Predictors of Response to Web-Based Cognitive Behavioral Therapy With High-Intensity Face-to-Face Therapist Guidance for Depression: A Bayesian Analysis

Assessing Patient Adherence to and Engagement With Digital Interventions for Depression in Clinical Trials: Systematic Literature Review

BACKGROUND

New approaches to the treatment of depression are necessary for patients who do not respond to current treatments or lack access to them because of barriers such as cost, stigma, and provider shortage. Digital interventions for depression are promising; however, low patient engagement could limit their effectiveness.

OBJECTIVE

This systematic literature review (SLR) assessed how participant adherence to and engagement with digital interventions for depression have been measured in the published literature, what levels of adherence and engagement have been reported, and whether higher adherence and increased engagement are linked to increased efficacy.

METHODS

We focused on a participant population of adults (aged ≥18 years) with depression or major depressive disorder as the primary diagnosis and included clinical trials, feasibility studies, and pilot studies of digital interventions for treating depression, such as digital therapeutics. We screened 756 unique records from Ovid MEDLINE, Embase, and Cochrane published between January 1, 2000, and April 15, 2022; extracted data from and appraised the 94 studies meeting the inclusion criteria; and performed a primarily descriptive analysis. Otsuka Pharmaceutical Development & Commercialization, Inc (Princeton, New Jersey, United States) funded this study.

RESULTS

This SLR encompassed results from 20,111 participants in studies using 47 unique web-based interventions (an additional 10 web-based interventions were not described by name), 15 mobile app interventions, 5 app-based interventions that are also accessible via the web, and 1 CD-ROM. Adherence was most often measured as the percentage of participants who completed all available modules. Less than half (44.2%) of the participants completed all the modules; however, the average dose received was 60.7% of the available modules. Although engagement with digital interventions was measured differently in different studies, it was most commonly measured as the number of modules completed, the mean of which was 6.4 (means ranged from 1.0 to 19.7) modules. The mean amount of time participants engaged with the interventions was 3.9 (means ranged from 0.7 to 8.4) hours. Most studies of web-based (34/45, 76%) and app-based (8/9, 89%) interventions found that the intervention group had substantially greater improvement for at least 1 outcome than the control group (eg, care as usual, waitlist, or active control). Of the 14 studies that investigated the relationship between engagement and efficacy, 9 (64%) found that increased engagement with digital interventions was significantly associated with improved participant outcomes. The limitations of this SLR include publication bias, which may overstate engagement and efficacy, and low participant diversity, which reduces the generalizability.

CONCLUSIONS

Patient adherence to and engagement with digital interventions for depression have been reported in the literature using various metrics. Arriving at more standardized ways of reporting adherence and engagement would enable more effective comparisons across different digital interventions, studies, and populations.

A blended psychological intervention for postpartum depression: acceptability and preferences in women presenting depressive symptoms

OBJECTIVES

To evaluate the acceptability of and preferences for a blended psychological intervention (combining face-to-face sessions and web-based interventions) for the treatment of postpartum depression among Portuguese women presenting depressive symptoms and to explore the factors associated with its acceptability.

BACKGROUND

Despite its high prevalence and the existence of effective treatment, still few women seek professional help for postpartum depression, demanding for new treatment formats, such as blended interventions.

METHODS

Women (n = 235) presenting postpartum depressive symptoms (EPDS>9) completed an internet survey assessing sociodemographic and clinical information, depressive symptoms, e-health literacy and the acceptability of and preferences for a blended intervention for postpartum depression.

RESULTS

Most of the participants considered a blended intervention for postpartum depression to be useful and would be available to use it. Women reported significantly more advantages than disadvantages in regard to this treatment format. Married women, employed, with younger babies and with less severe depressive symptoms had a higher likelihood of finding a blended intervention useful. Higher educational levels increased the likelihood of being available to obtain a blended treatment. Most participants preferred an equal distribution of content across face-to-face and online sessions. Approximately one-third of the sample preferred a 75% face-to-face/ 25% online proportion. Most of the women preferred a duration of 45-60 minutes for face-to-face sessions and 30-45 minutes for online sessions.

CONCLUSION

Our findings support and inform the development of blended psychological treatments for postpartum depression, according to women's preferences, and highlight the prioritisation of this format according to women's characteristics.

Age, Motivation, and Emotion Regulation Skills Predict Treatment Outcome in an Internet-Based Self-Help Intervention for COVID-19 Related Psychological Distress

Introduction

First evidence suggests that internet-based self-help interventions effectively reduce COVID-19 related psychological distress. However, it is yet unclear which participant characteristics are associated with better treatment outcomes. Therefore, we conducted secondary analyses on data from a randomized controlled trial investigating the efficacy of a 3-week internet-based self-help intervention for COVID-19 related psychological distress. In this exploratory analysis, we examined several predictors ranging from sociodemographic variables to psychological distress, resource-related, and treatment-related variables. This includes, for example, age, motivation, and emotion regulation skills. Treatment outcomes were defined as post-treatment depressive symptoms and post-treatment resilience.

