An Implementation and Biobehavioral Study of Temporomandibular Joint and Muscle Disorder (TMJMD)

With the great economic costs and traditionally poor outcomes among chronic temporomandibular joint and muscle disorder (TMJMD) patients, it has become important to treat patients in the acute state, in order to prevent these more chronic disability problems. This has been the goal of two past funded grant projects. Results of the initial project isolated risk factors that successfully predicted the development of chronicity with a 91% accuracy rate. A statistical algorithm was developed which was used in the second project to screen out "high-risk" patients. These patients were then randomly assigned an early intervention or non-intervention group. One-year follow-up evaluations documented the treatment efficacy and cost effectiveness of early intervention. These results have major implications for effective early intervention and significant health care cost savings for this prevalent pain and disability problem. For the present proposed project, we plan to implement this treatment program in order to evaluate its effectiveness in more community-based dental practices. This is in response to NIH's request for the implementation of evidence-based treatment approaches, developed in controlled clinical settings, to the "real world" of diverse practices in the community. Acute TMJMD patients will be recruited from two community-based clinics. Based upon our "risk" screening algorithm, high-risk patients will be randomly assigned to one of two groups (n=225/group): an early biobehavioral intervention or an attention-control group. It is hypothesized that the attention control "high-risk" patients will display more chronic TMJMD problems, relative to the "high-risk" early intervention patients, at one- and two-year follow-ups. A number of biopsychosocial measures will be evaluated, including chewing performance, the RDC/TMD, self-reported pain and stress, etc. Such a multi-level, multi-systems approach has not been applied to better understand the biopsychosocial underp