| Literature DB >> 26860992 |
Rei Goto1,2, Hiroaki Kakihara3.
Abstract
BACKGROUND: The shortage of physicians in rural areas and in some specialties is a societal problem in Japan. Expensive tuition in private medical schools limits access to them particularly for students from middle- and low-income families. One way to reduce this barrier and lessen maldistribution is to offer conditional scholarships to private medical schools.Entities:
Mesh:
Year: 2016 PMID: 26860992 PMCID: PMC4748598 DOI: 10.1186/s12960-016-0102-2
Source DB: PubMed Journal: Hum Resour Health ISSN: 1478-4491
Attributes and levels used in DCE
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|---|---|---|
| Average annual tuition after receiving scholarship | 0 | 0 |
| 600 000 yen ($6 000) | 60 | |
| 1 200 000 yen ($12 000) | 120 | |
| 1 800 000 yen ($18 000) | 180 | |
| Location of medical school | Suburban or rural area | 0 |
| Urban area | 1 | |
| Possibility to commute from his/her home | Possible | 0 |
| Impossible | 1 | |
| Postgraduate obligation for local regions | Not present | 0 |
| Present | 1 | |
| Postgraduate obligation for specific specialties | Not present | 0 |
| Present | 1 | |
| The length of postgraduate obligation | 0 (no obligation) | 0 |
| 5 years | 5 | |
| 7 years | 7 | |
| 9 years | 9 |
Figure 1Sample question.
Descriptive statistics of the samples
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| |
|---|---|
| Age | 19.3 ± 2.4 |
| Female | 115 (33.1%) |
| Status of students | |
| High school students | 28 (8.1%) |
| Ronin | 278 (80.1%) |
| Sai-juken | 41 (11.8%) |
| Location of preparatory school | |
| Hokkaido | 25 (7.2%) |
| Tohoku | 20 (5.8%) |
| Kanto | 155 (44.7%) |
| Hokuriku | 27 (7.8%) |
| Chubu | 45 (13.0%) |
| Kinki | 9 (2.6%) |
| Chugoku | 39 (11.2%) |
| Shikoku | 0 (0%) |
| Kyusyu | 27 (7.8%) |
| Founder of high school | |
| National | 20 (5.8%) |
| Local government | 166 (47.8%) |
| Private | 161 (46.4%) |
| Occupation of parent | |
| Public servant | 50 (14.4%) |
| Company executive | 26 (7.5%) |
| Employed | 96 (27.7%) |
| Teacher | 15 (4.3%) |
| Medical practitioner | 47 (13.5%) |
| Hospital physician | 32 (9.2%) |
| Health professional other than physician | 22 (6.3%) |
| Self-employed | 46 (13.3%) |
| Farmer and fishery | 0 (0%) |
| Legal professional | 1 (0.3%) |
| Freelance | 6 (1.7%) |
| Part-time worker | 4 (1.2%) |
| Unemployed | 2 (0.6%) |
| First-choice medical school | |
| National | 242 (69.7%) |
| Local government | 39 (11.2%) |
| Private | 38 (11.0%) |
| Special medical school (Jichi and Sangyo Medical School) | 12 (3.5%) |
The percentage is shown within each category.
Probit estimation results concerning the choice to apply only to public medical schools
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|
| |
|---|---|---|
| Age | 0.041 6 | 0.406 |
| Female dummy | 0.062 4 | 0.709 |
| Status of students | ||
| Ronin ( | 0.254 2 | 0.394 |
| Sai-juken ( | 0.178 7 | 0.714 |
| Occupation of parent | ||
| Public servant ( | 0.675 | 0.016 |
| Company executive ( | −0.126 6 | 0.668 |
| Teacher ( | −0.362 5 | 0.312 |
| Medical practitioner ( | −1.125 5 | 0.000 |
| Hospital physician ( | −0.467 4 | 0.076 |
| Health professional other than physician ( | −0.739 5 | 0.015 |
| Self-employed and others ( | −0.138 3 | 0.567 |
| Part-time worker ( | −0.153 1 | 0.826 |
| Unemployed ( | −1.096 6 | 0.287 |
| Constant | −0.423 5 | 0.641 |
| McFadden’s | 0.117 2 | |
|
| 347 | |
The dependent variable is dichotomous (students applying only to public medical school equal to 1, otherwise equal to 0). “High school student” is the reference variable in “Status of students.” “Employed” is the reference variable in “Occupation of parent.” “Self-employed and others” includes “Self-employed,” “Legal professional,” and “Freelance”.