Methods

In a total of 107 participants with at least mild depressive symptoms, possible predictor variables and treatment outcomes were assessed using self-report measures. For example, emotion regulation skills were assessed by the Self-report measure for the assessment of emotion regulation skills. In a first step, we performed a separate linear regression analysis for each potential predictor. In a second step, predictors meeting a significant threshold of p < 0.05 were entered in linear multiple regression models. Baseline scores of the respective outcome measure were controlled for.

Results

The mean age of the participants was 40.36 years (SD = 14.59, range = 18–81 years) with the majority being female (n = 87, 81.3%). Younger age predicted lower post-treatment depressive symptoms. Additionally, higher motivation to use the intervention and better pre-treatment emotion regulation skills predicted higher post-treatment resilience.

Conclusion

The current study provides preliminary evidence regarding the relationship between participant characteristics and treatment outcome in internet-based self-help interventions for COVID-19 related distress. Our results suggest that under the circumstances surrounding COVID-19 such interventions might be particularly beneficial for young adults regarding depressive symptoms. Moreover, focusing on participants' existing strengths might be a promising approach to promote resilience through internet-based self-help interventions. However, since this was an exploratory analysis in an uncontrolled setting, further studies are needed to draw firm conclusions about the relationship of participant characteristics and treatment outcome in internet-based self-help interventions for COVID-19 related psychological distress.

Inpatient psychotherapy for depression in a large routine clinical care sample: A Bayesian approach to examining clinical outcomes and predictors of change

BACKGROUND

A routinely collected dataset was analyzed (1) to determine the naturalistic effectiveness of inpatient psychotherapy for depression in routine psychotherapeutic care, and (2) to identify potential predictors of change.

METHODS

In a sample of 22,681 inpatients with depression, pre-post and pre-follow-up effect sizes were computed for various outcome variables. To build a probabilistic model of predictors of change, an independent component analysis generated components from demographic and clinical data, and Bayesian EFA extracted factors from the available pre-test, post-test and follow-up questionnaires in a subsample (N = 6377). To select the best-fitted model, the BIC of different path models were compared. A Bayesian path analysis was performed to identify the most important factors to predict changes.

RESULTS

Effect sizes were large for the primary outcome and moderate for various secondary outcomes. Almost all pretreatment factors exerted significant influences on different baseline factors. Several factors were found to be resistant to change during treatment: suicidality, agoraphobia, life dissatisfaction, physical disability and pain. The strongest cross-loadings were observed from suicidality on negative cognitions, from agoraphobia on anxiety, and from physical disability on perceived disability.

LIMITATIONS

No causal conclusions can be drawn directly from our results as we only used cross-lagged panel data without control group.

CONCLUSIONS

The results indicate large effects of inpatient psychotherapy for depression in routine clinical care. The direct influence of pretreatment factors decreased over the course of treatment. However, some factors appeared stable and difficult to treat, which might hinder treatment outcome. Findings of different predictors of change are discussed.

Praxisorientierte Forschung in der Psychotherapie

Zusammenfassung. In den letzten Jahrzehnten hat sich durch randomisiert-kontrollierte Studien (RCTs) eine breite Evidenzbasis von Psychotherapie mit mittleren bis großen Effekten für verschiedene psychische Störungen gebildet. Neben der Bestimmung dieser Wirksamkeit („Efficacy“) ebneten Studien zur Wirksamkeit unter alltäglichen Routinebedingungen („Effectiveness“) historisch den Weg zur Entwicklung eines praxisorientierten Forschungsparadigmas. Im Beitrag wird argumentiert, dass im Rahmen dieses Paradigmas praxisbasierte Studien eine wertvolle Ergänzung zu RCTs darstellen, da sie existierende Probleme in der Psychotherapieforschung adressieren können. In der gegenwärtigen praxisorientierten Forschung liefern dabei neue Ansätze aus der personalisierten Medizin und Methoden aus der ‚Computational Psychiatry‘ wichtige Anhaltspunkte zur Optimierung von Effekten in der Psychotherapie. Im Kontext der Personalisierung werden bspw. klinische multivariable Prädiktionsmodelle entwickelt, welche durch Rückmeldeschleifen an Praktiker_innen kurzfristig ein evidenzbasiertes Outcome-Monitoring ermöglicht und langfristig das Praxis-Forschungsnetzwerk in Deutschland stärkt. Am Ende des Beitrags werden zukünftige Richtungen für die praxisorientierte Forschung im Sinne des ‘Precision Mental Health Care’ -Paradigmas abgeleitet und diskutiert.

Characteristics of Mobile Health Platforms for Depression and Anxiety: Content Analysis Through a Systematic Review of the Literature and Systematic Search of Two App Stores

Background

Mobile health (mHealth) platforms show promise in the management of mental health conditions such as anxiety and depression. This has resulted in an abundance of mHealth platforms available for research or commercial use.

Objective

The objective of this review is to characterize the current state of mHealth platforms designed for anxiety or depression that are available for research, commercial use, or both.

