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Original Contribution  |   September 2018
Association of Mindfulness With Residency Preference and Curriculum Selection in Preclinical Osteopathic Medical Students
Author Notes
  • From the New York Institute of Technology College of Osteopathic Medicine in Old Westbury. 
  • Financial Disclosures: None reported. 
  • Support: None reported. 
  •  *Address correspondence to Gregg Saggio, DO, Department of Clinical Specialties, New York Institute of Technology College of Osteopathic Medicine, Northern Blvd, PO Box 8000, Old Westbury, NY 11568-8000. Email: gsaggio@nyit.edu
     
Article Information
Medical Education / Graduate Medical Education / Curriculum
Original Contribution   |   September 2018
Association of Mindfulness With Residency Preference and Curriculum Selection in Preclinical Osteopathic Medical Students
The Journal of the American Osteopathic Association, September 2018, Vol. 118, 587-595. doi:10.7556/jaoa.2018.142
The Journal of the American Osteopathic Association, September 2018, Vol. 118, 587-595. doi:10.7556/jaoa.2018.142
Abstract

Context: Recent studies suggest the shortage of US primary care physicians will be more than 50,000 by the year 2025. Mindful osteopathic medical students may be more inclined to pursue a career in primary care practice than those demonstrating lower levels of mindfulness. If so, assessing mindfulness before and after admission to medical school may reduce this shortage.

Objective: In this cross-sectional survey-based study, the authors assessed whether mindfulness among preclinical osteopathic medical students was associated with (a) their current preference for primary care practice as a residency, and (b) their choice between 2 alternative curricula.

Method: Participants were first- and second-year osteopathic medical students enrolled at the New York Institute of Technology College of Osteopathic Medicine (NYITCOM). They completed a 7-factor questionnaire of demographic variables and the online Five Facet Mindfulness Questionnaire (FFMQ) to determine their mindfulness score. They also identified their current preference for a residency. Data were then presented using various descriptive statistics and analyzed using independent t tests, χ2 tests, and multiple logistic regression.

Results: Among the 208 respondents, authors found that osteopathic medical students who expressed a preference for primary care practice showed no significant differences in mindfulness compared with those interested in specialist fields, as indicated by mean (SD) mindfulness scores of 3.34 (0.44) vs 3.33 (0.41), respectively (P=.88). However, among demographic variables, female students expressed a preference for primary care practice fields at significantly higher rates than male students (OR, 4.4; 95% CI, 2.2-8.5; P<.001). Also, students who matriculated less than 6 months after completing their undergraduate education were drawn to primary care practice at higher rates than those who delayed enrollment (OR, 2.3; 95% CI, 1.2-4.5; P=.016). None of the remaining demographic variables were associated with students’ residency preference.

Conclusion: Being female and matriculating immediately after undergraduate education was associated with a preference for primary care residency. However, no significant association was found between mindfulness and either residency preference or choice of alternative curricula.

