The investigation of the problem implies a specific setting. Considering the hypothesis which states that the improvement of the healthcare will contribute to the better outcomes related to obesity rates, the most common approaches used in the given sphere could be considered the main aspects of the investigation. These become a crucial element that should be included in the investigation because of the character of the research question and the obvious necessity to determine the character and impact of the approaches that are explored in the healthcare today (Fallah-Fini, Rahmandad, Huang, Burens, & Glass, 2014).
About 10 medical care units across the state are chosen in terms of random sampling. Considering the aim of the research, it is necessary to trace the correlation between the level of the suggested services, workers competence and obesity rates. For this reason, such variables as practices that help to treat obesity and the obesity rate in the USA are chosen These are dependent and independent variables correspondingly.
In other words, a set of methods that are today used in the healthcare sector along with the specific equipment becomes crucial for the research (Dietz et al., 2015). The chosen medical care units are located in different regions and are characterized by different environment. The additional training to improve the care delivery and admit its impact on population is common to all units.
As for the type of the research, it could be considered quantitative study that is focused on the investigation of a causal impact of an intervention on a target population. In the suggested study, alteration of the quality of care preconditions quantitative changes in obesity rates. For this reason, it is crucial to apply this study design to calculate basic alterations.
References
Dietz, W. H., Baur, L. A., Hall, K., Puhl, R. M., Taveras, E. M., Uauy, R., & Kopelman, P. (2015). Management of obesity: Improvement of health-care training and systems for prevention and care. The Lancet, 385(9986), 2521–2533.
Fallah-Fini, S., Rahmandad, H., Huang, T. T. K., Burens, R. M., & Glass, T. A. (2014). Modeling US adult obesity trends: A system dynamics model for estimating energy imbalance gap. American Journal of Public Health, 104(7), 1230-1239.