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Telephone-based interactive voice response (IVR) systems could be an effective tool for promotion of physical activity among older women. To test IVR feasibility, we enrolled 30 older women in a 10-week physical activity intervention designed around National Institute on Aging (NIA) Go4Life® educational materials with IVR coaching. Participants (mean age = 76 years) significantly increased physical activity by a mean 79 ± 116 (SD) minutes/week (p < .001). Participants reported that the Go4Life® materials, pedometer, and IVR coaching (70% reported easy technology) were useful tools for change. This pilot study demonstrates IVR acceptability as an evidence-based physical activity program for older women.

Telephone-based interactive voice response (IVR) systems could be an effective tool for promotion of physical activity among older women. To test IVR feasibility, we enrolled 30 older women in a 10-week physical activity intervention designed around National Institute on Aging (NIA) Go4Life® educational materials with IVR coaching. Participants (mean age = 76 years) significantly increased physical activity by a mean 79 ± 116 (SD) minutes/week (p < .001). Participants reported that the Go4Life® materials, pedometer, and IVR coaching (70% reported easy technology) were useful tools for change. This pilot study demonstrates IVR acceptability as an evidence-based physical activity program for older women.

Background Physical activity (PA) public health programming has been widely used in Mexico; however, few studies have documented individual and organizational factors that might be used to evaluate their public health impact. The RE-AIM framework is an evaluation tool that examines individual and organizational factors of public health programs. The purpose of this study was to use the RE-AIM framework to determine the degree to which PA programs in Mexico reported individual and organizational factors and to investigate whether reporting differed by the program’s funding source. Methods Public health programs promoting PA were systematically identified during 2008–2013 and had to have an active program website. Initial searches produced 23 possible programs with 12 meeting inclusion criteria. A coding sheet was developed to capture behavioral, outcome and RE-AIM indicators from program websites. Results In addition to targeting PA, five (42%) programs also targeted dietary habits and the most commonly reported outcome was change in body composition (58%). Programs reported an average of 11.1 (±3.9) RE-AIM indicator items (out of 27 total). On average, 45% reported reach indicators, 34% reported efficacy/effectiveness indicators, 60% reported adoption indicators, 40% reported implementation indicators, and 35% reported maintenance indicators. The proportion of RE-AIM indicators reported did not differ significantly for programs that were government supported (M = 10, SD = 3.1) and programs that were partially or wholly privately or corporately supported (M = 12.0, SD = 4.4). Conclusion While reach and adoption of these programs were most commonly reported, there is a need for stronger evaluation of behavioral and health outcomes before the public health impact of these programs can be established.

Background Physical activity (PA) public health programming has been widely used in Mexico; however, few studies have documented individual and organizational factors that might be used to evaluate their public health impact. The RE-AIM framework is an evaluation tool that examines individual and organizational factors of public health programs. The purpose of this study was to use the RE-AIM framework to determine the degree to which PA programs in Mexico reported individual and organizational factors and to investigate whether reporting differed by the program’s funding source. Methods Public health programs promoting PA were systematically identified during 2008–2013 and had to have an active program website. Initial searches produced 23 possible programs with 12 meeting inclusion criteria. A coding sheet was developed to capture behavioral, outcome and RE-AIM indicators from program websites. Results In addition to targeting PA, five (42%) programs also targeted dietary habits and the most commonly reported outcome was change in body composition (58%). Programs reported an average of 11.1 (±3.9) RE-AIM indicator items (out of 27 total). On average, 45% reported reach indicators, 34% reported efficacy/effectiveness indicators, 60% reported adoption indicators, 40% reported implementation indicators, and 35% reported maintenance indicators. The proportion of RE-AIM indicators reported did not differ significantly for programs that were government supported (M = 10, SD = 3.1) and programs that were partially or wholly privately or corporately supported (M = 12.0, SD = 4.4). Conclusion While reach and adoption of these programs were most commonly reported, there is a need for stronger evaluation of behavioral and health outcomes before the public health impact of these programs can be established.

Background: The extensive availability of online health information offers the public opportunities to become independently informed about their care, but what affects the successful retrieval and understanding of accurate and detailed information? We have limited knowledge about the ways individuals use the Internet and the personal characteristics that affect online health literacy. Objective: This study examined the extent to which age and cognitive style predicted success in searching for online health information, controlling for differences in education, daily Internet use, and general health literacy. Methods: The Online Health Study (OHS) was conducted at Johns Hopkins School of Public Health and Stanford University School of Medicine from April 2009 to June 2010. The OHS was designed to explore the factors associated with success in obtaining health information across different age groups. A total of 346 men and women aged 35 years and older of diverse racial and ethnic backgrounds participated in the study. Participants were evaluated for success in searching online for answers to health-related tasks/questions on nutrition, cancer, alternative medicine, vaccinations, medical equipment, and genetic testing. Results: Cognitive style, in terms of context sensitivity, was associated with less success in obtaining online health information, with tasks involving visual judgment most affected. In addition, better health literacy was positively associated with overall success in online health seeking, specifically for tasks requiring prior health knowledge. The oldest searchers were disadvantaged even after controlling for education, Internet use, general health literacy, and cognitive style, especially when spatial tasks such as mapping were involved. Conclusions: The increasing availability of online health information provides opportunities to improve patient education and knowledge, but effective use of these resources depends on online health literacy. Great