Estimation results of the DCE
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|---|---|---|---|---|---|---|
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| Average annual tuition | −0.011 | 0.000 | −0.014 | 0.000 | −0.006 | 0.000 |
| Urban location | 0.206 | 0.154 | 0.086 | 0.658 | 0.428 | 0.005 |
| Impossibility of commuting from home | −0.243 | 0.099 | −0.304 | 0.122 | −0.185 | 0.230 |
| Obligation for specific specialties | −0.489 | 0.000 | −0.4 | 0.026 | −0.724 | 0.000 |
| Obligation for rural regions | 0.212 | 0.192 | 0.322 | 0.131 | 0.01 | 0.958 |
| Length of obligation | −0.215 | 0.000 | −0.203 | 0.000 | −0.276 | 0.000 |
| Age | 0.054 | 0.004 | 0.072 | 0.003 | 0.039 | 0.223 |
| Female dummy | 0.101 | 0.297 | 0.042 | 0.726 | 0.238 | 0.180 |
| Physician’s child | −0.17 | 0.109 | −0.381 | 0.018 | 0.043 | 0.784 |
| Constant | 1.59 | 0.000 | 1.538 | 0.004 | 1.667 | 0.013 |
| Log likelihood | −1 535.99 | −962.84 | −531.06 | |||
| McFadden’s | 0.143 | 0.167 | 0.158 | |||
| Number of observations | 2 776 | 1 816 | 960 | |||
Figure 2Tuition and the probability of entering private medical school. Case 1: no obligations. Case 2: strict obligation (9-year agreement to provide service in a specific specialty in a rural region). Note: The change in the probability of entering private medical schools with regard to tuition is estimated. In both cases, DCE variables, except for tuitions and obligations, are fixed at the sample mean.
The number of physicians secured and total amount of scholarship in exchange for predetermined specialties in rural areas
| Duration of obligation | After-scholarship annual tuition ($) | The number of those willing to accept the conditional scholarship | Total annual scholarship ($) | ||
|---|---|---|---|---|---|
| Non-applicants | Applicants | Total | |||
| 9 years | 6 000 | 107 | 32 | 139 | 6 936 100 |
| 12 000 | 63 | 24 | 87 | 3 819 300 | |
| 18 000 | 32 | 18 | 50 | 1 895 000 | |
| 7 years | 6 000 | 128 | 31 | 159 | 7 934 100 |
| 12 000 | 83 | 24 | 107 | 4 697 300 | |
| 18 000 | 45 | 18 | 63 | 2 387 700 | |
| 5 years | 6 000 | 147 | 61 | 208 | 10 379 200 |
| 12 000 | 104 | 51 | 155 | 6 804 500 | |
| 18 000 | 61 | 40 | 101 | 3 827 900 | |
Conditional scholarships are assumed to be provided for 326 students (approx. 10%) from a total of 3263 private medical school enrollments in 2011. Also, the proportion of non-applicants to private medical schools is assumed to be the same with this sample. Thus, 212 students (65%) are non-applicants to private medical schools and 114 (35%) are applicants among all scholarship candidates. The number of those willing to accept scholarships is calculated from the probability of entering private medical schools in the event of scholarships in exchange for 9 years of service in specified specialties in certain rural regions. Each probability is estimated when we change the duration of the obligation and tuition using estimates from the DCE. The probability in specific cases is shown in Figure 2. Total annual scholarships are calculated as the number of those willing to accept them (average annual tuition of private medical schools minus post-scholarship annual tuition).