According to current calculations, by 2025 the United States will require an additional 50,000 practicing primary care physicians to meet the needs of the ever-growing and aging US population.1 In response, medical schools are trying to recruit more students who are likely to enter primary care practice, which includes the fields of internal medicine, family medicine, and pediatrics, as defined by the American Academy of Family Physicians.2 (There are alternative definitions of primary care, some of which include obstetrics-gynecology and emergency medicine.) To recruit new students and motivate current students, many schools are searching for indicators that can predict which students are likely to pursue primary care. However, little is known about indicators that may be used to predict which students will eventually enter certain specialties. 
This preliminary study investigates whether mindfulness is associated with students’ preference for a primary care field for their residency. If so, and if we can assess mindfulness prior to matriculation, then accepting a greater number of mindful students to medical schools may help address the primary care shortage in the United States. In addition to its use in the enrollment process, a finding that high mindfulness scores is correlated with increased interest in primary care could prompt medical schools to foster this interest during students’ medical education in the hope of further increasing the number of primary care graduates. 
Mindfulness in Medicine
Over the past few years, medical schools have increasingly recognized the concept of mindfulness as a method of improving medical education for students and faculty.3,4 The term mindfulness includes 2 distinct usages. Its original meaning, derived from the Buddhist tradition, included forms of meditation believed to have therapeutic effects, such as relief from stress and pain.5,6 Kabat-Zinn was a prominent advocate of this version.7 
Langer8 proposed an alternative concept. She agreed with Ludwig and Kabat-Zinn9 that mindfulness centers on the mental skill of “being in the moment; being aware” and “staying focused in the present,” but her application focused on its use as a cognitive approach to improving behavior, rather than a psycho-emotional technique for reducing stress. Both approaches have the potential to benefit medical education. According to Langer,8 the most important payoff from mindfulness is superior performance. Thus, a mindful physician may reduce medical error and improve patient care.9 
The current research takes these findings to the next stage and investigates whether the qualities of mindfulness are also associated with students’ preference for a residency specialty. Specifically, it asks whether medical students who possess higher levels of mindfulness on a validated measurement instrument will show significantly different residency preferences than do students who score at lower levels. The study does not address the question of why these patterns may exist, but only whether they are evident in the data. 
In light of the research by Langer and Kabat-Zinn, it is reasonable to hypothesize relationships between medical students’ mindfulness and their preference for a primary care over a specialist residency. Primary care practice tends to require a wider scope of interest and higher tolerance of uncertainty than do other specialties. It calls for greater willingness to adapt to the external environment, rather than apply proven and singular methods to control it. Those who are more attuned to adapting to and accepting the external environment, rather than controlling it, may be more inclined to show an interest in these primary care specialties. Langer's research supports these hypotheses.8 
Higher levels of mindfulness also support the principles and practice of osteopathic medicine: “Health is the adaptive and optimal attainment of physiological, mental, emotional, and spiritual well-being. It is based on our natural capacity to meet, with adequate reserves, the usual stresses of daily life and the occasional severe stresses imposed by extremes of environment and activity.”10 These definitions of mindfulness3-9 refer to states of physiological, mental, emotional, and spiritual well-being. 
Preclinical Study Tracks
At the time of this study, the New York Institute of Technology College of Osteopathic Medicine (NYITCOM) had an enrollment of 635 preclinical (years 1 and 2) students. Upon admission, students are required to select 1 of 2 alternative basic science curricula or tracks: lecture discussion based (LDB) and problem-based learning (PBL). The LDB track is the traditional approach to medical education in which a content expert presents lectures to students who then are tested accordingly. The PBL track stresses small-group, self-directed learning based on a case or patient presentation. Two faculty members facilitate small-group meetings, but students are free and encouraged to explore topics related to the case according to their own judgment. At the time of the study, enrollment in the LDB track was 560 (88% of preclinical students); enrollment in the PBL curriculum was 75 (12%). 
The PBL curriculum seems to provide an environment conducive to primary care practice. It requires students to rely on and trust their inner resources more than does the LDB curriculum, which encourages students to follow the lead of their professors. Self-reliance requires and rewards greater levels of mindfulness than does the LDB experience. Mindfulness highlights the idea that “rules, routines and goals guide you but they don't govern you.”11 Students in the PBL track have more freedom in their education, along with the opportunity to delve more deeply into individual cases and develop stronger relationships with their instructors and peers. This structure may facilitate interest in the areas of primary care practice, with its emphasis on multiple aspects of each case and long-term relationships with patients. 
In contrast, the rigid course structure of the LDB program leaves little room for creativity, and students may lose focus on relationships during a long-term regimen of lectures. Compared with PBL, the LDB environment may discourage selection of primary care practice as a residency preference. 
Hypotheses
We made the following hypotheses: 
