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.

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.

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.

Prognostic models for predicting relapse or recurrence of major depressive disorder in adults.

BACKGROUND: Relapse (the re-emergence of depressive symptoms after some level of improvement but preceding recovery) and recurrence (onset of a new depressive episode after recovery) are common in depression, lead to worse outcomes and quality of life for patients and exert a high economic cost on society. Outcomes can be predicted by using multivariable prognostic models, which use information about several predictors to produce an individualised risk estimate. The ability to accurately predict relapse or recurrence while patients are well (in remission) would allow the identification of high-risk individuals and may improve overall treatment outcomes for patients by enabling more efficient allocation of interventions to prevent relapse and recurrence. OBJECTIVES: To summarise the predictive performance of prognostic models developed to predict the risk of relapse, recurrence, sustained remission or recovery in adults with major depressive disorder who meet criteria for remission or recovery. SEARCH METHODS: 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 2020. We also searched sources of grey literature, screened the reference lists of included studies and performed a forward citation search. There were no restrictions applied to the searches by date, language or publication status . SELECTION CRITERIA: We included development and external validation (testing model performance in data separate from the development data) studies of any multivariable prognostic models (including two or more predictors) to predict relapse, recurrence, sustained remission, or recovery in adults (aged 18 years and over) with remitted depression, in any clinical setting. We included all study designs and accepted all definitions of relapse, recurrence and other related outcomes. We did not specify a comparator prognostic model. DATA COLLECTION AND ANALYSIS: Two review authors independently screened references; extracted data (using a template based on the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS)); and assessed risks of bias of included studies (using the Prediction model Risk Of Bias ASsessment Tool (PROBAST)). We referred any disagreements to a third independent review author. Where we found sufficient (10 or more) external validation studies of an individual model, we planned to perform a meta-analysis of its predictive performance, specifically with respect to its calibration (how well the predicted probabilities match the observed proportions of individuals that experience the outcome) and discrimination (the ability of the model to differentiate between those with and without the outcome). Recommendations could not be qualified using the GRADE system, as guidance is not yet available for prognostic model reviews. MAIN RESULTS: We identified 11 eligible prognostic model studies (10 unique prognostic models). Seven were model development studies; three were model development and external validation studies; and one was an external validation-only study. Multiple estimates of performance measures were not available for any of the models and, meta-analysis was therefore not possible. Ten out of the 11 included studies were assessed as being at high overall risk of bias. Common weaknesses included insufficient sample size, inappropriate handling of missing data and lack of information about discrimination and calibration. One paper (Klein 2018) was at low overall risk of bias and presented a prognostic model including the following predictors: number of previous depressive episodes, residual depressive symptoms and severity of the last depressive episode. The external predictive performance of this model was poor (C-statistic 0.59; calibration slope 0.56; confidence intervals not reported). None of the identified studies examined the clinical utility (net benefit) of the developed model. AUTHORS' CONCLUSIONS: Of the 10 prognostic models identified (across 11 studies), only four underwent external validation. Most of the studies (n = 10) were assessed as being at high overall risk of bias, and the one study that was at low risk of bias presented a model with poor predictive performance. There is a need for improved prognostic research in this clinical area, with future studies conforming to current best practice recommendations for prognostic model development/validation and reporting findings in line with the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement.

Differential attainment in the MRCPsych according to ethnicity and place of qualification between 2013 and 2018: a UK cohort study.

