BACKGROUND: Young people's mental health and well-being is an important concern in the UK. Provision of education and support to schools has been highlighted as an area for improvement; however, evidence-based programmes are scarce and costly. AIMS: To provide an acceptable education programme to improve pupils' confidence and knowledge of mental health and well-being. It covered the mental and emotional well-being outcomes set by the Scottish Government in their schools' curriculum. METHOD: Lessons were designed by A.P. and delivered by volunteer doctors and medical students, and supervised by a psychiatrist. Outcomes were measured using questionnaires before and after lessons with optional comments. RESULTS: PsychEd was piloted in 2016 in six schools to pupils between the ages of 11 and 18. There was a statistically significant improvement in pupil confidence and knowledge after the lessons (P < 0.001). Of the pupils 84% felt that having lessons on mental health was useful. Qualitative feedback was also collected and coded into positive, constructive and negative comments. In total, 72% of pupil comments were positive. CONCLUSIONS: PsychEd showed promising results. Future areas of development include reaching a greater number of local authority schools, longer training for volunteers and provision of teaching materials to teachers for their own use. DECLARATION OF INTEREST: None.
In: Alcohol and alcoholism: the international journal of the Medical Council on Alcoholism (MCA) and the journal of the European Society for Biomedical Research on Alcoholism (ESBRA), Band 48, Heft 4, S. 433-444
Abstract Major depressive disorder often originates in adolescence and is associated with long-term functional impairment. Mechanistically characterizing this heterogeneous illness could provide important leads for optimizing treatment. Importantly, reward learning is known to be disrupted in depression. In this pilot fMRI study of 21 adolescents (16–20 years), we assessed how reward network disruption impacts specifically on Bayesian belief representations of self-efficacy (SE-B) and their associated uncertainty (SE-U), using a modified instrumental learning task probing activation induced by the opportunity to choose, and an optimal Hierarchical Gaussian Filter computational model. SE-U engaged caudate, nucleus accumbens (NAcc), precuneus, posterior parietal and dorsolateral prefrontal cortex (PFWE < 0.005). Sparse partial least squares analysis identified SE-U striatal activation as associating with one's sense of perceived choice and depressive symptoms, particularly anhedonia and negative feelings about oneself. As Bayesian uncertainty modulates belief flexibility and their capacity to steer future actions, this suggests that these striatal signals may be informative developmentally, longitudinally and in assessing response to treatment.
BACKGROUND: Negative symptoms of psychosis do not respond to the traditional therapy with first- or second-generation antipsychotics and are among main causes of a decrease in quality of life observed in individuals suffering from the disorder. Minocycline, a broad-spectrum tetracyclic antibiotic displaying neuroprotective properties has been suggested as a new potential therapy for negative symptoms. In the two previous clinical trials comparing minocycline and placebo, both added to the standard care, patients receiving minocycline showed increased reduction in negative symptoms. Three routes to neuroprotection by minocycline have been identified: neuroprotection against grey matter loss, anti-inflammatory action and stabilisation of glutamate receptors. However, it is not yet certain what the extent of the benefit of minocycline in psychosis is and what its mechanism is. We present a protocol for a multi-centre double-blind randomised placebo-controlled clinical trial entitled The Benefit of Minocycline on Negative Symptoms of Psychosis: Extent and Mechanism (BeneMin). METHODS: After providing informed consent, 226 participants in the early phase of psychosis will be randomised to receive either 100 mg modified-release capsules of minocycline or similar capsules with placebo for 12 months in addition to standard care. The participants will be tested for outcome variables before and after the intervention period. The extent of benefit will be tested via clinical outcome measures, namely the Positive and Negative Syndrome Scale score, social and cognitive functioning scores, antipsychotic medication dose equivalent and level of weight gain. The mechanism of action of minocycline will be tested via blood screening for circulating cytokines and magnetic resonance imaging with three-dimensional T1-weighted rapid gradient-echo, proton density T2-weighted dual echo and T2*-weighted gradient echo planar imaging with N-back task and resting state. Eight research centres in UK and 15 National Health Service Trusts and Health Boards will be involved in recruiting participants, performing the study and analysing the data. DISCUSSION: The BeneMin trial can inform as to whether in minocycline we have found a new and effective therapy against negative symptoms of psychosis. The European Union Clinical Trial Register: EudraCT 2010-022463-35 with the registration finalised in July 2011. The recruitment in the trial started in January 2013 with the first patient recruited in March 2013.
