In the Absence of Effects: An Individual Patient Data Meta-Analysis of Non-response and Its Predictors in Internet-Based Cognitive Behavior Therapy

Making the most out of timeseries symptom data: A machine learning study on symptom predictions of internet-based CBT

Objective

Predicting who will not benefit enough from Internet-Based Cognitive Behavioral (ICBT) Therapy early on can assist in better allocation of limited mental health care resources. Repeated measures of symptoms during treatment is the strongest predictor of outcome, and we want to investigate if methods that explicitly account for time-dependency are superior to methods that do not, with data from (a) only two pre-treatment timepoints and (b) the pre-treatment timepoints and three timepoints during initial treatment.

Methods

We use 1) commonly used time-independent methods (i.e., Linear Regression and Random Forest models) and 2) time-dependent methods (i.e., multilevel model regression, mixed-effects random forest, and a Long Short-Term Memory model) to predict symptoms during treatment, including the final outcome. This is done with symptom scores from 6436 ICBT patients from regular care, using robust multiple imputation and nested cross-validation methods.

Results

The models had a 14 %-12 % root mean squared error (RMSE) in predicting the post-treatment outcome, corresponding to a balanced accuracy of 67-74 %. Time-dependent models did not have higher accuracies. Using data for the initial treatment period (b) instead of only from before treatment (a) increased prediction results by 1.3 % percentage points (12 % to 10.7 %) RMSE and 6 % percentage points BACC (69 % to 75 %).

Conclusion

Training prediction models on only symptom scores of the first few weeks is a promising avenue for symptom predictions in treatment, regardless of which model is used. Further research is necessary to better understand the interaction between model complexity, dataset length and width, and the prediction tasks at hand.

Methodological choices and clinical usefulness for machine learning predictions of outcome in Internet-based cognitive behavioural therapy

BACKGROUND

While psychological treatments are effective, a substantial portion of patients do not benefit enough. Early identification of those may allow for adaptive treatment strategies and improved outcomes. We aimed to evaluate the clinical usefulness of machine-learning (ML) models predicting outcomes in Internet-based Cognitive Behavioural Therapy, to compare ML-related methodological choices, and guide future use of these.

METHODS

Eighty main models were compared. Baseline variables, weekly symptoms, and treatment activity were used to predict treatment outcomes in a dataset of 6695 patients from regular care.

RESULTS

We show that the best models use handpicked predictors and impute missing data. No ML algorithm shows clear superiority. They have a mean balanced accuracy of 78.1% at treatment week four, closely matched by regression (77.8%).

CONCLUSIONS

ML surpasses the benchmark for clinical usefulness (67%). Advanced and simple models perform equally, indicating a need for more data or smarter methodological designs to confirm advantages of ML.

Understanding change from the patient perspective in a transdiagnostic Internet-based intervention for emotional disorders: a qualitative content analysis

Qualitative investigations that openly explore changes and facilitators of changes from the patient's perspective might offer valuable insights on impacts of therapy and helpful and hindering aspects. Our aim for this study was to explore the perspective of patients on a transdiagnostic Internet-based intervention to understand (1) which changes (positive as well as negative effects) responders and non-responders experienced, and (2) which aspects of the intervention they found helpful or hindering in facilitating those changes. We interviewed 21 patients that showed response or non-response to treatment using the Change Interview Schedule following a 10-week Internet-based intervention based on the Unified Protocol. Interviews were analyzed using qualitative content analysis. Both responders and non-responders reported positive changes, with few negative changes mentioned. Across both groups, increased positive affect was reported most frequently (81%). Both groups reported helpful factors, with guidance mentioned most frequently across both responders and non-responders (85.7%). Mainly, aspects of the specific framework were perceived as hindering (e.g. lack of personalization) (66.7%). Overall, patients reported mostly positive impacts, even if they did not respond to treatment. Results highlighted that what patients find helpful or hindering is individual.

Evaluation of additional resources used in therapist-assisted transdiagnostic internet-delivered cognitive behaviour therapy

Background

In internet-delivered cognitive behavioural therapy (ICBT) programs, beyond standardized core ICBT lessons, brief additional resources are sometimes available to clients to address comorbid concerns or offer additional information/strategies. These resources remain understudied in terms of how they are selected and perceived by clients, as well as their relationship to satisfaction and outcomes.

Methods

Among clients (N = 793) enrolled in a 5-lesson transdiagnostic ICBT course, we examined client use and perceptions of 18 additional resources at 8 weeks in terms of whether clients found resources informative (yes/no) and or helpful (yes/no). Resources elaborated on cognitive strategies (managing beliefs, risk calculation) or on managing specific problems (agricultural stress, alcohol misuse, anger, assertiveness, chronic conditions, communication, grief, health anxiety, motivation, pain, panic, postpartum depression/anxiety, PTSD, sleep, workplace accomodations, worry). Clients also completed symptom measures and ICBT satisfaction questions at 8 weeks.

Results

Approximately 50 % (n = 398) of clients rated the resources and, on average, clients reported that 3.35 (SD = 3.34) resources were informative and 2.35 (SD = 2.52) resources were helpful as measured by direct questions developed for this study. Higher pre-treatment PTSD and GAD scores were related to a greater number of resources perceived as informative and or helpful. Rating more resources as informative and or helpful had a weak but positive association with ICBT satisfaction and depression, anxiety, PTSD and insomnia change scores. Limitations of the study include that 31 % (n = 245) did not respond to questions about use of resources and 18.9 % (n = 150) said they did not review resources.

Conclusions

There is considerable use of diverse additional resources in ICBT in routine care. Associations suggest that clients are using resources to personalize treatment to their needs and these resources are associated with treatment satisfaction and outcomes. The correlational associations between symptoms and perceived helpfulness of resources can help inform personalization algorithms to optimize ICBT delivery for clients. Further research on how to match clients with, encourage use of, and maximize benefits of resources would be beneficial.

A systematic review of predictors and moderators of treatment outcomes in internet- and mobile-based interventions for depression

This systematic review aimed to synthesize evidence on predictors and moderators of treatment outcomes in internet- and mobile-based interventions (IMIs) for depression, informing personalized care. A systematic search across PubMed, PsycInfo, and Cochrane yielded 33,002 results. Two reviewers independently performed screening, data extraction, risk of bias assessment, and methodological quality evaluation. Fifty-eight single studies (m = 466 analyses) focusing on baseline-predictors (59.7 %, m = 278), process-predictors (16.5 %, m = 77), and moderators (21.9 %, m = 102), and six individual patient data meta-analyses (m = 93) were included. Only 24.0 % (m = 112/466) of analyses in single studies and 15.1 % (m = 14/93) in individual patient data meta-analyses were significant. Evidence from single studies was rated as insufficient for all variable categories with only 2 out of 40 categories showing >50 % significant results. Baseline depression severity had the strongest predictive value with higher scores linked to better outcomes followed by variables indicative for the course-of-change. Other frequently analyzed and potentially relevant variables with significant results were adherence, age, educational level, ethnicity, relationship status, treatment history, and behavioral variables. More high quality quantitative studies with sufficient power are essential to validate and expand findings, identifying predictors and moderators specifically relevant in IMIs to explain differential treatment effects.

