Suppr超能文献

使用人际问题量表预测药物滥用治疗中的脱落情况。

Predicting attrition from substance misuse treatment using the Inventory of Interpersonal Problems.

作者信息

Lovaglia M J, Matano R

机构信息

Stanford University, California 94305.

出版信息

Int J Addict. 1994 Jan;29(1):105-13. doi: 10.3109/10826089409047371.

Abstract

A simple, self-report scale to predict who would leave substance misuse treatment against medical advice was developed and tested. Scale items were drawn from the Inventory of Interpersonal Problems which measures interpersonal distress in the same format that the SCL-90-R uses to measure personal distress. Potential items were selected using data from an initial sample of 66 patients at a substance misuse clinic. Factor analytic techniques were then used to decide which of these items to include in the scale. It was tested using 98 patients not included in the initial sample. Logistic regression analysis confirmed that patients with high scores on the scale were significantly more likely to leave treatment than were patients with low scores.

摘要

开发并测试了一种简单的自我报告量表,用于预测谁会违背医嘱离开药物滥用治疗。量表项目取自人际问题量表,该量表以SCL - 90 - R测量个人困扰相同的格式来测量人际困扰。使用来自一家药物滥用诊所66名患者的初始样本数据选择潜在项目。然后运用因子分析技术来决定量表应包含哪些项目。使用未纳入初始样本的98名患者进行测试。逻辑回归分析证实,量表得分高的患者比得分低的患者更有可能离开治疗。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验