Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Background: In order to conduct translational science, scientists must combine domain-specific expertise with knowledge on how to identify and cross translational hurdles, and insights on positioning discoveries for the next translational stage. Expert educators from the Clinical and Translational Science Awards (CTSA) Consortium identified 97 knowledge, skills, and abilities (KSAs) important to include in training programs for translational scientists. To assist educators and trainees to use these KSAs, a conceptual model called "Personalized Pathways" was developed that prioritizes KSAs based on trainee background, research area, or phenotype, and expertise on the research team.
Purpose: To understand how CTSA educators prioritize specific KSAs when developing personalized training plans for different translational phenotypes and to identify areas of similarity and difference across phenotypes.
Methods: A web-based, cross-sectional survey of CTSA educators was done. For a selected phenotype, respondents recommended one of four levels of mastery for each of the 97 KSAs. Results were tabulated by frequency, weighted by importance, and divided into tertiles representing high, middle, and lower priority KSAs. Agreement across phenotypes was compared using Krippendorff's alpha.
Results: Ten KSAs were high training priority for Preclinical, Clinical, and Community-Engaged phenotypes. These address research methods, responsible conduct of research, team building, and communicating research results. Nine KSAs were in the next tertile for priority reflecting KSAs in biostatistics, bioinformatics, regulatory precepts, and translating implications of research findings.
Conclusion: A smaller set of KSAs can be prioritized for training Preclinical-, Clinical-, and Community-Engaged researchers. Future work should explore this approach for other phenotypes.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7159805 | PMC |
http://dx.doi.org/10.1017/cts.2019.445 | DOI Listing |
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