PURPOSE OF THE STUDY: To explore if differential pass rates exist in the clinical component of the UK postgraduate clinical psychiatry exam, the Clinical Assessment of Skills and Competencies (CASC), according to ethnicity and place of qualification (UK vs EEA vs overseas graduates). STUDY DESIGN: Observational study using data from the UK Medical Education Database for 2140 doctors sitting the CASC for the first time between 2013 and 2018. RESULTS: After controlling for age, sex, time of sitting and performance in the written components of the MRCPsych, differences in CASC pass rates persisted between UK graduates self-identifying as Black and Minority Ethnicity (BME) and non-BME (OR for passing 0.36, 95% CI 0.23 to 0.56, p<0.001). Both EEA (OR 0.25, 0.15 to 0.40, p<0.001) and overseas graduates (OR 0.07, 0.05 to 0.11, p<0.001) were less likely to pass the CASC at first attempt, even after controlling for the influence of educational and background variables. These groups, on average, had lower scores on written exams with substantial content relating to procedural skills (eg, critical appraisal) rather than pure recall of factual knowledge. CONCLUSIONS: Substantial differences exist in clinical examination performance between UK BME and non-BME candidates, as well as between UK and non-UK graduates. These differences are not explained by differing levels of clinical knowledge. In the interests of equality, this situation requires further investigation and remediation. Future research should focus on understanding how potential bias may be acting within different stages of recruitment, training and assessment within psychiatry.

Situational judgement test validity for selection: A systematic review and meta-analysis.

CONTEXT: Situational judgement tests (SJTs) are widely used to evaluate 'non-academic' abilities in medical applicants. However, there is a lack of understanding of how their predictive validity may vary across contexts. We conducted a systematic review and meta-analysis to synthesise existing evidence relating to the validity of such tools for predicting outcomes relevant to interpersonal workplace performance. METHODS: Searches were conducted in relevant databases to June 2019. Study quality and risk of bias were assessed using the Quality In Prognosis Studies (QUIPS) tool. Results were pooled using random effects meta-analysis and meta-regressions. RESULTS: Initially, 470 articles were identified, 218 title or abstracts were reviewed, and 44 full text articles were assessed with 30 studies meeting the final inclusion criteria and were judged, overall, to be at moderate risk of bias. Of these, 26 reported correlation coefficients relating to validity, with a pooled estimate of 0.32 (95% confidence interval 0.26 to 0.39, P < .0001). Considerable heterogeneity was observed (I2  = 96.5%) with the largest validity coefficients tending to be observed for postgraduate, rather than undergraduate, selection studies (ß = 0.23, 0.11 to 0.36, P < .001). The correction of validity coefficients for attenuation was also independently associated with larger effects (ß = 0.13, 0.03 to 0.23, P = .01). No significant associations with test medium (video vs text format), cross-sectional study design, or period of assessment (one-off vs longer-term) were observed. Where reported, the scores generally demonstrated incremental predictive validity, over and above tests of knowledge and cognitive ability. CONCLUSIONS: The use of SJTs in medical selection is supported by the evidence. The observed trend relating to training stage requires investigation. Further research should focus on developing robust criterion-relevant outcome measures that, ideally, capture interpersonal aspects of typical workplace performance. This will facilitate additional work identifying the optimal place of SJTs within particular selection contexts and further enhancing their effectiveness.

Situational judgement tests for selection: Traditional vs construct-driven approaches.

CONTEXT: Historically, situational judgement tests (SJTs) have been widely used for personnel selection. Their use in medical selection in Europe is growing, with plans for further expansion into North America and Australasia, in an attempt to measure and select on 'non-academic' personal attributes. However, there is a lack of clarity regarding what such tests actually measure and how they should be designed, scored and implemented within the medical and health education selection process. In particular, the theoretical basis from which such tests are developed will determine the scoring options available, influencing their psychometric properties and, ultimately, their validity. METHODS: The aim of this article is to create an awareness of the previous theory and practice that has informed SJT development. We describe the emerging interest in the use of the SJT format to measure specific constructs (eg 'resilience', 'dependability', etc.), drawing on the tradition of 'individual differences' psychology. We compare and contrast this newer 'construct-driven' method with the traditional, pragmatic approach to SJT creation, often employed by organisational psychologists. Making reference to measurement theory, we highlight how the anticipated psychometric properties of traditional vs construct-driven SJTs are likely to differ. CONCLUSIONS: Compared to traditional SJTs, construct-driven SJTs have a strong theoretical basis, are uni- rather than multidimensional, and may behave more like personality self-report instruments. Emerging evidence also suggests that construct-driven SJTs have comparable predictive validity for workplace performance, although they may be more prone to 'faking' effects. It is possible that construct-driven approaches prove more appropriate at early stages of medical selection, where candidates have little or no health care work experience. Conversely, traditional SJTs may be more suitable for specialty recruitment, where a range of hypothetical workplace scenarios can be sampled in assessments.

