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- Furukawa, T. A., et al.
(author)
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Dismantling, optimising, and personalising internet cognitive behavioural therapy for depression: a systematic review and component network meta-analysis using individual data
- 2021
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In: Lancet Psychiatry. - : Elsevier BV. - 2215-0374 .- 2215-0366. ; 8:6, s. 500-511
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Journal article (peer-reviewed)abstract
- Findings We identified 76 RCTs, including 48 trials contributing individual participant data (11 704 participants) and 28 trials with aggregate data (6474 participants). The participants' weighted mean age was 42.0 years and 12 406 (71%) of 17 521 reported were women. There was suggestive evidence that behavioural activation might be beneficial (iMD -1.83 [95% credible interval (CrI) -2.90 to -0.80]) and that relaxation might be harmful (1.20 [95% CrI 0.17 to 2.27]). Baseline severity emerged as the strongest prognostic factor for endpoint depression. Combining human and automated encouragement reduced dropouts from treatment (incremental odds ratio, 0.32 [95% CrI 0.13 to 0.93]). The risk of bias was low for the randomisation process, missing outcome data, or selection of reported results in most of the included studies, uncertain for deviation from intended interventions, and high for measurement of outcomes. There was moderate to high heterogeneity among the studies and their components. 511
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- Andersson, E, et al.
(author)
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Internet-based cognitive behaviour therapy for obsessive-compulsive disorder: a randomized controlled trial
- 2012
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In: Psychological Medicine. - : Cambridge University Press (CUP). - 0033-2917 .- 1469-8978. ; 42:10, s. 2193-2203
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Journal article (peer-reviewed)abstract
- Background. Cognitive behaviour therapy (CBT) is an effective treatment for obsessive-compulsive disorder (OCD) but access to CBT is limited. Internet-based CBT (ICBT) with therapist support is potentially a more accessible treatment. There are no randomized controlled trials testing ICBT for OCD. The aim of this study was to investigate the efficacy of ICBT for OCD in a randomized controlled trial. less thanbrgreater than less thanbrgreater thanMethod. Participants (n=101) diagnosed with OCD were randomized to either 10 weeks of ICBT or to an attention control condition, consisting of online supportive therapy. The primary outcome measure was the Yale-Brown Obsessive Compulsive Scale (YBOCS) administered by blinded assessors. less thanbrgreater than less thanbrgreater thanResults. Both treatments lead to significant improvements in OCD symptoms, but ICBT resulted in larger improvements than the control condition on the YBOCS, with a significant between-group effect size (Cohens d) of 1.12 (95% CI 0.69-1.53) at post-treatment. The proportion of participants showing clinically significant improvement was 60% (95% CI 46-72) in the ICBT group compared to 6% (95% CI 1-17) in the control condition. The results were sustained at follow-up. less thanbrgreater than less thanbrgreater thanConclusions. ICBT is an efficacious treatment for OCD that could substantially increase access to CBT for OCD patients. Replication studies are warranted.
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- Andersson, Gerhard, et al.
(author)
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Förekomst av tinnitus i Sverige
- 2002
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In: Läkaresällskapets Rikstämma 27-29 november 2002. ; , s. 130-
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Conference paper (peer-reviewed)
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- Edmonds, M., et al.
(author)
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Treating comorbid insomnia in patients enrolled in therapist-assisted transdiagnostic internet-delivered cognitive behaviour therapy for anxiety and depression : A randomized controlled trial
- 2024
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In: Internet Interventions. - : Elsevier. - 2214-7829. ; 35
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Journal article (peer-reviewed)abstract
- Transdiagnostic Internet-delivered cognitive behaviour therapy (ICBT) for patients experiencing anxiety and depression can produce large improvements in symptoms. Comorbid insomnia is common among individuals seeking treatment for anxiety and depression, yet transdiagnostic ICBT rarely targets insomnia and many ICBT patients report that symptoms of insomnia remain after treatment. This trial explored the impact of including a brief intervention for insomnia alongside an existing transdiagnostic ICBT course that included brief weekly therapist assistance. Patients were randomly assigned to receive either the Standard transdiagnostic (n = 75) or a Sleep-Enhanced course (n = 142), which included information on sleep restriction and stimulus control. Intentto-treat analyses using generalized estimating equation (GEE) showed significant, large reductions in all primary outcomes (insomnia: d = 0.96, 95 % CI [0.68, 1.24]; depression: d = 1.04, 95 % CI [0.76, 1.33]; and anxiety: d = 1.23, 95 % CI [0.94, 1.52]) from pre-treatment to post-treatment, with changes maintained at 3-months. Patients assigned to the Sleep-Enhanced course reported larger reductions in insomnia than patients in the Standard transdiagnostic course (Cohen's d = 0.31, 95 % CI [0.034, 0.60]) at post-treatment but no significant betweengroup differences in any of the primary outcomes were found at follow-up. Patient-reported adherence to sleep restriction guidelines (p = .03), but not stimulus control instructions (p = .84) was associated with greater reductions in insomnia symptoms during the course. Overall, patients who received the Sleep-Enhanced course were satisfied with the materials and most patients reported making sleep behaviour changes. The trial results demonstrate that including a brief intervention targeting insomnia can be beneficial for many patients who enroll in ICBT primarily for symptoms related to anxiety and depression.