  • 1. Preclinical students who express an interest in a field of primary care (defined by the American Academy of Family Physicians as internal medicine, family medicine, and pediatrics2) are more mindful than students who express a preference for other specialties. If the hypothesis is confirmed, we will conduct a follow-up study to determine whether the preclinical students who express a preference for primary care eventually enter these specialties as residencies.
  • 2. In light of differences between NYITCOM's 2 preclinical tracks, students who self-selected the PBL curriculum are more mindful than are students who chose the LDB curriculum. If hypothesis 2 is confirmed, we will have evidence that selection of the PBL track is an additional indicator of interest in primary care practice.
Methods
The study protocol was approved by the NYITCOM institutional review board. Response to the survey was evidence of informed consent. 
Participants
All preclinical osteopathic medical students (ie, year 1 and year 2) at NYITCOM were contacted via email to participate in the study. Participation was voluntary. No other inclusion or exclusion criteria were identified. The study was designed to measure students’ current state of mindfulness as a predictor of residency preference, not to develop the qualities of mindfulness in students. Thus, the students were not provided formal exposure to mindfulness before receiving the survey. 
Survey Tool
To measure degrees of mindfulness, we conducted a cross-sectional survey of our preclinical osteopathic medical students (year 1 and year 2) using the Five Facet Mindfulness Questionnaire (FFMQ). This 39-question instrument has been validated as a reliable measure of an individual's disposition toward the 5 facets of mindfulness (observing, describing, acting with awareness, nonjudging of inner experience, and nonreactivity to inner experience), as well as an overall mindfulness score.4,12 Scores for each of the 5 facets, ranging from 1 (lowest level of mindfulness) to 5 (highest level of mindfulness), as well as an overall mindfulness score, are computed by a scoring algorithm. Its internal consistency was adequate for all 5 facets and total scores, with α coefficients of 0.80 (observing), 0.92 (describing), 0.89 (acting with awareness), 0.89 (nonjudging of inner experience), 0.79 (nonreactivity to inner experience), and 0.92 (overall). Its construct validity was investigated by Baer et al,12 who found strong relationships between the FFMQ facets and psychological symptoms such as well-being. 
National norms are not available, but Baer et al12 have reported comparative mindfulness scores from a large group of college students who regularly meditated vs another group whose members did not meditate. The average mindfulness scores were 3.1 for nonmeditating students and 3.9 for meditating students, showing a substantial difference between the groups. 
In addition, a demographic question was included to obtain information on 7 variables: age, sex, preclinical year (year 1 or year 2), marital status, curriculum (LDB or PBL), undergraduate major, and time of matriculation after undergraduate education (early/within 6 months or later). 
Surveys were sent via email in January 2015. Two follow-up reminders to complete the survey were sent to nonresponders 2 weeks and 4 weeks after the initial email. 
Statistical Analyses
To analyze the data, we computed the mean and SD for variables of continuous scale (ie, student mindfulness ratings gathered from the FFMQ). We then computed frequency and proportion for each of 7 binary categorical variables: 
  • ■ gender = female
  • ■ matriculation within 6 months of undergraduate education = yes
  • ■ preclinical year = year 1
  • ■ age = 27 years or older
  • ■ undergraduate major = biology/biological sciences
  • ■ marital status = single
  • ■ curriculum = PBL
For exploratory comparisons between groups, we conducted independent t tests (appropriate for the continuous variables, ie, mindfulness facets and overall mindfulness score) and χ2 tests (best fitted for the categorical variables). None of the scores for the 5 facets of mindfulness were statistically significant. Therefore, for our major analysis with multiple logistic regression, only the overall mindfulness score was included as a predictor. This approach avoids the issue of colinearity because the overall mindfulness score was highly correlated with all of the 5 subscores. 
As a primary analysis of the association of mindfulness with residency choice, we conducted multiple logistic regression, controlling for the 7 demographic variables as possible confounding variables. 
Statistical significance was evaluated at the significance level α=.05. All statistical analyses were performed using IBM SPSS Statistics 22. 
Results
Surveys were emailed to all 635 preclinical students at the same time, with 208 students (33%) responding. 
Exploratory Analysis
Among the 208 respondents, the mean (SD) mindfulness scores were not significantly different from normal distribution (3.33 [0.42]; minimum=2.2, maximum=3.4, IQR=0.6; P>.05). The overall mindfulness scores’ distribution and the mean value were not significantly different by class (Table 1). Of the 208 respondents, 81 (38.9%) chose a primary care specialty for their anticipated residency program. Mean (SD) overall mindfulness scores between those respondents who chose a primary care specialty (3.34 [0.44]) and those respondents who chose a non–primary care specialty (3.33 [0.41]) were not significantly different (P=.88) (Table 2 and Figure). Thus, for the overall population of preclinical students, mindfulness was not a factor in their current choice of a residency program. 
Figure.
Mindfulness as a factor in preclinical students’ choice of residency. Abbreviations: NMM/OMM, neuromusculoskeletal medicine/osteopathic manipulative medicine; OB-GYN, obstetrics-gynecology; PMR, physical medicine and rehabilitation.
Figure.
Mindfulness as a factor in preclinical students’ choice of residency. Abbreviations: NMM/OMM, neuromusculoskeletal medicine/osteopathic manipulative medicine; OB-GYN, obstetrics-gynecology; PMR, physical medicine and rehabilitation.
Table 1.
Descriptive Statistics for Mindfulness Scores on the Five Factor Mindfulness Questionnaire by Preclinical Year
Mindfulness Score All
(N=208)
Year 1
(n=89)
Year 2
(n=119)
Mean (SD)a 3.33 (0.42) 3.30 (0.45) 3.36 (0.40)
Minimum 2.2 2.2 2.5
Maximum 4.5 4.5 4.5
Range (IQR) 2.3 (0.6) 2.3 (0.6) 2.0 (0.5)
Normality
 Skewnessb 0.18 0.24 0.17
 Kurtosisc 0.04 0.11 −0.03
P valued .09 .20 .20

