| Literature DB >> 29594191 |
Stutee Khandelwal1,2, Sarah E Zemore1,3, Anke Hemmerling1.
Abstract
BACKGROUND: Although physicians are expected to provide dietary counseling for patients with cardiovascular (CV) risk factors such as hypertension, hyperlipidemia, diabetes, and obesity, nutrition education in graduate medical education remains limited. Few studies have recently examined nutrition education and dietary counseling practices in Internal Medicine (IM) residency training.Entities:
Keywords: Internal Medicine; Nutrition education; dietary counseling; residency
Year: 2018 PMID: 29594191 PMCID: PMC5865517 DOI: 10.1177/2382120518763360
Source DB: PubMed Journal: J Med Educ Curric Dev ISSN: 2382-1205
Survey instrument and variable treatment.
| Variable | Item | Answer options | |
|---|---|---|---|
| Predictor variables | Amount of nutrition education across each: obesity, diabetes, hypertension, dyslipidemia | “How much training have you had on dietary counseling for the following diseases in the outpatient setting?” | “None at all,” “a little bit,” “quite a bit,” and “extensive” |
| No. of instruction methods[ | “How have you learned about outpatient nutrition and dietary counseling for cardiovascular risk factors (obesity, hypertension, dyslipidemia, diabetes) during residency?” | “Teaching by preceptors in primary care clinic” | |
| Outcome variable | Self-reported frequency of counseling[ | “In a typical ambulatory week, for what percentage of patients with the following cardiovascular risk factors, do you engage in dietary counseling?” | “Never (0%),” “rarely (1%-20%),” “sometimes (21%-40%),” “half the time (41%-60%),” “often (61%-80%),” “very often (81%-99%),” and “always (100%)” |
| Moderators | Program support for healthy eating habits[ | “Residency sponsored meals have healthy food options” | “Strongly disagree,” “disagree,” “agree,” and “strongly agree” |
| Personal daily fruit and vegetable intake[ | Diet screener with 6 items: fruit juice, fruit other than as juice, vegetable juice, green salad, vegetable soup or stew, any other vegetables | No. of servings per day ranging from 0 to 6 and per day/week/month |
Adapted from the Preventive Medicine Attitudes and Activities Questionnaire (PMAAQ) scale (α = .85, test-retest reliability correlation = 0.72).[19]
Two-item scale had an α of .78.
Validated in medical students with reproducibility correlation r = .77 and correlation with Food Frequency Questionnaire r = .50.[20]
Sample characteristics of the educators and the Internal Medicine programs they belonged to.
| No. (%) | ||
|---|---|---|
| Respondent type | Program director | 31 (77.5) |
| Associate program director | 9 (22.2) | |
| Region | Northeast | 11 (27.5) |
| Midwest | 7 (17.5) | |
| South | 10 (25.0) | |
| West | 12 (30.0) | |
| Type of program | Community-based | 5 (12.5) |
| Community-based-university-affiliated | 19 (47.5) | |
| University-based | 14 (35.0) | |
| Other | 2 (5.0) | |
| Presence of primary care track | Yes | 14 (35.0) |
| No | 26 (65.0) | |
| % of residents entering primary care | 0-20 | 22 (55.0) |
| 21-40 | 11 (27.5) | |
| 41-60 | 5 (12.5) | |
| 61-80 | 1 (2.5) | |
| 81-100 | 1 (2.5) | |
| Opinion on importance of nutrition education[ | None | 1 (2.6) |
| Somewhat | 16 (41.0) | |
| Moderately important | 22 (56.4) | |
| Extremely important | 0 (0.0) | |
| Presence of formal curriculum[ | Yes | 1 (2.6) |
| No | 38 (97.4) | |
| Reported providing “quite a bit”/“extensive” training in dietary counseling for[ | Obesity | 16 (42.1) |
| Hypertension | 18 (47.4) | |
| Dyslipidemia | 18 (47.4) | |
| Diabetes | 20 (52.6) | |
| Methods used to teach[ | Teaching by preceptors in primary care clinic | 36 (95.0) |
| Teaching on inpatient wards | 30 (79.0) | |
| Providing online material | 30 (79.0) | |
| Providing resource list of texts | 23 (60.5) | |
| Participating in specialty clinic that focusses on nutrition | 15 (40.0) | |
| Scholarly projects (eg, quality improvement/curricula improvement) | 14 (37.0) | |
| Elective offering | 11 (29.0) | |
| Structured individual study with selected reading material | 8 (21.1) | |
| Other | 4 (10.5) | |
| Structured individual study with educational CD | 1 (2.6) | |
| Attendance at a national nutrition conference | 1 (2.6) | |
| Total fruit and vegetable intake (mean ± SD) | 5.3 ± 2.8 | |
| ≥5 servings of fruit and vegetable intake a day | 24 (60) |
1 educator with missing information.
