Stages of change for health-related behaviours in 18 year-old Australians

Abstract This study investigated the validity of a Stages of Change algorithm with respect to independent measures of physical activity and fitness. dietary intake and alcohol consumption in 18 year-old Ausmlian men (n = 301) and women (n = 282). Stage of Change categories were related to fat and fibre intakes in men and fibre intake in women as well as hit and vegetable intakes in men and women. Physical activity and fitness for men and women also showed significant linear associations with Stage of Change categories. Alcohol consumption was significantly associated with Stage of Change categories for men but not for women although recorded alcohol consumption was very variable for women. However, the algorithm was valid for both men and women when drinking alcohol consistent with national guidelines on safe drinking was used. In summary, with reference to actual health behaviours, the Stages of Change algorithm was valid for young men and women for diet. physical activity and alcohol drinking. Independent behavioural data were not available for smoking behaviours. Using the algorithm, there were significant associations in men between prccontemplation status for diet and drinking and diet and physical activity, in women between diet and smoking and in both men and women between drinking and smoking. Covariance between precontemplation status for different health behaviours therefore suggests the need for multimodal interventions.     

Stages of change for health-related behaviours in 18 year-old Australians

Abstract

This study investigated the validity of a Stages of Change algorithm with respect to independent measures of physical activity and fitness. dietary intake and alcohol consumption in 18 year-old Ausmlian men (n = 301) and women (n = 282). Stage of Change categories were related to fat and fibre intakes in men and fibre intake in women as well as hit and vegetable intakes in men and women. Physical activity and fitness for men and women also showed significant linear associations with Stage of Change categories. Alcohol consumption was significantly associated with Stage of Change categories for men but not for women although recorded alcohol consumption was very variable for women. However, the algorithm was valid for both men and women when drinking alcohol consistent with national guidelines on safe drinking was used. In summary, with reference to actual health behaviours, the Stages of Change algorithm was valid for young men and women for diet. physical activity and alcohol drinking. Independent behavioural data were not available for smoking behaviours. Using the algorithm, there were significant associations in men between prccontemplation status for diet and drinking and diet and physical activity, in women between diet and smoking and in both men and women between drinking and smoking. Covariance between precontemplation status for different health behaviours therefore suggests the need for multimodal interventions.     

Expansion of Genetic Services Utilizing a General Genetic Counseling Clinic

We established a general genetic counseling clinic (GCC) to help reduce long wait times for new patient appointments and to enhance services for a subset of patients. Genetic counselors, who are licensed in Tennessee, were the primary providers and MD geneticists served as medical advisors. This article describes the clinic referral sources, reasons for referral and patient dispositions following their GCC visit(s). We obtained patients by triaging referrals made to our medical genetics division. Over 24 months, our GCC provided timely visits for 321 patients, allowing the MD geneticists to focus on patients needing a clinical exam and/or complex medical management. Following their GCC visit(s), over 80 % of patients did not need additional appointments with an MD geneticist. The GCC allowed the genetic counselor to spend more time with patients than is possible in our traditional medical genetics clinic. Patient satisfaction surveys (n?=?30) were very positive overall concerning the care provided. Added benefits for the genetic counselors were increased professional responsibility, autonomy and visibility as health care providers. We conclude that genetic counselors are accepted as health care providers by patients and referring providers for a subset of clinical genetics cases. A GCC can expand genetic services, complement more traditional genetic clinic models and utilize the strengths of the genetic counselor health care provider.