Improving Acceptability and Uptake Behavior for Internet-Based Cognitive-Behavioral Therapy

Association between expectations and clinical outcomes in online v. face-to-face therapy - an individual participant data meta-analysis

BACKGROUND

Online treatments are increasing in number and are currently available for a wide range of clinical problems. To date little is known about the role of treatment expectations and other placebo-like mechanisms in online settings compared to traditional face-to-face treatment. To address this knowledge gap, we analyzed individual participant data from randomized clinical trials that compared online and face-to-face psychological interventions.

METHODS

MEDLINE (Ovid) and PsycINFO (Ovid) were last searched on 2 February 2021. Randomized clinical trials of therapist guided online v. face-to-face psychological interventions for psychiatric or somatic conditions using a randomized controlled design were included. Titles, abstracts, and full texts of studies were independently screened by multiple observers. The Preferred Reporting Items for Systematic Reviews and Meta-analyses guideline was followed. Authors of the matching trials were contacted for individual participant data. Ratings from the Credibility and Expectancy Questionnaire and the primary outcome measure from each trial were used to estimate the association between expectation ratings and treatment outcomes in online v. face-to-face interventions, using a mixed-effects model.

RESULTS

Of 7045 screened studies, 62 full-text articles were retrieved whereof six studies fulfilled the criteria and provided individual participant data (n = 491). Overall, CEQ ratings predicted clinical outcomes (β = 0.27) at end of treatment with no moderating effect of treatment modality (online v. face-to-face).

CONCLUSIONS

Online treatment appears to be equally susceptible to expectancy effects as face-to-face therapy. This furthers our understanding of the importance of placebo-like factors in online treatment and may aid the improvement of healthcare in online settings.

Does outcome expectancy predict outcomes in online depression prevention? Secondary analysis of randomised-controlled trials

BACKGROUND

Evidence shows that online interventions could prevent depression. However, to improve the effectiveness of preventive online interventions in individuals with subthreshold depression, it is worthwhile to study factors influencing intervention outcomes. Outcome expectancy has been shown to predict treatment outcomes in psychotherapy for depression. However, little is known about whether this also applies to depression prevention. The aim of this study was to investigate the role of participants' outcome expectancy in an online depression prevention intervention.

METHODS

A secondary data analysis was conducted using data from two randomised-controlled trials (N = 304). Multilevel modelling was used to explore the effect of outcome expectancy on depressive symptoms and close-to-symptom-free status postintervention (6-7 weeks) and at follow-up (3-6 months). In a subsample (n = 102), Cox regression was applied to assess the effect on depression onset within 12 months. Explorative analyses included baseline characteristics as possible moderators. Outcome expectancy did not predict posttreatment outcomes or the onset of depression.

RESULTS

Small effects were observed at follow-up for depressive symptoms (β = -.39, 95% confidence interval [CI]: [-0.75, -0.03], p = .032, padjusted = .130) and close-to-symptom-free status (relative risk = 1.06, 95% CI: [1.01, 1.11], p = .013, padjusted = 0.064), but statistical significance was not maintained when controlling for multiple testing. Moderator analyses indicated that expectancy could be more influential for females and individuals with higher initial symptom severity.

CONCLUSION

More thoroughly designed, predictive studies targeting outcome expectancy are necessary to assess the full impact of the construct for effective depression prevention.

PATIENT OR PUBLIC CONTRIBUTION

This secondary analysis did not involve patients, service users, care-givers, people with lived experience or members of the public. However, the findings incorporate the expectations of participants using the preventive online intervention, and these exploratory findings may inform the future involvement of participants in the design of indicated depression prevention interventions for adults.

CLINICAL TRIAL REGISTRATION

Original studies: DRKS00004709, DRKS00005973; secondary analysis: osf.io/9xj6a.

Implementing Digital Cognitive-Behavioral Therapy for Major Depressive Disorder in Routine Psychiatric Appointments: A Pilot Project in a Rural Population

Psychotherapy is well-established as an effective treatment for major depressive disorder (MDD). However, many individuals with MDD in rural areas of the United States do not have access to psychotherapy. Self-management (SM) strategies are now the standard of care for chronic medical conditions and may be a viable alternative for individuals without access to psychotherapy. The current article describes the implementation of a 13-week pilot project to integrate digital cognitive-behavioral therapy (dCBT) SM programs into routine psychiatric advanced practice nurse (APN) telehealth appointments in the rural United States. Eight participants completed the project. The project did not meet the benchmark of 20 participants to improve access to treatment; however, one half (n = 4) of participants reported clinically significant improvement in MDD symptoms over 6 weeks. For clients without access to psychotherapy, dCBT SM programs can be effective in improving individual client outcomes when implemented by APNs in routine telehealth appointments. [Journal of Psychosocial Nursing and Mental Health Services, 61(10), 44-51.].

