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BACKGROUND: Major depressive disorder (MDD) is highly prevalent and burdensome for individuals and society. While there are psychological interventions able to prevent and treat MDD, uptake remains low. To overcome structural and attitudinal barriers, an indirect approach of using online insomnia interventions seems promising because insomnia is less stigmatized, predicts MDD onset, is often comorbid and can outlast MDD treatment. This individual-participant-data meta-analysis evaluated the potential of the online insomnia intervention GET.ON Recovery as an indirect treatment to reduce depressive symptom severity (DSS) and potential MDD onset across a range of participant characteristics. METHODS: Efficacy on depressive symptom outcomes was evaluated using multilevel regression models controlling for baseline severity. To identify potential effect moderators, clinical, sociodemographic, and work-related variables were investigated using univariable moderation and random-forest methodology before developing a multivariable decision tree. RESULTS: IPD were obtained from four of seven eligible studies (N = 561); concentrating on workers with high work-stress. DSS was significantly lower in the intervention group both at post-assessment (d = -0.71 [95% CI-0.92 to -0.51]) and at follow-up (d = -0.84 [95% CI -1.11 to -0.57]). In the subsample (n = 121) without potential MDD at baseline, there were no significant group differences in onset of potential MDD. Moderation analyses revealed that effects on DSS differed significantly across baseline severity groups with effect sizes between d = -0.48 and -0.87 (post) and d = - 0.66 to -0.99 (follow-up), while no other sociodemographic, clinical, or work-related characteristics were significant moderators. CONCLUSIONS: An online insomnia intervention is a promising approach to effectively reduce DSS in a preventive and treatment setting.
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BACKGROUND: GET.ON (HelloBetter) treatment interventions have been shown to be efficacious in multiple randomized controlled trials. OBJECTIVE: This study evaluated the effectiveness of 2 GET.ON interventions, GET.ON Mood Enhancer and GET.ON Stress, in a national digital mental health service implemented across Germany. METHODS: Following an initial web-based questionnaire, participants were allocated to either intervention based on their baseline symptom severity and personal choice and received a semistandardized guided, feedback-on-demand guided, or self-guided version of the treatment. Uncontrolled routine care data from 851 participants were analyzed using a pretest-posttest design. Half of the participants (461/851, 54.2%) were allocated to the stress intervention (189/461, 41% semistandardized; 240/461, 52% feedback on demand; and 32/461, 6.9% self-guided), and almost all participants in the mood intervention (349/352, 99.2%) received semistandardized guidance. RESULTS: Results on depression-related symptom severity indicated a reduction in reported symptoms, with a large effect size of d=-0.92 (95% CI -1.21 to -0.63). Results on perceived stress and insomnia indicated a reduction in symptom severity, with large effect sizes of d=1.02 (95% CI -1.46 to -0.58) and d=-0.75 (95% CI -1.10 to -0.40), respectively. A small percentage of participants experienced deterioration in depression-related symptoms (11/289, 3.8%), perceived stress (6/296, 2%), and insomnia (5/252, 2%). After completing treatment, 51.9% (150/289) of participants showed a clinically reliable change in depression-related symptoms, whereas 20.4% (59/289) achieved a close to symptom-free status. Similar improvements were observed in perceived stress and insomnia severity. Guidance moderated the effectiveness of and adherence to the interventions in reducing depressive symptom severity. Effect sizes on depression-related symptom severity were d=-1.20 (95% CI -1.45 to -0.93) for the semistandardized group, d=-0.36 (95% CI -0.68 to -0.04) for the feedback-on-demand group, and d=-0.83 (95% CI -1.03 to -0.63) for the self-guided group. Furthermore, 47.6% (405/851) of the participants completed all modules of the intervention. Participant satisfaction was high across all patient groups and both interventions; 89.3% (242/271) of participants would recommend it to a friend in need of similar help. Limitations include the assignment to treatments and guidance formats based on symptom severity. Furthermore, part of the differences in symptom change between groups must be assumed to be due to this baseline difference in the measures. CONCLUSIONS: Future digital health implementation and routine care research should focus on monitoring symptom deterioration and other negative effects, as well as possible predictors of deterioration and the investigation of individual patient trajectories. In conclusion, this study supports the effectiveness of tailored digital mental health services in routine care for depression- and stress-related symptoms in Germany. The results highlight the importance of guidance in delivering internet-based cognitive behavioral therapy interventions and provide further evidence for its potential delivered as web-only solutions for increasing access to and use of psychological treatments.
