All Academic, Inc. Research Logo

Info/CitationFAQResearchAll Academic Inc.
Document

Risk and Efficacy as Motivators of Change: Test of the Risk Perception Attitude (RPA) Framework
Unformatted Document Text:  The RPA Framework 4 this confounding effect of prior knowledge, the current study was designed to manipulate risk regarding a disease, diabetes, about which participants have little or no prior knowledge. The underlying premise is that, if participants have little prior knowledge about a disease or of their risk status, when confronted with a risk assessment, they are likely to believe it. If so, the RPA framework would predict that the avoidance group (high risk, low efficacy) should score lower than the responsive group (high risk, high efficacy) in intentions to seek information or to engage in self-protective behaviors. This is also the prediction of the EPPM. The RPA framework also predicts that the proactive group (low risk, high efficacy) will show healthier responses than the indifference group (low risk, low efficacy). The EPPM, however, predicts no difference between these two groups. Hence, our hypotheses are: H1A: There will be a significant interaction between risk perception and efficacy beliefs. H1B: The responsive group, relative to the avoidance group, will be associated with healthier outcomes. H1C: The proactive group, relative to the indifference group, will be associated with healthier outcomes. This first hypothesis validates the designation of the four groups – avoidance, responsive, proactive, and indifference – based on participants’ risk perception and efficacy beliefs. In accordance with the RPA framework, our second and third hypotheses predict differences between the two high-risk (responsive and avoidance) and the two low-risk (proactive and indifference) groups, respectively. The specific health issue we investigate in this paper is diabetes. Diabetes was chosen primarily because we anticipated that few college students (our study population) would know much about it. Thus, results from this study could be used to test the incredulity hypothesis.

Authors: Rimal, Rajiv., Morrison, Dan. and Mitchell, Monique.
first   previous   Page 4 of 27   next   last



background image
The RPA Framework
4
this confounding effect of prior knowledge, the current study was designed to manipulate risk
regarding a disease, diabetes, about which participants have little or no prior knowledge. The
underlying premise is that, if participants have little prior knowledge about a disease or of their
risk status, when confronted with a risk assessment, they are likely to believe it. If so, the RPA
framework would predict that the avoidance group (high risk, low efficacy) should score lower
than the responsive group (high risk, high efficacy) in intentions to seek information or to engage
in self-protective behaviors. This is also the prediction of the EPPM. The RPA framework also
predicts that the proactive group (low risk, high efficacy) will show healthier responses than the
indifference group (low risk, low efficacy). The EPPM, however, predicts no difference between
these two groups. Hence, our hypotheses are:
H1A: There will be a significant interaction between risk perception and efficacy beliefs.
H1B: The responsive group, relative to the avoidance group, will be associated with
healthier outcomes.
H1C: The proactive group, relative to the indifference group, will be associated with
healthier outcomes.
This first hypothesis validates the designation of the four groups – avoidance, responsive,
proactive, and indifference – based on participants’ risk perception and efficacy beliefs. In
accordance with the RPA framework, our second and third hypotheses predict differences
between the two high-risk (responsive and avoidance) and the two low-risk (proactive and
indifference) groups, respectively.
The specific health issue we investigate in this paper is diabetes. Diabetes was chosen
primarily because we anticipated that few college students (our study population) would know
much about it. Thus, results from this study could be used to test the incredulity hypothesis.


Convention
Convention is an application service for managing large or small academic conferences, annual meetings, and other types of events!
Submission - Custom fields, multiple submission types, tracks, audio visual, multiple upload formats, automatic conversion to pdf.
Review - Peer Review, Bulk reviewer assignment, bulk emails, ranking, z-score statistics, and multiple worksheets!
Reports - Many standard and custom reports generated while you wait. Print programs with participant indexes, event grids, and more!
Scheduling - Flexible and convenient grid scheduling within rooms and buildings. Conflict checking and advanced filtering.
Communication - Bulk email tools to help your administrators send reminders and responses. Use form letters, a message center, and much more!
Management - Search tools, duplicate people management, editing tools, submission transfers, many tools to manage a variety of conference management headaches!
Click here for more information.

first   previous   Page 4 of 27   next   last

©2012 All Academic, Inc.