An Online Mindfulness Intervention for International Students: A Randomized Controlled Feasibility Trial

Background

Student mobility across borders poses challenges to health systems at the university and country levels. International students suffer from stress more than their local peers, however, do not seek help or underutilize existing help offers. Some barriers to help-seeking among international students are insufficient information regarding the health offers, stigma, and language, which might be overcome via culturally adapted internet and mobile-based interventions (IMI).

Method

A randomized controlled feasibility trial with a parallel design assessed the feasibility and potential efficacy of an online mindfulness intervention adapted for international university students. Participants were randomized into either an adapted online mindfulness intervention (StudiCareM-E) (IG, n = 20) or a waitlist control group (WL, n = 20). Participants were assessed at baseline (t0) and eight-week post-randomization (t1). The feasibility of StudiCareM-E was evaluated regarding intervention adherence, client satisfaction, and potential negative effects. The potential efficacy of StudiCareM-E was measured by means of the level of mindfulness, perceived stress, depression, anxiety, presenteeism, and wellbeing. Efficacy outcomes were evaluated with regression models on the intention-to-treat (ITT) sample (n = 40), adjusting for the baseline values.

Results

Participants' formative feedback suggested improvements in the content of the IMI. There were no crucial negative effects compared to WL. Assessment dropout was 35% (IG: 50%: WL: 20%), and intervention dropout was 60%. StudiCareM-E yielded significant improvements in mindfulness (β = .34), well-being (β = .37), and anxiety (β = -.42) compared to WL.

Conclusion

StudiCareM-E might be used among culturally diverse international student populations to improve their well-being. Future studies might carefully inspect the extent of the adaptation needs of their target group and design their interventions accordingly.

Engagement with mobile health interventions for depression: A systematic review

BACKGROUND

Depressive disorders are a major public health problem, and many people face barriers to accessing evidence-based mental health treatment. Mobile health (mHealth) interventions may circumvent logistical barriers to in-person care (e.g., cost, transportation), however the symptoms of depression (low motivation, concentration difficulties) may make it difficult for people with the disorder to engage with mHealth.

OBJECTIVE

The aim of this systematic review is to examine assessment and reporting of engagement in clinical trials of mHealth interventions for depression, including objective engagement (e.g., number of times program is used), subjective engagement (e.g., qualitative data on users' experiences), and associations between engagement and other clinically important variables (e.g., symptom improvement, participant characteristics).

METHODS

Three electronic databases (PsycINFO, Web of Science, PubMed) were searched in February 2020 using search terms for mHealth and depression. Studies were included in the review if they tested a mHealth intervention designed for people with depressive disorders or elevated depression symptoms.

RESULTS

Thirty studies met inclusion criteria and were reviewed. Most studies reported objective engagement (N = 23, 76.7%), approximately half reported subjective engagement (N = 16, 53.3%), and relatively few examined associations between engagement and clinical improvement, participant characteristics, or other clinically relevant variables (N = 13, 43.3%).

CONCLUSIONS

Although most studies in this small but rapidly growing literature report at least one measure of engagement, there is substantial heterogeneity. Intentional, theory-driven, and consistent measurement of engagement with mHealth interventions for depression may advance the field's understanding of effective engagement to facilitate clinical improvement, identify dose-response relationships, and maximize generalizability for underserved populations.

Increasing Acceptability and Outcome Expectancy for Internet-Based Cognitive Behavioral Therapy During the COVID-19 Pandemic

Background: e-Health interventions for mental health have the potential to reduce burdens on health care systems, but large survey studies find low acceptability for these interventions. The COVID-19 pandemic may make attitudes toward e-health more malleable. The current study examined whether an intervention to improve attitudes toward Internet-based cognitive behavioral therapy (iCBT) has a greater impact during the COVID-19 pandemic than before the pandemic. Materials and Methods: Individuals (N = 662) recruited from a large university and surrounding community who participated in a study about the acceptability of iCBT in 2018 and 2019 were asked to participate in a follow-up survey. In the original study, participants were randomized to receive or not receive a rationale designed to increase acceptability of iCBT, and then they completed measures of acceptability and outcome expectancy for iCBT. Fifty-one participants enrolled in the follow-up study from May to July 2020. They received a treatment rationale for iCBT (or not) in keeping with randomization from the parent study and re-completed measures assessing the acceptability and outcome expectancy for iCBT. Results: Contrary to hypotheses, two-way analyses of covariance (ANCOVA's) demonstrated that there was no significant interaction between time point and rationale condition on acceptability or outcome expectancy for iCBT. There was a significant main effect of rationale condition on acceptability, such that participants who received a treatment rationale reported greater acceptability for iCBT. There were no significant main effects of time. Conclusions: A treatment rationale was effective in improving acceptability for iCBT in a general population sample, but not more so during the COVID-19 pandemic.