Hostname: page-component-745bb68f8f-v2bm5 Total loading time: 0 Render date: 2025-01-18T20:20:49.225Z Has data issue: false hasContentIssue false

Reimagining psychosis prevention: responding to the accessibility issues of At-Risk Mental State (ARMS) services through a selective public health approach

Published online by Cambridge University Press:  15 January 2025

Luke Brown*
Affiliation:
Centre for Applied Psychology, School of Psychology, University of Birmingham, Birmingham, UK Black Country Partnership NHS Foundation Trust, Dudley, UK Institute of Mental Health, School of Psychology, University of Birmingham, Birmingham, UK
Siân Lowri Griffiths
Affiliation:
Institute of Mental Health, School of Psychology, University of Birmingham, Birmingham, UK
*
Correspondence to Luke Brown ([email protected])
Rights & Permissions [Opens in a new window]

Abstract

At-Risk Mental State (ARMS) services aim to prevent the onset of first-episode psychosis (FEP) in those with specific clinical or genetic risk markers. In England, ARMS services are currently expanding, but the accessibility of this preventative approach remains questionable, especially for a subgroup of FEP patients and those from specific ethnic minority communities. This commentary outlines the key debates about why a complimentary approach to psychosis prevention is necessary, and gives details for an innovative public health strategy, drawing on existing research and health prevention theory.

Type
Editorial
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - SA
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-ShareAlike licence (http://creativecommons.org/licenses/by-sa/4.0), which permits re-use, distribution, and reproduction in any medium, provided the same Creative Commons licence is used to distribute the re-used or adapted article and the original article is properly cited.
Copyright
Copyright © The Author(s), 2025. Published by Cambridge University Press on behalf of Royal College of Psychiatrists

At-Risk Mental State (ARMS) servicesReference Yung, McGorry, McFarlane, Jackson, Patton and Rakkar1 continue to remain the most established approach to preventing psychosis in the Western world.Reference Kotlicka-Antczak, Podgórski, Oliver, Maric, Valmaggia and Fusar-Poli2 According to the definition set out by the World Health Organization3 (Table 1), ARMS services are classified as indicative primary prevention,Reference Fusar-Poli, Correll, Arango, Berk, Patel and Ioannidis7 as they aim to stop the onset of first-episode psychosis (FEP) in those with specific clinical or genetic risk markers, also known as the ultra-high-risk criteria. In England, UK, ARMS services are expanding, with all regional Early Intervention in Psychosis teams expected to deliver psychosis prevention to 14- to 35-year-olds.8,9 Despite such advancements, there has been little debate about the suitability of ARMS services for all FEP patients.Reference Murray, David and Ajnakina10,Reference Ajnakina and David11

Table 1 World Health Organization's classification of preventive approaches for mental disorders3

The challenges of ARMS prevention

There are two main reasons why ARMS services are criticised for being the sole approach to prevent psychosis. First, there remains a lack of clarity about the proportion of patients who benefit from ARMS clinics. It is estimated that about a third of patients experience no ARMS symptoms before the onset of psychosis, and so would be ineligible to access ARMS care even if they were to seek help during the prodromal phase.Reference Shah, Crawford, Mustafa, Iyer, Joober and Malla12 Furthermore, transition rates from ARMS services to FEP is low (8–17%),Reference Morrison, French, Stewart, Birchwood, Fowler and Gumley13Reference Malla, de Bonneville, Shah, Jordan, Pruessner and Faridi16 and so it remains unclear how sensitive the ARMS criteria is to those who truly are at risk. The second critique of ARMS services is their constrained appeal. Only a small proportion (4.1%) of patients presenting to psychiatric care with a diagnosis of FEP come via ARMS services. ARMS services are most likely to be accessed by patients who voluntarily seek help from the healthcare system,Reference Ajnakina, Morgan, Gayer-Anderson, Oduola, Bourque and Bramley17 and are disproportionately underused by individuals from Black ethnic backgrounds (African, Caribbean and British)Reference Byrne, Codjoe, Morgan, Stahl, Day and Fearon18 despite this group being at increased psychosis risk.Reference Kirkbride, Errazuriz, Croudace, Morgan, Jackson and Boydell19,Reference Jongsma, Turner, Kirkbride and Jones20 This may be caused by cultural differences in help-seeking preferences;Reference Ajnakina, Morgan, Gayer-Anderson, Oduola, Bourque and Bramley17,Reference Byrne, Codjoe, Morgan, Stahl, Day and Fearon18,Reference Morrison, Stewart, French, Bentall, Birchwood and Byrne21Reference Kirkbride, Stochl, Zimbrón, Crane, Metastasio and Aguilar23 alternative beliefs about the causes of psychosis;Reference Anderson, Fuhrer and Malla24,Reference Halvorsrud, Nazroo, Otis, Brown Hajdukova and Bhui25 or the result of a more acute form of psychosis onset, resulting in urgent, involuntary and coercive psychiatric treatment.Reference Burnett, Mallett, Bhugra, Hutchinson, Der and Leff26,Reference Singh, Brown, Winsper, Gajwani, Islam and Jasani27 Collectively, these points raise questions about the accessibility and sensitivity of the ARMS preventative model, which is further concerning given the National Health Service's (NHS) commitment to preventative healthcare and reducing health inequalities.28

