Hazard avoidance, symbolic and practical: the case of Americans’ reported responses to Ebola

Abstract

Reducing potential dangers by changing routine behavior to avoid certain people, places, or technologies can be prudent, but reporting avoidance also can be symbolic. This study probed Americans’ reactions to Ebola from December 2014 to May 2015 with a longitudinal study (final n = 625), plus a representative sample in May: How much did they claim to avoid West Africans, commercial flights, Ebola-associated cities, and four other targets? What factors affected self-reported avoidance? Did people with opportunities to implement avoidance report more (e.g. frequent flyers can change their routine behavior more to avoid commercial flights than can infrequent flyers)? The December 2014 survey found most people never considered avoidance, but substantial minorities claimed acting or intending to avoid each target; substantial majorities of May 2015 respondents reported avoidance intentions if a new Ebola outbreak occurred in Africa or the United States. Perceptions of personal risk, concern about infection, and following Ebola news were primary factors in reported avoidance, with temporal reversals (e.g. news following increased avoidance in December but decreased it in May). Opportunity enhanced reported avoidance in December 2014 by indirect effects through personal risk, concern, and news following, but decreased avoidance intentions in May 2015 through direct effects of opportunity on avoidance. Temporal shifts in avoidance reports and associations seem consistent with objective declines in Ebola cases, perhaps mediated by changes in news coverage. Further consideration of avoidance behavior and the role of opportunity could enhance hazard management.

Keywords:

• Ebola
• avoidance behavior
• opportunity
• stigma

Notes

1. One abstract cited ‘avoidance behavior’ as ‘a form of “technological stigma”’ (Flynn et al. 1998).

2. Consistent with this general consistency and implied symbolic avoidance, people who reported living near U.S. treatment cities, being frequent flyers, or likely to encounter West Africans or Ebola helpers were significantly more likely to engage in all avoidance behaviors – including attendance at mass events likely to attract Africans and wearing of mask/gloves – than those without such opportunities. This pattern was weaker (e.g. one non-significant and three marginally significant contrasts each) for avoiding train or bus use; frequent train/bus users were less like non-users for avoidance not related to that transport mode.

3. Compared to those dropping out of the study by February 2015, those who stayed were in December less likely to avoid Ebola-linked cities and marginally less likely to avoid West Africans, but did not differ on other actions.

4. The December measure, from a public health research survey (Johnson 2017), was deemed to misrepresent the airborne pathway based on CDC comments, so was revised as in Table 4 to better represent it.

5. Repetition of Table 4 (December 2014 linear index) analysis, adding February 2015 data on descriptive and injunctive norms, found explained variance increased significantly (F (18,388)) = 28.03, p < 0.0005; R² = 0.565, $R_{\text{adj}}^2$ = 0.545, ∆R² = 0.027, p < 0.0005; n = 407); see author for details.

6. Total effects (direct plus indirect) in December ranged from 0.21 (bus user > buses/trains) to 0.79 (flyer > commercial flights); total indirect effects were 0.34–0.79 (same mediations, plus 0.79 flyer > airports). These figures mean (e.g.) that a switch from infrequent to frequent flying indirectly increased reported avoidance of commercial air travel by 0.79 units on the four-unit index (1 = never considered it, 4 = done it, excluding ‘decided not to do it’).

7. Analyses unreported here show people who ‘decided not’ to avoid differed from others only in perceived risk, concern and other responses (more than the ‘never considered’ or ‘currently considering’, less than the ‘done it’ or ‘intended’), so those factors cannot explain that choice.