethics Committee on 28 April 2020 (REC reference 20/SC/0135) and Health Research Authority (HRA) on 23 June 2020. An amendment was approved by the Ethics Committee on 01 October 2020 and HRA on 27 October 2020. Results will be made available to patients and the public, the funders, stakeholders in the IAPT services and other researchers. TRIAL REGISTRATION NUMBER: ISRCTN93895792.

Developing a Web-Based App to Assess Mental Health Difficulties in Secondary School Pupils: Qualitative User-Centered Design Study.

BACKGROUND: Secondary schools are an ideal setting to identify young people experiencing mental health difficulties such as anxiety or depression. However, current methods of identification rely on cumbersome paper-based assessments, which are lengthy and time-consuming to complete and resource-intensive for schools to manage. Artemis-A is a prototype web app that uses computerized adaptive testing technology to shorten the length of the assessment and provides schools with a simple and feasible solution for mental health assessment. OBJECTIVE: The objectives of this study are to coproduce the main components of the Artemis-A app with stakeholders to enhance the user interface, to carry out usability testing and finalize the interface design and functionality, and to explore the acceptability and feasibility of using Artemis-A in schools. METHODS: This study involved 2 iterative design feedback cycles-an initial stakeholder consultation to inform the app design and user testing. Using a user-centered design approach, qualitative data were collected through focus groups and interviews with secondary school pupils, parents, school staff, and mental health professionals (N=48). All transcripts were thematically analyzed. RESULTS: Initial stakeholder consultations provided feedback on preferences for the user interface design, school administration of the assessment, and outcome reporting. The findings informed the second iteration of the app design and development. The unmoderated usability assessment indicated that young people found the app easy to use and visually appealing. However, school staff suggested that additional features should be added to the school administration panel, which would provide them with more flexibility for data visualization. The analysis identified four themes relating to the implementation of the Artemis-A in schools, including the anticipated benefits and drawbacks of the app. Actionable suggestions for designing mental health assessment apps are also provided. CONCLUSIONS: Artemis-A is a potentially useful tool for secondary schools to assess the mental health of their pupils that requires minimal staff input and training. Future research will evaluate the feasibility and effectiveness of Artemis-A in a range of UK secondary schools.

On Dimensionality, Measurement Invariance, and Suitability of Sum Scores for the PHQ-9 and the GAD-7.

In psychiatry, severity of mental health conditions and their change over time are usually measured via sum scores of items on psychometric scales. However, inferences from such scores can be biased if psychometric properties such as unidimensionality and temporal measurement invariance for instruments are not met. Here, we aimed to evaluate these properties for common measures of depression (Patient Health Questionnaire-9) and anxiety (Generalized Anxiety Disorder Assessment-7) in a large clinical sample (N = 22,362) undergoing psychotherapy. In addition, we tested consistency in dimensionality results across different methods (parallel analysis, factor analysis, explained common variance, the partial credit model, and the Mokken model). Results showed that while both Patient Health Questionnaire-9 and Generalized Anxiety Disorder Assessment-7 are multidimensional instruments with highly correlated factors, there is justification for sum scores as measures of severity. Temporal measurement invariance across 10 therapy sessions was evaluated. Strict temporal measurement invariance was established in both scales, allowing researchers to compare sum scores as severity measures across time.

Determinants of patient-reported outcome trajectories and symptomatic recovery in Improving Access to Psychological Therapies (IAPT) services.

