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Ballester L, Alayo I, Vilagut G, Mortier P, Almenara J, Cebrià AI, Echeburúa E, Gabilondo A, Gili M, Lagares C, Piqueras JA, Roca M, Soto-Sanz V, Blasco MJ, Castellví P, Miranda-Mendizabal A, Bruffaerts R, Auerbach RP, Nock MK, Kessler RC, Alonso J. Predictive models for first-onset and persistence of depression and anxiety among university students. J Affect Disord 2022; 308:432-441. [PMID: 35398107 DOI: 10.1016/j.jad.2021.10.135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2020] [Revised: 10/21/2021] [Accepted: 10/25/2021] [Indexed: 11/15/2022]
Abstract
BACKGROUND Depression and anxiety are both prevalent among university students. They frequently co-occur and share risk factors. Yet few studies have focused on identifying students at highest risk of first-onset and persistence of either of these conditions. METHODS Multicenter cohort study among Spanish first-year university students. At baseline, students were assessed for lifetime and 12-month Major Depressive Episode and/or Generalized Anxiety Disorder (MDE-GAD), other mental disorders, childhood-adolescent adversities, stressful life events, social support, socio-demographics, and psychological factors using web-based surveys; 12-month MDE-GAD was again assessed at 12-month follow-up. RESULTS A total of 1253 students participated in both surveys (59.2% of baseline respondents; mean age = 18.7 (SD = 1.3); 56.0% female). First-onset of MDE-GAD at follow-up was 13.3%. Also 46.7% of those with baseline MDE-GAD showed persistence at follow-up. Childhood/Adolescence emotional abuse or neglect (OR= 4.33), prior bipolar spectrum disorder (OR= 4.34), prior suicidal ideation (OR=4.85) and prior lifetime symptoms of MDE (ORs=2.33-3.63) and GAD (ORs=2.15-3.75) were strongest predictors of first-onset MDE-GAD. Prior suicidal ideation (OR=3.17) and prior lifetime GAD symptoms (ORs=2.38-4.02) were strongest predictors of MDE-GAD persistence. Multivariable predictions from baseline showed AUCs of 0.76 for first-onset and 0.81 for persistence. 74.9% of first-onset MDE-GAD cases occurred among 30% students with highest predicted risk at baseline. LIMITATIONS Self-report data were used; external validation of the multivariable prediction models is needed. CONCLUSION MDE-GAD among university students is frequent, suggesting the need to implement web-based screening at university entrance that identify those students with highest risk.
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Affiliation(s)
- Laura Ballester
- Health Services Research Group, IMIM (Institut Hospital del Mar d'Investigacions Mèdiques), Barcelona, Spain; Girona University (UdG), Girona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain
| | - Itxaso Alayo
- Health Services Research Group, IMIM (Institut Hospital del Mar d'Investigacions Mèdiques), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain
| | - Gemma Vilagut
- Health Services Research Group, IMIM (Institut Hospital del Mar d'Investigacions Mèdiques), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain
| | - Philippe Mortier
- Health Services Research Group, IMIM (Institut Hospital del Mar d'Investigacions Mèdiques), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain
| | | | - Ana Isabel Cebrià
- Department of Mental Health, Corporació Sanitaria Parc Taulí, Sabadell, Spain; CIBER Salud Mental (CIBERSAM), Madrid, Spain
| | | | - Andrea Gabilondo
- BioDonostia Health Research Institute, Osakidetza, San Sebastián, Spain
| | - Margalida Gili
- Institut Universitari d'Investigació en Ciències de la Salut (IUNICS-IDISBA), Rediapp, University of Balearic Islands (UIB), Palma de Mallorca, Spain
| | | | | | - Miquel Roca
- Institut Universitari d'Investigació en Ciències de la Salut (IUNICS-IDISBA), Rediapp, University of Balearic Islands (UIB), Palma de Mallorca, Spain
| | | | - Maria Jesús Blasco
- Health Services Research Group, IMIM (Institut Hospital del Mar d'Investigacions Mèdiques), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain
| | - Pere Castellví
- International University of Catalonia (UIC), Barcelona, Spain
| | | | - Ronny Bruffaerts
- Universitair Psychiatrisch Centrum (UPC-KUL), Center for Public Health Psychiatry, KULeuven, Leuven, Belgium
| | - Randy P Auerbach
- Department of Psychiatry, Columbia University, New York, United States
| | - Matthew K Nock
- Department of Psychology, Harvard University, Boston, MA, United States
| | - Ronald C Kessler
- Department of Health Care Policy, Harvard Medical School, Boston, MA, United States
| | - Jordi Alonso
- Health Services Research Group, IMIM (Institut Hospital del Mar d'Investigacions Mèdiques), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain; Department of Medicine and Life Scienes, Universitat Pompeu Fabra, Barcelona, Spain.
