Editorial: Open science and methods review for Child and Adolescent Mental Health.

This editorial introduces the journal's new open data policy for original articles using quantitative data. It discusses key opportunities from data and code sharing. It further briefly sets out the new methods review that articles which use quantitative analysis will automatically undergo. With both changes we hope to strengthen our review process and contribute to a better evidence base in the field.

Malnutrition, sarcopenia and cachexia: exploring prevalence, overlap, and perceptions in older adults with cancer.

BACKGROUND: Older adults with cancer are a growing population requiring tailored care to achieve optimum treatment outcomes. Their care is complicated by under-recognised and under-treated wasting disorders: malnutrition, sarcopenia, and cachexia. We aimed to investigate the prevalence, overlap, and patients' views and experiences of malnutrition, sarcopenia, and cachexia, in older adults with cancer. METHODS: Mixed-methods study with cross-sectional study and qualitative interviews. Interviews were thematically analysed through a phenomenological lens, with feedback loop analysis investigating relationships between themes and findings synthesised using modified critical interpretative synthesis. FINDINGS: n = 30 were screened for malnutrition, sarcopenia, and cachexia, n = 8 completed semi-structured interviews. Eighteen (60.0%) were malnourished, 16 (53.3%) sarcopenic, and 17 (56.7%) cachexic. One or more condition was seen in 80%, and all three in 30%. In univariate analysis, Rockwood clinical frailty score (OR 2.94 [95% CI: 1.26-6.89, p = 0.013]) was associated with sarcopenia, reported percentage meal consumption (OR 2.28 [95% CI: 1.24-4.19, p = 0.008]), and visible wasting (OR 8.43 [95% CI: 1.9-37.3] p = 0.005) with malnutrition, and percentage monthly weight loss (OR 8.71 [95% CI: 1.87-40.60] p = 0.006) with cachexia. Screening tools identified established conditions rather than 'risk'. Nutritional and functional problems were often overlooked, overshadowed, and misunderstood by both patients and (in patients' perceptions) by clinicians; misattributed to ageing, cancer, or comorbidities. Patients viewed these conditions as both personal impossibilities, yet accepted inevitabilities. CONCLUSION: Perceptions, identification, and management of these conditions needs to improve, and their importance recognised by clinicians and patients so those truly 'at risk' are identified whilst conditions are more remediable to interventions.

The validity of the selection methods for recruitment to UK core psychiatry training: cohort study.

AIMS AND METHOD: Selection into core psychiatry training in the UK uses a computer-delivered Multi-Specialty Recruitment Assessment (MSRA; a situational judgement and clinical problem-solving test) and, previously, a face-to-face Selection Centre. The Selection Centre assessments were suspended during the COVID-19 pandemic. We aimed to evaluate the validity of this selection process using data on 3510 psychiatry applicants. We modelled the ability of the selection scores to predict subsequent performance in the Clinical Assessment of Skills and Competencies (CASC). Sensitivity to demographic characteristics was also estimated. RESULTS: All selection assessment scores demonstrated positive, statistically significant, independent relationships with CASC performance and were sensitive to demographic factors. IMPLICATIONS: All selection components showed independent predictive validity. Re-instituting the Selection Centre assessments could be considered, although the costs, potential advantages and disadvantages should be weighed carefully.

New evidence on the validity of the selection methods for recruitment to general practice training: a cohort study.

BACKGROUND: Selection into UK-based GP training has used the Multi-Specialty Recruitment Assessment (MSRA) and a face-to-face selection centre (SC). The MSRA comprises of a situational judgement test and clinical problem-solving test. The SC was suspended during the COVID-19 pandemic. Evidence is needed to guide national and international selection policy. AIM: To evaluate the validity of GP training selection. DESIGN & SETTING: A retrospective cohort study using data from UK-based national recruitment to GP training, from 2015-2021. METHOD: Data were available for 32 215 GP training applicants. The ability of scores from the specialty selection process to predict subsequent performance in the Clinical Skills Assessment (CSA) of the Membership of the Royal College of General Practitioners examination was modelled using path analysis. The effect sizes for sex, professional family background, and world region of qualification were estimated. RESULTS: All component scores of the selection process demonstrated statistically significant independent relationships with CSA performance (P<0.001), thus establishing their predictive validity. All were sensitive to demographic factors. The SC scores had the weakest relationship with future CSA performance. However, for candidates with MSRA scores below the lowest quartile, the relative contribution of the SC scores to predicting CSA performance was similar to that observed for MSRA components. CONCLUSION: The MSRA has predictive validity in this context. Re-instituting an SC for those with relatively low MSRA scores should be considered. However, the relative costs and potential advantages and disadvantages should be carefully weighed.

