One challenging aspect of measuring such a cleansing program is that, theoretically, subjects may feel worse on the way to feeling better. Ayurveda addresses this as the body’s cleansing mechanism and other CAM systems label such reactions as “healing crises”. Given this, the researchers were surprised that there were no serious side effects reported and a low level of reported mild side effects, such as gastrointestinal upset or brief insomnia. At baseline, 21% of subjects reported mild side effects, which most likely represent the effects of the preprogram dietary changes and the experience of everyday life. The moderate level of reported side effects rose insignificantly to 26% after 5 days at the retreat. While this result is positive, we were disappointed that our main hypothesis was not supported; there were also no significant changes, positive or negative, in general symptoms as measured by the SF-12[23
]. There are many possible explanations for this: a true lack of benefit to overall quality of life, the negative effects of the cleansing process were balanced by any positive effects, or the self-report measurement was not sensitive in this sample. We were also surprised that anxiety decreased significantly at 3 months post-treatment, but not immediately after treatment; this could be an indication of the situational anxiety caused by the deep cleansing program, and lack of ability to rely on home-based behavior patterns and comfortable routines.
While we did not find evidence that overall quality of life was improved through the use of Panchakarma, as a program of behavior change, our preliminary results suggest that the complex intervention may be effective in assisting one’s actual and expected adherence to new and healthier behavior patterns. That is, with statistical significance, following the intervention, the Lifestyle Profile II showed a greater frequency of positive patterns and subjects reported greater self-efficacy in using Ayurveda to promote positive health changes.
It also appears that that perceived social support might be part of the mechanism of these changes. With a larger sample and adequate controls, we could model social support as a mediator or modifier of behavior change. Yet it may be more appropriate to consider the social world as a necessary part of a holistic intervention. While social factors may mediate one’s ability to achieve a certain outcome, considering such changes exclusively in a linear manner, at least in the beginning of an investigation, would impede our ability to see how factors are related to each other. Research in this area has indicated that the addition of social support, even as a piece of a larger intervention, may not be effective[19
]. Perhaps an important mechanism in complex CAM systems is the very thing that subjects report enjoying most — the patient is considered as a whole, in context[7
]. Social support is not an added factor, but an emergent quality of the system. This is supported by other research that shows that behavior change programs are more effective the more relevant the messages are or how well the program is incorporated into the person’s regular life[32
]. Behavior change programs work better when the program is made salient to the subject. Improving perceived social support might be a way to improve salience and social support may be easily influenced through holistic systems.
If this is true, then it points to new questions in the area of health behavior research. One frustration to health behavior scientists is that, generally, important aspects of subjects’ social world are nonmodifiable. Many of our health risks are affected by our social determinants — race, gender, education — factors that are not easily modifiable. Yet the results of these social determinants — anxiety, low self-efficacy — may be modifiable in the context of complex CAM medical interventions for the very reason that such interventions work inherently on the level of the subject’s social world.
But how do we know that we modified perceived social support and did not just add new social connections? While not a main study outcome, we wanted to consider this question and thus we also measured the subjects’ reported social network index[33
] at the same three data collection points. The social network index is a structural measure of the subject’s social contacts and the use of those contacts. No significant reported changes were found following Panchakarma in this structural measure. This is interesting because it supports the idea that perceived social support could be increased without actual structural changes in the social network. The way that the subject thinks about his/her social world changes, even if no new individuals are added; it is a perceptual and phenomenological change, not a structural change. Adding supportive people may help, but this study suggests that changing the individual’s perceptions, without adding people, may also be important.
Much research has shown that perceptual factors, such as quality of life and expectation about health, are predictive of overall health[32
]. Holistic health interventions may offer insights on how to modify lived experience. In such a holistic world view, lived or phenomenological experiences are factors or symptoms that can be treated. This project also included the collection of three qualitative interviews conducted prior to the retreat, immediately after, and 3 months postretreat. The interviews investigated the subject’s health history, health practices, expectations of treatment, and experiences with the Panchakarma program. A future step for this project is to analyze the qualitative interview data in order to add a phenomenological understanding of this process, and perhaps to link phenomenology with standardized outcomes. If the qualities of lived experience are related to later disease outcomes, then examining and modifying such qualities may be helpful in disease prevention. This idea is utilized in other well-studied health sciences[35
], so learning more about how Ayurveda models such relationships will likely add to our scientific understanding of the mechanisms of health and healing.
Although these results are encouraging, a significant limitation is the generalizability of the sample. This is a self-selected population and data were not collected on the individuals who dropped out, leaving us unsure if those that remained in the study had more positive experiences. Future work would be strengthened by the addition of a control group, the addition of selected biomarkers of health status, and further exploration of who dropouts are. Still, our initial preliminary look at this program is promising, both in terms of feasibility, but also in that we achieved statistical significance for the measures selected. Also, our use of a long-term follow-up allowed us to see that the positive effects achieved during the program were maintained 3 months after the program was completed and the individuals returned to their usual life context.