Thesis Summary


Abstract: The author utilized the study protocol termed within subject design and 30 postmenopausal women with poor sleep quality were recruited to wear a validated Actigraph sleep monitor wristwatch (Sadeh, Sharkey, & Carskadon, 1994). The sleep monitors was worn for 6 consecutive nights of measurement. The first two nights were used to measure baseline sleep architecture and also included the Canadian School of Osteopathy Manual Practice osteopathic assessment on the first night. The first of two 90-minute treatments occurred on the third day and the final 90-minute treatment occurred on the fifth day. Participants returned the actigraph sleep monitor after 6 nights for data collection.
Introduction of Problem Statement: This particular population of women often complains of hot flashes associated with sleep disturbances. However there are studies that both correlate and dispute hot flashes as a primary cause of sleep disturbances (McAvey & Neal-Perry, 2010). Quality of sleep remains difficult to manage safely for many women during the climacteric stage and chronic sleep deprivation increases health risks. According to Cappucio, D’Elia, Strazzullo, and Miller (2010, p.414), the development of type 2 diabetes can be significantly predicted by the quantity and quality of sleep and the mechanisms behind this relationship may differ according to the specific sleep pattern.
Goal and Objectives: The goal of this study is to improve the sleep quality of postmenopausal women by improving the adaptability of the inherent physiology, which the author postulates can lead to decreased climacteric symptoms and improved sleep quality. The author chose to work on this subject because he believes that methodology of the Canadian School of Osteopathy Manual Practice—Vancouver Campus (CSO–VC)) can be a safe treatment solution to help improve the quality of sleep for women who pass through the climacteric stage and who can often suffer greatly from sleep disturbances, which can lead to insomnia and depression (Eichling & Sahni, 2005).
Current State of knowledge and Research justification: According to a systematic review and meta-analysis by Xu and Lang (2014) there is an independent relationship within stages of menopause and sleep disturbances that is beyond the effects of aging. There was also a higher occurrence of sleep disturbances in postmenopausal women compared to premenopausal women. This study by Xu and Lang only identified culture and ethnicity as cofounders to increased sleep disturbances and did not consider the concept of lack of physiological adaptability as a contributing factor. The author postulates that the CSO–VC methodology is ideal in its approach to restoring physiological adaptability to postmenopausal women with sleep disturbances. Lack of physiological adaptability may be an unexplored cofounder in sleep disturbances amongst postmenopausal women. A recent editorial in the publication Neuropsychopharmacology eloquently expresses the necessity to appreciate individual differences in a woman’s ability to adapt to stressors. McEwen (2000) states that there is a paradox within the general adaptation syndrome theory by Hans Selye (1936), specifically that the autonomic and adrenocortical systems act to protect the body from stress in the short run, but also can cause damage and disease when they are active over a long period of time. According the text Sleep Disorders Medicine, sleep is regulated by homeostasis and includes increasing sleep drive during continued wakefulness and circadian factors. Sleep is essentially caused by the cessation of sensory signals assailing the brain. This requires that the sympathetic tonus of the central nervous system be met with the available parasympathetic system to dampen sensory input (Chokroverty, 2009). The application of the CSO–VC methodology may be ideal for decreasing sympathetic facilitation and increasing parasympathetic tonus, which has possible implications for decreasing sleep disturbances in postmenopausal women. Arousals are transient phenomena resulting in fragmented sleep without behavioural awakening and will be defined as sleep disturbances for the purpose of this study.
Anatomy: The relevant anatomy includes the liver, diaphragm, stellate ganglion, hypothalamus, pituitary, kidneys/adrenals, thyroid and ovaries. There are many ways in which each one of these structures could be lesioned indirectly by surrounding structures or directly through trauma. There are different variables that influence each woman uniquely and there may also be certain pre- pathological trends that are worth considering in how the individual is able to adapt to the stressors of the climacteric period.
Methods: The practice and methodology of general osteopathic techniques as taught by the Canadian School of Osteopathy Manual Practice–Vancouver Campus. The research method will be comprised of general osteopathic assessment prior to osteopathic treatment intervention, utilizing the methodology of assessment and prioritization of lesions developed by the CSO–VC (Appendix A). Given the serious consequences associated with sleep deprivation, patients may benefit from a concentrated treatment application of three hours of treatment within two days. The goal of this concentrated treatment application is to trigger a change in the physiology away from allostatic load, which is defined by Shulkin (2004, p.78) as the integrated output of physiological systems that negatively affect the body as it tries to adapt repeatedly back towards homeostasis.
Study Design: This research is a within subject design and time series. The study will consist of a baseline measurement, two treatment interventions and post-treatment measurements. This study duration is six nights in total: two nights with a base line measurement and four nights post treatment measurements. Participants are assessed and a medical history interview takes place on night number one. Participants return on night’s number three and five for a 90-minute treatment.
Subjects: All participants in the study will be symptomatic, non-surgical postmenopausal women, not limited by age or race, with an accompanied PSQI sleep score of greater than 5 and a score of greater than “0” on the GCS. A medical intake form will be used to identify other concerns that could be contributing to poor sleep or potential medical conditions that would require consulting a physician (Appendix G).
