Digital Cognitive Behavioral Therapy Research Articles

Integrating digital behavioural therapy for insomnia into primary care: A feasibility mixed-methods study.

Digital cognitive behavioural therapy for insomnia has been developed to increase capacity and scalability for patients with insomnia, but implementation in primary care remains limited. The aim of the trial was to evaluate the implementation of digital insomnia therapy into primary care practice for patients with insomnia. We conducted a single-arm feasibility trial of digital behavioural therapy for insomnia (SleepFix) providing sleep restriction therapy with insomnia patients in primary care. Healthcare professionals (comprising General Practitioners, community pharmacists and nurses) were enrolled into the trial and, when deemed clinically appropriate, prescribed SleepFix to patients with insomnia. The primary outcome was uptake assessed by the number of downloads of SleepFix. Interviews with primary care healthcare professionals explored their attitudes towards implementing/using insomnia digital therapeutics in clinical practice, and patients about their experiences with SleepFix. Insomnia symptoms, mood and sleep quality were measured before and after the trial. This trial was prospectively registered (ACTRN12620000055909). Thirty healthcare professionals and 105 patients were enrolled into the trial. Fourteen healthcare professionals administered at least one insomnia digital therapeutic prescription between November 2021 and March 2022. Fifty patients downloaded and used SleepFix (47.6% uptake). In post-trial interviews, healthcare professionals felt they could incorporate digital sleep health into clinical practice and patients found SleepFix acceptable. There were significant improvements in insomnia symptoms, mood and sleep quality at week 6 (all p < 0.05). This trial shows a real-world implementation of a digital insomnia therapy into primary care that could provide a framework for prescribing digital sleep interventions.

A Systematic Review of Parental Involvement in Digital Cognitive Behavioural Therapy Interventions for Child Anxiety.

Cognitive behavioural therapy (CBT) is an efficacious intervention for child anxiety that has been translated into accessible digital formats, many of which involve parents in treatment. However, the value of parental involvement in treatment is not clearly understood. This systematic review examined characteristics of parental involvement (i.e., format and content of sessions, level of therapist guidance, and parent session compliance) in digital CBT for child anxiety (mean child age ≤ 12years) and their relation to child outcomes (primary disorder remission, clinician-, parent-, and child-rated anxiety, and global functioning). Systematic searches in CINAHL, Embase, ERIC, PsychINFO, PubMed, and Scopus up to 14th August 2023, and citation searching, identified 27 articles (as 23 studies) assessing 14 interventions. Two were parent-only programmes for 3-6-year-old children, with the remaining being parent-child programmes targeting older children. Parents were actively involved as coaches/collaborators, assisting their children with anxiety management and exposure, and less often as co-clients working on their own difficulties. Benefits of treatment were observed across interventions, except for one, psychoeducation-based programme. Higher remission rates were more frequently observed in interventions delivered in controlled settings, those with fewer parent-only sessions, or those incorporating more parent- or therapist-led exposure sessions. Most studies were conducted with affluent samples, limiting generalisability, and several received a high risk of bias rating. Future research should examine parent and family related mechanisms of change and modify interventions for improved adherence, such as restricting the number of modules parents are required to complete and teaching key therapeutic strategies such as exposure early in the programme.

Effectiveness of digital cognitive behavioral therapy for insomnia on professional activity: a systematic review and meta-analysis of randomized controlled trials

Effectiveness of digital cognitive behavioral therapy for insomnia on professional activity: a systematic review and meta-analysis of randomized controlled trials

Enhancing sleep and mood in depressed adolescents: A randomized trial on nurse-led digital cognitive behavioral therapy for insomnia

