IMPORTANCE Self-guided internet-based cognitive behavioral therapy (iCBT) has the potential to increase access and availability of evidence-based therapy and reduce the cost of depression treatment.OBJECTIVES To estimate the effect of self-guided iCBT in treating adults with depressive symptoms compared with controls and evaluate the moderating effects of treatment outcome and response.DATA SOURCES A total of 13 384 abstracts were retrieved through a systematic literature search in PubMed, Embase, PsycINFO, and Cochrane Library from database inception to January 1, 2016.STUDY SELECTION Randomized clinical trials in which self-guided iCBT was compared with a control (usual care, waiting list, or attention control) in individuals with symptoms of depression. DATA EXTRACTION AND SYNTHESISPrimary authors provided individual participant data from 3876 participants from 13 of 16 eligible studies. Missing data were handled using multiple imputations. Mixed-effects models with participants nested within studies were used to examine treatment outcomes and moderators. MAIN OUTCOMES AND MEASURESOutcomes included the Beck Depression Inventory, Center for Epidemiological Studies-Depression Scale, and 9-item Patient Health Questionnaire scores. Scales were standardized across the pool of the included studies. RESULTSOf the 3876 study participants, the mean (SD) age was 42.0 (11.7) years, 2531 (66.0%) of 3832 were female, 1368 (53.1%) of 2574 completed secondary education, and 2262 (71.9%) of 3146 were employed. Self-guided iCBT was significantly more effective than controls on depressive symptoms severity (β = −0.21; Hedges g = 0.27) and treatment response (β = 0.53; odds ratio, 1.95; 95% CI, 1.52-2.50; number needed to treat, 8). Adherence to treatment was associated with lower depressive symptoms (β = −0.19; P = .001) and greater response to treatment (β = 0.90; P < .001). None of the examined participant and study-level variables moderated treatment outcomes.CONCLUSIONS AND RELEVANCE Self-guided iCBT is effective in treating depressive symptoms. The use of meta-analyses of individual participant data provides substantial evidence for clinical and policy decision making because self-guided iCBT can be considered as an evidence-based first-step approach in treating symptoms of depression. Several limitations of the iCBT should be addressed before it can be disseminated into routine care. M any studies [1][2][3][4] have found that depressive symptoms can be effectively treated with psychotherapy, pharmacotherapy, or both. Nevertheless, many people with depressive symptoms do not seek help, and even well-resourced health care systems find it difficult to marshal enough qualified therapists to offer psychological interventions. Access barriers to psychotherapy include limited availability of trained clinicians, high cost of treatment, and fear of stigmatization.5-8 As a consequence, a significant number of individuals with depressive symptoms remain untreated.9,10Self-guided internet-based cognitive behavioral therapy (iCBT) wi...

Background Depression is associated with immense suffering and costs, and many patients receive inadequate care, often because of the limited availability of treatment. Web-based treatments may play an increasingly important role in closing this gap between demand and supply. We developed the integrative, Web-based program Deprexis, which covers therapeutic approaches such as behavioral activation, cognitive restructuring, mindfulness/acceptance exercises, and social skills training.Objective To evaluate the effectiveness of the Web-based intervention in a randomized controlled trial.Methods There were 396 adults recruited via Internet depression forums in Germany, and they were randomly assigned in an 80:20 weighted randomization sequence to either 9 weeks of immediate-program-access as an add-on to treatment-as-usual (N = 320), or to a 9-week delayed-access plus treatment-as-usual condition (N = 76). At pre- and post-treatment and 6-month follow-up, we measured depression (Beck Depression Inventory) as the primary outcome measure and social functioning (Work and Social Adjustment Scale) as the secondary outcome measure. Completer analyses and intention-to-treat analyses were performed.Results Of 396 participants, 216 (55%) completed the post-measurement 9 weeks later. Available case analyses revealed a significant reduction in depression severity (BDI), Cohen’s d = .64 (CI 95% = 0.33 - 0.94), and significant improvement in social functioning (WSA), Cohen’s d = .64, 95% (CI 95% = 0.33 - 0.95). These improvements were maintained at 6-month follow-up. Intention-to-treat analyses confirmed significant effects on depression and social functioning improvements (BDI: Cohen’s d = .30, CI 95% = 0.05 - 0.55; WSA: Cohen’s d = .36, CI 95% = 0.10 - 0.61). Moreover, a much higher percentage of patients in the intervention group experienced a significant reduction of depression symptoms (BDI: odds ratio [OR] = 6.8, CI 95% = 2.90 - 18.19) and recovered more often (OR = 17.3, 95% CI 2.3 - 130). More than 80% of the users felt subjectively that the program had been helpful.Conclusions This integrative, Web-based intervention was effective in reducing symptoms of depression and in improving social functioning. Findings suggest that the program could serve as an adjunctive or stand-alone treatment tool for patients suffering from symptoms of depression.Trial Registration International Standard Randomized Controlled Trial Number (ISRCTN): 64953693; http://www.controlled-trials.com/ISRCTN64953693/64953693 (Archived by WebCite at http://www.webcitation.org/5ggzvTJPD)

