ICBT can be delivered effectively using smartphones. (PsycINFO Database Record

BackgroundInternet-based cognitive–behavioural treatment (ICBT) for anxiety disorders has shown some promise, but no study has yet examined unguided ICBT in primary care. This randomized controlled trial (RCT) investigated whether a transdiagnostic, unguided ICBT programme for anxiety disorders is effective in primary care settings, after a face-to-face consultation with a physician (MD). We hypothesized that care as usual (CAU) plus unguided ICBT would be superior to CAU in reducing anxiety and related symptoms among patients with social anxiety disorder (SAD), panic disorder with or without agoraphobia (PDA) and/or generalized anxiety disorder (GAD).MethodAdults (n = 139) with at least one of these anxiety disorders, as reported by their MD and confirmed by a structured diagnostic interview, were randomized. Unguided ICBT was provided by a novel transdiagnostic ICBT programme (‘velibra’). Primary outcomes were generic measures, such as anxiety and depression symptom severity, and diagnostic status at post-treatment (9 weeks). Secondary outcomes included anxiety disorder-specific measures, quality of life, treatment adherence, satisfaction, and general psychiatric symptomatology at follow-up (6 months after randomization).ResultsCAU plus unguided ICBT was more effective than CAU at post-treatment, with small to medium between-group effect sizes on primary (Cohen's d = 0.41–0.47) and secondary (Cohen's d = 0.16–0.61) outcomes. Treatment gains were maintained at follow-up. In the treatment group, 28.2% of those with a SAD diagnosis, 38.3% with a PDA diagnosis, and 44.8% with a GAD diagnosis at pretreatment no longer fulfilled diagnostic criteria at post-treatment.ConclusionsThe unguided ICBT intervention examined is effective for anxiety disorders when delivered in primary care.

No abstract

Predicting therapeutic outcome in the mental health domain is of utmost importance to enable therapists to provide the most effective treatment to a patient. Using information from the writings of a patient can potentially be a valuable source of information, especially now that more and more treatments involve computer-based exercises or electronic conversations between patient and therapist. In this paper, we study predictive modeling using writings of patients under treatment for a social anxiety disorder. We extract a wealth of information from the text written by patients including their usage of words, the topics they talk about, the sentiment of the messages, and the style of writing. In addition, we study trends over time with respect to those measures. We then apply machine learning algorithms to generate the predictive models. Based on a dataset of 69 patients we are able to show that we can predict therapy outcome with an Area Under the Curve (AUC) of 0.83 halfway through the therapy and with a precision of 0.78 when using the full data (i.e., the entire treatment period). Due to the limited number of participants it is hard to generalize the results, but they do show great potential in this type of information.

Transdiagnostic treatments span a heterogeneous group of interventions that target a wider range of disorders and can be applied to treat several disorders simultaneously. Several meta-analyses have highlighted the evidence base of these novel therapies. However, these meta-analyses adopt different definitions of transdiagnostic treatments, and the growing field of transdiagnostic therapies has become increasingly difficult to grasp. The current narrative review proposes a distinction of “one size fits all” unified and “my size fits me” individualized approaches within transdiagnostic therapies. Unified treatments are applied as “broadband” interventions to a range of disorders without tailoring to the individual, while individualized treatments are tailored to the specific problem presentation of the individual, e.g., by selecting modules within modular treatments. The underlying theoretical foundation and relevant empirical evidence for these different transdiagnostic approaches are examined. Advantages and limitations of the transdiagnostic treatments as well as future developments are discussed.

