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Efficacy of Face-to-Face Delivered Cognitive Behavioral Therapy in Improving Health Status of Patients With Insomnia: A Meta-Analysis.

ABSTRACT: Background: Face-to-face cognitive behavioral therapy (CBT) is one of the most widely used non-pharmacological treatment approaches for insomnia. The aim of this study is to assess the efficacy of face-to-face delivered CBT on health outcomes and to evaluate the effect of CBT components as subgroup variables to explain the efficacy of face-to-face delivered CBT on health outcomes in adults over 18 years old with insomnia. Methods: Relevant randomized controlled trial studies published in the past 22 years were searched through the electronic databases. The Physiotherapy Evidence Database (PEDro) scale was used to assess the quality of the 31 included studies. The mean difference and standard deviation of outcome variables and subgroup variables were analyzed using random effect model, and the heterogeneity among the articles was assessed with the Q-test and I ². Egger regression analysis was used to assess publication bias. Results: The meta-analysis showed a significant reduction in Insomnia Severity Index [standardized mean difference (SMD) = -2.56, 95% CI -3.81 to -1.30, p < 0.001], Pittsburgh Sleep Quality Index (SMD = -0.96, 95% CI -1.25 to -0.68, p < 0.001), sleep onset latency (SMD = -1.31, 95% CI -2.00 to -0.63, p < 0.001), wakening after sleep onset (SMD = -1.44, 95% CI -2.14 to -0.74, p < 0.001), number of awakenings (SMD = -1.18, 95% CI -2.10 to -0.26, p < 0.05), depression (SMD = -1.14, 95% CI -1.85 to -0.42, p < 0.01), and fatigue (SMD = -2.23, 95% CI -3.87 to -0.58, p < 0.01), and a significant increase in total sleep time (SMD = 0.63, 95% CI 0.28 to 0.98, p < 0.001), sleep efficiency (SMD = 1.61, 95% CI 0.92 to 2.29, p < 0.001), and physical health (SMD = 0.42, 95% CI 0.08 to 0.76, p < 0.05), in the CBT intervention group compared with the control group. There was no significant change in anxiety (SMD = -0.62, 95% CI -1.55 to 0.32, p > 0.05) and mental health (SMD = 1.09, 95% CI -0.59 to 2.77, p > 0.05) in CBT intervention group compared with control group. Group-delivered studies with larger number of intervention sessions and longer duration of single session provided a larger improvement in sleep quality. Conclusion: Face-to-face delivered CBT is effective in increasing total sleep time, sleep efficiency, and physical health, and reducing Insomnia Severity Index scores, Pittsburgh Sleep Quality Index scores, sleep onset latency, wakening after sleep onset, number of awakenings, depression, anxiety, and fatigue in patients with insomnia. Face-to-face delivered CBT is more effective when delivered through a larger number of sessions with longer duration of each session, and when delivered in groups. Face-to-face CBT is recommended to provide treatment to patients with insomnia in clinical settings. Systematic Review Registration: www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020200091, identifier: CRD4202020009.

SUBMITTER: Xu D

PROVIDER: S-EPMC8733003 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundInsomnia is of major public health importance. While cognitive behavioral therapy is beneficial, in-person treatment is often unavailable. We assessed the effectiveness of internet-delivered cognitive behavioral therapy for insomnia.ObjectivesThe primary objectives were to determine whether online cognitive behavioral therapy for insomnia could improve sleep efficiency and reduce the severity of insomnia in adults. Secondary outcomes included sleep quality, total sleep time, time in bed, sleep onset latency, wake time after sleep onset, and number of nocturnal awakenings.Data sourcesWe searched PubMed/MEDLINE, the Cumulative Index to Nursing and Allied Health Literature, PsycInfo, Cochrane Library, Embase, and the Web of Science for randomized trials.MethodsStudies were eligible if they were randomized controlled trials in adults that reported application of cognitive behavioral therapy for insomnia via internet delivery. Mean differences in improvement in sleep measures were calculated using the Hartung-Knapp-Sidik-Jonkman method for random effects meta-analysis.ResultsWe found 15 trials, all utilizing a pretest-posttest randomized control group design. Sleep efficiency was 72% at baseline and improved by 7.2% (95% CI: 5.1%, 9.3%; p<0.001) with internet-delivered cognitive behavioral therapy versus control. Internet-delivered cognitive behavioral therapy resulted in a decrease in the insomnia severity index by 4.3 points (95% CI: -7.1, -1.5; p = 0.017) compared to control. Total sleep time averaged 5.7 hours at baseline and increased by 20 minutes with internet-delivered therapy versus control (95% CI: 9, 31; p = 0.004). The severity of depression decreased by 2.3 points (95% CI: -2.9, -1.7; p = 0.013) in individuals who received internet-delivered cognitive behavioral therapy compared to control. Improvements in sleep efficiency, the insomnia severity index and depression scores with internet-delivered cognitive behavioral therapy were maintained from 4 to 48 weeks after post-treatment assessment. There were no statistically significant differences between sleep efficiency, total sleep time, and insomnia severity index for internet-delivered versus in-person therapy with a trained therapist.ConclusionIn conclusion, internet-delivered cognitive behavioral therapy is effective in improving sleep in adults with insomnia. Efforts should be made to educate the public and expand access to this therapy. Registration Number, Prospero: CRD42015017622.