BackgroundDespite the effectiveness of digital cognitive behavior therapy for insomnia (dCBT-I) in treating comorbid insomnia and depression, its accessibility and high dropout rates among adolescents and young adults remain significant limitations. A potential solution could be nurse-led dCBT-I. This study evaluates the feasibility and efficacy of nurse-led dCBT-I in reducing insomnia symptoms and improving mood in adolescents and young adults with depression. AimsOur objective was to evaluate the feasibility and effectiveness of a nurse-led dCBT-I in reducing insomnia severity among adolescents and young adults with depression. MethodsA parallel-group randomized controlled trial involved 40 adolescents and young adults aged 14 to 24 with major depressive disorder and insomnia. They were assigned to receive either a nurse-led 6-week dCBT-I or usual care. The study evaluated outcomes such as insomnia severity, depression severity, and sleep parameters. Measurements were taken at baseline, immediately after the intervention (6 weeks), and during a follow-up at 18 weeks. ResultsThe intention-to-treat analysis was performed using a generalized linear mixed model (GLMM). Results indicated that, compared to the control group, participants in the intervention group exhibited a significant reduction in insomnia severity at the 18-week follow-up, with a large effect size (Cohen's d = −0.965, p < 0.001). Additionally, the intervention group demonstrated a significant decrease in depression severity both at the end of the intervention (Cohen's d = −0.686, p = 0.001) and at the 18-week follow-up (Cohen's d = −0.508, p = 0.011), indicating a medium effect size. ConclusionsNurse-led dCBT-I is an effective treatment for adolescents and young adults with depression and insomnia.

Digital cognitive-behavioral therapy for substance use: systematic review and meta-analysis of randomized controlled trials.

Background: Prior meta-analyses have evaluated digital interventions for alcohol exclusively and alcohol/tobacco combined. These meta-analyses showed positive outcomes pertaining to alcohol and alcohol/tobacco combined. Yet questions remain pertaining to the effect of digital cognitive-behavioral therapy (CBT) on reducing alcohol and drug use.Objectives: The purpose of the meta-analysis was to determine the mean effect size, relative to control groups, of digital CBT, for posttest reductions in drug and/or alcohol use.Methods: The Preferred Reporting Items for Systematic Reviews and Meta-analyses criteria was used to guide this review and meta-analysis. Electronic databases (APA PsycArticles, Academic Search Complete, APA PsycInfo, CINAHL Complete, ERIC, MEDLINE, Psychology and Behavioral Sciences Collection, Social Sciences Full Text, Social Work Abstracts, SocINDEX), clinicaltrials.gov, reference lists were searched. The protocol was registered in PROSPERO (ID#: CRD42023471492). The CBT interventions included cognitive restructuring.Results: All but one of the effect sizes favored digital CBT (from -0.02 to -1.45). After the removal an outlier, a small, significant, random effects model Hedges' g summary effect of -0.23 (95% confidence interval: -0.32, -0.14, p < .0001) showed a reduction in substance use at the posttest, favoring digital CBT relative to the control group. A variety of control conditions were used; however, the effects sizes had minimal heterogeneity (k = 17, I2 = 5.34, Q = 16.9, p = .39). The funnel plot and Egger regression test intercept (0.01, p = .99) lacked publication bias.Conclusion: The meta-analytic findings suggest digital CBT is an efficacious treatment for reducing alcohol and drug use overall.

Digital cognitive-behavioral therapy for insomnia in patients with multiple sclerosis: A multiple baseline single-case pilot study

Insomnia has an estimated prevalence of over 20 % in patients with multiple sclerosis (MS) and preliminary evidence suggests that treating insomnia through cognitive behavioral therapy for insomnia (CBT-I) can alleviate fatigue and other secondary symptoms in this population. Video-based CBT-I, an emerging remote treatment modality, has shown promise in previous studies for addressing insomnia in various populations, indicating its potential as an efficient treatment approach for individuals with MS. This pilot study aimed to assess the impact of video-based cognitive behavioral therapy for insomnia (VCBT-I) on individuals with comorbid insomnia and multiple sclerosis (MS). Out of the ten participants, six experienced statistically significant reductions in total wake time during the night, while seven demonstrated clinically significant improvements in waking time, and eight achieved insomnia remission based on the Insomnia Severity Index (ISI). These findings align with prior research indicating the effectiveness of CBT-I in addressing sleep disturbances and its promising potential for insomnia in MS. Moreover, improvements in depression symptoms, as measured by the PHQ-9, and reductions in worry, as assessed by the GAD-7, were observed. Although fatigue outcomes varied, suggesting a potential need for optimal sleep duration, participants reported enhanced quality of life and high treatment satisfaction. These results suggest that VCBT-I is a well-tolerated and effective treatment option for individuals with comorbid MS and insomnia, highlighting its potential to alleviate both sleep-related and psychological symptoms.