Evaluating the recruitment process into UK anaesthesia core training: a national data linkage study of doctors' performance at selection and subsequent postgraduate training.

PURPOSE OF THE STUDY: To explore which factors increase the likelihood of being deemed appointable to core anaesthesia training in the UK and whether those factors subsequently predict performance in postgraduate training. STUDY DESIGN: Observational study linking UK medical specialty recruitment data with postgraduate educational performance, as measured by Annual Review of Competence Progression (ARCP) outcomes. Data were available for 2782 trainee doctors recruited to anaesthesia core training from 2012 to 2016 with at least one subsequent ARCP outcome. RESULTS: Both higher interview and shortlisting scores were independent and statistically significant (p≤0.001) predictors of more satisfactory ARCP outcomes, even after controlling for the influence of postgraduate exam failure. It was noted that a number of background variables (eg, age at application) were independently associated with the odds of being deemed appointable at recruitment. Of these, increasing age and experience were also negative predictors of subsequent ARCP rating. These influences became statistically non-significant once ARCP outcomes associated with exam failure were excluded. CONCLUSIONS: The predictors of 'appointability' largely also predict subsequent performance in postgraduate training, as indicated by ARCP ratings. This provides evidence for the validity of the selection process. Our results also suggest that greater weight could be applied to shortlisting scores within the overall process of ranking applicants for posts.

The psychometrics of psychosis - assessing and rating perceptual and ideational disturbance in adolescents.

BACKGROUND: The early recognition and management of psychosis spectrum disorders is associated with superior outcomes in affected individuals. However, this can be challenging for numerous reasons. This article provides perspectives on the effective evaluation and rating of potentially psychotic phenomena young people. We compare and contrast two widely used instruments that can support this process. FINDINGS: The Comprehensive Assessment for At-Risk Mental States (CAARMS) is used to explore potentially psychotic experiences in young people perceived to be at risk of an emerging or imminent psychosis. There is evidence to support its reliability and, to some extent, the predictive validity of the resultant scores. However, relatively low short-medium transition rates to psychosis in 'positive' cases suggest that its use as a screening instrument should be restricted to groups who show some indication of impending risk (e.g. help-seeking, distress, declining functioning, perceptual disturbance, etc.). In contrast, the Positive and Negative Syndrome Scale (PANSS) is calibrated to rate symptoms in those with an established psychosis, especially those with a diagnosis related to the schizophrenia spectrum. Consequently, the PANSS is useful for evaluating the clinical course and outcomes of psychotic illness. CONCLUSIONS: Although neither instrument is designed specifically for use in those under 18, with care they can be used to effectively support the management of adolescents reporting perceptual and ideational disturbance. However, it is important that any instrument ratings are placed meaningfully in the context of the overall clinical picture and all available information.

Modelling out-of-area admissions.

Out-of-area (OOA) placements occur when patients cannot be admitted to local facilities, which can be extremely stressful for patients and families. Thus, the Department of Health aims to eliminate the need for OOA admissions. Using data from a UK mental health trust we developed a 'virtual mental health ward' to evaluate the potential impact of referral rates and length of stay (LOS) on OOA rates. The results indicated OOA rates were equally sensitive to LOS and referral rate. This suggests that investment in community services that reduce both LOS and referral rates are required to meaningfully reduce OOA admission rates.Declaration of interestP.A.T. holds an honorary consultant contract with the Tees, Esk and Wear Valleys NHS Foundation Trust.