Public health approaches to psychosis prevention

Although there is greater recognition of the need for complementary approaches to ARMS services,Reference Murray, David and Ajnakina10,Reference Ajnakina and David11,Reference Jongsma and Kirkbride29Reference Anderson31 rare is there a discussion about how this can be achieved.Reference Gordon RS4 Selective and universal public health preventative approaches (Table 1) have the potential to overcome the limitations of the ARMS model, as preventative care is directly targeted at the general population, in what is referred to as ‘upstream’ working.Reference Williams, Costa, Odunlami and Mohammed32 These approaches are likely to be more accessible and have a wider reach, as they exist outside of the boundaries of the psychiatric care system. They are also more likely to be acceptable and therefore more appealing, as they offer care in less stigmatising, less coercive and more culturally attuned settings.

One of the overarching mechanisms by which selective or universal prevention could act to stop psychosis transition is by addressing the social factors that predispose healthy individuals to psychosis, known as social determinants. These determinants act at the individual, neighbourhood and environmental levels, comprising of factors like socioeconomic disadvantage, childhood adversity and trauma, migration, discrimination, neighbourhood socioeconomic disadvantage, social capital, social fragmentation, ethnic density and cannabis use.Reference Kirkbride, Anglin, Colman, Dykxhoorn, Jones and Patalay6,Reference Murray, David and Ajnakina10,Reference Schäfer and Fisher33 Public health interventions are effective in acting on the social determinants of psychosis.Reference Kirkbride, Anglin, Colman, Dykxhoorn, Jones and Patalay6 Despite this, there continues to remain a lack of evidence demonstrating the direct effect of public health interventions in reducing future psychosis incident rates in the real world, and no clear agreement about a model of service delivery.

Future considerations

According to Frieden'sReference Frieden34 Six Components Model, innovation is central to the effective design and implementation of any public health programme. Building on this premise, we outline our considerations for building a public health preventative strategy for FEP.

Selective prevention

Rather than employing a universal strategy, we think there is greater utility and better use of resources by adopting a selective preventative approach. This public health model would aim to stop the development of new FEP cases from subpopulations at increased social risk. Individuals within these subgroups may be asymptomatic or display nonspecific symptoms of mental distress associated to the social risk factors they have been exposed to. We also believe this work should be children and young people specific, as the onset of psychosis is most common in youth.Reference Solmi, Radua, Olivola, Croce, Soardo and Salazar de Pablo35

Risk prediction–detection modelling

To identify at-risk individuals from within the general population, a new prediction–detection tool will be needed. Through an innovative, data-science-based approach, this tool could be mathematically modelled on existing FEP patients’ sociodemographic information and social determinant data. By using real-world metrics, the tool should be able to: (a) identify neighbourhoods and communities at high risk, in terms of their probabilistic likelihood of containing future psychosis cases; and (b) predict the demographic level characteristics of at-risk individuals within those neighbourhoods. The tool would therefore enable a place-based focus to risk prediction and detection, which would facilitate localised prevention planning. There are existing examples of data-driven tools that utilise either patientReference Baio, Coid, Ding, Dliwayo, French and Jones36 or social determinantReference Oliver, Arribas, Perry, Whiting, Blackman and Krakowski37 data to predict and forecast psychosis cases in clinical and population contexts. Although these digital technologies are not specifically designed to aid selective prevention programmes for FEP, they do provide support for what is achievable in this space through their combination.

