Throughout this course you will be developing a formal, evidence-based practice proposal. The proposal is the plan for an evidence-based practice project designed to address a problem, issue, or conce

CHANGE MODEL 5

Section D: Change Model

HCA-699

June 17, 2020









Change Model

Change is an inevitable life process. One of the significant challenges in change management is resistance to change. While resistance is a normal human reaction to new development, there is a need for the management in question to embrace processes that ensure the gradual adoption of new practices. Rodger’s Diffusion of Innovation theory is one of the models that could be applied in introducing the new change, which is evidence-based practice (EBP) in nursing. Dearing and Cox (2018) defined diffusion as the social process that takes place during the learning of innovation, with the example of an evidence-based approach for improving health care. Simin and Jankovic (2014) highlighted the Diffusions of Innovations as a crucial theory developed in the United States by rural sociologists. This theory describes the change processes with the example of the diffusions of innovations in society.

The Diffusion of Innovation (DOI) theory, as developed by E.M. Rodgers, is one of the major theories in social sciences. This theory sought to expound how a product gains popularity among a group of people and is slowly assimilated into a social system. According to Kaminski (2011), the DOI theory was historically explored by Gabriel Tarde, a French sociologist. The current version of the theory, as popularized by Everett Rogers, has additional categories. An analysis of this model will unearth the different individuals and their characteristics, which should be considered when introducing a new EBP. Kaminski (2011) outlined categories of adopters and their influence on the adoption and innovative process.

  1. Innovators. Kamanski (2011) defined individuals in this category as technology enthusiasts. Among all the categories, these individuals require the least time to adapt to a new change. The author added that these individuals easily understand and apply complex concepts to deal with a high degree of uncertainty. During the EBP introduction, these people make up the least number.

  2. Early adopters. Kamanski (2011) highlighted that early adopters are also visionaries. Individuals under this category attract admiration from their peers, with their adventurous nature drawing them to projects with high risks or rewards. An implementation with early adopters stands a higher chance of success, especially due to the challenging aspect of EBP.

  3. Early Majority. Also known as the pragmatists, Kamanski (2011) noted that this category has people that frequently interact with their peers while also serving as opinion leaders later on in the process. These people make up 34% hence the need to ensure their cooperation during the introduction of change. Their opposition could significantly influence the stand of others, lowering the chance of succeeding.

  4. Late majority. These people are also known as conservatives and have the same composition as the pragmatists. According to Kamanski (2011), the late majority derive their motivation from the need to keep up with the competition or existing trends. These people are easily influenced by the laggards, which mean that they could be easily influenced by declining the awaiting change. The late majority make up 34%.

  5. Laggards. They are also known as skeptics and make up 19%. Kamanski (2011) stated that the laggards prefer to maintain the status quo. As such, these individuals may prove difficult during EBP implementation.

The first step before the introduction of the change would be identifying the presence of the highlighted categories among the participants. This realization would help to determine what people to include in completing particular elements of the plan.

References

Dearing, J. & Cox, J. (2018). Diffusion of Innovations Theory, Principles, And Practice. Health Affairs, 37(2), 183-190. https://doi.org/10.1377/hlthaff.2017.1104

Kaminski, J. (2011). Diffusion of Innovation Theory. Canadian Journal of Nursing Informatics, 6(2). https://cjni.net/journal/?p=1444

Simin, M. & Jankovic, D. (2014). Applicability of Diffusion Of Innovation Theory In Organic Agriculture. Belgrade, 61(2), 517-529