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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

DeterminantVaccinated patients / Patients in category (%)AdjustedUnadjusted
SubgroupInteractionSubgroupInteraction
aOR [95% CI]aORHigh/aORLow [95% CI]OR [95% CI]ORHigh/ORLow [95% CI]
Model A: Overall Effects of Frames
 Social-benefit36/106 (34.0)1 1 
 Self-benefit49/116 (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 Group15/63 (23.8)    
  Social-benefit6/29 (20.7)1111
  Self-benefit9/34 (26.5)1.82 [0.53–6.17]1.38 [0.42–4.49]
 High Risk Group70/159 (44.0)    
  Social-benefit30/77 (39.0)10.88 [0.22–3.55]11.08 [0.28–4.13]
  Self-benefit40/82 (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 Group62/171 (36.3)    
  Social-benefit29/80 (36.3)1111
  Self-benefit33/91 (36.3)1.11 [0.56–2.20]1.00 [0.53–1.87]
 High Risk Group23/51 (45.1)    
  Social-benefit7/26 (26.9)15.59 [1.30–24.05]14.82 [1.25–18.56]
  Self-benefit16/25 (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
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