A growing body of evidence suggests that internet-based cognitive behavioural treatments (ICBT) are effective to treat social anxiety disorder (SAD). Whereas the efficacy of clinician-guided ICBT has been established, ICBT in a group format has not yet been systematically investigated. This three-arm RCT compared the efficacy of clinician-guided group ICBT (GT) with clinician guided individual ICBT (IT) and a wait-list (WL). A total of 149 individuals meeting the diagnostic criteria for SAD were randomly assigned to one of three conditions. Primary endpoints were self-report measures of SAD and diagnostic status taken at baseline, after the twelve-week intervention and at six-month follow-up. Secondary endpoints were symptoms of depression, interpersonal problems and general symptomatology. At post-treatment, both active conditions showed superior outcome regarding SAD symptoms (GT vs. WL: d = 0.84-0.74; IT vs. WL: d = 0.94-1.22). The two active conditions did not differ significantly in symptom reduction (d = 0.12-0.26, all ps > 0.63), diagnostic response rate or attrition. Treatment gains were maintained at follow-up. The group format reduced weekly therapist time per participant by 71% (IT: 17 min, GT: 5 min). Findings indicate that a clinician-guided group format is a promising approach in treating SAD.

Objectives Internet‐ and mobile‐based interventions (IMIs) offer the opportunity to deliver mental health treatments on a large scale. This randomized controlled trial evaluated the efficacy of an unguided IMI (StudiCare SAD) for university students with social anxiety disorder (SAD). Methods University students (N = 200) diagnosed with SAD were randomly assigned to an IMI or a waitlist control group (WLC) with full access to treatment as usual. StudiCare SAD consists of nine sessions. The primary outcome was SAD symptoms at posttreatment (10 weeks), assessed via the Social Phobia Scale (SPS) and the Social Interaction Anxiety Scale (SIAS). Secondary outcomes included depression, quality of life, fear of positive evaluation, general psychopathology, and interpersonal problems. Results Results indicated moderate to large effect sizes in favor of StudiCare SAD compared with WLC for SAD at posttest for the primary outcomes (SPS: d = 0.76; SIAS: d = 0.55, p < 0.001). Effects on all secondary outcomes were significant and in favor of the intervention group. Conclusion StudiCare SAD has proven effective in reducing SAD symptoms in university students. Providing IMIs may be a promising way to reach university students with SAD at an early stage with an effective treatment.

Background A growing number of psychological interventions are delivered via smartphones with the aim of increasing the efficacy and effectiveness of these treatments and providing scalable access to interventions for improving mental health. Most of the scientifically tested apps are based on cognitive behavioral therapy (CBT) principles, which are considered the gold standard for the treatment of most mental health problems. Objective This review investigates standalone smartphone-based ecological momentary interventions (EMIs) built on principles derived from CBT that aim to improve mental health. Methods We searched the MEDLINE, PsycINFO, EMBASE, and PubMed databases for peer-reviewed studies published between January 1, 2007, and January 15, 2020. We included studies focusing on standalone app-based approaches to improve mental health and their feasibility, efficacy, or effectiveness. Both within- and between-group designs and studies with both healthy and clinical samples were included. Blended interventions, for example, app-based treatments in combination with psychotherapy, were not included. Selected studies were evaluated in terms of their design, that is, choice of the control condition, sample characteristics, EMI content, EMI delivery characteristics, feasibility, efficacy, and effectiveness. The latter was defined in terms of improvement in the primary outcomes used in the studies. Results A total of 26 studies were selected. The results show that EMIs based on CBT principles can be successfully delivered, significantly increase well-being among users, and reduce mental health symptoms. Standalone EMIs were rated as helpful (mean 70.8%, SD 15.3; n=4 studies) and satisfying for users (mean 72.6%, SD 17.2; n=7 studies). Conclusions Study quality was heterogeneous, and feasibility was often not reported in the reviewed studies, thus limiting the conclusions that can be drawn from the existing data. Together, the studies show that EMIs may help increase mental health and thus support individuals in their daily lives. Such EMIs provide readily available, scalable, and evidence-based mental health support. These characteristics appear crucial in the context of a global crisis such as the COVID-19 pandemic but may also help reduce personal and economic costs of mental health impairment beyond this situation or in the context of potential future pandemics.