Improving sleep after stroke: A randomised controlled trial of digital cognitive behavioural therapy for insomnia.

Stroke is frequently accompanied by long-term sleep disruption. We therefore aimed to assess the efficacy of digital cognitive behavioural therapy for insomnia to improve sleep after stroke. A parallel group randomised controlled trial was conducted remotely in participant's homes/online. Randomisation was online with minimisation of between-group differences in age and baseline Sleep Condition Indicator-8 score. In total, 86 community-dwelling stroke survivors consented, of whom 84 completed baseline assessments (39 female, mean 5.5 years post-stroke, mean 59 years old), and were randomised to digital cognitive behavioural therapy or control (sleep hygiene information). Follow-up was at post-intervention (mean 75 days after baseline) and 8 weeks later. The primary outcome was self-reported insomnia symptoms, as per the Sleep Condition Indicator-8 (range 0-32, lower numbers indicate more severe insomnia, reliable change 7 points) at post-intervention. There were significant improvements in Sleep Condition Indicator-8 for digital cognitive behavioural therapy compared with control (intention-to-treat, digital cognitive behavioural therapy n = 48, control n = 36, 5 imputed datasets, effect of group p ≤ 0.02, η p 2 = 0.07-0.12 [medium size effect], pooled mean difference = -3.35). Additionally, secondary outcomes showed shorter self-reported sleep-onset latencies and better mood for the digital cognitive behavioural therapy group, but no significant differences for self-efficacy, quality of life or actigraphy-derived sleep parameters. Cost-effectiveness analysis found that digital cognitive behavioural therapy dominates over control (non-significant cost savings and higher quality-adjusted life years). No related serious adverse events were reported to the researchers. Overall, digital cognitive behavioural therapy for insomnia effectively improves sleep after stroke. Future research is needed to assess earlier stages post-stroke, with a longer follow-up period to determine whether it should be included as part of routine post-stroke care. Clinicaltrials.gov NCT04272892.

Disseminating cognitive behavioural therapy (CBT) for insomnia at scale: capitalising on the potential of digital CBT to deliver clinical guideline care.

Cognitive behavioural therapy (CBT) is the recommended first-line treatment for insomnia. However, guideline care is very seldom available and most patients receive no treatment, or less effective second-line pharmacotherapy or sleep hygiene, neither of which are evidence-based for chronic insomnia. The primary challenge for CBT has been supply. There are not enough therapists to meet the enormous demand. We must accelerate clinician training, but this approach can never be sufficient, even with abbreviated, efficient therapies. Fortunately, however, the treatment landscape has also changed dramatically. Fully-automated digital CBT (dCBT) has emerged as a safe, effective, and scalable treatment delivery format. dCBT is software only, so it can be disseminated as readily and widely as sleep medication. Moreover, dCBT can be integrated into services. Just as medications can be delivered through health professionals and health systems, approved dCBT programmes can be the same. However, an ecosystem of psychologically-based care should not necessitate a medical prescription model. Our proposed stepped care framework, comprises both population health and clinical health service initiatives, enabling universal access to guideline care for insomnia. The diverse ways in which CBT may be delivered (in-person, face-to-face, using telehealth, group therapy, digitally) can operate congruently and efficiently to optimise treatment for people at all levels of complexity and need. With safe and clinically effective dCBT products now set to become established as treatments, clearly differentiated from wellness apps, there is potential to rapidly transform insomnia services and, for the first time, to deliver clinical guideline care at international scale.

Insomnia disorder: State of the science and challenges for the future.

