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Little is known about potential harmful effects as a consequence of self-guided internet-based cognitive behaviour therapy (iCBT), such as symptom deterioration rates. Thus, safety concerns remain and hamper the implementation of self-guided iCBT into clinical practice. We aimed to conduct an individual participant data (IPD) meta-analysis to determine the prevalence of clinically significant deterioration (symptom worsening) in adults with depressive symptoms who received self-guided iCBT compared with control conditions. Several socio-demographic, clinical and study-level variables were tested as potential moderators of deterioration.
Randomised controlled trials that reported results of self-guided iCBT compared with control conditions in adults with symptoms of depression were selected. Mixed effects models with participants nested within studies were used to examine possible clinically significant deterioration rates.
Thirteen out of 16 eligible trials were included in the present IPD meta-analysis. Of the 3805 participants analysed, 7.2% showed clinically significant deterioration (5.8% and 9.1% of participants in the intervention and control groups, respectively). Participants in self-guided iCBT were less likely to deteriorate (OR 0.62, p < 0.001) compared with control conditions. None of the examined participant- and study-level moderators were significantly associated with deterioration rates.
Self-guided iCBT has a lower rate of negative outcomes on symptoms than control conditions and could be a first step treatment approach for adult depression as well as an alternative to watchful waiting in general practice.
Almost nothing is known about the potential negative effects of Internet-based psychological treatments for depression. This study aims at investigating deterioration and its moderators within randomized trials on Internet-based guided self-help for adult depression, using an individual patient data meta-analyses (IPDMA) approach.
Studies were identified through systematic searches (PubMed, PsycINFO, EMBASE, Cochrane Library). Deterioration in participants was defined as a significant symptom increase according to the reliable change index (i.e. 7.68 points in the CES-D; 7.63 points in the BDI). Two-step IPDMA procedures, with a random-effects model were used to pool data.
A total of 18 studies (21 comparisons, 2079 participants) contributed data to the analysis. The risk for a reliable deterioration from baseline to post-treatment was significantly lower in the intervention v. control conditions (3.36 v. 7.60; relative risk 0.47, 95% confidence interval 0.29–0.75). Education moderated effects on deterioration, with patients with low education displaying a higher risk for deterioration than patients with higher education. Deterioration rates for patients with low education did not differ statistically significantly between intervention and control groups. The benefit–risk ratio for patients with low education indicated that 9.38 patients achieve a treatment response for each patient experiencing a symptom deterioration.
Internet-based guided self-help is associated with a mean reduced risk for a symptom deterioration compared to controls. Treatment and symptom progress of patients with low education should be closely monitored, as some patients might face an increased risk for symptom deterioration. Future studies should examine predictors of deterioration in patients with low education.
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.
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.
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).
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.
Evidence about the cost-effectiveness and cost utility of computerised
cognitive–behavioural therapy (CCBT) is still limited. Recently, we
compared the clinical effectiveness of unsupported, online CCBT with
treatment as usual (TAU) and a combination of CCBT and TAU (CCBT plus
TAU) for depression. The study is registered at the Netherlands Trial
Register, part of the Dutch Cochrane Centre (ISRCTN47481236).
To assess the cost-effectiveness of CCBT compared with TAU and CCBT plus
Costs, depression severity and quality of life were measured for 12
months. Cost-effectiveness and cost-utility analyses were performed from
a societal perspective. Uncertainty was dealt with by bootstrap
replications and sensitivity analyses.
Costs were lowest for the CCBT group. There are no significant group
differences in effectiveness or quality of life. Cost-utility and
cost-effectiveness analyses tend to be in favour of CCBT.
On balance, CCBT constitutes the most efficient treatment strategy,
although all treatments showed low adherence rates and modest
improvements in depression and quality of life.
Computerised cognitive–behavioural therapy (CCBT) might offer a solution
to the current undertreatment of depression.
To determine the clinical effectiveness of online, unsupported CCBT for
depression in primary care.
Three hundred and three people with depression were randomly allocated to
one of three groups: Colour Your Life; treatment as usual (TAU) by a
general practitioner; or Colour Your Life and TAU combined. Colour Your
Life is an online, multimedia, interactive CCBT programme. No assistance
was offered. We had a 6-month follow-up period.
No significant differences in outcome between the three interventions
were found in the intention-to-treat and per protocol analyses.
Online, unsupported CCBT did not outperform usual care, and the
combination of both did not have additional effects. Decrease in
depressive symptoms in people with moderate to severe depression was
moderate in all three interventions. Online CCBT without support is not
beneficial for all individuals with depression.
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.
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 (Lewinsohn's 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.
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).
People aged over 50 years with subthreshold depression can still benefit from internet-based CBT 1 year after the start of treatment.
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