Informing patients about possible negative effects of psychological treatment: A survey of Swedish clinical psychologists' attitudes and practices

OBJECTIVE

The present study explored Swedish clinical psychologists' attitudes and practices of informing patients about possible negative effects of psychological treatment.

METHOD

An anonymous online survey with closed and open-ended questions was distributed via Facebook and two mailing lists. In total, 320 clinical psychologists (age M = 38.6, SD = 10.3; 76% women; 77.3% Cognitive Behavior Therapy) completed the survey. Responses were analyzed using χ2, binominal regression analysis, and thematic analysis.

RESULTS

No significant associations were identified between demographic variables selected a priori and informing patients about possible negative effects, i.e., years in practice, therapeutic orientation, age, and male gender. The thematic analysis resulted in several positive (e.g., creating realistic expectations of treatment and increasing resilience) and negative attitudes (e.g., causing excessive worry) of sharing patients with information about possible negative effects. It also revealed various factors that prevent an open discussion on the topic, despite being seen as important.

CONCLUSION

The need to offer patients information about possible negative effects should be included in ethical guidelines, codes of conduct, and taught during clinical training. Lack of knowledge, fear, lack of time, and patient characteristics however seem to prevent therapists from discussing the issue during the informed consent procedure.

Outcomes of transdiagnostic internet-delivered cognitive behavioural therapy tailored to public safety personnel: A longitudinal observational study

First responders and other public safety personnel (PSP) experience high rates of mental health problems and face barriers to accessing mental healthcare. Internet-delivered cognitive behavioural therapy (ICBT) is an effective and accessible treatment for various mental health concerns. Canadian PSP report favorable attitudes toward ICBT, and preliminary outcomes demonstrate that they benefit from it. Expanding on this research, the current study consisted of a longitudinal observational study of 560 Canadian PSP who participated in ICBT. It was designed to assess the longer term effectiveness of ICBT and moderators of outcomes by gender, linguistic and occupational group, and years of occupational experience. We evaluated symptom change at 8, 26, and 52 weeks post-enrollment, and results among PSP who had elevated clinical scores, showed large reductions (Hedges' g) in symptoms of depression (g = 1.3), anxiety (g =1.48), posttraumatic stress (g =1.24), panic (g =1.19), and anger (g =1.07) and moderate reductions in symptoms of social anxiety (g =.48-.56). Moderator analyses revealed modest differences in pre-treatment symptoms among certain groups but no group differences in symptom change over time. Clients showed good completion of treatment materials and reported high treatment satisfaction. The results suggest further study of ICBT tailored to PSP is warranted, including evaluating ICBT tailored for PSP in other countries.

What to do when the unwanted happens? Negative event management in studies on internet- and mobile-based interventions for youths and adults with two case reports

Background

Despite severely burdened individuals, often being excluded from research studies on internet- and mobile-based interventions (IMIs), negative events (NEs) including suicidal thoughts and behaviors (STBs) can still occur during a trial. NEs require monitoring and adequate safety measures. However, study protocols frequently lack comprehensive descriptions of procedures for managing NEs.

Aims

This study aimed to illustrate the assessment, monitoring, and procedures for addressing NEs in two studies on IMIs in adults and youth using case reports, to identify strengths and weaknesses of the NE management approaches, and to derive key learnings and recommendations.

Methods

Two case reports were drawn from two distinct IMI studies. The first study, PSYCHOnlineTHERAPY, evaluates the combination of an IMI with on-site psychotherapy for anxiety and depressive disorders in adults (adult blended study). The second study evaluates a standalone, therapist-guided IMI for post-traumatic stress disorder (PTSD) in youth (youth standalone study). Potential NEs were predefined depending on the study sample. The case studies thoroughly document the systematic recording and ongoing monitoring of NEs through self-report and observer-based assessments during the interventions. The cases illustrate a variety of NE management strategies, including automated and personalized approaches, adapted to the specific nature and severity of the NEs. The NE management approaches are visualized using decision trees.

Results

In the adult blended case study, online questionnaires detected STBs and triggered automated support information. As on-site therapy had already ended, a telephone consultation session allowed for the identification and discussion of the heightened intensity of suicidal thoughts, along with the development of specific additional help options. In the youth standalone case study, heightened tension in an adolescent with PTSD during trauma processing could be addressed in a telephone therapeutic session focusing on resource activation and emotion regulation. The referral to on-site treatment was supported. Overall, advantages of the NE management included automated procedures, multimodal assessment of a wide range of NEs, and standardized procedures tailored to different severity levels. Weaknesses included the use of single-item assessments for STBs and lack of procedures in case of deterioration or nonresponse to treatment.

Conclusion

This study provides practical insights and derives key learnings and recommendations regarding the management of NEs in different IMI contexts for both adults and youth.

Demographic and clinical characteristics associated with anxiety and depressive symptom outcomes in users of a digital mental health intervention incorporating a relational agent

BACKGROUND

Digital mental health interventions (DMHIs) may reduce treatment access issues for those experiencing depressive and/or anxiety symptoms. DMHIs that incorporate relational agents may offer unique ways to engage and respond to users and to potentially help reduce provider burden. This study tested Woebot for Mood & Anxiety (W-MA-02), a DMHI that employs Woebot, a relational agent that incorporates elements of several evidence-based psychotherapies, among those with baseline clinical levels of depressive or anxiety symptoms. Changes in self-reported depressive and anxiety symptoms over 8 weeks were measured, along with the association between each of these outcomes and demographic and clinical characteristics.

METHODS

This exploratory, single-arm, 8-week study of 256 adults yielded non-mutually exclusive subsamples with either clinical levels of depressive or anxiety symptoms at baseline. Week 8 Patient Health Questionnaire-8 (PHQ-8) changes were measured in the depressive subsample (PHQ-8 ≥ 10). Week 8 Generalized Anxiety Disorder-7 (GAD-7) changes were measured in the anxiety subsample (GAD-7 ≥ 10). Demographic and clinical characteristics were examined in association with symptom changes via bivariate and multiple regression models adjusted for W-MA-02 utilization. Characteristics included age, sex at birth, race/ethnicity, marital status, education, sexual orientation, employment status, health insurance, baseline levels of depressive and anxiety symptoms, and concurrent psychotherapeutic or psychotropic medication treatments during the study.

RESULTS

Both the depressive and anxiety subsamples were predominantly female, educated, non-Hispanic white, and averaged 38 and 37 years of age, respectively. The depressive subsample had significant reductions in depressive symptoms at Week 8 (mean change =-7.28, SD = 5.91, Cohen's d = -1.23, p < 0.01); the anxiety subsample had significant reductions in anxiety symptoms at Week 8 (mean change = -7.45, SD = 5.99, Cohen's d = -1.24, p < 0.01). No significant associations were found between sex at birth, age, employment status, educational background and Week 8 symptom changes. Significant associations between depressive and anxiety symptom outcomes and sexual orientation, marital status, concurrent mental health treatment, and baseline symptom severity were found.