Insomnia disorder comprises symptoms during night and day that strongly affect quality of life and wellbeing. Prolonged sleep latency, difficulties to maintain sleep and early morning wakening characterize sleep complaints, whereas fatigue, reduced attention, impaired cognitive functioning, irritability, anxiety and low mood are key daytime impairments. Insomnia disorder is well acknowledged in all relevant diagnostic systems: Diagnostic and Statistical Manual of the American Psychiatric Association, 5th revision, International Classification of Sleep Disorders, 3rd version, and International Classification of Diseases, 11th revision. Insomnia disorder as a chronic condition is frequent (up to 10% of the adult population, with a preponderance of females), and signifies an important and independent risk factor for physical and, especially, mental health. Insomnia disorder diagnosis primarily rests on self-report. Objective measures like actigraphy or polysomnography are not (yet) part of the routine diagnostic canon, but play an important role in research. Disease concepts of insomnia range from cognitive-behavioural models to (epi-) genetics and psychoneurobiological approaches. The latter is derived from knowledge about basic sleep-wake regulation and encompass theories like rapid eye movement sleep instability/restless rapid eye movement sleep. Cognitive-behavioural models of insomnia led to the conceptualization of cognitive-behavioural therapy for insomnia, which is now considered as first-line treatment for insomnia worldwide. Future research strategies will include the combination of experimental paradigms with neuroimaging and may benefit from more attention to dysfunctional overnight alleviation of distress in insomnia. With respect to therapy, cognitive-behavioural therapy for insomnia merits widespread implementation, and digital cognitive-behavioural therapy may assist delivery along treatment guidelines. However, given the still considerable proportion of patients responding insufficiently to cognitive-behavioural therapy for insomnia, fundamental studies are highly necessary to better understand the brain and behavioural mechanisms underlying insomnia. Mediators and moderators of treatment response/non-response and the associated development of tailored and novel interventions also require investigation. Recent studies suggest that treatment of insomnia may prove to add significantly as a preventive strategy to combat the global burden of mental disorders.

A qualitative examination of the usability of a digital cognitive behavioral therapy for insomnia program after stroke.

OBJECTIVE: Sleep is commonly impaired after stroke. Cognitive Behavioral Therapy for Insomnia (CBT-I) is the first-line recommended treatment for sleep difficulty. "Sleepio" is a digital CBT-I program, allowing delivery of this treatment at scale. However, Sleepio has not yet been tested specifically in people with stroke. Before doing so, we wanted to explore the experience of people with stroke using the program, and potential barriers to completion. METHOD: Community dwelling survivors of stroke (n = 11, 41-78 years of age, 6 male) were given access to Sleepio. Participants discussed their experiences with the program during a semi-structured interview, which was analyzed using thematic analysis. RESULTS: We found four common themes: (1) positive and negative experiences impacted engagement with the program, (2) motivation to follow the program was proportional to perceived severity of sleep problem, (3) impractical advice for people with stroke, (4) difficulty operating the program. CONCLUSION: Sleepio can be used by some people at the chronic stage of stroke. However, some barriers to completion were highlighted, and not all suggestions were deemed practical for everyone. We therefore suggest possible adaptations which may make the program more easily usable and engaging for survivors of stroke with varying impairments.

Insomnia as a mediating therapeutic target for depressive symptoms: A sub-analysis of participant data from two large randomized controlled trials of a digital sleep intervention.

Insomnia predicts the onset of depression, commonly co-presents with depression and often persists following depression remission. However, these conditions can be challenging to treat concurrently using depression-specific therapies. Cognitive behavioural therapy for insomnia may be an appropriate treatment to improve both insomnia and depressive symptoms. We examined the effects of a fully-automated digital cognitive behavioural therapy intervention for insomnia (Sleepio) on insomnia and depressive symptoms, and the mediating role of sleep improvement on depressive symptoms in participants from two randomized controlled trials of digital cognitive behavioural therapy for insomnia. We also explored potential moderators of intervention effects. All participants met criteria for probable insomnia disorder and had clinically significant depressive symptomatology (PHQ-9 ≥ 10; n = 3,352). Individuals allocated to treatment in both trials were provided access to digital cognitive behavioural therapy. Digital cognitive behavioural therapy significantly improved insomnia (p < .001; g = 0.76) and depressive symptoms (p < .001; g = 0.48) at post-intervention (weeks 8-10), and increased the odds (OR = 2.9; 95% CI = 2.34, 3.65) of clinically significant improvement in depressive symptoms (PHQ-9 < 10). Improvements in insomnia symptoms at mid-intervention mediated 87% of the effects on depressive symptoms at post-intervention. No variables moderated effectiveness outcomes, suggesting generalizability of these findings. Our results suggest that effects of digital cognitive behavioural therapy for insomnia extend to depressive symptoms in those with clinically significant depressive symptomatology. Insomnia may, therefore, be an important therapeutic target to assist management of depressive symptoms.

