The impact of the endorsing channel upon physicians' decisions to adopt clustered and unclustered drug treatment innovations.
type: CreativeWork
description: This thesis tests two hypotheses. First, the more credible an endorsing channel is perceived, the greater probability that a physician will choose to adopt a drug treatment innovation. An Endorsing Channel Influence Scale is reported for people interested in predicting whether an endorsing channel is likely to result in a decision to prescribe a given drug treatment innovation. The minimally sufficient endorsing channel's probable impact on adoption is derived from the Endorsing Channel Influence Scale. The results of this scalogram counter notions that interpersonal channels are associated with a greater likelihood in promoting adoption of an innovation than mass communication channels. The second hypothesis is a clustered drug treatment innovation will result in a lower minimally sufficient endorsing channel threshold than a non-clustered drug treatment innovation. This hypothesis is tested by comparing the mean scores for clustered and non-clustered situations. A t-test resulted in rejection of this hypothesis.
abstract: This thesis tests two hypotheses. First, the more credible an endorsing channel is perceived, the greater probability that a physician will choose to adopt a drug treatment innovation. An Endorsing Channel Influence Scale is reported for people interested in predicting whether an endorsing channel is likely to result in a decision to prescribe a given drug treatment innovation. The minimally sufficient endorsing channel's probable impact on adoption is derived from the Endorsing Channel Influence Scale. The results of this scalogram counter notions that interpersonal channels are associated with a greater likelihood in promoting adoption of an innovation than mass communication channels. The second hypothesis is a clustered drug treatment innovation will result in a lower minimally sufficient endorsing channel threshold than a non-clustered drug treatment innovation. This hypothesis is tested by comparing the mean scores for clustered and non-clustered situations. A t-test resulted in rejection of this hypothesis.
author: Arquette, Toby James.
language: en
keywords: Communication -- Network analysis., Diffusion of innovations.
date published: 1998-05
date modified: 2026-07-24T01:08:02Z
provider: Baylor University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Baylor University.

PropertyValue
property ID: Handle
value: https://hdl.handle.net/2104/14322