CONCLUSIONS

The present study suggests early promise for W-MA-02 as an intervention for depression and/or anxiety symptoms. Although exploratory in nature, this study revealed potential user characteristics associated with outcomes that can be investigated in future studies.

TRIAL REGISTRATION

This study was retrospectively registered on ClinicalTrials.gov (#NCT05672745) on January 5th, 2023.

Predictors of nonresponse to treatment and low adherence to internet-based cognitive behavioral therapy in depressed/anxious women facing the couple's fertility problems: a secondary analysis of a randomized control trial

BACKGROUND

The study aimed to examine the predictors of treatment nonresponse and low adherence to Internet-based cognitive behavioral therapy and face-to-face therapy for treating depression and anxiety in women facing the couple's fertility problems.

METHODS

This is a secondary analysis based on a previous randomized controlled trial including 152 depressed/anxious women facing the couple's fertility problems. The study defines low adherence as receiving less than 4 sessions (out of 8 sessions). Nonresponse to treatment refers to a < 50% reduction in the anxiety and depression total scores.

RESULTS

A high level of anxiety/depression score before psychotherapy increases the risk of nonresponse to both Internet-based and face-to-face psychotherapies by 1.4 to 2 times in women facing the couple's fertility problems after the treatment and in the 6-month follow-up. However, 4 factors, including diagnosis of mixed anxiety and depression, low education level, long marriage duration, and infertility caused by mixed female/male factors, reduced the risk of nonresponse to psychotherapies.

CONCLUSION

Women facing the couple's fertility problems with high depression and anxiety scores are at risk of poor prognosis in response to psychotherapy. Psychologists and healthcare providers of infertility centers should pay more attention to the timely identification and referral of depressed/anxious patients to psychologists.

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.

Improving mental well-being in psychocardiology-a feasibility trial for a non-blended web application as a brief metacognitive-based intervention in cardiovascular disease patients

Background

Many patients with cardiovascular disease also show a high comorbidity of mental disorders, especially such as anxiety and depression. This is, in turn, associated with a decrease in the quality of life. Psychocardiological treatment options are currently limited. Hence, there is a need for novel and accessible psychological help. Recently, we demonstrated that a brief face-to-face metacognitive therapy (MCT) based intervention is promising in treating anxiety and depression. Here, we aim to translate the face-to-face approach into digital application and explore the feasibility of this approach.

Methods

We translated a validated brief psychocardiological intervention into a novel non-blended web app. The data of 18 patients suffering from various cardiac conditions but without diagnosed mental illness were analyzed after using the web app over a two-week period in a feasibility trial. The aim was whether a non-blended web app based MCT approach is feasible in the group of cardiovascular patients with cardiovascular disease.

Results

Overall, patients were able to use the web app and rated it as satisfactory and beneficial. In addition, there was first indication that using the app improved the cardiac patients' subjectively perceived health and reduced their anxiety. Therefore, the approach seems feasible for a future randomized controlled trial.

Conclusion

Applying a metacognitive-based brief intervention via a non-blended web app seems to show good acceptance and feasibility in a small target group of patients with CVD. Future studies should further develop, improve and validate digital psychotherapy approaches, especially in patient groups with a lack of access to standard psychotherapeutic care.

A Call to Action on Assessing and Mitigating Bias in Artificial Intelligence Applications for Mental Health

Advances in computer science and data-analytic methods are driving a new era in mental health research and application. Artificial intelligence (AI) technologies hold the potential to enhance the assessment, diagnosis, and treatment of people experiencing mental health problems and to increase the reach and impact of mental health care. However, AI applications will not mitigate mental health disparities if they are built from historical data that reflect underlying social biases and inequities. AI models biased against sensitive classes could reinforce and even perpetuate existing inequities if these models create legacies that differentially impact who is diagnosed and treated, and how effectively. The current article reviews the health-equity implications of applying AI to mental health problems, outlines state-of-the-art methods for assessing and mitigating algorithmic bias, and presents a call to action to guide the development of fair-aware AI in psychological science.

Who benefits from guided internet-based interventions? A systematic review of predictors and moderators of treatment outcome

To our knowledge, no systematic review has been conducted on predictors or moderators of treatment outcome across diagnoses in guided internet-based interventions (IBIs) for adults. To identify who benefits from this specific format and therein inform future research on improving patient-treatment fit, we aimed to aggregate results of relevant studies. 2100 articles, identified by searching the databases PsycInfo, Ovid Medline, and Pubmed and through snowballing, were screened in April/May 2021 and October 2022. Risk of bias and intra- and interrater reliability were assessed. Variables were grouped by predictor category, then synthesized using vote counting based on direction of effect. N = 60 articles were included in the review. Grouping resulted in 88 predictors/moderators, of which adherence, baseline symptoms, education, age, and gender were most frequently assessed. Better adherence, treatment credibility, and working alliance emerged as conclusive predictors/moderators for better outcome, whereas higher baseline scores predicted more reliable change but higher post-treatment symptoms. Results of all other predictors/moderators were inconclusive or lacked data. Our review highlights that it is currently difficult to predict, across diagnoses, who will benefit from guided IBIs. Further rigorous research is needed to identify predictors and moderators based on a sufficient number of studies. PROSPERO registration: CRD42021242305.

An open trial of the feasibility of brief internet-delivered acceptance and aommitment therapy (iACT) for chronic anxiety and depression

Anxiety and depressive disorders are common, often chronic and result in significant disability and distress. The delivery of psychological interventions via the internet is now recognised to be a safe and effective way to treat these disorders. The predominant therapeutic model in clinical trials and in routine care has been cognitive-behavioural therapy (CBT), which helps patients identify and modify unhelpful thoughts and behaviours. However, other models of treatment for anxiety and depression, such as acceptance and commitment therapy (ACT), which uses the examination of both positive and negative experiences in the service of living a personally meaningful and values-based life, have been developed and tested, although most of these interventions are long and require more clinician support to ensure adherence and achieve positive outcomes. The aim of the present study was to examine the feasibility of a new brief, clinician supported transdiagnostic internet-delivered (iACT) program, designed to treat symptoms of both anxiety and depression and improve social function. A single-group open trial was conducted on 24 adults with long-term symptoms of anxiety and depression. The course is comprised of five online modules delivered over 8 weeks either self-guided or with support from a clinician. There was a high course completion rate (70 %) and a high level of satisfaction with the course (94 % satisfied or very satisfied). Significant clinical improvement in our primary outcome measures (within-group Cohen's d) of anxiety (d ≥ 0.62), depression (d ≥ 0.63), disability (d ≥ 0.43) and quality of life (d ≥ -0.57) were observed at posttreatment. Relatively little clinician time was required per participant (M = 30.6 min, SD = 5.7). The findings of the current study support the feasibility and potential of a transdiagnostic iACT treatment for adults experiencing long-term symptoms of anxiety and depression, including those patients who have not derived benefit from other treatments.