Digital cognitive behavioral therapy vs education for pain in adults with sickle cell disease

AbstractDespite the significant burden of chronic pain in sickle cell disease (SCD), nonpharmacological approaches to manage pain in SCD are lacking. Behavioral interventions incorporating digital cognitive behavioral therapy (CBT) for pain should be compared with available education efforts. This multisite randomized comparative effectiveness trial aimed to compare a CBT intervention tailored for adults with SCD with a digital pain/SCD educational intervention (“Education”) in terms of improving pain and associated symptoms. Participants were recruited virtually from 7 comprehensive SCD centers and community organizations in the United States. Adults (aged ≥18 years) with SCD-related chronic pain and/or daily opioid use were randomly assigned to CBT or Education. Over 12 weeks, the CBT arm received an app-based intervention for pain management; the Education arm received digital pain/SCD education. Both groups received interactive chatbot lessons plus personalized health coach support. Changes in the pain interference scale (primary outcome) and other patient-reported secondary outcomes, including pain intensity, depression, anxiety, quality of life, and self-efficacy, were assessed over 6 months. Of the 453 participants who completed screening, 359 (79%) were randomly assigned to CBT (n = 181) or Education (n = 178), 332 (92%) were Black African American, and 238 were (66.3%) female. At 6 months, 250 (70%) participants (n = 125 per arm) completed follow-up assessments, 93 (26%) missed their follow-up window, and 16 (4%) withdrew. Engagement with the chatbot content was variable (76% connected, 48% completed ≥1 lesson). However, 80% of participants completed ≥1 session with a health coach via phone, video, or text. The 6-month change in pain interference in the CBT (−2.13; 95% confidence interval [CI], −3.42 to −0.84) and Education (−2.66; 95% CI, −3.97 to −1.36) groups was not significantly different (mean difference, 0.54; 95% CI, −1.30 to 2.37; ∗P = ∗.57). Daily pain intensity ratings did not change for either group. There were no between-arm differences in depression, anxiety, quality of life, or the effect of the intervention on pain and mental health in SCD when combined with health coaching. Variable engagement with digital components and high engagement with health coaching may explain the lack of between-group differences, but these findings also provide insights into delivering digital interventions in racial minority and difficult-to-reach populations. This trial was registered at www.clinicaltrials.gov as #NCT04419168.

An indirect treatment comparison meta-analysis of digital versus face-to-face cognitive behavior therapy for headache

Cognitive behavioral therapy (CBT) is effective for headache disorders. However, it is unclear whether the emerging digital CBT is noninferior to face-to-face CBT. An indirect treatment comparison (ITC) meta-analysis was conducted to assess the relative effects between them using standard mean differences (SMDs). Effective sample size (ESS) and required sample size (RSS) were calculated to demonstrate the robustness of the results. Our study found that digital CBT had a similar effect on headache frequency reduction (SMD, 0.12; 95%CI, −2.45 to 2.63) compared with face-to-face CBT. The ESS had 84 participants, while the RSS had 466 participants to achieve the same power as a non-inferior head-to-head trial. Digital CBT is as effective as face-to-face CBT in preventing headache disorders. Due to the heterogeneity (I2 = 94.5%, τ2 = 1.83) and the fact that most of the included studies were on migraine prevention, further head-to-head trials are warranted.

Digital cognitive behavioural therapy for insomnia versus digital sleep education control in an Australian community-based sample: a randomised controlled trial.