Acknowledgements We would like to thank all of the patients, relatives and control individuals who participated in the study. We are indebted to the late Prof. Walter Muir, Chair of Developmental Psychiatry and Honorary Consultant in Learning Disability Psychiatry, University of Edinburgh, who initiated these studies and whose work was dedicated to the welfare of the patients who generously participated. We are also grateful to Mrs. Pat Malloy for her assistance with DNA collection and MAQ assays screening of the Scottish samples. The Scottish sample collection was supported by a grant from the Chief Scientist Office (CSO), part of the Scottish Government Health and Social Care Directorates. This research was funded by grants from the CSO to B.S.P. (grant CZB/4/610), The Academy of Medical Sciences/Wellcome Trust to M.J. (grant R41455) and The RS Macdonald Charitable Trust (grant D21419 together with J.H.), the Swedish Research Council (grants 2003-5158 and 2006-4472), the Medical Faculty, Umeå University, and the County Councils of Västerbotten and Norrbotten, Sweden, as well as by grants from the Fund for Scientific Research Flanders (FWO-F), the Industrial Research Fund (IWT) and the Special Research Fund of the University of Antwerp, Belgium. M.J. is funded by a Wellcome Trust Clinical Research Fellowship for MB PhD graduates (R42811). We acknowledge the contribution of the personnel of the VIB Genetic Service Facility (http://www.vibgeneticservicefacility.be/) for the genetic analysis of the Swedish samples. Research nurses Gunnel Johansson, Lotta Kronberg, Tage Johansson and Lisbeth Bertilsson are thankfully acknowledged for their help and expertise. The Betula Study was funded by the Swedish Research Council (grants 345-2003-3883 and 315-2004-6977). We also acknowledge the contribution by the staff in the Betula project ; Peer reviewed ; Publisher PDF
ACKNOWLEDGEMENTS We would like to thank all of the Generation Scotland participants for their contribution to this study. We also thank the research assistants, clinicians and technicians for their help in collecting the data. Generation Scotland received core support from the Chief Scientist Office of the Scottish Government Health Directorates [CZD/16/6] and the Scottish Funding Council [HR03006] and is currently supported by the Wellcome Trust [216767/Z/19/Z]. This study was also supported and funded by the Wellcome Trust Strategic Award 'Stratifying Resilience and Depression Longitudinally' (STRADL) (Reference 104036/Z/14/Z). We acknowledge the support of the British Heart Foundation (RE/18/5/34216). CG is supported by the Medical Research Council and the University of Edinburgh through the Precision Medicine Doctoral Training Programme. MCB is supported by a Guarantors of Brain Non-Clinical Post-Doctoral Fellowship. JMW is funded by the UK Dementia Research Institute which is funded by the UK Medical Research Council, Alzheimer's Research UK and Alzheimer's Society ; Peer reviewed ; Publisher PDF
Funding Information: Generation Scotland received core support from the Chief Scientist Office of the Scottish Government Health Directorates [CZD/16/6] and the Scottish Funding Council [HR03006] and is currently supported by the Wellcome Trust [216767/Z/19/Z]. Genotyping of the GS:SFHS samples was carried out by the Genetics Core Laboratory at the Edinburgh Clinical Research Facility, University of Edinburgh, Scotland and was funded by the Medical Research Council UK and the Wellcome Trust (Wellcome Trust Strategic Award "STratifying Resilience and Depression Longitudinally" (STRADL) Reference 104036/Z/14/Z). CG is supported by The Medical Research Council and The University of Edinburgh through the Precision Medicine Doctoral Training program. SRC is supported by the UK Medical Research Council [MR/R024065/1] and a National Institutes of Health (NIH) research grant R01AG054628. Acknowledgements The authors thank all of the STRADL and Generation Scotland participants for their time and effort taking part in this study. We would also like to thank all of the research assistants, clinicians and technicians for their help in the collecting this data. ; Peer reviewed ; Publisher PDF
PSYSCAN Consortium. ; In the last 2 decades, several neuroimaging studies investigated brain abnormalities associated with the early stages of psychosis in the hope that these could aid the prediction of onset and clinical outcome. Despite advancements in the field, neuroimaging has yet to deliver. This is in part explained by the use of univariate analytical techniques, small samples and lack of statistical power, lack of external validation of potential biomarkers, and lack of integration of nonimaging measures (eg, genetic, clinical, cognitive data). PSYSCAN is an international, longitudinal, multicenter study on the early stages of psychosis which uses machine learning techniques to analyze imaging, clinical, cognitive, and biological data with the aim of facilitating the prediction of psychosis onset and outcome. In this article, we provide an overview of the PSYSCAN protocol and we discuss benefits and methodological challenges of large multicenter studies that employ neuroimaging measures. ; The PSYSCAN Project is supported by grant agreement no. 603196 under the European Union's Seventh Framework Programme. ; Peer reviewed
PSYSCAN Consortium. ; In the last 2 decades, several neuroimaging studies investigated brain abnormalities associated with the early stages of psychosis in the hope that these could aid the prediction of onset and clinical outcome. Despite advancements in the field, neuroimaging has yet to deliver. This is in part explained by the use of univariate analytical techniques, small samples and lack of statistical power, lack of external validation of potential biomarkers, and lack of integration of nonimaging measures (eg, genetic, clinical, cognitive data). PSYSCAN is an international, longitudinal, multicenter study on the early stages of psychosis which uses machine learning techniques to analyze imaging, clinical, cognitive, and biological data with the aim of facilitating the prediction of psychosis onset and outcome. In this article, we provide an overview of the PSYSCAN protocol and we discuss benefits and methodological challenges of large multicenter studies that employ neuroimaging measures. ; The PSYSCAN Project is supported by grant agreement no. 603196 under the European Union's Seventh Framework Programme.
