Impact of Wellness Policy Review, Wellness Council Activity, and Student Health Objectives on Overall School Wellness Climate

Abstract

BackgroundThe whole school, whole community, whole child (WSCC) model suggests wellness councils, ongoing review of wellness policy, and a plan for evaluating set objectives are some of the key features needed to support school wellness infrastructure. This study explored the relationship between implementation of these infrastructure features and overall school wellness environment assessment scores among a sampling of Pennsylvania schools.MethodsThe Healthy Champions program provides Pennsylvania schools an opportunity to self‐assess their wellness environments across several school wellness topics. Staff enrolled their school in the program by completing a self‐report electronic assessment. Enrollment data from the 2020/2021 program year were analyzed using the Kruskal‐Wallis test and linear fixed model to identify the impact of varied implementation levels across 3 wellness infrastructure activities. Interactions between these variables and overall assessment score were also analyzed.ResultsOf the 645 Pennsylvania schools enrolled and analyzed, we observed higher mean wellness environment assessment scores (∆ 0.74 95% CI 0.40‐1.07; p < 0.001) among schools that reported some frequency of all 3 wellness infrastructure activities, compared to schools that reported no frequency for the activities.ImplicationsSchools with existing policies and practices related to the 3 wellness infrastructure activities should consider the degree of implementation to best support overall wellness in their school setting. Additional research to explore implementation barriers and supports is needed.ConclusionsAnalyses indicated that overall wellness environment assessment scores are impacted by implementation thresholds for wellness council meeting frequency, revision of wellness policy, and review of student health promotion objectives.

Development of a Dog Health Score Using an Artificial Intelligence Disease Prediction Algorithm Based on Multifaceted Data

“…Scores between 6 and 10 are indicative of a generally healthy state. The validity of these assessments was corroborated by three veterinarians, who compared the AI-generated scores with the AI's learning outcomes [22]. The behavioral data integral to this study comprised scratching, licking, swallowing (both food and water), and sleeping.…”

“…Scores between 6 and 10 are indicative of a generally healthy state. The validity of these assessments was corroborated by three veterinarians, who compared the AI-generated scores with the AI's learning outcomes [22]. 1) presents the calculation formula, incorporating the result value's weight (W), reference data, and the associative memory learning model [23].…”