↓ Skip to main content

Using medical specialty and selection criteria clusters to study specialty selection by Israeli medical students

Overview of attention for article published in BMC Medical Education, January 2017
Altmetric Badge

Mentioned by

facebook
1 Facebook page

Citations

dimensions_citation
12 Dimensions

Readers on

mendeley
53 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Using medical specialty and selection criteria clusters to study specialty selection by Israeli medical students
Published in
BMC Medical Education, January 2017
DOI 10.1186/s12909-017-0854-y
Pubmed ID
Authors

Yoram G. Weiss, Rachel Yaffa Zisk-Rony, Howard Tandeter, Uriel Elchalal, Alex Avidan, Josh E. Schroeder, Charles Weissman

Abstract

During their final year of medical school, Israeli students must consider which specialty to choose for residency. Based on the vocational counseling literature we presumed that choices are made by selecting from a cluster of related specialties while considering professional and socio-economic issues. Questionnaires distributed to final-year medical students at two Israeli medical schools ascertained inclinations toward various medical specialties and the importance of various selection criteria. Analysis focused on seven specialties where >20% of students reported they had positive inclinations. For each such specialty, the specialty and selection criteria query were compared using unpaired two-tailed Student's t-tests to determine differences between students with positive inclinations toward the specialty with those not so inclined. These data were placed in tables, with the significant differences highlighted to facilitate visual recognition of cluster patterns. Completed questionnaires were obtained from 317 of 455 students. Students often had positive inclinations toward more than one specialty (specialty clusters) associated with a group of selection criteria (selection criteria clusters). For example, interest in internal medicine was clustered with interest in internal medicine subspecialties, cardiology and research. Furthermore, there was a "reciprocal" aspect to some specialty cluster patterns. For example, those interested in internal medicine had little interest in surgical specialties. Selection criteria clusters revealed occupational interests and socio-environmental factors associated with the specialty clusters. For example, family medicine, which clustered with pediatrics and psychiatry, had a sub-cluster of: Bedside specialty with family orientation affording long-term patient care. Another sub-cluster was time for childrearing and family, only daytime work and outpatient care. Clusters also revealed students' perceptions that differed from expected: Cardiology is changing from a cognitive to a procedure-oriented subspecialty, clustering not only with internal medicine and its subspecialties but also with emergency medicine, surgical subspecialties and anesthesiology. The concept that career choice involves selecting from a cluster of related specialties provides information about the specialties students might be considering. Moreover, students are not only looking for individual aspects of a specialty, but for a package including clusters of socio-economic and occupational features. Practically, examining clusters can help in career counseling of medical students and assist residency program directors in marketing their specialties.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 53 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 13%
Student > Master 4 8%
Student > Bachelor 4 8%
Student > Ph. D. Student 3 6%
Student > Doctoral Student 3 6%
Other 14 26%
Unknown 18 34%
Readers by discipline Count As %
Medicine and Dentistry 21 40%
Unspecified 2 4%
Social Sciences 2 4%
Psychology 2 4%
Biochemistry, Genetics and Molecular Biology 1 2%
Other 3 6%
Unknown 22 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 January 2017.
All research outputs
#20,411,380
of 22,961,203 outputs
Outputs from BMC Medical Education
#3,171
of 3,348 outputs
Outputs of similar age
#354,279
of 418,510 outputs
Outputs of similar age from BMC Medical Education
#46
of 49 outputs
Altmetric has tracked 22,961,203 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,348 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 418,510 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 49 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.