B3855 - Predicting Illness Trajectories after Adolescent Psychotic Experiences - 26/08/2021

B number: 
Principal applicant name: 
William W. Eaton | Johns Hopkins Bloomberg School of Public Health (USA)
Katrina Rodriguez
Title of project: 
Predicting Illness Trajectories after Adolescent Psychotic Experiences
Proposal summary: 

Psychotic experiences, such as hearing voices or seeing things others cannot see or hear, and delusions, are not unusual in adolescents, with a large population-based study finding a cumulative incidence proportion of 8.1% in the period between 12 and 24 years of age (Sullivan et al., 2020). Psychotic experiences are a risk factor for multiple disorders including psychotic disorders, anxiety disorders, and depressive disorders (Fisher et al., 2013; Kaymaz et al., 2012). Additionally, compared to adolescents who do not report psychotic experiences, those who do have higher odds of suicidal behavior, independently of depressive symptoms (S. A. Sullivan et al., 2015; Yates et al., 2019). It is well established that longer durations of untreated psychosis, which is commonly defined as the time from the first psychotic experience to the initiation of appropriate treatment, lead to worse outcomes, including more relapses and hospitalizations and lower functioning (Marshall et al., 2005). However, there are currently no well-established methods of identifying those who will go on to be diagnosed with a mental disorder or exhibit suicidal behaviors. Prediction of those who are most at risk of being later diagnosed with mental disorders or suicidal behaviors would provide both targets for intervention as well as more precise treatments, positively affecting prognosis and saving lives.
In this study our primary aim is to identify the cumulative incidence of schizophrenia spectrum, anxiety, depressive disorders, and suicidal behaviors in young adults who had reported psychotic experiences in adolescence and to compare incidence rates to those adults who did not report psychotic experiences in adolescence. Our secondary aim is to identify the biopsychosocial characteristics that predict outcomes such as mental disorders and/or suicidal behavior, as well as persistent psychotic experiences in the absence of mental disorders, after psychotic experiences in adolescence; and to develop an algorithm for prediction. Longitudinal studies of incidence of mental disorders beginning at birth have been conducted using population health registers (Byrne et al., 2007), but unlike the ALSPAC research, these studies fail to capture the range of occurrences which do not lead to treatment in the health care system and they do not have the capability of measuring psychotic experiences in the absence of mental disorder. Also, this area of research does not appear to have been fully explored using the ALSPAC data; however ALSPAC’s inclusion of prenatal factors and a longitudinal follow-up from birth to adulthood provides the ideal study design to answer these questions in a holistic manner.

Impact of research: 
Early intervention is the best modifiable risk factor for mental disorders. Developing the ability to predict who may or may not go on to develop specific disorders in such a critical developmental period as adolescence can inform treatment and dramatically lessen the burden of mental disorders. The applicant has reviewed a wide range of research in the field of early psychosis, yet none involve both a population-based sample and such a holistic range of predictors ranging from birth to young adulthood as we propose to study here. Examining this critical period of development will not only inform treatment but also provide insight into the etiology of mental disorders.
Date proposal received: 
Wednesday, 18 August, 2021
Date proposal approved: 
Thursday, 26 August, 2021
Mental health - Psychology, Psychiatry, Cognition, Statistical methods, Statistical methods