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 Table of Contents  
ORIGINAL RESEARCH ARTICLE
Year : 2017  |  Volume : 30  |  Issue : 2  |  Page : 146-155

Clinical medical education in rural and underserved areas and eventual practice outcomes: A systematic review and meta-analysis


1 3rd Year Medical Student, Mercer University School of Medicine, Columbus, GA, USA
2 2nd Year Psychiatry Resident, Department of Psychiatry, Emory University School of Medicine, Atlanta, GA, USA

Date of Web Publication19-Sep-2017

Correspondence Address:
Ryan William Raymond Guilbault
33 West 11th Street, P.O. Box 870, Columbus, GA 31902-0870
USA
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/efh.EfH_226_16

  Abstract 

Background: Undergraduate medical students are enrolled in clinical education programs in rural and underserved urban areas to increase the likelihood that they will eventually practice in those areas and train in a primary care specialty to best serve those patient populations. Methods: MEDLINE and Cochrane Library online databases were searched to identify articles that provide a detailed description of the exposure and outcome of interest. A qualitative review of articles reporting outcome data without comparison or control groups was completed using the Medical Education Research Study Quality Instrument (MERSQI). A meta-analysis of articles reporting outcome data with comparison or control groups was completed with statistical and graphical summary estimates. Results: Seven hundred and nine articles were retrieved from the initial search and reviewed based on inclusion and exclusion criteria. Of those, ten articles were identified for qualitative analysis and five articles included control groups and thus were included in the quantitative analysis. Results indicated that medical students with clinical training in underserved areas are almost three times as likely to practice in underserved areas than students who do not train in those areas (relative risk [RR] = 2.94; 95% confidence interval [CI]: 2.17, 4.00). Furthermore, medical students training in underserved areas are about four times as likely to practice primary care in underserved areas than students who do not train in those locations (RR = 4.35; 95% CI: 1.56, 12.10). Discussion: These estimates may help guide medical school administrators and policymakers to expand underserved clinical training programs to help relieve some of the problems associated with access to medical care among underserved populations.

Keywords: Clinical education, health professional shortage area, medical education, medically underserved area, practice outcomes


How to cite this article:
Raymond Guilbault RW, Vinson JA. Clinical medical education in rural and underserved areas and eventual practice outcomes: A systematic review and meta-analysis. Educ Health 2017;30:146-55

How to cite this URL:
Raymond Guilbault RW, Vinson JA. Clinical medical education in rural and underserved areas and eventual practice outcomes: A systematic review and meta-analysis. Educ Health [serial online] 2017 [cited 2020 Oct 26];30:146-55. Available from: https://www.educationforhealth.net/text.asp?2017/30/2/146/215091


  Background Top


The United States (U.S.) is currently facing a significant maldistribution of physicians, particularly among primary care physicians and in rural and low-income urban areas.[1],[2],[3],[4],[5] These underserved patients represent a significant proportion of the U.S. population and face disproportionally unfavorable health outcomes, partially due to their inability to easily access preventive and maintenance health services.[2],[6],[7],[8]

Recent reports reveal that approximately 20% of the U.S. population currently lives in rural areas. Although the rural population is declining as people gravitate toward urban centers, physicians serving rural areas have not been able to keep pace with an increasingly underserved and aging pool of patients.[9],[10],[11] In fact, almost 40% of the U.S. rural populous lives in federally designated health professional shortage areas (HPSAs).[12] As of June 2014, there were over 6,100 federally designated primary care HPSAs and medically underserved areas (MUAs) based on the demographic characteristics of and medical resources available in the county or census track in question.[13] Conservative estimates project that an additional 8200 primary care physicians would need to practice in HPSAs alone to alleviate the health burdens associated with inadequate health-care services received by these low-income urban and rural patients.[14]

While expansion of the overall enrollment of medical students has attempted to match the rate of population growth, declining interest in primary care among medical students has exacerbated the disproportion of specialists relative to primary care physicians.[15] Surveys of medical students in 2014 revealed that the distribution of physicians practicing in underserved areas will likely worsen in the future, with just a 1% increase in the number of students reporting an intention to practice in underserved areas since 2012.[16]

