SELF-CARE AGENCY AND HEALTH-PROMOTING BEHAVIOR OF A MILITARY POPULATION.
Contributors: Medical College of Georgia.
Published: 1990
Number of pages: 186
Subjects: Health Sciences, Nursing.
Description: A self-care perspective has emerged as a significant theme in the identification and understanding of health behavior patterns in various populations. This study examined the extent to which exercise of self-care agency and the basic conditioning factors of age, gender, marital status, ethnicity, military rank, duty type, formal education, and perceived health state explained reported performance of health-promoting behaviors in a military population. The Health-Promoting Self-Care System Model was developed from three nursing frameworks and tested in a random sample of 421 active-duty Navy men and women. Data were collected over a three-month period by mailed questionnaires, which included a Personal Data Form, the Exercise of Self-Care Agency (ESCA) Scale (Kearney & Fleischer, 1979), and the Health-Promoting Lifestyle Profile (HPLP) (Walker, Sechrist, & Pender, 1987). The construct validity of study measures was evaluated by principal-components analysis, revealing a five-component structure for the ESCA Scale and a six-component structure for the HPLP. Internal consistency reliabilities were.92 for the ESCA Scale and.95 for the HPLP. Stepwise multiple regression analyses demonstrated that total and subscale scores on the ESCA Scale were the strongest predictors (p $<$.001) of total and subscale scores on the HPLP. The basic conditioning factors of marital status, ethnicity, duty type, formal education, and perceived health state were differentially predictive of scores on the total HPLP and its six subscales. Cross-validation of the derived regression models on two random subsamples (n = 210 and n = 211) indicated similar findings relative to explained variances and strength of predictor variables. Prediction of group membership into high or low levels of health behavior performance, based on the full sample regression models, established a 67% to 83% range of correct classifications.
Notes: Source: Dissertation Abstracts International, Volume: 51-05, Section: B, page: 2290.

Thesis (PH.D.)--MEDICAL COLLEGE OF GEORGIA, 1990.

School code: 0305.