Trait Emotional Intelligence and Its Correlates in Oman Medical Specialty Board Residents.

Trait Emotional Intelligence and Its Correlates in Oman Medical Specialty Board Residents.

Al Huseini, Salim;Al Alawi, Mohammed;Al Sinawi, Hamed;Al-Balushi, Naser;Jose, Sachin;Al-Adawi, Samir;
journal of graduate medical education 2019 Vol. 11 pp. 134-140
258
al-huseini2019traitjournal

Abstract

As part of the globalization of medical education, residency programs in Oman have adopted competency-based standards by the Accreditation Council for Graduate Medical Education International (ACGME-I). Correctly perceiving the emotions of others and managing one's own emotions are essential to high-quality patient care.We tested the reliability and construct validity of the Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF), and assessed trait Emotional Intelligence (EI) in Oman Medical Specialty Board (OMSB) residents in multiple specialties. We explored for correlations with trainees' sociodemographic background data.We conducted a cross-sectional, observational study between February and August 2017. Participants were OMSB residents. We administered the TEIQue-SF and collected sociodemographic data from participants. Multiple linear regression analysis was conducted to identify independent predictors of trait EI.The present cohort scored high in the trait EI subscale of Well-being, followed by Sociability, Self-control, and Emotionality. Among sociodemographic factors, female gender and high income were significant predictors of TEIQue-SF's Well-being subscale and high income and living in a rented home were significant predictors of the Sociability subscale.This is the first study conducted among medical residents in Oman regarding trait EI and its correlates. Our findings of overall high EI and several socioeconomic predictors echo the literature on the assessment of EI in trainees. The findings add to the evidence of cross-cultural applicability of instruments to measure trait EI, and use assessments of EI in resident selection and education.

Citation

ID: 28056
Ref Key: al-huseini2019traitjournal
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
28056
Unique Identifier:
10.4300/JGME-D-18-00388
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet