Importance: Although digital cognitive behavioral therapy for insomnia (dCBT-I) has been studied in many randomized clinical trials and is recommended as a first-line treatment option, few studies have systematically examined its effectiveness, engagement, durability, and adaptability in clinical settings.Objective: To evaluate the clinical effectiveness, engagement, durability, and adaptability of dCBT-I.Design, Setting, and Participants: This retrospective cohort study was conducted using longitudinal data collected via a mobile app named Good Sleep 365 between November 14, 2018, and February 28, 2022. Three therapeutic modes (ie, dCBT-I, medication, and their combination) were compared at month 1, month 3, and month 6 (primary). Inverse probability of treatment weighting (IPTW) using propensity scores was applied to enable homogeneous comparisons between the 3 groups.Exposures: Treatment with dCBT-I, medication therapy, or combination therapy according to prescriptions.Main Outcomes and Measures: The Pittsburgh Sleep Quality Index (PSQI) score and its essential subitems were used as the primary outcomes. Effectiveness on comorbid somnolence, anxiety, depression, and somatic symptoms were used as secondary outcomes. Cohen d effect size, P value, and standardized mean difference (SMD) were used to measure differences in treatment outcomes. Changes in outcomes and response rates (≥3 points change in PSQI score) were also reported.Results: A total of 4052 patients (mean [SD] age, 44.29 [12.01] years; 3028 [74.7%] female participants) were selected for dCBT-I (n = 418), medication (n = 862), and their combination (n = 2772). Compared with the change in PSQI score at 6 months for participants receiving medication alone (from a mean [SD] of 12.85 [3.49] to 8.92 [4.03]), both dCBT-I (from a mean [SD] of 13.51 [3.03] to 7.15 [3.25]; Cohen d, −0.50; 95% CI, −0.62 to −0.38; P < .001; SMD = 0.484) and combination therapy (from a mean [SD] of 12.92 [3.49] to 6.98 [3.43]; Cohen d, 0.50; 95% CI, 0.42 to 0.58; P < .001; SMD = 0.518) were associated with significant reductions; dCBT-I had a comparable effect as combination therapy (Cohen d, 0.05; 95% CI, −0.05 to 0.15; P = .66; SMD = 0.05), but showed unstable durability. Outcomes of dCBT-I improved steadily and rapidly during the first 3 months, and then fluctuated. The response rates with dCBT-I and combination therapy were higher than with medication. Changes in secondary outcomes indicated statistically significant benefits from dCBT-I and combination therapy. The results of subgroup analysis were consistent with the main findings, demonstrating the superiority of dCBT-I vs medication therapy in various subpopulations.Conclusions and Relevance: In this study, clinical evidence suggested that combination therapy was optimal, and dCBT-I was more effective than medication therapy, with long-term benefits for insomnia. Future studies are needed to analyze its clinical effectiveness and reliability in distinct subpopulations.

To observe the effect of soothing-liver and nourishing-heart acupuncture on selective serotonin reuptake inhibitor (SSRIs) treatment effect onset in patients with depressive disorder and related indicators of neuroimmunology. Overall, 126 patients with depressive disorder were randomly divided into a medicine and acupuncture-medicine group using a random number table. Patients were treated for 6 consecutive weeks. The two groups were evaluated by the Montgomery-Asberg Depression Rating Scale (MADRS) and Side Effects Rating Scale (SERS) to assess the effect of the soothing-liver and nourishing-heart acupuncture method on early onset of SSRI treatment effect. Changes in serum 5-hydroxytryptamine (5-HT) and inflammatory cytokines before and after treatment were recorded and compared between the medicine group and the acupuncture-medicine group. The acupuncture-medicine group had significantly lower MADRS scores at weeks 1, 2, 4, and 6 after treatment compared with the medicine group (P < 0.01). The acupuncture group had significantly lower SERS scores at weeks 1, 2, 4, and 6 after treatment compared with the medicine group (P < 0.01). At 6 weeks after treatment, serum 5-HT in the acupuncture-medicine group was significantly higher compared with the medicine group (P < 0.01). Interleukin-6 (IL-6) in the acupuncture-medicine group was significantly lower than that in the medicine group (P < 0.01), whereas there was no significant difference in IL-1β between the groups (P > 0.05). Anti-inflammatory cytokines IL-4 and IL-10 were significantly higher in the acupuncture-medicine group compared with the medicine group (P < 0.01, P < 0.05, respectively). The soothing-liver and nourishing-heart acupuncture method can effectively accelerate the onset of SSRI effects when treating depressive disorder and can significantly reduce the adverse reactions of SSRIs. Moreover, acupuncture can enhance serum 5-HT and regulate the balance of pro-inflammatory cytokines and anti-inflammatory cytokines.

