Assessing factors for choosing a primary care specialty in medical students; A longitudinal study

Figures & data

Table 1. Descriptive statistics of those who did/did not match into a primary care specialty. Comparison of descriptive statistics of students who matched into internal medicine, pediatrics, or family medicine specialties. Likert scores taken from M1 survey. Pooled Genders

Characteristic	Matched Into Primary Care Specialty, Pooled Genders. Mean (SD) or N (%).	Did Not Match Into Primary Care Specialty, Pooled Genders. Mean (SD) or N (%).	Test of differences
Count	137 (36.63%)	237 (63.37%)	-
Avg. age at matriculation	23.3 (1.97), N = 110	23.54 (2.41), N = 197	N = 307, 2-sided t-test, t(305) = 0.87, p = 0.38
Gender is female	77 (56.20%)	87 (36.71%)	N = 374, χ[^2](1) = 13.40, p < 0.01
Ethnicity is white	106 (77.37%)	189 (79.75%)	N = 374, χ[^2](1) = 0.29, p = 0.59
Physicians in family	27 (22.13%)	44 (20.95%)	N = 332, χ[^2](1) = 0.06, p = 0.80
Undergrad science based major	95 (87.96%)	173 (88.72%)	N = 303, χ[^2](1) = 0.04, p = 0.84
Debt from pre-med education	48 (36.36%)	89 (40.09%)	N = 354, χ[^2](1) = 0.48, p = 0.49
Pre-med research	54 (44.26%)	115 (54.76%)	N = 332, χ[^2](1) = 3.40, p = 0.07
Pre-med mentor	45 (36.89%)	82 (39.05%)	N = 332, χ[^2](1) = 0.15, p = 0.70
Ever married	27 (19.71%)	54 (22.78%)	N = 374, χ[^2](1) = 0.48, p = 0.49
Mentor in primary care specialty in 1^st 2 years	29 (21.17%)	34 (14.35%)	N = 374, χ[^2](1) = 2.88, p = 0.09
Research in medical school	91 (66.42%)	205 (86.50%)	N = 374, χ[^2](1) = 21.20, p < 0.01
Amount of time in patient contact (Likert scale)	2.20 (1.59), N = 108	2.46 (1.44), N = 195	N = 303, 2-sided t-test, t(301) = 1.44, p = 0.15
Quality of life (Likert scale)	2.32 (1.67), N = 108	2.53 (1.59), N = 195	N = 303, 2-sided t-test, t(301) = 1.08, p = 0.28
Technical skills necessary (Likert scale)	2.07 (1.03), N = 108	2.13 (1.02), N = 195	N = 303, 2-sided t-test, t(301) = 0.42, p = 0.63
Med school debt at match	90 (87.38%)	150 (81.97%)	N = 286, χ[^2](1) = 1.43, p = 0.23
Med school debt influenced specialty choice	9 (9.09%)	44 (24.58%)	N = 278, χ[^2](1) = 9.91, p < 0.01

Table 2. M1-2 factors associated with matching into a primary care specialty. Dependent variable is matching into a primary care specialty. Primary care is comprised of internal medicine, pediatrics, and family medicine specialties. Adjusted odds ratios are presented, with standard errors in parentheses. Additional controls include whether individuals had a primary care mentor in first 2 years, performed primary care research in first 2 years, the subjective importance of academic vs. private practice opportunities and intellectual stimulation, none of which had significant associations. Lifestyle and debt responses taken from M2 survey. Pseudo R² is McFadden’s. *** p < 0.01, ** p < 0.05, * p < 0.1 for odds ratio different from 1

