
Am J Psychiatry 163:1323-1334, August 2006
doi: 10.1176/appi.ajp.163.8.1323
© 2006 American Psychiatric Association
Assessing Decisional Capacity for Clinical Research or Treatment: A Review of Instruments
Laura B. Dunn, M.D.,
Milap A. Nowrangi, M.Be.,
Barton W. Palmer, Ph.D.,
Dilip V. Jeste, M.D., and
Elyn R. Saks, J.D.
OBJECTIVE: The need to evaluate decisional capacity among patients in treatment settings as well as subjects in clinical research settings has increasingly gained attention. Decisional capacity is generally conceptualized to include not only an understanding of disclosed information but also an appreciation of its significance, the ability to use the information in reasoning, and the ability to express a clear choice. The authors critically reviewed existing measures of decisional capacity for research and treatment. METHOD: Electronic medical and legal databases were searched for articles published from 1980 to 2004 describing structured assessments of adults capacity to consent to clinical treatment or research protocols. The authors identified 23 decisional capacity assessment instruments and evaluated each in terms of format, content, administration features, and psychometric properties. RESULTS: Six instruments focused solely on understanding of disclosed information, and 11 tested for understanding, appreciation, reasoning, and expression of a choice. The instruments varied substantially in format, degree of standardization of disclosures, flexibility of item content, and scoring procedures. Reliability and validity also varied widely. All instruments have limitations, ranging from lack of supporting psychometric data to lack of generalizability across contexts. CONCLUSIONS: Of the instruments reviewed, the MacArthur Competence Assessment Tools for Clinical Research and for Treatment have the most empirical support, although other instruments may be equally or better suited to certain situations. Contextual factors are important but understudied. Capacity assessment tools should undergo further empirically based development and refinement as well as testing with a variety of populations.
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