2 educators with missing information.
Resident sample characteristics by the number of methods used to learn about nutrition for the outpatient setting.
| No. of methods | |||
|---|---|---|---|
| ≤3 | >3 | ||
| No. (%)[ | 70 (56.0) | 55 (44.0) | |
| Age (y, mean ± SD) | 29 ± 3 | 30 ± 3 |
|
| Gender (n) | .94 | ||
| Female | 39 (55.7) | 31 (44.3) | |
| Training level (n) | .47 | ||
| Post graduate year 1 | 29 (55.8) | 23 (44.2) | |
| Post graduate year 2 | 22 (64.7) | 12 (35.3) | |
| Post graduate year 3 | 12 (44.4) | 15 (55.6) | |
| Post graduate year 4 | 7 (58.3) | 5 (41.7) | |
| Career path (n) | .89 | ||
| Primary care | 19 (57.6) | 14 (42.4) | |
| Subspecialty | 35 (53.0) | 31 (47.0) | |
| Undecided | 10 (62.5) | 6 (37.5) | |
| Other | 6 (60.0) | 4 (40.0) | |
| Region (n) |
| ||
| Northeast | 23(49.0) | 24 (51.0) | |
| Midwest | 16 (66.7) | 8 (33.3) | |
| South | 21 (72.4) | 8 (27.6) | |
| West | 9 (39.1) | 14 (60.8) | |
| Type of program (n) |
| ||
| Community-based | 8 (24.2) | 25 (75.8) | |
| Community-based-university-affiliated | 29 (63.0) | 17 (40.0) | |
| University-based | 33 (71.7) | 13 (28.3) | |
| Presence of PC track (n) | .24 | ||
| Yes | 44 (52.4) | 40 (47.6) | |
| No | 26 (63.4) | 15 (36.6) | |
| In PC track (of those in programs with a PC track) (n) | .14 | ||
| Yes | 11 (40.7) | 16 (59.3) | |
| No | 33 (57.9) | 25 (42.1) | |
| Medical education (n) | .09 | ||
| US | 52 (61.2) | 33 (38.8) | |
| Foreign | 18 (45.0) | 23 (55.0) | |
| Prior nutrition education (n) | |||
| Before medical school | 16 (76.2) | 6 (23.8) |
|
| In medical school | 42 (53.2) | 39 (46.8) |
|
| Daily fruit and vegetable intake (mean no. of servings ± SD) | 3.6 ± 2.6 | 4.9 ± 4.9 | |
Abbreviation: PC, primary care.
8 residents with missing information.
Bold values in the table represents numbers which are statistically significant.
Resident sample characteristics by frequency of nutrition counseling in the outpatient setting.
| Never/rarely | Sometimes/half the time | Often/very often/always | ||
|---|---|---|---|---|
| No. (%)[ | 38 (32.7) | 56 (48.3) | 22 (19.0) | |
| Age (y, mean ± SD) | 28.9 ± 2.2 | 29.6 ± 3.2 | 30.4 ± 2.7 | .13 |
| Gender (n) | .51 | |||
| Female | 23 (35.4) | 32 (49.2) | 10 (15.4) | |
| Training level (n) | .53 | |||
| Post graduate year 1 | 16 (34.0) | 21 (44.7) | 10 (21.3) | |
| Post graduate year 2 | 13 (39.4) | 16 (48.5) | 4 (12.1) | |
| Post graduate year 3 | 6 (24.0) | 15 (60.0) | 4 (16.0) | |
| Post graduate year 4 | 3 (27.2) | 4 (36.4) | 4 (36.4) | |
| Career path (n) | .38 | |||
| Primary care | 8 (25.0) | 21 (65.6) | 3 (9.4) | |
| Subspecialty | 22 (36.1) | 25 (41.0) | 14 (22.9) | |
| Undecided | 5 (33.3) | 6 (40.0) | 7 (26.7) | |
| Other | 3 (37.5) | 4 (50) | 1 (12.5) | |
| Region (n) |
| |||
| Northeast | 9 (20.4) | 24 (54.6) | 11(25.0) | |
| Midwest | 3 (13.0) | 15 (65.2) | 5 (21.7) | |
| South | 14 (53.9) | 9 (34.6) | 3 (11.5) | |
| West | 11 (52.4) | 7 (33.3) | 3 (14.3) | |
| Type of program (n) | .20 | |||
| Community-based | 8 (26.7) | 14 (46.6) | 8 (26.7) | |
| Community-based-university-affiliated | 17 (38.7) | 17 (38.7) | 10 (22.7) | |
| University-based | 13 (31.0) | 25 (59.5) | 4 (9.5) | |
| Presence of PC track (n) |
| |||
| Yes | 20 (25.6) | 44 (56.4) | 14 (18.0) | |
| No | 18 (47.4) | 12 (31.6) | 8 (21.0) | |
| In PC track (n) | .66 | |||
| Yes | 5 (19.2) | 16 (61.5) | 5 (19.2) | |
| No | 15 (28.9) | 28 (53.8) | 9 (17.3) | |
| Medical education (n) | .10 | |||
| US | 29 (36.7) | 39 (49.4) | 11 (13.9) | |
| Foreign | 9 (24.3) | 17 (46.0) | 15 (29.7) | |
| Prior nutrition education (n) | ||||
| Before medical school | 8 (42.1) | 8 (42.1) | 3 (15.8) | .64 |
| In medical school | 20 (26.3) | 41 (54.0) | 20 (19.7) | .12 |
| Daily fruit and vegetable intake (mean no. of servings ± SD) | 3.4 ± 2.1 | 4 ± 2.4 | 7.5 ± 6.7 | .45 |
Abbreviation: PC, primary care.
