Applying the Integrative Model
Quantitative analysis of data is essential in giving a broader meaning to the collected data. This primarily consists of further breaking down of smaller components of research question and the purpose statement. The integrative model in quantity design employs a variety of methods in research design. With special attention to the integrative model, this paper will apply an interdisciplinary review, and adopt a quantitative approach with the integrative model to the existing research on relationship between back pains and employee performance.
The Problem Statement
According to Rooney (2008), approximately 70-85% of adults will have low back pain at some point in their lives, thereby making lower back pain the most frequent complaint among human beings. It is defined as physical suffering or discomfort that is localized between the bottom of the ribs and the tops of the legs, and can also involve leg pain (Milczarek, 2009). As many suffer from low back pain, the underlying problem is it can hinder productivity and require a person to take days off from work. This can have several implications for companies including the financial costs to the organization in terms of wages and delays in deadlines and deliverables. The implementation of yoga to alleviate the occurrence of back pain, decrease absenteeism in the work place and lower the number of worker’s compensation cases, and the number of lower back injuries.
Adopting the Integrative Model in Research Design and Methodology
In order to attain integrative model, both the research method and methodology must embrace variety and dynamism. Literature review therefore ensures that the research problem or question adopts the integrative model; as the research question will have been strengthened and diversified through use of varying sources, to prove the existence of the problem (Boslaugh & Watters, 2008). In addition, research is performed on different individuals with multiple differences in terms of gender, race, attitude, beliefs, values, and geographical locations, among others. This also serves to ensure rich research findings and presents findings that have a higher level of reliability and validity. For an integrative model to be effected, the research considers different variables. Therefore, apart from back pain and employee performance, the research may as well include additional factors. These additional variables could be easily derived from the environment, the employees themselves, as well as the organization. These may act independently or simultaneously interact to produce the problematic scenario that is identified in the research problem. More variables therefore, allow for a descriptive approach or methodology in research (Boslaugh & Watters, 2008).
Incorporating Integrative Model in Data Analysis
Data analysis is a sensitive stage, which serves to evaluate the data, giving it meaning, and finally presenting it for public reference. Therefore, comprehensive and meaningful findings will attract public interest. This will be achieved if the statistical analysis embraces an integrative model. This is through the use of a variety of methods of statistical analysis, which should provide similar results to determine reliability and validity of the methods used, as well as the findings. The use of Statistical Package for the Social Sciences (SPSS) is a more advanced method that can be used in data analysis due to its high reliability (Trochim, 2006). In addition to other data analysis methods, it is imperative that more than one method of data analysis be used for effective data analysis. In this research, by using the integrative model, it is possible to test the probability that employees will accept yoga as a way of reducing their back pains. This is because the integrative model can be used to determine choice and attitude of the research subjects, as it strongly bases on relationship between cognition and affect.
Integrative model is advantageous as it allows for the assessment of different variables at the same time. Research shows that this model is better than the other traditional models, as it has high predictive validity (Corner, 2002). The findings resulting from this model are comprehensive as they put into consideration more than one factor, as well as the interplay between variables. Apart from structural equations modelling, testing the integrative model also involves the use of logit framework, as well as regression, which all prove that the integrative model has high predictive validity, making it effective in research analysis.
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