The current model of undergraduate medical student clinical placement is primarily hospital driven, but many medical schools have created programs and altered admission criteria to rectify the growing physician gap in rural areas, MUAs, and HPSAs.[17],[18],[19],[20] Previous systematic reviews have summarized the effectiveness of such programs pertaining to narrowing the physician gap in rural areas.[14],[21],[22],[23],[24],[25] However, few identified reviews have expanded the scope of study to include urban underserved populations, and no reviews included a meta-analysis component in their quantitative review. Thus, the purpose of this study was to summarize the existing evidence of the association between undergraduate medical student clinical education experiences in rural areas, MUAs, and HPSAs with eventual practice specialty and location outcomes.


  Methods Top


Exposure and practice outcomes defined

For the purposes of this review, the process of study inclusion was kept as transparent and selective as possible. Therefore, the term “primary care” was limited to physicians practicing general internal medicine, general pediatric medicine, or family medicine. General internists, pediatricians, and family doctors are widely accepted as primary care physicians, and this interpretation of primary care is employed in most medical literatures.[26] MUA designation was restricted to the U.S. Department of Health and Human Resources definition of HPSAs (an area physician to population ratio of <1:3500) and MUAs (formula including the ratio of primary care physicians per 1000 population, infant mortality rate, percentage of the population with incomes below the poverty line, and percentage of the population aged 65 years and older in the census track or county in question).[13] HPSAs and MUAs both include rural and urban underserved areas, and thus expand the scope of the study beyond rural areas alone. Finally, rural areas were limited to areas federally recognized as nonstandardized statistical metropolitan areas (SMSAs), defined as urban areas with a population >50,000.[27] Due to the controversial nature of the definition of rural and underserved areas, studies were only included for review if the study concept of rural or urban underserved was clearly defined and fits the definitions listed above.

Inclusion and exclusion criteria

Educational interventions are often difficult to assess due to the number of uncontrollable variables in observational settings. Selective inclusion and exclusion criteria were employed in this review in an effort to evaluate the effect of clinical education alone on eventual practice outcomes and to standardize all included studies for statistically sound aggregation of quantitative data.

The purpose of this review was to provide a qualitative and quantitative summary of existing evidence that undergraduate medical student clinical education in rural or underserved areas improves the likelihood of eventual practice of primary care specialties in those areas. The exposure of interest of this review was undergraduate medical student clinical education in rural or underserved areas. The outcome of interest was eventual practice location and specialty. Thus, studies including descriptions of the exposure of interest (e.g., duration of clinical education, clinical setting, patient population, and/or preceptor practice specialty) and associated outcome of interest (e.g., eventual practice location, practice specialty, and/or patient population served at practice) were included.

Countries outside the U.S. have different health-care systems that may unintentionally or intentionally attract or deter physicians from practicing primary care specialties and/or in rural or underserved areas. Thus, studies that reported data from countries outside of the U.S., regardless if the studies reported the exposure or outcome of interest of this review, were excluded. Studies reporting high school, collegiate, graduate medical or resident, practicing physician, or other allied health field clinical education in rural or underserved areas were also excluded from further study. It is recognized that osteopathic medical schools produce a higher proportion of primary care physicians and in underserved areas and train students using slightly different curricula than allopathic medical schools.[28] Thus, studies reporting osteopathic medical school clinical education were also excluded from the review. Studies that only reported undergraduate medical student perceptions, intentions to practice various specialties, or practice in various locations were excluded due to lack of quantitative practice outcome data. Students selecting or “matching” into internal medicine or pediatric residency programs can further specialize and may not practice as general internists or pediatricians. Additionally, medical residents training in rural or underserved areas may not necessarily practice in those areas. Thus, articles reporting residency data as the sole study outcome were excluded from further review.