Collaborative case identification

An effective preventive strategy will need to consider the mechanisms by which FEP prediction–detection technologies are used to find at-risk cases in the real world. In addressing some of the accessibility issues of ARMS services, selective prevention will need to go beyond the psychiatric care system and reach into the wider social institutions that children, young people and families interact. We therefore feel a localised and coordinated network of institutions across the health and social sector will be best positioned to identify at-risk individuals in the community. Religious; voluntary, community and social enterprise, education and social care services are some of the likely candidates for this network. We also believe there is a role for the NHS, particularly Child and Adolescent Mental Health ServicesReference Kelleher38 and general practices, because of their specialised or localised focus on child and family health.

In a practical sense, the detection of at-risk cases would involve a whole range of integrated measures across the network of providers. For example, in the health and social care system, a nationally coordinated selective screening programmeReference Bobrowska, Murton, Seedat, Visintin, Mackie and Steele39 could be used to proactively invite at-risk individuals for routine mental health screening assessments. Outside of the NHS, voluntary, community and social enterprise organisations and schools in areas of high risk could be trained to spot early cases, leading to supported referral or screening processes.

Multi-layered youth-focused preventative interventions

Existing evidence should be used to decide which preventative interventions are adopted within the selective prevention programme.Reference Frieden34 Prevention will also need to be multi-layered, able to intervene on a range of direct and distal psychosocial developmental levels in childhood,Reference Bronfenbrenner40 and able to influence key social determinants.Reference Kirkbride, Anglin, Colman, Dykxhoorn, Jones and Patalay6,Reference Jester, Thomas, Sturm, Harvey, Keshavan and Davis41

First, interventions should aim to address the impact of childhood adversity.Reference Varchmin, Montag, Treusch, Kaminski and Heinz42,Reference Davies, Segre, Estradé, Radua, De Micheli and Provenzani43 Psychological interventions should be considered because of their effectiveness in targeting the effects of childhood abuse, neglect and victimization. For example, eye movement desensitization and reprocessing has been shown to reduce the symptoms of childhood trauma by adapting negative memory pathways and lessening one's reactivity to traumatic stimuli.Reference Moreno-Alcázar, Treen, Valiente-Gómez, Sio-Eroles, Pérez and Amann44,Reference Lewey, Smith, Burcham, Saunders, Elfallal and O'Toole45 Family-focused therapy should also be included, because of its effectiveness in addressing various adolescent mental health difficulties. Furthermore, eye movement desensitisation and reprocessing and family therapy have both been shown to lessen psychotic experiences in clinical and non-clinical populations.Reference O'Brien, Miklowitz and Cannon46,Reference Hardy, Keen, van den Berg, Varese, Longden and Ward47

Second, a preventative strategy should also aim to address the effects of social disconnectedness, such as social fragmentation, social marginalisation and racial discrimination.Reference Jester, Thomas, Sturm, Harvey, Keshavan and Davis41,Reference Jongsma, Gayer-Anderson, Tarricone, Velthorst, van der Ven and Quattrone48 Interventions that improve civic engagement should also be considered, including youth-focused social prescribing and educational/vocational participation schemes.Reference Kirkbride, Anglin, Colman, Dykxhoorn, Jones and Patalay6 At the neighbourhood level, improving community resources and infrastructure will also be pivotal. Cultural centres, community organisations, outdoor recreational areas and religious organisations are likely to act as protective factors,Reference Jester, Thomas, Sturm, Harvey, Keshavan and Davis41 by providing greater community cohesion. Family interventions might lessen youth alienation, by improving family cohesion and connectedness.Reference Holt-Lunstad, Robles and Sbarra49

