Objective: Early identification of failing psychological treatments could be of high clinical value, but therapists themselves have been found to be bad at predicting who will benefit or not. Previous research has some methodological limitations, and therapists' predictive accuracy has never been examined in internet-delivered treatments. Method: Therapists providing internet-delivered cognitive behavior therapy for depression, social anxiety disorder, and panic disorder in routine psychiatric care made outcome predictions for 897 patients during the fourth week of treatment. Therapists' accuracies were also compared to the accuracy of a simple statistical model and benchmarks for clinically acceptable/useful levels of accuracy from previous research. Results: Therapists were more accurate than chance, but their balanced accuracy was on average nine percentage points lower than the balanced accuracy of the statistical model (though confidence intervals often overlapped) and only in one case did the predictions reach the clinical acceptance and utility benchmarks. Therapists could predict on average 16% of the variance in outcome. Therapists were overly optimistic, predicting positive outcomes on average twice as often as they occurred. They differed in confidence in their predictions, though this did not affect how correct they were. Conclusions: Internet-delivered cognitive behavior therapy-therapists can often predict treatment outcomes better than chance, but generally not as well as the statistical model, and probably not accurately enough that they would be willing to act on their predictions, or that they could be used in an adaptive treatment strategy. Our previous findings suggest that patients would benefit from statistical monitoring and prediction tools in clinical settings.

Background: Symptom reduction occurring early in depression treatment is associated with favourable posttreatment outcome, but it is not known how early reduction in specific depression symptoms affect treatment outcome. We aimed to determine the impact of symptom-specific change from pre-treatment to week four during internet-delivered CBT (ICBT) on overall and symptom-specific depression severity at post-treatment. We hypothesized that change in mood and emotional involvement would be most strongly associated with later overall depression severity.

Methods: 1300 participants with Major Depressive Disorder were followed over 12 weeks of ICBT using the selfreport Montgomery-& Aring;sberg Depression Rating Scale gauging nine symptoms. Linear models, informed by causal inference and cross-lagged network analysis methods, were used to estimate associations between early symptom-specific change and post-treatment depression severity, controlling for register-based and self-reported pre-treatment confounders.

Results: Early reduction in all symptoms was associated with lower overall and symptom-specific depression severity post-ICBT. Seven symptoms showed similar associations between early change and overall depression severity post-treatment: mood (standardized beta [(3] = 0.44), feelings of unease ((3 = 0.39), ability to concentrate ((3 = 0.46), initiative ((3 = 0.43), emotional involvement ((3 = 0.42), pessimism ((3 = 0.44), and zest for life ((3 = 0.42). Change in sleep ((3 = 0.27) and appetite ((3 = 0.27) had weaker associations with overall depression severity at post-treatment and were the only symptoms showing the hypothesized difference compared with mood and emotional involvement.

Conclusions: The impact of early symptom-specific reduction on post-treatment depression severity in ICBT for MDD may be similar across most symptoms, but less for the sleep and appetite symptoms, although causal interpretations rests on several assumptions.

Study Objectives Insomnia disorder, affecting 10% of the population, poses a significant public health concern and is a risk-factor for many health issues. Cognitive behavioral therapy is first-choice treatment, but the key component-sleep restriction therapy-presents with side effects and adherence challenges. Sleep compression therapy, suggested as a potentially gentler alternative, has never been directly compared to sleep restriction therapy.Methods Single-blind trial at the Internet Psychiatry Clinic in Stockholm, Sweden. Patients with insomnia disorder were randomized 1:1 to evaluate non-inferiority of sleep compression therapy to sleep restriction therapy in improving insomnia and to compare important clinical aspects. Primary outcome: self-reported Insomnia Severity Index (ISI), assessed pretreatment, weeks 1-5, and week 10. Non-inferiority analysis based on intent-to-treat analyses with multiple imputation and mixed effects models.Results Adults with insomnia (n = 234; mean age 44.3 [SD = 13.7] years, 173 [73.4%] female) received treatment as a 10-week highly structured, therapist-guided online program, to strengthen experimental integrity and treatment fidelity. Both treatments improved insomnia severity with large effects. Sleep compression therapy failed to show non-inferiority with a conservative limit of 1.6 ISI-points (95% CI: -0.01, 1.70), gave statistically significantly smaller improvements (p = .006), and was associated with slower improvements despite better adherence and somewhat less side effects.Conclusions This direct comparison and well-controlled trial provides empirically based support for clinicians to prioritize sleep restriction therapy over sleep compression therapy, while the latter can be a valid alternative when sleep restriction therapy cannot be used.Clinical Trial CompRest-a Comparison Between Sleep Compression and Sleep Restriction for Treating Insomnia. URL: https://clinicaltrials.gov/study/NCT02743338?term=NCT02743338&rank=1Registration NCT02743338.

