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Open Access 01-12-2018 | Research

Using Bayesian methodology to explore the profile of mental health and well-being in 646 mothers of children with 13 rare genetic syndromes in relation to mothers of children with autism

Authors: Dawn Adams, Richard P Hastings, Clair Alston-Knox, Rina Cianfaglione, Kate Eden, David Felce, Gemma Griffith, Jo Moss, Chris Stinton, Chris Oliver

Published in: Orphanet Journal of Rare Diseases | Issue 1/2018

Abstract

Background

It is well documented that mothers of children with intellectual disabilities or autism experience elevated stress, with mental health compromised. However, comparatively little is known about mothers of children with rare genetic syndromes. This study describes mental health and well-being in mothers of children with 13 rare genetic syndromes and contrasts the results with mothers of children with autism.

Methods

Mothers of children with 13 genetic syndromes (n = 646; Angelman, Cornelia de Lange, Down, Fragile-X, Phelan McDermid, Prader-Willi, Rett, Rubenstein Taybi, Smith Magenis, Soto, Tuberous Sclerosis Complex, 1p36 deletion and 8p23 deletion syndromes) and mothers of children with autism (n = 66) completed measures of positive mental health, stress and depression. Using Bayesian methodology, the influence of syndrome, child ability, and mother and child age were explored in relation to each outcome. Bayesian Model Averaging was used to explore maternal depression, positive gain and positive affect, and maternal stress was tested using an ordinal probit regression model.

Results

Different child and mother factors influenced different aspects of mental well-being, and critically, the importance of these factors differed between syndromes. Maternal depression was influenced by child ability in only four syndromes, with the other syndromes reporting elevated or lower levels of maternal depression regardless of child factors. Maternal stress showed a more complex pattern of interaction with child ability, and for some groups, child age. Within positive mental health, mother and child age were more influential than child ability. Some syndromes reported comparable levels of depression (SMS, 1p36, CdLS) and stress (SMS, AS) to mothers of children with autism.

Conclusions

Bayesian methodology was used in a novel manner to explore factors that explain variability in mental health amongst mothers of children with rare genetic disorders. Significant proportions of mothers of children with specific genetic syndromes experienced levels of depression and stress similar to those reported by mothers of children with autism. Identifying such high-risk mothers allows for potential early intervention and the implementation of support structures.

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Title: Using Bayesian methodology to explore the profile of mental health and well-being in 646 mothers of children with 13 rare genetic syndromes in relation to mothers of children with autism
Authors: Dawn Adams
Richard P Hastings
Clair Alston-Knox
Rina Cianfaglione
Kate Eden
David Felce
Gemma Griffith
Jo Moss
Chris Stinton
Chris Oliver
Publication date: 01-12-2018
Publisher: BioMed Central
Published in: Orphanet Journal of Rare Diseases / Issue 1/2018
Electronic ISSN: 1750-1172
DOI: https://doi.org/10.1186/s13023-018-0924-1

ACC 2024 Congress

Springer Medicine

Using Bayesian methodology to explore the profile of mental health and well-being in 646 mothers of children with 13 rare genetic syndromes in relation to mothers of children with autism

Abstract

Background

Methods

Results

Conclusions

ACC 2024 Congress

Springer Medicine

Abstract

Background

Methods

Results

Conclusions

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