Finally, strategy should aim to lessen the impact of social economic disadvantage. Some examples might be improving the economic state of families in high-poverty neighbourhoods through direct payment schemes, which have been shown to reduce distress and anxiety in parents and children.Reference Holt-Lunstad, Robles and Sbarra49 Neighbourhood regeneration schemes that improve the physical quality of the built environment by planting trees, removing litter and landscaping vacant land should also be included,Reference Holt-Lunstad, Robles and Sbarra49 as these initiatives have been shown to lower depressive symptoms and improve self-worth amongst residents.

A placed-based health partnershipReference Naylor and Charles50 will be most effective in delivering these interventions. For example, local authorities and public health departments could be responsible for delivering the community and neighbourhood-level components of the preventive strategy, whereas schools and social care organisations could be tasked to facilitate the individual and family level. This collaborative approach to prevention ensures that the most effective interventions are delivered at the right time and by the right provider.

In conclusion, the accessibility of existing preventative strategies for psychosisReference Griffiths, Brown and Kirkbride51 requires us to explore greater diversity in our approach.Reference Ajnakina and David11,Reference Kelleher38 What is lacking is the how – the specific strategies that ensure that all communities have equal access to preventative care. We believe that a public health approach employing a selective preventative strategy offers a novel and equitable way to achieve this, by focusing on communities at increased risk in the general population and developing collaboration between the healthcare system and different social organisations. Interventions within such a strategy should be youth-focused and aim to target multiple levels within the life course of the young. Future pilot research is however needed to establish which preventive interventions have the greatest impact in reducing incident rates of psychosis in a population. From this, recommendations for health policy and political commitment can be generated, so that effective interventions can be expanded to the national stage.

About the authors

Luke Brown, BSc, MRes, PhD, ClinPsyD, is an assistant professor at the Centre for Applied Psychology, School of Psychology, University of Birmingham, Birmingham, UK; assistant professor at the Institute of Mental Health, School of Psychology, University of Birmingham, Birmingham, UK; and a principal clinical psychologist with the Early Intervention in Psychosis Service, Black Country Partnership NHS Foundation Trust, Dudley, UK. Siân Lowri Griffiths, BSc, MSc, PhD, is an assistant professor at the Institute of Mental Health, School of Psychology, University of Birmingham, Birmingham, UK.

Data availability

Data availability is not applicable to this article as no new data were created or analysed.

Author contributions

The ideas within this commentary were jointly developed by L.B. and S.L.G. Both authors contributed to the original and final versions of the manuscript.

Funding

This research received no specific grant from any funding agency, commercial or not-for-profit sector.

Declaration of interest

None.

