Who Fights, Who Flees? An Integration of the LC4MP and Psychological Reactance Theory

ABSTRACT

This study tests the hypothesis that defensive message processing, like defensive behaviors in the real world, has two directions, fight-and-flight. The Limited Capacity Model of Motivated Mediated Message Processing (LC4MP) characterizes defensive message processing by increases in unpleasantness and arousal reports, and accelerated heart rate indicating either a focus on internal processing (internal thoughts) or the active withdrawal of cognitive resources from processing highly arousing and unpleasant media messages. However, the LC4MP has not included direct measures that allow discrimination between fight-and-flight responses. Psychological reactance theory (PRT) predicts defensive responses including anger and counterarguments (reactance) when media messages threaten viewers’ freedom and autonomy. We hypothesized that PRT provides the LC4MP with the appropriate measures (anger and counterarguments) needed to discriminate fight-or-flight responses. Results supported this prediction. Participants (N = 49 adult-smokers) high in defensive and low in appetitive reactivity (risk-avoiders) withdrew from the message (fled: characterized by low anger and counterarguments) while those high in appetitive and low in defensive reactivity (risk-takers) experienced reactance (fought: characterized by high anger and counterarguments) in response to freedom threatening antitobacco messages that are highly arousing and unpleasant. Moreover, both reactance and message withdrawal yielded the same cognitive, emotional, and physiological responses predicted by the LC4MP as indicators of defensive message processing. Theoretical and message design recommendations are discussed.

Notes

1. Specifying a standard small effect size (0.20) and an alpha = 0.05 in the G*Power program (Faul, Erdfelder, Lang, & Buchner, 2009), the proposed repeated measures design discussed below requires at least 44 participants to have a 0.95 power estimate.

2. The six absent smoking cue messages (C-) were coded for presence/absence of other tobacco related cues (e.g., ashtrays, tobacco packing etc.) following completion of the study. Coders (N = 3) had perfect agreement not only on the absence of smoking cue depictions but also on the absence of other tobacco-related cues.

3. Formula used for computing signal detection measures: A’ = 1 – .25 × [p(FA) / p(h) + (1 – p(h)] / [1 – p(FA)]; B” = {p(h) × [1 – p(h)] – p(FA) × [1 – p(FA)]} / {p(h) × [1 – p(h)] + p(FA) × [1 – p(FA)]}.

4. Formula used for MAM calculations: ASA = (Mean positivity of positive images @ Arousal Level 6) – (Mean positivity of both positive and negative images @ Arousal Level 1). DSA = (Mean negativity of negative images @ Arousal Level 3&4) – (Mean negativity of both positive and negative images @ Arousal Level 1).