Literature search

A comprehensive search of MEDLINE and Cochrane Library was completed to identify previously published literature on the topic of interest. Specifically, empirical studies providing quantitative results about undergraduate medical students' clinical training in rural and underserved areas and subsequent practice location and specialty were sought. Studies were identified using the Boolean logic and search terms seen in [Figure 1]. Using the prespecified inclusion and exclusion criteria, titles and abstracts were reviewed independently by two investigators for potential relevance. Articles included by either reviewer were included for full-text screening. During full-text screening, each researcher independently reviewed the articles and indicated a decision to include or exclude the article for data abstraction. Differences of opinion regarding article inclusion were reconciled through additional review and discussion.
Figure 1: Boolean logic search terms used to identify potential studies for systematic review and meta-analysis

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References of relevant review articles, meta-analyses, and methods articles were manually searched and cross-referenced against the library of citations identified through database searching. The remaining articles were obtained in full and reviewed for study content, quality, and relevance. Studies reporting medical programs that met all study inclusion criteria were only included if student placement and practice outcomes were described in sufficient enough detail to allow analysis. Studies with overlapping study populations were eliminated in an effort to avoid overemphasis on any single population. The studies that remained were included for a qualitative analysis of study design and results [Figure 2].
Figure 2: The search, review, and selection of publication of clinical medical education in underserved areas and eventual practice outcomes

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Qualitative and meta-analyses

We utilized the Medical Education Research Study Quality Instrument (MERSQI) to assess study quality of articles included for qualitative review.[28] The MERSQI has been independently validated for observational studies assessing medical school education and is accepted as the criterion reference standard of study quality assessment instruments in medical education research.[29] While the MERSQI score is helpful for discerning relative study quality, it is displayed [Table 1] for summary and for external comparison purposes only. The MERSQI criteria are part of a larger rubric for assessing study quality in this review, but the score itself is not being used in such a manner.
Table 1: Assessment of study quality of articles included for qualitative analysis using the Medical Education Research Study Quality Instrument (MERSQI)

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Following qualitative assessment, we independently eliminated studies that did not include or adequately describe study comparison or control groups. Study intervention and comparison groups and definitions of underserved areas were also reviewed to achieve the highest possible level of study homogeneity and reduce the risk of bias. Once all the remaining studies were determined to have homogeneous exposures, outcomes, and study design [Table 2], we independently abstracted necessary data to calculate relative risks (RRs). Study data were then assessed for heterogeneity using a visual inspection of study heterogeneity, and confirmed using the I2 statistic, which describes the percentage of total variation across multiple studies that is due to heterogeneity beyond chance. An I2 value of 0% indicates that there is no inter-study heterogeneity beyond chance, with larger values describing increasing values of variance up to 100. Forest plots [Figure 3],[Figure 4],[Figure 5] displaying individual study RRs, summary measures (RRs), and accompanying estimates of error (95% confidence intervals [CIs]) were created using Review Manager (RevMan) 5.3 software (The Cochrane Collaboration, Copenhagen, Denmark).[30]
Table 2: Study design description of articles included for quantitative analysis

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Figure 3: Summary of published studies on effects of medical undergraduate clinical education in underserved areas on eventual practice in underserved areas

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Figure 4: Summary of published studies on effects of medical undergraduate clinical education in underserved areas on eventual primary care practice

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Figure 5: Summary of published studies on effects of medical undergraduate clinical education in underserved areas on eventual primary care practice in underserved areas

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  Results Top


The initial database search returned 709 potentially relevant studies. After applying the predetermined inclusion and exclusion criteria during abstract and title review, 100 articles remained. The full texts of these 100 articles were obtained and evaluated for meeting predetermined inclusion and exclusion criteria. We reviewed the reference lists of fifty review articles and methods papers, identifying an additional six potential studies. This process resulted in the identification of ten articles that met all inclusion and exclusion criteria, did not overlap with other study data, clearly reported exposure and outcome data, and defined rural or underserved areas [Figure 2]. These ten studies were subsequently included for qualitative analysis and their characteristics are summarized in [Table 1].[31],[32],[33],[34],[35],[36],[37],[38],[39],[40]

Qualitative analysis

Studies included for qualitative analysis included medical students trained across the continental U.S. in medical schools specifically aimed at increasing the primary care and/or rural or underserved area physician supply. Included studies focused on schools in Florida, Illinois, Minnesota, New Mexico, Pennsylvania, and Alabama, and assessed graduates from 1971 to 2007. The study outcomes included practicing in a rural or underserved area, practicing a primary care specialty, and practicing a primary care specialty in a rural or underserved area. Of the studies included for qualitative analysis, all but Rabinowitz et al. 2001 and Wheat et al. reported multiple outcomes of interest.[37],[39] All included studies had a retrospective cohort study design and were conducted at a single institution except for Pathman et al., which assessed the characteristics of medical education among American physicians practicing in non-SMSAs or HPSAs in a retrospective case study design.[35] Among the ten studies included for qualitative analysis, the mean (±standard deviation) MERSQI score was 9.05 (±1.26) out of a possible 15 with a range of 7.5–11.