Methods

A systematic review was conducted using a two-pronged approach: searching relevant literature with prespecified search terms to identify platforms in published research and simultaneously searching 2 major app stores—Google Play Store and Apple App Store—to identify commercially available platforms. Key characteristics of the mHealth platforms were synthesized, such as platform name, targeted condition, targeted group, purpose, technology type, intervention type, commercial availability, and regulatory information.

Results

The literature and app store searches yielded 169 and 179 mHealth platforms, respectively. Most platforms developed for research purposes were designed for depression (116/169, 68.6%), whereas the app store search reported a higher number of platforms developed for anxiety (Android: 58/179, 32.4%; iOS: 27/179, 15.1%). The most common purpose of platforms in both searches was treatment (literature search: 122/169, 72.2%; app store search: 129/179, 72.1%). With regard to the types of intervention, cognitive behavioral therapy and referral to care or counseling emerged as the most popular options offered by the platforms identified in the literature and app store searches, respectively. Most platforms from both searches did not have a specific target age group. In addition, most platforms found in app stores lacked clinical and real-world evidence, and a small number of platforms found in the published research were available commercially.

Conclusions

A considerable number of mHealth platforms designed for anxiety or depression are available for research, commercial use, or both. The characteristics of these mHealth platforms greatly vary. Future efforts should focus on assessing the quality—utility, safety, and effectiveness—of the existing platforms and providing developers, from both commercial and research sectors, a reporting guideline for their platform description and a regulatory framework to facilitate the development, validation, and deployment of effective mHealth platforms.

Clinical Effectiveness of Blended CBT Compared vs Face-to-Face CBT for adult depression: a Randomised Controlled Non-Inferiority Trial (Preprint)

Background

Internet-based cognitive behavioral therapy (iCBT) has been demonstrated to be cost- and clinically effective. There is a need, however, for increased therapist contact for some patient groups. Combining iCBT with traditional face-to-face (FtF) consultations in a blended format may produce a new treatment format (B-CBT) with multiple benefits from both traditional CBT and iCBT, such as individual adaptation, lower costs than traditional therapy, wide geographical and temporal availability, and possibly lower threshold to implementation.

Objective

The primary aim of this study is to compare directly the clinical effectiveness of B-CBT with FtF-CBT for adult major depressive disorder.

Methods

A 2-arm randomized controlled noninferiority trial compared B-CBT for adult depression with treatment as usual (TAU). The trial was researcher blinded (unblinded for participants and clinicians). B-CBT comprised 6 sessions of FtF-CBT alternated with 6-8 web-based CBT self-help modules. TAU comprised 12 sessions of FtF-CBT. All participants were aged 18 or older and met the diagnostic criteria for major depressive disorder and were recruited via a national iCBT clinic. The primary outcome was change in depression severity on the 9-item Patient Health Questionnaire (PHQ-9). Secondary analyses included client satisfaction (8-item Client Satisfaction Questionnaire [CSQ-8]), patient expectancy (Credibility and Expectancy Questionnaire [CEQ]), and working (Working Alliance Inventory [WAI] and Technical Alliance Inventory [TAI]). The primary outcome was analyzed by a mixed effects model including all available data from baseline, weekly measures, 3-, 6, and 12-month follow-up.

Results

A total of 76 individuals were randomized, with 38 allocated to each treatment group. Age ranged from 18 to 71 years (SD 13.96) with 56 (74%) females. Attrition rate was 20% (n=15), which was less in the FtF-CBT group (n=6, 16%) than in the B-CBT group (n=9, 24%). As many as 53 (70%) completed 9 or more sessions almost equally distributed between the groups (nFtF-CBT=27, 71%; nB-CBT=26, 68%). PHQ-9 reduced 11.38 points in the FtF-CBT group and 8.10 in the B-CBT group. At 6 months, the mean difference was a mere 0.17 points. The primary analyses confirmed large and significant within-group reductions in both groups (FtF-CBT: β=–.03; standard error [SE] 0.00; P<.001 and B-CBT: β=–.02; SE 0.00; P<.001). A small but significant interaction effect was observed between groups (β=.01; SE 0.00; P=.03). Employment status influenced the outcome differently between groups, where the B-CBT group was seen to profit more from not being full-time employed than the FtF group.

Conclusions

With large within-group effects in both treatment arms, the study demonstrated feasibility of B-CBT in Denmark. At 6 months’ follow-up, there appeared to be no difference between the 2 treatment formats, with a small but nonsignificant difference at 12 months. The study seems to demonstrate that B-CBT is capable of producing treatment effects that are close to FtF-CBT and that completion rates and satisfaction rates were comparable between groups. However, the study was limited by small sample size and should be interpreted with caution.