Insomnia is a prevalent condition in Australia that increases the risk of depression and anxiety symptoms. Cognitive behaviour therapy for insomnia (CBT-i) is the recommended 'first line' treatment but is accessed by a minority of people with insomnia. To improve CBT-i access in Australia, we aimed to develop and test a self-guided interactive digital CBT-i program. An online randomised controlled trial was conducted from August 2022 to August 2023 to investigate the effect of digital CBT-i, versus digital sleep education control, on symptoms of insomnia (ISI), depression (PHQ-9), anxiety (GAD-7), fatigue, sleepiness and maladaptive beliefs about sleep at 8-week follow-up. The control group accessed the intervention after the 8-week follow-up. Questionnaires were additionally administered at 16 and 24 weeks. Intent-to-treat mixed models and complete-case chi-squared analyses were used. Participants included 62 adults with insomnia symptoms (age M (SD) = 52.5 (16.3), 82% female, ISI = 18.6 (2.9)). There were no between-group differences in baseline characteristics or missing 8-week data (14.5%). After adjusting for baseline scores, CBT-i was associated with lower insomnia (Diffadj (95% CI) = 7.32 (5.0-9.6), P < 0.001, d = 1.64), depression (3.36 (1.3-5.4), p = 0.002, d = 0.84), fatigue (5.2 (2.5-7.9), P < 0.001, d = 1.00) and maladaptive beliefs about sleep (11.0 (4.1-18.0), P = 0.002, d = 0.82), but not anxiety symptoms at 8 weeks (1.84 (-0.1 to 3.8), p = 0.060, d = 0.50). Compared to control, CBT-i was associated with greater rates of insomnia remission (ISI <8; 0.0%, vs 40.0%, P < 0.001) and response at 8 weeks (ISI reduction ≥6; 7.1% vs 72.0%, P < 0.001). Improvements in insomnia and depression were maintained at 24 weeks in the CBT-i group. This interactive digital CBT-i program resulted in large and sustained improvements in symptoms of insomnia, depression, fatigue and maladaptive beliefs about sleep in Australian adults with insomnia symptoms. Implementation programs are required to increase digital CBT-i access and uptake.

A mixed-method randomised controlled feasibility trial of digital CBT and emotion regulation skills training for employees in the workplace (REST)

Background and aimDigital interventions for depression and anxiety can be as effective as face-to-face therapy. One in six workers experience some form of mental health problems, making the workplace a potential avenue to deliver mental health interventions as part of a stepped care model. This study aimed to assess the acceptability, feasibility, and preliminary efficacy of a digital cognitive behavioural therapy (dCBT) on depression and anxiety for employees in the workplace.MethodsA mixed-methods evaluation of employees allocated to dCBT (n=25), or a waitlist control group (n=27) was used to assess five feasibility objectives related to recruitment of employers and employees, engagement, study procedure and preliminary efficacy of the intervention. Quantitative outcome measures and qualitative interviews at 8 weeks post-randomisation were used. Quantitative outcomes were also assessed within subject at 3-, 6-, and 12-month follow-up. Qualitative data was analysed using thematic and framework analysis in Nvivo, whilst quantitative outcomes were analysed using mixed effect linear models between and within subject in R and SPSS.ResultsThirty-Three businesses agreed to facilitate the delivery of three trials run by the University of Warwick in their workplaces. 52 participants consented into the REST trial. Adherence/usage of participants of the treatment platform was just over 50% across the whole sample. There was a reduction in depression and anxiety symptoms post-intervention and at follow-up timepoints across all participants and over time although there were no statistically significant between group differences. High acceptability and satisfaction of the intervention were reported by participants based on qualitative interview data at post-intervention.ConclusionsResults from this feasibility study suggests that the dCBT programme (REST) was acceptable and shows improvement in depression and anxiety symptoms, albeit not over and above the treatment effects in the control group. Recruitment of participants and engagement with the intervention made the feasibility of the delivery somewhat challenging. With better recruitment promotion and engagement strategies, as well as implementing the learnings from the feasibility trial, a fully powered study can inform the efficacy of the REST intervention.Trial registrationThe study is registered in the BMC Springer Nature ISRCTN registry ISRCTN31161020 (registered on 08/06/2021).