a Overall mean was compared between classes by 2-sample t test (P=.34).

b The normal distribution has a skewness value of 0.

c The normal distribution has a kurtosis value of 0.

d Normality calculated by Kolmogorov-Smirnov test.

Table 1.
Descriptive Statistics for Mindfulness Scores on the Five Factor Mindfulness Questionnaire by Preclinical Year
Mindfulness Score All
(N=208)
Year 1
(n=89)
Year 2
(n=119)
Mean (SD)a 3.33 (0.42) 3.30 (0.45) 3.36 (0.40)
Minimum 2.2 2.2 2.5
Maximum 4.5 4.5 4.5
Range (IQR) 2.3 (0.6) 2.3 (0.6) 2.0 (0.5)
Normality
 Skewnessb 0.18 0.24 0.17
 Kurtosisc 0.04 0.11 −0.03
P valued .09 .20 .20

a Overall mean was compared between classes by 2-sample t test (P=.34).

b The normal distribution has a skewness value of 0.

c The normal distribution has a kurtosis value of 0.

d Normality calculated by Kolmogorov-Smirnov test.

×
Table 2.
Demographic Variables as Predictors of Residency Preference (Primary Care vs Specialist) Among Preclinical Studentsa
Residency Preference
Demographic Variables All Students
(N=208)
Primary Careb
(n=81)
Specialist
(n=127)
P Valuec
Gender <.001
 Male 99 (47.6) 24 (24.2) 75 (75.8)
 Female 109 (52.4) 57 (52.3) 52 (47.7)
Matriculation in Medical School .06
 Early 64 (30.8) 31 (48.4) 33 (51.6)
 Late 144 (69.2) 50 (34.7) 94 (65.3)
Preclinical Year .29
 Year 1 89 (42.8) 31 (34.8) 58 (65.2)
 Year 2 119 (57.1) 50 (42.0) 69 (58.0)
Age, y .33
 21-26 159 (76.4) 59 (37.1) 100 (62.9)
 >26 49 (23.6) 22 (44.9) 27 (55.1)
Undergraduate Major .38
 Biology/biological sciences 100 (48.1) 42 (42.0) 58 (58.0)
 Other majors 108 (51.9) 39 (36.1) 69 (63.9)
Marital Status .53
 Married 27 (13.0) 12 (44.4) 15 (55.6)
 Single 181 (87.0) 69 (38.1) 112 (61.9)
Curriculum .85
 Problem-based learning 35 (16.8) 13 (37.1) 22 (62.9)
 Lecture discussion based 173 (83.2) 68 (39.3) 105 (60.7)

a Data presented as No. (%).

b Primary care included family medicine, internal medicine, and pediatrics.

c Calculated using χ2 test that compared the proportions of expressed residency preference between the 2 categories of each demographic factor.

