4.6 Article

Acupuncture combined with cognitive-behavioural therapy for insomnia (CBT-I) in patients with insomnia: study protocol for a randomised controlled trial

Journal

BMJ OPEN
Volume 12, Issue 12, Pages -

Publisher

BMJ PUBLISHING GROUP
DOI: 10.1136/bmjopen-2022-063442

Keywords

CLINICAL PHYSIOLOGY; Rehabilitation medicine; COMPLEMENTARY MEDICINE; REHABILITATION MEDICINE

Funding

  1. Key R&D Program of Guangdong Province [2020B1111120001]

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This study aims to evaluate the efficacy and effectiveness of electroacupuncture combined with CBT-I in patients with insomnia, with sleep architecture analyzed using deep learning on PSGs. Participants will be randomized to receive either electroacupuncture combined with CBT-I or sham acupuncture combined with CBT-I and followed up for 4 weeks. The results will be disseminated through peer-reviewed journals.
Introduction Insomnia affects physical and mental health due to the lack of continuous and complete sleep architecture. Polysomnograms (PSGs) are used to record electrical information to perform sleep architecture using deep learning. Although acupuncture combined with cognitive-behavioural therapy for insomnia (CBT-I) could not only improve sleep quality, solve anxiety, depression but also ameliorate poor sleep habits and detrimental cognition. Therefore, this study will focus on the effects of electroacupuncture combined with CBT-I on sleep architecture with deep learning. Methods and analysis This randomised controlled trial will evaluate the efficacy and effectiveness of electroacupuncture combined with CBT-I in patients with insomnia. Participants will be randomised to receive either electroacupuncture combined with CBT-I or sham acupuncture combined with CBT-I and followed up for 4weeks. The primary outcome is sleep quality, which is evaluated by the Pittsburgh Sleep Quality Index. The secondary outcome measures include a measurement of depression severity, anxiety, maladaptive cognitions associated with sleep and adverse events. Sleep architecture will be assessed using deep learning on PSGs. Ethics and dissemination This trial has been approved by the institutional review boards and ethics committees of the First Affiliated Hospital of Sun Yat-sun University (2021763). The results will be disseminated through peer-reviewed journals. The results of this trial will be disseminated through peer-reviewed publications and conference abstracts or posters. Trial registration number CTR2100052502.

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