...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Quality of life research: An international journal of quality of life aspects of treatment, care and rehabilitation >Empirically driven definitions of 'good,' 'moderate,' and 'poor' levels of functioning in the treatment of schizophrenia
【24h】

Empirically driven definitions of 'good,' 'moderate,' and 'poor' levels of functioning in the treatment of schizophrenia

机译：Empirically driven definitions of "good," "moderate," and "poor" levels of functioning in the treatment of schizophrenia

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相关主题

摘要

Purpose: This study used an empirical approach to identify and validate the classification of patients with schizophrenia in "good," "moderate," or "poor" functioning groups based on the assessment of functional measures. Methods: Using data from a study of schizophrenia outpatients, patients were classified into functional groups using cluster analysis based on the Heinrich-Carpenter Quality of Life Scale (QLS), the 36-item Short-Form Health Survey (SF-36) Mental Component Summary Score, and a productivity measure. A three-cluster solution was chosen. Concurrent, convergent, and discriminant validity were assessed. Criteria for classifying patient functioning as "good," "moderate," or "poor" were established using classification and regression tree analysis. Results: The three clusters consistently differentiated patients on the QLS, SF-36 Mental Component Summary Score, and productivity measure. The clusters also differed on other functional measures and were concordant with previous functional classifications. Concurrent, convergent, and discriminant validity were good. "Good" functioning was identified as a QLS total score ≥84.5; "moderate" and "poor" functioning were separated by a cutoff score of 15.5 on the QLS intrapsychic foundation domain. Sensitivity ranged from 86 to 93 % and specificity from 89 to 99 %. Conclusions: The heterogeneity in functioning of schizophrenia patients can be classified reliably in an empirical manner using specific cutoff scores on commonly used functional measures.

著录项

获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号