Literature DB >> 19437298

Mood assessment via animated characters: a novel instrument to evaluate feelings in young children with anxiety disorders.

Katharina Manassis1, Sandra Mendlowitz, David Kreindler, Charles Lumsden, Jason Sharpe, Mark D Simon, Nicholas Woolridge, Suneeta Monga, Gili Adler-Nevo.   

Abstract

We evaluated a novel, computerized feelings assessment instrument (MAAC) in 54 children with anxiety disorders and 35 nonanxious children ages 5 to 11. They rated their feelings relative to 16 feeling animations. Ratings of feelings, order of feeling selection, and correlations with standardized anxiety measures were examined. Positive emotions were rated more highly and visited earlier by nonanxious children. Children with anxiety disorders explored fewer emotions. MAAC ratings on several positive emotions showed inverse correlations with state anxiety. Although needing further evaluation, MAAC may facilitate feelings assessment in young children and may distinguish children with anxiety disorders from nonanxious children.

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Year:  2009        PMID: 19437298     DOI: 10.1080/15374410902851655

Source DB:  PubMed          Journal:  J Clin Child Adolesc Psychol        ISSN: 1537-4416


  4 in total

Review 1.  Focusing on the positive: a review of the role of child positive affect in developmental psychopathology.

Authors:  Molly Davis; Cynthia Suveg
Journal:  Clin Child Fam Psychol Rev       Date:  2014-06

2.  Co-design and qualitative validation of animated assessment item content for a child-reported digital distress screener.

Authors:  Kirsty Zieschank; Jamin Day; Michael J Ireland; Sonja March
Journal:  Internet Interv       Date:  2021-03-04

3.  The Interactive Child Distress Screener: Development and Preliminary Feasibility Testing.

Authors:  Sonja March; Jamin Day; Kirsty Zieschank; Michael Ireland
Journal:  JMIR Mhealth Uhealth       Date:  2018-04-19       Impact factor: 4.773

4.  Development and evaluation of the HRSD-D, an image-based digital measure of the Hamilton rating scale for depression.

Authors:  Adi Berko; Avigail Bar-Sella; Hadar Fisher; Michael Sobolev; J P Pollak; Sigal Zilcha-Mano
Journal:  Sci Rep       Date:  2022-08-22       Impact factor: 4.996

  4 in total

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