Self-experiments and analytical relapse prevention

Quality Management in Health Care
Farrokh AlemiHeibatollah Baghi

Abstract

Patients give many reasons for why they have not kept up with their resolutions; research shows that many of these causal attributions are wrong. This article provides a tool to help patients sort out causes of and constraints on their behavior, in general, and exercise, in particular. Patient's diary data can be analyzed to flag erroneous causal attributions, and thus assist patients to understand their behavior. To start the diary, the clinician works with the patient to assemble a list of possible causes. Using the list, a diary is organized that tracks the occurrences of various causes and the target behavior. At the end of 2 to 3 weeks, the diary data is analyzed using conditional probability models, causal Bayesian networks or logistic regression. A key issue in the analysis of diary data is to separate out the effect of various causes. Typically, causes co-occur, making it difficult to understand their independent effects. Another problem with analysis of diary data is the small size of the data. This article shows how small longitudinal data from patient diaries can be analyzed. The analysis may refute or support causes hypothesized by the client. The patient uses the insights gained from the diary analysis to prevent r...Continue Reading

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Citations

Apr 22, 2008·Quality Management in Health Care·Duncan Neuhauser
Apr 30, 2013·Journal of Religion and Health·Jordan BrownAllison R Webel
Apr 18, 2014·Nutrition in Clinical Practice : Official Publication of the American Society for Parenteral and Enteral Nutrition·Satomi IchimaruTakahiro Atsumi
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Nov 5, 2013·American Journal of Critical Care : an Official Publication, American Association of Critical-Care Nurses·Carolina Keiko Yamamoto HondaFlávia Ribeiro Machado

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