Economic Evaluations of Internet-Based Psychological Interventions for Anxiety Disorders and Depression: A Systematic Review

Economic evaluation of Be a Mom, a web-based intervention to prevent postpartum depression in high-risk women alongside a randomized controlled trial

BACKGROUND

Postpartum depression (PPD) poses significant challenges, affecting both mothers and children, with substantial societal and economic implications. Internet-based cognitive behavioral therapy interventions (iCBT) offer promise in addressing PPD, but their economic impact remains unexplored. This study aimed to evaluate the cost-utility of Be a Mom, a self-guided iCBT intervention, compared with a waiting-list control among postpartum women at high risk of PPD.

METHODS

This economic evaluation was conducted alongside a 14-month randomized controlled trial adopting a societal perspective. Participants were randomized to Be a Mom (n = 542) or a waitlisted control group (n = 511). Self-report data on healthcare utilization, productivity losses, and quality-adjusted life years (QALYs) were collected at baseline, post-intervention, and 4 and 12 months post-intervention. Incremental cost-effectiveness ratios (ICERs) were calculated, and cost-effectiveness acceptability curves were generated using nonparametric bootstrapping. Sensitivity analyses were conducted to assess result robustness.

RESULTS

Over 14 months, Be a Mom generated a QALY gain of 0.0184 (0.0022, 0.0346), and cost savings of EUR 34.06 (-176.16, 108.04) compared to the control group. At a willingness to pay of EUR 20,000, Be a Mom had a 97.6 % probability of cost-effectiveness.

LIMITATIONS

Results have limitations due to self-selected sample, potential recall bias in self-reporting, missing data, limited follow-up, and the use of a waiting-list control group.

CONCLUSIONS

This study addresses a critical gap by providing evidence on the cost-utility of an iCBT intervention tailored for PPD prevention. Further research is essential to identify scalable and cost-effective interventions for reducing the burden of PPD.

Health-Economic Evaluation of Psychological Interventions for Anxiety Prevention: A Systematic Review

OBJECTIVE

Although evidence supports the effectiveness of psychological interventions for prevention of anxiety, little is known about their cost-effectiveness. The aim of this study was to conduct a systematic review of health-economic evaluations of psychological interventions for anxiety prevention.

METHODS

PubMed, PsycInfo, Web of Science, Embase, Cochrane Central Register of Controlled Trials, EconLit, National Health Service (NHS) Economic Evaluations Database, NHS Health Technology Assessment, and OpenGrey databases were searched electronically on December 23, 2022. Included studies focused on economic evaluations based on randomized controlled trials of psychological interventions to prevent anxiety. Study data were extracted, and the quality of the selected studies was assessed by using the Consensus on Health Economic Criteria and the Cochrane risk-of-bias tool.

RESULTS

All included studies (N=5) had economic evaluations that were considered to be of good quality. In two studies, the interventions showed favorable cost-effectiveness compared with usual care groups. In one study, the intervention was not cost-effective. Findings from another study cast doubt on the cost-effectiveness of the intervention, and the cost-effectiveness of the intervention in the remaining study could not be established.

CONCLUSIONS

Although the findings suggest some preliminary evidence of cost-effectiveness of psychological interventions for preventing anxiety, they were limited by the small number of included studies. Additional research on the cost-effectiveness of psychological interventions for anxiety in different countries and populations is required.

Developing a Program Costs Checklist of Digital Health Interventions: A Scoping Review and Empirical Case Study

INTRODUCTION

The rate of development and complexity of digital health interventions (DHIs) in recent years has to some extent outpaced the methodological development in economic evaluation and costing. Particularly, the choice of cost components included in intervention or program costs of DHIs have received scant attention. The aim of this study was to build a literature-informed checklist of program cost components of DHIs. The checklist was next tested by applying it to an empirical case, Mamma Mia, a DHI developed to prevent perinatal depression.

METHOD

A scoping review with a structured literature search identified peer-reviewed literature from 2010 to 2022 that offers guidance on program costs of DHIs. Relevant guidance was summarized and extracted elements were organized into categories of main cost components and their associated activities following the standard three-step approach, that is, activities, resource use and unit costs.

