Editorial Reviews. ronaldweinland.info Review. When you look at the popularity of mind- body medicine today, it's hard to understand what a groundbreaking book this. The term, 'Relaxation Response' was coined by Dr. Herbert Benson, book The Relaxation Response, Dr. Benson describes the scientific. The Relaxation Response is a natural innate protective mechanism which allows us to turn off harmful effects from stress through changes that decrease heart.
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Page 1. Page 2. Page 3. Page 4. Page 5. Page 6. Page 7. Page 8. Page 9. Page Page Page The relaxation response (RR) is a mind-body intervention that counteracts the harmful effects of stress. Previous studies with relaxation techniques have shown the non-pharmacological benefit of reducing stress and improving the memory of healthy older adults.  The technique. Steps to Elicit the Relaxation Response. The following is the technique reprinted with permission from Dr. Herbert Benson's book. The Relaxation Response.
Conceived and designed the experiments: Performed the experiments: Analyzed the data: Wrote the paper: The relaxation response RR is the counterpart of the stress response.
In addition, we also investigated the effect of the pre-contraction level on the relaxation task.
All participants provided informed consent, and the study protocol was approved by the ethics committee of the National Institute of Fitness and Sports in Kanoya. Experimental procedures Participants were seated comfortably in a custom-designed chair with the right leg fully extended.
When performing the release, participants were specifically instructed not to activate the antagonist muscle. Figure 1 Study schematic. Schematic of experimental set-up a , and an example of EMG recording in soleus muscle during contraction or relaxation tasks during light-on status or light-off status dotted line b. Triangles indicate onset or termination of EMG signal. The soleus muscle was chosen because it is a single-joint muscle[ 11 ].
A DL single-differential, parallel-bar configuration 4 Assist, Inc. Statistical analysis The contraction response time C-RT was measured from the light-on or light-off status to the onset of EMG activity. The relaxation response time R-RT was measured from the light-on or light-off status to the termination of EMG activity.
The EMG signals were processed using full-wave rectification time constant: 0. The threshold was set at above 3 standard deviation of the mean of baseline activity. Muscle activity onset was defined as the first point at which the EMG exceeded this threshold for at least For the purposes of this analysis, the utilization rate was defined as the number of billable encounters and services used over the course of a year.
Utilization rates were compared before and after within the intervention arm and before and after against the control arm.
Both arms were further stratified by the type of encounter: Both intervention and control arms were also stratified by class of the chief complaint: Standard statistical methods were used including t-tests, ANOVA and regression methods where appropriate. The project was approved by the Partners Healthcare Institutional Review Board, the body providing ethics oversight for research. All patient records and information were anonymized and de-identified prior to analysis and stored on encrypted servers only accessible to the pri- mary investigator or his institutionally approved designate.
Results After matching participants by age, gender and ethnicity we found that intervention patients were more likely to speak English, identify as Asian versus African-American and more likely to identify as Jewish or not having a religious affiliation.
Members of the control group were slightly more likely to identify as Christian or Muslim Table 1. Individuals in the intervention group were also less likely to be a veteran, though they were more likely to be US born.
In the propensity score, high utilization matched subgroup, the intervention group was slightly more female than the group as a whole and the control group was slightly older, more Christian and more likely to be from the US and be a veteran than the group as a whole.
Both interven- tion and control groups spent the same amount of time, greater than 4 years continuously, within the healthcare system Table 2. For the propensity score and initial high utilization rate matched sub group this was an absolute The intervention group had significant absolute reductions in all clinical encounter types Table 4 for both the group as a whole and in the subset analysis. Socio-demographic data. This increase in clinical encounters was most pronounced in the specialty care settings in the control group.
With regard to clinical categories Table 5 , All within pre and post phase comparisons in the comparisons between intervention and control were statistically significantly different with Table 2. Patient Continuous Time in Healthcare Network. Functional Category: Utilization Rate Pre- vs. Service Site: Disease Category: High Control Utilization subgroup vs Intervention Group. The top five presenting areas in terms of total encounters in the intervention group were: In the high utilization subgroup comparison, the top four presenting areas were: Utilization by Functional class: Subgroup analysis In subgroup analysis, in the propensity scored matched subgroup, high utilizers in the control group, matched to by utilization rate to the intervention group, did show some regression to the mean over time Figs 2 and 3.
However, the matched intervention group had statistically greater reductions in healthcare resource utilization than the control group in the post inter- vention period across all functional categories and all site categories except for Emergency Care Table 4.
The intervention group statistically significantly outperformed the controls with an average relative utilization reduction of: With regard to site utilization, the intervention group had significant reductions in all cate- gories except Hospital care. In the Urgent care category the intervention group had fewer abso- lute visits post intervention than the control group. In the General Medicine, Emergency department and Hospital settings, the intervention group went from significantly more use than the controls to becoming indistinguishable from the control in the post intervention period.
In the Specialty care category, the intervention group had a Utilization by Clinical Site: With regard to functional categories, the intervention group showed significant reduction in all categories, except for procedures which increased in both groups. Imaging decreased in both groups over the study period. Laboratory testing and Imaging converged becoming indis- tinguishable from controls in the post intervention period. Clinical encounters were Discussion The main finding of this study is that the Relaxation Response Resiliency Program 3RP may sig- nificantly reduce healthcare utilization.
This reduction is on the order of that found by Caudill , Group Health, and Kaiser Permanente and other similar time-limited interventions. The focus in healthcare is shifting from high utilization of specialized care for the treatment of late-stage disease to an emphasis on patient-centered approaches and coordinated care teams that promote wellness, support self-care, provide preventive care and effective disease management.
