Are threat perceptions associated with patient adherence to antibiotics? Insights from a survey regarding antibiotics and antimicrobial resistance among the Singapore public

Table 4 Summary of hierarchical regression analysis for variables predicting adherence to antibiotics

Predictors	Model 1			Model 2			Model 3			Model 4
Predictors	B	SE B	β	B	SE B	β	B	SE B	β	B	SE B	β
Age	0.013	0.002	0.222**	0.011	0.002	0.183**	0.003	0.002	0.049 (p = .06)	0.005	0.002	0.077* (p = .01)
Sex	0.043	0.049	0.029 (p = .38)	0.012	0.048	0.008 (p = .80)	−0.031	0.036	−0.021 (p = .40)	0.003	0.043	0.002 (p = .94)
Education level	−0.079	0.032	−0.084 (p = .01)	− 0.09	0.031	−0.095** (p = .004)	−0.072	0.024	−0.076** (p = .003)	−0.073	0.028	−0.078** (p = .009)
Antibiotics knowledge				0.044	0.005	0.287**	0.011	0.004	0.073* (p = .01)	0.016	0.005	0.104** (p = .002)
AMR knowledge				−0.033	0.015	−0.077* (p = .03)	−0.018	0.012	−0.041 (p = .15)	−0.064	0.014	−0.148**
Susceptibility							0.091	0.025	0.097**
Severity							−0.070	0.032	−0.069** (p = .03)
Self-Efficacy							0.041	0.033	0.036 (p = .22)
Response-Efficacy							0.095	0.031	0.096** (p = .002)
Response Cost							−0.544	0.024	−0.61**
Threat appraisal										0.055	0.023	0.082* (p = .02)
Coping appraisal										0.212	0.016	0.455**
R²	0.066			0.137			0.508			0.316
Adjusted R²	0.063			0.132			0.502			0.310
F for change in R²	19.82**			34.62**			126.00**			109.22**

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