Patient-Reported Outcome Measures in Dermatology: A Systematic Review.

By relying on data from existing patient-reported outcome measures of quality of life, the true impact of skin conditions on patients' lives may be underestimated. This study systematically reviewed all dermatology-specific (used across skin conditions) patient-reported outcome measures and makes evidence-based recommendations for their use. The study protocol is registered on PROSPERO (CRD42018108829). PubMed, PsycInfo and CINAHL were searched from inception to 25 June 2018. The Consensus-based Standards for the Selection of Health Measurement Instruments (COSMIN) criteria were used to assess the measurement properties and methodological quality of studies. A total of 12,925 abstracts were identified. Zero patient-reported outcome measures were assigned to category A (ready for use without further validation), 31 to category B (recommended for use, but only with further validation) and 5 to category C (not recommended for use). There is no gold-standard dermatology-specific patient-reported outcome measure that can be recommended or used without caution. A new measure that can comprehensively capture the impact of dermatological conditions on the patient's life is needed.

Long-term benefits of digital cognitive behavioural therapy for insomnia: Follow-up report from a randomized clinical trial.

Digital cognitive behavioural therapy (dCBT) is an effective treatment for chronic insomnia and also improves well-being and quality of life (QoL). We assessed whether these benefits are sustained and if the effects of dCBT extend to the use of sleep medication and healthcare. In total 1,711 adults (48.0 ± 13.8 years, 77.6% female) with complaints of chronic insomnia participated in a previously published randomized controlled trial (ISRCTN 60530898) comparing dCBT (n = 853) with sleep hygiene education (SHE, n = 858). At weeks 0, 4, 8, 24, 36 and 48, we assessed functional health (Patient-Reported Outcomes Measurement Information System: Global Health Scale); psychological well-being (Warwick-Edinburgh Mental Well-being Scale) and sleep-related QoL (Glasgow Sleep Impact Index), prescribed and non-prescribed sleep medication use, and healthcare utilization. At week 25, those who received SHE at baseline were offered dCBT. dCBT improved functional health (difference: 2.45, 95% confidence interval [CI]: 2.03; 2.88, Cohen's d: 0.50, p < .001), psychological well-being (difference: 4.34, 95% CI: 3.70; 4.98, Cohen's d: 0.55, p < .001) and sleep-related QoL (difference: -44.61, 95%CI: -47.17; -42.05, Cohen's d: -1.44, p < .001) at week 48 compared to baseline. At week 24 dCBT, compared to SHE, also reduced use of prescription and non-prescription sleep medication up to week 24 (adjusted rate ratio [RR]: 0.64, 95% CI: 0.42; 0.97, p = .037 and adjusted RR: 0.52, 95% CI: 0.37; 0.74, p < .0001, respectively), but not healthcare utilization. Uncontrolled follow-up suggests that these effects were sustained for non-prescribed sleep medication (RR: 0.52, 95% CI: 0.40; 0.67, p < .001). In conclusion, this study suggests that dCBT results in sustained benefits to insomnia and its daytime outcomes.

Efficacy of digital cognitive behavioral therapy for moderate-to-severe symptoms of generalized anxiety disorder: A randomized controlled trial.