Table 2.
Demographic Variables as Predictors of Residency Preference (Primary Care vs Specialist) Among Preclinical Studentsa
Residency Preference
Demographic Variables All Students
(N=208)
Primary Careb
(n=81)
Specialist
(n=127)
P Valuec
Gender <.001
 Male 99 (47.6) 24 (24.2) 75 (75.8)
 Female 109 (52.4) 57 (52.3) 52 (47.7)
Matriculation in Medical School .06
 Early 64 (30.8) 31 (48.4) 33 (51.6)
 Late 144 (69.2) 50 (34.7) 94 (65.3)
Preclinical Year .29
 Year 1 89 (42.8) 31 (34.8) 58 (65.2)
 Year 2 119 (57.1) 50 (42.0) 69 (58.0)
Age, y .33
 21-26 159 (76.4) 59 (37.1) 100 (62.9)
 >26 49 (23.6) 22 (44.9) 27 (55.1)
Undergraduate Major .38
 Biology/biological sciences 100 (48.1) 42 (42.0) 58 (58.0)
 Other majors 108 (51.9) 39 (36.1) 69 (63.9)
Marital Status .53
 Married 27 (13.0) 12 (44.4) 15 (55.6)
 Single 181 (87.0) 69 (38.1) 112 (61.9)
Curriculum .85
 Problem-based learning 35 (16.8) 13 (37.1) 22 (62.9)
 Lecture discussion based 173 (83.2) 68 (39.3) 105 (60.7)

a Data presented as No. (%).

b Primary care included family medicine, internal medicine, and pediatrics.

c Calculated using χ2 test that compared the proportions of expressed residency preference between the 2 categories of each demographic factor.

×
Demographic Factors Affecting Residency Choice
Fifty-seven of 109 female respondents (52.3%) chose a primary care specialty for their residency program, while only 24 of 99 male respondents (24.2%) did so, which represents a statistically significant difference (P<.001). Thus, during the preclinical years, female respondents were more likely to choose a primary care specialty for their residency program. 
None of the remaining demographic factors (age, preclinical year, curriculum, marital status, undergraduate major, and time of matriculation) had a significant effect on choice of residency (Table 3). 
Table 3.
Multivariate Logistic Regression Examining Factors Associated With Residency Preference
Factors Associated With Residency: Program = Primary Carea B (SE) OR (95% CI) P Value
Gender = female 1.4 (0.3) 4.4 (2.2-8.5) <.001
Begin medical school immediately? = Yes 0.8 (0.3) 2.3 (1.2-4.5) .016
Age = ≥27 y 0.7 (0.4) 2.6 (0.9-7.1) .06
Undergraduate major = biology/biological sciences 0.3 (0.3) 1.3 (0.7-2.5) .38
Curriculum = problem-based learning 0.1 (0.4) 1.1 (0.5-2.5) .82
Overall mindfulness 0.2 (0.4) 1.1 (0.6-1.8) .82
Constant −2.4 (1.3)

a Primary care included family medicine, internal medicine, and pediatrics.

Table 3.
Multivariate Logistic Regression Examining Factors Associated With Residency Preference
Factors Associated With Residency: Program = Primary Carea B (SE) OR (95% CI) P Value
Gender = female 1.4 (0.3) 4.4 (2.2-8.5) <.001
Begin medical school immediately? = Yes 0.8 (0.3) 2.3 (1.2-4.5) .016
Age = ≥27 y 0.7 (0.4) 2.6 (0.9-7.1) .06
Undergraduate major = biology/biological sciences 0.3 (0.3) 1.3 (0.7-2.5) .38
Curriculum = problem-based learning 0.1 (0.4) 1.1 (0.5-2.5) .82
Overall mindfulness 0.2 (0.4) 1.1 (0.6-1.8) .82
Constant −2.4 (1.3)

a Primary care included family medicine, internal medicine, and pediatrics.

