[CBT administered via the internet]. / Internetförmedlad psykologisk egenvård.

Cognitive behavioral therapy (CBT) can be administered clinically to individuals and in group settings. More recently, CBT has been administered successfully via the internet (ICBT). We provide a concept aiming at further developing ICBT in a self-care format. We use recent development in user interface (UI) design in order to optimize the user interface and allow easy and flexible use via smartphone, tablet, or computer. Preliminary evidence indicates that an optimized user interface and adjusted information facilitate increased use of training programs compared to a traditional ICBT interface. Our aims are to allow increased availability of evidence-based CBT tools for self-care to improve people's health and recovery from disease. So far, evidence for effects and safe use is indicated for atopic dermatitis, insomnia and high-risk use of alcohol.

Psychological Treatment of Comorbid Insomnia and Depression: A Double-Blind Randomized Placebo-Controlled Trial.

INTRODUCTION: Insomnia and depression are highly prevalent disorders and commonly occur together. Cognitive behavioral therapy for insomnia, CBT-I, has been shown to be effective in treating insomnia and also comorbid depression. However, it is unclear whether effects of CBT-I on depression are specific or nonspecific. Also, depressive symptoms often remain too high after CBT-I, indicating a need for improved treatments. The objective was to determine whether combining CBT-I with CBT for depression, without increasing treatment length, reduces both insomnia and depression more than CBT for depression with a placebo insomnia intervention. METHODS: A 12-week double-blind randomized controlled trial with a 6-month follow-up in a psychiatric setting using therapist-guided internet-delivered treatments was conducted. Patients (N = 126) were diagnosed with insomnia disorder and major depression by physicians. Primary outcome measures were as follows: self-rating scales Insomnia Severity Index (ISI) and Montgomery-Åsberg Depression Rating Scale (MADRS-S). RESULTS: The combined treatment showed specific effects on insomnia severity over the control treatment (p = 0.007) but was not more effective in reducing depression severity. Within-group effects (Cohen's d) at post and at 6 months were as follows: ISI 1.40 and 1.42 (combined treatment), 0.95 and 1.00 (control); MADRS-S 0.97 and 1.12 (combined), 0.88 and 0.89 (control). CONCLUSIONS: CBT-I shows large specific effects on insomnia severity and is superior to control in this regard. Both treatments had similar effects on depression severity, i.e., combining CBT-I with CBT for depression did not enhance outcomes on depression compared to control. We suggest CBT-I should always be offered to patients with insomnia and depression comorbidity, possibly as the first-hand choice. Combining it with a psychological treatment for depression could be too burdening and may not be beneficial.

Brief digital self-care intervention for health anxiety in a Swedish Medical University Clinic: a prospective single-group feasibility study.

OBJECTIVES: In routine psychiatric care in Stockholm, Sweden, a comprehensive therapist-guided intervention for clinically significant health anxiety is implemented. However, there is a need for more easily accessible self-care interventions to improve treatment dissemination. This study aimed to transform an existing therapist-guided digital intervention into a self-care intervention, reducing patient burden and used clinical resources while maintaining quality and safety. DESIGN: An uncontrolled feasibility study. SETTING: Conducted at Karolinska Institutet, a medical university in Sweden, with nationwide recruitment trough online advertisements. PARTICIPANTS: Twenty-five adults used the self-care intervention and underwent telephone assessments, along with completing self-rated questionnaires. INTERVENTION: The newly developed 8-week self-care intervention was designed to be user-friendly without therapist guidance, and to facilitate high levels of behavioural engagement. PRIMARY AND SECONDARY OUTCOME MEASURES: Indicators of quality and safety, including changes in health anxiety severity (primary), clinician time, participant adherence, perceived credibility/satisfaction with the intervention and adverse events, were benchmarked against a previous study of the more comprehensive intervention it was based on. RESULTS: Compared with the original guided intervention, the self-care intervention was condensed in terms of text (up to 70% less reading), duration (8 weeks instead of 12) and number of exercises. Quality indicators were similar to the original version. Most participants worked actively with core components in the self-care intervention. Within-group effects on health anxiety from pretreatment to the 3-month follow-up were large (g=1.37; 95% CI 0.74 to 2.00). No serious adverse events were reported. CONCLUSIONS: This brief digital self-care intervention shows potential for increasing access to treatment for individuals with health anxiety while reducing the burden on patients and clinical resources. Future studies should investigate the optimal type of intervention and support for different individuals, and if non-inferiority can be established. TRIAL REGISTRATION NUMBER: NCT05446766.