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Fusar‐Poli P, Correll CU, Arango C, Berk M, Patel V, Ioannidis JP. Preventive psychiatry: a blueprint for improving the mental health of young people. World Psychiatry 2021; 20:200-221. [PMID: 34002494 PMCID: PMC8129854 DOI: 10.1002/wps.20869] [Citation(s) in RCA: 170] [Impact Index Per Article: 56.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Preventive approaches have latterly gained traction for improving mental health in young people. In this paper, we first appraise the conceptual foundations of preventive psychiatry, encompassing the public health, Gordon's, US Institute of Medicine, World Health Organization, and good mental health frameworks, and neurodevelopmentally-sensitive clinical staging models. We then review the evidence supporting primary prevention of psychotic, bipolar and common mental disorders and promotion of good mental health as potential transformative strategies to reduce the incidence of these disorders in young people. Within indicated approaches, the clinical high-risk for psychosis paradigm has received the most empirical validation, while clinical high-risk states for bipolar and common mental disorders are increasingly becoming a focus of attention. Selective approaches have mostly targeted familial vulnerability and non-genetic risk exposures. Selective screening and psychological/psychoeducational interventions in vulnerable subgroups may improve anxiety/depressive symptoms, but their efficacy in reducing the incidence of psychotic/bipolar/common mental disorders is unproven. Selective physical exercise may reduce the incidence of anxiety disorders. Universal psychological/psychoeducational interventions may improve anxiety symptoms but not prevent depressive/anxiety disorders, while universal physical exercise may reduce the incidence of anxiety disorders. Universal public health approaches targeting school climate or social determinants (demographic, economic, neighbourhood, environmental, social/cultural) of mental disorders hold the greatest potential for reducing the risk profile of the population as a whole. The approach to promotion of good mental health is currently fragmented. We leverage the knowledge gained from the review to develop a blueprint for future research and practice of preventive psychiatry in young people: integrating universal and targeted frameworks; advancing multivariable, transdiagnostic, multi-endpoint epidemiological knowledge; synergically preventing common and infrequent mental disorders; preventing physical and mental health burden together; implementing stratified/personalized prognosis; establishing evidence-based preventive interventions; developing an ethical framework, improving prevention through education/training; consolidating the cost-effectiveness of preventive psychiatry; and decreasing inequalities. These goals can only be achieved through an urgent individual, societal, and global level response, which promotes a vigorous collaboration across scientific, health care, societal and governmental sectors for implementing preventive psychiatry, as much is at stake for young people with or at risk for emerging mental disorders.
