Distinctive prosodic features of people with autism spectrum disorder: a systematic review and meta-analysis study

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Abstract
In this systematic review, we analyzed and evaluated the findings of studies on prosodic features of vocal productions of people with autism spectrum disorder (ASD) in order to recognize the statistically significant, most confirmed and reliable prosodic differences distinguishing people with ASD from typically developing individuals. Using suitable keywords, three major databases including Web of Science, PubMed and Scopus, were searched. The results for prosodic features such as mean pitch, pitch range and variability, speech rate, intensity and voice duration were extracted from eligible studies. The pooled standard mean difference between ASD and control groups was extracted or calculated. Using I2statistic and Cochrane Q-test, between-study heterogeneity was evaluated. Furthermore, publication bias was assessed using funnel plot and its significance was evaluated using Egger’s and Begg’s tests. Thirty-nine eligible studies were retrieved (including 910 and 850 participants for ASD and control groups, respectively). This systematic review and meta-analysis showed that ASD group members had a significantly larger mean pitch (SMD = − 0.4, 95% CI [− 0.70, − 0.10]), larger pitch range (SMD = − 0.78, 95% CI [− 1.34, − 0.21]), longer voice duration (SMD = − 0.43, 95% CI [− 0.72, − 0.15]), and larger pitch variability (SMD = − 0.46, 95% CI [− 0.84, − 0.08]), compared with typically developing control group. However, no significant differences in pitch standard deviation, voice intensity and speech rate were found between groups. Chronological age of participants and voice elicitation tasks were two sources of between-study heterogeneity. Furthermore, no publication bias was observed during analyses (p > 0.05). Mean pitch, pitch range, pitch variability and voice duration were recognized as the prosodic features reliably distinguishing people with ASD from TD individuals.
Funding Information
  • Vice Chancellor for Research and Technology, Hamadan University of Medical Sciences (140004082979)

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