Testing terror management health model and integrating its predictions with the theory of psychological reactance

ABSTRACT

Two experiments (N_study1 = 203; N_study2 = 177), using STD prevention messages and a 2 (mortality: salient, control) × 2 (freedom threat: high, low) design, tested the Terror Management Health Model and integrated its predictions with the Theory of Psychological Reactance to examine how reactance and mortality salience interact to affect risk communication. In Study 1, mortality salience mitigated freedom-threat perceptions but only at low threat to freedom and, consistent with distal defenses, reduced intentions to use condoms and abstain from sex. Study 2 examined the effects of mortality salience on proximal defenses. As predicted, mortality salience mitigated high levels of freedom threat, but, contrary to TMHM, it also reduced condom use intentions. These and other results are discussed.

KEYWORDS:

• Reactance
• terror management theory
• freedom threat
• death
• mortality salience
• sexually transmitted diseases (STDs)

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Elena Bessarabova (Ph.D., University of Maryland) is an associate professor in the Department of Communication at the University of Oklahoma.

Zachary B. Massey (Ph.D., University of Oklahoma) is currently a postdoctoral fellow at the School of Public Health at Georgia State University. This project was completed while Zach Massey was a graduate student at the University of Oklahoma.

Notes

1 Although not all STDs are deadly, many of them, if left untreated, have severe consequences including death. Per TMHM, health behaviors (even benign ones such as applying suntan lotion) are suitable for inductions eliciting existential threat (i.e., mortality salience) because they reference the effects of health behaviors on human body: Such references serve as reminders of the physicality (and, to a certain extent, fragility) of the body (Goldenberg, McCoy, Pyszczynski, Greenberg, & Solomon, 2000) that paired with mortality-salience inductions facilitate bringing death thoughts into focus. These inductions have been employed successfully on samples of young adults: In TMHM, mortality-salience inductions have been repeatedly shown to activate death awareness in college students notwithstanding how deadly the consequences of the message topic might be (e.g., safe suntan practices or exercise; see Arndt et al., 2003; Routledge et al., 2004).

2 Participants received the following instructions. Suppose we would like to know how much knowledge you have about your major. To answer this question, use a number from zero to infinity. Zero means you have no knowledge at all about your major, and higher numbers represent greater levels of knowledge. If you feel you have moderate knowledge about your major, rate your knowledge as 100. If your knowledge is twice as much as a moderate level, rate your knowledge as 200; if your knowledge about your major is half the moderate level, rate your knowledge as 50. You can use any number from zero on up such as 18, 193, or 347.

3 We intentionally did not include a lexical-decision task as a mortality-salience-induction check. As systematic examinations of mortality-salience-induction checks indicate, lexical-decision tasks may unintentionally bring death-thoughts back into focal awareness (Hayes & Schimel, 2018). Thus, consistent with previous research (e.g., Arndt et al., 2003; Routledge et al., 2004), proximal or distal effects were inferred from the scores on the outcome variables.

4 Magnitude scales (see Lodge, 1981, for a discussion) are ratio-type scales (with zero at the origin; unbounded at the top) that have long been established as being effective at measuring a wide range of phenomena across different disciplines. Relative to ordinal measures (including Likert-type scales), magnitude scales are better suited for the analyses requiring interval-level data, and, because the response categories are unfixed, they allow discovering the true range of responses, help avoid ceiling effects and restricted variance range (Lodge, 1981).

5 Variables measured with magnitude scales tend to be positively skewed because magnitude scales are unbounded at the top end of the scale. To control for outliers, all variables (except negative thoughts) were winsorized by recoding a variable’s scores to a lower value. Most variables were winsorized to the 95th or 90th percentile.

6 Transformations affect the data in predictable ways. In a transformation equation, Y* = (Y + k)^λ, where Y is the original variable, Y* is the transformed variable, and k is a constant, using λ < 1 is likely to result in a more symmetric distribution for positively skewed data, and using λ > 1 is likely to result in a more symmetric distribution for negatively skewed data (Fink, 2009). Although transformations affect the scale on which a variable is measured, they do not change “the relative difference between people for a given variable” (Field, 2013, p. 201).

7 For example, the initial skewness of one of the threat perceptions items was 3.16 (SE= 0.17), indicating a significant departure from normality. Transformed item skewness became 0.24, showing a substantial improvement. Different transformation formulas were used for different variables to accommodate the specific type of skewness present in a given variable. In Study 1, threat perception= (winsorized original item + 1)^.04; anger= (winsorized original item + .09)^.1; attitudes= (winsorized original item + 1)^.05; message quality= (winsorized original item + 1)^.15; intention= (winsorized original item + 10)^.13; religiosity= (winsorized original item + 1)^.05

8 Attempts to aggregate any combination of these items failed to produce a reliable index.

9 Study 2 transformation formulas: intention= (winsorized original item + 1)^.12; attitudes= (winsorized original item + 1)^.05; threat perceptions= (winsorized original item + 20)^.45; anger= ln(winsorized original item + .01); negative thoughts= ln(winsorized original item + .5); message quality= (winsorized original item + 1)^.15; religiosity= (winsorized original item + 1)^.04.

10 Note that in both threat by mortality salience interactions on attitudes and on condom use intentions, the means in the mortality salience condition when threat was high (vs. low) trended in the direction indicative of an increase in positive attitudes and an increased intention to use condoms, but the mean differences failed to reach statistical significance.