Challenges and opportunities for telehealth assessment during COVID-19: iT-RES, adapting a remote version of the test for rating emotions in speech

Int J Audiol. 2021 May;60(5):319-321. doi: 10.1080/14992027.2020.1833255. Epub 2020 Oct 16.

Abstract

Objective: COVID-19 social isolation restrictions have accelerated the need to adapt clinical assessment tools to telemedicine. Remote adaptations are of special importance for populations at risk, e.g. older adults and individuals with chronic medical comorbidities. In response to this urgent clinical and scientific need, we describe a remote adaptation of the T-RES (Oron et al. 2020; IJA), designed to assess the complex processing of spoken emotions, based on identification and integration of the semantics and prosody of spoken sentences.

Design: We present iT-RES, an online version of the speech-perception assessment tool, detailing the challenges considered and solution chosen when designing the telehealth tool. We show a preliminary validation of performance against the original lab-based T-RES.

Study sample: A between-participants design, within two groups of 78 young adults (T-RES, n = 39; iT-RES, n = 39).

Results: i-TRES performance closely followed that of T-RES, with no group differences found in the main trends, identification of emotions, selective attention, and integration.

Conclusions: The design of iT-RES mapped the main challenges for remote auditory assessments, and solutions taken to address them. We hope that this will encourage further efforts for telehealth adaptations of clinical services, to meet the needs of special populations and avoid halting scientific research.

Keywords: COVID-19; remote assessment; speech and hearing sciences; telehealth.

Publication types

  • Evaluation Study
  • Letter
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Attention
  • Audiology / methods*
  • Audiometry, Speech / methods*
  • COVID-19*
  • Emotions
  • Female
  • Humans
  • Male
  • Quarantine
  • SARS-CoV-2
  • Semantics
  • Speech Perception
  • Telemedicine / methods*
  • Voice Recognition*
  • Young Adult