
pmid: 27132495
Engagement with psychiatric services is critical for ensuring successful outcomes in patients experiencing a first episode of psychosis (FEP). However, it is not known how sociodemographic factors and patient beliefs about the causes of mental illness affect engagement. This study explored predictors of engagement in a cohort of 103 FEP patients presenting to an early-intervention service. Beliefs that mental illness is caused by social stress or thinking odd thoughts predicted higher engagement scores. Patients with no qualifications were found to have higher engagement scores than those educated to a higher level. Ethnicity, gender, age and socioeconomic factors were not significantly correlated with engagement scores. Duration of untreated illness (DUI) significantly predicted higher engagement scores, but only for values >1220days. Duration of untreated psychosis (DUP) was not a significant predictor of patient engagement scores. Patient beliefs about the causes of mental illness are an important factor to be taken into consideration and may represent a target of interventions to increase engagement in FEP.
Male, Analysis of Variance, Statistics, Nonparametric, Time-to-Treatment, Cohort Studies, Young Adult, Psychotic Disorders, Humanitarian and Conflict Response Institute, Educational Status, Humans, Regression Analysis, Female, Patient Participation, RA, Attitude to Health, ResearchInstitutes_Networks_Beacons/humanitarian_conflict_response_institute; name=Humanitarian and Conflict Response Institute
Male, Analysis of Variance, Statistics, Nonparametric, Time-to-Treatment, Cohort Studies, Young Adult, Psychotic Disorders, Humanitarian and Conflict Response Institute, Educational Status, Humans, Regression Analysis, Female, Patient Participation, RA, Attitude to Health, ResearchInstitutes_Networks_Beacons/humanitarian_conflict_response_institute; name=Humanitarian and Conflict Response Institute
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
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