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. 2019 Apr 24;69(684):e507–e514. doi: 10.3399/bjgp19X702713

Table 3.

Regression outputs indicating whether burnout and wellbeing variables explain safety outcomes (aim 2)

Model F statistic Model P-value Model R2 (mean) OLBI OLBI: D OLBI: E GHQ-12 QoL
Safe practitionera 3.58 0.002 0.091 0.267c 0.019 −0.014
Safe practitionerb 5.02 <0.001 0.105 0.015 0.300d
PSIe 1.33 0.242 n/a 1.012 0.881 1.078
Adverse evente 0.79 0.576 n/a 0.980 0.940 1.063
Near misse 1.44 0.196 n/a 1.021 0.856f 1.070

Variables listed vertically indicate model outcome variables. Variables listed horizontally indicate predictor variables. Bold font indicates significant models and variables.

a

Model included only total OLBI score and not scores from the two separate scales.

b

Model included disengagement scores and exhaustion scores, but not total OLBI score.

c

Variable made a significant independent contribution to the model at P < 0.01.

d

Variable made a significant independent contribution to the model at P < 0.001.

e

Logistic regression.

f

Variable made a significant independent contribution to the model at P < 0.05. All regressions controlled for age, sex, and years in practice. Statistics represent mean standardised β coefficients for linear regressions, odds ratios for logistic regressions. GHQ = general health questionnaire. n/a = not applicable. OLBI = Oldenburg burnout inventory. OLBI: D = Oldenburg burnout inventory: disengagement. OLBI: E= Oldenburg burnout inventory: exhaustion. PSI = patient safety incident. QoL = quality of life.