The structure of the ultra high risk mental state for psychosis. A latent class cluster analysis study

2011 ◽  
Vol 26 (S2) ◽  
pp. 2087-2087 ◽  
Author(s):  
L. Valmaggia ◽  
D. Stahl ◽  
A. Yung ◽  
B. Nelson ◽  
P. McGorry ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
High Risk ◽  
Mental State ◽  
Negative Symptoms ◽  
Latent Class ◽  
Community Mental Health Services ◽  
Psychotic Symptoms ◽  
Latent Class Cluster Analysis ◽  
Class 1 ◽  
Ultra High Risk

IntroductionIndividuals at Ultra High Risk (UHR) for psychosis typically present with attenuated psychotic symptoms. However it is difficult to predict which individuals will later develop frank psychosis when their mental state is rated in terms of individual symptoms.The objective of the study was to examine the phenomenological structure of the UHR mental state and identify symptom profiles that predict later transition to psychosis.MethodPsychopathological data from a large sample of UHR subjects were analysed using latent class cluster analysis.A total of 318 individuals with a UHR for psychosis. Data were collected from two specialised community mental health services for people at UHR for psychosis: OASIS in London and PACE, in Melbourne.ResultsLatent class cluster analysis produced 4 classes: Class 1 - Mild was characterized by lower scores on all the CAARMS items. Subjects in Class 2 - Moderate scored moderately on all CAARMS items and was more likely to be in employment. Those in Class 3 - Moderate-Severe scored moderately-severe on negative symptoms, social isolation and impaired role functioning. Class 4 - Severe was the smallest group and was associated with the most impairment: subjects in this class scored highest on all items of the CAARMS, had the lowest GAF score and were more likely to be unemployed. This group was also characterized by the highest transition rate (41%).ConclusionsDifferent constellations of symptomatology are associates with varying levels of risk to of transition to psychosis.

scholarly journals Negative psychotic symptoms and impaired role functioning predict transition outcomes in the at-risk mental state: a latent class cluster analysis study

2013 ◽  
Vol 43 (11) ◽  
pp. 2311-2325 ◽  
Author(s):  
L. R. Valmaggia ◽  
D. Stahl ◽  
A. R. Yung ◽  
B. Nelson ◽  
P. Fusar-Poli ◽  
...  
Keyword(s):  
At Risk ◽  
Cluster Analysis ◽  
Mental State ◽  
Latent Class ◽  
Mental States ◽  
Psychotic Symptoms ◽  
Role Functioning ◽  
Latent Class Cluster Analysis ◽  
At Risk Mental State

BackgroundMany research groups have attempted to predict which individuals with an at-risk mental state (ARMS) for psychosis will later develop a psychotic disorder. However, it is difficult to predict the course and outcome based on individual symptoms scores.MethodData from 318 ARMS individuals from two specialized services for ARMS subjects were analysed using latent class cluster analysis (LCCA). The score on the Comprehensive Assessment of At-Risk Mental States (CAARMS) was used to explore the number, size and symptom profiles of latent classes.ResultsLCCA produced four high-risk classes, censored after 2 years of follow-up: class 1 (mild) had the lowest transition risk (4.9%). Subjects in this group had the lowest scores on all the CAARMS items, they were younger, more likely to be students and had the highest Global Assessment of Functioning (GAF) score. Subjects in class 2 (moderate) had a transition risk of 10.9%, scored moderately on all CAARMS items and were more likely to be in employment. Those in class 3 (moderate–severe) had a transition risk of 11.4% and scored moderately severe on the CAARMS. Subjects in class 4 (severe) had the highest transition risk (41.2%), they scored highest on the CAARMS, had the lowest GAF score and were more likely to be unemployed. Overall, class 4 was best distinguished from the other classes on the alogia, avolition/apathy, anhedonia, social isolation and impaired role functioning.ConclusionsThe different classes of symptoms were associated with significant differences in the risk of transition at 2 years of follow-up. Symptomatic clustering predicts prognosis better than individual symptoms.

scholarly journals The reality of at risk mental state services: a response to recent criticisms

2019 ◽  
pp. 1-7 ◽  
Author(s):  
Alison R. Yung ◽  
Stephen J. Wood ◽  
Ashok Malla ◽  
Barnaby Nelson ◽  
Patrick McGorry ◽  
...  
Keyword(s):  
At Risk ◽  
High Risk ◽  
Psychotic Disorder ◽  
Mental State ◽  
Help Seeking ◽  
Psychotic Symptoms ◽  
Ultra High Risk ◽  
Psychological Medicine ◽  
Poor Outcomes ◽  
At Risk Mental State