Trial Registration

ClinicalTrials.gov NCT02796573; https://clinicaltrials.gov/ct2/show/NCT02796573

International Registered Report Identifier (IRRID)

RR2-10.1186/s12888-016-1140-y

Virtual versus Face-to-Face Cognitive Behavioral Treatment of Depression: Meta-Analytic Test of a Noninferiority Hypothesis and Men's Mental Health Inequities

Global rates of depression have increased significantly since the beginning of the COVID-19 pandemic. It is unclear how the recent shift of many mental health services to virtual platforms has impacted service users, especially for the male population which are significantly more likely to complete suicide than women. This paper presents the findings of a rapid meta-analytic research synthesis of 17 randomized controlled trials on the relative efficacy of virtual versus traditional face-to-face cognitive behavioral therapy (CBT) in mitigating symptoms of depression. Participants' aggregated depression scores were compared upon completion of the therapy (posttest) and longest follow-up measurement. The results supported the noninferiority hypothesis indicating that the two modes of CBT delivery are equally efficacious, but the results proved to be significantly heterogeneous indicating the presence of moderating effects. Indirect suggestive evidence was found to support moderation by gender; that is, depressed males may benefit more from virtual CBT. Perhaps, this field's most telling descriptive finding was that boys/men have been grossly underrepresented in its trials. Future trials ought to oversample those who have been at this field's margins to advance the next generation of knowledge, allowing us to best serve people of all genders, those who live in poverty, Indigenous, Black, and other Peoples of Colour, as well as any others at risk of being marginalized or oppressed in contemporary mental health care systems.

Predictors of Treatment Response to an Internet-Delivered Intervention Targeting Residual Cognitive Symptoms After Major Depressive Disorder

OBJECTIVE

Residual cognitive symptoms after depression are common and associated with reduced daily life functioning and an increased risk of depression relapse. There is a lack of knowledge on treatments targeting residual cognitive symptoms after major depressive disorder (MDD), including the factors associated with treatment response. The aim of the current study is to explore factors of treatment response to a guided internet-delivered intervention for former depressed adults experiencing residual cognitive symptoms.

METHOD

Forty-three former depressed adults with residual cognitive symptoms were included. Linear mixed model analyses were used to investigate the impact of pre-treatment demographic-, illness, and symptom variables, and therapy process variables, such as credibility, expectancy, and user behavior, on reduction in residual cognitive symptoms from pre-treatment to 6-month follow-up.

RESULTS

Having had MDD for a year or less predicted more reductions in residual cognitive symptoms from pre- to 6-month follow-up. Higher levels of perceived treatment credibility and expectancy evaluated in the early course of treatment did also predict a positive treatment response. No demographic-, symptom-variables, previous number of episodes with MDD, and user behavior were associated with change in residual cognitive symptoms.

CONCLUSION

This study suggests that individuals with shorter duration of previous depressions might have larger reductions in residual cognitive symptoms at 6-month follow-up compared to those with a longer duration of depression. Treatment credibility and expectancy also predicted treatment response and effort should also be made to ensure interventions credibility. Results should be interpreted with caution due to the study having a low sample size. Further investigation of predictors should be conducted in a full scale randomized controlled trial.

Acceptability and Effectiveness of Artificial Intelligence Therapy for Anxiety and Depression (Youper): Longitudinal Observational Study

Background

Youper is a widely used, commercially available mobile app that uses artificial intelligence therapy for the treatment of anxiety and depression.

Objective

Our study examined the acceptability and effectiveness of Youper. Further, we tested the cumulative regulation hypothesis, which posits that cumulative emotion regulation successes with repeated intervention engagement will predict longer-term anxiety and depression symptom reduction.

Methods

We examined data from paying Youper users (N=4517) who allowed their data to be used for research. To characterize the acceptability of Youper, we asked users to rate the app on a 5-star scale and measured retention statistics for users’ first 4 weeks of subscription. To examine effectiveness, we examined longitudinal measures of anxiety and depression symptoms. To test the cumulative regulation hypothesis, we used the proportion of successful emotion regulation attempts to predict symptom reduction.

Results

Youper users rated the app highly (mean 4.36 stars, SD 0.84), and 42.66% (1927/4517) of users were retained by week 4. Symptoms decreased in the first 2 weeks of app use (anxiety: d=0.57; depression: d=0.46). Anxiety improvements were maintained in the subsequent 2 weeks, but depression symptoms increased slightly with a very small effect size (d=0.05). A higher proportion of successful emotion regulation attempts significantly predicted greater anxiety and depression symptom reduction.

Conclusions

Youper is a low-cost, completely self-guided treatment that is accessible to users who may not otherwise access mental health care. Our findings demonstrate the acceptability and effectiveness of Youper as a treatment for anxiety and depression symptoms and support continued study of Youper in a randomized clinical trial.

Do sociodemographic variables moderate effects of an internet intervention for mild to moderate depressive symptoms? An exploratory analysis of a randomised controlled trial (EVIDENT) including 1013 participants

OBJECTIVE

To explore the moderating effects of sociodemographic variables on treatment benefits received from participating in an internet intervention for depression.

DESIGN

Randomised, assessor-blind, controlled trial.

SETTING

Online intervention, with participant recruitment using multiple settings, including inpatient and outpatient medical and psychological clinics, depression online forums, health insurance companies and the media (eg, newspaper, radio).

