Exercise is widely recognized for its myriad of health benefits, particularly in the realm of chronic disease prevention and treatment. Despite this knowledge, exercise remains significantly underutilized in the United States, with only a quarter of the population meeting the recommended physical activity guidelines set by the Department of Health and Human Services (Piercy et al., 2018). Recent research has spotlighted specific regions known as Blue Zones, where natural movement is incorporated into daily lives and populations are characterized by increased longevity and improved health outcomes, including lower rates of chronic diseases. This study aimed to explore and compare exercise behaviors between the United States and the Ikaria Blue Zone in Greece, investigating their potential implications for a longer lifespan and enhanced health. Employing ethnographic methods, including immersive observation, semi-structured, qualitative interviews with locals, and the distribution of validated International Physical Activity Questionnaire (IPAQ) surveys, comprehensive data on exercise habits within the Ikarian population was collected in November 2023. The findings from this study shed light on alternative forms of physical activity that have proven successful in populations with increased longevity. By identifying and understanding these practices, there is an opportunity to implement them in the United States, potentially contributing to improved exercise adherence and the prevention and treatment of chronic diseases. This research underscores the significance of cross-cultural insights in developing effective strategies to promote healthier lifestyles and enhance overall well-being.

The purpose of this study was to evaluate the impact of a mentoring program on self-efficacy beliefs. High-risk undergraduate students at Arizona State University majoring in Public Health and other closely-related fields represent this study’s sample. Bandura’s Self-Efficacy Theory guides this study’s theoretical framework. This study used a mixed method, action research design. Participants took a pre-test that measures their self-efficacy and registered the barriers to their academic success; following that, they enrolled and participated in a mentoring program. Upon completion of the program, they completed a post-test to evaluate any changes to their perspectives. Non-parametric Wilcoxon signed-rank tests were applied to the surveys. Throughout the mentoring program, participants completed field notes and I completed a journal about our interactions. These, along with two focus group discussions, were analyzed using grounded theory in addition to the pre- and post-tests. The surveys found that the mentoring program impacted their self-efficacy in overcoming educational barriers the qualitative data showed a strong correlation between the intervention and perceived confidence. This included their perceived ability to perform difficult or unusual tasks, but also their ability to overcome barriers.

The 284 residents of the rural community of Cooper Landing, Alaska are subject to many health risks. Cooper Landing is home to a large population of older adults whom suffer from a disproportionate physician to population ratio. Limited rural health care infrastructure and poor physician to population ratios are not conducive to primary health care implementation. Limited access to primary health care is linked to vast health disparities in rural communities like Cooper Landing. Preventive care and healthy lifestyle incentives have been largely overlooked as viable alternatives to primary health care access. In Cooper Landing, implementation of such incentives has proved to be either underutilized or unsuccessful by the private, public, and nonprofit sectors. To remedy this, the Rural Alaska Wellness Project (RAWP), a nonprofit organization, carries out its mission to promote health and wellness by providing a community resource for preventive care in Cooper Landing, Alaska. RAWP intends to increase the availability of the Cooper Landing School's gymnasium for community use, donate fitness equipment, implement TeleHealth initiatives, and host annual health fairs through grant funding, generous donations, and fundraising activities.

Purpose: This study explored the potential correlates of exercise self-efficacy among older adults with a self-reported diagnosis of arthritis. Methods: This study was a secondary data analysis and used a cross-sectional design. Data was collected from a convenience sample of Non-Hispanic White and Non-Hispanic Black individuals between 2006-2008 (N=208). Descriptive statistics were run to assess means and frequencies within the sample. Bivariate statistics (Pearson and Spearman correlations, T-tests and one-way analysis of variance) were run to examine relationships between the independent and dependent variables. Multiple linear regression analyses were conducted to examine independent predictors of self-efficacy for exercise (SEE) and barriers self-efficacy for exercise (BSE). Results: Participants were predominantly female (85.6%), white (62.9%), retired (58.1%) and had a mean age of 66.6 [10.7] years. For education level, 23.4% reported a Master’s degree or higher and 18.6% reported they had at most a high school degree or GED. Nearly 47% of the sample were classified as obese based on self-reported body mass index (BMI) and 68.3% of the sample were not meeting the American College of Sports Medicine physical activity (PA) recommendations. Participants reported a relatively high BSE (22.6) and an average SEE (22.7). Significant positive associations were seen with outcome expectation for exercise (EOE), social support, and total minutes of PA and negative associations with BMI, physical function, pain, and negative affect with SEE and BSE. Meeting the PA guidelines (t134.5=4.60, 95%CI= 4.7(6.71-2.68), p<0.001) and being white (t164=2.82, 95%CI=2.82(0.57-5.08), p=0.014) were associated with SEE and BSE (t165=3.42, 95%CI= 4.37(6.89-1.85), p=0.001) and (t164=2.34, 95%CI= 2.95(0.46-5.43), p=0.021), respectively. In regression analyses, significant predictors of SEE were education (p=.006), physical function (p=.006) and EOE (p<.001). Significant predictors of BSE were physical function (p=.020), social support (p=.031), EOE (p=<.001), education level (p=.037), and total minutes of PA (p=.022). The variables in the SEE model accounted for 50.5% (R=.737, R2=.505) of the total variance and the variables in BSE model accounted for 41.1% (R=.672, R2=.411) of the total variance of the model. Discussion: EOE appears to be an important predictor of SEE and BSE. Examining the temporal relationship between EOE and SEE is warranted.