	Pooled	Men	Women	Pooled	Men	Women
Female	2.21*** (0.62)	-	-	2.06** (0.64)	-	-
Ethnicity is White	0.58 (0.20)	0.42* (0.22)	0.63 (0.30)	0.54* (0.19)	0.54 (0.29)	0.34* (0.20)
Age at Matriculation	1.12 (0.08)	1.00 (0.10)	1.43* (0.26)	1.14 (0.09)	0.96 (0.11)	1.57** (0.30)
Family Member Practices Primary Care	3.41** (1.78)	2.13 (1.47)	6.67** (6.16)	3.53** (2.00)	2.30 (1.86)	17.16*** (18.86)
Married in 1st 2 Years	1.70 (0.65)	3.36** (1.79)	1.03 (0.60)	1.92 (0.78)	3.15** (1.83)	1.58 (1.16)
Has children in 1st 2 Years	0.09** (0.09)	0.12* (0.15)	0.05 (0.09)	0.08** (0.08)	0.13 (0.18)	0.02 (0.05)
Amount of time in patient contact	-	-	-	0.81** (0.09)	0.81 (0.13)	0.87 (0.16)
Potential Salary	-	-	-	0.78* (0.10)	0.66** (0.13)	0.95 (0.24)
Quality of Life	-	-	-	1.05 (0.11)	1.17 (0.18)	0.96 (0.18)
Responsibilities at home	-	-	-	1.15 (0.14)	1.33 (0.27)	1.03 (0.18)
Specialty status/reputation	-	-	-	1.21 (0.14)	1.46** (0.28)	1.03 (0.18)
Spouse/partner’s career	-	-	-	1.33** (0.17)	1.13 (0.23)	1.99*** (0.49)
Technical skills necessary	-	-	-	1.06 (0.13)	0.87 (0.15)	1.46 (0.34)
Debt from Medical Education	1.55 (0.66)	1.64 (1.03)	1.38 (0.85)	1.67 (0.76)	2.49 (1.77)	1.87 (1.31)
Debt Influences Specialty Preference	0.99 (0.27)	0.61 (0.26)	1.49 (0.57)	0.91 (0.26)	0.58 (0.27)	1.71 (0.79)
Constant	0.03** (0.05)	0.48 (1.18)	0.00** (0.00)	0.00** (0.01)	0.62 (1.96)	0.00*** (0.00)
Observations	273	153	120	264	148	116
Pseudo R^2	0.08	0.09	0.08	0.12	0.17	0.20

Table 3. Post-match factors associated with matching into a primary care specialty. Dependent variable is matching into a primary care specialty. Primary care is comprised of internal medicine, pediatrics, and family medicine specialties. Adjusted odds ratios are presented, with standard errors in parentheses. Lifestyle and debt responses taken from match survey. Additional controls include whether individuals had a primary care mentor in first 2 years, performed primary care research in first 2 years, the subjective importance of academic vs. private practice opportunities and intellectual stimulation, none of which had significant associations. Pseudo R² is McFadden’s. *** p < 0.01, ** p < 0.05, * p < 0.1 for odds ratio different from 1

	Pooled	Men	Women	Pooled	Men	Women
Female	1.76* (0.59)	-	-	1.61 (0.62)	-	-
Ethnicity is White	0.66 (0.27)	0.65 (0.39)	0.59 (0.35)	0.57 (0.27)	0.57 (0.41)	0.51 (0.38)
Age at Matriculation	1.18** (0.10)	1.03 (0.12)	1.46** (0.25)	1.11 (0.11)	0.88 (0.15)	1.59** (0.36)
Family Member Practices Primary Care	4.05** (2.83)	2.62 (2.41)	7.22 (8.94)	5.45** (4.34)	5.71 (6.87)	8.18 (10.93)
Married in Medical School	1.10 (0.52)	2.08 (1.41)	0.93 (0.65)	1.26 (0.69)	4.03 (3.52)	0.85 (0.78)
Had Children in Medical School	0.22* (0.20)	0.30 (0.34)	0.26 (0.46)	0.22 (0.23)	0.15 (0.20)	1.62 (3.23)
Primary Care Mentor in 1st 2 Years	1.45 (0.59)	0.67 (0.50)	2.23 (1.17)	1.30 (0.59)	0.71 (0.64)	2.4 (1.46)
Conducted Primary Care Research in Medical School	0.83 (0.29)	1.54 (0.78)	0.54 (0.28)	0.93 (0.36)	2.61 (1.71)	0.45 (0.29)
Amount of time in patient contact	-	-	-	0.99 (0.16)	0.83 (0.21)	1.09 (0.29)
Potential Salary	-	-	-	0.73 (0.15)	0.50** (0.16)	0.95 (0.34)
Quality of Life	-	-	-	0.65** (0.12)	0.55* (0.18)	0.57* (0.18)
Responsibilities at home	-	-	-	1.44* (0.29)	1.55 (0.55)	1.47 (0.46)
Specialty status/reputation	-	-	-	1.37 (0.27)	1.50 (0.46)	1.50 (0.52)
Spouse/partner’s career	-	-	-	1.29 (0.21)	1.75** (0.50)	1.35 (0.34)
Technical skills necessary	-	-	-	0.54*** (0.09)	0.42*** (0.12)	0.54** (0.15)
Debt from Medical Education	1.53 (0.70)	1.86 (1.20)	1.17 (0.82)	2.02 (1.03)	2.62 (2.10)	1.58 (1.30)
Debt Influences Specialty Preference	0.29** (0.16)	0.24** (0.17)	0.39 (0.34)	0.33* (0.20)	0.34 (0.29)	0.32 (0.34)
Constant	0.01** (0.02)	0.15 (0.42)	0.00** (0.00)	0.18 (0.49)	97.07 (418.00)	0.00** (0.00)
Observations	197	111	86	189	108	81
Pseudo R^2	0.08	0.08	0.11	0.19	0.29	0.21