The 10Kin1day workshop was generously sponsored by the Neuroscience and Cognition program Utrecht (NCU) of the Utrecht University (https://www.uu.nl/en/research/neuroscience-and-cognition-utrecht), the ENIGMA consortium (http://enigma.ini.usc.edu), and personal grants: MvdH: NWO-VIDI (452-16-015), MQ Fellowship; SB-C: the Wellcome Trust; Medical Research Council UK; NIHR CLAHRC for Cambridgeshire and Peterborough Foundation National Health Services Trust; Autism Research Trust; LB: New Investigator Award, Canadian Institutes of Health Research; Dara Cannon: Health Research Board (HRB), Ireland (grant code HRA-POR-2013-324); SC: Research Grant Council (Hong Kong)-GRF 14101714; Eveline Crone: ERC-2010-StG-263234; UD: DFG, grant FOR2107 DA1151/5-1, DA1151/5-2, SFB-TRR58, Project C09, IZKF, grant Dan3/012/17; SD: MRC-RFA-UFSP-01-2013 (Shared Roots MRC Flagship grant); TF: Marie Curie Programme, International Training Programme, r'Birth; DG: National Science Centre (UMO-2011/02/A/NZ5/00329); BG: National Science Centre (UMO-2011/02/A/NZ5/00329); JH: Western Sydney University Postgraduate Research Award; LH: Science Foundation Ireland, ERC; HH: Research Grant Council (Hong Kong)-GRF 14101714; LJ: Velux Stiftung, grant 369 & UZH University Research Priority Program Dynamics of Healthy Aging; AJ: DFG, grant FOR2107 JA 1890/7-1; KJ: National Science Centre (UMO-2013/09/N/HS6/02634); VK: The Russian Foundation for Basic Research (grant code 15-06-05758 A); TK: DFG, grant FOR2107 KI 588/14-1, DFG, grant FOR2107 KI 588/15-1; AK: DFG, grant FOR2107 KO 4291/4-1, DFG, grant FOR2107 KO 4291/3-1; IL: The Russian Foundation for Basic Research (grant code 15-06-05758 A); EL: Health and Medical Research Fund - 11121271; SiL: NHMRC-ARC Dementia Fellowship 1110414, NHMRC Dementia Research Team Grant 1095127, NHMRC Project Grant 1062319; CL-J: 537-2011, 2014-849; AM: Wellcome Trust Strategic Award (104036/Z/14/Z), MRC Grant MC_PC_17209; CM: Heisenberg-Grant, German Research Foundation, DFG MO 2363/3-2; PM: Foundation for Science and Technology, Portugal - PDE/BDE/113601/2015; KN: National Science Centre (UMO-2011/02/A/NZ5/00329); PN: National Science Centre (UMO-2013/09/N/HS6/02634); JiP: NWO-Veni 451-10-007; PaR: PER and US would like to thank the Schizophrenia Research Institute and the Chief-Investigators of the Australian Schizophrenia Research Bank V. Carr, U. Schall, R. Scott, A. Jablensky, B. Mowry, P. Michie, S. Catts, F. Henskens, and C. Pantelis; AS: National Science Centre (UMO-2011/02/A/NZ5/00329); SS: European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 707730; CS-M: Carlos III Health Institute (PI13/01958), Carlos III Health Institute (PI16/00889), Carlos III Health Institute (CPII16/00048); ES: National Science Centre (UMO-2011/02/A/NZ5/00329); AT: The Russian Foundation for Basic Research (grant code 15-06-05758 A); DT-G: PI14/00918, PI14/00639; Leonardo Tozzi: Marie Curie Programme, International Training Programme, r'Birth; SV: IMPRS Neurocom stipend; TvE: National Center for Research Resources at the National Institutes of Health (grant numbers: NIH 1 U24 RR021992 (Function Biomedical Informatics Research Network), NIH 1 U24 RR025736-01 (Biomedical Informatics Research Network Coordinating Center; http://www.birncommunity.org) and the NIH Big Data to Knowledge (BD2K) award (U54 EB020403 to Paul Thompson). NvH: NWO-VIDI (452-11-014); MW: National Science Centre (UMO-2011/02/A/NZ5/00329); Veronica O'Keane: Meath Foundation; AV and AW: CRC Obesity Mechanism (SFB 1052) Project A1 funded by DFG. The funding sources had no role in the study design, data collection, analysis, and interpretation of the data ; We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain. Ongoing grand-scale projects like the European Human Brain Project (1), the US Brain Initiative (2), the Human Connectome Project (3), the Chinese Brainnetome (4) and exciting world-wide neuroimaging collaborations such as ENIGMA (5) herald the new era of big neuroscience. In conjunction with these major undertakings, there is an emerging trend for bottom-up initiatives, starting with small-scale projects built upon existing collaborations and infrastructures. As described by Mainen et al. (6), these initiatives are centralized around self-organized groups of researchers working on the same challenges and sharing interests and specialized expertise. These projects could scale and open up to a larger audience and other disciplines over time, eventually lining up and merging their findings with other programs to make the bigger picture.