A Precision Treatment Model for Internet-Delivered Cognitive Behavioral Therapy for Anxiety and Depression Among University Students: A Secondary Analysis of a Randomized Clinical Trial

Importance

Guided internet-delivered cognitive behavioral therapy (i-CBT) is a low-cost way to address high unmet need for anxiety and depression treatment. Scalability could be increased if some patients were helped as much by self-guided i-CBT as guided i-CBT.

Objective

To develop an individualized treatment rule using machine learning methods for guided i-CBT vs self-guided i-CBT based on a rich set of baseline predictors.

Design, Setting, and Participants

This prespecified secondary analysis of an assessor-blinded, multisite randomized clinical trial of guided i-CBT, self-guided i-CBT, and treatment as usual included students in Colombia and Mexico who were seeking treatment for anxiety (defined as a 7-item Generalized Anxiety Disorder [GAD-7] score of ≥10) and/or depression (defined as a 9-item Patient Health Questionnaire [PHQ-9] score of ≥10). Study recruitment was from March 1 to October 26, 2021. Initial data analysis was conducted from May 23 to October 26, 2022.

Interventions

Participants were randomized to a culturally adapted transdiagnostic i-CBT that was guided (n = 445), self-guided (n = 439), or treatment as usual (n = 435).

Main Outcomes and Measures

Remission of anxiety (GAD-7 scores of ≤4) and depression (PHQ-9 scores of ≤4) 3 months after baseline.

Results

The study included 1319 participants (mean [SD] age, 21.4 [3.2] years; 1038 women [78.7%]; 725 participants [55.0%] came from Mexico). A total of 1210 participants (91.7%) had significantly higher mean (SE) probabilities of joint remission of anxiety and depression with guided i-CBT (51.8% [3.0%]) than with self-guided i-CBT (37.8% [3.0%]; P = .003) or treatment as usual (40.0% [2.7%]; P = .001). The remaining 109 participants (8.3%) had low mean (SE) probabilities of joint remission of anxiety and depression across all groups (guided i-CBT: 24.5% [9.1%]; P = .007; self-guided i-CBT: 25.4% [8.8%]; P = .004; treatment as usual: 31.0% [9.4%]; P = .001). All participants with baseline anxiety had nonsignificantly higher mean (SE) probabilities of anxiety remission with guided i-CBT (62.7% [5.9%]) than the other 2 groups (self-guided i-CBT: 50.2% [6.2%]; P = .14; treatment as usual: 53.0% [6.0%]; P = .25). A total of 841 of 1177 participants (71.5%) with baseline depression had significantly higher mean (SE) probabilities of depression remission with guided i-CBT (61.5% [3.6%]) than the other 2 groups (self-guided i-CBT: 44.3% [3.7%]; P = .001; treatment as usual: 41.8% [3.2%]; P < .001). The other 336 participants (28.5%) with baseline depression had nonsignificantly higher mean (SE) probabilities of depression remission with self-guided i-CBT (54.4% [6.0%]) than guided i-CBT (39.8% [5.4%]; P = .07).

Conclusions and Relevance

Guided i-CBT yielded the highest probabilities of remission of anxiety and depression for most participants; however, these differences were nonsignificant for anxiety. Some participants had the highest probabilities of remission of depression with self-guided i-CBT. Information about this variation could be used to optimize allocation of guided and self-guided i-CBT in resource-constrained settings.

Trial Registration

ClinicalTrials.gov Identifier: NCT04780542.

Predicting the Outcomes of Internet-Based Cognitive Behavioral Therapy for Tinnitus: Applications of Artificial Neural Network and Support Vector Machine

PURPOSE

Internet-based cognitive behavioral therapy (ICBT) has been found to be effective for tinnitus management, although there is limited understanding about who will benefit the most from ICBT. Traditional statistical models have largely failed to identify the nonlinear associations and hence find strong predictors of success with ICBT. This study aimed at examining the use of an artificial neural network (ANN) and support vector machine (SVM) to identify variables associated with treatment success in ICBT for tinnitus.

METHOD

The study involved a secondary analysis of data from 228 individuals who had completed ICBT in previous intervention studies. A 13-point reduction in Tinnitus Functional Index (TFI) was defined as a successful outcome. There were 33 predictor variables, including demographic, tinnitus, hearing-related and treatment-related variables, and clinical factors (anxiety, depression, insomnia, hyperacusis, hearing disability, cognitive function, and life satisfaction). Predictive models using ANN and SVM were developed and evaluated for classification accuracy. SHapley Additive exPlanations (SHAP) analysis was used to identify the relative predictor variable importance using the best predictive model for a successful treatment outcome.

RESULTS

The best predictive model was achieved with the ANN with an average area under the receiver operating characteristic value of 0.73 ± 0.03. The SHAP analysis revealed that having a higher education level and a greater baseline tinnitus severity were the most critical factors that influence treatment outcome positively.

CONCLUSIONS

Predictive models such as ANN and SVM help predict ICBT treatment outcomes and identify predictors of outcome. However, further work is needed to examine predictors that were not considered in this study as well as to improve the predictive power of these models.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.21266487.

A meta-analytic review of randomized clinical trials of online treatments for anxiety: Inclusion/exclusion criteria, uptake, adherence, dropout, and clinical outcomes

Over the last decade there has been rapid growth in the number of clinical trials examining internet-delivered interventions for anxiety. While there have been numerous analyses of treatment efficacy, few studies have examined treatment engagement. The current meta-analysis examined participant eligibility, uptake, adherence, and drop-out in clinical trials of internet-delivered treatments for anxiety. This meta-analysis used random effects models to obtain estimates of participant inclusion, uptake, adherence, drop-out, and within-group treatment effect size. Moderator analyses examined the effects of anxiety disorder type, treatment type, and level of clinician guidance. After screening, 140 trials with 199 treatment arms (N = 11,021) were included. An average of 46% (95% CI 42, 50) of interested people were included in the clinical trials. In the active treatment arms, 98% (95% CI 97, 99) of participants began treatment, 81% (95% CI 78, 85) of the assigned treatments were completed, 21% (95% CI 18, 23) of individuals dropped out at post-treatment based on questionnaire non-completion, and an overall within-group effect size of g = 1.03 (95% CI 0.94, 1.13) was obtained. Several moderators of interest were significant (e.g., clinical guidance, anxiety disorder type), and there was substantial heterogeneity in estimates. In conclusion, a large number of inclusion and exclusion criteria have been used in trials of internet-delivered treatments for anxiety. Once recruited into a trial, however, most people appear to begin, adhere, and complete internet-delivered treatment for anxiety. Further research exploring various eligibility criteria and their impact on engagement and efficacy is warranted.

