This project is aimed at providing objective data on causes of non- adherence to nasal continuous positive airway pressure (CPAP) in patients with obstructive sleep apnea (OSA) during the first week of treatment. Nasal CPAP is the primary non-surgical treatment for OSA. However, recent evidence indicates that only about half of all patients who accept CPAP actually follow this prescription, and that for the approximately 45% of patients who become non-adherent to CPAP, the pattern of non-adherence is established early in treatment within the first few days of CPAP use are limited and we believe that the development of ways to improve CPAP depends heavily upon first establishing reliable predictors to CPAP non- adherence. Given how early non-adherence to CPAP occurs in patients, we hypothesize that after the first night of home treatment, adherence on subsequent nights will be determined by: 1) patients' pre-treatment perceived self-efficacy (i.e., perceived vulnerability to OSA risks, expectations regarding ability of CPAP to reduce OSA risks, and perception of ability to master demands of CPAP therapy); 2) immediate treatment disease-reduction efficacy (i.e., capability of CPAP treatment to reduce elements of disease severity such as apnea); and 3) immediate treatment- delivery efficacy (i.e., delivery of therapeutic pressure and presence of side effects). In addition, to these three components of our conceptual model, we will also study the predictive value of demographic characteristics and objective and subjective disease severity. A sample size of 200 OSA patients RDI greater than or equal to 15) will be recruited. After their polysomnogram subjects will complete subjective and objective measure of pre-treatment disease severity and perceived self- efficacy. Daily diaries and actigraphs will be completed pre-treatment and during treatment to obtain home measures of subjective objective sleep quality. For the first seven days of treatment, the presence of residual apneic events, airflow limitation, and mask leaks will be monitored in the home using the AutoSet/TM Clinical system (ResMed Corp.). This system will also be used the following 14 days, but only to monitor CPAP use to determine the pattern of CPAP adherence. Presence of side effects will be documented on the diary completed during treatment. The results of the most powerful prediction equation we can derive from this study will be used for the detection of patients most likely to become non-adherent to CPAP therapy and to target the most cost-effective ways to intervene and enhance the use of CPAP by patients with OSA.
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