PARTICIPANTS

The EVIDENT trial included 1013 participants with mild to moderate depressive symptoms.

INTERVENTIONS

The intervention group subjects (n=509) received an online intervention (Deprexis) in addition to care as usual (CAU), while 504 participants received CAU alone.

METHODS

To explore subgroup differences, moderating effects were investigated using linear regression models based on intention-to-treat analyses. Moderating effects included sex, age, educational attainment, employment status, relationship status and lifetime frequency of episodes.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary endpoint was change in self-rated depression severity measured by the Patient Health Questionnaire-9 (PHQ-9), comparing baseline versus 12-week post-test assessment. Secondary outcome measures were the Hamilton Rating Scale for Depression and the Quick Inventory of Depressive Symptoms each at 12 weeks and at 6 and 12 months, and PHQ-9 at 6 and 12 months, respectively. In this article, we focus on the primary outcome measure only.

RESULTS

Between-group differences were observed in post-test scores, indicating the effectiveness of Deprexis. While the effects of the intervention could be demonstrated across all subgroups, some showed larger between-group differences than others. However, after exploring the moderating effects based on linear regression models, none of the selected variables was found to be moderating treatment outcomes.

CONCLUSIONS

Our findings suggest that Deprexis is equally beneficial to a wide range of people; that is, participant characteristics were not associated with treatment benefits. Therefore, participant recruitment into web-based psychotherapeutic interventions should be broad, while special attention may be paid to those currently under-represented in these interventions.

TRIAL REGISTRATION NUMBER

NCT01636752.

Digital Interventions for Screening and Treating Common Mental Disorders or Symptoms of Common Mental Illness in Adults: Systematic Review and Meta-analysis

BACKGROUND

Digital interventions targeting common mental disorders (CMDs) or symptoms of CMDs are growing rapidly and gaining popularity, probably in response to the increased prevalence of CMDs and better awareness of early help-seeking and self-care. However, no previous systematic reviews that focus on these novel interventions were found.

OBJECTIVE

This systematic review aims to scope entirely web-based interventions that provided screening and signposting for treatment, including self-management strategies, for people with CMDs or subthreshold symptoms. In addition, a meta-analysis was conducted to evaluate the effectiveness of these interventions for mental well-being and mental health outcomes.

METHODS

Ten electronic databases including MEDLINE, PsycINFO, and EMBASE were searched from January 1, 1999, to early April 2020. We included randomized controlled trials (RCTs) that evaluated a digital intervention (1) targeting adults with symptoms of CMDs, (2) providing both screening and signposting to other resources including self-care, and (3) delivered entirely through the internet. Intervention characteristics including target population, platform used, key design features, and outcome measure results were extracted and compared. Trial outcome results were included in a meta-analysis on the effectiveness of users' well-being and mental health outcomes. We also rated the meta-analysis results with the Grading of Recommendations, Assessment, Development, and Evaluations approach to establish the quality of the evidence.

RESULTS

The electronic searches yielded 21 papers describing 16 discrete digital interventions. These interventions were investigated in 19 unique trials including 1 (5%) health economic study. Most studies were conducted in Australia and North America. The targeted populations varied from the general population to allied health professionals. All interventions offered algorithm-driven screening with measures to assess symptom levels and to assign treatment options including automatic web-based psychoeducation, self-care strategies, and signposting to existing services. A meta-analysis of usable trial data showed that digital interventions improved well-being (3 randomized controlled trials [RCTs]; n=1307; standardized mean difference [SMD] 0.40; 95% CI 0.29 to 0.51; I2=28%; fixed effect), symptoms of mental illness (6 RCTs; n=992; SMD -0.29; 95% CI -0.49 to -0.09; I2=51%; random effects), and work and social functioning (3 RCTs; n=795; SMD -0.16; 95% CI -0.30 to -0.02; I2=0%; fixed effect) compared with waitlist or attention control. However, some follow-up data failed to show any sustained effects beyond the post intervention time point. Data on mechanisms of change and cost-effectiveness were also lacking, precluding further analysis.

CONCLUSIONS

Digital mental health interventions to assess and signpost people experiencing symptoms of CMDs appear to be acceptable to a sufficient number of people and appear to have enough evidence for effectiveness to warrant further study. We recommend that future studies incorporate economic analysis and process evaluation to assess the mechanisms of action and cost-effectiveness to aid scaling of the implementation.

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.

Moderators of Cognitive Therapy and Bright Light Therapy Effects on Depressive Symptoms in Patients with Breast Cancer

BACKGROUND

Cognitive therapy (CT) and bright light therapy (BLT) have been found to be effective to treat depressive symptoms in breast cancer patients. No study has investigated the baseline patients' characteristics that are associated with better outcomes with CT vs. BLT in this population. This study aimed to assess, in breast cancer patients, the moderating role of eight clinical variables on the effects of CT and BLT on depressive symptoms.

METHODS

This is a secondary analysis of a randomized controlled trial conducted in 59 women who received an 8-week CT or BLT and completed questionnaires evaluating depression and possible moderating variables.

