Skip to main content

Table 2 Effect of frames on vaccination and its moderation by objective and subjective risk group

From: Limits of the social-benefit motive among high-risk patients: a field experiment on influenza vaccination behaviour

Determinant Vaccinated patients / Patients in category (%) Adjusted Unadjusted
Subgroup Interaction Subgroup Interaction
aOR [95% CI] aORHigh/aORLow [95% CI] OR [95% CI] ORHigh/ORLow [95% CI]
Model A: Overall Effects of Frames
 Social-benefit 36/106 (34.0) 1   1  
 Self-benefit 49/116 (42.2) 1.63 [0.90–2.95]   1.42 [0.82–2.46]  
Model B: Moderation of framing effects by objective risk (medical assessment)
 Low Risk Group 15/63 (23.8)     
  Social-benefit 6/29 (20.7) 1 1 1 1
  Self-benefit 9/34 (26.5) 1.82 [0.53–6.17] 1.38 [0.42–4.49]
 High Risk Group 70/159 (44.0)     
  Social-benefit 30/77 (39.0) 1 0.88 [0.22–3.55] 1 1.08 [0.28–4.13]
  Self-benefit 40/82 (48.8) 1.60 [0.80–3.17] 1.49 [0.79–2.81]
Model C: Moderation of framing effects by subjective risk (patient perception)
 Low Risk Group 62/171 (36.3)     
  Social-benefit 29/80 (36.3) 1 1 1 1
  Self-benefit 33/91 (36.3) 1.11 [0.56–2.20] 1.00 [0.53–1.87]
 High Risk Group 23/51 (45.1)     
  Social-benefit 7/26 (26.9) 1 5.59 [1.30–24.05] 1 4.82 [1.25–18.56]
  Self-benefit 16/25 (64.0) 6.22 [1.69–22.88] 4.83 [1.46–15.92]
  1. Note. Table presents vaccination rates and describes corresponding logistic model estimates for three models. Model A describes the overall effect of message frame treatment on vaccination. Model B describes the interaction between objective risk and treatment, whereas Model C describes the interaction between subjective risk and treatment. Adjusted estimates include two covariates: doctor’s recommendation and reading of the pamphlet. Unadjusted estimates provide consistent results. Robust SE. p < 0.05 in bold