Pre-matriculation factors associated with matching into a primary care specialty. Adjusted odds ratios, standard errors in parentheses. Primary care is comprised of internal medicine, pediatrics, and family medicine specialties. Pseudo R² is McFadden’s. *** p < 0.01, ** p < 0.05, * p < 0.1 for odds ratio different from 1

	Pooled	Men	Women
Female	2.126*** (0.545)	-	-
Ethnicity is white	0.664 (0.200)	0.683 (0.302)	0.671 (0.286)
Age at matriculation	0.994 (0.0586)	0.925 (0.0705)	1.220 (0.150)
Science major in undergraduate education	0.842 (0.335)	0.571 (0.306)	1.581 (1.028)
Debt from undergraduate education	0.936 (0.244)	1.099 (0.399)	0.762 (0.298)
Mentor in primary care	1.637 (0.563)	1.764 (0.887)	1.810 (0.917)
Performed primary care research	0.893 (0.312)	1.350 (0.686)	0.522 (0.258)
Family member practices primary care	2.859** (1.340)	2.724 (1.777)	3.719* (2.706)
Constant	0.645 (0.998)	4.313 (8.576)	0.00802 (0.0246)
Observations	302	169	133
Pseudo R^2	0.05	0.03	0.05

Appendix A.2. Descriptive statistics of men. Comparison of descriptive statistics of students who matched into internal medicine, pediatrics, or family medicine specialties. Likert scores taken from M1 survey

Characteristic	Matched Into Primary Care Specialty, Men. Mean (SD) or N (%).	Did Not Match Into Primary Care Specialty, Men. Mean (SD) or N (%).	Test of differences
Count	60 (28.57%)	150 (71.43%)	-
Avg. age at matriculation	23.63 (1.95)	24.00 (2.91)	N = 172, 2-sided t-test, t(170) = 0.84, p = 0.20
Ethnicity is white	48 (80.00%)	120 (80.00%)	N = 210, χ^2(1) = 0.00, p = 1.00
Physicians in family	11 (21.15%)	32 (24.06%)	N = 185, χ^2(1) = 0.18, p = 0.67
Undergrad science based major	40 (85.11%)	109 (88.62%)	N = 170, χ^2(1) = 0.39, p = 0.53
Debt from pre-med education	22 (39.39%)	60 (42.55%)	N = 197, χ^2(1) = 0.18, p = 0.68
Pre-med research	28 (53.85%)	69 (51.88%)	N = 185, χ^2(1) = 0.06, p = 0.81
Pre-med mentor	18 (34.62%)	51 (38.35%)	N = 185, χ^2(1) = 0.22, p = 0.64
Ever married	16 (26.67%)	39 (26.00%)	N = 210, χ^2(1)<0.01, p = 0.92
Mentor in primary care in 1^st 2 years	6 (10.00%)	16 (10.67%)	N = 210, χ^2(1) = 0.02, p = 0.89
Research in medical school	46 (76.67%)	134 (89.33%)	N = 210, χ^2(1) = 5.62, p = 0.02**
Amount of time in patient contact (Likert scale)	2.34 (1.54)	2.45 (1.39)	N = 170, 2-sided t-test, t(168) = 0.44, p = 0.66
Quality of life (Likert scale)	2.53 (1.57)	2.55 (1.57)	N = 170, 2-sided t-test, t(168) = 0.07, p = 0.94
Technical skills necessary (Likert scale)	2.00 (1.04)	2.24 (1.07)	N = 170, 2-sided t-test, t(168) = 1.29, p = 0.20
Med school debt at match	42 (87.50%)	94 (81.03%)	N = 164, χ^2(1) = 1.00, p = 0.32
Med school debt influenced specialty choice	3 (5.66%)	9 (13.64%)	N = 119, χ^2(1) = 2.06, p = 0.15

Appendix A.3. Descriptive statistics of women. Comparison of descriptive statistics of students who matched into internal medicine, pediatrics, or family medicine specialties. Likert scores taken from M1 survey

