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Table 3 Univariate logistic regression analysis of vignette and respondent characterstics, with the Kruskall–Wallis test of influence of State or Territory

From: Differences in identifying healthcare associated infections using clinical vignettes and the influence of respondent characteristics: a cross-sectional survey of Australian infection prevention staff

Variable (proportion of respondents)

Vignette 1

Vignette 3

Vignette 4

Vignette 5

Vignette 6

Vignette 7

RR

RR

RR

RR

RR

RR

n = 92

(95 % CI)

(95 % CI)

(95 % CI)

(95 % CI)

(95 % CI)

(95 % CI)

Hospital over 200 beds (64 %)

n/a

1.15 (0.47, 2.10)

1.00 (0.58, 1.36)

0.94 (0.30, 2.15)

0.56 (0.14, 1.41)

1.13 (0.44, 1.90)

Hospital over 400 beds (38 %)

0.95 (0.11, 3.07)

1.50 (0.71, 2.42)

1.10 (0.72, 1.41)

2.42** (1.09, 3.45)

1.02 (0.46, 1.74)

1.07 (0.51, 1.72)

Academic degree or higher (72 %)

0.95 (0.01, 3.24)

1.41 (0.58, 2.41)

1.33 (0.91, 1.59)

1.02 (0.33, 2.27)

0.56 (0.14, 1.41)

1.36 (0.59, 2.05)

Public hospital (79 %)

1.40 (0.14, 3.30)

0.97 (0.29, 2.04)

0.76 (0.32, 1.25)

1.27 (0.37, 2.72)

1.74 (0.71, 2.46)

1.31 (0.44, 2.12)

Less than 5 years infection control experience (23 %)

1.07 (0.92, 3.15)

0.50 (0.16, 1.35)

0.66 (0.27, 1.13)

1.02 (0.19, 2.53)

0.63 (0.18, 1.56)

1.86 (0.85, 2.42)

Formal surveillance training (48 %)

1.76 (0.29, 3.44)

1.23 (0.54, 2.20)

0.70 (0.35, 1.11)

1.02 (0.19, 2.53)

1.25 (0.54, 2.02)

1.22 (0.56, 1.91)

Trained by central organisation (21 %)

1.07 (0.20, 2.82)

1.53 (0.58, 2.66)

1.02 (0.52, 1.44)

2.27 (0.53, 3.68)

1.04 (0.37, 1.92)

1.00 (0.35, 1.82)

Surveillance skills assessed (17 %)

n/a

0.99 (0.32, 2.34)

0.72 (0.27, 1.25)

0.32*** (0.09, 0.98)

1.94 (0.85, 2.60)

1.05 (0.37, 1.92)

Work in a team (73 %)

2.04 (0.04, 3.81)

2.16* (1.14, 2.97)

1.02 (0.58, 1.40)

1.02 (0.33, 2.27)

0.85 (0.26, 1.75)

1.69 (0.86, 2.24)

Daily access to Infectious Diseases Physician (59 %)

1.73 (0.18, 3.49)

0.89 (0.35, 1.77)

1.05 (0.64, 1.39)

0.53 (0.14, 1.55)

0.58 (0.16, 1.38)

1.17 (0.48, 1.90)

Daily access to Epidemiologist (1 %)

1.35 (0.14, 3.73)

1.14 (0.25, 2.99)

1.39 (0.68, 1.71)

1.45 (0.23, 3.37)

1.63 (0.32, 2.67)

1.20 (0.27, 2.29)

Daily access to Microbiologist (64 %)

1.73 (0.18, 3.49)

0.90 (0.34, 1.81)

0.82 (0.44, 1.23)

1.39 (0.51, 2.65)

1.00 (0.35, 1.87)

0.91 (0.31, 1.72)

Effective full time staff >3 (27 %)

0.49 (0.05, 2.34)

0.84 (0.23, 2.11)

0.69 (0.29, 1.19)

0.76 (0.24, 1.82)

0.95 (0.30, 1.90)

0.39 (0.08, 1.19)

Rarely or never have access to an ICP with more experience (43 %)

0.49 (0.08, 1.91)

1.51 (0.69, 2.49)

1.07 (0.66, 1.41)

0.66 (0.23, 1.60)

0.93 (0.36, 1.74)

1.04 (0.43, 1.78)

Work part time (34 %)

0.26 (0.04, 1.40)

0.57 (0.21, 1.34)

0.83 (0.44, 1.25)

0.72 (0.21, 1.86)

0.63 (0.18, 1.56)

1.05 (2.46, 1.92)

Kruskall–Wallis test for State/Territory (P-value)

0.0875

0.0454

0.4163

0.0427

0.2826

0.3389

  1. RR Risk Ratio, 95 % CI 95 % Confidence Interval
  2. *p = 0.011 **p = 0.033 ***p = 0.049