Swedish multimodal cohort of patients with anxiety or depression treated with internet-delivered psychotherapy (MULTI-PSYCH).

PURPOSE: Depression and anxiety afflict millions worldwide causing considerable disability. MULTI-PSYCH is a longitudinal cohort of genotyped and phenotyped individuals with depression or anxiety disorders who have undergone highly structured internet-based cognitive-behaviour therapy (ICBT). The overarching purpose of MULTI-PSYCH is to improve risk stratification, outcome prediction and secondary preventive interventions. MULTI-PSYCH is a precision medicine initiative that combines clinical, genetic and nationwide register data. PARTICIPANTS: MULTI-PSYCH includes 2668 clinically well-characterised adults with major depressive disorder (MDD) (n=1300), social anxiety disorder (n=640) or panic disorder (n=728) assessed before, during and after 12 weeks of ICBT at the internet psychiatry clinic in Stockholm, Sweden. All patients have been blood sampled and genotyped. Clinical and genetic data have been linked to several Swedish registers containing a wide range of variables from patient birth up to 10 years after the end of ICBT. These variable types include perinatal complications, school grades, psychiatric and somatic comorbidity, dispensed medications, medical interventions and diagnoses, healthcare and social benefits, demographics, income and more. Long-term follow-up data will be collected through 2029. FINDINGS TO DATE: Initial uses of MULTI-PSYCH include the discovery of an association between PRS for autism spectrum disorder and response to ICBT, the development of a machine learning model for baseline prediction of remission status after ICBT in MDD and data contributions to genome wide association studies for ICBT outcome. Other projects have been launched or are in the planning phase. FUTURE PLANS: The MULTI-PSYCH cohort provides a unique infrastructure to study not only predictors or short-term treatment outcomes, but also longer term medical and socioeconomic outcomes in patients treated with ICBT for depression or anxiety. MULTI-PSYCH is well positioned for research collaboration.

Treatment feasibility of a digital tool for brief self-help behavioural therapy for insomnia (FastAsleep).

Cognitive behavioural therapy for insomnia is efficacious and recommended for insomnia, but availability is scarce. Cognitive behavioural therapy for insomnia self-help interventions could increase availability, especially if unguided. Optimizing cognitive behavioural therapy for insomnia methods and system user-friendliness, we developed a short, digital, self-help programme-FastAsleep-based on the behavioural components of sleep restriction and stimulus control. This study investigated its feasibility and preliminary effects. Thirty media-recruited participants with moderate to severe insomnia were assessed via telephone before using FastAsleep for 4 weeks, and were interviewed afterwards. Self-ratings with web questionnaires were conducted at screening, pre-, mid- and post-treatment, and at 3-month follow-up. Primary outcomes were feasibility (credibility, adherence, system user-friendliness and adverse effects), and secondary outcomes were changes in symptom severity (insomnia, depression and anxiety). Adherence was generally high, participants' feasibility ratings were favourable, and adverse effects matched previously reported levels for cognitive behavioural therapy for insomnia. Symptoms of insomnia decreased after the treatment period (Hedge's g = 1.79, 95% confidence interval = 1.20-2.39), as did symptoms of depression and anxiety. FastAsleep can be considered feasible and promising for alleviating insomnia symptoms among patients fit for self-care. Future controlled trials are needed to establish the efficacy of FastAsleep and its suitability in a stepped care model.

Corrigendum to "The effect of user interface on treatment engagement in a self-guided digital problem-solving intervention: A randomized controlled trial" [Internet Interv. 26 (2021) 1-10/100448].

[This corrects the article DOI: 10.1016/j.invent.2021.100448.].

Clinically sufficient classification accuracy and key predictors of treatment failure in a randomized controlled trial of Internet-delivered Cognitive Behavior Therapy for Insomnia.

