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A novel faculty development tool for writing a letter of recommendation

OBJECTIVE: Based on a national survey of program directors we developed a letter of recommendation (LOR) scoring rubric (SR) to assess LORs submitted to a pediatric residency program. The objective was to use the SR to analyze: the consistency of LOR ratings across raters and LOR components that con...

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Autores principales: Saudek, Kris, Treat, Robert, Rogers, Amanda, Hahn, Danita, Lauck, Sara, Saudek, David, Weisgerber, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7743943/
https://www.ncbi.nlm.nih.gov/pubmed/33326489
http://dx.doi.org/10.1371/journal.pone.0244016
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author Saudek, Kris
Treat, Robert
Rogers, Amanda
Hahn, Danita
Lauck, Sara
Saudek, David
Weisgerber, Michael
author_facet Saudek, Kris
Treat, Robert
Rogers, Amanda
Hahn, Danita
Lauck, Sara
Saudek, David
Weisgerber, Michael
author_sort Saudek, Kris
collection PubMed
description OBJECTIVE: Based on a national survey of program directors we developed a letter of recommendation (LOR) scoring rubric (SR) to assess LORs submitted to a pediatric residency program. The objective was to use the SR to analyze: the consistency of LOR ratings across raters and LOR components that contributed to impression of the LOR and candidate. METHODS: We graded 30 LORs submitted to a pediatric residency program that were evenly distributed based on final rank by our program. The SR contained 3 sections (letter features, phrases, and applicant abilities) and 2 questions about the quality of the LOR (LORQ) and impression of the candidate (IC) after reading the LOR on a 5-point Likert scale. Inter-rater reliability was calculated with intraclass correlation coefficients (ICC(2,1)). Pearson (r) correlations and stepwise multivariate linear regression modeling predicted LORQ and IC. Mean scores of phrases, features, and applicant abilities were analyzed with ANOVA and Bonferroni correction. RESULTS: Phrases (ICC(2,1) = 0.82, p<0.001)) and features (ICC(2,1) = 0.60, p<0.001)) were rated consistently, while applicant abilities were not (ICC(2,1) = 0.28, p<0.001)). For features, LORQ (R(2) = 0.75, p<0.001) and IC (R(2) = 0.58, p<0.001) were best predicated by: writing about candidates’ abilities, strength of recommendation, and depth of interaction with the applicant. For abilities, LORQ (R(2) = 0.47, p<0.001) and IC (R(2) = 0.51, p<0.001) were best predicted by: clinical reasoning, leadership, and communication skills (0.2). There were significant differences for phrases and features (p<0.05). CONCLUSIONS: The SR was consistent across raters and correlates with impression of LORQ and IC. This rubric has potential as a faculty development tool for writing LORS.
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spelling pubmed-77439432020-12-31 A novel faculty development tool for writing a letter of recommendation Saudek, Kris Treat, Robert Rogers, Amanda Hahn, Danita Lauck, Sara Saudek, David Weisgerber, Michael PLoS One Research Article OBJECTIVE: Based on a national survey of program directors we developed a letter of recommendation (LOR) scoring rubric (SR) to assess LORs submitted to a pediatric residency program. The objective was to use the SR to analyze: the consistency of LOR ratings across raters and LOR components that contributed to impression of the LOR and candidate. METHODS: We graded 30 LORs submitted to a pediatric residency program that were evenly distributed based on final rank by our program. The SR contained 3 sections (letter features, phrases, and applicant abilities) and 2 questions about the quality of the LOR (LORQ) and impression of the candidate (IC) after reading the LOR on a 5-point Likert scale. Inter-rater reliability was calculated with intraclass correlation coefficients (ICC(2,1)). Pearson (r) correlations and stepwise multivariate linear regression modeling predicted LORQ and IC. Mean scores of phrases, features, and applicant abilities were analyzed with ANOVA and Bonferroni correction. RESULTS: Phrases (ICC(2,1) = 0.82, p<0.001)) and features (ICC(2,1) = 0.60, p<0.001)) were rated consistently, while applicant abilities were not (ICC(2,1) = 0.28, p<0.001)). For features, LORQ (R(2) = 0.75, p<0.001) and IC (R(2) = 0.58, p<0.001) were best predicated by: writing about candidates’ abilities, strength of recommendation, and depth of interaction with the applicant. For abilities, LORQ (R(2) = 0.47, p<0.001) and IC (R(2) = 0.51, p<0.001) were best predicted by: clinical reasoning, leadership, and communication skills (0.2). There were significant differences for phrases and features (p<0.05). CONCLUSIONS: The SR was consistent across raters and correlates with impression of LORQ and IC. This rubric has potential as a faculty development tool for writing LORS. Public Library of Science 2020-12-16 /pmc/articles/PMC7743943/ /pubmed/33326489 http://dx.doi.org/10.1371/journal.pone.0244016 Text en © 2020 Saudek et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Saudek, Kris
Treat, Robert
Rogers, Amanda
Hahn, Danita
Lauck, Sara
Saudek, David
Weisgerber, Michael
A novel faculty development tool for writing a letter of recommendation
title A novel faculty development tool for writing a letter of recommendation
title_full A novel faculty development tool for writing a letter of recommendation
title_fullStr A novel faculty development tool for writing a letter of recommendation
title_full_unstemmed A novel faculty development tool for writing a letter of recommendation
title_short A novel faculty development tool for writing a letter of recommendation
title_sort novel faculty development tool for writing a letter of recommendation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7743943/
https://www.ncbi.nlm.nih.gov/pubmed/33326489
http://dx.doi.org/10.1371/journal.pone.0244016
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