References

Yung, AR, McGorry, PD, McFarlane, CA, Jackson, HJ, Patton, GC, Rakkar, A. Monitoring and care of young people at incipient risk of psychosis. Schizophr Bull 1996; 22(2): 283303.CrossRefGoogle ScholarPubMed
Kotlicka-Antczak, M, Podgórski, M, Oliver, D, Maric, NP, Valmaggia, L, Fusar-Poli, P. Worldwide implementation of clinical services for the prevention of psychosis: the IEPA early intervention in mental health survey. Early Interv Psychiatry 2020; 14(6): 741–50.CrossRefGoogle ScholarPubMed
World Health Organization (WHO). Prevention of Mental Disorders: Effective Interventions and Policy Options: Summary Report. WHO, 2004 (https://www.who.int/publications/i/item/924159215X).Google Scholar
Gordon RS, J. An operational classification of disease prevention. Public Health Rep 1983; 98(2): 107–9.Google ScholarPubMed
US Institute of Medicine. Reducing Risks for Mental Disorders: Frontiers for Preventive Intervention Research. National Academies Press, 1994.Google Scholar
Kirkbride, JB, Anglin, DM, Colman, I, Dykxhoorn, J, Jones, PB, Patalay, P, et al. The social determinants of mental health and disorder: evidence, prevention and recommendations. World Psychiatry 2024; 23(1): 5890.CrossRefGoogle ScholarPubMed
Fusar-Poli, P, Correll, CU, Arango, C, Berk, M, Patel, V, Ioannidis, JPA. Preventive psychiatry: a blueprint for improving the mental health of young people. World Psychiatry 2021; 20(2): 200–21.CrossRefGoogle ScholarPubMed
NHS England. Implementing the Early Intervention in Psychosis Access and Waiting Time Standard. NHS England, 2023 (https://www.england.nhs.uk/wp-content/uploads/2023/03/B1954-implementing-the-early-intervention-in-psychosis-access-and-waiting-time-standard.pdf).Google Scholar
Murray, RM, David, AS, Ajnakina, O. Prevention of psychosis: moving on from the at-risk mental state to universal primary prevention. Psychol Med 2021; 51(2): 223–7.CrossRefGoogle ScholarPubMed
Ajnakina, O, David, AS. Murray RM. ‘at risk mental state’ clinics for psychosis – an idea whose time has come – and gone!. Psychol Med 2019; 49(4): 529–34.CrossRefGoogle ScholarPubMed
Shah, JL, Crawford, A, Mustafa, SS, Iyer, SN, Joober, R, Malla, AK. Is the clinical high-risk state a valid concept? Retrospective examination in a first-episode psychosis sample. Psychiatr Serv 2017; 68(10): 1046–52.CrossRefGoogle Scholar
Morrison, AP, French, P, Stewart, SLK, Birchwood, M, Fowler, D, Gumley, AI, et al. Early detection and intervention evaluation for people at risk of psychosis: multisite randomised controlled trial. BMJ 2012; 344: e2233.CrossRefGoogle ScholarPubMed
Carrión, RE, Cornblatt, BA, Burton, CZ, Tso, IF, Auther, AM, Adelsheim, S, et al. Personalized prediction of psychosis: external validation of the NAPLS-2 psychosis risk calculator with the EDIPPP project. Am J Psychiatry 2016; 173(10): 989–96.CrossRefGoogle ScholarPubMed
Conrad, AM, Lewin, TJ, Sly, KA, Schall, U, Halpin, SA, Hunter, M, et al. Utility of risk-status for predicting psychosis and related outcomes: evaluation of a 10-year cohort of presenters to a specialised early psychosis community mental health service. Psychiatry Res 2017; 247: 336–44.CrossRefGoogle ScholarPubMed
Malla, A, de Bonneville, M, Shah, J, Jordan, G, Pruessner, M, Faridi, K, et al. Outcome in patients converting to psychosis following a treated clinical high risk state. Early Interv Psychiatry 2018; 12(4): 715–9.CrossRefGoogle ScholarPubMed
Ajnakina, O, Morgan, C, Gayer-Anderson, C, Oduola, S, Bourque, F, Bramley, S, et al. Only a small proportion of patients with first episode psychosis come via prodromal services: a retrospective survey of a large UK mental health programme. BMC Psychiatry 2017; 17(1): 308.CrossRefGoogle Scholar
Byrne, M, Codjoe, L, Morgan, C, Stahl, D, Day, F, Fearon, P, et al. The relationship between ethnicity and service access, treatment uptake and the incidence of psychosis among people at ultra high risk for psychosis. Psychiatry Res 2019; 272: 618–27.CrossRefGoogle ScholarPubMed