Restless legs syndrome (RLS) is a highly prevalent condition that significantly disrupts sleep and causes reduced quality of life. While previous RLS research has mainly focused on the pharmacological treatment, this study presents the first instrument to measure self-care, the RLS-Self-care Behaviour questionnaire (RLS-ScBq). Self-care, defined as an active decision-making process, can empower patients to effectively participate in their own healthcare through awareness, self-control, and self-reliance to cope with their disease. Self-care can in a RLS context include actions such as physical exercise, meditation, and massage. Hence, the aim of this study is to explore the psychometric properties of the RLS-ScBq in patients with RLS. A cross-sectional design, including 788 patients with RLS (65% women, mean age 70.8 years, [standard deviation (SD) =11.4]) was used. Sociodemographics, comorbidities, and RLS-related treatment data, including insomnia symptoms (i.e., Insomnia Severity Index), daytime sleepiness (i.e., Epworth Sleepiness Scale) and RLS symptoms (i.e., RLS-6 scale) were collected. The validity and reliability of the RLS-ScBq were investigated using exploratory factor analysis and Rasch models. The two-factor solution (i.e., physical, and mental actions) showed an explained variance of 32.33% for The Self-care Behaviour Frequency part and 36.28% for The Benefit of Self-care Behaviour part. The internal consistency measured by Cronbach's alpha was 0.57 and 0.60, and McDonald's omega was 0.60 and 0.67, respectively. No differential item functioning was identified for gender, age, insomnia, daytime sleepiness, or RLS severity. The eight-item RLS-ScBq can serve as a tool enabling healthcare personnel to explore use and benefit of self-care activities in patients with RLS.

Introduction: Therapist-supported internet-based Cognitive Behavioural Therapy (ICBT) has strong scientific support, but all patients are not helped, and further improvements are needed. Personalized medicine could enhance ICBT. One promising approach uses a Machine learning (ML) based predictive decision support tool (DST) to help therapists identify patients at risk of treatment failure and adjust their treatments accordingly. ICBT is a suitable clinical context for developing and testing such predictive DST's, since its delivery is quite flexible and can quickly be adapted for probable non-responders, for example by increasing the level and nature of therapist support, to avoid treatment failures and improve overall outcomes. This type of strategy has never been tested in a triple-blind randomised controlled trial (RCT) and has rarely been studied in ICBT. The aim of this protocol is to expand on previous registered protocols with more detailed descriptions of methods and analyses before analyses is being conducted. Methods and analysis: A triple blind RCT comparing ICBT with a DST (DST condition), to ICBT as usual (TAU condition). The primary objective is to evaluate if the DST condition is superior to the TAU condition in decreasing diagnose-specific symptoms among patients identified to be at risk of failure. Secondary objectives are to evaluate if the DST improves functioning, interaction, adherence, patient satisfaction, and therapist time efficiency and decreases the number of failed treatments. Additionally, we will investigate the therapists' experience of using the DST. Patients and therapists have been recruited nationally. They were randomised and given a sham rationale for the trial to ensure allocation blindness. The total number of patients included was 401, and assessments were administered pre-treatment, weekly during treatment, at post-treatment and at 12-month follow-up. Primary outcome is one of the three diagnosis-specific symptom rating scales for respective treatment and primary analysis is difference in change from pre- to post-treatment for at-risk patients on these scales. Human ethics and consent to participate: Informed consent to participate in the study was obtained from all participants. Both therapists and patients are participants in this trial. For patients, informed consent to participate in the study was obtained when they registered interest for the study via the study's secure web platform and carried out initial screening before the diagnostic and fit for treatment assessment, they first received the research subject information and were asked for consent by digitally signing that they had read and understood the information. For therapists who were part of the study, consent was requested after they had registered their interest. Therapists then received an email with a link to the study's secure web platform with the research person's information and were asked for consent by digitally signing that they had read and understood the information. All documents are stored in secure, locked filing cabinets on the clinic's premises or on a secure digital consent database. Approval committee: Approved by the Swedish Ethical Review Authority (SERA), record number 2020-05772.

