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Personality in Children With Vocal Fold Nodules: A Multitrait Analysis.

Jeong Min LeeNelson RoyAlbert ParkHarlan MuntzJeremy MeierJonathan SkirkoMarshall Smith
Published in: Journal of speech, language, and hearing research : JSLHR (2021)
Purpose Vocal fold nodules (VNs) are bilateral, symmetrical, callous-like lesions secondary to phonotrauma and possibly related to specific personality traits. This case-control study examined the relation between personality and VNs in children within the context of the Trait Theory of VNs. Method Parents of children with VNs (N = 39, M = 7.43, SD = 2.01 years) and two medical control groups (i.e., voice disordered controls, but not VNs [VDCs; N = 40, M = 7.09, SD = 2.01 years] and vocally normal controls [VNCs; N = 40, M = 7.6, SD = 1.54 years]) completed the Inventory of Child Individual Differences, a personality instrument that describes the Big Five superfactors as well as 15 lower order personality traits. Results Children with VNs, as compared with VNCs, were (a) emotionally reactive (i.e., higher N-Neuroticism, p < .005, Cohen's d = 0.53), (b) Antagonistic, Strong-Willed, and less Compliant (i.e., lower A-Agreeableness, p < .014, Cohen's d = 0.59), and (c) Distractible and Disorganized (i.e., lower C-Conscientiousness, p < .009, Cohen's d = 0.62). Both voice disordered groups displayed elevated scores on the personality superfactor of Neuroticism (N; and the "Negative Emotions" lower order trait). Conclusions The combination of personality traits identified in this study (i.e., high N, low A and C) may play a central role in VNs development and possibly attenuate voice therapy success. Children with VNs displayed a similar personality typology as women with VNs, with the exception of elevated Extraversion (E), thereby providing support for the relevance of the Trait Theory of VNs in both children and adults. Clinicians treating children with voice disorders, including VNs, should consider their underlying personality traits in assessment and management.
Keyphrases
  • young adults
  • healthcare
  • palliative care
  • mental health
  • machine learning
  • mesenchymal stem cells
  • genome wide
  • stem cells
  • gene expression
  • bone marrow
  • replacement therapy