Shirley M. Moore

Predictors of cardiac rehabilitation initiation.

&NA; This study determines the effects of 15 potential predictors on cardiac rehabilitation (CR) initiation: demographic information, measures of perceived severity, perceived susceptibility, perceived cardiac threat, social support, depression, comorbid conditions, left ventricular ejection fraction, strength of physician recommendation, and benefits and barriers. Results showed that greater strength of physician recommendation and less disease severity were significant predictors of higher levels of CR initiation; female gender was a marginally significant predictor of less CR initiation. The strength of the associations for these predictors varied. Strength of physician recommendation was the strongest predictor. This information can be used to increase the number of patients starting CR through programs designed to increase physician awareness of the importance of their recommendation, the continuing need to refer women to CR, and the need to design programs that meet womens needs.

CABG Discharge Information Addressing Women's Recovery

Womens descriptions of the coronary artery bypass surgery recovery experience were elicited for development of a preparatory discharge information intervention. In a convenience sample, 20 women (mean age= 67 years) were interviewed about the physical sensations, emotions, and concerns they experienced after CABG at three measurement points: discharge, 2 days after discharge, and 3 weeks following discharge. Many of the recovery experiences reported by women in this study are not addressed in traditional CABG discharge information.

Recovery symptoms and mood states in Thai CABG patients

Recovery symptoms and related mood states during early recovery after coronary artery bypass graft surgery (CABG) have never been assessed in Thailand. This cross-sectional descriptive correlational study was to identify the relationships between frequency of recovery symptoms and mood states of a convenience sample of 91 Thai CABG patients during 2 weeks after discharge. Standardized tools/procedures were used to measure the variables of interest. The most common recovery symptoms were chest and leg incision pain, having trouble sleeping, and neck and shoulder or back discomfort. The most common mood states were confusion, anxiety, and anger, respectively. In addition, Thai CABG patients who had more frequent recovery symptoms also had greater negative mood disturbance. These findings provide a beginning explanation about the phenomena of recovery symptoms and mood states in a specific culture, Thai CABG patients.

Older adults' early disability following a cardiac event.

Using the disablement model, the authors examined the following questions in adults 70 years of age and older during the 6 weeks following hospitalization for a cardiac event: (a) What are the patterns in physical performance, self-report of functional limitations, and disability, and (b) to what extent does physical performance in the hospital and self-report of functional limitations pre-event predict 6-week disability? Data were collected before discharge and 3 and 6 weeks later on a sample of 60 older adults after a cardiac event. Results show that although the majority of participants improved in their objective physical performance, 70% self-reported no improvement or worsening. Physical performance during hospitalization is a better predictor of disability than a pre-event self-report of functional limitations, even when controlling for depression, gender, and comorbidity. Assessment of objective physical performance prior to discharge will help to identify older adults at risk for progressive disability.

Self-experiments and analytical relapse prevention.

Patients give many reasons for why they have not kept up with their resolutions; research shows that many of these causal attributions are wrong. This article provides a tool to help patients sort out causes of and constraints on their behavior, in general, and exercise, in particular. Patients diary data can be analyzed to flag erroneous causal attributions, and thus assist patients to understand their behavior. To start the diary, the clinician works with the patient to assemble a list of possible causes. Using the list, a diary is organized that tracks the occurrences of various causes and the target behavior. At the end of 2 to 3 weeks, the diary data is analyzed using conditional probability models, causal Bayesian networks or logistic regression. A key issue in the analysis of diary data is to separate out the effect of various causes. Typically, causes co-occur, making it difficult to understand their independent effects. Another problem with analysis of diary data is the small size of the data. This article shows how small longitudinal data from patient diaries can be analyzed. The analysis may refute or support causes hypothesized by the client. The patient uses the insights gained from the diary analysis to prevent relapse to unhealthy behaviors. The process is continued for several cycles of organizing, keeping, and analyzing the diary data. In each cycle, the patient gains new insights and makes additional attempts to create a positive environment that allows him or her to succeed even if his or her motivation waivers. This article provides details of how diary data can be analyzed to help patients make correct causal attributions.