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Clinician attributions and disease model perspectives of mentally ill, chemically addicted patients: a preliminary investigation
Journal article   Open access   Peer reviewed

Clinician attributions and disease model perspectives of mentally ill, chemically addicted patients: a preliminary investigation

Jacqueline D Kloss and Stephen A Lisman
Substance use & misuse, v 38(14), pp 2097-2107
Dec 2003
PMID: 14677783
url
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.465.9083View

Abstract

Adaptation, Psychological Adult Alcoholism - complications Alcoholism - therapy Attitude of Health Personnel Attitude to Health Diagnosis, Dual (Psychiatry) - psychology Female Humans Male Mental Health Services - manpower Middle Aged Models, Psychological Problem Solving Professional-Patient Relations Schizophrenia - complications Schizophrenia - diagnosis Schizophrenia - therapy Substance Abuse Treatment Centers - manpower Surveys and Questionnaires
Brickman et al.'s (Brickman, P., Rabinowitz, V. C., Coates, D., Cohn, E., Kidder, L. (1982). Models of helping and coping. American Psychologist 37:364-384.) models of helping and coping provided a framework by which to compare clinicians' attributions of blame and control among several hypothetical patients. Sixty-one mental health clinicians (MHCs) and addiction clinicians (ACs)--mostly master's level clinicians and registered nurses--rated attributions toward vignettes that depicted individuals with schizophrenia, alcoholism, and mentally ill, chemically addicted (MICA) classifications in 1995. Results indicate that MHCs attributed more blame to MICA patients than did ACs, but did not differ on their attributions of control. MHCs' and ACs' attributions of blame and control were generally low, consistent with a medical model. However, the endorsement of a disease model of alcoholism did not significantly predict the amount of blame attributed by the clinicians. Implications for treatment planning for MICA patients are discussed.

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Collaboration types
Domestic collaboration
Web of Science research areas
Psychiatry
Psychology
Substance Abuse
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