Many studies^1-4 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.^9,10

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.

Internet-delivered self-help for depression with therapist guidance has shown efficacy in several trials. Results from meta-analyses suggest that guidance is important and that self-help programs without support are less effective. However, there are no direct experimental comparisons between guided and unguided internet-based treatments for depression. The present study compared the benefits of a 10-week web-based unguided self-help treatment with the same intervention complemented with weekly therapist support via e-mail. A waiting-list control group was also included. Seventy-six individuals meeting the diagnostic criteria of major depression or dysthymia were randomly assigned to one of the three conditions. The Beck Depression Inventory (BDI-II) was used as the primary outcome measure. Secondary outcomes included general psychopathology, interpersonal problems, and quality of life. Sixty-nine participants (91%) completed the assessment at posttreatment and 59 (78%) at 6-month follow-up. Results showed significant symptom reductions in both treatment groups compared to the waiting-list control group. At posttreatment, between-group effect sizes on the BDI-II were d = .66 for unguided self-help versus waiting-list and d = 1.14 for guided self-help versus waiting-list controls. In the comparison of the two active treatments, small-to-moderate, but not statistically significant effects in favor of the guided condition were found on all measured dimensions. In both groups, treatment gains were maintained at 6-month follow-up. The findings provide evidence that internet-delivered treatments for depression can be effective whether support is added or not. However, all participants were interviewed in a structured diagnostic telephone interview before inclusion, which prohibits conclusions regarding unguided treatments that are without any human contact.

Objectives: Research on Internet interventions has grown rapidly over the recent years and evidence is growing that Internet-based treatments often result in similar outcomes as conventional face-to-face psychotherapy. Yet there are still unanswered concerns such as whether a therapeutic alliance can be established over the Internet and whether the alliance is important in this new treatment format. Methods: A narrative review of studies formally assessing the therapeutic alliance in Internet interventions was conducted. It is the first review summarizing findings on the therapeutic alliance that (i) distinguishes between different forms of Internet interventions and (ii) does not restrict itself to specific Internet-based treatment formats such as guided self-help treatments, e-mail or videoconferencing therapies. Results: Independent of communication modalities, diagnostic groups and amount of contact between clients and therapists, client-rated alliance scores were high, roughly equivalent to alliance ratings found in studies on face-to-face therapy. Mixed results were found regarding the therapist-rated alliance and alliance-outcome associations. Conclusions: The review points to the limitations of the available evidence and identifies unanswered questions. It is concluded that one of the major tasks for future research is to identify unique characteristics of the therapeutic alliance in the different treatment formats.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet