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Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
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Development and Validation of Telehealth Competency Questionnaire-Provider.

Steven Taylor1, Lauren M Little1

  • 1Department of Occupational Therapy, College of Health Sciences, Rush University, Chicago, Illinois, USA.

Telemedicine Journal and E-Health : the Official Journal of the American Telemedicine Association
|February 5, 2024
PubMed
Summary

A new tool, the Telehealth Competency Questionnaire-Provider (TCQ-P), assesses healthcare provider skills in virtual care. This validated 17-item measure evaluates telehealth competency across evaluation, rapport, and troubleshooting domains.

Keywords:
behavioral healthe-healtheducationtelehealthtelemedicine

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Area of Science:

  • Healthcare Education
  • Digital Health
  • Psychometrics

Background:

  • Telehealth utilization is rapidly increasing, necessitating virtual service delivery by healthcare providers.
  • Limited validated measures exist to assess telehealth competency gained through structured training.
  • Assessing provider competency is crucial for ensuring effective and safe virtual healthcare delivery.

Purpose of the Study:

  • To develop and validate the Telehealth Competency Questionnaire-Provider (TCQ-P) to measure healthcare provider competency in telehealth delivery.
  • To provide a reliable tool for assessing the impact of telehealth training programs on provider skills.
  • To establish a psychometrically sound instrument for evaluating essential telehealth competency domains.

Main Methods:

  • The Telehealth Competency Questionnaire-Provider (TCQ-P) was developed through a multistep process, including literature review and expert input.
  • Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were employed using two large datasets (N=701 and N=721) for validation.
  • Model fit was assessed using established indices (CFI, TLI, SRMR, RMSEA) to refine the 17-item, 3-factor structure.

Main Results:

  • The final TCQ-P consists of 17 items, refined through EFA and validated by CFA.
  • Confirmatory factor analysis supported a robust 3-factor model: Evaluation, Rapport, and Troubleshooting.
  • Excellent model fit was achieved (CFI=0.984, TLI=0.978, RMSEA=0.051, SRMR=0.035), indicating strong psychometric properties.

Conclusions:

  • The TCQ-P effectively measures three critical domains of telehealth competency for healthcare providers.
  • This validated instrument is suitable for evaluating telehealth training outcomes and assessing provider readiness for virtual care.
  • The TCQ-P serves as an essential tool for the evolving landscape of digital health education and practice.