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

Factors influencing the effectiveness of digital cognitive behavioural therapy for chronic insomnia in clinical practice

Digital cognitive behavioural therapy for chronic insomnia (D-CBT-I) has been shown to be as efficacious as traditional CBT-I. However, not all patients achieve insomnia remission after treatment. We explored the factors influencing the effectiveness of D-CBT-I in a clinical practice. A total of 414 Asian chronic insomniacs were studied during a 6 week D-CBT-I intervention. All patients were assessed at baseline and posttreatment and were determined to be remitters or non-remitters, responders or non-responders by posttreatment criteria; Insomnia Severity Index (ISI <8) or ISI reduction ≥8, to examine whether remission and response status were associated with patient baseline characteristics. The average baseline ISI score in all subjects was 16.29 points. At posttreatment, 192 (46.4%) patients achieved ISI remission and 218 (52.7%) patients demonstrated an ISI response. An increased baseline early morning awakening time and ISI score were independently associated with a lower odds for remission (OR, 0.995 and 0.991, respectively). Increased baseline Patients Health Questionnaire-9 score was independently associated with higher odds for response (OR, 1.114). Our results suggest that D-CBT-I can be recommended as the first-line treatment for chronic insomnia, particularly in insomniacs with milder insomnia symptoms and more severe depressive symptoms. Meanwhile, the effectiveness of D-CBT-I was adversely affected by longer early morning awakening time and higher insomnia severity at pretreatment, which may be improved by more intense intervention and greater therapeutic support or by traditional CBT-I.

Predicting non-improvement of symptoms in daily mental healthcare practice using routinely collected patient-level data: a machine learning approach

Objectives

Anxiety and mood disorders greatly affect the quality of life for individuals worldwide. A substantial proportion of patients do not sufficiently improve during evidence-based treatments in mental healthcare. It remains challenging to predict which patients will or will not benefit. Moreover, the limited research available on predictors of treatment outcomes comes from efficacy RCTs with strict selection criteria which may limit generalizability to a real-world context. The current study evaluates the performance of different machine learning (ML) models in predicting non-improvement in an observational sample of patients treated in routine specialized mental healthcare.

Methods

In the current longitudinal exploratory prediction study diagnosis-related, sociodemographic, clinical and routinely collected patient-reported quantitative outcome measures were acquired during treatment as usual of 755 patients with a primary anxiety, depressive, obsessive compulsive or trauma-related disorder in a specialized outpatient mental healthcare center. ML algorithms were trained to predict non-response (< 0.5 standard deviation improvement) in symptomatic distress 6 months after baseline. Different models were trained, including models with and without early change scores in psychopathology and well-being and models with a trimmed set of predictor variables. Performance of trained models was evaluated in a hold-out sample (30%) as a proxy for unseen data.

Results

ML models without early change scores performed poorly in predicting six-month non-response in the hold-out sample with Area Under the Curves (AUCs) < 0.63. Including early change scores slightly improved the models' performance (AUC range: 0.68-0.73). Computationally-intensive ML models did not significantly outperform logistic regression (AUC: 0.69). Reduced prediction models performed similar to the full prediction models in both the models without (AUC: 0.58-0.62 vs. 0.58-0.63) and models with early change scores (AUC: 0.69-0.73 vs. 0.68-0.71). Across different ML algorithms, early change scores in psychopathology and well-being consistently emerged as important predictors for non-improvement.

Conclusion

Accurately predicting treatment outcomes in a mental healthcare context remains challenging. While advanced ML algorithms offer flexibility, they showed limited additional value compared to traditional logistic regression in this study. The current study confirmed the importance of taking early change scores in both psychopathology and well-being into account for predicting longer-term outcomes in symptomatic distress.

Moderators of the cost-effectiveness of transdiagnostic CBT for anxiety disorders over an 8-month time horizon using a net-benefit regression framework

BACKGROUND

Access to evidence-based psychological treatment is a concern in many parts of the globe due to government-level financial constraints and patient-level barriers. Transdiagnostic cognitive behavioural therapy (tCBT) is an effective treatment approach that uses a single protocol for anxiety disorders which could enhance the dissemination of evidence-based psychotherapy. In a context of limited resources, the study of treatment moderators can allow to identify subgroups for which the cost-effectiveness of an intervention differs, information that could impact decision-making. So far, there has been no economic evaluation of tCBT for different subpopulations. The objectives of this study, using the net-benefit regression framework, were to explore clinical and sociodemographic factors as potential moderators of the cost-effectiveness of tCBT compared to treatment-as-usual (TAU).

METHODS

This is a secondary data analysis of a pragmatic randomized controlled trial opposing tCBT added to TAU (n = 117) to TAU only (n = 114). Data on costs from the health system and the limited societal perspectives, as well as anxiety-free days, an effectiveness measure based on the Beck Anxiety Inventory, were collected over an 8-month time horizon and used to derive individual net-benefits. The net-benefit regression framework was used to assess moderators of the cost-effectiveness of tCBT + TAU as opposed to TAU alone. Variables of sociodemographic and clinical nature were assessed.

RESULTS

Results showed that the number of comorbid anxiety disorders significantly moderated the cost-effectiveness of tCBT + TAU compared to TAU from the limited societal perspective.

CONCLUSIONS

The number of comorbid anxiety disorders was identified as a moderator affecting the cost-effectiveness of tCBT + TAU compared to TAU from the limited societal perspective. More research is needed to strengthen the case of tCBT from an economic standpoint for large-scale dissemination.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT02811458, 23/06/2016.

Remote cognitive behavioral therapy for older adults with anxiety symptoms: A systematic review and meta-analysis

INTRODUCTION

In-person cognitive behavioral therapy (CBT) can reduce self-reported anxiety in older adults. However, studies are limited for remote CBT. We assessed the effectiveness of remote CBT in mitigating self-reported anxiety in older adults.

METHODS

We conducted a systematic review and meta-analysis based on a literature search of PubMed, Embase, PsycInfo, and Cochrane databases up to March 31, 2021, for randomized controlled clinical trials comparing the effectiveness of remote CBT versus non-CBT controls on mitigating self-reported anxiety in older adults. We calculated within-group pre-to-post-treatment standardized mean difference using Cohen's d, obtained the difference between a remote CBT group and a non-CBT control group as our effect size for cross-study comparison, and conducted a random-effects meta-analysis. Changes in scores on self-reported anxiety symptoms (Generalized Anxiety Disorder-7 item Scale, Penn State Worry Questionnaire, or Penn State Worry Questionnaire - Abbreviated), and self-reported depressive symptoms (Patient Health Questionnaire-9 item Scale or Beck Depression Inventory) were primary and secondary outcomes, respectively.

RESULTS

Six eligible studies, containing 633 participants with a pooled mean age of 66.6 years, were included in the systematic review and meta-analysis. There was a significant mitigating effect of intervention on self-reported anxiety, favoring remote CBT over non-CBT controls (between-group effect size: -0.63; 95% CI: -0.99 to -0.28). We also found a significant mitigating effect of intervention on self-reported depressive symptoms (between-group effect size: -0.74; 95% CI: -1.24 to -0.25).

DISCUSSION

Remote CBT is more effective in reducing self-reported anxiety and depressive symptoms than non-CBT control in older adults.

Outcomes and prognosis of adjustment disorder in adults: A systematic review

Adjustment disorder (AD) is one of the most commonly diagnosed mental health disorders and is generally conceptualized to be mild and short-lived. Despite the frequent use of AD in clinical settings, little is known about the prognosis of this condition. Our goal was to systematically review research on a range of AD outcomes in order to provide a broad characterization of AD prognosis. We conducted searches in MEDLINE, EMBASE, and PsycINFO. We included 31 cohort or randomized controlled trials with a total of 1,385,358 participants. Many patients maintained an AD diagnosis or were diagnosed with another mental health disorder months to years after initial diagnosis. Patients with AD tended to show symptom improvement at higher rates and to utilize less treatment than did patients with other disorders. AD-diagnosed groups experienced subsequent development of numerous physical conditions, such as infection, cancers, Parkinson's disease, and cardiovascular events, at higher rates than did control groups. Results were mixed regarding suicidality and occupational impairment. We rated most studies as having a moderate risk of bias. Based on limited findings, AD appears to progress as a milder disorder than do other disorders, but it not uncommonly transitions to more severe mental health states and may predict the development of future health issues, both mental and physical. Future prospective research that conforms to prognosis study guidelines is needed to better understand the course of this common disorder.

The effectiveness and associated factors of online psychotherapy on COVID-19 related distress: A systematic review and meta-analysis

Objective

A quantitative synthesis of online psychotherapies' effectiveness in managing COVID-19 related distress is lacking. This study aimed to estimate online psychological interventions' effectiveness and associated factors on COVID-19 related psychological distress.

Methods

Multi-databases including PubMed, EBSCO, ProQuest, and Cochrane were searched repeatedly till the end of June 2022. Hand-picking was also utilized for relevant papers. Depression, anxiety, stress, and quality of sleep were evaluated as outcomes. The risk of bias was evaluated using the Cochrane tool. Data analyses were conducted through Review Manager (version 5.4.1).

Results

A total of 13 studies involving 1,897 participants were included for meta-analysis. Results showed that online psychotherapy significantly reduced the levels of depression [standard mean difference, SMD = −0.45, 95% CI (−0.69, −0.20)], anxiety [SMD = −0.67, 95% CI (−0.99, −0.36)], and stress [SMD = −0.73, 95% CI (−1.11, −0.34)], but not quality of sleep [SMD = −0.53, 95% CI (−1.23, 0.17)]. In addition, guided therapies were more effective than self-help ones on reducing levels of anxiety (χ2 = 5.58, p = 0.02, and I2 = 82.1%), and ≤ 2 weeks' daily interventions were more effective on treating depression than 2-month weekly interventions (χ2 = 7.97, p = 0.005, I2 = 87.5%).

Conclusion

Online psychological interventions effectively reduced COVID-19 related depression, anxiety, and stress levels, and the effectiveness was influenced by settings like guidance and duration and frequency.

Systematic review registration

https://inplasy.com/inplasy-2022-7-0081/, identifier: INPLASY202270081.

Adolescent Resilience during the COVID-19 Pandemic: A Review of the Impact of the Pandemic on Developmental Milestones

This review explores the literature regarding the ways in which the COVID-19 pandemic has affected the navigation of developmental milestones among adolescents, specifically those in late adolescence, across several domains of their lives. The exploration is contextualized globally, focusing on five key areas: mental health, physical health, education, peer relationships, and family relationships. Implications for practice and interventions are explored in each key area to provide recommendations for those working with adolescents, as well as future research. The changes brought about by the pandemic and the readjustment to what some have referred to as the “new normalcy” will undoubtedly have lasting effects on all areas of life for this cohort of adolescents, who have shown remarkable resilience navigating this new and unfamiliar world. These changes are synthesized, with the aim to highlight differences and similarities of the shared experiences of the pandemic globally. After exploring the current realities, this chapter goes on to outline the ways in which the experience of such a significant developmental period of one’s life during the COVID-19 pandemic will have an impact on adolescents for years to come. Although it is still impossible to comprehend the long-term effects, in examining proximal effects, we can postulate distal implications and potential future effects, as well as possible ways to mitigate these implications as we transition back to more of what was experienced pre-pandemic life, from a post-pandemic experience.

Are Changes in Beliefs About Rumination and in Emotion Regulation Skills Mediators of the Effects of Internet-Delivered Cognitive-Behavioral Therapy for Depression and Anxiety? Results from a Randomized Controlled Trial

Background

Internet-delivered cognitive behavior therapy (iCBT) is effective in treating anxiety and depression. Research on how these interventions operate is scarce. This study explored whether emotion regulation skills and positive beliefs about rumination were affected by iCBT and if these constructs mediated changes in depression and anxiety.

Methods

This is a secondary analysis of a pragmatic randomized waitlist-controlled trial testing the effectiveness of supported iCBT. Adults with at least mild symptoms of depression or anxiety were included. Depression (PHQ-9), anxiety (GAD-7), positive beliefs about rumination (PBRS-A) and two emotion regulation skills: cognitive reappraisal (ERQ-A) and expressive suppression (ERQ-S), were measured at baseline and 8-weeks post-treatment.

