Search Results for « MBHs »

The Multidimensional Behavioral Health Screen (MBHS) is a brief screening measure of behavioral health symptoms. Although the measure was first developed for primary care, it is likely to have clinical utility in other settings. This study examined the MBHS’s factor structure and psychometric properties with a university undergraduate and graduate student sample ( n = 602, 58.6% female, 75.9% White, primarily aged 20–24) during the COVID-19 pandemic. MBHS subscale scores demonstrated internal consistency reliability and both convergent and discriminant relations with external, criterion variables. Confirmatory factor analyses supported a 7-subscale factor structure of the MBHS and did not find evidence of higher order factors. Clinical and theoretical implications, as well as future research directions, are discussed.

Product layout significantly impacts consumer demand for purchases in supermarkets. Product shelf renovation is a crucial process that can increase supermarket efficiency. The development of a sequential pattern mining algorithm for investigating the correlation patterns of product layouts, solving the numerous problems of shelf design, and the development of an algorithm that considers in-store purchase and shelf profit data with the goal of improving supermarket efficiency, and consequently profitability, were the goals of this research. The authors of this research developed two types of algorithms to enhance efficiency and reach the goals. The first was a PrefixSpan algorithm, which was used to optimize sequential pattern mining, known as the PrefixSpan mining approach. The second was a new multi-objective design that considered the objective functions of profit volumes and closeness rating using the mutation-based harmony search (MBHS) optimization algorithm, which was used to evaluate the performance of the first algorithm based on the PrefixSpan algorithm. The experimental results demonstrated that the PrefixSpan algorithm can determine correlation rules more efficiently and accurately ascertain correlation rules better than any other algorithms used in the study. Additionally, the authors found that MBHS with a new multi-objective design can effectively find the product layout in supermarket solutions. Finally, the proposed product layout algorithm was found to lead to higher profit volumes and closeness ratings than traditional shelf layouts, as well as to be more efficient than other algorithms.