Viola Spek

Internet-based cognitive behaviour therapy for symptoms of depression and anxiety: a meta-analysis

BACKGROUND We studied to what extent internet-based cognitive behaviour therapy (CBT) programs for symptoms of depression and anxiety are effective. METHOD A meta-analysis of 12 randomized controlled trials. RESULTS The effects of internet-based CBT were compared to control conditions in 13 contrast groups with a total number of 2334 participants. A meta-analysis on treatment contrasts resulted in a moderate to large mean effect size [fixed effects analysis (FEA) d=0.40, mixed effects analysis (MEA) d=0.60] and significant heterogeneity. Therefore, two sets of post hoc subgroup analyses were carried out. Analyses on the type of symptoms revealed that interventions for symptoms of depression had a small mean effect size (FEA d=0.27, MEA d=0.32) and significant heterogeneity. Further analyses showed that one study could be regarded as an outlier. Analyses without this study showed a small mean effect size and moderate, non-significant heterogeneity. Interventions for anxiety had a large mean effect size (FEA and MEA d=0.96) and very low heterogeneity. When examining the second set of subgroups, based on therapist assistance, no significant heterogeneity was found. Interventions with therapist support (n=5) had a large mean effect size, while interventions without therapist support (n=6) had a small mean effect size (FEA d=0.24, MEA d=0.26). CONCLUSIONS In general, effect sizes of internet-based interventions for symptoms of anxiety were larger than effect sizes for depressive symptoms; however, this might be explained by differences in the amount of therapist support.

A General Propensity to Psychological Distress Affects Cardiovascular Outcomes Evidence From Research on the Type D (Distressed) Personality Profile

Evidence Specific negative emotions have been related to adverse cardiac events, but a general propensity to psychological distress may also affect cardiovascular outcomes. In this summary article, we provide a reliable estimate of the prognostic risk associated with Type D (distressed) personality, a general propensity to distress that is defined by high scores on the “negative affectivity” and “social inhibition” traits. Quantitative analyses of prospective studies that included a total of 6121 patients with a cardiovascular condition indicated that Type D personality was associated with a more than 3-fold increased risk of adverse events (9 studies) and long-term psychological distress (11 studies). In addition, a narrative review of 29 studies showed that Type D personality and depression are distinct manifestations of psychological distress, with different and independent cardiovascular effects. There are also plausible biological and behavioral pathways that may explain this adverse effect of Type D personality. The findings reported in this summary article support the simultaneous use of specific and general measures of distress in cardiovascular research and practice. Depression, anxiety, anger, and posttraumatic stress are specific markers of distress that have been related to cardiac disorder,1,–,5 whereas broader markers of psychological distress have received substantially less attention in cardiovascular research.6 However, the general distress shared across these specific markers may predict the development of coronary heart disease1 and may also partly account for the association of depression and anxiety with myocardial infarction,3 poor cardiac prognosis,4 and autonomic cardiac dysregulation.7 Hence, the conceptual idea of psychological distress as a cardiovascular risk marker may be broadened to include a general propensity to distress. Many studies report on depression, anxiety, and cardiovascular outcomes.2,–,4 Although patients may go in and out of depressive and anxious episodes, there …

Internet-based cognitive behavioural therapy for subthreshold depression in people over 50 years old:a randomized controlled clinical trial

BACKGROUND Subthreshold depression is a highly prevalent condition and a risk factor for developing a major depressive episode. Internet-based cognitive behaviour therapy may be a promising approach for the treatment of subthreshold depression. The current study had two aims: (1) to determine whether an internet-based cognitive behaviour therapy intervention and a group cognitive behaviour therapy intervention are more effective than a waiting-list control group; and (2) to determine whether the effect of the internet-based cognitive behaviour therapy differs from the group cognitive behaviour therapy intervention. METHOD A total of 191 women and 110 men with subthreshold depression were randomized into internet-based treatment, group cognitive behaviour therapy (Lewinsohns Coping With Depression course), or a waiting-list control condition. The main outcome measure was treatment response after 10 weeks, defined as the difference in pre- and post-treatment scores on the Beck Depression Inventory (BDI). Missing data, a major limitation of this study, were imputed using the Multiple Imputation (MI) procedure Data Augmentation. RESULTS In the waiting-list control group, we found a pre- to post-improvement effect size of 0.45, which was 0.65 in the group cognitive behaviour therapy condition and 1.00 within the internet-based treatment condition. Helmert contrasts showed a significant difference between the waiting-list condition and the two treatment conditions (p=0.04) and no significant difference between both treatment conditions (p=0.62). CONCLUSIONS An internet-based intervention may be at least as effective as a commonly used group cognitive behaviour therapy intervention for subthreshold depression in people over 50 years of age.

Effectiveness of E-Self-help Interventions for Curbing Adult Problem Drinking: A Meta-analysis

Background Self-help interventions without professional contact to curb adult problem drinking in the community are increasingly being delivered via the Internet. Objective The objective of this meta-analysis was to assess the overall effectiveness of these eHealth interventions. Methods In all, 9 randomized controlled trials (RCTs), all from high-income countries, with 9 comparison conditions and a total of 1553 participants, were identified, and their combined effectiveness in reducing alcohol consumption was evaluated by means of a meta-analysis. Results An overall medium effect size (g = 0.44, 95% CI 0.17-0.71, random effect model) was found for the 9 studies, all of which compared no-contact interventions to control conditions. The medium effect was maintained (g = 0.39; 95% CI 0.23-0.57, random effect model) after exclusion of two outliers. Type of control group, treatment location, type of analysis, and sample size did not have differential impacts on treatment outcome. A significant difference (P = .04) emerged between single-session personalized normative feedback interventions (g = 0.27, 95% CI 0.11-0.43) and more extended e- self-help (g = 0.61, 95% CI 0.33-0.90). Conclusion E-self-help interventions without professional contact are effective in curbing adult problem drinking in high-income countries. In view of the easy scalability and low dissemination costs of such interventions, we recommend exploration of whether these could broaden the scope of effective public health interventions in low- and middle-income countries as well.