RESULTS

Patients benefited more from BLT when they had no prior history of major depressive disorder, higher depression scores on the Hospital Anxiety and Depression Scale (HADS-D) at baseline, a greater initial preference for BLT, and when they received BLT during spring or summer. Patients benefited more from CT when they had a lower initial preference for receiving CT, higher depression scores on the HADS-D, and seasonal depressive symptoms.

CONCLUSIONS

Although replication is needed, findings of this study suggest the existence of different profiles of patients more likely to benefit from CT and BLT.

TRIAL REGISTRATION

NCT01637103 https://clinicaltrials.gov/ct2/show/NCT01637103.

Guided Self-Help Works: Randomized Waitlist Controlled Trial of Pacifica, a Mobile App Integrating Cognitive Behavioral Therapy and Mindfulness for Stress, Anxiety, and Depression

Background

Despite substantial improvements in technology and the increased demand for technology-enabled behavioral health tools among consumers, little progress has been made in easing the burden of mental illness. This may be because of the inherent challenges of conducting traditional clinical trials in a rapidly evolving technology landscape.

Objective

This study sought to validate the effectiveness of Pacifica, a popular commercially available app for the self-management of mild-to-moderate stress, anxiety, and depression.

Methods

A total of 500 adults with mild-to-moderate anxiety or depression were recruited from in-app onboarding to participate in a randomized waitlist controlled trial of Pacifica. We conducted an all-virtual study, recruiting, screening, and randomizing participants through a Web-based participant portal. Study participants used the app for 1 month, with no level of use required, closely mimicking real-world app usage. Participants in the waitlist group were given access to the app after 1 month. Measurements included self-reported symptoms of stress, anxiety, depression, and self-efficacy. We performed an intent-to-treat analysis to examine the interactive effects of time and condition.

Results

We found significant interactions between time and group. Participants in the active condition demonstrated significantly greater decreases in depression, anxiety, and stress and increases in self-efficacy. Although we did not find a relationship between overall engagement with the app and symptom improvement, participants who completed relatively more thought record exercises sustained improvements in their symptoms through the 2-month follow-up to a greater degree than those who completed fewer. In addition, we found that participants who reported concomitantly taking psychiatric medications during the trial benefitted less from the app, as measured by the symptoms of anxiety and stress.

Conclusions

This study provides evidence that Pacifica, a popular commercially available self-help app, is effective in reducing self-reported symptoms of depression, anxiety, and stress, particularly among individuals who utilize thought records and are not taking psychiatric medication.

Trial Registration

ClinicalTrials.gov NCT03333707; https://clinicaltrials.gov/ct2/show/NCT03333707 (Archived by WebCite at http://www.webcitation.org/78YE07ADB)

Psychosocial, psychopharmacological and demographic predictors of changes in psychological distress over a course of computerised cognitive behavioural therapy (cCBT)

Social group identification, socioeconomic deprivation, and a number of other clinical and demographic factors have been found to predict severity of psychological distress prior to treatment in those referred to receive computerised cognitive behavioural therapy (cCBT) as an intervention for mild to moderate depression. The aim of the current study is to investigate whether the same key factors are able to predict magnitude of change in psychological distress across treatment in a sample receiving cCBT. Participants (N = 1158) consisted of individuals completing the 'Beating the Blues' (BtB) programme. Participants completed three versions of the group identifications scale (GIS), one for each of three groups: family, community, and a social group of choice. Changes in psychological distress showed statistically significant improvements between pre- and post-treatment assessment in all outcome measure subscales. Significantly greater changes (reductions) in psychological distress were found in those who had more severe pre-treatment psychological distress, those who lived in a lesser state of socioeconomic deprivation, those who identified with more social groups, and those taking antidepressant medication (ADM) concurrently. These findings provide valuable information on the likely course of treatment in those receiving cCBT, and highlight both the potential of social group identification as a 'social cure' for poor psychological health and the inequalities of the socioeconomic health gradient.

Guided Internet-Based Cognitive Behavioral Therapy for Adult Depression and Anxiety in Routine Secondary Care: Observational Study

BACKGROUND

Internet-based cognitive behavioral therapy (iCBT) is a promising new treatment method for depression and anxiety. However, it is important to determine whether its results can be replicated in routine care before its implementation on a large scale. Although many studies have demonstrated the efficacy of iCBT under controlled conditions, only a few studies have investigated its effectiveness in routine care. Furthermore, several effects of iCBT such as treatment effects in routine care are unclear.

OBJECTIVE

This study aimed to evaluate the clinical effectiveness of iCBT for depression and anxiety in routine secondary care.

METHODS

n a retrospective cohort study, we analysed patients treated for depression or anxiety in a dedicated iCBT clinic in secondary care in Denmark. Patients were examined before treatment and weekly thereafter by using the Patient Health Questionnaire-9 and the Generalized Anxiety Disorder-7 scales for the diagnoses of depression and anxiety, respectively. Primary analyses were conducted using a linear mixed-effects model with random slope and intercept. Secondary analyses were conducted using baseline characteristics as predictors (gender, age, highest level of education, occupational status, marital status, psychotropic medication use, consumption of alcohol, and leisure drugs). Additionally, logistic regression analyses were used to predict noncompletion of treatment.