Rise of the machines? Machine learning approaches and mental health: opportunities and challenges.

Machine learning methods are being increasingly applied to physical healthcare. In this article we describe some of the potential benefits, challenges and limitations of this approach in a mental health context. We provide a number of examples where machine learning could add value beyond conventional statistical modelling.Declaration of interestNone.

The ability of 'non-cognitive' traits to predict undergraduate performance in medical schools: a national linkage study.

BACKGROUND: In addition to the evaluation of educational attainment and intellectual ability there has been interest in the potential to select medical school applicants on non-academic qualities. Consequently, a battery of self-report measures concerned with assessing 'non-cognitive' traits was piloted as part of the UK Clinical Aptitude Test (UKCAT) administration to evaluate their potential to be used in selection. METHODS: The four non-cognitive instruments piloted were: 1) the Libertarian-communitarian scale, (2) The NACE (narcissism, aloofness, confidence and empathy, (3) the MEARS (Managing emotions and resilience scale; self-esteem, optimism, control, self-discipline, emotional-nondefensiveness and faking, and (4) an abridged version of instruments (1) and (2) combined. Non-cognitive scores and sociodemographic characteristics were available for 14,387 applicants. A series of univariable and multivariable analyses were conducted in order to assess the ability of the non-cognitive scores to predict knowledge and skills-based performance, as well as the odds of passing each academic year at first attempt. Non-cognitive scores and medical performance were standardised within cohorts. RESULTS: The scores on the non-cognitive scales showed only very small (magnitude of standardised betas< 0.2), though sometimes statistically significant (p < 0.01) univariable associations with subsequent performance on knowledge or skills-based assessments. The only statistically significant association between the non-cognitive scores and the probability of passing an academic year at first attempt was the narcissism score from one the abridged tests (OR 0.84,95% confidence intervals 0.71 to 0.97, p = 0.02). CONCLUSIONS: Our findings are consistent with previously published research. The tests had a very limited ability to predict undergraduate academic performance, though further research on identifying narcissism in medical students may be warranted. However, the validity of such self-report tools in high-stakes settings may be affected, making such instruments unlikely to add value within the selection process.

Predictors of fitness to practise declarations in UK medical undergraduates.

BACKGROUND: Misconduct during medical school predicts subsequent fitness to practise (FtP) events in doctors, but relatively little is known about which factors are associated with such issues during undergraduate education. This study exploits the newly created UK medical education database (UKMED), with the aim of identifying predictors of conduct or health-related issues that could potentially impair FtP. The findings would have implications for policies related to both the selection and support of medical students. METHODS: Data were available for 14,379 students obtaining provisional registration with the General Medical Council who started medical school in 2007 and 2008. FtP declarations made by students were available, as were various educational and demographic predictor variables, including self-report 'personality measures' for students who participated in UK Clinical Aptitude Test (UKCAT) pilot studies. Univariable and multivariable logistic regression models were developed to evaluate the predictors of FtP declarations. RESULTS: Significant univariable predictors (p < 0.05) for conduct-related declarations included male gender, white ethnicity and a non-professional parental background. Male gender (OR 3.07) and higher 'self-esteem' (OR 1.45) were independently associated with an increased risk of a conduct issue. Female gender, a non-professional background, and lower self-reported 'confidence' were, among others, associated with increased odds of a health-related declaration. Only 'confidence' was a significant independent predictor of a health declaration (OR 0.69). Female gender, higher UKCAT score, a non-professional background and lower 'confidence' scores were significant predictors of reported depression, and the latter two variables were independent predictors of declared depression. CONCLUSIONS: White ethnicity and UK nationality were associated with increased odds of both conduct and health-related declarations, as were certain personality traits. Students from non-professional backgrounds may be at increased risk of depression and therefore could benefit from targeted support. The small effect sizes observed for the 'personality measures' suggest they would offer little potential benefit for selection, over and above those measures already in use.