BACKGROUND: Despite evidence for the general effectiveness of psychological therapies, there exists substantial heterogeneity in patient outcomes. We aimed to identify factors associated with baseline severity of depression and anxiety symptoms, rate of symptomatic change over the course of therapy, and symptomatic recovery in a primary mental health care setting. METHODS: Using data from a service evaluation involving 35 527 patients in England's psychological and wellbeing [Improving Access to Psychological Therapies (IAPT)] services, we applied latent growth models to explore which routinely-collected sociodemographic, clinical, and therapeutic variables were associated with baseline symptom severity and rate of symptomatic change. We used a multilevel logit model to determine variables associated with symptomatic recovery. RESULTS: Being female, younger, more functionally impaired, and more socioeconomically disadvantaged was associated with higher baseline severity of both depression and anxiety symptoms. Being older, less functionally impaired, and having more severe baseline symptomatology was associated with more rapid improvement of both depression and anxiety symptoms (male gender and greater socioeconomic disadvantage were further associated with rate of change for depression only). Therapy intensity and appointment frequency seemed to have no correlation with rate of symptomatic improvement. Patients with lower baseline symptom severity, less functional impairment, and older age had a greater likelihood of achieving symptomatic recovery (as defined by IAPT criteria). CONCLUSIONS: We must continue to investigate how best to tailor psychotherapeutic interventions to fit patients' needs. Patients who begin therapy with more severe depression and/or anxiety symptoms and poorer functioning merit special attention, as these characteristics may negatively impact recovery.

Short- and Long-Term Effects of DBS on Gait in Parkinson's Disease.

The aim was to compare the short and long-term effects of subthalamic nucleus (STN) deep brain stimulation (DBS) on gait dysfunction and other cardinal symptoms of Parkinson's disease (PD). Two groups of patients were studied. The first group (short-term DBS, n = 8) included patients recently implanted with STN DBS (mean time since DBS 15.8 months, mean age 58.8 years, PD duration 13 years); the second group (long-term DBS, n = 10) included patients with at least 5 years of DBS therapy (mean time since DBS 67.6 months, mean age 61.7 years, PD duration 17.1 years). Both groups were examined using the Unified Parkinson's Disease Rating Scale (UPDRS) and Gait and Balance scale (GABS) during four stimulation/medication states (ON/OFF; OFF/OFF; OFF/ON; ON/ON). Data were analyzed using repeated measures ANOVA with time since implantation (years) between groups and medication or DBS effect (ON, OFF) within groups. In the short-term DBS group, stimulation improved all UPDRS subscores similar to dopaminergic medications. In particular, average gait improvement was over 40% (p = 0.01), as measured by the UPDRS item 29 and GABS II. In the long-term DBS group, stimulation consistently improved all clinical subscores with the exception of gait and postural instability. In these patients, the effect of levodopa on gait was partially preserved. Short-term improvement of gait abnormalities appears to significantly decline after 5 years of STN DBS in PD patients, while effectiveness for other symptoms remains stable. Progressive non-dopaminergic (non-DBS responsive) mechanisms or deleterious effects of high frequency STN stimulation on gait function may play a role.

Development and external validation of the Psychosis Metabolic Risk Calculator (PsyMetRiC): a cardiometabolic risk prediction algorithm for young people with psychosis.

BACKGROUND: Young people with psychosis are at high risk of developing cardiometabolic disorders; however, there is no suitable cardiometabolic risk prediction algorithm for this group. We aimed to develop and externally validate a cardiometabolic risk prediction algorithm for young people with psychosis. METHODS: We developed the Psychosis Metabolic Risk Calculator (PsyMetRiC) to predict up to 6-year risk of incident metabolic syndrome in young people (aged 16-35 years) with psychosis from commonly recorded information at baseline. We developed two PsyMetRiC versions using the forced entry method: a full model (including age, sex, ethnicity, body-mass index, smoking status, prescription of a metabolically active antipsychotic medication, HDL concentration, and triglyceride concentration) and a partial model excluding biochemical results. PsyMetRiC was developed using data from two UK psychosis early intervention services (Jan 1, 2013, to Nov 4, 2020) and externally validated in another UK early intervention service (Jan 1, 2012, to June 3, 2020). A sensitivity analysis was done in UK birth cohort participants (aged 18 years) who were at risk of developing psychosis. Algorithm performance was assessed primarily via discrimination (C statistic) and calibration (calibration plots). We did a decision curve analysis and produced an online data-visualisation app. FINDINGS: 651 patients were included in the development samples, 510 in the validation sample, and 505 in the sensitivity analysis sample. PsyMetRiC performed well at internal (full model: C 0·80, 95% CI 0·74-0·86; partial model: 0·79, 0·73-0·84) and external validation (full model: 0·75, 0·69-0·80; and partial model: 0·74, 0·67-0·79). Calibration of the full model was good, but there was evidence of slight miscalibration of the partial model. At a cutoff score of 0·18, in the full model PsyMetRiC improved net benefit by 7·95% (sensitivity 75%, 95% CI 66-82; specificity 74%, 71-78), equivalent to detecting an additional 47% of metabolic syndrome cases. INTERPRETATION: We have developed an age-appropriate algorithm to predict the risk of incident metabolic syndrome, a precursor of cardiometabolic morbidity and mortality, in young people with psychosis. PsyMetRiC has the potential to become a valuable resource for early intervention service clinicians and could enable personalised, informed health-care decisions regarding choice of antipsychotic medication and lifestyle interventions. FUNDING: National Institute for Health Research and Wellcome Trust.

Tracking Stress, Mental Health, and Resilience Factors in Medical Students Before, During, and After a Stress-Inducing Exam Period: Protocol and Proof-of-Principle Analyses for the RESIST Cohort Study.

BACKGROUND: Knowledge of mental distress and resilience factors over the time span from before to after a stressor is important to be able to leverage the most promising resilience factors and promote mental health at the right time. To shed light on this topic, we designed the RESIST (Resilience Study) study, in which we assessed medical students before, during, and after their yearly exam period. Exam time is generally a period of notable stress among medical students, and it has been suggested that exam time triggers mental distress. OBJECTIVE: In this paper, we aim to describe the study protocol and to examine whether the exam period indeed induces higher perceived stress and mental distress. We also aim to explore whether perceived stress and mental distress coevolve in response to exams. METHODS: RESIST is a cohort study in which exam stress functions as a within-subject natural stress manipulation. In this paper, we outline the sample (N=451), procedure, assessed measures (including demographics, perceived stress, mental distress, 13 resilience factors, and adversity), and ethical considerations. Moreover, we conducted a series of latent growth models and bivariate latent change score models to analyze perceived stress and mental distress changes over the 3 time points. RESULTS: We found that perceived stress and mental distress increased from the time before the exams to the exam period and decreased after the exams to a lower level than before the exams. Our findings further suggest that higher mental distress before exams increased the risk of developing more perceived stress during exams. Higher perceived stress during exams, in turn, increased the risk of experiencing a less successful (or quick) recovery of mental distress after exams. CONCLUSIONS: As expected, the exam period caused a temporary increase in perceived stress and mental distress. Therefore, the RESIST study lends itself well to exploring resilience factors in response to naturally occurring exam stress. Such knowledge will eventually help researchers to find out which resilience factors lend themselves best as prevention targets and which lend themselves best as treatment targets for the mitigation of mental health problems that are triggered or accelerated by natural exam stress. The findings from the RESIST study may therefore inform student support services, mental health services, and resilience theory.

Longitudinal association between CRP levels and risk of psychosis: a meta-analysis of population-based cohort studies.

