NIDA research monograph最新文献_第4页

Back to basics: fundamental cognitive therapy skills for keeping drug-dependent individuals in treatment. 回到基础:基本的认知治疗技巧，让药物依赖者继续接受治疗。

NIDA research monograph Pub Date : 1997-01-01

B S Liese, A T Beck

{"title":"Back to basics: fundamental cognitive therapy skills for keeping drug-dependent individuals in treatment.","authors":"B S Liese, A T Beck","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Cognitive therapists who treat drug-dependent patients are likely to lose at least 50 percent of their patients to dropout. This chapter has presented a cognitive model for conceptualizing missed sessions and dropout, along with strategies for reducing the likelihood of missed sessions and dropout. The following should serve to highlight these strategies. 1. Therapists are encouraged to offer warm, empathetic, collaborative relationships in which drug-dependent patients can feel accepted, understood, and validated. 2. Therapists are encouraged to develop comprehensive, accurate case conceptualizations, with attention paid to the potential for missed sessions and dropout. Case conceptualizations should ultimately guide cognitive and behavioral techniques. 3. Therapists are encouraged to structure sessions and elicit feedback regarding their patient's thoughts and beliefs about therapy and the therapist. This feedback is facilitated by such questions as, \"What do you like most about therapy?\" \"What do you like least?\" \"What has changed in your life as a result of therapy?\" \"How do you view our relationship?\" 4. Therapists are encouraged to socialize patients in a timely, appropriate manner. 5. Similar to the process of socialization, therapists are encouraged to use cognitive and behavioral techniques in a timely, appropriate manner. It is unrealistic to think that the problems of missed sessions and dropout from drug treatment will ever be fully resolved. Nonetheless, the authors believe that the conceptual models and fundamental strategies presented in this chapter represent a significant step in addressing these problems.</p>","PeriodicalId":76229,"journal":{"name":"NIDA research monograph","volume":"165 ","pages":"207-32"},"PeriodicalIF":0.0,"publicationDate":"1997-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"20187203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The use of the psychological laboratory to study sensitive survey topics. 利用心理实验室研究敏感的调查课题。

NIDA research monograph Pub Date : 1997-01-01

G B Willis

引用次数: 0

Inhalation studies with drugs of abuse. 药物滥用的吸入研究。

NIDA research monograph Pub Date : 1997-01-01

Y Meng, A H Lichtman, D T Bridgen, B R Martin

引用次数: 0

Antibodies as pharmacokinetic and metabolic modifiers of neurotoxicity. 抗体作为神经毒性的药代动力学和代谢调节剂。

NIDA research monograph Pub Date : 1997-01-01

S M Owens

引用次数: 0

Treatment effectiveness score as an outcome measure in clinical trials. 治疗效果评分作为临床试验结果的衡量标准。

NIDA research monograph Pub Date : 1997-01-01 DOI: 10.1037/e495552006-011

W. Ling, S. Shoptaw, D. Wesson, R. Rawson, Margaret A. Compton, Klett Cj

{"title":"Treatment effectiveness score as an outcome measure in clinical trials.","authors":"W. Ling, S. Shoptaw, D. Wesson, R. Rawson, Margaret A. Compton, Klett Cj","doi":"10.1037/e495552006-011","DOIUrl":"https://doi.org/10.1037/e495552006-011","url":null,"abstract":"A variety of measures are used for evaluating patients’ responses to substance abuse treatments. These range from physical measures (such as samples of urine, breath, hair, or blood), self-reports of drug use (such as the Addiction Severity Index (ASI) or the Time Line Follow-Back), self-reports of psychological or physiological functioning (such as symptom checklists or craving or mood ratings), and collateral reports. Physical indices of recent drug use, such as urine toxicology screens, are preferable to self-report or collateral reports for evaluating patients’ responses to drug abuse treatments because of their objectivity. In order to optimize the likelihood of both detecting individual episodes of problem drug use and correctly inferring drug abstinence based on urine toxicology results, guidelines have been suggested for collection procedures and timing for collection of urine specimens (Blaine et al. 1994; Cone and Dickerson 1992; Jain 1992). However, the difficult task of aggregating urine toxicology results remains, whether when interpreting the response of a single patient to a specific treatment or when evaluating a treatment’s effectiveness based on a group of patients’ responses in a clinical trial. Difficulties in aggregating urine toxicology results include, but certainly would not be limited to, such problems as the frequency and sensitivity of toxicology screens, early termination of some patients from treatment (or, conversely, the continued participation of some patients who respond poorly to treatment), and problems of analyzing a data matrix that contains a large number of missing datapoints. This chapter reviews the objective indices of treatment response that have traditionally been used and suggests three composite methods for evaluating these data: the Treatment Effectiveness Score (TES), the Joint Probability score (JP), and the Clinical Stabilization Score (CSS).","PeriodicalId":76229,"journal":{"name":"NIDA research monograph","volume":"175 1","pages":"208-20"},"PeriodicalIF":0.0,"publicationDate":"1997-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57798737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 52