Kaycee M Sink,1 Mark A Espeland,2 Julia Rushing,2 Cynthia M Castro,3 Timothy S Church,4 Ronald Cohen,5 Thomas M Gill,6 Leora Henkin,2 Janine M Jennings,7 Diana R Kerwin,8 Todd M Manini,5 Valerie Myers,9 Marco Pahor,5 Kieran F Reid,10 Nancy Woolard,1 Stephen R Rapp,11 Jeff D Williamson1 On behalf of LIFE Investigators 1Department of Internal Medicine, Section on Gerontology and Geriatric Medicine, Sticht Center on Aging, Wake Forest School of Medicine, Winston-Salem, NC, USA; 2Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA; 3Stanford Prevention Research Center, Stanford University School of Medicine, Stanford, CA, USA; 4Pennington Biomedical, Louisiana State University, Baton Rouge, LA, USA; 5Institute on Aging and Department of Aging and Geriatric Research, University of Florida, Gainesville, FL, USA; 6Yale School of Medicine, Department of Internal Medicine, New Haven, CT, USA; 7Department of Psychology, Wake Forest University, Winston-Salem, NC, USA; 8Texas Alzheimer’s and Memory Disorders, Texas Health Presbyterian Hospital Dallas, TX, USA; 9Klein Buendel, Inc., Golden, CO, USA; 10Nutrition, Exercise Physiology and Sarcopenia Laboratory, Jean Mayer United States Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA; 11Department of Psychiatry and Behavioral Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA Abstract: Observational studies have shown beneficial relationships between exercise and cognitive function. Some clinical trials have also demonstrated improvements in cognitive function in response to moderate–high intensity aerobic exercise; however, these have been limited by relatively small sample sizes and short durations. The Lifestyle Interventions and Independence for Elders (LIFE) Study is the largest and longest randomized controlled clinical trial of physical activity with cognitive outcomes, in older sedentary adults at

Background Little research has explored who responds better to an automated vs. human advisor for health behaviors in general, and for physical activity (PA) promotion in particular. The purpose of this study was to explore baseline factors (i.e., demographics, motivation, interpersonal style, and external resources) that moderate intervention efficacy delivered by either a human or automated advisor. Methods Data were from the CHAT Trial, a 12-month randomized controlled trial to increase PA among underactive older adults (full trial N = 218) via a human advisor or automated interactive voice response advisor. Trial results indicated significant increases in PA in both interventions by 12 months that were maintained at 18-months. Regression was used to explore moderation of the two interventions. Results Results indicated amotivation (i.e., lack of intent in PA) moderated 12-month PA (d = 0.55, p < 0.01) and private self-consciousness (i.e., tendency to attune to one’s own inner thoughts and emotions) moderated 18-month PA (d = 0.34, p < 0.05) but a variety of other factors (e.g., demographics) did not (p > 0.12). Conclusions Results provide preliminary evidence for generating hypotheses about pathways for supporting later clinical decision-making with regard to the use of either human- vs. computer-delivered interventions for PA promotion.

Background Little research has explored who responds better to an automated vs. human advisor for health behaviors in general, and for physical activity (PA) promotion in particular. The purpose of this study was to explore baseline factors (i.e., demographics, motivation, interpersonal style, and external resources) that moderate intervention efficacy delivered by either a human or automated advisor. Methods Data were from the CHAT Trial, a 12-month randomized controlled trial to increase PA among underactive older adults (full trial N = 218) via a human advisor or automated interactive voice response advisor. Trial results indicated significant increases in PA in both interventions by 12 months that were maintained at 18-months. Regression was used to explore moderation of the two interventions. Results Results indicated amotivation (i.e., lack of intent in PA) moderated 12-month PA (d = 0.55, p < 0.01) and private self-consciousness (i.e., tendency to attune to one’s own inner thoughts and emotions) moderated 18-month PA (d = 0.34, p < 0.05) but a variety of other factors (e.g., demographics) did not (p > 0.12). Conclusions Results provide preliminary evidence for generating hypotheses about pathways for supporting later clinical decision-making with regard to the use of either human- vs. computer-delivered interventions for PA promotion.