RESULTS

A total of 203 (depression, N=60; anxiety, N=143) patients were included. Participants were mainly female (78.3% with depression and 65.7% with anxiety), with a mean age of 36.03 (SD 10.97) years (range, 19-67 years) for patients with depression and 36.80 (SD 13.55) years (range, 19-69 years) for patients with anxiety. The completion rates were 62% (37) and 40% (57) for depression and anxiety treatments, respectively. The primary analyses revealed large and significant reductions in the symptom levels of depression (beta=-6.27, SE 0.83, P<.001, d=1.0) and anxiety (beta=-3.78, SE 0.43, P<.001, d=1.1). High baseline severity of the primary disorder was associated with high treatment gains (r=-0.31 for depression; r=-0.41 for anxiety). In patients with anxiety, high baseline severity also predicted a high risk of noncompletion (odds ratio=1.08, CI=1.01-1.16, P=.03). An increase in the baseline severity of the comorbid disorder slightly increased the risk of noncompletion for both disorders (depression: odds ratio=1.03, CI=1.01-1.06, P=.02; anxiety: odds ratio=1.08, CI=1.01-1.16, P=.03).

CONCLUSIONS

iCBT can be clinically effective in routine care. Since depression and anxiety are costly and debilitating disorders that are vastly undertreated, this finding is important. Additionally, iCBT may help bridge the gap between the need for treatment and its provision. Our results are comparable to the within-group results of efficacy and effectiveness studies. Our noncompletion rates are similar to those observed in psychotherapy but are higher than those reported in similar clinics. Multiple factors predicted outcome and noncompletion. However, all predictor effects were statistically weak.

A review of web-based support systems for students in higher education

Background

Recent evidence suggests that there is an increasing need for accessible and anonymous services to support higher education (HE) students suffering from psychological and/or academic difficulties. Such difficulties can lead to several negative outcomes, including poor academic performance, sub-optimal mental health, reduced study satisfaction, and dropout from study. Currently, universities in the UK lack financial resources and the on-campus mental health services traditionally offered to students are increasingly economically unsustainable. Compounded by the perceived stigma of using such services, mental health providers have been driven to address the escalating needs of students through online services.

Methods

In this paper, we review online support systems identified through a literature search and a manual search of references in the identified papers. Further systems were identified through web searches, and systems still in development were identified by consultation with researchers in the field. We accessed systems online to extract relevant information, regarding the main difficulties addressed by the systems, the psychological techniques used and any relevant research evidence to support their effectiveness.

Conclusion

A large number of web-based support systems have been developed to support mental health and wellbeing, although few specifically target HE students. Further research is necessary to establish the effectiveness of such interventions in providing a cost-effective alternative to face-to-face therapy, particularly in certain settings such as HE institutions.

Blending Face-to-Face and Internet-Based Interventions for the Treatment of Mental Disorders in Adults: Systematic Review

Background

Many studies have provided evidence for the effectiveness of Internet-based stand-alone interventions for mental disorders. A newer form of intervention combines the strengths of face-to-face (f2f) and Internet approaches (blended interventions).

Objective

The aim of this review was to provide an overview of (1) the different formats of blended treatments for adults, (2) the stage of treatment in which these are applied, (3) their objective in combining face-to-face and Internet-based approaches, and (4) their effectiveness.

Methods

Studies on blended concepts were identified through systematic searches in the MEDLINE, PsycINFO, Cochrane, and PubMed databases. Keywords included terms indicating face-to-face interventions (“inpatient,” “outpatient,” “face-to-face,” or “residential treatment”), which were combined with terms indicating Internet treatment (“internet,” “online,” or “web”) and terms indicating mental disorders (“mental health,” “depression,” “anxiety,” or “substance abuse”). We focused on three of the most common mental disorders (depression, anxiety, and substance abuse).

Results

We identified 64 publications describing 44 studies, 27 of which were randomized controlled trials (RCTs). Results suggest that, compared with stand-alone face-to-face therapy, blended therapy may save clinician time, lead to lower dropout rates and greater abstinence rates of patients with substance abuse, or help maintain initially achieved changes within psychotherapy in the long-term effects of inpatient therapy. However, there is a lack of comparative outcome studies investigating the superiority of the outcomes of blended treatments in comparison with classic face-to-face or Internet-based treatments, as well as of studies identifying the optimal ratio of face-to-face and Internet sessions.

Conclusions

Several studies have shown that, for common mental health disorders, blended interventions are feasible and can be more effective compared with no treatment controls. However, more RCTs on effectiveness and cost-effectiveness of blended treatments, especially compared with nonblended treatments are necessary.

