BackgroundDepression is a highly recurrent disorder, with more than 50% of those affected experiencing a subsequent episode. Although there is relatively little stability in symptoms across... Show moreBackgroundDepression is a highly recurrent disorder, with more than 50% of those affected experiencing a subsequent episode. Although there is relatively little stability in symptoms across episodes, some evidence indicates that suicidal ideation may be an exception. However, these findings warrant replication, especially over longer periods and across multiple episodes.AimsTo assess the relative stability of suicidal ideation in comparison with other non-core depressive symptoms across episodes.MethodWe examined 490 individuals with current major depressive disorder (MDD) at baseline and at least one subsequent episode during 9-year follow-up within the Netherlands Study of Depression and Anxiety (NESDA). The Inventory of Depressive Symptomatology (IDS) was used to assess DSM-5 non-core MDD symptoms (fatigue, appetite/weight change, sleep disturbance, psychomotor disturbance, concentration difficulties, worthlessness/guilt, suicidal ideation) at baseline and 2-, 4-, 6- and 9-year follow-up. We examined consistency in symptom presentation (i.e. whether the symptom met the diagnostic threshold, based on a binary categorisation of the IDS) using kappa (κ) and percentage agreement, and stability in symptom severity using Spearman correlation, based on the continuous IDS scores.ResultsOut of all non-core depressive symptoms, insomnia appeared the most stable across episodes (r = 0.55–0.69, κ = 0.31–0.47) and weight decrease the least stable (r = 0.03–0.33, κ = 0.06–0.19). For suicidal ideation, correlations across episodes ranged from r = 0.36 to r = 0.55 and consistency ranged from κ = 0.28 to κ = 0.49.ConclusionsSuicidal ideation is moderately stable in recurrent depression over 9 years. Contrary to prior reports, however, it does not exhibit substantially more stability than most other non-core symptoms of depression. Show less
Background: Worldwide, insomnia remains a highly prevalent public health problem. eHealth presents a novel opportunity to deliver effective, accessible, and affordable insomnia treatments on a... Show moreBackground: Worldwide, insomnia remains a highly prevalent public health problem. eHealth presents a novel opportunity to deliver effective, accessible, and affordable insomnia treatments on a population-wide scale. However, there is no quantitative integration of evidence regarding the effectiveness of eHealth-based psychosocial interventions on insomnia. Objective: We aimed to evaluate the effectiveness of eHealth-based psychosocial interventions for insomnia and investigate the influence of specific study characteristics and intervention features on these effects. Methods: We searched PubMed, Embase, Web of Science, PsycINFO, and the Cochrane Central Register of Controlled Trials from database inception to February 16, 2021, for publications investigating eHealth-based psychosocial interventions targeting insomnia and updated the search of PubMed to December 6, 2021. We also screened gray literature for unpublished data. Eligible studies were randomized controlled trials of eHealth-based psychosocial interventions targeting adults with insomnia. Random-effects meta-analysis models were used to assess primary and secondary outcomes. Primary outcomes were insomnia severity and sleep quality. Meta-analyses were performed by pooling the effects of eHealth-based psychosocial interventions on insomnia compared with inactive and in-person conditions. We performed subgroup analyses and metaregressions to explore specific factors that affected the effectiveness. Secondary outcomes included sleep diary parameters and mental health-related outcomes. Results: Of the 19,980 identified records, 37 randomized controlled trials (13,227 participants) were included. eHealth-based psychosocial interventions significantly reduced insomnia severity (Hedges g=-1.01, 95% CI -1.12 to -0.89; P<.001) and improved sleep quality (Hedges g=-0.58, 95% CI -0.75 to -0.41; P<.001) compared with inactive control conditions, with no evidence of publication bias. We found no significant difference compared with in-person treatment in alleviating insomnia severity (Hedges g=0.41, 95% CI -0.02 to 0.85; P=.06) and a significant advantage for in-person treatment in enhancing sleep quality (Hedges g=0.56, 95% CI 0.24-0.88; P<.001). eHealth-based psychosocial interventions had significantly larger effects (P=.01) on alleviating insomnia severity in clinical samples than in subclinical samples. eHealth-based psychosocial interventions that incorporated guidance from trained therapists had a significantly greater effect on insomnia severity (P=.05) and sleep quality (P=.02) than those with guidance from animated therapists or no guidance. Higher baseline insomnia severity and longer intervention duration were associated with a larger reduction in insomnia severity (P=.004). eHealth-based psychosocial interventions significantly improved each secondary outcome. Conclusions: eHealth interventions for insomnia are effective in improving sleep and mental health and can be considered a promising treatment for insomnia. Our findings support the wider dissemination of eHealth interventions and their further promotion in a stepped-care model. Offering blended care could improve treatment effectiveness. Future research needs to elucidate which specific intervention components are most important to achieve intervention effectiveness. Blended eHealth interventions may be tailored to benefit people with low socioeconomic status, limited access to health care, or lack of eHealth literacy. Show less