Background: Digital cognitive behavior therapy for insomnia (dCBT-I) is an effective treatment in alleviating insomnia. This study examined the effect of dCBT-I for improving sleep quality in patients with insomnia complaints from a clinical population in a real-world setting. Methods: The study included 6,002 patients aged 18 years and above with primary complaints of dissatisfying sleep from a sleep clinic in a psychiatric hospital from November 2016 to April 2021. Patients were diagnosed with insomnia, anxiety disorders, or anxiety comorbid with insomnia or depression according to ICD-10. A mobile app was developed for self-reported assessment and delivering dCBT-I interventions and treatment prescriptions to participants. The primary outcome was change in global sleep quality measured by the Pittsburgh Sleep Quality Index (PSQI). At 8- and 12-week follow-up, 509 patients were reassessed. Data were analyzed with non-parametric tests for repeated measures. Results: Patients treated with dCBT-I monotherapy were younger, with a more frequent family history of insomnia compared to those with medication monotherapy and those with combined dCBT-I and medication therapy. Improvements of sleep quality from baseline to 8-week follow-up were significant in each treatment type. Compared to 8-week follow-up, PSQI scores at 12-week were significantly decreased in the depression group receiving combined therapy and in the anxiety group treated with dCBT-I monotherapy and with combined therapy. A time-by-treatment interaction was detected in anxiety patients indicating differential reduction in PSQI scores over time between different treatment options. Conclusion: The current findings suggest dCBT-I is a practical and effective approach for lessening insomnia symptoms, especially for patients with anxiety symptoms suggesting with a more extended intervention period (i.e., 12 weeks). Trial registration: Chinese Clinical Trial Registry (ChiCTR1900022699).

This study aims to explore the factors that affect the prognosis of patients with insomnia who are treated with mobile cognitive behavioral therapy. Patients with insomnia who visited the sleep disorders clinic were selected and completed mobile Cognitive behavioral therapy. Patients completed at least three evaluations (including baseline, monthly evaluations thereafter, and a final evaluation at the end of one year) and responded well to treatment within one year of follow-up. Insomnia, anxiety, and depression symptoms were evaluated using the Pittsburgh Sleep Quality Index (PSQI), the Generalized Anxiety Disorder 7-item (GAD-7) scale, and the 9-item Patient Health Questionnaire (PHQ-9), respectively. Treatment prognosis including relapse, recurrence, and remission group. These 339 patients were divided into three groups: 160 patients who remission, 100 patients who relapsed, and 79 patients who experienced recurrence after remission. Demographic characteristics of the 339 patients showed no significant difference in gender between the three groups (P = 0.978). However, significant differences were found in age (P = 0.006) and onset time (P = 0.000) among the three groups. The remission group had a higher average age than the recurrence group and the relapse group, and the onset time was slower than the other two groups. Multivariate logistic regression analysis showed that age and delayed onset time were protective factors for good treatment prognosis, while low educational level and high GAD-7 scores were independent risk factors for poor prognosis. There are many factors that affect the treatment prognosis of insomnia. Age, low educational level, high GAD-7 scores, and delayed onset time can be used to predict the prognosis of insomnia treatment.

Dysfunctional brain networks have been found in patients with major depressive disorder (MDD). In this study, to verify this in a more straightforward way, we investigated the intrinsic organization of brain networks in MDD by leveraging the resting-state functional near-infrared spectroscopy (rs-fNIRS). Thirty-four MDD patients (24 females, 38.41 ± 13.14 years old) and thirty healthy controls (22 females, 34.43 ± 5.03 years old) underwent a 10 min rest while their brain activity was recorded via fNIRS. The results showed that MDD patients and healthy controls exhibited similar resting-state functional connectivity. Moreover, the depression group showed lower small-world Lambda (1.12 ± 0.04 vs. 1.16 ± 0.10, p = 0.04) but higher global efficiency (0.51 ± 0.03 vs. 0.48 ± 0.05, p = 0.03) than the control group. Importantly, MDD patients, as opposed to healthy controls, showed a significantly lower nodal local efficiency at the left middle occipital gyrus (0.56 ± 0.36 vs. 0.81 ± 0.20, p_FDR < 0.05), which predicted the level of depression in MDD (r = 0.45, p = 0.01, R² = 0.15). In sum, we found a more integrated brain network in MDD patients with a lower nodal local efficiency at the occipital hub, which could predict depressive symptoms.