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Table 1 Patient characteristics across models and bivariate associations with continuity score presented as multilevel regression coefficients representing effect size

From: Predictors of relational continuity in primary care: patient, provider and practice factors

Patient characteristic Profile distribution Association with overall continuity score across all models Standardized effect size
  CHC FFS FHN HSO Effect size (%) 95% CI 1 ES/SD2
Patient with continuity score (n) 1194 1366 1479 1257    
Patient profile (n) 1219 1375 1494 1273    
Age (years)†3 47 50 51 51 0.14 (0.12, 0.16)*** S
Sex (% female)† 73 67 66 61 0.44 (−0.29, 1.2) S
At least one chronic disease (%) 66.8 65.3 68.7 65.2 4 (3.2, 4.7)*** S
Low Income (%)4 33.6 12.5 11.6 11.3 1.4 (0.03, 2.4)* S
Worked in the past 12 months (%)† 53.7 66.4 63.5 66.4 −3.9 (−4.7, -3.2)*** S
Patient of the practice less than 2 years (%)† 28.4 18.4 14.2 6.6 −3.5 (−4.5, -2.5)*** S
Mental Problems (%)§ 47.3 44.8 42.8 40.7 −1.7 (−2.5, -1.0)*** S
Education (At least high school completed) (%)† 77.5 85.4 84.2 83.7 −3.4 (−4.4, -2.5)*** S
  1. 1 Symbols adjacent to the confidence interval indicate that the effect size is significantly associated with the continuity score:
  2. * p < 0.05.
  3. ** p < 0.01. *** p < .001.
  4. These are generated by multi-level linear regression.
  5. 2 ES/SD: Effect Size / Standard deviation; S if ES/SD < 0.2; M if 0.2 < =ES/SD < 0.5; L if 0.5 < =ES/SD < 0.8; VL if ES/SD > =0.8; CI = Confidence Interval.
  6. 3 Symbols adjacent to the patient characteristic indicate that it is statistically different across the models:
  7. § p < 0.05.
  8. p < 0.01.
  9. p < 0.001.
  10. These are generated by Chi-square statistic or by F-statistic (ANOVA), as appropriate.
  11. 4Income less than Low Income Cut Off [37].