Characteristic	Matched Into Primary Care Specialty, Women. Mean (SD) or N (%).	Did Not Match Into Primary Care Specialty, Women. Mean (SD) or N (%).	Test of differences
Count	77 (46.95%)	87 (53.05%)	-
Avg. age at matriculation	23.05 (1.95)	22.75 (1.29)	N = 135, 2-sided t-test, t(133) = −1.05, p = 0.30
Ethnicity is white	58 (75.32%)	69 (79.31%)	N = 164, χ^2(1) = 0.37, p = 0.54
Physicians in family	16 (22.86%)	12 (15.58%)	N = 147, χ^2(1) = 1.26, p = 0.26
Undergrad science based major	55 (90.16%)	64 (88.89%)	N = 133 χ^2(1) = 0.06, p = 0.81
Debt from pre-med education	26 (34.21%)	29 (35.80%)	N = 157, χ^2(1) = 0.04, p = 0.83
Pre-med research	26 (37.14%)	46 (59.74%)	N = 147, χ^2(1) = 7.49, p < 0.01***
Pre-med mentor	27 (38.57%)	31 (40.26%)	N = 147, χ^2 (1) = 0.04, p = 0.83
Ever married	11 (14.29%)	15 (17.24%)	N = 164, χ^2(1) = 0.27, p = 0.61
Mentor in primary care in 1^st 2 years	23 (29.87%)	18 (20.69%)	N = 164, χ^2(1) = 1.84, p = 0.18
Research in medical school	45 (58.44%)	71 (81.61%)	N = 164, χ^2(1) = 10.59, p < 0.01***
Amount of time in patient contact (Likert scale)	2.09 (1.64)	2.49 (1.53)	N = 133, 2-sided t-test, t(131) = 1.41, p = 0.16
Quality of life (Likert scale)	2.16 (1.73)	2.50 (1.60)	N = 133, 2-sided t-test, t(131) = 1.15, p = 0.25
Technical skills necessary (Likert scale)	2.13 (1.02)	1.96 (0.91)	N = 133, 2-sided t-test, t(131) = −1.03, p = 0.31
Med school debt at match	48 (87.27%)	56 (83.58%)	N = 122, χ^2(1) = 0.33, p = 0.57
Med school debt influenced specialty choice	6 (13.04%)	35 (30.97%)	N = 159, χ^2(1) = 5.49, p = 0.02

Appendix A.4. Descriptive statistics comparing women and men. Comparison of descriptive statistics of men and women. Likert responses taken from M1 survey

Characteristic	Men	Women	Test of differences
Count	210	164	-
Matched into primary care specialty	60 (28.57%)	77 (46.95%)	N = 374, χ^2(1) = 13.40, p < 0.01***
Avg. age at matriculation	23.90 (2.68), N = 172	22.89 (1.63), N = 135	N = 307, 2-sided t-test, t(305) = 3.86, p < 0.01***
Ethnicity is white	168 (80.00%)	127 (77.44%)	N = 374, χ^2 (1) = 0.36, p = 0.55
Physicians in family	43 (23.24%)	28 (19.05%)	N = 332, χ^2(1) = 0.66, p = 0.35
Undergrad science based major	149 (87.65%)	119 (89.47%)	N = 303, χ^2(1) = 0.24, p = 0.62
Debt from pre-med education	82 (41.62%)	55 (35.03%)	N = 354, χ^2(1) = 1.60, p = 0.21
Pre-med research	97 (52.43%)	72 (48.98%)	N = 332, χ^2(1) = 0.39, p = 0.53
Pre-med mentor	69 (37.30%)	58 (39.46%)	N = 332, χ^2(1) = 0.16, p = 0.69
Ever married	55 (26.19%)	26 (15.85%)	N = 374, χ^2(1) = 5.80, p = 0.02**
Mentor in primary care in 1^st 2 years	22 (10.48%)	41 (25.00%)	N = 374, χ^2(1) = 13.87, p < 0.01***
Research in medical school	180 (85.71%)	116 (70.73%)	N = 374, χ^2(1) = 12.52, p < 0.01***
Amount of time in patient contact (Likert scale)	2.42 (1.43)	2.31 (1.59)	N = 303, 2-sided t-test, t(301) = 0.63, p = 0.53
Quality of life (Likert scale)	2.55 (1.57)	2.35 (1.69)	N = 303, 2-sided t-test, t(301) = 1.07, p = 0.28
Technical skills necessary (Likert scale)	2.17 (1.07)	2.04 (0.96)	N = 303, 2-sided t-test, t(301) = 0.48, p = 0.63
Med school debt at match	136 (82.93%)	104 (85.25%)	N = 286, χ^2(1) = 0.28, p = 0.60
Med school debt influenced specialty Choice	41 (25.79%)	12 (10.08%)	N = 278, χ^2(1) = 10.88, p < 0.01

Table

□ Geography	□ Residents/culture
□ Family	□ Work-life balance
□ Program reputation	□ Opportunities for fellowships
□ Program faculty	□ Research opportunities
□ Program size	□ Other _______________
□ Curriculum

Table

	Extremely Important	Somewhat Important	Neutral	Not Likely Important	Not at all Important
a.Academic vs private practice opportunities
bAmount of time in patient contact
c.Intellectual stimulation
d.Potential Salary
e.Quality of Life
f.Responsibilities at home
g.Specialty status/reputation
h.Spouse/partner’s career
i.Technical skills necessary

Tu HT, O’Malley AS. Exodus of male physicians from primary care drives shift to specialty practice. Track Rep. 2007;(17):1–6. http://www.hschange.org/CONTENT/934/.

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Data Availability

The datasets analyzed in this study are available in anonymized form upon reasonable request to the corresponding author.