Background: In Adaptive Treatment Strategies, each patient's outcome is predicted early in treatment, and treatment is adapted for those at risk of failure. It is unclear what minimum accuracy is needed for a classifier to be clinically useful. This study aimed to establish a empirically supported benchmark accuracy for an Adaptive Treatment Strategy and explore the relative value of input predictors. Method: Predictions from 200 patients receiving Internet-delivered cognitive-behavioral therapy in an RCT was analyzed. Correlation and logistic regression was used to explore all included predictors and the predictive capacity of different models. Results: The classifier had a Balanced accuracy of 67 %. Eleven out of the 21 predictors correlated significantly with Failure. A model using all predictors explained 56 % of the outcome variance, and simpler models between 16 and 47 %. Important predictors were patient rated stress, treatment credibility, depression change, and insomnia symptoms at week 3 as well as clinician rated attitudes towards homework and sleep medication. Conclusions: The accuracy (67 %) found in this study sets a minimum benchmark for when prediction accuracy could be clinically useful. Key predictive factors were mainly related to insomnia, depression or treatment involvement. Simpler predictive models showed some promise and should be developed further, possibly using machine learning methods.

A self-guided and monitored digital problem-solving intervention for patients with symptoms of depression or anxiety on the waiting list for treatment in routine psychiatric care: feasibility study.

BACKGROUND: There is often a waiting period for people who seek psychiatric treatment for depression or anxiety. As this delay risks worsening symptoms, an alternative could be to provide an intervention that requires minimal resources during the waiting period. AIMS: The aim was to investigate if a digital problem-solving intervention delivered in a self-guided format with automated features is feasible to provide for patients on the waiting list in routine psychiatric care. METHOD: A total of 12 patients with symptoms of depression or anxiety on the waiting list for treatment in routine psychiatric care were given access to a self-guided and monitored digital problem-solving intervention over 4 weeks. Primary outcome measures were treatment credibility and usability. Secondary outcome measures were behavioural engagement, symptoms of depression and anxiety, and negative effects. RESULTS: A majority of participants rated the intervention as both credible and usable. The intervention was used at least once by nine out of 12 individuals, with an average of 11 logins. The participants did, on average, initiate 2.8 problem-solving attempts and 10.1 solutions. A few participants reached a clinically relevant symptom improvement of depression and anxiety. No serious negative effects were reported. CONCLUSIONS: The credibility and usability of the intervention was perceived as good, and the behavioural engagement with the intervention was deemed sufficient compared with similar self-guided interventions. A self-guided and monitored digital problem-solving intervention may be a beneficial option for patients waiting for or receiving treatment in routine psychiatric care, and should be further evaluated.

Very long-term outcome of cognitive behavioral therapy for insomnia: one- and ten-year follow-up of a randomized controlled trial.

Insomnia is a common and chronic disorder, and cognitive behavioral therapy (CBT) is the recommended treatment. Very long-term follow-ups of CBT are very rare, and this study aimed to investigate if improvements were stable one and ten years after CBT for insomnia (CBT-i). Based on a three-armed randomized controlled trial of bibliotherapeutic CBT-i, participants received an insomnia-specific self-help book and were randomized to therapist guidance, no guidance, or a waitlist receiving unguided treatment after a delay. Six weeks of treatment was given to 133 participants diagnosed with insomnia disorder. After one and ten years, participants were assessed with self-reports and interviews. Improvements were statistically significant and well maintained at one- and ten-year follow-ups. Average Insomnia Severity Index score [95%CI] was 18.3 [17.7-18.8] at baseline, 10.1 [9.3-10.9] at post-treatment, 9.2 [8.4-10.0] at one- and 10.7 [9.6-11.8] at ten-year follow-up, and 64% and 66% of participants no longer fulfilled criteria for an insomnia diagnosis at one and ten years, respectively. Positive effects of CBT were still present after ten years. Insomnia severity remained low, and two-thirds of participants no longer fulfilled criteria for an insomnia diagnosis. This extends previous findings of CBT, further confirming it as the treatment of choice for insomnia.

Large-scale implementation of insomnia treatment in routine psychiatric care: patient characteristics and insomnia-depression comorbidity.