Project description:BackgroundThis study is one of the first randomized controlled trials investigating cognitive behavioral therapy for insomnia (CBT-I) delivered by a fully automated mobile phone app. Such an app can potentially increase the accessibility of insomnia treatment for the 10% of people who have insomnia.ObjectiveThe objective of our study was to investigate the efficacy of CBT-I delivered via the Sleepcare mobile phone app, compared with a waitlist control group, in a randomized controlled trial.MethodsWe recruited participants in the Netherlands with relatively mild insomnia disorder. After answering an online pretest questionnaire, they were randomly assigned to the app (n=74) or the waitlist condition (n=77). The app packaged a sleep diary, a relaxation exercise, sleep restriction exercise, and sleep hygiene and education. The app was fully automated and adjusted itself to a participant's progress. Program duration was 6 to 7 weeks, after which participants received posttest measurements and a 3-month follow-up. The participants in the waitlist condition received the app after they completed the posttest questionnaire. The measurements consisted of questionnaires and 7-day online diaries. The questionnaires measured insomnia severity, dysfunctional beliefs about sleep, and anxiety and depression symptoms. The diary measured sleep variables such as sleep efficiency. We performed multilevel analyses to study the interaction effects between time and condition.ResultsThe results showed significant interaction effects (P<.01) favoring the app condition on the primary outcome measures of insomnia severity (d=-0.66) and sleep efficiency (d=0.71). Overall, these improvements were also retained in a 3-month follow-up.ConclusionsThis study demonstrated the efficacy of a fully automated mobile phone app in the treatment of relatively mild insomnia. The effects were in the range of what is found for Web-based treatment in general. This supports the applicability of such technical tools in the treatment of insomnia. Future work should examine the generalizability to a more diverse population. Furthermore, the separate components of such an app should be investigated. It remains to be seen how this app can best be integrated into the current health regimens.Trial registrationNetherlands Trial Register: NTR5560; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=5560 (Archived by WebCite at http://www.webcitation.org/6noLaUdJ4).

Project description:BackgroundPatients with chronic pain often experience insomnia symptoms. Pain initiates, maintains, and exacerbates insomnia symptoms, and vice versa, indicating a complex situation with an additional burden for these patients. Hence, the evaluation of insomnia-related interventions for patients with chronic pain is important.ObjectiveThis randomized controlled trial examined the effectiveness of internet-based cognitive behavioral therapy for insomnia (ICBT-i) for reducing insomnia severity and other sleep- and pain-related parameters in patients with chronic pain. Participants were recruited from the Swedish Quality Registry for Pain Rehabilitation.MethodsWe included 54 patients (mean age 49.3, SD 12.3 years) who were randomly assigned to the ICBT-i condition and 24 to an active control condition (applied relaxation). Both treatment conditions were delivered via the internet. The Insomnia Severity Index (ISI), a sleep diary, and a battery of anxiety, depression, and pain-related parameter measurements were assessed at baseline, after treatment, and at a 6-month follow-up (only ISI, anxiety, depression, and pain-related parameters). For the ISI and sleep diary, we also recorded weekly measurements during the 5-week treatment. Negative effects were also monitored and reported.ResultsResults showed a significant immediate interaction effect (time by treatment) on the ISI and other sleep parameters, namely, sleep efficiency, sleep onset latency, early morning awakenings, and wake time after sleep onset. Participants in the applied relaxation group reported no significant immediate improvements, but both groups exhibited a time effect for anxiety and depression at the 6-month follow-up. No significant improvements on pain-related parameters were found. At the 6-month follow-up, both the ICBT-i and applied relaxation groups had similar sleep parameters. For both treatment arms, increased stress was the most frequently reported negative effect.ConclusionsIn patients with chronic pain, brief ICBT-i leads to a more rapid decline in insomnia symptoms than does applied relaxation. As these results are unique, further research is needed to investigate the effect of ICBT-i on a larger sample size of people with chronic pain. Using both treatments might lead to an even better outcome in patients with comorbid insomnia and chronic pain.Trial registrationClinicalTrials.gov NCT03425942; https://clinicaltrials.gov/ct2/show/NCT03425942.