Meta-analyses of cross-sectional studies suggest that patients with psychosis have higher circulating levels of C-reactive protein (CRP) compared with healthy controls; however, cause and effect is unclear. We examined the prospective association between CRP levels and subsequent risk of developing a psychotic disorder by conducting a systematic review and meta-analysis of population-based cohort studies. Databases were searched for prospective studies of CRP and psychosis. We obtained unpublished results, including adjustment for age, sex, body mass index, smoking, alcohol use, and socioeconomic status and suspected infection (CRP > 10 mg/L). Based on random effect meta-analysis of 89,792 participants (494 incident cases of psychosis at follow-up), the pooled odds ratio (OR) for psychosis for participants with high (>3 mg/L), as compared to low (≤3 mg/L) CRP levels at baseline was 1.50 (95% confidence interval [CI], 1.09-2.07). Evidence for this association remained after adjusting for potential confounders (adjusted OR [aOR] = 1.31; 95% CI, 1.03-1.66). After excluding participants with suspected infection, the OR for psychosis was 1.36 (95% CI, 1.06-1.74), but the association attenuated after controlling for confounders (aOR = 1.23; 95% CI, 0.95-1.60). Using CRP as a continuous variable, the pooled OR for psychosis per standard deviation increase in log(CRP) was 1.11 (95% CI, 0.93-1.34), and this association further attenuated after controlling for confounders (aOR = 1.07; 95% CI, 0.90-1.27) and excluding participants with suspected infection (aOR = 1.07; 95% CI, 0.92-1.24). There was no association using CRP as a categorical variable (low, medium or high). While we provide some evidence of a longitudinal association between high CRP (>3 mg/L) and psychosis, larger studies are required to enable definitive conclusions.

Polygenic risk for immuno-metabolic markers and specific depressive symptoms: A multi-sample network analysis study.

BACKGROUND: About every fourth patient with major depressive disorder (MDD) shows evidence of systemic inflammation. Previous studies have shown inflammation-depression associations of multiple serum inflammatory markers and multiple specific depressive symptoms. It remains unclear, however, if these associations extend to genetic/lifetime predisposition to higher inflammatory marker levels and what role metabolic factors such as Body Mass Index (BMI) play. It is also unclear whether inflammation-symptom associations reflect direct or indirect associations, which can be disentangled using network analysis. METHODS: This study examined associations of polygenic risk scores (PRSs) for immuno-metabolic markers (C-reactive protein [CRP], interleukin [IL]-6, IL-10, tumour necrosis factor [TNF]-α, BMI) with seven depressive symptoms in one general population sample, the UK Biobank study (n = 110,010), and two patient samples, the Munich Antidepressant Response Signature (MARS, n = 1058) and Sequenced Treatment Alternatives to Relieve Depression (STAR*D, n = 1143) studies. Network analysis was applied jointly for these samples using fused graphical least absolute shrinkage and selection operator (FGL) estimation as primary analysis and, individually, using unregularized model search estimation. Stability of results was assessed using bootstrapping and three consistency criteria were defined to appraise robustness and replicability of results across estimation methods, network bootstrapping, and samples. RESULTS: Network analysis results displayed to-be-expected PRS-PRS and symptom-symptom associations (termed edges), respectively, that were mostly positive. Using FGL estimation, results further suggested 28, 29, and six PRS-symptom edges in MARS, STAR*D, and UK Biobank samples, respectively. Unregularized model search estimation suggested three PRS-symptom edges in the UK Biobank sample. Applying our consistency criteria to these associations indicated that only the association of higher CRP PRS with greater changes in appetite fulfilled all three criteria. Four additional associations fulfilled at least two consistency criteria; specifically, higher CRP PRS was associated with greater fatigue and reduced anhedonia, higher TNF-α PRS was associated with greater fatigue, and higher BMI PRS with greater changes in appetite and anhedonia. Associations of the BMI PRS with anhedonia, however, showed an inconsistent valence across estimation methods. CONCLUSIONS: Genetic predisposition to higher systemic inflammatory markers are primarily associated with somatic/neurovegetative symptoms of depression such as changes in appetite and fatigue, consistent with previous studies based on circulating levels of inflammatory markers. We extend these findings by providing evidence that associations are direct (using network analysis) and extend to genetic predisposition to immuno-metabolic markers (using PRSs). Our findings can inform selection of patients with inflammation-related symptoms into clinical trials of immune-modulating drugs for MDD.

Longitudinal Trends in Childhood Insulin Levels and Body Mass Index and Associations With Risks of Psychosis and Depression in Young Adults.