A Digital Cognitive Behavioral Therapy Program for Adults With Alcohol Use Disorder

Cognitive behavioral therapy (CBT) is an evidence-based treatment for alcohol use, yet patient access is limited and may be enhanced through digital therapeutics. To evaluate the efficacy of a digital CBT program (Computer-Based Training for Cognitive Behavioral Therapy [CBT4CBT]) or clinician-delivered CBT compared with standard treatment for reducing alcohol use. A 3-arm randomized clinical trial was conducted at outpatient substance use treatment facilities in Connecticut between February 14, 2017, and December 31, 2021, that included an 8-week treatment period with a 6-month follow-up period. Treatment-seeking adults were included who met criteria for current alcohol use disorder and reported drinking at least 14 (men) or 7 (women) drinks per week in the past month and were sufficiently stable for outpatient treatment. Participants were randomly assigned to 1 of the following groups: (1) treatment as usual (TAU) consisting of weekly group or individual counseling, (2) CBT delivered weekly by trained and fidelity-monitored clinicians, or (3) web-based CBT plus brief weekly clinical monitoring. Rates of alcohol use were measured weekly during the treatment period and at 1-, 3-, and 6-month follow-up using the timeline follow-back method. The primary outcome was the percentage of days abstinent (PDA) from alcohol per month. Intention-to-treat analyses were conducted. Of the 99 randomized participants (mean [SD] age, 45.5 [12.7]), 66 were male (66.7%); 39 identified as Black/African American (39.8%), 19 (19.2%) as Hispanic, and 47 (48.0%) as White. Mean (SD) rates of PDA from baseline to 6-month follow-up were 49.3% (27.8%) to 69.6% (34.4%) for TAU; 53.7% (29.8%) to 70.2% (35.1%) for CBT; and 47.6% (31.8%) to 82.6% (25.3%) for digital CBT. Results of random-effects regression showed a significant increase in PDA during the study period, with those assigned to digital CBT increasing PDA at a faster rate than TAU (t733 = 2.55; P = .01) and CBT (t733 = 3.36; P < .001). However, there was no statistically significant difference between treatment groups during the 8-week treatment period. In this randomized clinical trial, while there was no significant difference between treatment groups during the 8-week treatment period, there was differential change between treatments during the 8-month study period that provides support for the efficacy of this digital CBT program. ClinicalTrials.gov Identifier: NCT02742246.

Cost-effectiveness of automated digital CBT (Daylight) for generalized anxiety disorder: A Markov simulation model in the United States

This study examines the cost-effectiveness and cost-benefit of a fully automated smartphone-delivered digital cognitive behavioral therapy (CBT) intervention for Generalized Anxiety Disorder (GAD). In a simulated Markov model, 100,000 individuals with GAD were studied under one of five (n = 20,000 per arm) treatments (digital CBT [Daylight], individual CBT, group CBT, pharmacotherapy, or no GAD treatment). Model inputs were determined from the literature and included direct treatment costs and disease costs. Net monetary benefit (NMB) determined whether digital CBT is cost-beneficial from both a private payer and societal perspective in the United States in 2020. Digital CBT was found to generate the lowest 12-month total cost ($167.02m) and the second highest number of total quality-adjusted life years (14,711.86). Digital CBT showed a positive NMB relative to each alternative treatment and to no treatment for GAD in both a payer and societal perspective. Relative to no treatment, the average NMB of digital CBT was $1,836.83 from the payer perspective and $4,126.88 from the societal perspective. Digital CBT generates the most value in both a payer and societal perspective, and results were robust to sensitivity analysis with respect to effectiveness, pricing, and attrition parameters.

Digital Cognitive-Behavioral Therapy for Insomnia in Cancer Survivors: Protocol for a Pragmatic Clinical Trial.