Kirkbride, JB, Errazuriz, A, Croudace, TJ, Morgan, C, Jackson, D, Boydell, J, et al. Incidence of schizophrenia and other psychoses in England, 1950–2009: a systematic review and meta-analyses. PLoS One 2012; 7(3): e31660.CrossRefGoogle ScholarPubMed
Jongsma, HE, Turner, C, Kirkbride, JB, Jones, PB. International incidence of psychotic disorders, 2002–17: a systematic review and meta-analysis. Lancet Public Health 2019; 4(5): e229–e44.CrossRefGoogle ScholarPubMed
Morrison, AP, Stewart, SL, French, P, Bentall, RP, Birchwood, M, Byrne, R, et al. Early detection and intervention evaluation for people at high-risk of psychosis-2 (EDIE-2): trial rationale, design and baseline characteristics. Early Interv Psychiatry 2011; 5(1): 2432.CrossRefGoogle ScholarPubMed
Burke, T, Thompson, A, Mifsud, N, Yung, AR, Nelson, B, McGorry, P, et al. Proportion and characteristics of young people in a first-episode psychosis clinic who first attended an at-risk mental state service or other specialist youth mental health service. Schizophr Res 2022; 241: 94101.CrossRefGoogle ScholarPubMed
Kirkbride, JB, Stochl, J, Zimbrón, J, Crane, CM, Metastasio, A, Aguilar, E, et al. Social and spatial heterogeneity in psychosis proneness in a multilevel case-prodrome-control study. Acta Psychiatr Scand 2015; 132(4): 283–92.CrossRefGoogle Scholar
Anderson, KK, Fuhrer, R, Malla, AK. The pathways to mental health care of first-episode psychosis patients: a systematic review. Psychol Med 2010; 40(10): 1585–97.CrossRefGoogle ScholarPubMed
Halvorsrud, K, Nazroo, J, Otis, M, Brown Hajdukova, E, Bhui, K. Ethnic inequalities and pathways to care in psychosis in England: a systematic review and meta-analysis. BMC Med 2018; 16(1): 223.CrossRefGoogle Scholar
Burnett, R, Mallett, R, Bhugra, D, Hutchinson, G, Der, G, Leff, J. The first contact of patients with schizophrenia with psychiatric services: social factors and pathways to care in a multi-ethnic population. Psychol Med 1999; 29(2): 475–83.CrossRefGoogle Scholar
Singh, SP, Brown, L, Winsper, C, Gajwani, R, Islam, Z, Jasani, R, et al. Ethnicity and pathways to care during first episode psychosis: the role of cultural illness attributions. BMC Psychiatry 2015; 15(1): 287.CrossRefGoogle ScholarPubMed
Jongsma, K, Kirkbride, J. Understanding the excess psychosis risk in ethnic minorities: the impact of structure and identity. Soc Psychiatry Psychiatr Epidemiol 2021; 56(11): 1913–21.CrossRefGoogle ScholarPubMed
Yung, AR, Wood, SJ, Malla, A, Nelson, B, McGorry, P, Shah, J. The reality of at risk mental state services: a response to recent criticisms. Psychol Med 2021; 51(2): 212–8.CrossRefGoogle ScholarPubMed
Anderson, KK. Towards a public health approach to psychotic disorders. Lancet Public Health 2019; 4(5): e212–e3.CrossRefGoogle ScholarPubMed
Williams, DR, Costa, MV, Odunlami, AO, Mohammed, SA. Moving upstream: how interventions that address the social determinants of health can improve health and reduce disparities. J Public Health Manag Pract 2008; 14(6): S8S17.CrossRefGoogle ScholarPubMed
Schäfer, I, Fisher, HL. Childhood trauma and psychosis – what is the evidence? Dialogues Clin Neurosci 2011; 13(3): 360–5.CrossRefGoogle ScholarPubMed
Frieden, TR. Six components necessary for effective public health program implementation. Am J Public Health 2014; 104(1): 1722.CrossRefGoogle ScholarPubMed
Solmi, M, Radua, J, Olivola, M, Croce, E, Soardo, L, Salazar de Pablo, G, et al. Age at onset of mental disorders worldwide: large-scale meta-analysis of 192 epidemiological studies. Mol Psychiatry 2022; 27(1): 281–95.CrossRefGoogle ScholarPubMed
