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Can cognitive insight predict symptom remission in a first episode psychosis cohort?

Overview of attention for article published in BMC Psychiatry, February 2017
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Title
Can cognitive insight predict symptom remission in a first episode psychosis cohort?
Published in
BMC Psychiatry, February 2017
DOI 10.1186/s12888-017-1210-9
Pubmed ID
Authors

Jennifer A. O’Connor, Lyn Ellett, Olesya Ajnakina, Tabea Schoeler, Anna Kollliakou, Antonella Trotta, Benjamin D. Wiffen, Aurora M. Falcone, Marta Di Forti, Robin M. Murray, Sagnik Bhattacharyya, Anthony S. David

Abstract

The outcome of first episode psychosis (FEP) is highly variable and difficult to predict. Cognitive insight measured at illness onset has previously been found to predict psychopathology 12-months later. The aims of this study were to examine whether the prospective relationship between cognitive insight and symptom severity is evident at four-years following FEP and to examine some psychological correlates of cognitive insight. FEP participants (n = 90) completed the Beck Cognitive Insight Scale (BCIS) at illness onset, and associations between BCIS scores with symptom severity outcomes (4-years after FEP) were assessed. The BCIS scales (self-reflectiveness and self-certainty) were examined as a composite score, and individually compared to other cognitive measures (IQ and jumping to conclusions (JTC) bias). Regression analyses revealed that the cognitive insight composite did not predict 4-year symptom remission in this study while the self-reflection subscale of the BCIS predicted severity of symptoms at 4-years. Self-certainty items of the BCIS were not associated with symptom severity. Significant correlations between the JTC bias, self-certainty and IQ were found, but self-reflection did not correlate with these other cognitive measures. Self-reflective capacity is a more relevant and independent cognitive construct than self-certainty for predicting prospective symptom severity in psychosis. Improving self-reflection may be a useful target for early intervention research.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
Unknown 76 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 14 18%
Student > Ph. D. Student 12 16%
Researcher 9 12%
Student > Bachelor 7 9%
Other 6 8%
Other 18 23%
Unknown 11 14%
Readers by discipline Count As %
Psychology 32 42%
Medicine and Dentistry 13 17%
Nursing and Health Professions 3 4%
Neuroscience 2 3%
Pharmacology, Toxicology and Pharmaceutical Science 1 1%
Other 5 6%
Unknown 21 27%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 June 2017.
All research outputs
#11,169,996
of 14,687,926 outputs
Outputs from BMC Psychiatry
#2,534
of 3,292 outputs
Outputs of similar age
#229,162
of 350,159 outputs
Outputs of similar age from BMC Psychiatry
#1
of 2 outputs
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