Internet-based cognitive behavior therapy for eating disorders - Development and feasibility evaluation

BACKGROUND

Eating disorders (ED) are severe psychiatric conditions, characterized by decreased quality of life and high mortality. However, only a minority of patients with ED seek care and very few receive treatment. Internet-delivered cognitive behavioral therapy (ICBT) has the potential to increase access to evidence-based treatments.

AIMS

The aims of the present study were to (1) develop and evaluate the usability of an Internet-delivered guided self-help treatment based on Enhanced Cognitive Behavioral Therapy (ICBT-E) for patients with full or subthreshold bulimia nervosa (BN) or binge eating disorder (BED) with a user centered design process, and (2) to evaluate its feasibility and preliminary outcome in a clinical environment.

METHOD

The study was undertaken in two stages. In Stage I, a user-centered design approach was applied with iterative phases of prototype development and evaluation. Participants were eight clinicians and 30 individuals with current or previous history of ED. In Stage II, 41 patients with full or subthreshold BN or BED were recruited to a single-group open trial to evaluate the feasibility and preliminary outcome of ICBT-E. Primary outcome variables were diagnostic status and self-rated ED symptoms.

RESULTS

The user-centered design process was instrumental in the development of the ICBT-E, by contributing to improvements of the program and to the content being adapted to the needs and preferences of end-users. The overall usability of the program was found to be good. ICBT-E targets key maintaining factors in ED by introducing healthy eating patterns and addressing over-evaluation of weight and shape. The results indicate that ICBT-E, delivered in a clinical setting, is a feasible and promising treatment for full or subthreshold BN or BED, with a high level of acceptability observed and treatment completion of 73.2 %. Participation in ICBT-E was associated with significant symptom reductions in core ED symptomology, functional impairment as well as depressive symptoms, and the results were maintained at the 3-month follow-up.

CONCLUSIONS

ICBT-E was developed with end-users' preferences in mind, in accordance with the identified recommendations, and the program was perceived as usable by end-users. The study demonstrated the potential of ICBT-E, which marks a step forward in the effort to make powerful, empirically supported psychological interventions targeting ED more widely available and accessible.

Lessons Learned from an Attempted Pragmatic Randomized Controlled Trial for Improvement of Chronic Pain-Associated Disability in Green Professions: Long-Term Effectiveness of a Guided Online-Based Acceptance and Commitment Therapy &nbsp;(PACT-A)

Musculoskeletal symptoms are increased in farmers, whereas the prevalence of chronified pain is unknown. Online interventions based on acceptance and commitment therapy (ACT) have shown encouraging results in the general population, representing a promising approach for reducing pain interference in green professions (i.e., farmers, foresters, gardeners). We conducted a pragmatic RCT comparing a guided ACT-based online intervention to enhanced treatment-as-usual in entrepreneurs, contributing spouses, family members and pensioners in green professions with chronic pain (CPG: ≥grade II, ≥6 months). Recruitment was terminated prematurely after 2.5 years at N = 89 (of planned N = 286). Assessments were conducted at 9 weeks (T1), 6 months (T2) and 12 months (T3) post-randomization. The primary outcome was pain interference (T1). The secondary outcomes encompassed pain-, health- and intervention-related variables. No treatment effect for reduction of pain interference was found at T1 (β = -0.16, 95%CI: -0.64-0.32, p = 0.256). Improvements in cognitive fusion, pain acceptance, anxiety, perceived stress and quality of life were found only at T3. Intervention satisfaction as well as therapeutic and technological alliances were moderate, and uptake and adherence were low. Results are restricted by low statistical power due to recruitment issues, high study attrition and low intervention adherence, standing in contrast to previous studies. Further research is warranted regarding the use of ACT-based online interventions for chronic pain in this occupational group. Trial registration: German Clinical Trial Registration: DRKS00014619. Registered: 16 April 2018.

Predicting remission after internet-delivered psychotherapy in patients with depression using machine learning and multi-modal data

This study applied supervised machine learning with multi-modal data to predict remission of major depressive disorder (MDD) after psychotherapy. Genotyped adult patients (n = 894, 65.5% women, age 18-75 years) diagnosed with mild-to-moderate MDD and treated with guided Internet-based Cognitive Behaviour Therapy (ICBT) at the Internet Psychiatry Clinic in Stockholm were included (2008-2016). Predictor types were demographic, clinical, process (e.g., time to complete online questionnaires), and genetic (polygenic risk scores). Outcome was remission status post ICBT (cut-off ≤10 on MADRS-S). Data were split into train (60%) and validation (40%) given ICBT start date. Predictor selection employed human expertise followed by recursive feature elimination. Model derivation was internally validated through cross-validation. The final random forest model was externally validated against a (i) null, (ii) logit, (iii) XGBoost, and (iv) blended meta-ensemble model on the hold-out validation set. Feature selection retained 45 predictors representing all four predictor types. With unseen validation data, the final random forest model proved reasonably accurate at classifying post ICBT remission (Accuracy 0.656 [0.604, 0.705], P vs null model = 0.004; AUC 0.687 [0.631, 0.743]), slightly better vs logit (bootstrap D = 1.730, P = 0.084) but not vs XGBoost (D = 0.463, P = 0.643). Transparency analysis showed model usage of all predictor types at both the group and individual patient level. A new, multi-modal classifier for predicting MDD remission status after ICBT treatment in routine psychiatric care was derived and empirically validated. The multi-modal approach to predicting remission may inform tailored treatment, and deserves further investigation to attain clinical usefulness.

The impact of comorbid spinal pain in depression on work participation and clinical remission following brief or short psychotherapy. Secondary analysis of a randomized controlled trial with two-year follow-up

Objectives

This explorative study analyses the influence of baseline comorbid long-lasting spinal pain (CSP) on improvement of long term work participation and clinical remission of mental health illness following either brief coping-focussed or short-term psychotherapy for depression. Whether type of treatment modifies outcome with or without CSP is also analysed.

Design

A secondary post hoc subgroup analysis of a pragmatic randomised controlled trial.

Interventions

Brief or standard short psychotherapy.

Methods

Based on baseline assessment, the sample was subdivided into a subgroup with and a subgroup without CSP. Work participation and clinical remission of depression and anxiety were assessed as treatment outcome at two-year follow-up. Simple and multivariate logistic regression analyses, across the intervention arms, were applied to evaluate the impact of CSP on treatment outcome. Selected baseline variables were considered as potential confounders and included as variates if relevant. The modifying effect of CSP on treatment outcome was evaluated by including intervention modality as an interaction term.

Main results

Among the 236 participants with depressive symptoms, 83 participants (35%) were identified with CSP. In simple logistic regression analysis, CSP reduced improvements on both work participation and clinical remission rate. In the multivariate analysis however, the impact of CSP on work participation and on clinical remission were not significant after adjusting for confounding variables. Reduction of work participation was mainly explained by the higher age of the CSP participants and the reduced clinical remission by the additional co-occurrence of anxiety symptoms at baseline. The occurrence of CSP at baseline did not modify long term outcome of brief compared to short psychotherapy.