Predicting fitness to practise events in international medical graduates who registered as UK doctors via the Professional and Linguistic Assessments Board (PLAB) system: a national cohort study.

BACKGROUND: International medical graduates working in the UK are more likely to be censured in relation to fitness to practise compared to home graduates. Performance on the General Medical Council's (GMC's) Professional and Linguistic Assessments Board (PLAB) tests and English fluency have previously been shown to predict later educational performance in this group of doctors. It is unknown whether the PLAB system is also a valid predictor of unprofessional behaviour and malpractice. The findings would have implications for regulatory policy. METHODS: This was an observational study linking data relating to fitness to practise events (referral or censure), PLAB performance, demographic variables and English language competence, as evaluated via the International English Language Test System (IELTS). Data from 27,330 international medical graduates registered with the GMC were analysed, including 210 doctors who had been sanctioned in relation to at least one fitness to practise issue. The main outcome was risk of eventual censure (including a warning). RESULTS: The significant univariable educational predictors of eventual censure (versus no censures or referrals) were lower PLAB part 1 (hazard ratio [HR], 0.99; 95% confidence interval, 0.98 to 1.00) and part 2 scores (HR, 0.94; 0.91 to 0.97) at first sitting, multiple attempts at both parts of the PLAB, lower IELTS reading (HR, 0.79; 0.65 to 0.94) and listening scores (HR, 0.76; 0.62 to 0.93) and higher IELTS speaking scores (HR, 1.28; 1.04 to 1.57). Multiple resits at either part of the PLAB and higher IELTS speaking score (HR, 1.49; 1.20 to 1.84) were also independent predictors of censure. We estimated that the proposed limit of four attempts at both parts of the PLAB would reduce the risk in this entire group by only approximately two censures per 5 years in this group of doctors. CONCLUSIONS: Making the PLAB, or any replacement assessment, more stringent and raising the required standards of English reading and listening may result in fewer fitness to practice events in international medical graduates. However, the number of PLAB resits permitted would have to be further capped to meaningfully impact the risk of sanctions in this group of doctors.

Predictive validity of the UKCAT for medical school undergraduate performance: a national prospective cohort study.

BACKGROUND: The UK Clinical Aptitude Test (UKCAT) has been shown to have a modest but statistically significant ability to predict aspects of academic performance throughout medical school. Previously, this ability has been shown to be incremental to conventional measures of educational performance for the first year of medical school. This study evaluates whether this predictive ability extends throughout the whole of undergraduate medical study and explores the potential impact of using the test as a selection screening tool. METHODS: This was an observational prospective study, linking UKCAT scores, prior educational attainment and sociodemographic variables with subsequent academic outcomes during the 5 years of UK medical undergraduate training. The participants were 6812 entrants to UK medical schools in 2007-8 using the UKCAT. The main outcome was academic performance at each year of medical school. A receiver operating characteristic (ROC) curve analysis was also conducted, treating the UKCAT as a screening test for a negative academic outcome (failing at least 1 year at first attempt). RESULTS: All four of the UKCAT scale scores significantly predicted performance in theory- and skills-based exams. After adjustment for prior educational achievement, the UKCAT scale scores remained significantly predictive for most years. Findings from the ROC analysis suggested that, if used as a sole screening test, with the mean applicant UKCAT score as the cut-off, the test could be used to reject candidates at high risk of failing at least 1 year at first attempt. However, the 'number needed to reject' value would be high (at 1.18), with roughly one candidate who would have been likely to pass all years at first sitting being rejected for every higher risk candidate potentially declined entry on this basis. CONCLUSIONS: The UKCAT scores demonstrate a statistically significant but modest degree of incremental predictive validity throughout undergraduate training. Whilst the UKCAT could be considered a fairly crude screening tool for future academic performance, it may offer added value when used in conjunction with other selection measures. Future work should focus on the optimum role of such tests within the selection process and the prediction of post-graduate performance.

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.

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.

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.