Project description:Study objectivesDigital Cognitive Behavioral Therapy for Insomnia (dCBT-I) has demonstrated efficacy in reducing insomnia severity in self-referred and community samples. It is unknown, however, how dCBT-I compares to individual face-to-face (FtF) CBT-I for individuals referred to clinical secondary services. We undertook a randomized controlled trial to test whether fully automated dCBT-I is non-inferior to individual FtF CBT-I in reducing insomnia severity.MethodsEligible participants were adult patients with a diagnosis of insomnia disorder recruited from a sleep clinic provided via public mental health services in Norway. The Insomnia Severity Index (ISI) was the primary outcome measure. The non-inferiority margin was defined a priori as 2.0 points on the ISI at week 33.ResultsIndividuals were randomized to FtF CBT-I (n = 52) or dCBT-I (n = 49); mean baseline ISI scores were 18.4 (SD 3.7) and 19.4 (SD 4.1), respectively. At week 33, the mean scores were 8.9 (SD 6.0) and 12.3 (SD 6.9), respectively. There was a significant time effect for both interventions (p < 0.001); and the mean difference in ISI at week 33 was -2.8 (95% CI: -4.8 to -0.8; p = 0.007, Cohen's d = 0.7), and -4.6 at week 9 (95% CI -6.6 to -2.7; p < 0.001), Cohen's d = 1.2.ConclusionsAt the primary endpoint at week 33, the 95% CI of the estimated treatment difference included the non-inferiority margin and was wholly to the left of zero. Thus, this result is inconclusive regarding the possible inferiority or non-inferiority of dCBT-I over FtF CBT-I, but dCBT-I performed significantly worse than FtF CBT-I. At week 9, dCBT-I was inferior to FtF CBT-I as the 95% CI was fully outside the non-inferiority margin. These findings highlight the need for more clinical research to clarify the optimal application, dissemination, and implementation of dCBT-I. Clinicaltrials.gov: NCT02044263: Cognitive Behavioral Therapy for Insomnia Delivered by a Therapist or on the Internet: a Randomized Controlled Non-inferiority Trial.

Project description:Introduction Coronavirus Disease 2019 (COVID-19) has made a serious public health threat worldwide. Recent evidence has indicated that COVID-19 patients in convalescence frequently experience insomnia, which reduces their quality of life and causes unknown risks. The positive effect of cognitive behavior on insomnia has been well addressed in previous studies. Given the high infectivity and epidemicity of COVID-19, Internet-delivered intervention may be safer than face-to-face treatment. However, whether Internet-delivered cognitive behavioral therapy can effectively improve the insomnia of COVID-19 patients in convalescence has not been completely determined yet. Therefore, we conducted a meta-analysis and systematic review to evaluate the effects of Internet-delivered cognitive behavioral therapy on insomnia in COVID-19 patients in convalescence, with the aim to confer some guidance for its clinical application. Methods and analysis This systematic review and meta-analysis has been registered in the International Prospective Register of Systematic Reviews (PROSPERO). Two researchers will retrieve the relevant literature on Internet-delivered cognitive behavioral therapy for insomnia in convalescent patients with COVID-19 in PubMed, Web of Science, Embase, MEDLINE, Cochrane Library, Clinical Trials gov, Chinese Biomedical Literature Database (CBM), and Chinese National Knowledge Infrastructure (CNKI) from inception to 11th of December. In addition, we will review the relevant trials and references of the included literature and manually searched the grey literature. The two researchers will independently extracted data and information and evaluated the quality of the included literature. The Review Manager software (version 5.3) and Stata software (version 14.0) will be used for data analysis. The mean difference or the standardized mean difference of 95% CI will be used to calculate continuous variables to synthesize the data. In addition, I2 and Cochrane will be used for heterogeneity assessment. Trial registration PROSPERO registration number CRD42021271278.

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Efficacy of Face-to-Face Delivered Cognitive Behavioral Therapy in Improving Health Status of Patients With Insomnia: A Meta-Analysis.

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