With the impetus of Digital Mental Health Interventions (DMHIs), complex data can be leveraged to improve and personalize mental health care. However, most approaches rely on a very limited number of often costly features. Computer mouse trajectories can be unobtrusively and cost-efficiently gathered and seamlessly integrated into current baseline processes. Empirical evidence suggests that mouse movements hold information on user motivation and attention, both valuable aspects otherwise difficult to measure at scale. Further, mouse trajectories can already be collected on pre-treatment questionnaires, making them a promising candidate for early predictions informing treatment allocation. Therefore, this paper discusses how to collect and process mouse trajectory data on questionnaires in DMHIs. Covering different complexity levels, we combine hand-crafted features with non-sequential machine learning models, as well as spatiotemporal raw mouse data with stateof-the-art sequential neural networks. The data processing pipeline for the latter includes task-specific preprocessing to convert the variable length trajectories into a single prediction per user. As a feasibility study, we collected mouse trajectory data from 183 patients filling out a pre-intervention depression questionnaire. While the hand-crafted features slightly improve baseline predictions, the spatiotemporal models underperform. However, considering our small data set size, we propose more research to investigate the potential value of this novel and promising data type and provide the necessary steps and open-source code to do so.

Background. Online treatments are increasing in number and are currently available for a wide range of clinical problems. To date little is known about the role of treatment expectations and other placebo-like mechanisms in online settings compared to traditional face-to-face treatment. To address this knowledge gap, we analyzed individual participant data from randomized clinical trials that compared online and face-to-face psychological interventions.Methods. MEDLINE (Ovid) and PsycINFO (Ovid) were last searched on 2 February 2021. Randomized clinical trials of therapist guided online v. face-to-face psychological interventions for psychiatric or somatic conditions using a randomized controlled design were included. Titles, abstracts, and full texts of studies were independently screened by multiple observers. The Preferred Reporting Items for Systematic Reviews and Meta-analyses guideline was followed. Authors of the matching trials were contacted for individual participant data. Ratings from the Credibility and Expectancy Questionnaire and the primary outcome measure from each trial were used to estimate the association between expectation ratings and treatment outcomes in online v. face-to-face interventions, using a mixed-effects model.Results. Of 7045 screened studies, 62 full-text articles were retrieved whereof six studies fulfilled the criteria and provided individual participant data (n = 491). Overall, CEQ ratings predicted clinical outcomes (beta = 0.27) at end of treatment with no moderating effect of treatment modality (online v. face-to-face).Conclusions. Online treatment appears to be equally susceptible to expectancy effects as face-to-face therapy. This furthers our understanding of the importance of placebo-like factors in online treatment and may aid the improvement of healthcare in online settings.

Objective: This study proposes a way of increasing dataset sizes for machine learning tasks in Internet-based Cognitive Behavioral Therapy through pooling interventions. To this end, it (1) examines similarities in user behavior and symptom data among online interventions for patients with depression, social anxiety, and panic disorder and (2) explores whether these similarities suffice to allow for pooling the data together, resulting in more training data when prediction intervention dropout. Methods: A total of 6418 routine care patients from the Internet Psychiatry in Stockholm are analyzed using (1) clustering and (2) dropout prediction models. For the latter, prediction models trained on each individual intervention's data are compared to those trained on all three interventions pooled into one dataset. To investigate if results vary with dataset size, the prediction is repeated using small and medium dataset sizes. Results: The clustering analysis identified three distinct groups that are almost equally spread across interventions and are instead characterized by different activity levels. In eight out of nine settings investigated, pooling the data improves prediction results compared to models trained on a single intervention dataset. It is further confirmed that models trained on small datasets are more likely to overestimate prediction results. Conclusion: The study reveals similar patterns of patients with depression, social anxiety, and panic disorder regarding online activity and intervention dropout. As such, this work offers pooling different interventions’ data as a possible approach to counter the problem of small dataset sizes in psychological research.