Independent Variables: The independent variable is one 90-minute assessment and two 90-minute treatments within one week. Each visit is two days apart. The assessment and treatments will be performed according to Canadian School of Osteopathy Manual Practice–Vancouver Campus methodology (Appendix A).
Dependant Variable: The dependent variable is the decrease in sleep cycle movement as measured by the validated Actigraph sleep monitor (Appendix I). A secondary dependant variable will be the validated Green Climacteric Scale (GCS) is used with permission (Appendix K).
Measuring Devices: A validated Sleep Quality Index (Buysse, 1989), (Appendix D).The Green Climacteric Scale (GCS) is used with permission (Appendix K) and is a standard measure of core menopausal symptoms or complaints. The ActiGraphTM wrist watch sleep monitor has been validated in a comparative study with the “gold standard” polysomnography (PSG) and had a value of 97 percent when using the Sadeh algorithms against a PSG (de Souza, 2003).The National Sleep Foundation sleep diary was obtained from the National Sleep Foundation (NSF) website (Appendix L).
Bias and Ethics: The author will blind himself from all data collected by the ActiGraphTM for the duration of the one-week study, as the sleep monitors are without a display and data can only be viewed in a read-only format once it is downloaded at the end of the study. Titles from the Greene Climacteric Scale and the Pittsburgh Sleep Quality Index will be removed so that participants will
not be biased when completing the questionnaires, which are to be handed in at the end of the study.
Data Analysis: The sleep analysis report will be delivered to the statistician to formulate final analysis. Data from the ActiGraphTM are processed by the ActiLife 6 software, which downloads all data collected. ActiLife 6 is used to prepare ActiGraphTM devices for data collection and to download, process, score and securely manage collected data into a sleep analysis report. ActiLife 6 contains the independently validated, industry standard Sadeh and Cole Kripke algorithms (Sadeh, 1994).
Results: There was no significant decrease in sleep disturbances present in the data, which included all of the 30 study participants. For this reason subgroups were created by the author and studied separately by the statistician utilizing a linear regression. The linear regression compared nights three, four, five and six against age of the participants, GCS score totals; PSQI score totals and body mass index (BMI) score totals. Although linear regression analysis determined that there was no statistically significant data,but there was a measureable trend within the (p-value=0.058) linear relationship between actigraph data at night 6 post-treatment and the women with BMI of 25 and over. This means that there was no change in sleep disturbances for nights three, four and five, but there was finally a measureable change at night six, however only with the women who had a BMI of equal to or higher than 25. A BMI of 25 of higher is considered overweight. Inferential statistics were compiled using the validated Greene Climacteric Scale (GCS), which were completed pre-study and again following night 6 post-treatment. A paired t-test was used to compare mean GCS scores pre- and post-treatment. The paired t-test showed a statistically significant difference (p-value <0.0001) in mean scores between pre- and post-treatment GCS scores (mean 8.6667, 95% CI (-11.6172, -5.7161)). This means that the symptoms of the climacteric stage measured pre-treatment had significantly decreased post-treatment.
Discussion: All 29 participants reacted with very little variability to the treatments, which supports the author’s notion that the CSO–VC methodology was applied consistently for each participant regardless of individual physiological circumstances. There were no adverse reactions to the osteopathic treatments such as increasing sleep disturbances. There were only two women out of 29 who reported worse scores post-treatment on the GCS, which indicates that climacteric symptoms had worsened. This left 27 out of 29 women with a significant improvement in climacteric symptoms according to the validated GCS. There was no correlation for the two women who reported an increase in symptoms with any increase in sleep disturbances present in the data analysis. This was also supported by the fact that there was so little variability among all study participants. There was also no correlation between the remaining 27 women, representing 90% of participants, who reported improved symptoms with the GCS recorded in the actigraph sleep data. This indicates that the subjective changes of improved symptoms were not expressed with decreased sleep disturbances for the first five nights as the body was likely still in allostatic load resistance and needed more time or more treatments to change.
On the sixth night, the participants with higher Body Mass Indices began to show a trend of a decrease in sleep disturbances likely due to the fact that the higher Body Mass Index (BMI) contributed to more stress on the physiology. The BMI is a scale that uses a weight-to-height ratio, which is then calculated by the division of a participant’s weight in kilograms against the square of one’s height in meters. This measurement is used as an indicator of obesity or, conversely, of being underweight. The data revealed that participants with a BMI of 25 or more, the threshold for indicating obesity, were the first to respond to treatments; it can be said that they seemed to have required fewer treatments to establish a trend of a decrease in sleep disturbances than participants with a lower BMI. Since there was very little variability between all participants, indicating that there was very little change in the way that each participant responded to the treatments, the author postulates that the treatments were consistently applied according to individual needs. The approach by the author did not change during the experiment regardless of the circumstances or lesions present. The author believes the methodology of the CSO–VC was applied safely and appropriately according to available patient vitality
Conclusion: The hypothesis presented by the author states that osteopathic treatment can decrease sleep cycle movement in symptomatic postmenopausal women with sleep disturbances as measured by the Actigraph sleep monitor. The hypothesis was null as no significant data collected by the actigraph sleep monitor was measured. There was however significance in the Greene climacteric index used to measure menopausal symptoms. Although the original hypothesis did not include the linear comparison of BMI scores, the final data revealed a measureable trend towards less sleep disturbances for this population of a BMI of 25 or more.