Background: It is well known that web-based interventions can be effective treatments for

Objective To assess how initial severity of depression affects the benefit derived from low intensity interventions for depression.Design Meta-analysis of individual patient data from 16 datasets comparing low intensity interventions with usual care.Setting Primary care and community settings.Participants 2470 patients with depression.Interventions Low intensity interventions for depression (such as guided self help by means of written materials and limited professional support, and internet delivered interventions).Main outcome measures Depression outcomes (measured with the Beck Depression Inventory or Center for Epidemiologic Studies Depression Scale), and the effect of initial depression severity on the effects of low intensity interventions.Results Although patients were referred for low intensity interventions, many had moderate to severe depression at baseline. We found a significant interaction between baseline severity and treatment effect (coefficient −0.1 (95% CI −0.19 to −0.002)), suggesting that patients who are more severely depressed at baseline demonstrate larger treatment effects than those who are less severely depressed. However, the magnitude of the interaction (equivalent to an additional drop of around one point on the Beck Depression Inventory for a one standard deviation increase in initial severity) was small and may not be clinically significant.Conclusions The data suggest that patients with more severe depression at baseline show at least as much clinical benefit from low intensity interventions as less severely depressed patients and could usefully be offered these interventions as part of a stepped care model.

Prior analyses from the National Institute of Mental Health Treatment of Depression Collaborative Research Program indicated that patients' expectancies of treatment effectiveness (S. M. Sotsky et al., 1991) and the quality of the therapeutic alliance (J. L. Krupnick et al., 1996) predicted clinical improvement. These data were reanalyzed to examine the hypothesis that the link between treatment expectancies and outcome would be mediated by patients' contribution to the alliance. Among 151 patients who completed treatment, this hypothesis was supported, suggesting that patients who expect treatment to be effective tend to engage more constructively in session, which helps bring about symptom reduction. Therapists' expectancies for patient improvement also predicted outcome, although this association was not mediated by the alliance. None of the expectancy scales interacted with alliance ratings in the prediction of clinical improvement.

Little is known about clinically relevant changes in guided Internet-based interventions for depression. Moreover, methodological and power limitations preclude the identification of patients' groups that may benefit more from these interventions. This study aimed to investigate response rates, remission rates, and their moderators in randomized controlled trials (RCTs) comparing the effect of guided Internet-based interventions for adult depression to control groups using an individual patient data meta-analysis approach. Literature searches in PubMed, Embase, PsycINFO and Cochrane Library resulted in 13,384 abstracts from database inception to January 1, 2016. Twenty-four RCTs (4889 participants) comparing a guided Internet-based intervention with a control group contributed data to the analysis. Missing data were multiply imputed. To examine treatment outcome on response and remission, mixed-effects models with participants nested within studies were used. Response and remission rates were calculated using the Reliable Change Index. The intervention group obtained significantly higher response rates (OR = 2.49, 95% CI 2.17-2.85) and remission rates compared to controls (OR = 2.41, 95% CI 2.07-2.79). The moderator analysis indicated that older participants (OR = 1.01) and native-born participants (1.66) were more likely to respond to treatment compared to younger participants and ethnic minorities respectively. Age (OR = 1.01) and ethnicity (1.73) also moderated the effects of treatment on remission.Moreover, adults with more severe depressive symptoms at baseline were more likely to remit after receiving internet-based treatment (OR = 1.19). Guided Internet-based interventions lead to substantial positive treatment effects on treatment response and remission at post-treatment. Thus, such interventions may complement existing services for depression and potentially reduce the gap between the need and provision of evidence-based treatments.

