Please use this identifier to cite or link to this item: https://oxfordhealth-nhs.archive.knowledgearc.net/handle/123456789/513
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dc.contributor.authorCroker, Abigail
dc.contributor.authorDenne, Megan
dc.contributor.authorSmith, Jacqueline
dc.contributor.authorStallard, Paul
dc.date.accessioned2020-07-15T13:54:21Z
dc.date.available2020-07-15T13:54:21Z
dc.date.issued2020-03
dc.identifier.citationBethany Cliffe, Abigail Croker, Megan Denne, Jacqueline Smith, Paul Stallard. Digital Cognitive Behavioral Therapy for Insomnia for Adolescents With Mental Health Problems: Feasibility Open Trial.JMIR Ment Health 2020;7(3):e14842en
dc.identifier.issn1438-8871
dc.identifier.urihttps://oxfordhealth-nhs.archive.knowledgearc.net/handle/123456789/513
dc.description.abstractBackground: Insomnia in adolescents is common, persistent, and associated with poor mental health including anxiety and depression. Insomnia in adolescents attending child mental health services is seldom directly treated, and the effects of digital cognitive behavioral therapy (CBT) for insomnia (CBTi) on the mental health of adolescents with significant mental health problems are unknown. Objective: This open study aimed to assess the feasibility of adding supported Web-based CBT for insomnia to the usual care of young people aged 14 to 17 years attending specialist child and adolescent mental health services (CAMHS). Methods: A total of 39 adolescents with insomnia aged 14 to 17 years attending specialist CAMHS were assessed and offered digital CBTi. The digital intervention was Sleepio, an evidence-based, self-directed, fully automated CBTi that has proven effective in multiple randomized controlled trials with adults. Self-report assessments of sleep (Sleep Condition Indicator [SCI], Insomnia Severity Scale, and Web- or app-based sleep diaries), anxiety (Revised Child Anxiety and Depression Scale [RCADS]), and depression (Mood and Feelings Questionnaire [MFQ]) were completed at baseline and post intervention. Postuse interviews assessed satisfaction with digital CBTi. Results: Average baseline sleep efficiency was very poor (53%), with participants spending an average of 9.6 hours in bed but only 5.1 hours asleep. All participants scored less than 17 on the SCI, with 92% (36/39) participants scoring 15 or greater on the Insomnia Severity Scale, suggesting clinical insomnia. Of the 39 participants, 36 (92%) scored 27 or greater on the MFQ for major depression and 20 (51%) had clinically elevated symptoms of anxiety. The majority of participants (38/49, 78%) were not having any treatment for their insomnia, with the remaining 25% (12/49) receiving medication. Sleepio was acceptable, with 77% (30/39) of the participants activating their account and 54% (21/39) completing the program. Satisfaction was high, with 84% (16/19) of the participants finding Sleepio helpful, 95% (18/19) indicating that they would recommend it to a friend, and 37% (7/19) expressing a definite preference for a digital intervention. Statistically significant pre-post improvements were found in weekly diaries of sleep efficiency (P=.005) and sleep quality (P=.001) and on measures of sleep (SCI: P=.001 and Insomnia Severity Index: P=.001), low mood (MFQ: P=.03), and anxiety (RCADS: P=.005). Conclusions: Our study has a number of methodological limitations, particularly the small sample size, absence of a comparison group and no follow-up assessment. Nonetheless, our findings are encouraging and suggest that digital CBTi for young people with mental health problems might offer an acceptable and an effective way to improve both sleep and mental health.en
dc.description.sponsorshipSupported by Oxford Health NHS FT R&D.
dc.description.urihttps://doi.org/10.2196/14842en
dc.language.isoenen
dc.subjectCognitive Behaviour Therapyen
dc.subjectAdolescents and Young Adultsen
dc.subjectInsomniaen
dc.subjectSleepioen
dc.titleDigital Cognitive Behavioral Therapy for Insomnia for Adolescents With Mental Health Problems: Feasibility Open Trialen
dc.typeArticleen
dc.contributor.disciplineOHFT Research & Development
Appears in Collections:Digital Medicine
R&D-supported publications

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