BACKGROUND: Cognitive behavioral therapy (CBT) is an efficacious intervention for generalized anxiety disorder (GAD). Digital CBT may provide a scalable means of delivering CBT at a population level. We investigated the efficacy of a novel digital CBT program in those with GAD for outcomes of anxiety, worry, depressive symptoms, sleep difficulty, wellbeing, and participant-specific quality of life. METHODS: This online, two-arm parallel-group superiority randomized controlled trial compared digital CBT with waitlist control in 256 participants with moderate-to-severe symptoms of GAD. Digital CBT (Daylight), was delivered using participants' own smartphones. Online assessments took place at baseline (Week 0; immediately preceding randomization), mid-intervention (Week 3; from randomization), post-intervention (Week 6; primary endpoint), and follow-up (Week 10). RESULTS: Overall, 256 participants were randomized and intention-to-treat analysis found Daylight reduced symptoms of anxiety compared with waitlist control at post-intervention, reflecting a large effect size (adjusted difference [95% CI]: 3.22 [2.14, 4.31], d = 1.08). Significant improvements were found for measures of worry; depressive symptoms, sleep difficulty, wellbeing, and participant-specific quality of life. CONCLUSION: Digital CBT (Daylight) appears to be safe and efficacious for symptoms of anxiety, worry, and further measures of mental health compared with waitlist control in individuals with GAD.

The Sleepio After Cancer (SAC) study. Digital cognitive behavioural therapy for insomnia (dCBT-I) in women cancer patients - Trial protocol of a randomised controlled trial.

AIMS: This study will assess the efficacy of digital CBT for insomnia (dCBT-I) compared to sleep hygiene education (SHE) for the management of insomnia in women with cancer. BACKGROUND: 30% of patients with cancer meet insomnia diagnostic criteria and this can be detrimental to health outcomes. Insomnia disorder comprises a dissatisfaction with sleep quantity or quality characterized by difficulty initiating sleep, frequent awakenings, or early morning wakening without the ability to return to sleep, at least 3 nights per week, for at least 3 months, causing significant impairment or distress in areas of functioning. METHODS: We will recruit 308 women with a current or prior cancer diagnosis who are currently experiencing insomnia; defined as a score of 16 or less on the Sleep Condition Indicator (SCI). Participants will be randomised to dCBT-I or SHE. dCBT-I will be delivered online via 6 sessions. SHE will be provided in an online format. Assessments of sleep and other related parameters, through validated questionnaires, will be taken at 12 and 24 weeks following intervention. Once 24 week assessments are completed, participants will crossover to the alternate arm (either SHE or dCBT-I) and undergo a final assessment at week 36. OUTCOMES: The primary outcome will be the mean continuous change in SCI score in the intervention arm compared to the control arm at 24 weeks. Additionally, the proportion of women with an SCI > 16 at 24 weeks will be assessed. Secondary outcomes include fatigue, sleep related quality of life, depression, anxiety, and hot flush interference. REGISTRATION: This study is registered on ClinicalTrials.gov with number NCT05816460.

Multimodal, Technology-Assisted Intervention for the Management of Menopause after Cancer Improves Cancer-Related Quality of Life-Results from the Menopause after Cancer (Mac) Study.

BACKGROUND: Vasomotor symptoms (VMSs) associated with menopause represent a significant challenge for many patients after cancer treatment, particularly if conventional menopausal hormone therapy (MHT) is contraindicated. METHODS: The Menopause after Cancer (MAC) Study (NCT04766229) was a single-arm phase II trial examining the impact of a composite intervention consisting of (1) the use of non-hormonal pharmacotherapy to manage VMS, (2) digital cognitive behavioral therapy for insomnia (dCBT-I) using Sleepio (Big Health), (3) self-management strategies for VMS delivered via the myPatientSpace mobile application and (4) nomination of an additional support person/partner on quality of life (QoL) in women with moderate-to-severe VMS after cancer. The primary outcome was a change in cancer-specific global QoL assessed by the EORTC QLC C-30 v3 at 6 months. Secondary outcomes included the frequency of VMS, the bother/interference of VMS and insomnia symptoms. RESULTS: In total, 204 women (82% previous breast cancer) with a median age of 49 years (range 28-66) were recruited. A total of 120 women completed the protocol. Global QoL scores increased from 62.2 (95%CI 58.6-65.4) to 70.4 (95%CI 67.1-73.8) at 6 months (p < 0.001) in the intention to treatment (ITT) cohort (n = 204) and from 62 (95%CI 58.6-65.4) to 70.4 (95%CI 67.1-73.8) at 6 months (p < 0.001) in the per-protocol (PP) cohort (n = 120). At least 50% reductions were noticed in the frequency of VMS as well as the degree of bother/interference of VMS at six months. The prevalence of insomnia reduced from 93.1% at the baseline to 45.2% at 6 months (p < 0.001). The Sleep Condition Indicator increased from 8.5 (SEM 0.4) to 17.3 (SEM 0.5) (p < 0.0005) in the ITT cohort and 7.9 (SEM 0.4) to 17.3 (SEM 0.5) (p < 0.001) in the PP cohort. CONCLUSIONS: A targeted composite intervention improves the quality of life for cancer patients with frequent and bothersome vasomotor symptoms with additional benefits on frequency, the bother/interference of VMS and insomnia symptoms.