Conclusions

CSP at baseline reduced work participation and worsened remission of mental health symptoms two-year following psychotherapy. Older age and more severe baseline anxiety are associated to reduced effectiveness. Type of psychotherapy received did not contribute to differences.

The unified protocol as an internet-based intervention for emotional disorders: Randomized controlled trial

The Unified Protocol (UP) as a transdiagnostic intervention has primarily been applied in the treatment of anxiety disorders and in face-to-face-settings. The current study investigated the efficacy of a 10-week Internet-based adaptation of the UP for anxiety, depressive, and somatic symptom disorders. The trial was registered under DRKS00014820 at the German Clinical Trial Registry, DRKS. Participants (n = 129) were randomized to treatment or waitlist control. Significant treatment effects were found for symptom distress, satisfaction with life, positive/negative affect and markers of anxiety, depression, and somatic symptom burden (within-group Hedges’ g = 0.32–1.38 and between-group g = 0.20–1.11). Treatment gains were maintained at 1- and 6-month-follow-up. Subgroup analyses showed comparable effects in participants with anxiety and depressive disorders. 26.6% dropped out of treatment and 35.38% did not provide post-treatment assessments. The results strengthen the application of the UP as an Internet-based treatment for alleviating symptom distress across emotional disorders. More research on the applicability for single disorders is needed and avenues to improve adherence and attrition rates should be explored.

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 Psychosocial Approach to Erectile Dysfunction: Position Statements from the European Society of Sexual Medicine (ESSM)

INTRODUCTION

Although erectile dysfunction (ED) involves an interaction between physiological and psychological pathways, the psychosocial aspects of ED have received considerably less attention so far.

AIM

To review the available evidence on the psychosocial aspects of ED in order to develop a position statement and clinical practice recommendations on behalf of the European Society of Sexual Medicine (ESSM).

METHOD

A comprehensive, narrative review of the literature was performed.

MAIN OUTCOME MEASURES

Specific statements and recommendations according to the Oxford Centre for Evidence-Based Medicine 2011 Levels of Evidence criteria were provided.

RESULTS

A multidisciplinary treatment, in which medical treatment is combined with a psychological approach, is preferred over unimodal treatment. There is increasing evidence that psychological treatments of ED can improve medical treatments, the patient's adherence to treatment, and the quality of the sexual relationship. The main components of psychological treatment of ED involve cognitive and behavioral techniques aimed at reducing anxiety, challenging dysfunctional beliefs, increasing sexual stimulation, disrupting sexual avoidance, and increasing intimacy and communication skills in a relational context. When applicable and possible, it is strongly recommended to include the partner in the assessment and treatment of ED and to actively work on interpartner agreement and shared decision-making regarding possible treatment options. To ensure a better integration of the biopsychosocial model into clinical practice, developing concrete treatment protocols and training programs are desirable.

CONCLUSION

Because the psychosocial approach to ED has been underexposed so far, this position statement provides valuable information for clinicians treating ED. Psychological interventions on ED are based on existing theoretical models that are grounded in empirical evidence. However, the quality of available studies is low, which calls for further research. The sexual medicine field would benefit from pursuing more diversity, inclusivity, and integration when setting up treatments and evaluating their effect. Dewitte M, Bettocchi C, Carvalho J, et al. A Psychosocial Approach to Erectile Dysfunction: Position Statements from the European Society of Sexual Medicine (ESSM). Sex Med 2021;9:100434.

Are guided internet-based interventions for the indicated prevention of depression in green professions effective in the long run? Longitudinal analysis of the 6- and 12-month follow-up of a pragmatic randomized controlled trial (PROD-A)

OBJECTIVE

Evidence of long-term stability for positive mental health effects of internet-based interventions (IBIs) for depression prevention is still scarce. We evaluate long-term effectiveness of a depression prevention program in green professions (i.e. agriculture, horticulture, forestry).

METHODS

This pragmatic RCT (n = 360) compares a tailored IBI program to enhanced treatment as usual (TAU+) in green professions with at least subthreshold depression (PHQ ≥ 5). Intervention group (IG) received one of six IBIs shown previously to efficaciously reduce depressive symptoms. We report 6- and 12-month follow-up measures for depression, mental health and intervention-related outcomes. Intention-to-treat and per-protocol regression analyses were conducted for each measurement point and complemented by latent growth modeling.

RESULTS

After 6 months, depression severity (β = -0.30, 95%-CI: -0.52; -0.07), insomnia (β = -0.22, 95%-CI: -0.41; -0.02), pain-associated disability (β = -0.26, 95%-CI: -0.48; -0.04) and quality of life (β = 0.29, 95%-CI: 0.13; 0.45) in IG were superior to TAU+. Onset of possible depression was not reduced. After 12 months, no intervention effects were found. Longitudinal modeling confirmed group effects attenuating over 12 months for most outcomes. After 12 months, 55.56% of IG had completed at least 80% of their IBI.

CONCLUSIONS

Stability of intervention effects along with intervention adherence was restricted. Measures enhancing long-term effectiveness of IBIs for depression health promotion are indicated in green professions.

TRIAL REGISTRATION

German Clinical Trial Registration: DRKS00014000. Registered: 09 April 2018.

Transdiagnostic Processes as Mediators of Change in an Internet-Delivered Intervention Based on the Unified Protocol

Background

Transdiagnostic treatments target shared mechanisms between disorders to facilitate change across diagnoses. The Unified Protocol (UP) aims at changing dysfunctional reactions towards emotions by increasing mindful emotion awareness and cognitive flexibility, as well as decreasing anxiety sensitivity and emotion avoidance.

Method

We investigated whether these transdiagnostic processes were malleable by treatment and mediated the relationship between treatment and outcome in an internet-delivered adaptation of the UP. N = 129 participants with mixed anxiety, depressive, and somatic symptom disorders were randomized to treatment or waitlist.

Results

The treatment yielded significant changes in all transdiagnostic processes over time in comparison to a waitlist condition. In separate mediator models, significant mediating effects were found for mindfulness, cognitive flexibility, behavioral activation, and experiential avoidance. When all mediators were combined in a multiple mediator model, the indirect effects through mindfulness and cognitive flexibility emerged as significant.

Conclusion

These findings add to the growing body of research on transdiagnostic processes as mediators of change and emphasize mindfulness and cognitive flexibility as a transdiagnostic treatment target. However, these results should be interpreted cautiously, as temporal precedence could not be established.