HPSA physician supply program characteristics for studies evaluated in the quantitative analysis are provided in [Table 2]. Program characteristics for studies included only for qualitative analysis are summarized in the following paragraph. Pathman et al.'s retrospective case study was composed of physicians practicing in HPSAs from various U.S. medical schools, though among the participating physicians, 50% completed rural rotations in medical school and 25% attended medical schools that emphasized rural medicine.[35] The University of Minnesota Medical School Rural Physician Associate Program (analyzed by both Verby and Halaas et al.) involves a 36-week rotation in rural Minnesota practice during the 3rd year of medical school, a community health needs' assessment of the surrounding HPSA community, and “regular” online collaboration with other students participating in the program in other HPSA sites.[33],[40] The University of Illinois College of Medicine Rural Medical Education (RMED) Program, highlighted by Glasser et al., involved targeting undergraduate and high school students with stated interest in rural medicine or with a rural background, periodic visits to rural communities with education about common rural health problems, attending the Rockford (rural branch) campus, 16 weeks of primary care rotations in a rural community during 3rd and 4th years of medical school, and a completion of a community-oriented primary care project.[32] The University of Alabama School of Medicine Rural Health Leaders Pipeline Programs, evaluated by Wheat et al., involves elementary school puppet shows about health professional careers, increasing high school student interest in rural health, recruiting undergraduate and high school students with stated interest in rural medicine or with a rural background, periodic visits to rural communities with education about common rural health problems, and attending a rural satellite campus during clinical rotations during the 3rd and 4th years of medical school.[39]

Practice location

Seven of the ten studies included for qualitative analysis reported practice location – with an associated specialty – as an outcome.[31],[33],[34],[35],[36],[37],[40] Of the seven studies that reported practice location, only Mennin et al. reported eventual practice in MUAs as a study outcome.[34] Both Pathman et al. and Rabinowitz et al., 1999, reported eventual practice in HPSAs as outcomes, though both studies aggregated the data of eventual practice in HPSAs with eventual practice in non-SMSAs.[35],[36] The percentage of undergraduate medical students who had clinical training experience in rural or underserved areas and eventually practiced in those areas ranged from 4.7% to 62.5% among studies included for qualitative analysis.

Practice specialty

All included studies but Rabinowitz et al. 2001 and Wheat et al. reported primary care practice-without an associated location-as an outcome.[36],[39] Of the eight studies that reported primary care practice, Rabinowitz et al. 1999 was the only study that reported eventual practice of family medicine and not practice of all primary care specialties.[36] The percentage of undergraduate medical students who had clinical training experience in rural or underserved areas and eventually practiced primary care ranged from 31.8% to 85.4% among studies included for qualitative analysis.

Practice specialty by location

Of the studies included for qualitative analysis, five reported primary care practice in rural or underserved areas as an outcome.[32],[36],[37],[38],[39] Of the five studies that reported primary care practice data in rural or underserved areas, the study by Rabinowitz et al., 1999, was the only study that reported eventual practice of family medicine in non-SMSAs instead of practice of all primary care specialties in non-SMSAs.[37] The percentage of undergraduate medical students who had clinical training experience in rural or underserved areas and eventually practiced primary care in those areas ranged from 9.5% to 67% among studies included for qualitative analysis.[32],[37] It is important to note that three of the five studies reporting data for primary care practice in rural or underserved areas had a population consisting of graduates of the Physician Shortage Area Program (PSAP) of Thomas Jefferson University Jefferson Medical College.[36],[37],[38] While these studies did not have overlapping populations, the aggregate measures of primary care practice in underserved areas may be overly representative of the PSAP program and may lack external validity.

