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Some studies are designed to determine particularly the correctness of hypothesized fundamental models. The model-testing design demands that all factors that relate to the model should be considered. Normally, a heterogeneous large sample is needed and researchers have to determine all indicators that show the existence of relationships between concepts. Finally, the researchers formulate a theoretical map. Examination using the model-testing design is used to establish whether information and the model are consistent (Burns & Grove, 2011). The model-testing design is almost comparable with the predictive correlation models. However, it differs in that it tests a hypothesized causal model. Normally, predictive designs estimate the magnitude of the relationship between an outcome and the predictor. However, model-testing design estimates the correctness of a theorized model of associations and interrelationships. It is a process of theorizing how diverse factors in the environment of patient care interact, how the factors can be estimated, and the directions through which they affect the outcomes (Burns & Grove, 2011).
Model-testing designs show the complexity of patient care. Formulation and implementation of model-testing designs are not easy. Normally, they require the use of specialized software. Additionally, the elucidation of the designs requires statistical knowledge. Thus, they are used for the examination of hypotheses and not for analysis of nursing evidences (Burns & Grove, 2011). It would be advisable to use model-testing designs when there is need to examine the interrelationship of various factors in the patient care environment. Moreover, it would be advisable to use model-testing designs once a hypothesis about the relationship of the factors has been formulated. This is because the model testing designs analyze hypotheses. Model-testing designs can be used, for example, to determine the effects of the relationship between leadership, teamwork, staff stability, family and patient needs on resource intensity. Resource intensity is the outcome that is affected by the relationship of the various factors listed above.