×
Primary Analysis
As a primary analysis, multiple logistic regression was performed with overall mindfulness score as a predictor in the statistical model and choice of residency program as an outcome, controlling for the 7 possible confounding variables of gender, age, curriculum, undergraduate major, preclinical year, marital status, and time between undergraduate education and matriculation in medical school. Based on results of a regression analysis, the overall mindfulness score was not a strong predictor of students’ preference of residency program for all students (P=.82), but being female was associated with a preference for primary care interest (OR, 4.4; 95% CI, 2.2-8.5; P<.001), as was early matriculation (OR, 2.3; 95% CI, 1.2-4.5; P=.016) (Table 3). 
Discussion
Hypotheses
First- and second-year osteopathic medical students who expressed a preference for primary care practice showed similar scores on the overall FFMQ mindfulness scale when compared with the scores of students who reported preference for a specialty field. Thus, hypothesis 1 was rejected: A mindfulness score is not a predictor of interest in a residency field. One factor may be the inclination of many students to express preference for a primary care residency anticipating that they will need this experience as a precondition for entry into one of the specialties, such as emergency medicine or surgery. 
Students enrolled in NYITCOM's PBL track did not have significantly different mindfulness scores when compared with their counterparts in the LDB curriculum. Thus, hypothesis 2 was rejected: Students’ current state of mindfulness was not associated with their choice of curriculum. 
Post-hoc Findings
Male vs Female Students
While there was no significant relationship between mindfulness and preference for primary care practice among respondents, the factors of gender and immediate matriculation from undergraduate to medical education were moderately correlated with students’ interest in a particular residency. Specifically, the factors of being female and beginning medical school immediately after undergraduate education were both associated with a preference for primary care as a field for residency, at least in the preclinical years. 
Primary analysis of the data revealed that, compared with male students, significantly more female students expressed preference for primary care. Over the past few decades, increasing numbers of women have entered all medical fields, yet there are few data to suggest whether these women gravitate more toward primary care or other specialties.13 A 1990 study13 suggested that women would be drawn toward specialties with a “controllable” lifestyle, such as radiology, dermatology, and anesthesiology, which afford predictable hours. However, a 2005 study14 suggested that this was not the case—a greater percentage of women than men favored careers with “uncontrollable lifestyles,” defined in the study as careers in internal medicine, obstetrics-gynecology, orthopedic surgery, pediatrics, general surgery, and urology.10 This finding supports the conclusion, suggested by our research, that women are more attracted to a practice in primary care. Factors that may influence these findings include mentors,15 lifestyle goals, and different priorities when choosing a career. 
Early-Career vs Late-Career Matriculation
Students who matriculated into medical school immediately after completing undergraduate education were significantly more likely to express a preference for a primary care field of practice. This group seems to place greater emphasis on the longitudinal, or continuity, aspects of patient care. In contrast, students who have had more life experience may have accumulated lifestyle and financial burdens that disincline them to primary care practice, which traditionally requires greater time commitment and offers lower earning potential.16 In addition, older individuals may have acquired more external responsibilities and would be therefore drawn to a field that requires fewer years of training and the opportunity to earn more money sooner.16-21 
PBL vs LDB Curriculum
The similarity in mindfulness among students in both groups was unexpected. The PBL program demands and rewards independence and self-reliance over the more predictable learning experiences found in the LDB curriculum. We had expected to find that students who chose this more open path to medical education (PBL) would bring with them a higher level of mindfulness, which embodies independence and self-reliance over routine. The finding that both scored similarly on a mindfulness evaluation suggests that factors other than mindfulness prompt students to select from these 2 different approaches to learning. Additional research is needed to illuminate this aspect of student behavior. 
Limitations
This study is limited to a self-selected sample of 208 students from a single osteopathic medical school, representing 33% of the preclinical student population. This sample has limited generalizability to the total preclinical population of the school and less application to the national population of osteopathic medical students. The survey instrument was self-administered, confounding validity of the data. As a cross-sectional study, findings are limited to correlations among the scores on the FFMQ survey and expressed residency preference. 
Conclusion
In this study, mindfulness was not a predictor of student interest in primary care practice as a residency specialty. Looking forward, multiple replicative studies need to be conducted to establish a broad-based statistical foundation for the data collected. Findings from this preliminary study may be representative of the wider population of US-trained osteopathic and allopathic medical students, or they may be outliers. Likewise, the confounding areas of male vs female and early vs late matriculation call for further study. 
This study did not look into mindfulness scores in osteopathic vs allopathic students or the relationship of mindfulness scores for resident physicians, attending specialists, and attending primary care specialists. These would be logical areas for future study. Future study also needs to be done to determine the degree to which students’ preclinical preference predicts their actual selection of a residency specialty upon graduation. To this end, we are currently completing a parallel study of mindfulness in clinical (years 3 and 4) osteopathic medical students and osteopathic residents. 
We expect to see more investigation into the wide range of predictors of residency preference. As future studies accumulate, medical schools will be better prepared to admit students whose career goals serve both their own aspirations and the need for primary care physicians in the United States. 
Author Contributions
All authors provided substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data; all authors drafted the article or revised it critically for important intellectual content; all authors gave final approval of the version of the article to be published; and all authors agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. 
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Figure.
Mindfulness as a factor in preclinical students’ choice of residency. Abbreviations: NMM/OMM, neuromusculoskeletal medicine/osteopathic manipulative medicine; OB-GYN, obstetrics-gynecology; PMR, physical medicine and rehabilitation.
Figure.
Mindfulness as a factor in preclinical students’ choice of residency. Abbreviations: NMM/OMM, neuromusculoskeletal medicine/osteopathic manipulative medicine; OB-GYN, obstetrics-gynecology; PMR, physical medicine and rehabilitation.
Table 1.
Descriptive Statistics for Mindfulness Scores on the Five Factor Mindfulness Questionnaire by Preclinical Year
Mindfulness Score All
(N=208)
Year 1
(n=89)
Year 2
(n=119)
Mean (SD)a 3.33 (0.42) 3.30 (0.45) 3.36 (0.40)
Minimum 2.2 2.2 2.5
Maximum 4.5 4.5 4.5
Range (IQR) 2.3 (0.6) 2.3 (0.6) 2.0 (0.5)
Normality
 Skewnessb 0.18 0.24 0.17
 Kurtosisc 0.04 0.11 −0.03
P valued .09 .20 .20