Insomnia is one of the most prevalent, persistent, and distressing conditions associated with cancer, affecting almost half of all cancer survivors. Although cognitive-behavioral therapy for insomnia is well established as the gold-standard treatment for insomnia, its accessibility is very limited in routine care. We aim to examine the real-world effectiveness and acceptability of a digital cognitive-behavioral therapy for insomnia for cancer survivors with insomnia symptoms through a randomized controlled trial in Portugal. Our cancer trial will test the effects and acceptability of an accessible internet-delivered self-administered cognitive-behavioral therapy for insomnia digital intervention with clinician support, OncoSleep. This online program includes six interactive, personalized weekly sessions featuring evidence-based techniques targeting psychophysiological hyperarousal and maladaptive conditioning, tailored for cancer survivors. Research study procedures include screening for eligibility in the general population and randomization into one of two arms: the digital CBT-I program or a waitlist control group. Insomnia severity (primary outcome), fatigue, sleep diary outcomes, psychological distress, and quality of life (secondary outcomes) will be assessed at baseline and post-intervention.

Assessing the Short-Term Efficacy of Digital Cognitive Behavioral Therapy for Insomnia With Different Types of Coaching: Randomized Controlled Comparative Trial.

Digital cognitive behavioral therapy for insomnia (dCBTi) is an effective intervention for treating insomnia. The findings regarding its efficacy compared to face-to-face cognitive behavioral therapy for insomnia are inconclusive but suggest that dCBTi might be inferior. The lack of human support and low treatment adherence are believed to be barriers to dCBTi achieving its optimal efficacy. However, there has yet to be a direct comparative trial of dCBTi with different types of coaching support. This study examines whether adding chatbot-based and human coaching would improve the treatment efficacy of, and adherence to, dCBTi. Overall, 129 participants (n=98, 76% women; age: mean 34.09, SD 12.05 y) whose scores on the Insomnia Severity Index [ISI] were greater than 9 were recruited. A randomized controlled comparative trial with 5 arms was conducted: dCBTi with chatbot-based coaching and therapist support (dCBTi-therapist), dCBTi with chatbot-based coaching and research assistant support, dCBTi with chatbot-based coaching only, dCBTi without any coaching, and digital sleep hygiene and self-monitoring control. Participants were blinded to the condition assignment and study hypotheses, and the outcomes were self-assessed using questionnaires administered on the web. The outcomes included measures of insomnia (the ISI and the Sleep Condition Indicator), mood disturbances, fatigue, daytime sleepiness, quality of life, dysfunctional beliefs about sleep, and sleep-related safety behaviors administered at baseline, after treatment, and at 4-week follow-up. Treatment adherence was measured by the completion of video sessions and sleep diaries. An intention-to-treat analysis was conducted. Significant condition-by-time interaction effects showed that dCBTi recipients, regardless of having any coaching, had greater improvements in insomnia measured by the Sleep Condition Indicator (P=.003; d=0.45) but not the ISI (P=.86; d=-0.28), depressive symptoms (P<.001; d=-0.62), anxiety (P=.01; d=-0.40), fatigue (P=.02; d=-0.35), dysfunctional beliefs about sleep (P<.001; d=-0.53), and safety behaviors related to sleep (P=.001; d=-0.50) than those who received digital sleep hygiene and self-monitoring control. The addition of chatbot-based coaching and human support did not improve treatment efficacy. However, adding human support promoted greater reductions in fatigue (P=.03; d=-0.33) and sleep-related safety behaviors (P=.05; d=-0.30) than dCBTi with chatbot-based coaching only at 4-week follow-up. dCBTi-therapist had the highest video and diary completion rates compared to other conditions (video: 16/25, 60% in dCBTi-therapist vs <3/21, <25% in dCBTi without any coaching), indicating greater treatment adherence. Our findings support the efficacy of dCBTi in treating insomnia, reducing thoughts and behaviors that perpetuate insomnia, reducing mood disturbances and fatigue, and improving quality of life. Adding chatbot-based coaching and human support did not significantly improve the efficacy of dCBTi after treatment. However, adding human support had incremental benefits on reducing fatigue and behaviors that could perpetuate insomnia, and hence may improve long-term efficacy. ClinicalTrials.gov NCT05136638; https://www.clinicaltrials.gov/study/NCT05136638.