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Affiliation(s)
- Paolo Fusar‐Poli
- Early Psychosis: Interventions and Clinical‐detection (EPIC) Lab, Department of Psychosis StudiesInstitute of Psychiatry, Psychology & Neuroscience, King's College LondonLondonUK,OASIS Service, South London and Maudsley NHS Foundation TrustLondonUK,Department of Brain and Behavioral SciencesUniversity of PaviaPaviaItaly
| | - Christoph U. Correll
- Department of PsychiatryZucker Hillside Hospital, Northwell HealthGlen OaksNYUSA,Department of Psychiatry and Molecular MedicineZucker School of Medicine at Hofstra/NorthwellHempsteadNYUSA,Center for Psychiatric NeuroscienceFeinstein Institute for Medical ResearchManhassetNYUSA,Department of Child and Adolescent PsychiatryCharité Universitätsmedizin BerlinBerlinGermany
| | - Celso Arango
- Department of Child and Adolescent PsychiatryInstitute of Psychiatry and Mental Health, Hospital General Universitario Gregorio MarañónMadridSpain,Health Research Institute (IiGSM), School of MedicineUniversidad Complutense de MadridMadridSpain,Biomedical Research Center for Mental Health (CIBERSAM)MadridSpain
| | - Michael Berk
- Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Deakin UniversityBarwon HealthGeelongVICAustralia,Department of PsychiatryUniversity of MelbourneMelbourneVICAustralia,Orygen Youth HealthUniversity of MelbourneMelbourneVICAustralia,Florey Institute for Neuroscience and Mental HealthUniversity of MelbourneMelbourneVICAustralia
| | - Vikram Patel
- Department of Global Health and Social MedicineHarvard University T.H. Chan School of Public HealthBostonMAUSA,Department of Global Health and PopulationHarvard T.H. Chan School of Public HealthBostonMAUSA
| | - John P.A. Ioannidis
- Stanford Prevention Research Center, Department of MedicineStanford UniversityStanfordCAUSA,Department of Biomedical Data ScienceStanford UniversityStanfordCAUSA,Department of Epidemiology and Population HealthStanford UniversityStanfordCAUSA
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Nigatu YT, Elton-Marshall T, Wells S, Jankowicz D, Wickens CM, Hamilton HA. The association between COVID-19 diagnosis or having symptoms and anxiety among Canadians: A repeated cross-sectional study. ANXIETY STRESS AND COPING 2021; 34:503-512. [PMID: 34032525 DOI: 10.1080/10615806.2021.1932837] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
BACKGROUND The mental health effects of being diagnosed with COVID-19 are unknown. The present study examined whether individuals or those with someone close to them with a COVID-19 diagnosis differentially experienced anxiety during the pandemic. METHODS Four web-based repeated cross-sectional surveys were conducted among Canadians aged 18 and older (n = 4015) regarding the impact of COVID-19 on mental health between May 8th and July 14th, 2020. Data on sociodemographic, COVID-19 symptoms/diagnoses for self or someone close, and anxiety were collected. Multiple logistic regression analyses were performed controlling for potential confounders. RESULTS Anxiety among individuals affected by the pandemic remained stable over time. Individuals or those with someone close diagnosed with COVID-19 had greater odds of having anxiety (OR = 1.55; 95%CI 1.12, 2.14) compared to those who had not been diagnosed (self or close other) with COVID-19. Individuals or those with someone close to them who had symptoms of COVID-19 had greater odds of having anxiety (OR = 2.08; 95%CI 1.51, 2.87) compared to those who did not report symptoms (self or close other). CONCLUSIONS This evidence highlights the importance of targeted psychosocial interventions for those directly impacted by the COVID-19 virus.
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Affiliation(s)
- Yeshambel T Nigatu
- Institute for Mental Health Policy Research, Centre for Addiction and Mental Health, Toronto, Canada
| | - Tara Elton-Marshall
- Institute for Mental Health Policy Research, Centre for Addiction and Mental Health, Toronto, Canada.,Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.,Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, London
| | - Samantha Wells
- Institute for Mental Health Policy Research, Centre for Addiction and Mental Health, Toronto, Canada.,Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.,Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, London.,Department of Psychiatry, University of Toronto, Toronto, Canada.,School of Psychology, Deakin University, Burwood, Australia
| | - Damian Jankowicz
- Information Management, Centre for Addiction and Mental Health, Toronto, Canada
| | - Christine M Wickens
- Institute for Mental Health Policy Research, Centre for Addiction and Mental Health, Toronto, Canada.,Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.,Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada.,Department of Pharmacology and Toxicology, University of Toronto, Toronto, Canada
| | - Hayley A Hamilton
- Institute for Mental Health Policy Research, Centre for Addiction and Mental Health, Toronto, Canada.,Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