Cognitive-neuromotor assessment of substance abuse: focus on issues related to cocaine abuse treatment. 药物滥用的认知神经运动评估：关注可卡因滥用治疗相关问题。

NIDA research monograph Pub Date : 1997-01-01 DOI: 10.1037/E495552006-010

E. Ellinwood, T. Lee

引用次数: 2

Goals and rationale for pharmacotherapeutic approach in treating cocaine dependence: insights from basic and clinical research. 药物治疗方法治疗可卡因依赖的目的和基本原理:来自基础和临床研究的见解。

NIDA research monograph Pub Date : 1997-01-01 DOI: 10.1037/e495552006-002

M. Kreek

引用次数: 12

Analysis With Missing Data in Prevention Research 预防研究中缺失数据分析

NIDA research monograph Pub Date : 1997-01-01 DOI: 10.1037/10222-010

J. Graham, S. Hofer, A. Piccinin

{"title":"Analysis With Missing Data in Prevention Research","authors":"J. Graham, S. Hofer, A. Piccinin","doi":"10.1037/10222-010","DOIUrl":"https://doi.org/10.1037/10222-010","url":null,"abstract":"Missing data problems have been a thorn in the side of prevention researchers for years. Although some solutions for these problems have been available in the statistical literature, these solutions have not found their way into mainstream prevention research. This chapter is meant to serve as an introduction to the systematic application of the missing data analysis solutions presented recently by Little and Rubin (1987) and others. The chapter does not describe a complete strategy, but it is relevant for (1) missing data analysis with continuous (but not categorical) data, (2) data that are reasonably normally distributed, and (3) solutions for missing data problems for analyses related to the general linear model in particular, analyses that use (or can use) a covariance matrix as input. The examples in the chapter come from drug prevention research. The chapter discusses (1) the problem of wanting to ask respondents more questions than most individuals can answer; (2) the problem of attrition and some solutions; and (3) the problem of special measurement procedures that are too expensive or time consuming to obtain for all subjects. The authors end with several conclusions: Whenever possible, researchers should use the Expectation-Maximization (EM) algorithm (or other maximum likelihood procedure, including the multiple-group structural equation-modeling procedure or, where appropriate, multiple imputation, for analyses involving missing data [the chapter provides concrete examples]); If researchers must use other analyses, they should keep in mind that these others produce biased results and should not be relied upon for final analyses; When data are missing, the appropriate missing data analysis procedures do not generate something out of nothing but do make the most out of the data available; When data are missing, researchers should work hard (especially when planning a study) to find the cause of missingness and include the cause in the analysis models; and Researchers should sample the cases originally missing (whenever possible) and adjust EM algorithm parameter estimates accordingly.","PeriodicalId":76229,"journal":{"name":"NIDA research monograph","volume":"142 1","pages":"13-63"},"PeriodicalIF":0.0,"publicationDate":"1997-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57476962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 311

Network Theory: A Model for Understanding Drug Abuse Among African-American and Hispanic Youth 网络理论:一个理解非裔美国人和西班牙裔青年滥用药物的模型

NIDA research monograph Pub Date : 1997-01-01 DOI: 10.3109/10826089709035606

M. Krohn, T. Thornberry

引用次数: 2

The role of iminium-enamine species in the toxication and detoxication of cyclic tertiary amines. 最小烯胺类在环叔胺的毒性和解毒中的作用。

NIDA research monograph Pub Date : 1997-01-01 DOI: 10.1037/e495572006-009

L. Sayre, D. Engelhart, D. Nadkarni, M. K. Manoj Babu, A. M. Flammang, G. Mccoy

引用次数: 13