The Effectiveness of Digital Cognitive Behavioral Therapy in Improving Psychological Symptoms among Patients with Insomnia and Depression

The Effectiveness of Digital Cognitive Behavioral Therapy in Improving Psychological Symptoms among Patients with Insomnia and Depression

Skill enactment and knowledge acquisition among community users of digital mental health interventions: qualitative study with thematic analysis

BackgroundThe acquisition of knowledge and use of skills from digital mental health interventions (DMHIs) are considered important for effectiveness. However, our understanding of user experiences implementing skills learned from these interventions is limited, particularly outside of research trials. This qualitative study aimed to investigate how community users learn and apply knowledge and skills from DMHIs based on cognitive behavioural therapy (CBT) in daily life. The study also examined factors influencing the selection and use of skills and explored perceived changes in mental health resulting from the intervention.MethodsThirteen adults aged 26 to 66 years (10 females) were recruited using social media advertising and participated in semi-structured interviews by telephone or videoconference. All participants were living in Australia and had used a digital CBT program within the past 3 months. Interviews lasted on average 45 min. Transcripts were analysed using theoretical thematic analysis.ResultsParticipants demonstrated high levels of program engagement. Findings were organised into three topics with six major themes. Participants reported that their chosen intervention reinforced existing knowledge and fostered new skills and insights (Topic 1, Theme 1: knowledge consolidation). Most described actively applying skills (Topic 1, Theme 2: active approach to skill enactment), although the extent of learning and range of skills enacted varied across participants. Influences on skill selection included the perceived relevance of intervention strategies to the user’s needs and personal characteristics (Topic 2, Theme 1: relevance of intervention strategies), as well as the perceived or experienced effectiveness of those strategies (Topic 2, Theme 2: perceived and experienced benefit). Challenges to ongoing skill enactment included time scarcity, prioritisation difficulties, and lack of motivation (Topic 2, Theme 3: navigating time constraints and low motivation). Improvements in mental health were generally modest and attributed mainly to participants’ proactive efforts (Topic 3, Theme 1: perceived changes).ConclusionsDMHIs may reinforce existing understanding of psychotherapeutic strategies, offer new knowledge, and encourage the application of skills in everyday life among community users who actively engage with these interventions. Future research should prioritise personalising DMHIs and investigating methods to optimise the acquisition, retention, and sustained application of knowledge and skills.

Digital cognitive behavioral therapy for insomnia for people with comorbid psychological distress: A large scale randomized controlled trial

Study objectivesTo examine if comorbid anxiety and depression symptoms (psychological distress) moderate intervention effect in participants receiving digital Cognitive Behavioral Therapy for Insomnia (dCBT-I) in a large-scale randomized controlled trial (RCT), compared to a patient education (PE) control condition. Further, we investigate if dCBT-I reduced levels of psychological distress for those with insomnia and comorbid psychological distress. Methods1721 participants with insomnia completed online assessments of sleep, fatigue and psychological distress, at baseline and at nine-week follow-up. Primary outcome was Insomnia Severity Index (ISI), and secondary outcomes included self-reported sleep (diary), cognition, fatigue, and psychological distress. Participants with psychological distress (HADS>16) were separated from participants without psychological distress. Linear mixed models in SPSS were conducted to test the effects of the intervention. ResultsAt nine-week follow-up we found no difference in effect of the intervention between those who had comorbid psychological distress vs. those without psychological distress in terms of insomnia severity (p = 0.552) and fatigue (p = 0.744). Both groups had large effect size improvements on insomnia severity (p < 0.001=), small to medium (Cohen d < 0.08) improvements on fatigue (p < 0.01=) and sleep efficiency (p < 0.001), and small improvement on other sleep diary measures, compared to their respective control group. The psychological distress group showed a small, but statistically significant decrease in psychological distress (d = 0.2, p < 0.05) with dCBT-I compared to PE. ConclusiondCBT-I is a viable treatment for Insomnia also for those who have comorbid psychological distress.

