Are Functional Limitations Predictive of Use of Complementary and Alternative Medicine by Chronic Pain Patients?

Chronic pain is an escalating problem in the United States, with a prevalence of over 100 million people at an annual cost of $560 – 635 billion per year in medical costs and lost productivity. Some of the consequences of chronic pain are functional limitations, limitations in activities of daily living, and emotional limitations that present as anxiety, depression, and substance abuse. Many chronic pain patients turn to complementary and alternative medical techniques due to dissatisfaction with conventional medical care, despite the inconsistent results of clinical trials on these techniques. While some health-related and demographic predictors for use of complementary and alternative techniques are known, it is not known if the level of limitations can help predict the use of complementary and alternative techniques in chronic pain patients. The 2012 National Health Interview Survey had detailed questions asking about chronic pain conditions, functional limitations, limitations in activities of daily living, emotional limitations, and the use of a wide variety of complementary and alternative medicine techniques. This study tested whether limitations in activities of daily living, emotional limitations, and the number or type of functional limitations was predictive of the use of complementary and alternative medicine. This knowledge could be of use in designing future clinical trials of these techniques, in the hope of obtaining more consistent results. This study found that while the number or type of functional and emotional limitations was not a significant predictor of using complementary and alternative medicine, these limitations did significantly interact with the health-related and demographic predictors in the model. Further exploration of these interactions will be necessary to determine if they could be helpful in designing future clinical trials for complementary and alternative medical techniques.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Masters

Discipline thesis:degree_discipline

Bioinformatics (UMKC)

Grantor dc:publisher

University of Missouri--Kansas City

Year dc:date.issued

2017

Author dc:creator

• Montgomery, Deborah I. L.

Advisor dc:contributor.advisor

• Gerkovich, Mary M., 1950-

Language dc:language.iso

en_US

Handle dc:identifier.uri

https://hdl.handle.net/10355/62440

OAI identifier oai:identifier

oai:mospace.umsystem.edu:10355/62440