Baio, G, Coid, JW, Ding, T, Dliwayo, TR, French, P, Jones, PB, et al. Using epidemiological evidence to forecast population need for early treatment programmes in mental health: a generalisable Bayesian prediction methodology applied to and validated for first-episode psychosis in England. Br J Psychiatry 2021; 219(1): 383–91.Google Scholar
Oliver, D, Arribas, M, Perry, BI, Whiting, D, Blackman, G, Krakowski, K, et al. Using electronic health records to facilitate precision psychiatry. Biol Psychiatry 2024; 96(7): 532–42.CrossRefGoogle ScholarPubMed
Kelleher, I. Psychosis prediction 2.0: why child and adolescent mental health services should be a key focus for schizophrenia and bipolar disorder prevention research. Br J Psychiatry 2023; 222: 185–7.CrossRefGoogle ScholarPubMed
Bobrowska, A, Murton, M, Seedat, F, Visintin, C, Mackie, A, Steele, R, et al. Targeted screening in the UK: a narrow concept with broad application. Lancet Reg Health Eur 2022; 16: 100353.Google Scholar
Bronfenbrenner, U. Toward an experimental ecology of human development. Am Psychol 1977; 32: 513–31.CrossRefGoogle Scholar
Jester, DJ, Thomas, ML, Sturm, ET, Harvey, PD, Keshavan, M, Davis, BJ, et al. Review of major social determinants of health in schizophrenia-spectrum psychotic disorders: I. Clinical outcomes. Schizophr Bull 2023; 49(4): 837–50.CrossRefGoogle ScholarPubMed
Varchmin, L, Montag, C, Treusch, Y, Kaminski, J, Heinz, A. Traumatic events, social adversity and discrimination as risk factors for psychosis – an umbrella review. Front Psychiatry 2021; 12: 665957.CrossRefGoogle ScholarPubMed
Davies, C, Segre, G, Estradé, A, Radua, J, De Micheli, A, Provenzani, U, et al. Prenatal and perinatal risk and protective factors for psychosis: a systematic review and meta-analysis. Lancet Psychiatry 2020; 7(5): 399410.CrossRefGoogle ScholarPubMed
Moreno-Alcázar, A, Treen, D, Valiente-Gómez, A, Sio-Eroles, A, Pérez, V, Amann, BL, et al. Efficacy of eye movement desensitization and reprocessing in children and adolescent with post-traumatic stress disorder: a meta-analysis of randomized controlled trials. Front Psychol 2017; 8: 1750.CrossRefGoogle ScholarPubMed
Lewey, JH, Smith, CL, Burcham, B, Saunders, NL, Elfallal, D, O'Toole, SK. Comparing the effectiveness of EMDR and TF-CBT for children and adolescents: a meta-analysis. J Child Adolesc Trauma 2018; 11(4): 457–72.CrossRefGoogle ScholarPubMed
O'Brien, MP, Miklowitz, DJ, Cannon, TD. Decreases in perceived maternal criticism predict improvement in subthreshold psychotic symptoms in a randomized trial of family-focused therapy for individuals at clinical high risk for psychosis. J Fam Psychol 2015; 29(6): 945–51.CrossRefGoogle Scholar
Hardy, A, Keen, N, van den Berg, D, Varese, F, Longden, E, Ward, T, et al. Trauma therapies for psychosis: a state-of-the-art review. Psychology and psychotherapy: theory. Res Pract 2024; 97(1): 7490.Google Scholar
Jongsma, HE, Gayer-Anderson, C, Tarricone, I, Velthorst, E, van der Ven, E, Quattrone, D, et al. Social disadvantage, linguistic distance, ethnic minority status and first-episode psychosis: results from the EU-GEI case-control study. Psychol Med 2021; 51(9): 1536–48.CrossRefGoogle ScholarPubMed
Holt-Lunstad, J, Robles, TF, Sbarra, DA. Advancing social connection as a public health priority in the United States. Am Psychol 2017; 72(6): 517–30.CrossRefGoogle ScholarPubMed
Naylor, C, Charles, A. Place-based Partnerships Explained London. The King's Fund, 2022 (https://www.kingsfund.org.uk/insight-and-analysis/long-reads/place-based-partnerships-explained).Google Scholar
Griffiths, SL, Brown, L, Kirkbride, JB. RE: Psychosis prediction 2.0: why child and adolescent mental health services should be a key focus for schizophrenia and bipolar disorder prevention research. Br J Psychiatry 2023; 223(2): 394.CrossRefGoogle ScholarPubMed
Figure 0

Table 1 World Health Organization's classification of preventive approaches for mental disorders3

Submit a response

eLetters

No eLetters have been published for this article.