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

BMC Primary Care

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

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 Symbols adjacent to the confidence interval indicate that the effect size is significantly associated with the continuity score:
* p < 0.05.
** p < 0.01. *** p < .001.
These are generated by multi-level linear regression.
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.
³ Symbols adjacent to the patient characteristic indicate that it is statistically different across the models:
§ p < 0.05.
^‡ p < 0.01.
^† p < 0.001.
These are generated by Chi-square statistic or by F-statistic (ANOVA), as appropriate.
⁴Income less than Low Income Cut Off [37].

ISSN: 2731-4553