AbstractBackgroundIn the 1990s criteria were developed to detect individuals at high and imminent risk of developing a psychotic disorder. These are known as the at risk mental state, ultra high risk or clinical high risk criteria. Individuals meeting these criteria are symptomatic and help-seeking. Services for such individuals are now found worldwide. Recently Psychological Medicine published two articles that criticise these services and suggest that they should be dismantled or restructured. One paper also provides recommendations on how ARMS services should be operate.MethodsIn this paper we draw on the existing literature in the field and present the perspective of some ARMS clinicians and researchers.ResultsMany of the critics' arguments are refuted. Most of the recommendations included in the Moritz et al. paper are already occurring.ConclusionsARMS services provide management of current problems, treatment to reduce risk of onset of psychotic disorder and monitoring of mental state, including attenuated psychotic symptoms. These symptoms are associated with a range of poor outcomes. It is important to assess them and track their trajectory over time. A new approach to detection of ARMS individuals can be considered that harnesses broad youth mental health services, such as headspace in Australia, Jigsaw in Ireland and ACCESS Open Minds in Canada. Attention should also be paid to the physical health of ARMS individuals. Far from needing to be dismantled we feel that the ARMS approach has much to offer to improve the health of young people.

scholarly journals Latent class cluster analysis of symptom ratings identifies distinct subgroups within the clinical high risk for psychosis syndrome

2018 ◽  
Vol 197 ◽  
pp. 522-530 ◽  
Author(s):  
Arthur T. Ryan ◽  
Jean Addington ◽  
Carrie E. Bearden ◽  
Kristin S. Cadenhead ◽  
Barbara A. Cornblatt ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
High Risk ◽  
Latent Class ◽  
Clinical High Risk ◽  
Latent Class Cluster Analysis ◽  
Symptom Ratings

scholarly journals Latent class cluster analysis identified hidden headache phenotypes in COVID-19: impact of pulmonary infiltration and IL-6

2021 ◽  
Author(s):  
Ömer Karadaş ◽  
Bilgin Öztürk ◽  
Ali Rıza Sonkaya ◽  
Bahar Taşdelen ◽  
Aynur Özge ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Latent Class ◽  
Latent Class Cluster Analysis ◽  
Pulmonary Infiltration

scholarly journals Development of Executive Functions as Reflected in Daily Life Behaviors in Young Adults at Ultra-High Risk for Psychosis: Associations With Symptoms and Functioning

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Louise Birkedal Glenthøj ◽  
Carsten Hjorthøj ◽  
Tina Dam Kristensen ◽  
Christina Wenneberg ◽  
Merete Nordentoft ◽  
...  
Keyword(s):  
High Risk ◽  
Executive Functions ◽  
Social Functioning ◽  
Clinical Symptoms ◽  
Daily Life ◽  
Real Life ◽  
Psychotic Symptoms ◽  
Ultra High Risk ◽  
Behaviour Rating

Abstract There is a paucity of evidence on executive functions (EF) as reflected in daily life behaviors in individuals at ultra-high risk (UHR) for psychosis. This prospective follow-up study investigated the 1-year development in EF in UHR compared to healthy controls (HC) and how this change may relate to change in severity of clinical symptoms, social communication, and functioning. UHR (N = 132) and HC (N = 66) were assessed with the Behaviour Rating Inventory of Executive Function–Adult version (BRIEF-A) self and informant report at baseline and 12 months follow-up comprising the Behavioral Regulation Index (BRI) and the Metacognition Index (MI). Additionally, data on depressive-, negative-, and attenuated psychotic symptoms and everyday social functioning were collected. The study found UHR to display large baseline impairments in EF in real life on both self- and informant reports. UHR and HC showed a significantly different development of EF over time, with UHR displaying greater improvements in EF compared to HC. Change in clinical symptoms did not relate to improvements in EF, except for depressive symptoms negatively associating with the development of the MI. Improvements on the BRI and MI were significantly associated with improvements in social functioning. Findings suggest the potential of UHR individuals displaying a larger ongoing maturational development of daily life EF than HC that seems predominantly independent of development of clinical symptoms. If replicated, this supports a maturational trajectory of daily life EF in UHR that approaches, but do not reach, the level of HC and may indicate a window of opportunity for targeted remediation approaches.

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