title: Insight dimensions in first-episode psychosis patients: clinical, cognitive, pre-morbid and socio-demographic correlates.
abstract: OBJECTIVE
  To investigate pre-morbid, socio-demographic, clinical and cognitive variables as predictors of insight in a large and representative sample of first-episode psychosis patients.
  
  
  METHODS
  The abbreviated Scale to Assess Unawareness of Mental Disorder was used to assess insight dimensions. Patients with good and poor insight were independently compared on insight dimensions and logistic regression analyses were conducted to identify explanatory variables associated with each insight dimension.
  
  
  RESULTS
  The patients with good and poor insight of having a mental disorder differed in duration of untreated psychosis, diagnosis and attention, but only attention appeared as a predictor. The insight of the need for medication groups showed differences in age of onset, depression, severity of disorganized symptoms and hospitalization rate.Nevertheless, age of onset and disorganized symptoms seem to be the predictors. Groups of insight of the social consequences differed in duration of untreated psychosis, the negative and disorganized symptoms severity, disability, education, diagnosis and hospitalization rate.However, exclusively, the severity of disorganized symptoms seems to predict insight of social consequences.
  
  
  CONCLUSIONS
  When independently analysed, the three insight dimensions showed different rates of affectation and different predictors. These results suggest that there must be different mechanisms underlying the lack of insight. First-episode psychosis is a crucial period for treatment adherence formation, an issue strongly associated with good insight. Thus, a more accurate evaluation of the predictors of lack of insight into each dimension is warranted to achieve a better comprehension of the lack of insight in schizophrenia and in turn, to implement treatment programmes seeking to improve it.
authors.affiliation: University Hospital Marqués de Valdecilla-IFIMAV CIBERSAM, Department of Psychiatry, School of Medicine, University of Cantabria, Santander, Spain. rayesa@humv.es
authors.forename: Rosa
authors.initials: R
authors.lastname: Ayesa-Arriola
authors.forename: Jose Manuel
authors.initials: JM
authors.lastname: Rodríguez-Sánchez
authors.forename: Chiara
authors.initials: C
authors.lastname: Morelli
authors.forename: Jose María
authors.initials: JM
authors.lastname: Pelayo-Terán
authors.forename: Rocío
authors.initials: R
authors.lastname: Pérez-Iglesias
authors.forename: Ignacio
authors.initials: I
authors.lastname: Mata
authors.forename: Obdulia
authors.initials: O
authors.lastname: Martínez-Garcia
authors.forename: Gema
authors.initials: G
authors.lastname: Pardo-Garcia
authors.forename: Jose L
authors.initials: JL
authors.lastname: Vazquez-Barquero
authors.forename: Benedicto
authors.initials: B
authors.lastname: Crespo-Facorro
mesh_terms: D000293:Adolescent; D000328:Adult; D017668:Age of Onset; D001288:Attention; D001364:Awareness; D003710:Demography; D005260:Female; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D008875:Middle Aged; D009483:Neuropsychological Tests; D011569:Psychiatric Status Rating Scales; D011618:Psychotic Disorders / Q000175:diagnosis / Q000523:psychology*; D012720:Severity of Illness Index; D012959:Socioeconomic Factors