12 residents with missing information.
Bold values in the table represents numbers which are statistically significant.
Bivariate and multivariate predictors of residents’ frequency of dietary counseling in the outpatient setting.
| β[ | SE | ||
|---|---|---|---|
| Bivariate linear regression | |||
| Amount of training | 0.39 | 0.18 |
|
| No. of methods | 0.43 | 0.06 |
|
| Multivariable linear regression | |||
| Amount of training | 0.20 | 0.21 |
|
| No. of methods | 0.26 | 0.08 |
|
| Total fruit and vegetable intake | 0.24 | 0.03 |
|
| Nutrition education in medical school | 0.20 | 0.24 |
|
| Post graduate level | 0.19 | 0.12 | .06 |
| Age | −0.05 | 0.04 | .62 |
| Gender | 0.09 | 0.21 | .31 |
| Path | 0.13 | 0.14 | .15 |
| Type of program | −0.10 | 0.17 | .32 |
| Presence of primary care track | 0.03 | 0.23 | .72 |
| Being in primary care track | 0.08 | 0.31 | .40 |
| Medical education in the United States | −0.03 | 0.28 | .78 |
| Nutrition education before medical school | 0.10 | 0.31 | .28 |
| Region | |||
| Northeast (as reference) | |||
| Midwest | 0.36 | 0.30 | .71 |
| South | −0.16 | 0.31 | .13 |
| West | −0.16 | 0.32 | .12 |
A standardized β coefficient was used to account for differences in units of the variables.
Bold values in the table represents numbers which are statistically significant.
Barriers faced by program directors in providing nutrition education.
| Barrier | Correlation with no. of methods used | Correlation with amount of training provided | % reporting moderate-to-major barrier | ||
|---|---|---|---|---|---|
| Lack of physician faculty with expertise in nutrition | −0.33 |
| −0.13 | .45 | 76 |
| Lack of faculty interest | −0.17 | .33 | 0.03 | .83 | 54 |
| Competing curricular demands | −0.15 | .36 | −0.22 | .19 | 80 |
| Unclear evidence base for nutrition interventions | −0.11 | .53 | 0.21 | .20 | 33 |
| Lack of ACGME requirement | −0.09 | .59 | 0.10 | .55 | 26 |
| Lack of administrative support | −0.08 | .63 | 0.05 | .76 | 61 |
| Lack of resident interest | 0.06 | .69 | 0.21 | .20 | 43 |
| Inadequate financial resources for program development | −0.06 | .73 | 0.12 | .47 | 61 |
| Other | 0.02 | .87 | −0.22 | .18 | 22 |
| 1. “Teaching nutrition takes time” | |||||
| 2. “Work flow challenges” | |||||
| Lack of insurance reimbursement for nutrition interventions | 0.008 | .96 | −0.04 | .81 | 48 |
Bold values in the table represents numbers which are statistically significant.
Barriers faced by residents in counseling patients on diet.
| Barrier | Correlation with counseling provided | % reporting as important/very important | |
|---|---|---|---|
| Lack of personal interest in providing nutrition counseling | −0.19 |
| 21 |
| Lack of clinic preceptor’s interest in nutrition | −0.18 |
| 31 |
| Lack of proper patient education materials | −0.18 | 0.06 | 45 |
| Patients come for a different purpose | −0.17 | 0.08 | 59 |
| Lack of availability of health educators | −0.13 | 0.16 | 45 |
| Insufficient reimbursement | −0.13 | 0.17 | 33 |
| Lack of time | −0.12 | 0.20 | 69 |
| Lack of patient interest in nutrition | 0.08 | 0.40 | 52 |
| Lack of systems for tracking and prompting nutrition counseling | −0.05 | 0.55 | 46 |
| Cultural differences between you and your patients | 0.01 | 0.91 | 25 |
Bold values in the table represents numbers which are statistically significant.