Internet-Based Cognitive-Behavioral Therapy for Depression: Current Progress and Future Directions

The World Health Organization estimates that during a given 12-month period, approximately 34 million people suffering from major depressive disorder go untreated in Europe and the Americas alone. Barriers to treatment include geographic distance, lack of mental health insurance, prohibitive cost of treatment, long wait-lists, and perceived stigma. Over the past two decades, Internet-based cognitive-behavioral therapy (iCBT) programs have proliferated. A growing body of research supports the efficacy of iCBT for depression and other psychiatric conditions, and these programs may help address barriers that hinder access to effective treatment. The present review describes common iCBT programs along with the evidence base supporting their efficacy in reducing symptoms of depression, reviews research on moderators of treatment response, and provides suggestions for future directions in research and care.

Motivation and Treatment Credibility Predicts Dropout, Treatment Adherence, and Clinical Outcomes in an Internet-Based Cognitive Behavioral Relaxation Program: A Randomized Controlled Trial

Background

In previous research, variables such as age, education, treatment credibility, and therapeutic alliance have shown to affect patients’ treatment adherence and outcome in Internet-based psychotherapy. A more detailed understanding of how such variables are associated with different measures of adherence and clinical outcomes may help in designing more effective online therapy.

Objective

The aims of this study were to investigate demographical, psychological, and treatment-specific variables that could predict dropout, treatment adherence, and treatment outcomes in a study of online relaxation for mild to moderate stress symptoms.

Methods

Participant dropout and attrition as well as data from self-report instruments completed before, during, and after the online relaxation program were analyzed. Multiple linear and logistical regression analyses were conducted to predict early dropout, overall attrition, online treatment progress, number of registered relaxation exercises, posttreatment symptom levels, and reliable improvement.

Results

Dropout was significantly predicted by treatment credibility, whereas overall attrition was associated with reporting a focus on immediate consequences and experiencing a low level of intrinsic motivation for the treatment. Treatment progress was predicted by education level and treatment credibility, whereas number of registered relaxation exercises was associated with experiencing intrinsic motivation for the treatment. Posttreatment stress symptoms were positively predicted by feeling external pressure to participate in the treatment and negatively predicted by treatment credibility. Reporting reliable symptom improvement after treatment was predicted by treatment credibility and therapeutic bond.

Conclusions

This study confirmed that treatment credibility and a good working alliance are factors associated with successful Internet-based psychotherapy. Further, the study showed that measuring adherence in different ways provides somewhat different results, which underscore the importance of carefully defining treatment adherence in psychotherapy research. Lastly, the results suggest that finding the treatment interesting and engaging may help patients carry through with the intervention and complete prescribed assignments, a result that may help guide the design of future interventions.

Trial Registration

Clinicaltrials.gov NCT02535598; http://clinicaltrials.gov/ct2/show/NCT02535598 (Archived by WebCite at http://www.webcitation.org/6fl38ms7y).

Internet-based treatment for Romanian adults with panic disorder: protocol of a randomized controlled trial comparing a Skype-guided with an unguided self-help intervention (the PAXPD study)

BACKGROUND

Efficacy of self-help internet-based cognitive behavior therapy (ICBT) for anxiety disorders has been confirmed in several randomized controlled trials. However, the amount and type of therapist guidance needed in ICBT are still under debate. Previous studies have shown divergent results regarding the role of therapist guidance and its impact on treatment outcome. This issue is central to the development of ICBT programs and needs to be addressed directly. The present study aims to compare the benefits of regular therapist guidance via online real-time audio-video communication (i.e. Skype) to no therapist guidance during a 12-week Romanian self-help ICBT program for Panic Disorder. Both treatments are compared to a waiting-list control group.

METHODS/DESIGN

A parallel group randomized controlled trial is proposed. The participants, 192 Romanian adults fulfilling diagnostic criteria for panic disorder according to a diagnostic interview, conducted via secured Skype or telephone, are randomly assigned to one of the three conditions: independent use of the internet-based self-help program PAXonline, the same self-help treatment with regular therapist support via secured Skype, and waiting-list control group. The primary outcomes are severity of self-report panic symptoms (PDSS-SR) and diagnostic status (assessors are blind to group assignment), at the end of the intervention (12 weeks) and at follow-up (months 3 and 6). The secondary measures address symptoms of comorbid anxiety disorders, depression, quality of life, adherence and satisfaction with ICBT. Additional measures of socio-demographic characteristics, personality traits, treatment expectancies, catastrophic cognitions, body vigilance and working alliance are considered as potential moderators and/ or mediators of treatment outcome.

DISCUSSION

To the best of our knowledge, the present study is the first effort to investigate the efficacy of a self-help internet-based intervention with therapist guidance via real-time video communication. A direct comparison between therapist guided versus unguided self-directed intervention for panic disorder will also be addressed for the first time. Findings from this study will inform researchers and practitioners about the added value of online video-therapy guidance sessions and the type of patients who may benefit the most from guided and unguided ICBT for Panic disorder.

TRIAL REGISTRATION

ACTRN12614000547640 (Australian New Zealand Clinical Trials Registry). Registered 22/05/2014.