Bridging the gap from medical to psychological safety assessment: consensus study in a digital mental health context.

BACKGROUND: Digital Mental Health Interventions (DMHIs) that meet the definition of a medical device are regulated by the Medicines and Healthcare products Regulatory Agency (MHRA) in the UK. The MHRA uses procedures that were originally developed for pharmaceuticals to assess the safety of DMHIs. There is recognition that this may not be ideal, as is evident by an ongoing consultation for reform led by the MHRA and the National Institute for Health and Care Excellence. AIMS: The aim of this study was to generate an experts' consensus on how the medical regulatory method used for assessing safety could best be adapted for DMHIs. METHOD: An online Delphi study containing three rounds was conducted with an international panel of 20 experts with experience/knowledge in the field of UK digital mental health. RESULTS: Sixty-four items were generated, of which 41 achieved consensus (64%). Consensus emerged around ten recommendations, falling into five main themes: Enhancing the quality of adverse events data in DMHIs; Re-defining serious adverse events for DMHIs; Reassessing short-term symptom deterioration in psychological interventions as a therapeutic risk; Maximising the benefit of the Yellow Card Scheme; and Developing a harmonised approach for assessing the safety of psychological interventions in general. CONCLUSION: The implementation of the recommendations provided by this consensus could improve the assessment of safety of DMHIs, making them more effective in detecting and mitigating risk.

Exploring digital cognitive behavioural therapy for insomnia in an early intervention in psychosis service - A study protocol for an initial feasibility study with process evaluation.

AIM: Early psychosis may be a critical time at which clinical trajectories are still evolving, and sleep interventions hold promise to improve outcomes at this stage. Although cognitive behavioural therapy (CBT) for insomnia shows promise in psychosis, there has been limited evaluation of delivery within current care. This study aims to evaluate the feasibility and acceptability of providing fully-automated digital CBT for insomnia (CBT-I) within an early intervention in psychosis service. METHODS: We will conduct a single-arm feasibility trial within an early psychosis intervention service, and up to 40 individuals experiencing a first episode of psychosis and with evidence of insomnia can be enrolled (May 2021 - August 2022). Additional service user inclusion criteria are capacity to consent and access to a suitable technological device to access digital CBT. Participants will be offered access to a fully-automated digital CBT-I program (Sleepio) delivered using web and/or mobile app. The study comprises pre- and post- intervention questionnaire assessments and interviews with service users and staff to provide initial outcome signals. RESULTS: Quantitative questionnaire data will be analysed descriptively, alongside rates of eligibility, consent, uptake and completion. Qualitative data will be analysed using thematic analysis. Results will be used to develop a logic model describing feasibility and implementation. CONCLUSIONS: From this study, we hope to better understand how to deliver digital CBT for insomnia within an early intervention in psychosis service. This study will help inform further research, including how best to support staff in using Sleepio, and inform the design of subsequent trials in this area.

Insomnia, depression, and anxiety symptoms interact and individually impact functioning: A network and relative importance analysis in the context of insomnia.

