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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

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