Treating comorbid insomnia is important for recovery from, and prevention of, depression. The objective of this study was to compare comorbidity and patient characteristics among patients having treatment for depression before and after implementation of cognitive behavioural therapy for insomnia (CBT-I) in a routine care internet treatment clinic. We hypothesized that insomnia comorbidity would be lower among patients having treatment for depression after the treatment for insomnia became available, and that depression levels would be high among patients in the insomnia treatment group compared to previous studies of insomnia. Patients were assessed face-to-face by physicians and guided through internet-delivered treatment by psychologists in a psychiatric setting. We retrieved patient data from 3 years before and 3 years after the CBT-I implementation. Measures were the Montgomery-Åsberg Depression Rating Scale-Self rated (MADRS-S) and Insomnia Severity Index (ISI). Pretreatment symptom levels were high in both the depression (MADRS-S = 23, n = 1467) and insomnia treatment (ISI = 20, n = 552) groups, indicating a true psychiatric sample. Contrary to the hypothesis, there were no significant changes in the group having treatment for depression regarding insomnia severity or comorbid insomnia diagnosis (from 66% to 68%) after CBT-I implementation. Also contrary to the hypothesis, comorbid depression levels among insomnia patients having CBT-I were similar to or slightly higher than in previous studies. It is likely that more patients with this comorbidity, who currently receive treatment for depression, would benefit from CBT-I. We suggest an emphasis on information on the benefits of CBT-I among patients and clinical staff involved in the implementation of treatments for insomnia in psychiatry, and further research into possible differences between patients actively seeking treatment for insomnia or depression.

Practical and Emotional Problems Reported by Users of a Self-guided Digital Problem-solving Intervention During the COVID-19 Pandemic: Content Analysis.

BACKGROUND: To better direct assessments and interventions toward the general population during both the ongoing COVID-19 pandemic and future crises with societal restrictions, data on the types of practical and emotional problems that people are experiencing are needed. OBJECTIVE: The aim of this study was to examine the types of practical and emotional problems that the general population is experiencing during the COVID-19 pandemic and to construct an empirically derived inventory based on the findings. METHODS: A total of 396 participants, recruited among members of the general public in Sweden who were experiencing practical and/or emotional problems during the pandemic, accessed a self-guided digital problem-solving intervention for a period of 1 week to report and solve the problems they experienced. Prior to accessing the intervention, the participants completed a short self-assessment regarding symptoms of depression and anxiety. Content analysis was used to account for the types of problems participants reported. A set of items for an inventory was later proposed based on the problem categories derived from the analysis. RESULTS: A majority of participants had clinically relevant symptoms of either depression or anxiety. The problems reported were categorized as 13 distinct types of problems. The most common problem was difficulty managing daily activities. Based on the categories, a 13-item inventory was proposed. CONCLUSIONS: The 13 types of problems, and the proposed inventory, could be valuable when composing assessments and interventions for the general population during the ongoing pandemic or similar crises with societal restrictions. The most common problem was of a practical nature, indicating the importance of including examples of such problems within assessments and interventions. TRIAL REGISTRATION: ClinicalTrials.gov NCT04677270; https://clinicaltrials.gov/ct2/show/NCT04677270.

The effect of user interface on treatment engagement in a self-guided digital problem-solving intervention: A randomized controlled trial.

BACKGROUND: Resources are spent worldwide on the development of digital platforms and their user interfaces (UIs) for digital mental health services (DMHS). However, studies investigating the potential benefits of different UIs for DMHS are currently lacking. To fill this knowledge gap, the aim of this study was to investigate differences in treatment engagement between two different UIs for DMHS. METHODS: A total of 397 participants from the Swedish general public were randomized (1:1) to use a self-guided digital problem-solving intervention during one week, either with an optimized UI (N = 198), based on user experience (UX) design principles and with automated features, or a basic UI (N = 199), analogous with a UI used in Swedish regular health care comprising elementary UI features and less automation. Primary outcome measures were self-rated usability, on the System Usability Scale, and treatment credibility, on the Credibility/Expectancy Questionnaire. Secondary outcome measures included behavioral engagement with the intervention. FINDINGS: There were no significant differences between the UIs in ratings of usability or treatment credibility. However, participants who used the optimized UI were significantly more engaged with the intervention as measured by usage of the intervention at least once (odds ratio 2.54, 95% CI [1.67, 3.85]), total number of generated solutions (mean difference 1.41, 95% CI [0.72, 2.11]), and mean number of generated solutions per initiated problem-solving attempt (mean difference 1.45, 95% CI [1.06, 1.85]). Other findings included participants using the optimized UI rating the intervention as easier to understand, while feeling more overwhelmed, than those using the basic UI. INTERPRETATION: Our findings indicate that an optimized UI based on UX design principles, in comparison to a basic UI comprising elementary UI features, do not affect overall self-rated usability or treatment credibility but increases some measures of behavioral engagement with a digital intervention. FUNDING: Funded by the Government of Sweden, Ministry of Health and Social Affairs.