In the process of moving from transaction-based health care to wellness and pre- vention based care, it is prudent to identify strategies and therapies that are both clinically PLOS ONE DOI: Our results indicate that mind body interventions, such as 3RP, can reduce individual disease burden as well as the utilization of healthcare resources and are well suited to the changing healthcare environment.
Mind body medicine interventions are inexpensive relative to the cost of an emergency room visit, a hospitalization or even other complementary and alternative medicine CAM therapies.
Assuming societal values meps. This translates as a return on investment ROI of 4—6 months for the reduction of emergency department visits alone, based on commonly charged fees for 3RP and similar mind body programs.
Of course, patients use more than emer- gency rooms for their care.
Using an estimate, based on improvements in average utilization rates including outpatient care general and specialist , emergency department and urgent care visits and hospitalizations, instituting 3RP could save the healthcare system substantially.
The low end of these ranges assumes only the lowest cost treat- ment site category is used in a year and the high end assumes individual encounters in all treat- ment site categories in a single year. These estimates are rough and based on aggregate numbers but give a sense of the scale of the opportunities available.
In the move from transac- tional healthcare to a more systems-based healthcare environment, these interventions may be able to significantly improve financial margins. Recent studies point toward their cost-effec- tiveness [30—32,46]. A more detailed large prospective cost accounting analysis is beyond the scope of this current paper but is certainly called for and is being planned.
It should be noted the public may be ahead of medical and insurance organizations in adopting these kinds of patient-centered approaches. It is currently unclear how best to identify in advance patients who would be most effec- tively served by these interventions.
Nonetheless, our analysis suggests that likely categories to explore are patients with mental health, neurologic, musculoskeletal, and gastroenterological concerns, particularly those who endorse high levels of stress.
In this era of electronic medical records it may also be possible to identify other high utilizing patients as potential targeted beneficiaries. Limitations As with all retrospective studies, selection bias can occur, depending on how subjects were defined and the limitations of the categories available in the database.
We tried to limit this bias by oversampling our control group and matching subjects based on age, gender, and eth- nicity, then using propensity score matching methods. Using any set of administrative data, however, incurs the risk of data categories that are not specifically designed for clinical studies. As a result the data may be subject to the interpretation of the person entering the data and this data may have been entered for administrative or billing purposes rather than clinical needs.
However, because our focus is on utilization this shortcoming should not affect our main results. Another limitation of this project to date is that by focusing on utilization rather than cost accounting or long term outcomes such as mortality and morbidity, which were beyond the scope of data readily available through the database used, we can only look at relative changes PLOS ONE DOI: The RPDR database used does not readily permit these types of calculations but based on these initial results we will be seek- ing resources to perform a detailed cost accounting as part of the next phase of the project.
There is also a risk that data might be biased by patients entering the system for the inter- vention alone and subsequently leaving the network afterwards. This is an important risk to consider especially with a major teaching hospital which draws many transient patients from out of state. However, our analysis of how long patients, both control and intervention, were in the healthcare network suggest this risk is minimal. Both sets of patients appear to be endoge- nous to the geographical area of the hospital and stable in the network, being within the system on average for greater than 4 years.
The choice of the pre and post phase for the control group at the midpoint of their career in the health system was artificial and may have introduced a timing bias or sampled from periods of high or low utilization. However, those differences would be expected to average out across the population and over time.
The rationale for this choice was to help capture both baseline behavior and potential secular changes over time. Because the average healthcare system career was over 4 years, patient entry dates were uni- formly distributed across the entire sample period and since the pre-post interval was 2 years, it was felt this was a representative sample of the healthcare careers of both the intervention and control groups.
Patients who received the intervention were, in general, a high utilizing group. To control for regression to the mean and costs that might naturally decrease over time after patients had already been referred to specialists and received multiple tests, we matched this group to a simi- larly high utilizing control group and still noted significant decreases in utilization in the inter- vention group. Nonetheless, there may have been additional factors we could not account for.
In addition, because we only followed patients out 1 year post-intervention we may not have seen the full effects of the intervention and whether or not the effects continued. There were indications in the data that this might be the case. This would bias against the effectiveness of the intervention.
Finally, there is the risk of statistical over-precision versus clinical meaning. Abstract Although the physiological and biochemical changes that occur during the acute stress response have been well-characterized, the contrasting changes that underlie the relaxation response evoked by various mind-body techniques are less understood.
To help guide future mind-body research, we present a conceptual model that integrates patterns of change at the physiological and molecular levels.
In addition, we point to future research opportunities and discuss how repeated elicitation of these responses could influence the health of patients. One of the first attempts to understand the connection between the mind and body occurred nearly years ago when Harvard physiologist Walter Cannon described the fight or flight response, identifying a consistent set of physiological changes that occur when animals, including humans, are exposed to stress. The SR consists of an involuntary set of physiological alterations that include increases in heart rate, blood pressure, respiration rate, and metabolic shifts that liberate energy.
More than 30 years ago, cardiologist Herbert Benson, one of the authors of this article, characterized another physiological state, the relaxation response RR. As new technologies such as biochemical assays have become available, researchers have been able to investigate mechanistic changes that occur during these responses as well, initially focusing on hormones, but more recently on signaling molecules such as nitric oxide NO.
Our primary aim in this article is to present a model that accounts for the physiological and biochemical changes that take place during exposure to acute stressors or elicitation of the RR and the relationship between the 2 responses.
Physiological Changes The SR triggers a cascade of physiological responses. These include increases in volumetric oxygen consumption VO2 and respiration, dilation of the bronchiolar musculature and airways, increased blood pressure caused by increased cardiac output, and increased total peripheral resistance.
It also triggers an increase of blood flow to the skin, splanchnic region, muscles, and heart. Together, these physiological responses produce a coordinated series of changes that enable the body to respond to stressful stimuli by providing energy to the areas that need it most.