Add wos sample results library

02-data/intermediate/wos_sample/0ea4448f107e22785fa6d720d535489b-liu-shimeng-and-li/info.yaml

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+abstract: 'Although the number of medical workers has increased rapidly, its
+
+  scarcity in rural areas remains a serious problem in China. This study
+
+  aimed to investigate medical students'' stated preferences when choosing
+
+  a job, so as to assist policy makers with designing alternative
+
+  interventions to address the unbalanced distribution of the health
+
+  workforce in China.
+
+  A discrete choice experiment (DCE) was conducted to elicit the job
+
+  preferences of final year medical students. Attributes include work
+
+  location, hospital type, monthly income, bianzhi (which can be loosely
+
+  regarded as state administrative staffing), work environment, Training
+
+  and career development opportunity. This study was carried out during
+
+  April to June 2017 in 4 medical universities in Shandong Province,
+
+  China. Mixed logit models were used to analyze the relative importance
+
+  of job attributes.
+
+  A total of 519 medical students participated in the survey. All 6
+
+  attributes were statistically significant with the expected sign and
+
+  demonstrated the existence of preference heterogeneity. In the main
+
+  effects mixed logit model, working in the city and a superior working
+
+  environment were most strongly associated with job preference. A
+
+  relatively unexpected finding was the relatively lower utility of
+
+  offering bianzhi in job preferences. Subgroup analysis showed that
+
+  females and those who have an urban background were significantly
+
+  willing to pay more for working in the city. The most preferred scenario
+
+  for medical students was to select a better work environment job in a
+
+  tertiary hospital in the city, which could offer 9000 CNY monthly, with
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+  sufficient training and career development opportunities and bianzhi.
+
+  Both monetary and nonmonetary intervention could be considered by policy
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+  makers to attract medical students to work in rural areas in China.
+
+  There exists preference heterogeneity on medical students'' job
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+  preferences, which should also be taken into account in developing more
+
+  effective policy incentive packages.'
+affiliation: 'Li, SP (Corresponding Author), Shandong Univ, Sch Hlth Care Management,
+  44 Wenhua Xi Rd, Jinan 250012, Shandong, Peoples R China.
+
+  Li, SP (Corresponding Author), Shandong Univ, NHC Key Lab Hlth Econ \& Policy Res,
+  44 Wenhua Xi Rd, Jinan 250012, Shandong, Peoples R China.
+
+  Liu, Shimeng; Li, Shunping; Liu, Tongtong, Shandong Univ, Sch Hlth Care Management,
+  44 Wenhua Xi Rd, Jinan 250012, Shandong, Peoples R China.
+
+  Liu, Shimeng; Li, Shunping; Liu, Tongtong, Shandong Univ, NHC Key Lab Hlth Econ
+  \& Policy Res, 44 Wenhua Xi Rd, Jinan 250012, Shandong, Peoples R China.
+
+  Yang, Renyong, Jining Med Univ, Dept Finance, Jining, Peoples R China.
+
+  Chen, Gang, Flinders Univ S Australia, Coll Med \& Publ Hlth, Adelaide, SA, Australia.'
+article-number: e12358
+author: Liu, Shimeng and Li, Shunping and Yang, Renyong and Liu, Tongtong and Chen,
+  Gang
+author-email: lishunping@sdu.edu.cn
+author_list:
+- family: Liu
+  given: Shimeng
+- family: Li
+  given: Shunping
+- family: Yang
+  given: Renyong
+- family: Liu
+  given: Tongtong
+- family: Chen
+  given: Gang
+da: '2023-09-28'
+doi: 10.1097/MD.0000000000012358
+eissn: 1536-5964
+files: []
+issn: 0025-7974
+journal: MEDICINE
+keywords: 'China; discrete choice experiment; inequality; job preference; medical
+
+  students; mixed logit model'
+keywords-plus: HEALTH-CARE; REMOTE AREAS; POLICY
+language: English
+month: SEP
+number: '38'
+number-of-cited-references: '44'
+papis_id: 13b87784df63a3680fbb9c67256b4846
+ref: Liu2018jobpreferences
+times-cited: '8'
+title: Job preferences for medical students in China A discrete choice experiment
+type: Article
+unique-id: WOS:000449338200043
+usage-count-last-180-days: '2'
+usage-count-since-2013: '22'
+volume: '97'
+web-of-science-categories: Medicine, General \& Internal
+year: '2018'