This narrative historical review examines the development of internet-based cognitive behavioral therapy (ICBT) in Sweden, describing its progression within both academic and routine care settings. The review encompasses key publications, significant scientific findings, and contextual factors in real-world settings. Over 25 years ago, Sweden emerged as a pioneering force in internet-delivered treatment research for mental health. Since then, Swedish universities, in collaboration with research partners, have produced substantial research demonstrating the efficacy of ICBT across various psychological problems, including social anxiety disorder, panic disorder, generalized anxiety disorder, and depression. Although research conducted in clinical settings has been less frequent than in academic contexts, it has confirmed the effectiveness of therapist-supported ICBT programs for mild-to-moderate mental health problems in routine care. Early on, ICBT was provided as an option for patients at both the primary care level and in specialized clinics, using treatment programs developed by both public and private providers. The development of a national platform for delivering internet-based treatment and the use of procurement in selecting ICBT programs and providers are factors that have shaped the current routine care landscape. However, gaps persist in understanding how to optimize the integration of digital treatment in routine care, warranting further research and the use of specific implementation frameworks and outcomes. This historical perspective on the research and delivery of ICBT in Sweden over two decades offers insights for the international community into the development and broad dissemination of a specific digital mental health intervention within a national context.

Background: Dental phobia (DP) and injection phobia (IP) are common in children and adolescents and are considered some of the biggest obstacles to successful treatment in pediatric dentistry. Cognitive behavioral therapy (CBT) is an evidence -based treatment for anxiety and phobias. As the availability of CBT in dentistry is low, internet-based CBT (ICBT) was developed. Open trials have shown that ICBT is a promising intervention, but randomized trials are lacking. Objective: This randomized controlled trial tests whether therapist -guided ICBT supported by a parent could reduce fear, allowing children and adolescents with DP or IP to receive dental treatment. Methods: We enrolled 33 participants (mean age 11.2, SD 1.9 y) whom a clinical psychologist had diagnosed with DP, IP, or both. After inclusion, participants were randomized to either ICBT (17/33, 52%) or a control group of children on a waitlist (16/33, 48%). ICBT was based on exposure therapy and comprised a 12 -week at-home program combined with visits to their regular dental clinic. Participants corresponded weekly with their therapist after completing each module, and 1 parent was designated as a coach to support the child in the assignments during treatment. All participants completed measurements of the outcome variables before treatment start and after 12 weeks (at treatment completion). The measurements included a structured diagnostic interview with a clinical psychologist. Our primary outcome measure was the Picture -Guided Behavioral Avoidance Test (PG -BAT), which assesses the ability to approach 17 dental clinical procedures, and a positive clinical diagnosis. Secondary outcome measures included self -report questionnaires that measured self -efficacy and levels of dental and injection anxiety. The children and their parents completed the questionnaires. Results: All participants underwent the 12 -week follow-up. After treatment, 41% (7/17) of the participants in the ICBT group no longer met the diagnostic criteria for DP or IP, whereas all participants in the control group did (P=.004). Repeated -measure ANOVAs showed that ICBT led to greater improvements on the PG -BAT compared with the control group; between -group effect sizes for the Cohen d were 1.6 (P<.001) for the child -rated PG -BAT and 1.0 (P=.009) for the parent -rated PG -BAT. Reductions in our secondary outcomes-dental fear and anxiety (P<.001), negative cognitions (P=.001), and injection fear (P=.011)-as well as improvements in self -efficacy (P<.001), were all significantly greater among children in the ICBT group than in the controls. No participants reported adverse events. Conclusions: ICBT seems to be an effective treatment for DP and IP in children and adolescents. It reduced fear and anxiety and enabled participants to willingly receive dental treatment. ICBT should be seriously considered in clinical practice to increase accessibility; this therapy may reduce the need for sedation and restraint and lead to better dental health in children and adolescents.