STUDY OBJECTIVES: Insomnia, depression, and anxiety show high rates of comorbidity and functional impairment. Transdiagnostic symptom interactions may be implicated in this comorbidity. This network analysis sought to assess how symptoms of insomnia, depression, and anxiety may interact and individually predict impairment across several domains for individuals with insomnia. METHODS: Baseline psychometric data from a randomised controlled trial were analysed (N = 1711). A regularized partial correlation network was estimated from the symptom data. Centrality (symptom connectivity), community structure (symptom clustering), and bridging (inter-community connectivity) were assessed. The replicability of the network model was assessed via confirmatory analyses in a holdout sample. Separately, Shapley values were estimated to determine the relative importance of each symptom in predicting functioning (i.e., psychological wellbeing, psychosocial functioning, and physical health impairment). RESULTS: The most connected nodes were uncontrollable worrying; trouble relaxing; and depressed mood/hopelessness. Five communities were identified with trouble relaxing identified as the bridge symptom between communities. The model showed good fit in the holdout sample. Low energy and depressive affect symptoms (feelings of failure/guilt; depressed mood/hopelessness; anhedonia) were key predictors in the relative importance analysis across multiple domains of impairment. CONCLUSION: Trouble relaxing may be of clinical and transdiagnostic significance in the context of insomnia. In terms of how symptoms relate to functioning, it was clear that, while low energy and feelings of failure/guilt were prominent predictors, a range of symptoms are associated with functional impairment. Consideration of both symptoms and functional impairment across domains may be useful in determining targets for treatment. CLINICAL TRIAL REGISTRATION: This is a secondary analysis of an original clinical trial. TRIAL REGISTRATION NUMBER: ISRCTN60530898. Registry URL: https://www.isrctn.com/ISRCTN60530898.

Does treating insomnia with digital cognitive behavioural therapy (Sleepio) mediate improvements in anxiety for those with insomnia and comorbid anxiety? An analysis using individual participant data from two large randomised controlled trials.

BACKGROUND: Considerable comorbidity exists between insomnia and anxiety, and evidence shows that the benefits of CBT for insomnia extend to anxiety. Using data from two large trials of digital CBT (dCBT) for insomnia, we evaluated whether improving sleep is an effective treatment target to reduce both insomnia and anxiety symptoms in individuals with insomnia and clinically significant anxiety. METHODS: This was a controlled sub-analysis combining individual participant data from two previous randomised controlled trials of dCBT for insomnia (Sleepio). Participants (N = 2172) with insomnia disorder and clinically significant anxiety symptoms were included in this sub-analysis and received either dCBT or control (usual care or sleep hygiene education). Assessments were evaluated at baseline, post-intervention (week 8 or 10), and follow-up (week 22 or 24). Mediation was evaluated using structural equation models. RESULTS: dCBT for insomnia was superior to control at reducing both insomnia (Hedges' g range = 0.77-0.81; both p < 0.001) and anxiety symptoms (Hedges' g range = 0.39-0.44; both p < 0.001) at all time points. Baseline insomnia symptoms moderated the effects of dCBT on insomnia, however no variables moderated treatment effects on anxiety. Reductions in anxiety symptoms at follow-up were mediated by improvements in sleep at post-intervention (% mediated = 84 %), suggesting a causal pathway. LIMITATIONS: Participants did not have a formal anxiety disorder diagnosis and so the effects of dCBT for insomnia on anxiety may differ by anxiety disorder. CONCLUSIONS: Addressing sleep using dCBT for insomnia may serve as a treatment target from which to improve anxiety in individuals with insomnia and clinically significant comorbid anxiety. CLINICAL TRIAL REGISTRATIONS: Digital Insomnia therapy to Assist your Life as well as your Sleep (DIALS) - ISRCTN60530898 http://www.isrctn.com/ISRCTN60530898. Oxford Access for Students Improving Sleep (OASIS) - ISRCTN61272251 http://www.isrctn.com/ISRCTN61272251.

Improving sleep and learning in rehabilitation after stroke, part 2 (INSPIRES2): study protocol for a home-based randomised control trial of digital cognitive behavioural therapy (dCBT) for insomnia.