Meta-analysis

While five studies did report adequate data for inclusion in the meta-analysis, they did not include a control or comparison group in their study design.[32],[33],[35],[39],[40] Thus, their outcomes could only be measured in proportions and were not included in the meta-analysis as RRs and 95% CIs could not be calculated. All five studies that clearly defined control or comparison groups used undergraduate medical students from the same medical school that were not exposed to rural or underserved areas during clinical education as the control group.

Of the five studies that were included in quantitative analysis, four reported eventual practice location data.[31],[34],[36],[38] A meta-analysis revealed that undergraduate medical students' training in rural or underserved areas is about three times as likely to practice in those areas as their peers (RR = 2.94; 95% CI = 2.17, 4.00). The I2 statistic for eventual practice location was 56%, though visual inspection of the study data showed limited inter-study heterogeneity [Figure 3]. The I2 statistic for inter-study heterogeneity is sensitive to the number of studies included in analysis, thus we relied on a visual inspection of included studies for a more reliable assessment of inter-study heterogeneity.

Of the five studies that were included in quantitative analysis, three reported eventual practice specialty data.[31],[34],[36] A meta-analysis revealed that undergraduate medical students' training in rural or underserved areas is about two times as likely to practice primary care as their peers (RR = 2.09; 95% CI = 0.67, 6.48). The I2 statistic for eventual practice specialty was 97%, and visual inspection of the study data confirmed significant inter-study heterogeneity [Figure 4]. Furthermore, the 95% CI for the summary RR overlaps with one, indicating that the summary measure is not statistically significant.

Of the five studies that were included in quantitative analysis, three reported eventual practice specialty by location data.[36],[37],[38] A meta-analysis revealed that undergraduate medical students' training in rural or underserved areas is about four times as likely to practice primary care in those areas as their peers (RR = 4.35; 95% CI = 1.56, 12.10). The I2 statistic for eventual practice specialty by location was 98%, and visual inspection of the study data confirmed significant inter-study heterogeneity [Figure 5].


  Discussion Top


We sought to quantify the impact of medical education programs on eventual practice outcomes. The degree to which this review is applicable to all U.S. programs was limited by the number of previously published articles on the topic of interest and the employed exclusion criteria. The results of the review indicate that all included clinical education programs have been successful in training medical students for practices in primary care, rural or underserved areas, or primary care practice in rural or underserved areas.

Review strengths

This review was an expansion on previously published systematic reviews on similar topics that did not include urban underserved areas in their exposure or outcome data.[14],[21],[22],[23],[24],[25] The inclusion of urban underserved areas in this analysis improved the external validity of the review to countless medical education programs that seek to train students in any underserved area, regardless of rurality. The review may also allow medical schools that are positioned closer to SMSAs to consider designing educational programs with the goal of increasing the primary care and overall physician supply in underserved areas closer to their campuses.

This review was the only identified review on the topic of interest that utilized a previously independently validated quality assessment measurement tool (MERSQI) to help assess relative study quality. The inclusion of the MERSQI not only increased the internal validity of the study design and quality review process, but may also allow outside comparisons of individual study quality.

This review also utilized rather selective study exclusion criteria, which produced a more homogeneous group of included studies than previous reviews.[21],[22],[23],[24],[25] Due to the stringent exclusion criteria and relative study homogeneity, this review included a quantitative evaluation beyond descriptive statistical summaries, unlike previously published reviews on similar topics.[14],[21],[22],[23],[24],[25] The summary measures of effects generated in this meta-analysis may be used to quantify the impact of medical education programs in rural and underserved areas on the physician gap in those areas.

Review limitations

The summary measures generated in this review did have some substantial statistical limitations. Implementing a random effects model for calculation of the summary RRs accounted for some of the variance in study design, included populations, and reported outcomes. The small number of studies included in the summary measures of effects and the inter-study heterogeneity of included studies increased the margin of error in the models. Therefore, we cannot say with certainty that the generated RRs are precise summaries of the association between the exposure and outcomes of interest, and should thus be interpreted and applied with caution.

