Digital interventions in mental health: evidence syntheses and economic modelling

[Digital technologies to improve mental health]

The burden of mental diseases is enormous and constantly growing worldwide. The resulting increase in demand for psychosocial help is also having a negative impact on waiting times for psychotherapy in Germany. Digital interventions for mental health, such as interventions delivered through or with the help of a website (e.g. "telehealth"), smartphone, or tablet app-based interventions and interventions that use text messages or virtual reality, can help. This article begins with an overview of the functions and range of applications of digital technologies for mental health. The evidence for individual digital forms of interventions is addressed. Overall, it is shown that digital interventions for mental health are likely to be cost-effective compared to no therapy or a non-therapeutic control group. Newer approaches such as "digital phenotyping" are explained in the article. Finally, individual papers from the "Leibniz ScienceCampus Digital Public Health" are presented, and limitations and challenges of technologies for mental health are discussed.

Differences in psychological treatment outcomes by ethnicity and gender: an analysis of individual patient data

PURPOSE

There are discrepancies in mental health treatment outcomes between ethnic groups, which may differ between genders. NHS Talking Therapies for anxiety and depression provide evidence-based psychological therapies for common mental disorders. This study examines the intersection between ethnicity and gender as factors associated with psychological treatment outcomes. Aims were to explore by gender: (1) differences in psychological treatment outcomes for minoritized ethnic people compared to White-British people, (2) whether differences are observed when controlling for clinical and socio-demographic factors associated with outcomes, and (3) whether organization-level factors moderate differences in outcomes between ethnic groups.

METHODS

Patient data from eight NHS Talking Therapies for anxiety and depression services (n = 98,063) was used to explore associations between ethnicity and outcomes, using logistic regression. Stratified subsamples were used to separately explore factors associated with outcomes for males and females.

RESULTS

In adjusted analyses, Asian (OR = 0.82 [95% CI 0.78; 0.87], p < .001, 'Other' (OR = 0.79 [95%CI 0.72-0.87], p < .001) and White-other (0.93 [95%CI 0.89-0.97], p < .001) ethnic groups were less likely to reliably recover than White-British people. Asian (OR = 1.48 [95% CI 1.35-1.62], p < .001), Mixed (OR = 1.18 [95% CI 1.05-1.34], p = .008), 'Other' (OR = 1.60 [95% CI 1.38-1.84], p < .001) and White-other (OR = 1.18 [95% CI 1.09-1.28], p < .001) groups were more likely to experience a reliable deterioration in symptoms. Poorer outcomes for these groups were consistent across genders. There was some evidence of interactions between ethnic groups and organization-level factors impacting outcomes, but findings were limited.

CONCLUSIONS

Across genders, Asian, 'Other' and White-other groups experienced worse treatment outcomes across several measures in adjusted models. Reducing waiting times or offering more treatment sessions might lead to increased engagement and reduced drop-out for some patient groups.

Interdisciplinary perspectives on digital technologies for global mental health

Digital Mental Health Technologies (DMHTs) have the potential to close treatment gaps in settings where mental healthcare is scarce or even inaccessible. For this, DMHTs need to be affordable, evidence-based, justice-oriented, user-friendly, and embedded in a functioning digital infrastructure. This viewpoint discusses areas crucial for future developments of DMHTs. Drawing back on interdisciplinary scholarship, questions of health equity, consumer-, patient- and developer-oriented legislation, and requirements for successful implementation of technologies across the globe are discussed. Economic considerations and policy implications complement these aspects. We discuss the need for cultural adaptation specific to the context of use and point to several benefits as well as pitfalls of DMHTs for research and healthcare provision. Nonetheless, to circumvent technology-driven solutionism, the development and implementation of DMHTs require a holistic, multi-sectoral, and participatory approach.

Transforming global approaches to chronic disease prevention and management across the lifespan: integrating genomics, behavior change, and digital health solutions

Chronic illnesses are a major threat to global population health through the lifespan into older age. Despite world-wide public health goals, there has been a steady increase in chronic and non-communicable diseases (e.g., cancer, cardiovascular and metabolic disorders) and strong growth in mental health disorders. In 2010, 67% of deaths worldwide were due to chronic diseases and this increased to 74% in 2019, with accelerated growth in the COVID-19 era and its aftermath. Aging and wellbeing across the lifespan are positively impacted by the presence of effective prevention and management of chronic illness that can enhance population health. This paper provides a short overview of the journey to this current situation followed by discussion of how we may better address what the World Health Organization has termed the "tsunami of chronic diseases." In this paper we advocate for the development, validation, and subsequent deployment of integrated: 1. Polygenic and multifactorial risk prediction tools to screen for those at future risk of chronic disease and those with undiagnosed chronic disease. 2. Advanced preventive, behavior change and chronic disease management to maximize population health and wellbeing. 3. Digital health systems to support greater efficiencies in population-scale health prevention and intervention programs. It is argued that each of these actions individually has an emerging evidence base. However, there has been limited research to date concerning the combined population-level health effects of their integration. We outline the conceptual framework within which we are planning and currently conducting studies to investigate the effects of their integration.