Mental health trajectories in university students across the COVID-19 pandemic: findings from the Student Wellbeing at Northern England Universities prospective cohort study.

Introduction: Psychological wellbeing in university students is receiving increased focus. However, to date, few longitudinal studies in this population have been conducted. As such, in 2019, we established the Student Wellbeing At Northern England Universities (SWANS) cohort at the University of York, United Kingdom aiming to measure student mental health and wellbeing every six months. Furthermore, the study period included the COVID-19 pandemic, giving an opportunity to track student wellbeing over time, including over the pandemic. Methods: Eligible participants were invited to participate via email. Data were collected, using Qualtrics, from September 2019 to April 2021, across five waves (W1 to W5). In total, n = 4,622 students participated in at least one wave of the survey. Data collection included sociodemographic, educational, personality measures, and mental health and wellbeing. Latent profile analyses were performed, exploring trajectories of student wellbeing over the study period for those who had completed at least three of the five waves of the survey (n = 765), as measured by the Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS). Results: Five latent profile trajectories of student wellbeing were identified. Of these, the two latent classes with initially higher wellbeing scores had broadly stable wellbeing across time (total n = 505, 66%). Two classes had lower initial scores, which lowered further across time (total n = 227, 30%). Additionally, a fifth class of students was identified who improved substantially over the study period, from a mean WEMWBS of 30.4 at W1, to 49.4 at W5 (n = 33, 4%). Risk factors for having less favourable wellbeing trajectories generally included identifying as LGBT+, self-declaring a disability, or previously being diagnosed with a mental health condition. Conclusion: Our findings suggest a mixed picture of the effect of the COVID-19 pandemic on student wellbeing, with a majority showing broadly consistent levels of wellbeing across time, a smaller but still substantial group showing a worsening of wellbeing, and a small group that showed a very marked improvement in wellbeing. Those from groups traditionally underrepresented in higher education were most at risk of poorer wellbeing. This raises questions as to whether future support for wellbeing should target specific student subpopulations.

Situational judgement test performance and subsequent misconduct in medical students.

INTRODUCTION: Situational judgement tests (SJTs) have been widely adopted, internationally, into medical selection. It was hoped that such assessments could identify candidates likely to exhibit future professional behaviours. Understanding how performance on such tests may predict the risk of disciplinary action during medical school would provide evidence for the validity of such SJTs within student selection. It would also inform the implementation of such tests within student recruitment. METHODS: This cohort study used data for 6910 medical students from 36 UK medical schools who sat the University Clinical Aptitude Test (UCAT) SJT in 2013. The relationship between SJT scores at application and the risk of subsequent disciplinary action during their studies was modelled. The incremental ability of the SJT scores to predict the risk of disciplinary action, above that already provided by UCAT cognitive test scores and secondary (high) school achievement, was also evaluated in 5535 of the students with information available on this latter metric. RESULTS: Two hundred and ten (3.05%) of the students in the cohort experienced disciplinary action. The risk of disciplinary action reduced with increasing performance on the admissions SJT (odds ratio (OR) 0.80, 95% confidence interval (CI) 0.69 to 0.92, p = 0.002). This effect remained similar after adjusting for cognitive performance and prior academic attainment (OR 0.77, 95% CI 0.65 to 0.92, p = 0.004). The overall estimated effect-size was small (Cohen's d = 0.08) and no evidence of 'threshold' effects were observed for the SJT scores and risk of disciplinary action. CONCLUSIONS: Performance on admissions SJTs can, at least modestly, incrementally predict the risk of subsequent disciplinary action, supporting their use in this context. However, for this SJT and outcome, there did not seem a distinct threshold score above which the risk of disciplinary action disproportionately increased. This should be considered when using the scores within medical selection.

Knowledge and Response to the COVID-19 Pandemic in People With Severe Mental Illness in Bangladesh and Pakistan: A Cross-Sectional Survey.