In addition, while all publications included in the quantitative review met all inclusion and exclusion criteria, there was still significant heterogeneity between included publications' student clinical training duration and location. For instance, the extent of rural area clinical exposure ranged from “early” clinical exposure in underserved areas to 32 weeks of structured preceptorships in non-SMSAs. The high degree of study heterogeneity may be partially attributed to the variance in intervention program admission criteria. Fournier et al. reported that the program in medical sciences at the University of Florida College of Medicine, for example, places a priority on admitting applicants who are nontraditional (e.g., >25 years old, had nonhealth-related or other allied health careers, have established families with children, etc.), from financially or educationally disadvantaged backgrounds, and underrepresented minorities.[31] Conversely, Rabinowitz et al. reported that the PSAP at the Thomas Jefferson University Jefferson Medical College includes an extensive recruiting and application process among students in rural and disadvantaged areas.[36],[37],[38]

Similar heterogeneity was found among studies included for qualitative analysis, which may be partially attributed to the variance in medical school program curricula. Mennin et al. reported that the primary care curriculum at the University of New Mexico School Of Medicine, for instance, includes a 16-week, community-oriented primary care preceptorship often located in MUAs during the 1st and 2nd years of medical school.[34] However, Glasser et al. reported that the RMED program at the University of Illinois College of Medicine includes rural and community medicine concepts integrated into each year of course work, a 16-week preceptorship at a rural family medicine clinic, during the 3rd and 4th years of medical school, living in the rural area of the family medicine clinic during the 4th year of medical school rotation, and a community-oriented primary care capstone project during the 4th year of medical school.[32]

In addition, we realize that several notable U.S. programs were omitted from qualitative review. Michigan State University School of Medicine's Upper Peninsula Program and University of Minnesota Medical School-Duluth, as examples, had articles retrieved in the initial search, but did not meet review inclusion criteria and were subsequently eliminated from further review.

Furthermore, we understand that the twenty studies conducted in Japan, Australia, Europe, and Canada that were excluded from further review would have been included in the final qualitative and quantitative reviews had they been conducted in the U.S.A. We acknowledge that excluding international studies limits the generalizability of this study, and that the results of this study therefore cannot be directly applied to programs outside the U.S.A. However, as medical education studies already include a significant number of potentially confounding variables, the authors sought the most homogeneous set of studies possible. Readers outside the U.S.A. may keep individual program components discussed in [Table 2] and the results section and their associated outcomes in mind when structuring or re-structuring their curricula. In addition, future meta-analyses may consider including studies with non-American populations as a subgroup analysis for each country.

Furthermore, while results of this review can be applied to medical education programs with an aim to increase the rural or underserved physician supply, they cannot be applied to all medical students. The studies included for quantitative analysis were subject to differential selection bias, as they compared students in rural and underserved medical education programs to the rest of the student body. Therefore, additional factors that have been demonstrated to strongly influence future practice outcomes may have confounded the association between clinical education exposure and eventual practice outcome results alone. In fact, previous reviews found that factors such as medical school location, medical school emphasis on practice location and specialty, ties to rural or underserved areas, career intention upon medical school matriculation, and financial factors (i.e., payback programs, student loan burden, and future earning potential) had greater influence on medical students' future practice location and specialty than exposure to clinical experience in those areas during their preclinical education.[41],[42]

Future studies should attempt to adjust for confounding factors in an effort to quantify the relationship between clinical medical education and eventual practice outcomes among all medical students, while limiting potential biases.

Finally, as with all systematic reviews, there is potential for the researchers to overlook previously published studies relevant to the topic of interest. However, the use of an inclusive Boolean search strategy, a cross-checking process by multiple reviewers, and cross-referencing all included studies and identified methods, review, and meta-analyses' list of references sought to limit this oversight.


  Conclusion Top


A meta-analysis of studies of predetermined quality revealed that students completing clinical training in rural and underserved areas are significantly more likely to practice in those areas and practice primary care in those areas than their peers. We hope that these findings help medical school administration and policymakers expand medical education programs to rectify the growing physician gap in rural and underserved areas.

Acknowledgements

The authors wish to thank Dr. Mark Ebell MD, MS and Dr. Andreas Handel PhD for their advice and guidance on the statistical analytic methodology and interpretation of study results. The authors would also like to thank Cori Deutsch MMR for her assistance in statistical software coding and image modification.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

 
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    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]
 
 
    Tables

  [Table 1], [Table 2]


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