a Overall mean was compared between classes by 2-sample t test (P=.34).

b The normal distribution has a skewness value of 0.

c The normal distribution has a kurtosis value of 0.

d Normality calculated by Kolmogorov-Smirnov test.

Table 1.
Descriptive Statistics for Mindfulness Scores on the Five Factor Mindfulness Questionnaire by Preclinical Year
Mindfulness Score All
(N=208)
Year 1
(n=89)
Year 2
(n=119)
Mean (SD)a 3.33 (0.42) 3.30 (0.45) 3.36 (0.40)
Minimum 2.2 2.2 2.5
Maximum 4.5 4.5 4.5
Range (IQR) 2.3 (0.6) 2.3 (0.6) 2.0 (0.5)
Normality
 Skewnessb 0.18 0.24 0.17
 Kurtosisc 0.04 0.11 −0.03
P valued .09 .20 .20

a Overall mean was compared between classes by 2-sample t test (P=.34).

b The normal distribution has a skewness value of 0.

c The normal distribution has a kurtosis value of 0.

d Normality calculated by Kolmogorov-Smirnov test.

×
Table 2.
Demographic Variables as Predictors of Residency Preference (Primary Care vs Specialist) Among Preclinical Studentsa
Residency Preference
Demographic Variables All Students
(N=208)
Primary Careb
(n=81)
Specialist
(n=127)
P Valuec
Gender <.001
 Male 99 (47.6) 24 (24.2) 75 (75.8)
 Female 109 (52.4) 57 (52.3) 52 (47.7)
Matriculation in Medical School .06
 Early 64 (30.8) 31 (48.4) 33 (51.6)
 Late 144 (69.2) 50 (34.7) 94 (65.3)
Preclinical Year .29
 Year 1 89 (42.8) 31 (34.8) 58 (65.2)
 Year 2 119 (57.1) 50 (42.0) 69 (58.0)
Age, y .33
 21-26 159 (76.4) 59 (37.1) 100 (62.9)
 >26 49 (23.6) 22 (44.9) 27 (55.1)
Undergraduate Major .38
 Biology/biological sciences 100 (48.1) 42 (42.0) 58 (58.0)
 Other majors 108 (51.9) 39 (36.1) 69 (63.9)
Marital Status .53
 Married 27 (13.0) 12 (44.4) 15 (55.6)
 Single 181 (87.0) 69 (38.1) 112 (61.9)
Curriculum .85
 Problem-based learning 35 (16.8) 13 (37.1) 22 (62.9)
 Lecture discussion based 173 (83.2) 68 (39.3) 105 (60.7)

a Data presented as No. (%).

