Identifying mechanisms of treatment effects and recovery in rehabilitation of schizophrenia: Longitudinal analytic methods

Jason E. Peer, Zeno Kupper, Jeffrey D. Long, John S. Brekke, William D. Spaulding

Research output: Contribution to journalArticle

15 Scopus citations

Abstract

The longitudinal dimension of schizophrenia and related severe mental illness is a key component of theoretical models of recovery. However, empirical longitudinal investigations have been underrepresented in the psychopathology of schizophrenia. Similarly, traditional approaches to longitudinal analysis of psychopathological data have had serious limitations. The utilization of modern longitudinal methods is necessary to capture the complexity of biopsychosocial models of treatment and recovery in schizophrenia. The present paper summarizes empirical data from traditional longitudinal research investigating recovery in symptoms, neurocognition, and social functioning. Studies conducted under treatment as usual conditions are compared to psychosocial intervention studies and potential treatment mechanisms of psychosocial interventions are discussed. Investigations of rehabilitation for schizophrenia using the longitudinal analytic strategies of growth curve and time series analysis are demonstrated. The respective advantages and disadvantages of these modern methods are highlighted. Their potential use for future research of treatment effects and recovery in schizophrenia is also discussed.

Original languageEnglish (US)
Pages (from-to)696-714
Number of pages19
JournalClinical Psychology Review
Volume27
Issue number6
DOIs
StatePublished - Jul 2007

ASJC Scopus subject areas

  • Clinical Psychology
  • Psychiatry and Mental health

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