Germs are germs, and why not take a risk? Patients' expectations for prescribing antibiotics in an inner-city emergency department

Med Decis Making. 2015 Jan;35(1):60-7. doi: 10.1177/0272989X14553472. Epub 2014 Oct 20.

Abstract

Background: . Extensive use of unnecessary antibiotics has driven the emergence of resistant bacterial strains, posing a threat to public health. Physicians are more likely to prescribe antibiotics when they believe that patients expect them. Current attempts to change these expectations highlight the distinction between viruses and bacteria ("germs are germs"). Fuzzy-trace theory further predicts that patients expect antibiotics because they make decisions based on categorical gist, producing strategies that encourage risk taking when the status quo is bad (i.e., "why not take a risk?"). We investigate both hypotheses.

Methods: . We surveyed patients visiting the emergency department of a large urban hospital (72 [64%] were African American) using 17 Likert scale questions and 2 free-response questions regarding patient expectations for antibiotics.

Results: . After the clinical encounter, 113 patients completed the survey. Fifty-four (48%) patients agreed with items that assess the "germs are germs" hypothesis, whereas 86 (76%) agreed with items that assess the "why not take a risk?" hypothesis. "Why not take a risk?" captures significant unique variance in a factor analysis and is neither explained by "germs are germs" nor by patients' lack of knowledge regarding side effects. Of the 81 patients who rejected the "germs are germs" hypothesis, 61 (75%) still indicated agreement with the "why not take a risk?" hypothesis. Several other misconceptions were also investigated.

Conclusions: . Our findings suggest that recent public health campaigns that have focused on educating patients about the differences between viruses and bacteria omit a key motivation for why patients expect antibiotics, supporting fuzzy-trace theory's predictions about categorical gist. The implications for public health and emergency medicine are discussed.

Keywords: fuzzy-trace theory; health literacy; physician-patient communication; risk communication; risk perception.

MeSH terms

  • Adult
  • Aged
  • Anti-Bacterial Agents / administration & dosage*
  • Emergency Service, Hospital / statistics & numerical data*
  • Female
  • Health Knowledge, Attitudes, Practice*
  • Hospitals, Urban / statistics & numerical data
  • Humans
  • Male
  • Middle Aged
  • Patient Participation
  • Patient Preference
  • Patient Satisfaction*
  • Respiratory Tract Infections / drug therapy*
  • Surveys and Questionnaires
  • Young Adult

Substances

  • Anti-Bacterial Agents