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Salazar de Pablo G, Studerus E, Vaquerizo-Serrano J, Irving J, Catalan A, Oliver D, Baldwin H, Danese A, Fazel S, Steyerberg EW, Stahl D, Fusar-Poli P. Implementing Precision Psychiatry: A Systematic Review of Individualized Prediction Models for Clinical Practice. Schizophr Bull 2020; 47:284-297. [PMID: 32914178 PMCID: PMC7965077 DOI: 10.1093/schbul/sbaa120] [Citation(s) in RCA: 86] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
BACKGROUND The impact of precision psychiatry for clinical practice has not been systematically appraised. This study aims to provide a comprehensive review of validated prediction models to estimate the individual risk of being affected with a condition (diagnostic), developing outcomes (prognostic), or responding to treatments (predictive) in mental disorders. METHODS PRISMA/RIGHT/CHARMS-compliant systematic review of the Web of Science, Cochrane Central Register of Reviews, and Ovid/PsycINFO databases from inception until July 21, 2019 (PROSPERO CRD42019155713) to identify diagnostic/prognostic/predictive prediction studies that reported individualized estimates in psychiatry and that were internally or externally validated or implemented. Random effect meta-regression analyses addressed the impact of several factors on the accuracy of prediction models. FINDINGS Literature search identified 584 prediction modeling studies, of which 89 were included. 10.4% of the total studies included prediction models internally validated (n = 61), 4.6% models externally validated (n = 27), and 0.2% (n = 1) models considered for implementation. Across validated prediction modeling studies (n = 88), 18.2% were diagnostic, 68.2% prognostic, and 13.6% predictive. The most frequently investigated condition was psychosis (36.4%), and the most frequently employed predictors clinical (69.5%). Unimodal compared to multimodal models (β = .29, P = .03) and diagnostic compared to prognostic (β = .84, p < .0001) and predictive (β = .87, P = .002) models were associated with increased accuracy. INTERPRETATION To date, several validated prediction models are available to support the diagnosis and prognosis of psychiatric conditions, in particular, psychosis, or to predict treatment response. Advancements of knowledge are limited by the lack of implementation research in real-world clinical practice. A new generation of implementation research is required to address this translational gap.
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Affiliation(s)
- Gonzalo Salazar de Pablo
- Early Psychosis: Interventions and Clinical-detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, 16 De Crespigny Park, London, UK,Institute of Psychiatry and Mental Health, Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón School of Medicine, Universidad Complutense, Instituto de Investigación Sanitaria Gregorio Marañón, CIBERSAM, Madrid, Spain,Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Erich Studerus
- Division of Personality and Developmental Psychology, Department of Psychology, University of Basel, Basel, Switzerland
| | - Julio Vaquerizo-Serrano
- Early Psychosis: Interventions and Clinical-detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, 16 De Crespigny Park, London, UK,Institute of Psychiatry and Mental Health, Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón School of Medicine, Universidad Complutense, Instituto de Investigación Sanitaria Gregorio Marañón, CIBERSAM, Madrid, Spain,Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Jessica Irving
- Early Psychosis: Interventions and Clinical-detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, 16 De Crespigny Park, London, UK
| | - Ana Catalan
- Early Psychosis: Interventions and Clinical-detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, 16 De Crespigny Park, London, UK,Department of Psychiatry, Basurto University Hospital, Bilbao, Spain,Mental Health Group, BioCruces Health Research Institute, Bizkaia, Spain,Neuroscience Department, University of the Basque Country UPV/EHU, Leioa, Spain
| | - Dominic Oliver
- Early Psychosis: Interventions and Clinical-detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, 16 De Crespigny Park, London, UK
| | - Helen Baldwin
- Early Psychosis: Interventions and Clinical-detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, 16 De Crespigny Park, London, UK
| | - Andrea Danese
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK,Social, Genetic and Developmental Psychiatry Centre, King’s College London, London, UK,National and Specialist CAMHS Clinic for Trauma, Anxiety, and Depression, South London and Maudsley NHS Foundation Trust, London, UK
| | - Seena Fazel
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Ewout W Steyerberg
- Department of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, the Netherlands,Department of Public Health, Erasmus MC, Rotterdam, the Netherlands
| | - Daniel Stahl
- Biostatistics Department, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Paolo Fusar-Poli
- Early Psychosis: Interventions and Clinical-detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, 16 De Crespigny Park, London, UK,OASIS Service, South London and Maudsley NHS Foundation Trust, London, UK,Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy,National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, UK,To whom correspondence should be addressed; tel: +44-0-20-7848-0900, fax:+44-0-20-7848-0976, e-mail:
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