Purpose-The purposes of these analyses were to determine whether Strong Hearts, Healthy Communities (SHHC), a multi-level, cardiovascular disease risk reduction program for overweight, sedentary rural women aged 40 or older, led to improved functional fitness; and if changes in fitness accounted for weight loss associated with program participation.Methods-Sixteen rural communities were randomized to receive the SHHC intervention or a control program. Both programs involved groups of 12-16 participants. The SHHC program met one hour twice a week for 24 weeks where participants engaged in aerobic exercise and progressive strength training. Program content addressed diet and social and environmental influences on heart-healthy behavior. The control group met one hour each month for 6 months, covering current dietary and physical activity recommendations. Objective measures of functional fitness included the 30-second arm curl, 30-second chair stand and 2-minute step test. Selfreported functional fitness was measured by the Physical Functioning Subscale of the MOS Short Form-36 (SF-36 PF).Findings-The SHHC program was associated with increased strength and endurance, as represented by greater improvement in the chair stand and step test; and with increased physical function, as represented by the SF-36 PF. Adjustment for change in aerobic endurance, as measured by the step test, accounted for two-thirds of the intervention effect on weight loss at the end of the intervention.
Objective: To evaluate the implementation of a community-based cardiovascular disease prevention program for rural women: Strong Hearts, Healthy Communities (SHHC). Design: Mixed-methods process evaluation. Setting/Participants: 101 women from eight rural, medically underserved towns were enrolled in the SHHC program; 93 were enrolled as controls. Eligible participants were 40 years or older, sedentary, and overweight or obese. Local health educators (n=15) served as SHHC program leaders within each town. Outcome Measures: Reach, fidelity, dose delivered, dose received, and program satisfaction were assessed using after-class surveys, participant satisfaction surveys, interviews with program leaders, and participant focus groups. Analysis: Descriptive statistics, chi-square tests, thematic analysis. Results: Intervention sites reported high levels of fidelity (82%) to the program; average attendance was 67%. Most SHHC participants were satisfied with their experience and reported benefits such as camaraderie and awareness building. Common recommendations included increasing class time, expanding exercise variety, and enhancing group discussion.
Background and Objectives: Falls account for the highest proportion of preventable injury among older adults. Thus, the United States' Centers for Disease Control and Prevention (CDC) developed the Stopping Elderly Accidents, Deaths, and Injuries (STEADI) algorithm to screen for fall risk. We referred to our STEADI algorithm adaptation as "Quick-STEADI" and compared the predictive abilities of the three-level (low, moderate, and high risk) and two-level (at-risk and not at-risk) Quick-STEADI algorithms. We additionally assessed the qualitative implementation of the Quick-STEADI algorithm in clinical settings. Research Design and Methods: We followed a prospective cohort (N = 200) of adults (65+ years) in the Bassett Healthcare Network (Cooperstown, NY) for 6 months in 2019. We conducted a generalized linear mixed model, adjusting for sociodemographic variables, to determine how baseline fall risk predicted subsequent daily falls. We plotted receiver operating characteristic (ROC) curves and measured the area under the curve (AUC) to determine the predictive ability of the Quick-STEADI algorithm. We identified a participant sample (N = 8) to gauge the experience of the screening process and a screener sample (N = 3) to evaluate the screening implementation. Results: For the three-level Quick-STEADI algorithm, participants at low and moderate risk for falls had a reduced likelihood of daily falls compared to those at high risk (−1.09, p = 0.04; −0.99, p = 0.04). For the two-level Quick-STEADI algorithm, participants not at risk for falls were not associated with a reduced likelihood of daily falls compared to those at risk (−0.89, p = 0.13). The discriminatory ability of the three-level and two-level Quick-STEADI algorithm demonstrated similar predictability of daily falls, based on AUC (0.653; 0.6570). Furthermore, participants and screeners found the Quick-STEADI algorithm to be efficient and viable. Discussion and Implications: The Quick-STEADI is a suitable, alternative fall risk screening algorithm. Qualitative assessments of the Quick-STEADI algorithm Mielenz et al. Two-Level vs. Three-Level Falls Screening demonstrated feasibility in integrating a falls screening program in a clinical setting. Future research should address the validation and the implementation of the Quick-STEADI algorithm in community health settings to determine if falls screening and prevention can be streamlined in these settings. This may increase engagement in fall prevention programs and decrease overall fall risk among older adults.
The purpose of this scoping literature review was to understand what is known about how the rural profile influences beliefs regarding telehealth utilization. Rural nursing theory (RNT) provided a framework for the review. Search criteria were limited to peer-reviewed studies conducted in Europe, the United States, Canada, Australia, and New Zealand. A variety of search terms related to patient telehealth perceptions generated 213 unique articles, of which 10 met the inclusion criteria. Included studies incorporated qualitative methodologies and were from Australia, Canada, Sweden, or the United States. The review highlighted four themes related to the rural profile’s influence on telehealth beliefs: importance of familiar relationships, concerns with privacy and confidentiality, acceptance of limited access to care, and resourcefulness and frugality. These themes echo concepts within RNT. Nurses and other health professionals must acknowledge the rural profile’s influence on a person’s decision to use telehealth in order to provide optimal care.
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