b Primary care included family medicine, internal medicine, and pediatrics.

c Calculated using χ2 test that compared the proportions of expressed residency preference between the 2 categories of each demographic factor.

Table 2.
Demographic Variables as Predictors of Residency Preference (Primary Care vs Specialist) Among Preclinical Studentsa
Residency Preference
Demographic Variables All Students
(N=208)
Primary Careb
(n=81)
Specialist
(n=127)
P Valuec
Gender <.001
 Male 99 (47.6) 24 (24.2) 75 (75.8)
 Female 109 (52.4) 57 (52.3) 52 (47.7)
Matriculation in Medical School .06
 Early 64 (30.8) 31 (48.4) 33 (51.6)
 Late 144 (69.2) 50 (34.7) 94 (65.3)
Preclinical Year .29
 Year 1 89 (42.8) 31 (34.8) 58 (65.2)
 Year 2 119 (57.1) 50 (42.0) 69 (58.0)
Age, y .33
 21-26 159 (76.4) 59 (37.1) 100 (62.9)
 >26 49 (23.6) 22 (44.9) 27 (55.1)
Undergraduate Major .38
 Biology/biological sciences 100 (48.1) 42 (42.0) 58 (58.0)
 Other majors 108 (51.9) 39 (36.1) 69 (63.9)
Marital Status .53
 Married 27 (13.0) 12 (44.4) 15 (55.6)
 Single 181 (87.0) 69 (38.1) 112 (61.9)
Curriculum .85
 Problem-based learning 35 (16.8) 13 (37.1) 22 (62.9)
 Lecture discussion based 173 (83.2) 68 (39.3) 105 (60.7)

a Data presented as No. (%).

b Primary care included family medicine, internal medicine, and pediatrics.

c Calculated using χ2 test that compared the proportions of expressed residency preference between the 2 categories of each demographic factor.

×
Table 3.
Multivariate Logistic Regression Examining Factors Associated With Residency Preference
Factors Associated With Residency: Program = Primary Carea B (SE) OR (95% CI) P Value
Gender = female 1.4 (0.3) 4.4 (2.2-8.5) <.001
Begin medical school immediately? = Yes 0.8 (0.3) 2.3 (1.2-4.5) .016
Age = ≥27 y 0.7 (0.4) 2.6 (0.9-7.1) .06
Undergraduate major = biology/biological sciences 0.3 (0.3) 1.3 (0.7-2.5) .38
Curriculum = problem-based learning 0.1 (0.4) 1.1 (0.5-2.5) .82
Overall mindfulness 0.2 (0.4) 1.1 (0.6-1.8) .82
Constant −2.4 (1.3)

a Primary care included family medicine, internal medicine, and pediatrics.

Table 3.
Multivariate Logistic Regression Examining Factors Associated With Residency Preference
Factors Associated With Residency: Program = Primary Carea B (SE) OR (95% CI) P Value
Gender = female 1.4 (0.3) 4.4 (2.2-8.5) <.001
Begin medical school immediately? = Yes 0.8 (0.3) 2.3 (1.2-4.5) .016
Age = ≥27 y 0.7 (0.4) 2.6 (0.9-7.1) .06
Undergraduate major = biology/biological sciences 0.3 (0.3) 1.3 (0.7-2.5) .38
Curriculum = problem-based learning 0.1 (0.4) 1.1 (0.5-2.5) .82
Overall mindfulness 0.2 (0.4) 1.1 (0.6-1.8) .82
Constant −2.4 (1.3)

a Primary care included family medicine, internal medicine, and pediatrics.

×