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| 18. |
- Enander, J, et al.
(author)
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Internet administration of the Dimensional Obsessive-Compulsive Scale: A psychometric evaluation
- 2012
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In: Journal of Obsessive-Compulsive and Related Disorders. - : Elsevier. - 2211-3649. ; 1:4, s. 325-330
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Journal article (peer-reviewed)abstract
- The Dimensional Obsessive-Compulsive Scale (DOCS) was designed to address the current limitations of existing obsessive-compulsive (OC) symptom measures and is a self-report questionnaire that assesses the severity of the four most empirically supported OC symptom dimensions. The aim of this study was to examine the psychometric properties of a Swedish version of the DOCS when administered via the Internet. Internal consistency, factor structure, and convergent and discriminant validity were examined in a sample consisting of 101 patients diagnosed with obsessive-compulsive disorder. The DOCS sensitivity to treatment effects were examined in a sample consisting of 48 patients treated with Internet-delivered cognitive behavioral therapy were the main intervention was exposure with response prevention. Results showed that the internal consistency was high. The DOCS also showed adequate convergent and discriminant validity, as well as fair sensitivity to treatment effects. The factor analysis supported the DOCS four-factor solution. In summary, the results from the present study give initial support that the DOCS can be administered via the Internet with adequate psychometric properties. © 2012 Elsevier Ltd.
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- Kaldo, V., et al.
(author)
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AI-driven adaptive treatment strategies in internet-delivered CBT
- 2021
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In: European psychiatry. - : Cambridge University Press. - 0924-9338 .- 1778-3585. ; 64, s. S20-S20
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Journal article (other academic/artistic)abstract
- Introduction: Adaptive Treatment Strategies warns therapists of patients at risk of treatment failure to prompt an adaption of the intervention. Internet-delivered Cognitive Behavioural Therapy (ICBT) collects a wide range of data before and during treatment and can quickly be adapted by adjusting the level of therapist support. Objectives: To evaluate how accurate machine learning algorithms can predict a single patient’s final outcome and evaluate the opportunities for using them within an Adaptive Treatment Strategy. Methods: Over 6000 patients at the Internet Psychiatry Clinic in Stockholm receiving ICBT for major depression, panic disorder or social anxiety disorder composed a training data set for eight different machine learning methods (e.g. k-Nearest Neighbour, random forest, and multilayer perceptrons). Symptom measures, messages between therapist and patient, homework reports, and other data from baseline to treatment week four was used to predict treatment success (either 50% reduction or under clinical cut-off) for each primary symptom outcome. Results: The Balanced Accuracy for predicting failure/success always were significantly better than chance, varied between 56% and 77% and outperformed the predictive precision in a previous Adaptive Treatment Strategy trial. Predictive power increased when data from treatment weeks was cumulatively added to baseline data. Conclusions: The machine learning algorithms outperformed a predictive algorithm previously used in a successful Adaptive Treatment Strategy, even though the latter also received input from a therapist. The next steps are to visualize what factors contributes most to a specific patient’s prediction and to enhance predictive power even further by so called Ensemble Learning.No significant relationships.
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- Rozental, Alexander, et al.
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Consensus statement on defining and measuring negative effects of Internet interventions
- 2014
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Conference paper (other academic/artistic)abstract
- Introduction: Internet interventions have a great potential for alleviating emotional distress and promoting mental health. A number of clinical trials have demonstrated their efficacy for several psychiatric conditions, and Internet interventions will likely become a common alternative to face-to-face treatments. Meanwhile, research has paid little attention to the potential negative effects associated with treatment, warranting further investigation of the possibility that some patients might deteriorate or experience adverse events. Evidence from face-to-face treatments suggests that negative effects afflict 5-10% of all patients undergoing treatment in terms of deterioration alone. However, there is currently a lack of consensus on how to define and measure negative effects in psychotherapy research in general, leaving researchers without practical guidelines for monitoring and reporting negative effects in clinical trials.Method: The current paper seeks to provide recommendations that could promote the study of negative effects in Internet interventions with the aim of increasing the knowledge of its occurrence and characteristics. Ten leading experts in the field of Internet interventions were invited to participate and share their perspective on how to explore negative effects, using the Delphi technique to facilitate a dialogue and reach an agreement.Results: The importance of conducting further research on negative effects is emphasized, and suggestions on how to classify and measure negative effects in Internet interventions are provided, involving methods from both quantitative and qualitative research. Potential mechanisms underlying negative effects are also presented, differentiating common factors shared with face-to-face treatments from those unique to treatments delivered via the Internet.Conclusion: Negative effects are to be expected and need to be acknowledged to a greater extent, advising researchers to systematically probe for negative effects whenever conducting clinical trials involving Internet interventions, as well as to share their findings in scientific journals.
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