Relaxation training as complementary therapy for mild hypertension control and the implications of evidence-based...

Relaxation therapy for the treatment of hypertension presented a number of challenges, in terms of conducting and using research as well as gaining the wider acceptance of this complementary therapy in common practice in Hong Kong. Two issues were central to the current implementation of complementary therapies: the evidence-based practice movement and the management of risk during the implementation of new therapies. A major concern was how to maximize the chance of inclusion of research on complementary therapies in evidence-based practice systematic reviews. This was thought to be achievable by making the data amenable to meta-analysis when small samples may be unavoidable. The empirical work examined the effects of three relaxation therapies for the reduction of high blood pressure in nine Chinese subjects. Subjects were randomly assigned to three groups: (a) progressive muscle relaxation, (b) stretch release relaxation and (c) cognitive imagery relaxation. Systolic, diastolic blood pressure and heart rate were assessed in a baseline session, the 8th post-treatment session, and a 30-days follow-up session. Datawere analyzed using ANOVA and Paired sample t-test. One-Sample Kolmogorov-Smirnov Tests for the normal distribution were performed among the three groups. The results verified that the normality assumption for the data had not been violated. Results revealed that in the context of the study all relaxation therapies can reduce blood pressure in Chinese subjects, but stretch release relaxation and progressive muscle relaxation therapies appeared to be more effective in lowering blood pressure compared to cognitive imagery relaxation. These data are in a form available for meta-analysis at a later date. The study also shows a degree of clinical significance and validation with respect to a Hong Kong population. It demonstrates ways in which the inclusion of research on complementary therapies in systematic reviews can be maximized.