Bipolar disorder has been conceptualized as an outcome of dysregulation in the behavioral activation system (BAS), a brain system that regulates goal-directed activity. On the basis of the BAS model, the authors hypothesized that life events involving goal attainment would promote manic symptoms in bipolar individuals. The authors followed 43 bipolar I individuals monthly with standardized symptom severity assessments (the Modified Hamilton Rating Scale for Depression and the BechRafaelsen Mania Rating Scale). Life events were assessed using the Goal Attainment and Positivity scales of the Life Events and Difficulties Schedule. As hypothesized, manic symptoms increased in the 2 months following goal-attainment events, but depressed symptoms were not changed following goal-attainment events. These results are congruent with a series of recent polarity-specific findings.Bipolar disorder exacts a devastating toll from affected individuals. Most strikingly, this disorder leads to suicide in almost one out of every five diagnosed individuals (Isometsa, 1993). With adequate blood serum levels of lithium, one third of bipolar individuals relapse within 3 years (Keller et al., 1992), but in naturalistic studies with varied levels of patient compliance, two thirds of patients relapse within 2 years (Silverstone, McPherson, Hunt, & Romans, 1998). Given these high rates of relapse and the sustained unemployment rates following each episode of mania (Harrow, Goldberg, Grossman, & Meltzer, 1990), it is not surprising that bipolar disorder has been ranked as the sixth leading cause of disability among both physical and psychiatric disorders worldwide (Murray & Lopez, 1996). Fiscal costs for adult Americans with the disorder were estimated in 1991 at $45 billion (Wyatt & Henter, 1995).Although the modal course is severe, bipolar individuals experience substantial heterogeneity in symptom expression. For instance, as many as 25% of bipolar I individuals will never experience a depressive episode (Goodwin & Jamison, 1990). Further, whereas some individuals experience daily shifts between episode poles, others remain well for a decade or longer (Angst, 1984).For many years, biological models have dominated attempts to understand this heterogeneity. The importance of genetic influences for this disorder is supported by findings of a concordance rate of .84 for monozygotic twins compared with .35 for dizygotic twins among 110 twin pairs (Bertelsen, Harvald, & Hauge, 1977); similar findings have emerged across 12 twin studies (Vehmanen, Kaprio, & Loennqvist, 1995).Beyond the important role of genes, the psychosocial environment appears to be a trigger of episodes. For example, expressed emotion (Miklowitz et al., 1988), social support (Johnson, Winett, Meyer, Greenhouse, & Miller, 1999), and life events (Ellicott, 1989;Johnson & Miller, 1997) each have been shown to predict symptom changes in bipolar disorder. Recent models of bipolar course have incorporated biological and psychosocial variables (cf. Goodwin & Jamison, 199...

There is growing evidence that social rhythms (e.g., daily activities such as getting into or out of bed, eating, and adhering to a work schedule) have important implications for sleep. The present study used a prospective measure of daily activities to assess the relation between sleep and social rhythms. College students (n=243) 18 to 39 yrs of age, completed the Social Rhythm Metric (SRM) each day for 14 d and then completed the Pittsburgh Sleep Quality Index (PSQI). The sample was divided into groups of good or poor sleepers, according to a PSQI cut-off score of 5 points and was compared on the regularity, frequency, timing, and extent of social engagement during activities. There was a lower frequency and less regularity of social rhythms in poor sleepers relative to good sleepers. Good sleepers engaged more regularly in activities with active social engagement. Earlier rise time, first consumption of a beverage, going outdoors for the first time, and bedtime were associated with better sleep. Greater variability in rise time, consuming a morning beverage, returning home for the last time, and bedtime were associated with more disturbed sleep. The results are consistent with previous findings of reduced regularity in bedtime and rise time schedules in undergraduates, other age groups, and in clinical populations. Results augment the current thought that regulating behavioral zeitgebers may be important in influencing bed and rise times, and suggest that engaging in activities with other people may increase regularity.