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Terapia Cognitivo-Comportamental , Distúrbios do Início e da Manutenção do Sono , Humanos , Afeto , Depressão/terapia , Saúde DigitalRESUMO
BACKGROUND: The evidence base for internet-based cognitive behavioral therapy for insomnia (iCBT-I) is firm; however, little is known about iCBT-I's health-economic effects. OBJECTIVE: This study aimed to evaluate the cost-effectiveness and cost-utility of iCBT-I in reducing insomnia among schoolteachers. METHODS: Schoolteachers (N=128) with clinically significant insomnia symptoms and work-related rumination were randomized to guided iCBT-I or a wait list control group, both with unrestricted access to treatment as usual. Health care use, patient and family expenditures, and productivity losses were self-assessed and used for costing from a societal and a public health care perspective. Costs were related to symptom-free status (score <8 on the insomnia severity index) and quality-adjusted life years (QALYs) gained. Sampling error was handled using nonparametric bootstrapping. RESULTS: Statistically significant differences favoring the intervention group were found for both health outcomes (symptom-free status yes or no: ß=.30; 95% CI 0.16-0.43; QALYs: ß=.019, 95% CI 0.01-0.03). From a societal perspective, iCBT-I had a 94% probability of dominating the wait list control for both health outcomes. From a public health care perspective, iCBT-I was more effective but also more expensive than the wait list control, resulting in an incremental cost-effectiveness ratio of 650 per symptom-free individual. In terms of QALYs, the incremental cost-effectiveness ratio was 11,285. At a willingness-to-pay threshold of 20,000 per QALY gained, the intervention's probability of being cost-effective was 89%. CONCLUSIONS: Our trial indicates that iCBT could be considered as a good value-for-money intervention for insomnia. TRIAL REGISTRATION: German Clinical Trial Registry: DRKS00004700; https://tinyurl.com/2nnk57jm. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/1745-6215-14-169.
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Terapia Cognitivo-Comportamental , Distúrbios do Início e da Manutenção do Sono , Análise Custo-Benefício , Humanos , Internet , Saúde Pública , Anos de Vida Ajustados por Qualidade de Vida , Distúrbios do Início e da Manutenção do Sono/terapia , Resultado do TratamentoRESUMO
BACKGROUND: Blurred work-non-work boundaries can have negative effects on mental health, including sleep. OBJECTIVES: In a randomised control trial, we aimed to assess the effectiveness of an online recovery training programme designed to improve symptoms of insomnia in a working population exposed to blurred boundaries. METHODS: 128 participants with severe insomnia symptoms (Insomnia Severity Index ≥15) and working under blurred work and non-work conditions (segmentation supplies <2.25) were randomly assigned to either the recovery intervention or a waitlist control group (WLC). The primary outcome was insomnia severity, assessed at baseline, after 2 months (T2) and 6 months (T3). FINDINGS: A greater reduction in insomnia was observed in the intervention compared with the WLC group at both T2 (d=1.51; 95% CI=1.12 o 1.91) and T3 (d=1.63; 95% CI=1.23 to 2.03]. This was shown by Bayesian analysis of covariance (ANCOVA), whereby the ANCOVA model yielded the highest Bayes factor (BF 10=3.23×e60] and a 99.99% probability. Likewise, frequentist analysis revealed significantly reduced insomnia at both T2 and T3. Beneficial effects were found for secondary outcomes including depression, work-related rumination, and mental detachment from work. Study attrition was 16% at T2 and 44% at T3. CONCLUSIONS: The recovery training was effective in reducing insomnia symptoms, work related and general indicators of mental health in employees exposed to blurred boundaries, both at T2 and T3. CLINICAL IMPLICATIONS: In addition to demonstrating the intervention's effectiveness, this study exemplifies the utilisation of the Bayesian approach in a clinical context and shows its potential to empower recipients of interventional research by offering insights into result probabilities, enabling them to draw informed conclusions. TRIAL REGISTRATION NUMBER: German Clinical Trial Registration (DRKS): DRKS00006223, https://drks.de/search/de/trial/DRKS00006223.