Initial Low Levels of Suicidal Ideation Still Improve After Cognitive Behavioral Therapy for Insomnia in Regular Psychiatric Care.

Insomnia disorder is highly prevalent, and has been identified as a risk factor for many psychiatric problems, including depression, suicide ideation and suicide death. Previous studies have found that cognitive behavioral therapy for insomnia (CBT-I) reduce depression and suicidal ideation in samples with high levels of suicidal ideation. This study aims to investigate associations of CBT-I with suicidal ideation in a sample of 522 patients primarily seeking internet-delivered treatment for insomnia in regular psychiatric care. The sample had high pretreatment insomnia severity levels and a relatively high level of comorbid depression symptoms. Suicidal ideation levels were relatively low pretreatment but still improved significantly after CBT-I. Contrary to previous findings, the strongest predictor of changes in suicidal ideation were improvements in depressive symptoms, rather than improvements in insomnia. We conclude that suicidal ideation may not be a major problem in these patients primarily seeking treatment for insomnia, despite comorbid depressive symptoms, but that suicidal ideation still improves following CBT-i. Considering the increased risk for patients with untreated insomnia to develop depression, this finding is of interest for prevention of suicidal ideation.

An investigation and replication of sleep-related cognitions, acceptance and behaviours as predictors of short- and long-term outcome in cognitive behavioural therapy for insomnia.

The objectives were to investigate the potential for sleep-related behaviours, acceptance and cognitions to predict outcome (insomnia severity) of cognitive behavioural therapy for insomnia (CBT-I). Baseline and outcome data from four randomised controlled trials (n = 276) were used. Predictors were the Dysfunctional Beliefs and Attitudes about Sleep-10 (DBAS-10), Sleep-Related Behaviours Questionnaire (SRBQ), and Sleep Problems Acceptance Questionnaire (SPAQ), and empirically derived factors from a factor analysis combining all items at baseline (n = 835). Baseline values were used to predict post-treatment outcome, and pre-post changes in the predictors were used to predict follow-up outcomes after 3-6 months, 1 year, or 3-10 years, measured both as insomnia severity and as better or worse long-term sleep patterns. A majority (29 of 52) of predictions of insomnia severity were significant, but when controlling for insomnia severity, only two (DBAS-10 at short-term and SRBQ at mid-term follow-up) of the 12 predictions using established scales, and three of the 40 predictions using empirically derived factors, remained significant. The strongest predictor of a long-term, stable sleep pattern was insomnia severity reduction during treatment. Using all available predictors in an overfitted model, 21.2% of short- and 58.9% of long-term outcomes could be predicted. We conclude that although the explored constructs may have important roles in CBT-I, the present study does not support that the DBAS-10, SRBQ, SPAQ, or factors derived from them, would be unique predictors of outcome.

Dismantling, optimising, and personalising internet cognitive behavioural therapy for depression: a systematic review and component network meta-analysis using individual participant data.

BACKGROUND: Internet cognitive behavioural therapy (iCBT) is a viable delivery format of CBT for depression. However, iCBT programmes include training in a wide array of cognitive and behavioural skills via different delivery methods, and it remains unclear which of these components are more efficacious and for whom. METHODS: We did a systematic review and individual participant data component network meta-analysis (cNMA) of iCBT trials for depression. We searched PubMed, PsycINFO, Embase, and the Cochrane Library for randomised controlled trials (RCTs) published from database inception to Jan 1, 2019, that compared any form of iCBT against another or a control condition in the acute treatment of adults (aged ≥18 years) with depression. Studies with inpatients or patients with bipolar depression were excluded. We sought individual participant data from the original authors. When these data were unavailable, we used aggregate data. Two independent researchers identified the included components. The primary outcome was depression severity, expressed as incremental mean difference (iMD) in the Patient Health Questionnaire-9 (PHQ-9) scores when a component is added to a treatment. We developed a web app that estimates relative efficacies between any two combinations of components, given baseline patient characteristics. This study is registered in PROSPERO, CRD42018104683. 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. INTERPRETATION: The individual patient data cNMA revealed potentially helpful, less helpful, or harmful components and delivery formats for iCBT packages. iCBT packages aiming to be effective and efficient might choose to include beneficial components and exclude ones that are potentially detrimental. Our web app can facilitate shared decision making by therapist and patient in choosing their preferred iCBT package. FUNDING: Japan Society for the Promotion of Science.