Disorder-specific internet-based cognitive-behavioral therapy in treating panic disorder, comorbid symptoms and improving quality of life: A meta-analytic evaluation of randomized controlled trials

Compared to conventional face-to-face psychological treatments, internet-based cognitive-behavioral therapy (iCBT) presents an innovative alternative that has been found to be effective in the treatment of anxiety disorders. The current study provides a meta-analysis investigating the efficacy of disorder-specific guided self-help (Gsh) iCBT compared to various active and inactive control conditions, with focus on adult panic disorder sufferers with or without agoraphobia (PD/A). Systematic literature search yielded 13 randomized controlled trials (RCTs) (N = 1214) that met the eligibility criteria for this study. We found no statistically significant differences between Gsh iCBT and various active CBT interventions in reducing PD/A symptoms at both post-test (g = 0.015, k = 10) and follow-up (g = 0.113, k = 6) levels. Also, comorbid anxiety and depression were reduced equivalently at post-test (g = 0.004, k = 6) and follow-up (g = 0.004, k = 6). Quality of life was equally improved at post-test (g = -0.100, k = 5) and follow-up (g = 0.074, k = 2). When compared to inactive controls, we found large effect sizes in PD/A (g = -0.892, k = 9) and comorbid anxiety and depression (g = -0.723, k = 9) symptoms, and moderate change in quality of life (g = -0.484, k = 3) at post-test. There was no difference between Guided self-help iCBT and Self-help iCBT in PD/A (g = -0.025, k = 3) and comorbid anxiety and depression (g = -0.025, k = 3) at post-test. Baseline severity, country of original research and adherence to the treatment in form of initial uptake were identified as statistically significant moderators of the iCBT treatment.

Effectiveness of guided internet-based interventions in the indicated prevention of depression in green professions (PROD-A): Results of a pragmatic randomized controlled trial

BACKGROUND

Major Depressive Disorder (MDD) has a major impact on public health. Reduction of depression burden in general population is of greatest importance and might be achieved by implementation of depression prevention measures into routine care. We evaluate an online prevention measure as part of a national project aiming to reduce depression in the occupational group of green professions.

METHODS

This two-armed pragmatic RCT (n = 360) evaluates the effectiveness of a tailored internet-based intervention (IMI) program compared to enhanced treatment as usual. The IMI program entailed access to one of six guided IMIs each focusing on different symptom areas (depressive mood with optional comorbid diabetes, perceived stress, insomnia, panic and agoraphobia and harmful alcohol consumption). Eligible were entrepreneurs, spouses, family members and pensioners in green professions with adequate insurance status and at least subthreshold depression (PHQ≥5). Primary outcome was depressive symptom severity (QIDS-SR16) at 9-weeks post-treatment (T1). Various secondary outcomes were assessed at T1.

RESULTS

A small effect of depression reduction (d=-0.28, 95%-CI: -0.50 to -0.07) was found at T1 favouring the IMI program (β=-0.22, 95%-CI: -0.41 to -0.02, p=.033). Categorical analysis indicated a reduced risk of potential MDD with NNTB=28.11. Adherence to the IMI program at T1 was exceptionally low.

LIMITATIONS

Results are limited to green professions and representativeness might be restricted by self-selection of participants.

CONCLUSION

Depression burden in green professions can be reduced by this online prevention measure. Yet, short-term effectiveness is restricted by low adherence rates.

TRIAL REGISTRATION

German Clinical Trial Registration: DRKS00014000. Registered: 09 April 2018.

The 2020 Royal Australian and New Zealand College of Psychiatrists clinical practice guidelines for mood disorders

OBJECTIVES

To provide advice and guidance regarding the management of mood disorders, derived from scientific evidence and supplemented by expert clinical consensus to formulate s that maximise clinical utility.

METHODS

Articles and information sourced from search engines including PubMed, EMBASE, MEDLINE, PsycINFO and Google Scholar were supplemented by literature known to the mood disorders committee (e.g. books, book chapters and government reports) and from published depression and bipolar disorder guidelines. Relevant information was appraised and discussed in detail by members of the mood disorders committee, with a view to formulating and developing consensus-based recommendations and clinical guidance. The guidelines were subjected to rigorous consultation and external review involving: expert and clinical advisors, key stakeholders, professional bodies and specialist groups with interest in mood disorders.

RESULTS

The Royal Australian and New Zealand College of Psychiatrists mood disorders clinical practice guidelines 2020 (MDcpg²⁰²⁰) provide up-to-date guidance regarding the management of mood disorders that is informed by evidence and clinical experience. The guideline is intended for clinical use by psychiatrists, psychologists, primary care physicians and others with an interest in mental health care.

CONCLUSION

The MDcpg²⁰²⁰ builds on the previous 2015 guidelines and maintains its joint focus on both depressive and bipolar disorders. It provides up-to-date recommendations and guidance within an evidence-based framework, supplemented by expert clinical consensus.

MOOD DISORDERS COMMITTEE

Gin S Malhi (Chair), Erica Bell, Darryl Bassett, Philip Boyce, Richard Bryant, Philip Hazell, Malcolm Hopwood, Bill Lyndon, Roger Mulder, Richard Porter, Ajeet B Singh and Greg Murray.

To make a run for IT - A feasibility study of ICBT combined with physical exercise for patients with panic disorder

BACKGROUND

Guided Internet-based cognitive behavioural therapy (ICBT) is a recommended treatment for panic disorder promising to increase treatment availability, but there are some concerns regarding adherence, including adherence to the in vivo exposure given as home assignments. The aim of this study was to assess the feasibility of combining ICBT with physical exercise with the aim of improving adherence and treatment response to ICBT.

METHOD

12 participants were included via routine clinical practice to an open pre- post trial of feasibility using ICBT and an aerobe exercise protocol. We used a mixed model design investigating multiple areas of adherence, participants' experience and clinical outcome.

RESULTS

90.9% of the participants was considered completers in the ICBT program and the average adherence to the physical exercise was 93.1%. The experience of participating was summarized as "Hard work but worth it". Clinical outcomes effect sizes (d) ranged from 2.79 (panic severity) to .64 (Beck's anxiety index).

CONCLUSION

The sum results on adherence, qualitative and quantitative data all suggest that augmenting ICBT with an aerobic exercise protocol is feasible. We conclude that further research is warranted.

Transdiagnostic internet-delivered CBT and mindfulness-based treatment for depression and anxiety: A randomised controlled trial

AIM

To examine the efficacy of transdiagnostic internet-delivered cognitive behavioural therapy (iCBT), mindfulness-enhanced iCBT, and stand-alone online mindfulness training compared with a usual care control group (TAU) for clinical anxiety and depression.

METHOD

Individuals (N = 158) with a DSM-5 diagnosis of a depressive and/or anxiety disorder were randomised to one of the three clinician-guided online interventions, or TAU over a 14-week intervention period. The primary outcomes were self-reported depression (PHQ-9) and anxiety (GAD-7) severity at post-treatment. Secondary outcomes included adherence rates, functional impairment (WHODAS-II), general distress (K-10), and diagnostic status at the 3-month follow-up (intervention groups).

RESULTS

All three programs achieved significant and large reductions in symptoms of depression (g = 0.89-1.53), anxiety (g = 1.04-1.40), and distress (g = 1.25-1.76); and medium to large reductions in functional impairment (g = 0.53-0.98) from baseline to post-treatment and 3-month follow-up. Intention-to-treat linear mixed models showed that all three online programs were superior to usual care at reducing symptoms of depression (g = 0.89-1.18) and anxiety (g = 1.00-1.23).