Results

The analyses included 358 participants, 71% were female. Median age was 29. Linear mixed models showed statistically significant differences along ERQ-A in favor of the iCBT group (b = 1.83, SE = 0.82, p = .026). Mediation analyses showed reductions in depression (b = 0.31, SE = 0.15, p = 0.043) and anxiety symptoms (b = 0.27, SE = 0.14, p = 0.057) were partially mediated by gains in ERQ-A. No effects were observed for PBRS-A and ERQ-S.

Conclusions

These results align with findings from face-to-face therapy and add to the scarce literature on mediators of effects of iCBT, contributing to the understanding of how these interventions operate. Since mediator and outcome variables were measured at the same time, partial mediation results should be interpreted with caution since the study design did not account for temporality and therefore causality effects cannot be confirmed.

Trial Registration

ISRCTN91967124.

A Therapeutic Relational Agent for Reducing Problematic Substance Use (Woebot): Development and Usability Study

Background

Misuse of substances is common, can be serious and costly to society, and often goes untreated due to barriers to accessing care. Woebot is a mental health digital solution informed by cognitive behavioral therapy and built upon an artificial intelligence–driven platform to deliver tailored content to users. In a previous 2-week randomized controlled trial, Woebot alleviated depressive symptoms.

Objective

This study aims to adapt Woebot for the treatment of substance use disorders (W-SUDs) and examine its feasibility, acceptability, and preliminary efficacy.

Methods

American adults (aged 18-65 years) who screened positive for substance misuse without major health contraindications were recruited from online sources and flyers and enrolled between March 27 and May 6, 2020. In a single-group pre/postdesign, all participants received W-SUDs for 8 weeks. W-SUDs provided mood, craving, and pain tracking and modules (psychoeducational lessons and psychotherapeutic tools) using elements of dialectical behavior therapy and motivational interviewing. Paired samples t tests and McNemar nonparametric tests were used to examine within-subject changes from pre- to posttreatment on measures of substance use, confidence, cravings, mood, and pain.

Results

The sample (N=101) had a mean age of 36.8 years (SD 10.0), and 75.2% (76/101) of the participants were female, 78.2% (79/101) were non-Hispanic White, and 72.3% (73/101) were employed. Participants’ W-SUDs use averaged 15.7 (SD 14.2) days, 12.1 (SD 8.3) modules, and 600.7 (SD 556.5) sent messages. About 94% (562/598) of all completed psychoeducational lessons were rated positively. From treatment start to end, in-app craving ratings were reduced by half (87/101, 86.1% reporting cravings in the app; odds ratio 0.48, 95% CI 0.32-0.73). Posttreatment assessment completion was 50.5% (51/101), with better retention among those who initially screened higher on substance misuse. From pre- to posttreatment, confidence to resist urges to use substances significantly increased (mean score change +16.9, SD 21.4; P<.001), whereas past month substance use occasions (mean change −9.3, SD 14.1; P<.001) and scores on the Alcohol Use Disorders Identification Test-Concise (mean change −1.3, SD 2.6; P<.001), 10-item Drug Abuse Screening Test (mean change −1.2, SD 2.0; P<.001), Patient Health Questionnaire-8 item (mean change 2.1, SD 5.2; P=.005), Generalized Anxiety Disorder-7 (mean change −2.3, SD 4.7; P=.001), and cravings scale (68.6% vs 47.1% moderate to extreme; P=.01) significantly decreased. Most participants would recommend W-SUDs to a friend (39/51, 76%) and reported receiving the service they desired (41/51, 80%). Fewer felt W-SUDs met most or all of their needs (22/51, 43%).

Conclusions

W-SUDs was feasible to deliver, engaging, and acceptable and was associated with significant improvements in substance use, confidence, cravings, depression, and anxiety. Study attrition was high. Future research will evaluate W-SUDs in a randomized controlled trial with a more diverse sample and with the use of greater study retention strategies.

Trial Registration

ClinicalTrials.gov NCT04096001; http://clinicaltrials.gov/ct2/show/NCT04096001.

Telehealth mental health services during COVID-19: summary of evidence and clinical practice

OBJECTIVE

To provide a rapid clinical update on the evidence for telehealth in mental healthcare in the context of the COVID-19 pandemic public health measures.

CONCLUSIONS

Telehealth has been rapidly implemented in metropolitan and rural settings and the existing evidence base demonstrates that it represents an effective mode of service delivery.