A very brief self-report scale for measuring insomnia severity using two items from the Insomnia Severity Index - development and validation in a clinical population.

OBJECTIVE: To develop a very brief scale with selected items from the Insomnia Severity Index (ISI), and to investigate the psychometric properties of the proposed scale in a psychiatric sample. METHODS: Patient data from seven Cognitive Behavioral Therapy (CBT) for insomnia trials and from regular care were used in psychometric analyses (N = 280-15 653). The samples included patients screening (N = 6936) or receiving treatment (N = 1725) for insomnia and other psychiatric conditions. Six criteria relating to component structure, sensitivity to change and clinical representativeness were used to select items. Psychometric analyses for the proposed very brief scale were performed. RESULTS: One item representing satisfaction/dissatisfaction with current sleep pattern and one item representing interferences with daily functioning, were selected to create the 2-item ISI version. Correlations with the full scale were high at screening, pre and post, and for change (0.82-0.94). Categorical omega was ⍵C = 0.86. With a cut-off of 6 points, the scale could detect Insomnia Disorder with a sensitivity of 84% and a specificity of 76%, which was close to the full ISI showing 86% and 80% respectively. CONCLUSIONS: The systematic psychometric evaluation based on a large sample from different contexts makes the proposed 2-item ISI version (ISI-2) a strong candidate for a very brief scale measuring insomnia, both for detecting cases and for measuring change during CBT with an overall high discriminative validity. ISI-2 is especially useful in clinical settings or population studies where there is a need to measure more than one condition at a time without overburdening patients. CLINICAL TRIALS: Trials used in this analysis: ClinicalTrials.gov identifier: NCT01105052 (https://www.clinicaltrials.gov/ct2/show/NCT01105052) (sample b), ClinicalTrials.gov identifier: NCT01256099 (https://clinicaltrials.gov/ct2/show/NCT01256099) (sample c and d), German clinical trial (DRKS), registration ID: DRKS00008745 (https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00008745) (sample e), ClinicalTrials.gov identifier: NCT01663844 (https://clinicaltrials.gov/ct2/show/NCT01663844) (sample f and g), ClinicalTrials.gov Identifier: NCT02743338 (https://clinicaltrials.gov/ct2/show/NCT02743338) (sample h).

Internet-Based Cognitive Behavioral Therapy for Depression: A Systematic Review and Individual Patient Data Network Meta-analysis.

Importance: Personalized treatment choices would increase the effectiveness of internet-based cognitive behavioral therapy (iCBT) for depression to the extent that patients differ in interventions that better suit them. Objective: To provide personalized estimates of short-term and long-term relative efficacy of guided and unguided iCBT for depression using patient-level information. Data Sources: We searched PubMed, Embase, PsycInfo, and Cochrane Library to identify randomized clinical trials (RCTs) published up to January 1, 2019. Study Selection: Eligible RCTs were those comparing guided or unguided iCBT against each other or against any control intervention in individuals with depression. Available individual patient data (IPD) was collected from all eligible studies. Depression symptom severity was assessed after treatment, 6 months, and 12 months after randomization. Data Extraction and Synthesis: We conducted a systematic review and IPD network meta-analysis and estimated relative treatment effect sizes across different patient characteristics through IPD network meta-regression. Main Outcomes and Measures: Patient Health Questionnaire-9 (PHQ-9) scores. Results: Of 42 eligible RCTs, 39 studies comprising 9751 participants with depression contributed IPD to the IPD network meta-analysis, of which 8107 IPD were synthesized. Overall, both guided and unguided iCBT were associated with more effectiveness as measured by PHQ-9 scores than control treatments over the short term and the long term. Guided iCBT was associated with more effectiveness than unguided iCBT (mean difference [MD] in posttreatment PHQ-9 scores, -0.8; 95% CI, -1.4 to -0.2), but we found no evidence of a difference at 6 or 12 months following randomization. Baseline depression was found to be the most important modifier of the relative association for efficacy of guided vs unguided iCBT. Differences between unguided and guided iCBT in people with baseline symptoms of subthreshold depression (PHQ-9 scores 5-9) were small, while guided iCBT was associated with overall better outcomes in patients with baseline PHQ-9 greater than 9. Conclusions and Relevance: In this network meta-analysis with IPD, guided iCBT was associated with more effectiveness than unguided iCBT for individuals with depression, benefits were more substantial in individuals with moderate to severe depression. Unguided iCBT was associated with similar effectiveness among individuals with symptoms of mild/subthreshold depression. Personalized treatment selection is entirely possible and necessary to ensure the best allocation of treatment resources for depression.

