PURPOSE: Evaluate the long-term impact of telephone-based interventions that target high risk, ready-to-change individuals. DESIGN: Quasi-experimental design with pre/post comparisons of lifestyle-related health risks between participants and nonparticipants. SETTING: Six organizations from the private and public sectors. SUBJECTS: Subjects were 607 intervention participants who were compared with a control group of 1134 eligible nonparticipants. MEASURES: Health risk assessment at baseline and at an average of 2 years later measured risk in 13 lifestyle areas. INTERVENTION: Programs were offered in seven areas: back care, cholesterol control, eating habits, exercise and activities, stress management, tobacco use, and weight control. Each program was conducted by a trained health educator who provided information and counseling to facilitate change in the area selected by the participant. All counseling was done by telephone and included three to five contacts over a 1-year period. RESULTS: Binary logistic regression models controlling for gender and age revealed both specific and general effects. Participants were 1.8 to 3.5 times as likely as nonparticipants to reduce the targeted risk in six of seven risk areas. In addition, participants were 1.7 to 3.5 times as likely as nonparticipants to reduce their risks in nine of 13 areas not targeted by the intervention (i.e., general effect). Overall, participants significantly reduced their number of risks, whereas nonparticipants significantly increased their risk (difference of .85 risks). CONCLUSIONS: Results show that at-risk participants make long-term improvements in health risks directly related to the intervention in which they participate. Results also suggest that this intervention may help individuals develop behavior-change skills they can apply to other lifestyle issues.
PURPOSE: Evaluate the long-term impact of telephone-based interventions that target high risk, ready-to-change individuals. DESIGN: Quasi-experimental design with pre/post comparisons of lifestyle-related health risks between participants and nonparticipants. SETTING: Six organizations from the private and public sectors. SUBJECTS: Subjects were 607 intervention participants who were compared with a control group of 1134 eligible nonparticipants. MEASURES: Health risk assessment at baseline and at an average of 2 years later measured risk in 13 lifestyle areas. INTERVENTION: Programs were offered in seven areas: back care, cholesterol control, eating habits, exercise and activities, stress management, tobacco use, and weight control. Each program was conducted by a trained health educator who provided information and counseling to facilitate change in the area selected by the participant. All counseling was done by telephone and included three to five contacts over a 1-year period. RESULTS: Binary logistic regression models controlling for gender and age revealed both specific and general effects. Participants were 1.8 to 3.5 times as likely as nonparticipants to reduce the targeted risk in six of seven risk areas. In addition, participants were 1.7 to 3.5 times as likely as nonparticipants to reduce their risks in nine of 13 areas not targeted by the intervention (i.e., general effect). Overall, participants significantly reduced their number of risks, whereas nonparticipants significantly increased their risk (difference of .85 risks). CONCLUSIONS: Results show that at-risk participants make long-term improvements in health risks directly related to the intervention in which they participate. Results also suggest that this intervention may help individuals develop behavior-change skills they can apply to other lifestyle issues.
Authors: Laura J Damschroder; Lorraine R Buis; Felicia A McCant; Hyungjin Myra Kim; Richard Evans; Eugene Z Oddone; Lori A Bastian; Gwendolyn Hooks; Reema Kadri; Courtney White-Clark; Caroline R Richardson; Jennifer M Gierisch Journal: J Med Internet Res Date: 2020-08-04 Impact factor: 5.428
Authors: Suzan Jw Robroek; Frank J van Lenthe; Pepijn van Empelen; Alex Burdorf Journal: Int J Behav Nutr Phys Act Date: 2009-05-20 Impact factor: 6.457