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. 2011 Jun;65(3):183-91.
doi: 10.3109/08039488.2010.515687. Epub 2010 Sep 21.

No-shows, drop-outs and completers in psychotherapeutic treatment: demographic and clinical predictors in a large sample of non-psychotic patients

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No-shows, drop-outs and completers in psychotherapeutic treatment: demographic and clinical predictors in a large sample of non-psychotic patients

Morten Fenger et al. Nord J Psychiatry. 2011 Jun.

Erratum in

  • Nord J Psychiatry. 2011 Jun;65(3):191

Abstract

Background: A primary challenge in mental health services is a high rate of non-attendance (i.e. no-show and drop-out) for patients referred to treatment for psychiatric disorders.

Aim: The aim of the present study was to assess the influence of demographic and clinical variables on mental health treatment attendance and to investigate differences in predictors for no-shows and drop-outs.

Methods: A naturalistic study of 2473 non-psychotic consecutive patients offered psychotherapeutic treatment at a community mental health centre in Denmark. Fifteen demographic and clinical variables were recorded at assessment. Bivariate and multiple logistic regression analyses were conducted to investigate the associations between these variables and no-show and drop-out.

Results: Of the 2473 participants, 668 (27.0%) did not show up for treatment, whereas 290 (11.7%) dropped out of treatment. Regression analysis showed that the significant predictors of treatment no-show were: age below 25, no more than the compulsory 9 years of school education, no sick leave, a diagnosis of personality disorder, a Global Assessment of Functioning score (GAF) below 40 or above 70, no previous psychiatric/psychological treatment, no use of antidepressants and substance abuse. The significant predictors of treatment drop-out were: age below 45, no more than the compulsory 9 years of school education or up to 11 years of school education, no vocational/university education, unemployment and substance abuse.

Conclusion: No-show was predicted by both demographic and clinical factors, whereas drop-out was predicted by demographic factors and substance abuse as the only clinical factor. Results and strategies to reduce non-attendance are discussed.

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