Reliability of the Alberta Infant Motor Scale (AIMS) When Used via Telehealth for Neurodevelopmentally High-Risk

Serena Davies1, Barbara R Lucas2,3,4,5, Genevieve M Dwyer1

  • 1Physiotherapy Program, School of Health Sciences, Western Sydney University, NSW, Australia.

Insights

The Alberta Infant Motor Scale (AIMS) is a reliable tool for assessing infant motor skills via telehealth. This method is comparable in time to in-person assessments, with good reliability for both novice and expert raters.

Area of Science:

  • Pediatric Medicine
  • Developmental Pediatrics
  • Rehabilitation Sciences

Background:

  • Telehealth has emerged as a viable modality for remote healthcare delivery.
  • Reliable and valid assessment tools are crucial for monitoring infant development, especially for high-risk populations.

Purpose of the Study:

  • To evaluate the reliability of the Alberta Infant Motor Scale (AIMS) when administered through recorded telehealth sessions.
  • To compare the reliability of AIMS assessments conducted by novice versus expert raters via telehealth.

Main Methods:

  • Ten assessors (6 novice, 4 expert) independently rated video recordings of telehealth AIMS assessments for 23 high-risk infants.
  • Inter- and intra-rater reliability for AIMS subscale scores, total scores, and percentile rankings were calculated using intraclass correlation coefficients (ICCs).

Main Results:

  • Excellent inter-rater reliability was observed for AIMS total scores (ICC = 0.92-0.96) and most subscales (prone, supine, sitting: ICC = 0.90-0.96).
  • Novice intra-rater reliability varied (ICC = 0.45-0.94), while expert reliability was excellent (ICC = 0.93-1.00).
  • Telehealth assessment duration was comparable to face-to-face evaluations (mean 14.9 min), with novices utilizing video playback more frequently.

Conclusions:

  • The Alberta Infant Motor Scale (AIMS) demonstrates reliable performance when administered via telehealth consultations.
  • Telehealth assessments using AIMS are comparable in time to traditional face-to-face evaluations.
  • Training and the ability to review recordings contribute to the accuracy of telehealth-based AIMS assessments, even for novice raters.
Abstract

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