INTRODUCTION: Consolidation of motor skill learning, a key component of rehabilitation post-stroke, is known to be sleep dependent. However, disrupted sleep is highly prevalent after stroke and is often associated with poor motor recovery and quality of life. Previous research has shown that digital cognitive behavioural therapy (dCBT) for insomnia can be effective at improving sleep quality after stroke. Therefore, the aim of this trial is to evaluate the potential for sleep improvement using a dCBT programme, to improve rehabilitation outcomes after stroke. METHODS AND ANALYSIS: We will conduct a parallel-arm randomised controlled trial of dCBT (Sleepio) versus treatment as usual among individuals following stroke affecting the upper limb. Up to 100 participants will be randomly allocated (2:1) into either the intervention (6-8 week dCBT) or control (continued treatment as usual) group. The primary outcome of the study will be change in insomnia symptoms pre to post intervention compared with treatment as usual. Secondary outcomes include improvement in overnight motor memory consolidation and sleep measures between intervention groups, correlations between changes in sleep behaviour and overnight motor memory consolidation in the dCBT group and changes in symptoms of depression and fatigue between the dCBT and control groups. Analysis of covariance models and correlations will be used to analyse data from the primary and secondary outcomes. ETHICS AND DISSEMINATION: The study has received approval from the National Research Ethics Service (22/EM/0080), Health Research Authority (HRA) and Health and Care Research Wales (HCRW), IRAS ID: 306 291. The results of this trial will be disseminated via presentations at scientific conferences, peer-reviewed publication, public engagement events, stakeholder organisations and other forms of media where appropriate. TRIAL REGISTRATION NUMBER: NCT05511285.

Development of a hybrid sleep and physical activity improvement intervention for adults with osteoarthritis-related pain and sleep disturbance: a focus group study with potential users.

Objective: Suboptimal sleep and physical activity are common among people living with osteoarthritis (OA) and simultaneous improvements in both may have a beneficial impact on pain. This study aimed to gather perspectives of people living with OA on important aspects to incorporate in a hybrid sleep and physical activity improvement intervention for OA pain management. Design: Qualitative study using two rounds of two focus groups. Setting and participants: Focus groups were conducted with adults living with OA-related chronic pain and sleep disturbances. Eighteen people attended focus groups in January 2020 and, of these, 16 attended subsequent focus groups in February 2020. Methods: Discussion at the first round of focus groups informed generation of prototype intervention materials that were shared, discussed and refined at the second round of focus groups. Thematic analysis was used to identify themes and sub-themes from the data. Results: Three themes, each with three sub-themes, were identified: facilitators of engagement with the intervention (sub-themes: motivational language, accountability and education); barriers to engagement (sub-themes: suboptimal interaction with healthcare practitioners, recording behaviour as burdensome/disruptive and uncertainty about technique) and characteristics of a physical activity intervention component (sub-themes: tailored, sustainable and supported). Conclusion: We have identified important aspects to incorporate into the design and delivery of a hybrid sleep and physical activity improvement intervention for OA pain management. Insights will be incorporated into intervention materials and protocols, with feasibility and acceptability assessed in a future study.

Quality-adjusted life years for digital cognitive behavioural therapy for insomnia (Sleepio): a secondary analysis.

BACKGROUND: Insomnia is common, and difficulty with daytime functioning is a core symptom. Studies show cognitive behavioural therapy (CBT) improves functioning, but evidence is needed on its value for money. Quality-adjusted life years (QALYs), capturing length and quality of life, provide a standard metric by which to judge whether a treatment is worth its cost. Studies have found QALY gains with therapist-delivered and therapist-guided CBT, but most have not reached statistical significance. Estimates of QALY gains with fully automated digital CBT (dCBT) for insomnia are lacking. AIM: To assess whether dCBT (Sleepio) for insomnia is associated with gains in QALYs compared with a sleep hygiene education control. DESIGN & SETTING: A secondary analysis of a large effectiveness trial of 1711 participants from the UK, US, and Australia. METHOD: EQ-5D scores, the National Institute for Health and Care Excellence's (NICE's) preferred measure of health-related quality of life (HRQoL), were predicted (mapped) from the 10-item Patient-Reported Outcomes Measurement Information System (PROMIS-10) Global Health scores and used to determine QALYs from baseline to 24 weeks (controlled), and to 48 weeks (uncontrolled). RESULTS: At week 24, QALYs were significantly higher for the dCBT group, with mean QALYs 0.375 and 0.362 in the dCBT and control groups, respectively. The mean difference was 0.014 (95% confidence interval [CI] = 0.008 to 0.019), and this difference was maintained over the 48-week study period (0.026, 95% CI = 0.016 to 0.036). The difference of 0.026 QALYs is equivalent to 9.5 days in perfect health. CONCLUSION: Sleepio is associated with statistically significant gains in QALYs over time compared with control. Findings may be used to power future studies and inform cost-effectiveness analyses of automated dCBT for insomnia scaled to a population level.