Predicting treatment failure in regular care Internet-Delivered Cognitive Behavior Therapy for depression and anxiety using only weekly symptom measures.

OBJECTIVE: Therapist guided Internet-Delivered Cognitive Behavior Therapy (ICBT) is effective, but as in traditional CBT, not all patients improve, and clinicians generally fail to identify them early enough. We predict treatment failure in 12-week regular care ICBT for Depression, Panic disorder and Social anxiety disorder, using only patients' weekly symptom ratings to identify when the accuracy of predictions exceed 2 benchmarks: (a) chance, and (b) empirically derived clinician preferences for actionable predictions. METHOD: Screening, pretreatment and weekly symptom ratings from 4310 regular care ICBT-patients from the Internet Psychiatry Clinic in Stockholm, Sweden was analyzed in a series of regression models each adding 1 more week of data. Final score was predicted in a holdout test sample, which was then categorized into Success or Failure (failure defined as the absence of both remitter and responder status). Classification analyses with Balanced Accuracy and 95% Confidence intervals was then compared to predefined benchmarks. RESULTS: Benchmark 1 (better than chance) was reached 1 week into all treatments. Social anxiety disorder reached Benchmark 2 (> 65%) at week 5, whereas Depression and Panic Disorder reached it at week 6. CONCLUSIONS: For depression, social anxiety and panic disorder, prediction with only patient-rated symptom scores can detect treatment failure 6 weeks into ICBT, with enough accuracy for a clinician to take action. Early identification of failing treatment attempts may be a viable way to increase the overall success rate of existing psychological treatments by providing extra clinical resources to at-risk patients, within a so-called Adaptive Treatment Strategy. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Development of a very brief scale for detecting and measuring panic disorder using two items from the Panic Disorder Severity Scale-Self Report.

OBJECTIVE: To minimize the burden in detecting and monitoring Panic Disorder and Agoraphobia by developing a very brief scale with selected items from the Panic Disorder Severity Scale-Self Report (PDSS-SR), and to investigate the proposed scale's psychometric properties in a comorbid sample. METHODS: A sample of 5103 patients from the Internet Psychiatry Clinic in Sweden, diagnosed and treated with Internet-based cognitive behavioral therapy for panic disorder (n = 1390), social anxiety disorder (n = 1313) or depression (n = 2400), responded to the PDSS-SR. Six criteria related to factor structure, sensitivity to change and clinical representativeness were used to select items. Psychometric analyses for the selected very brief scale were performed. RESULTS: Items 2 (distress during panic attacks) and 4 (agoraphobic avoidance), were selected to create the very brief PDSS-SR version. Correlations with the full scale were high at screening, pre and post, and for change (0.87-0.93). Categorical Omega was ⍵C = 0.74. With a cut-off of 3 points, the scale could detect panic disorder in a psychiatric sample with a sensitivity of 85% and a specificity of 66%. LIMITATIONS: Limitations include lack of healthy controls and lack of blinding on secondary outcome measures. CONCLUSION: The proposed 2-item PDSS-SR version is a good candidate for a very brief panic disorder questionnaire, both for detecting cases and for measuring change. This is especially useful in clinical settings when measuring more than one condition at a time.