The study discusses the prevalence and impact of insomnia, a sleep disorder affecting a significant portion of the population. Insomnia is linked to various health issues, including hypertension, obesity, depression, and reduced quality of life. Cognitive Behavioral Therapy for Insomnia (CBT-I) is recommended as an effective intervention, targeting maladaptive thoughts and behaviors related to sleep. Traditional CBT-I is delivered in a structured manner by licensed clinicians, but there are limitations to its accessibility and long-term efficacy. Internet-based CBT-I is proposed as a more accessible and convenient alternative, potentially overcoming the obstacles associated with traditional delivery methods. The intervention described in the text adopts a digital format, delivering CBT-I remotely with the inclusion of motivational interview techniques to enhance engagement and self-efficacy. Motivational Interviewing (MI) techniques aim to build motivation, rapport, and treatment adherence. MI has been successfully integrated into various treatment interventions, including addiction, psychotherapy, and suicide counselling. The text highlights the research gap in exploring the efficacy and feasibility of internet-based CBT-I, particularly for individuals with mild to moderate insomnia without comorbid disorders. Additionally, there is a lack of research on lay counselling in internet-based CBT-I. Investigating these areas can expand the accessibility and effectiveness of internet-based CBT-I for individuals suffering from insomnia.

This study aims to evaluate the effectiveness and feasibility of remotely delivered cognitive-behavioral therapy for insomnia (CBT-I) combined with motivational interviewing for individuals with mild-moderate insomnia. The efficacy of the treatment will be measured by changes in sleep efficiency, sleep onset latency (SOL), and wake after sleep onset (WASO) using sleep diaries, as well as improvements in sleep quality and insomnia symptoms measured by the Insomnia Severity Index (ISI) and Sleep Condition Indicator (SCI). The feasibility aspect of the study will explore participants\&#39; experiences and perceptions before and after the treatment, determine dropout rates and reasons for dropouts, and examine the frequency of incomplete sleep diary entries and the underlying reasons. The research questions to be answered include whether internet-based CBT-I can effectively improve sleep quality and reduce insomnia symptoms, improve sleep efficiency, SOL, and WASO, and whether remote CBT-I is feasible in terms of participant dropout rates and financial feasibility compared to traditional CBT-I interventions.

The British Association of Psychopharmacology (BAP) has updated guidelines for the treatment of insomnia in different settings, focusing on insomnia without comorbidity, or with mild depressive or anxiety symptoms. This paper aims to provide support for mild-moderate insomnia disorders. Comorbid insomnia and chronic insomnia disorders are better treated with a combination of cognitive behavioral therapy for insomnia (CBT-I) and pharmacological treatments. The inclusion criteria for the study include adults aged 18-64 with mild or no depression and mild anxiety symptoms, as measured by the PHQ-9 and GAD-7 questionnaires. Participants should also have self-reported difficulties initiating or maintaining sleep that align with the DSM-5 insomnia criteria. Exclusion criteria include severe or chronic insomnia, major psychiatric or neurological disorders, cognitive impairments, and current use of CBT-I or medication for insomnia. The initial screening process involves online self-report questionnaires (PHQ-9 \&amp; GAD-7) to identify potential participants. The PHQ-9 is used to assess depression symptoms, while the GAD-7 is used to screen for anxiety disorders. A score of 10 or higher on the PHQ-9 indicates probable depression, and a score of 8 or higher on the GAD-7 indicates probable anxiety disorder. The study will be conducted online, and participants will be recruited through the non-profit organization Overcome in the United Kingdom. Recruitment will involve advertisements on the Overcome website and social media, and interested individuals will complete the initial screening questionnaires via email. Eligible participants will be allocated either to the Intervention Group or Waitlist Control Group. The Intervention Group will receive information about their CBT-I coach and access to a sleep diary.

The study will focus on individuals with mild to moderate insomnia symptoms, as measured by the Insomnia Severity Index (ISI) score. Participants should not exhibit significant signs of clinical depression or anxiety. The CBT-I intervention will be delivered remotely via video conferencing, guided by trained coaches. The study will be conducted online, including participant recruitment, screening, informed consent, assessments, and group allocation. Outcome measures will be assessed online at baseline and one week after the intervention. A subset of participants will be invited to participate in qualitative process evaluation interviews. Participants will be recruited through an online registration process, and randomisation will be conducted to ensure a balanced distribution. The intervention will be delivered by a team of trained coaches, supervised by an experienced coach specialising in CBT-I. Data collection will occur at baseline and post-intervention.

The text discusses the analysis plan for a pilot study, focusing on descriptive analysis rather than hypothesis testing due to the absence of formal power calculations. The goal is to provide a detailed account of the collected data. The plan includes assessing data saturation, member checking, and triangulation to enhance the qualitative findings. The research team will maintain comprehensive records of screening, enrollment, completion of measures, and participation in sessions. Feasibility outcomes will be analysed using frequencies, proportions, means, and standard deviations. Feedback will be thematically analysed through audio-recorded interviews. For efficacy analysis, data will be exported to a software, where statistical analysis will be performed.