Cost-effectiveness of digital cognitive behavioral therapy (Sleepio) for insomnia: a Markov simulation model in the United States.

STUDY OBJECTIVES: To examine the cost-effectiveness and potential net monetary benefit (NMB) of a fully automated digital cognitive behavioral therapy (CBT) intervention for insomnia compared with no insomnia treatment in the United States (US). Similar relative comparisons were made for pharmacotherapy and clinician-delivered CBT (individual and group). METHODS: We simulated a Markov model of 100,000 individuals using parameters calibrated from the literature including direct (treatment) and indirect costs (e.g. insomnia-related healthcare expenditure and lost workplace productivity). Health utility estimates were converted into quality-adjusted life years (QALYs) and one QALY was worth $50,000. Simulated individuals were randomized equally to one of five arms (digital CBT, pharmacotherapy, individual CBT, group CBT, or no insomnia treatment). Sensitivity was assessed by bootstrapping the calibrated parameters. Cost estimates were expressed in 2019 US dollars. RESULTS: Digital CBT was cost beneficial when compared with no insomnia treatment and had a positive NMB of $681.06 (per individual over 6 months). Bootstrap sensitivity analysis demonstrated that the NMB was positive in 94.7% of simulations. Relative to other insomnia treatments, digital CBT was the most cost-effective treatment because it generated the smallest incremental cost-effectiveness ratio (-$3,124.73). CONCLUSIONS: Digital CBT was the most cost-effective insomnia treatment followed by group CBT, pharmacotherapy, and individual CBT. It is financially prudent and beneficial from a societal perspective to utilize automated digital CBT to treat insomnia at a population scale.

Feasibility and efficacy of a digital CBT intervention for symptoms of Generalized Anxiety Disorder: A randomized multiple-baseline study.

BACKGROUND AND OBJECTIVES: Cognitive behavioral therapy (CBT) is a first-line treatment for anxiety, but it is not widely available as clinical guidelines recommend. We examined the feasibility and efficacy of a novel smartphone-based fully automated digital CBT intervention, 'Daylight™', to improve symptoms of Generalized Anxiety Disorder (GAD). METHODS: In this multiple-baseline design, 21 adults (20 F; mean age 43yrs. range 19-65yrs.) with moderate-to-severe symptoms of GAD were randomized to one of three baseline durations (2-, 4-, or 6-weeks) and then received access to digital CBT. Participants completed daily ratings of anxiety and worry, weekly measures of anxiety, depressive symptoms, and sleep, and measures of anxiety, worry, wellbeing, quality of life, CBT skill acquisition, and work performance at initial assessment prior to baseline randomization, post-intervention, and follow-up. RESULTS: Digital CBT was found to be feasible in terms of engagement, satisfaction, and safety. For preliminary efficacy, improvements were detected in daily and weekly outcomes of anxiety for most participants. Despite individual differences, significant improvements occurred with the introduction of digital CBT and not during baseline. Overall, 70% of participants no longer had clinically significant symptoms of GAD, 61% no longer had significant depressive symptoms, and 40% no longer had significant sleep difficulty at post-intervention. LIMITATIONS: The study sample was recruited using the internet and was mostly female, limiting the generalizability of the findings. CONCLUSIONS: Findings support the feasibility and efficacy of Daylight. Further examination in randomized controlled trials is now warranted.