One-year follow-up results of a randomized controlled clinical trial on internet-based cognitive behavioural therapy for subthreshold depression in people over 50 years

BACKGROUND Internet-based cognitive behaviour therapy (CBT) is a promising new approach for the treatment of depressive symptoms. The current study had two aims: (1) to determine whether, after 1 year, an internet-based CBT intervention was more effective than a waiting-list control group; and (2) to determine whether the effect of the internet-based CBT differed from the group CBT intervention, 1 year after the start of treatment. METHOD A total of 191 women and 110 men (mean age=55 years, s.d.=4.6) with subthreshold depression were randomized into internet-based treatment, group CBT (Lewinsohns Coping with Depression Course), or a waiting-list control condition. The main outcome measure was treatment response after 1 year, defined as the difference in pretreatment and follow-up scores on the Beck Depression Inventory (BDI). Missing data were imputed using the multiple imputation procedure of data augmentation. Analyses were performed using multiple imputation inference. RESULTS In the waiting-list control group, we found a pretreatment to follow-up improvement effect size of 0.69, which was 0.62 in the group CBT condition and 1.22 with the internet-based treatment condition. Simple contrasts showed a significant difference between the waiting-list condition and internet-based treatment (p=0.03) and no difference between both treatment conditions (p=0.08). CONCLUSIONS People aged over 50 years with subthreshold depression can still benefit from internet-based CBT 1 year after the start of treatment.

Efficacy of Self-guided Internet-Based Cognitive Behavioral Therapy in the Treatment of Depressive Symptoms: A Meta-analysis of Individual Participant Data

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 Synthesis Primary 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 Measures Outcomes 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. Results Of 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 (&bgr; = −0.21; Hedges g  = 0.27) and treatment response (&bgr; = 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 (&bgr; = −0.19; P = .001) and greater response to treatment (&bgr; = 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.

Predictors of treatment dropout in self-guided web-based interventions for depression: an 'individual patient data' meta-analysis

BACKGROUND It is well known that web-based interventions can be effective treatments for depression. However, dropout rates in web-based interventions are typically high, especially in self-guided web-based interventions. Rigorous empirical evidence regarding factors influencing dropout in self-guided web-based interventions is lacking due to small study sample sizes. In this paper we examined predictors of dropout in an individual patient data meta-analysis to gain a better understanding of who may benefit from these interventions. METHOD A comprehensive literature search for all randomized controlled trials (RCTs) of psychotherapy for adults with depression from 2006 to January 2013 was conducted. Next, we approached authors to collect the primary data of the selected studies. Predictors of dropout, such as socio-demographic, clinical, and intervention characteristics were examined. RESULTS Data from 2705 participants across ten RCTs of self-guided web-based interventions for depression were analysed. The multivariate analysis indicated that male gender [relative risk (RR) 1.08], lower educational level (primary education, RR 1.26) and co-morbid anxiety symptoms (RR 1.18) significantly increased the risk of dropping out, while for every additional 4 years of age, the risk of dropping out significantly decreased (RR 0.94). CONCLUSIONS Dropout can be predicted by several variables and is not randomly distributed. This knowledge may inform tailoring of online self-help interventions to prevent dropout in identified groups at risk.

Efficacy of Self-guided Internet-Based Cognitive Behavioral Therapy in the Treatment of Depressive Symptoms

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 Synthesis Primary 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 Measures Outcomes 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. Results Of 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 (&bgr; = −0.21; Hedges g  = 0.27) and treatment response (&bgr; = 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 (&bgr; = −0.19; P = .001) and greater response to treatment (&bgr; = 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.

Type D personality and health status in cardiovascular disease populations: a meta-analysis of prospective studies

Background: Knowledge of the factors associated with individual differences in patient-reported outcomes is essential to identify high-risk patients and improve secondary prevention. Design: In this meta-analysis, we examined the association between Type D personality and the individual differences in patient-reported physical and mental health status among cardiovascular patients. Methods: A computerized search of the literature through PUBMED and PsychINFO (from 1995 to May 2011) was performed and prospective studies were selected that analysed the association between Type D personality and health status in cardiovascular patients. Two separate meta-analyses were performed for the association of Type D personality with physical and mental health status, respectively. Results: Of all identified studies, ten studies met the selection criteria. The meta-analyses showed that Type D was associated with a two-fold increased odds for impaired physical health status (3035 patients, OR 1.94, 95% CI 1.49–2.52) and a 2.5-fold increased odds for impaired mental health status (2213 patients, OR 2.55, 95% CI 1.57–4.16). There was no significant heterogeneity between the studies on physical health status (Q = 12.78; p = 0.17; I2 = 29.59), but there was between those on mental health status (Q = 21.91; p = 0.003; I2 = 68.04). Subgroup analyses showed that the association between Type D and mental health status decreased yet remained significant when adjusting for baseline health status. Conclusion: Type D personality was shown to be an independent correlate of impaired patient-reported physical and mental health status in various cardiovascular patient groups. Clinicians should be aware of the association between chronic psychological distress and poor patient-reported outcomes.

Alexithymia and cognitive behaviour therapy outcome for subthreshold depression

Objective:  Alexithymia is hypothesized to be a stable trait that hinders favourable outcomes of psychotherapy. We tested two hypotheses: i) alexithymia is not stable but changes along with a change in depressive symptoms and ii) pretreatment alexithymia hinders gaining benefits from psychotherapy.