Investigating the efficacy of digital cognitive behavioural therapy in comparison to a sleep-monitoring application via integrated diary and actigraphy: A randomised-controlled trial.

Dissemination of digital cognitive behavioural therapy is a promising approach for treating insomnia in the broad population. Current evidence supports the effectiveness of the digital format, but clinical findings are often limited by the choice of control group and lack of in-depth therapeutic measures. This study was designed to investigate the specific effects of digital cognitive behavioural therapy in comparison to a self-monitoring application. Participants meeting criteria for insomnia were randomly allocated (1:1) to 8 weeks of digital cognitive behavioural therapy or 8 weeks of digital sleep monitoring (control application). The primary outcome, insomnia severity, was assessed at baseline, 8- and 16-weeks post-randomisation. Secondary outcomes included the assessment of sleep via application-integrated sleep diaries and actigraphy. Linear-mixed models were fitted to assess between-group differences. Fifty-six participants (48 females, mean age: M = 45.55 ± 13.70 years) were randomised to either digital cognitive behavioural therapy (n = 29) or digital sleep monitoring (n = 27). At 8- and 16-weeks post-randomisation, large treatment effects (d = 0.87-1.08) indicated robust reductions (-3.70 and -2.97, respectively; p ≤ 0.003) in insomnia severity in the digital cognitive behavioural therapy arm, relative to digital sleep monitoring. Treatment effects in favour of digital cognitive behavioural therapy were also found for self-reported and actigraphy-derived sleep continuity variables, indicating that sleep improved throughout the 8-week intervention period. Our study reinforces the role of digital cognitive behavioural therapy in achieving clinical improvements for patients with insomnia, affirming previous findings and supporting the specific effects of cognitive behavioural therapy.

Structural brain changes associated with cocaine use and digital cognitive behavioral therapy in cocaine use disorder treatment

BackgroundFew studies have investigated changes in brain structure and function associated with recovery from cocaine use disorder (CUD), and fewer still have identified brain changes associated with specific CUD treatments, which could inform treatment development and optimization. MethodsIn this longitudinal study, T1-weighted magnetic resonance imaging scans were acquired from 41 methadone-maintained individuals with CUD (15 women) at the beginning of and after 12 weeks of outpatient treatment. As part of a larger randomized controlled trial, these participants were randomly assigned to receive (or not) computer-based training for cognitive behavioral therapy (CBT4CBT), and galantamine (or placebo). ResultsIrrespective of treatment condition, whole-brain voxel-based morphometry analyses revealed a significant decrease in right caudate body, bilateral cerebellum, and right middle temporal gyrus gray matter volume (GMV) at post-treatment relative to the start of treatment. Subsequent region of interest analyses found that greater reductions in right caudate and bilateral cerebellar GMV were associated with higher relative and absolute levels of cocaine use during treatment, respectively. Participants who completed more CBT4CBT modules had a greater reduction in right middle temporal gyrus GMV. ConclusionsThese results extend previous findings regarding changes in caudate and cerebellar GMV as a function of cocaine use and provide the first evidence of a change in brain structure as a function of engagement in digital CBT for addiction. These data suggest a novel potential mechanism underlying how CBT4CBT and CBT more broadly may exert therapeutic effects on substance-use-related behaviors through brain regions implicated in semantic knowledge.

Cerina: cognitive–behavioural therapy-based mobile application for managing GAD symptoms among Ulster University Students in Northern Ireland – a protocol for a pilot feasibility randomised controlled trial

IntroductionUniversity students are one of the most vulnerable populations for anxiety disorders worldwide. In Northern Ireland, anxiety disorders appear to be more common among the university student population due to...