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Video analysis of parent-child interactions in behavioural sleep disorders: development of a scoring algorithm

Video analysis of parent-child interactions in behavioural sleep disorders: development of a scoring algorithm
Video analysis of parent-child interactions in behavioural sleep disorders: development of a scoring algorithm
Introduction: Behavioural sleep disorders, including chronic insomnia (CI), are generally assessed by subjective parent interview. However, evidence suggests that parental report of children’s overnight behaviours is unreliable, perhaps due to recall bias or confusion due to sleep deprivation. Video technology has been used clinically to capture complex behavioural disorders in children during the day. However, there is no standardised means of analysing child and parent behaviour at bedtime or during the night. We aimed to create an algorithm for this purpose.Methods: Child brain tumour survivors (a population previously shown to have a high prevalence of CI) were screened for difficulties initiating and maintaining sleep using sub-scales from the Sleep Disturbance Scale for Children. Those who screened positive (n=3) then completed a detailed parent interview to confirm a clinical diagnosis of CI. One night of home video footage was obtained from initial settling period to morning waking (SOMNOmedics camera). Footage was imported into BORIS© software and a coding system for parent and child behaviour was developed over multiple iterations until agreeable inter-rater reliability (>70%) was achieved between two independent coders.Results: The final coding categories were: 1) Time domains, 2) Physical environment, 3) Child global status, 4) Location, 5) Activity and 6) Physical interaction. This achieved 74% inter-reliability in its last iteration.Discussion: A statistically acceptable behaviour scoring algorithm was achieved. With further development, this tool could be applied clinically to investigate behavioural insomnia and in research to provide more objective outcome measurement.
1664-0640
1-8
Galbraith, Lorna
a12520ee-ecb1-4ede-bca6-85ddb09f38a8
Bull, Kim
751f8b25-29ba-4d4f-96e2-6c339a83a47f
Hill, Catherine
867cd0a0-dabc-4152-b4bf-8e9fbc0edf8d
Galbraith, Lorna
a12520ee-ecb1-4ede-bca6-85ddb09f38a8
Bull, Kim
751f8b25-29ba-4d4f-96e2-6c339a83a47f
Hill, Catherine
867cd0a0-dabc-4152-b4bf-8e9fbc0edf8d

Galbraith, Lorna, Bull, Kim and Hill, Catherine (2019) Video analysis of parent-child interactions in behavioural sleep disorders: development of a scoring algorithm. Frontiers in Psychiatry, 10, 1-8. (doi:10.3389/fpsyt.2019.00861).

Record type: Article

Abstract

Introduction: Behavioural sleep disorders, including chronic insomnia (CI), are generally assessed by subjective parent interview. However, evidence suggests that parental report of children’s overnight behaviours is unreliable, perhaps due to recall bias or confusion due to sleep deprivation. Video technology has been used clinically to capture complex behavioural disorders in children during the day. However, there is no standardised means of analysing child and parent behaviour at bedtime or during the night. We aimed to create an algorithm for this purpose.Methods: Child brain tumour survivors (a population previously shown to have a high prevalence of CI) were screened for difficulties initiating and maintaining sleep using sub-scales from the Sleep Disturbance Scale for Children. Those who screened positive (n=3) then completed a detailed parent interview to confirm a clinical diagnosis of CI. One night of home video footage was obtained from initial settling period to morning waking (SOMNOmedics camera). Footage was imported into BORIS© software and a coding system for parent and child behaviour was developed over multiple iterations until agreeable inter-rater reliability (>70%) was achieved between two independent coders.Results: The final coding categories were: 1) Time domains, 2) Physical environment, 3) Child global status, 4) Location, 5) Activity and 6) Physical interaction. This achieved 74% inter-reliability in its last iteration.Discussion: A statistically acceptable behaviour scoring algorithm was achieved. With further development, this tool could be applied clinically to investigate behavioural insomnia and in research to provide more objective outcome measurement.

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Accepted/In Press date: 1 November 2019
Published date: 22 November 2019

Identifiers

Local EPrints ID: 435403
URI: https://eprints.soton.ac.uk/id/eprint/435403
ISSN: 1664-0640
PURE UUID: c84171ec-7647-4589-b7e2-68415ed5b9e6
ORCID for Kim Bull: ORCID iD orcid.org/0000-0002-5541-4556
ORCID for Catherine Hill: ORCID iD orcid.org/0000-0003-2372-5904

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Date deposited: 05 Nov 2019 17:30
Last modified: 26 Nov 2019 01:55

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Contributors

Author: Lorna Galbraith
Author: Kim Bull ORCID iD
Author: Catherine Hill ORCID iD

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