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  5. Adapted CBT to Stabilize Sleep on Psychiatric Wards: a Transdiagnostic Treatment Approach

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Article
en
2018

Adapted CBT to Stabilize Sleep on Psychiatric Wards: a Transdiagnostic Treatment Approach

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0 Files

en
2018
Vol 46 (6)
Vol. 46
DOI: 10.1017/s1352465817000789

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Allison G Harvey
Allison G Harvey

University of California, Berkeley

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Bryony Sheaves
Louise Isham
Jonathan Bradley
+6 more

Abstract

Background: Almost all patients admitted at acute crisis to a psychiatric ward experience clinically significant symptoms of insomnia. Ward environments pose challenges to both sleep and the delivery of therapy. Despite this, there is no description of how to adapt cognitive behavioural therapy (CBT) for insomnia to overcome these challenges. Aims: (i) To describe the key insomnia presentations observed in the Oxford Ward Sleep Solution (OWLS) trial and (ii) outline key adaptations aimed to increase accessibility and hence effectiveness of CBT for insomnia for a ward setting. Methods: Trial therapists collaboratively agreed the key insomnia presentations and therapy adaptations based on their individual reflective logs used during the trial. Results: Three key insomnia presentations are outlined. These are used to illustrate the application of 10 CBT for insomnia therapy adaptations. These include use of sleep monitoring watches to engage patients in treatment, stabilizing circadian rhythms, reducing the impact of night-time observations and managing discharge as a sleep challenge. Conclusions : Whilst inpatient wards bring challenges for sleep and therapy delivery, creative adaptations can increase the accessibility of evidence based CBT for insomnia techniques. This therapy has proven popular with patients.

How to cite this publication

Bryony Sheaves, Louise Isham, Jonathan Bradley, Colin A. Espie, Álvaro Barrera, Felicity Waite, Allison G Harvey, Caroline Attard, Daniel Freeman (2018). Adapted CBT to Stabilize Sleep on Psychiatric Wards: a Transdiagnostic Treatment Approach. , 46(6), DOI: https://doi.org/10.1017/s1352465817000789.

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Publication Details

Type

Article

Year

2018

Authors

9

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1017/s1352465817000789

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