A mHealth intervention to reduce perceived stress in patients with ischemic heart disease: study protocol of the randomized, controlled confirmatory intervention "mStress-IHD" trial

BACKGROUND

Stress is highly prevalent in patients with ischemic heart disease (IHD) and is associated with lower health-related quality of life and impaired cardiovascular outcome. The importance of stress management is now recognized in recent guidelines for the management of cardiovascular disease. However, effective stress management interventions are not implemented in clinical routine yet. The development of easily disseminated eHealth interventions, particularly mHealth, may offer a cost-effective and scalable solution to this problem. The aim of the proposed trial is to assess the efficiency and cost-effectiveness of the mHealth intervention "mindfulHeart" in terms of reducing stress in patients with IHD.

METHODS AND ANALYSIS

This randomized controlled confirmatory interventional trial with two parallel arms has assessments at six measurement time points: baseline (T0, prior randomization), post-treatment (T1), and four follow-ups at months 1, 3, 6, and 12 after intervention (T2, T3, T4, and T5). We will include patients with confirmed diagnosis of IHD, high-perceived stress, and use of an internet-enabled smartphone. Patients will be randomized into two groups (intervention vs. control). The proposed sample size calculation allocates 128 participants in total. The primary analysis will be performed in the intention-to-treat population, with missing data imputed. An ANCOVA with the outcome at T1, a between-subject factor (intervention vs. control), and the participants' pre-intervention baseline values as a covariate will be used. Different ANOVAs, regression, and descriptive approaches will be performed for secondary analyses.

ETHICS

The Ethics Committee of the Medical Faculty of the University of Duisburg-Essen approved the study (22-11,015-BO).

TRIAL REGISTRATION

ClinicalTrials NCT05846334. Release 26.04.2023.

Psychological Outcomes and Mechanisms of Mindfulness-Based Training for Generalised Anxiety Disorder: A Systematic Review and Meta-Analysis

This systematic review aimed to identify 1) the effect of mindfulness training on pre-post measures of anxiety and attention among adults experiencing high levels of generalised anxiety; and 2) the impact of predictors, mediators and moderators on post-intervention changes in anxiety or attention. Trait mindfulness and distress measures were included as secondary outcomes. A systematic search was conducted in November 2021 in electronic databases using relevant search terms. Eight articles comprising four independent studies were included (N = 334). All studies included participants diagnosed with generalised anxiety disorder (GAD) who participated in an 8-week manualised program. The meta-analysis indicated that mindfulness training had a large effect on anxiety symptoms (g = -1.92, 95%CI[-3.44, -0.40]) when compared to inactive (i.e., care as usual, waitlist) or non-specified (i.e., condition not defined) controls. However, a significant effect was not found when compared to active controls. Effects for depression, worry and trait mindfulness did not reach statistical significance, despite small-large effect sizes favouring mindfulness compared to inactive/non-specified controls. Our narrative review found evidence that changes in aspects of trait mindfulness mediate anxiety reduction following mindfulness training. However, a small number of studies were available for inclusion in the review, with high risk of bias and low certainty of evidence present. Overall, the findings support the use of mindfulness training programs for GAD and indicate mechanisms that may differ from those involved in other cognitive therapy approaches. Further RCTs with evidence-based controls are needed to clarify techniques most beneficial for generalised anxiety to support individually tailored treatment.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12144-023-04695-x.

Digital mental health: challenges and next steps

Digital innovations in mental health offer great potential, but present unique challenges. Using a consensus development panel approach, an expert, international, cross-disciplinary panel met to provide a framework to conceptualise digital mental health innovations, research into mechanisms and effectiveness and approaches for clinical implementation. Key questions and outputs from the group were agreed by consensus, and are presented and discussed in the text and supported by case examples in an accompanying appendix. A number of key themes emerged. (1) Digital approaches may work best across traditional diagnostic systems: we do not have effective ontologies of mental illness and transdiagnostic/symptom-based approaches may be more fruitful. (2) Approaches in clinical implementation of digital tools/interventions need to be creative and require organisational change: not only do clinicians and patients need training and education to be more confident and skilled in using digital technologies to support shared care decision-making, but traditional roles need to be extended, with clinicians working alongside digital navigators and non-clinicians who are delivering protocolised treatments. (3) Designing appropriate studies to measure the effectiveness of implementation is also key: including digital data raises unique ethical issues, and measurement of potential harms is only just beginning. (4) Accessibility and codesign are needed to ensure innovations are long lasting. (5) Standardised guidelines for reporting would ensure effective synthesis of the evidence to inform clinical implementation. COVID-19 and the transition to virtual consultations have shown us the potential for digital innovations to improve access and quality of care in mental health: now is the ideal time to act.