Demographic, clinical, and service-use characteristics related to the clinician’s recommendation to transition from child to adult mental health services

Purpose: The service configuration with distinct child and adolescent mental health services (CAMHS) and adult mental health services (AMHS) may be a barrier to continuity of care. Because of a lack of transition policy, CAMHS clinicians have to decide whether and when a young person should transition to AMHS. This study describes which characteristics are associated with the clinicians’ advice to continue treatment at AMHS. Methods: Demographic, family, clinical, treatment, and service-use characteristics of the MILESTONE cohort of 763 young people from 39 CAMHS in Europe were assessed using multi-informant and standardized assessment tools. Logistic mixed models were fitted to assess the relationship between these characteristics and clinicians’ transition recommendations. Results: Young people with higher clinician-rated severity of psychopathology scores, with self- and parent-reported need for ongoing treatment, with lower everyday functional skills and without self-reported psychotic experiences were more likely to be recommended to continue treatment. Among those who had been recommended to continue treatment, young people who used psychotropic medication, who had been in CAMHS for more than a year, and for whom appropriate AMHS were available were more likely to be recommended to continue treatment at AMHS. Young people whose parents indicated a need for ongoing treatment were more likely to be recommended to stay in CAMHS. Conclusion: Although the decision regarding continuity of treatment was mostly determined by a small set of clinical characteristics, the recommendation to continue treatment at AMHS was mostly affected by service-use related characteristics, such as the availability of appropriate services

Cohort profile : demographic and clinical characteristics of the MILESTONE longitudinal cohort of young people approaching the upper age limit of their child mental health care service in Europe

Purpose: The presence of distinct child and adolescent mental health services (CAMHS) and adult mental health services (AMHS) impacts continuity of mental health treatment for young people. However, we do not know the extent of discontinuity of care in Europe nor the effects of discontinuity on the mental health of young people. Current research is limited, as the majority of existing studies are retrospective, based on small samples or used non-standardised information from medical records. The MILESTONE prospective cohort study aims to examine associations between service use, mental health and other outcomes over 24 months, using information from self, parent and clinician reports. Participants: Seven hundred sixty-three young people from 39 CAMHS in 8 European countries, their parents and CAMHS clinicians who completed interviews and online questionnaires and were followed up for 2 years after reaching the upper age limit of the CAMHS they receive treatment at. Findings to date: This cohort profile describes the baseline characteristics of the MILESTONE cohort. The mental health of young people reaching the upper age limit of their CAMHS varied greatly in type and severity: 32.8% of young people reported clinical levels of self-reported problems and 18.6% were rated to be ‘markedly ill’, ‘severely ill’ or ‘among the most extremely ill’ by their clinician. Fifty-seven per cent of young people reported psychotropic medication use in the previous half year. Future plans: Analysis of longitudinal data from the MILESTONE cohort will be used to assess relationships between the demographic and clinical characteristics of young people reaching the upper age limit of their CAMHS and the type of care the young person uses over the next 2 years, such as whether the young person transitions to AMHS. At 2 years follow-up, the mental health outcomes of young people following different care pathways will be compared. Trial registration number: NCT03013595

Population level inference for multivariate MEG analysis

Multivariate analysis is a very general and powerful technique for analysing Magnetoencephalography (MEG) data. An outstanding problem however is how to make inferences that are consistent over a group of subjects as to whether there are condition-specific differences in data features, and what are those features that maximise these differences. Here we propose a solution based on Canonical Variates Analysis (CVA) model scoring at the subject level and random effects Bayesian model selection at the group level. We apply this approach to beamformer reconstructed MEG data in source space. CVA estimates those multivariate patterns of activation that correlate most highly with the experimental design; the order of a CVA model is then determined by the number of significant canonical vectors. Random effects Bayesian model comparison then provides machinery for inferring the optimal order over the group of subjects. Absence of a multivariate dependence is indicated by the null model being the most likely. This approach can also be applied to CVA models with a fixed number of canonical vectors but supplied with different feature sets. We illustrate the method by identifying feature sets based on variable-dimension MEG power spectra in the primary visual cortex and fusiform gyrus that are maximally discriminative of data epochs before versus after visual stimulation

Ecologically or biologically significant areas in the pelagic realm: examples & guidelines–workshop report

no abstrac