Importance: Cardiometabolic disorders often occur concomitantly with psychosis and depression, contribute to high mortality rates, and are detectable from the onset of the psychiatric disorders. However, it is unclear whether longitudinal trends in cardiometabolic traits from childhood are associated with risks for adult psychosis and depression. Objective: To examine whether specific developmental trajectories of fasting insulin (FI) levels and body mass index (BMI) from early childhood were longitudinally associated with psychosis and depression in young adults. Design, Setting, and Participants: A cohort study from the Avon Longitudinal Study of Parents and Children, a prospective study including a population-representative British cohort of 14 975 individuals, was conducted using data from participants aged 1 to 24 years. Body mass index and FI level data were used for growth mixture modeling to delineate developmental trajectories, and associations with psychosis and depression were assessed. The study was conducted between July 15, 2019, and March 24, 2020. Exposures: Fasting insulin levels were measured at 9, 15, 18, and 24 years, and BMI was measured at 1, 2, 3, 4, 7, 9, 10, 11, 12, 15, 18, and 24 years. Data on sex, race/ethnicity, paternal social class, childhood emotional and behavioral problems, and cumulative scores of sleep problems, average calorie intake, physical activity, smoking, and alcohol and substance use in childhood and adolescence were examined as potential confounders. Main Outcomes and Measures: Psychosis risk (definite psychotic experiences, psychotic disorder, at-risk mental state status, and negative symptom score) depression risk (measured using the computerized Clinical Interview Schedule-Revised) were assessed at 24 years. Results: From data available on 5790 participants (3132 [54.1%] female) for FI levels and data available on 10 463 participants (5336 [51.0%] female) for BMI, 3 distinct trajectories for FI levels and 5 distinct trajectories for BMI were noted, all of which were differentiated by mid-childhood. The persistently high FI level trajectory was associated with a psychosis at-risk mental state (adjusted odds ratio [aOR], 5.01; 95% CI, 1.76-13.19) and psychotic disorder (aOR, 3.22; 95% CI, 1.29-8.02) but not depression (aOR, 1.38; 95% CI, 0.75-2.54). A puberty-onset major increase in BMI was associated with depression (aOR, 4.46; 95% CI, 2.38-9.87) but not psychosis (aOR, 1.98; 95% CI, 0.56-7.79). Conclusions and Relevance: The cardiometabolic comorbidity of psychosis and depression may have distinct, disorder-specific early-life origins. Disrupted insulin sensitivity could be a shared risk factor for comorbid cardiometabolic disorders and psychosis. A puberty-onset major increase in BMI could be a risk factor or risk indicator for adult depression. These markers may represent targets for prevention and treatment of cardiometabolic disorders in individuals with psychosis and depression.

Drug Use in Night Owls May Increase the Risk for Mental Health Problems.

Drugs of abuse are widely known to worsen mental health problems, but this relationship may not be a simple causational one. Whether or not a person is susceptible to the negative effects of drugs of abuse may not only be determined by their addictive properties, but also the users' chronotype, which determines their daily activity patterns. The present study investigates the relationship between chronotype, drug use and mental health problems in a cross-sectional community sample. Participants (n = 209) completed a selection of questionnaires online, including the Munich Chronotype Questionnaire, the Depression Anxiety Stress Scale, the Alcohol Use Disorder Identification Test, the Cannabis Use Disorder Identification Test and the Fagerström Test for Nicotine Dependence. We conducted multiple regression models to determine relationships between participants' chronotype and their reported mental health symptoms and then estimated mediation models to investigate the extent to which their drug consumption accounted for the identified associations. Chronotype was significantly associated with participants' overall mental health (ß = 0.16, p = 0.022) and their anxiety levels (ß = 0.18, p = 0.009) but not with levels of depression or stress. However, both relationships were fully mediated by participants' overall drug consumption. Thus, late chronotypes, so-called "night owls", not only use more drugs but consequently have an increased risk for developing anxiety and deteriorating mental health status. This group may be particularly vulnerable to the negative psychological effects of drugs. Our results point toward the importance of considering chronotype in designing preventative and therapeutic innovations, specifically for anxiety, which at present has been largely neglected.