Diffusion Of Innovations Theory
Diffusion Of Innovations Theory
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1. A description of the injury prevention intervention use of seat belts
2. Explain how you might apply the Diffusion of Innovations theory to the seatbelts intervention. Include characteristics of the innovations, characteristics of adopters, and features of the settings or environmental contexts.
3. Explain the strengths and limitations of using Diffusion of Innovations theory with the intervention.
Diffusion of innovations is a that seeks to explain how, why, and at what rate new and spread. , a professor of , popularized the theory in his book Diffusion of Innovations; the book was first published in 1962, and is now in its fifth edition (2003). Rogers argues that diffusion is the process by which an is communicated over time among the participants in a social system. The origins of the diffusion of innovations theory are varied and span multiple disciplines.
Rogers proposes that four main elements influence the spread of a new idea: the innovation itself, , time, and a social system. This process relies heavily on . The innovation must be widely adopted in order to self-sustain. Within the rate of adoption, there is a point at which an innovation reaches .
The categories of adopters are innovators, , early majority, late majority, and laggards. Diffusion manifests itself in different ways and is highly subject to the type of adopters and innovation-decision process. The criterion for the adopter categorization is innovativeness, defined as the degree to which an individual adopts a new idea.
Characteristics of innovations
Studies have explored many characteristics of innovations. Meta-reviews have identified several characteristics that are common among most studies. These are in line with the characteristics that Rogers initially cited in his reviews.
Potential adopters evaluate an innovation on its relative advantage (the perceived efficiencies gained by the innovation relative to current tools or procedures), its compatibility with the pre-existing system, its complexity or difficulty to learn, its trialability or testability, its potential for reinvention (using the tool for initially unintended purposes), and its observed effects. These qualities interact and are judged as a whole. For example, an innovation might be extremely complex, reducing its likelihood to be adopted and diffused, but it might be very compatible with a large advantage relative to current tools. Even with this high learning curve, potential adopters might adopt the innovation anyway.
Studies also identify other characteristics of innovations, but these are not as common as the ones that Rogers lists above. The fuzziness of the boundaries of the innovation can impact its adoption. Specifically, innovations with a small core and large periphery are easier to adopt. Innovations that are less risky are easier to adopt as the potential loss from failed integration is lower. Innovations that are disruptive to routine tasks, even when they bring a large relative advantage, might not be adopted because of added instability. Likewise, innovations that make tasks easier are likely to be adopted. Closely related to relative complexity, knowledge requirements are the ability barrier to use presented by the difficulty to use the innovation. Even when there are high knowledge requirements, support from prior adopters or other sources can increase the chances for adoption.