CONCLUSION

Transdiagnostic iCBT, mindfulness-enhanced iCBT and online mindfulness training are more efficacious for treating depression and anxiety disorders than usual care, and represent an accessible treatment option for these disorders.

Internet Interventions for Mental Health: Current State of Research, Lessons Learned and Future Directions

This article gives an overview of current research on internet interventions in the field of mental health. As a result of COVID-19, the implementation of internet interventions has been given a boost in the mental health sectors of several countries all over the world. With regard to these developments, a definition of internet interventions is provided and the current state of research on different formats, treatment contents, and settings of internet interventions is discussed. Current research on the therapeutic alliance in internet interventions and possible negative effects is also described. The review closes with lessons learned from the past decades of research on internet interventions along with possible implications and future directions.

Predictors of outcome in guided self-help cognitive behavioural therapy for common mental disorders in primary care

Cognitive behavioural therapy (CBT) can effectively treat common mental disorders (CMDs), but access to treatment is insufficient. Guided self-help (GSH) CBT has shown effects comparable to face-to-face CBT and may be a resource-efficient treatment alternative. However, not all patients respond to GSH. Learning more about predictors of outcome may increase knowledge regarding which patients respond to GSH. The aim of this study was to investigate predictors of outcome for GSH CBT for patients with CMDs in primary care. Consecutive patients (N = 396) with a principal disorder of depression, anxiety, insomnia or stress-related disorders were included. All patients received GSH CBT. Outcomes were remission status, reliable change and post-treatment depression ratings. Predictors investigated were clinical, demographic and therapy-related variables. Analyses were conducted using logistic and linear regression. Higher educational level predicted remission, higher quality of life ratings predicted remission and decreased depression, and higher age at onset predicted reliable change. Therapy-related variables, i.e. patient adherence to treatment and patients' and clinicians' estimation of treatment response, were all related to outcome. More large-scale studies are needed, but the present study points at the importance of therapy-related variables such as monitoring and supporting treatment adherence for an increased chance of remission.

Negative effects associated with internet-delivered cognitive behaviour therapy: An analysis of client emails

Internet-delivered cognitive behaviour therapy (ICBT) is an efficacious form of treatment for anxiety and depression, yet it is still possible for clients to experience negative effects associated with treatment. In the ICBT literature, the term negative effects is broadly used to refer to all potentially adverse or unwanted events or experiences that are perceived as undesirable by the client and may or may not be associated with long-term symptoms or distress. Previous ICBT studies have asked clients to retrospectively describe negative effects at post-treatment; however, no research has examined the content of clients' emails to their therapist to see whether clients are reporting negative effects as they arise. In the current study, 96 clients (80 completers; 16 non-completers) were randomly selected from a published ICBT trial and directed content analysis was used to examine client emails for mention of negative effects. In addition, correlational analyses were used to examine the relationship between negative effects and: 1) demographic characteristics; 2) treatment engagement; 3) treatment satisfaction; 4) working alliance; and 5) symptom outcomes among completers. The results indicated that 61.5% of clients experienced at least one negative effect during treatment, although total number of negative effects was not significantly correlated with client demographic characteristics, lessons completed, working alliance, treatment satisfaction, or symptom outcomes. Among completers, technical difficulties, implementation problems, and negative emotional states were the most commonly reported negative effects, whereas dropout was the most commonly reported negative effect by non-completers. Negative effects that have been identified in previous research, such as symptom deterioration, novel symptoms, and severe adverse events, were not identified in client emails. The high incidence of negative effects in the current study suggests there may be value in systematically monitoring client emails for negative effects throughout treatment as a supplement to retrospective post-treatment reports. This will give therapists the opportunity to intervene as negative effects occur and potentially mitigate any impact they have on treatment outcomes. Future research, both qualitative and quantitative, is needed to gain a more nuanced understanding of negative effects associated with ICBT.

Effectiveness of guided Internet-delivered treatment for major depression in routine mental healthcare - An open study

Depression is one of the most prevalent mental health disorders and is estimated to become the leading cause of disability worldwide by 2030. Increasing access to effective treatment for depression is a major societal challenge. In this context, the increasing use of computers in the form of laptops or smartphones has made it feasible to increase access to mental healthcare through digital technology. In this study, we examined the effectiveness of a 14-week therapist-guided Internet-delivered program for patients with major depression undergoing routine care. From 2015 to 2018, 105 patients were included in the study. For depressive symptoms, we identified significant within-group effect sizes (post-treatment: d = 0.96; 6-month follow-up: d = 1.21). We also found significant effects on secondary anxiety and insomnia symptoms (d = 0.55-0.92). Clinically reliable improvement was reported by 48% of those undergoing the main parts of the treatment, whereas 5% of the participants reported a clinically significant deterioration. However, a large proportion of patients showed no clinically reliable change. In summary, the study identified large treatment effects, but also highlighted room for improvement in the usability of the treatment.

Response and Remission Rates in Internet-Based Cognitive Behavior Therapy: An Individual Patient Data Meta-Analysis

Background: Internet-delivered cognitive behavior therapy (ICBT) was developed over 20 years ago and has since undergone a number of controlled trials, as well as several systematic reviews and meta-analyses. However, the crucial question of response rates remains to be systematically investigated. The aim of this individual patient meta-analysis (IPDMA) was to use a large dataset of trials conducted in Sweden to determine reliable change and recovery rates across trials for a range of conditions. Methods: We used previously collected and aggregated data from 2,866 patients in 29 Swedish clinical trials of ICBT for three categories of conditions: anxiety disorders, depression, and others. Raw scores at pre-treatment and post-treatment were used in an IPDMA to determine the rate of reliable change and recovery. Jacobson and Truax's, (1991) reliable change index (RCI) was calculated for each primary outcome measure in the trials as well as the recovery rates for each patient, with the additional requirement of having improved substantially. We subsequently explored potential predictors using binomial logistic regression. Results: In applying an RCI of z = 1.96, 1,162 (65.6%) of the patients receiving treatment were classified as achieving recovery, and 620 (35.0%) were classified as reaching remission. In terms of predictors, patients with higher symptom severity on the primary outcome measure at baseline [odds ratio (OR) = 1.36] and being female (OR = 2.22) increased the odds of responding to treatment. Having an anxiety disorder was found to decrease the response to treatment (OR = 0.51). Remission was predicted by diagnosis in the same direction (OR = 0.28), whereas symptom severity was inversely predictive of worse outcome (OR = 0.81). Conclusions: Response seems to occur among approximately half of all clients administered ICBT, whereas about a third reach remission. This indicates that the efficacy of ICBT is in line with that of CBT based in prior trials, with a possible caveat being the lower remission rates. Having more symptoms and being female might increase the chances of improvement, and a small negative effect of having anxiety disorder versus depression and other conditions may also exist. A limitation of the IPDMA was that only studies conducted in Sweden were included.