Clinicians and researchers are increasingly using the term integrative medicine to refer to the merging of complementary and alternative medicine (CAM) with conventional biomedicine. However, combination medicine (CAM added to conventional) is not integrative. Integrative medicine represents a higher-order system of systems of care that emphasizes wellness and healing of the entire person (bio-psycho-socio-spiritual dimensions) as primary goals, drawing on both conventional and CAM approaches in the context of a supportive and effective physician-patient relationship. Using the context of integrative medicine, this article outlines the relevance of complex systems theory as an approach to health outcomes research. In this view, health is an emergent property of the person as a complex living system. Within this conceptualization, the whole may exhibit properties that its separate parts do not possess. Thus, unlike biomedical research that typically examines parts of health care and parts of the individual, one at a time, but not the complete system, integrative outcomes research advocates the study of the whole. The whole system includes the patient-provider relationship, multiple conventional and CAM treatments, and the philosophical context of care as the intervention. The systemic outcomes encompass the simultaneous, interactive changes within the whole person.

Complementary Therapies↗

PubMed2002

Clinical decision-making--when science is uncertain.

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Acupuncture Therapy↗

PubMed2002

Going quasi: the premature disclosure effect in a randomized clinical trial.

This paper describes a randomized clinical trial investigating a stress management program for women with breast cancer, which inadvertently turned quasi-experimental. Due to logistical considerations, group assignment was disclosed to participants (n = 63) prior to baseline assessment. Analyses of baseline measures unexpectedly revealed statistically significant differences between groups on psychological functioning. We suggest that what appears to be failed randomization may in fact point toward an important phenomenon which we have termed premature disclosure effect (PDE). A hierarchical regression model, developed to help explain the PDE, accounted for 47% of the variance. The findings indicate the importance of considering participant belief, preferences, and attributes when designing research protocols and interventions. Potential implications of PDE for clinical research in behavioral medicine are discussed and specific statistical methodologies suggested.

Attitude to Health↗

PubMed2002

Evaluating how placebos produce change. Logical and causal traps and understanding cognitive explanatory mechanisms.

The renewed interest in placebo effects from psychological and methodological angles is manifested in two complementary facets: the causal relationship between placebo effects inside and outside of clinical trials and the continual effort to understand how the underlying mechanisms relate to notions of efficacy and effectiveness. The article challenges the premise that placebo effects can be measured precisely enough that variance attributed to "nonspecific" placebo effects can be hierarchically partitioned from variance attributed to other "more specific" elements of therapy and discusses some of the most important recent developments in the understanding of how placebos produce change through cognitive explanatory mechanisms, including efficacy, outcome, and response expectancies; reverse placebo effects; schemas; and biased-information processing. Although much is already known about the complexity of explanatory mechanisms in placebo and expectancy effects, there is still much to do before establishing causal relationships and developing valid treatments based on this knowledge.

Causality↗