BACKGROUND: People with severe mental illnesses (SMIs) are likely to face disproportionate challenges during a pandemic. They may not receive or be able to respond to public health messages to prevent infection or to limit its spread. Additionally, they may be more severely affected, particularly in low- and middle-income countries. METHODS: We conducted a telephone survey (May-June 2020) in a sample of 1,299 people with SMI who had attended national mental health institutes in Bangladesh and Pakistan before the pandemic. We collected information on top worries, socioeconomic impact of the pandemic, knowledge of COVID-19 (symptoms, prevention), and prevention-related practices (social distancing, hygiene). We explored the predictive value of socio-demographic and health-related variables for relative levels of COVID-19 knowledge and practice using regularized logistic regression models. FINDINGS: Mass media were the major source of information about COVID-19. Finances, employment, and physical health were the most frequently mentioned concerns. Overall, participants reported good knowledge and following advice. In Bangladesh, being female and higher levels of health-related quality of life (HRQoL) predicted poor and better knowledge, respectively, while in Pakistan being female predicted better knowledge. Receiving information from television predicted better knowledge in both countries. In Bangladesh, being female, accessing information from multiple media sources, and better HRQoL predicted better practice. In Pakistan, poorer knowledge of COVID-19 prevention measures predicted poorer practice. CONCLUSION: Our paper adds to the literature on people living with SMIs and their knowledge and practices relevant to COVID-19 prevention. Our results emphasize the importance of access to mass and social media for the dissemination of advice and that the likely gendered uptake of both knowledge and practice requires further attention.

Can achievement at medical admission tests predict future performance in postgraduate clinical assessments? A UK-based national cohort study.

OBJECTIVE: To determine whether scores on two undergraduate admissions tests (BioMedical Admissions Test (BMAT) and University Clinical Aptitude Test (UCAT)) predict performance on the postgraduate Membership of the Royal Colleges of Physicians (MRCP) examination, including the clinical examination Practical Assessment of Clinical Examination Skills (PACES). DESIGN: National cohort study. SETTING: Doctors who graduated medical school between 2006 and 2018. PARTICIPANTS: 3045 doctors who had sat BMAT, UCAT and the MRCP. PRIMARY OUTCOME MEASURES: Passing each section of the MRCP at the first attempt, including the clinical assessment PACES. RESULTS: Several BMAT and UCAT subtest scores displayed incremental predictive validity for performance on the first two (written) parts of the MRCP. Only aptitude and skills on BMAT (OR 1.34, 1.08 to 1.67, p=0.01) and verbal reasoning on UCAT (OR 1.34, 1.04 to 1.71, p=0.02) incrementally predicted passing PACES at the first attempt. CONCLUSIONS: Our results imply that the abilities assessed by aptitude and skills and verbal reasoning may be the most important cognitive attributes, of those routinely assessed at selection, for predicting future clinical performance. Selectors may wish to consider placing particular weight on scales assessing these attributes if they wish to select applicants likely to become more competent clinicians. These results are potentially relevant in an international context too, since many admission tests used globally, such as the Medical College Admission Test, assess similar abilities.

Technology Matters: Machine learning approaches to personalised child and adolescent mental health care.

There has been much interest in the potential for machine learning and artificial intelligence to enhance health care. In this article, we discuss the potential applications of the technology to child and adolescent mental health services (CAMHS). We also outline the four key criteria that are likely to be necessary for automated prediction to be translated into clinical benefit. These relate to the choice of task to be automated, the nature of the available data, the methods applied and the context of the system to be implemented.

Predicting relapse or recurrence of depression: systematic review of prognostic models.

BACKGROUND: Relapse and recurrence of depression are common, contributing to the overall burden of depression globally. Accurate prediction of relapse or recurrence while patients are well would allow the identification of high-risk individuals and may effectively guide the allocation of interventions to prevent relapse and recurrence. AIMS: To review prognostic models developed to predict the risk of relapse, recurrence, sustained remission, or recovery in adults with remitted major depressive disorder. METHOD: We searched the Cochrane Library (current issue); Ovid MEDLINE (1946 onwards); Ovid Embase (1980 onwards); Ovid PsycINFO (1806 onwards); and Web of Science (1900 onwards) up to May 2021. We included development and external validation studies of multivariable prognostic models. We assessed risk of bias of included studies using the Prediction model risk of bias assessment tool (PROBAST). RESULTS: We identified 12 eligible prognostic model studies (11 unique prognostic models): 8 model development-only studies, 3 model development and external validation studies and 1 external validation-only study. Multiple estimates of performance measures were not available and meta-analysis was therefore not necessary. Eleven out of the 12 included studies were assessed as being at high overall risk of bias and none examined clinical utility. CONCLUSIONS: Due to high risk of bias of the included studies, poor predictive performance and limited external validation of the models identified, presently available clinical prediction models for relapse and recurrence of depression are not yet sufficiently developed for deploying in clinical settings. There is a need for improved prognosis research in this clinical area and future studies should conform to best practice methodological and reporting guidelines.