Communicating the Consequences of Early Detection: The Role of Evidence and Framing

By Dena S Cox, Anthony D. Cox. 2001

292 citations recorded by the source corpus.

Subfields: Applied Psychology, Literature and Literary Theory, Marketing

View Paper: https://www.semanticscholar.org/paper/e34f60da96a819a069fffddeae98ce3a3015b8b7

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Citations in the corpus

Unintended Effects of Health Communication Campaigns (2007, unknown): “Cox and Cox (2001) discovered that positive appeals promoting mammography negatively affected women’s attitudes toward it and decreased their perceived susceptibility to breast cancer.”
The Advantages of Compliance or the Disadvantages of Noncompliance? A Meta-Analytic Review of the Relative Persuasive Effectiveness of Gain-Framed and Loss-Framed Messages (2006, unknown): “…& Gelinas-Chebat (1998) ATMs .290 56 5/4/3 Chebat et al. (1998) student loans .102 56 5/4/3 Cothran, Schneider, & Salovey (1998) .085 218 1/4/4 Cox & Cox (2001) anecdotal .306 55 1/3/3 Cox & Cox (2001) statistical .046 55 1/2/1 Davis (1995) .108 218 6/3/3 Detweiler, Bedell, Salovey,…”
American attitudes toward nudges (2016, background): “The literature on persuasion shows that, at least in some situations, negative frames are more effective than positive frames (Block & Keller 1995; Cox & Cox 2001).”
The Strategic Use of Gain- and Loss-Framed Messages to Promote Healthy Behavior: How Theory Can Inform Practice (2006, background): “…than gain-framed appeals in promoting interest in and the utilization of screening mammography and breast self-examination (Banks et al., 1995; Cox & Cox, 2001; Finney & Iannoti, 2002; Meyerowitz & Chaiken, 1987; Schneider et al., 2001) as well as colorectal cancer screening (Myers et al.…”
Health‐care product advertising: The influences of message framing and perceived product characteristics (2007, background): “In contrast, loss-framed messages are viewed as providing more powerful arguments for why consumers should endure the short-term discomfort of having a health problem possibly detected (Cox & Cox, 2001).”
In AI we trust? Perceptions about automated decision-making by artificial intelligence (2020, methodology): “Risk ( M = 4.51, SD = 1.01, α = 0.81) was measured with five items adapted from Cox and Cox (2001).”