RESULTS

Of the 3448 records reviewed, 12 studies met the criteria for data extraction. The main cost categories identified were development, research, maintenance, implementation and health personnel involvement (HPI). Costs are largely considered to be context-specific, may decrease as the DHI matures and vary with number of users. The five categories and their associated activities constitute the checklist. This was applied to estimate program costs per user for Mamma Mia Self-Guided and Blended, the latter including additional guidance from public health nurses during standard maternal check-ups. Excluding research, the program cost per mother was more than double for Blended compared with Self-Guided (€140.5 versus €56.6, 2022 Euros) due to increased implementation and HPI costs. Including research increased the program costs to €190.8 and €106.9, respectively. One-way sensitivity analyses showed sensitivity to changes in number of users, lifespan of the app, salaries and license fee.

CONCLUSION

The checklist can help increase transparency of cost calculation and improve future comparison across studies.

Cost-Effectiveness of Digital Mental Health Versus Usual Care During Humanitarian Crises in Lebanon: Pragmatic Randomized Trial

BACKGROUND

There is evidence from meta-analyses and systematic reviews that digital mental health interventions for depression, anxiety, and stress-related disorders tend to be cost-effective. However, no such evidence exists for guided digital mental health care in low and middle-income countries (LMICs) facing humanitarian crises, where the needs are highest. Step-by-Step (SbS), a digital mental health intervention for depression, anxiety, and stress-related disorders, proved to be effective for Lebanese citizens and war-affected Syrians residing in Lebanon. Assessing the cost-effectiveness of SbS is crucial because Lebanon's overstretched health care system must prioritize cost-effective treatment options in the face of continuing humanitarian and economic crises.

OBJECTIVE

This study aims to assess the cost-effectiveness of SbS in a randomized comparison with enhanced usual care (EUC).

METHODS

The cost-effectiveness analysis was conducted alongside a pragmatic randomized controlled trial in 2 parallel groups comparing SbS (n=614) with EUC (n=635). The primary outcome was cost (in US $ for the reference year 2019) per treatment response of depressive symptoms, defined as >50% reduction of depressive symptoms measured using the Patient Health Questionnaire (PHQ). The secondary outcome was cost per remission of depressive symptoms, defined as a PHQ score <5 at last follow-up (5 months post baseline). The evaluation was conducted first from the health care perspective then from the societal perspective.

RESULTS

Taking the health care perspective, SbS had an 80% probability to be regarded as cost-effective compared with EUC when there is a willingness to pay US $220 per additional treatment response or US $840 per additional remission. Taking the wider societal perspective, SbS had a >75% probability to be cost-saving while gaining response or remission.

CONCLUSIONS

To our knowledge, this study is the first cost-effectiveness analysis based on a large randomized controlled trial (n=1249) of a guided digital mental health intervention in an LMIC. From the principal findings, 2 implications flowed, from the (1) health care perspective and (2) wider societal perspective. First, our findings suggest that SbS is associated with greater health benefits, albeit for higher costs than EUC. It is up to decision makers in health care to decide if they find the balance between additional health gains and additional health care costs acceptable. Second, as seen from the wider societal perspective, there is a substantial likelihood that SbS is not costing more than EUC but is associated with cost-savings as SBS participants become more productive, thus offsetting their health care costs. This finding may suggest to policy makers that it is in the interest of both population health and the wider Lebanese economy to implement SbS on a wide scale. In brief, SbS may offer a scalable, potentially cost-saving response to humanitarian emergencies in an LMIC.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03720769; https://clinicaltrials.gov/ct2/show/NCT03720769.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/21585.

A Brief Workplace Training Program to Support Help-Seeking for Mental Ill-Health: Protocol for the Helipad Cluster Randomized Controlled Trial

BACKGROUND

Most people with mental health problems do not seek help, with delays of even decades in seeking professional help. Lack of engagement with professional mental health services can lead to poor outcomes and functional impairment. However, few effective interventions have been identified to improve help-seeking in adults, and those that exist are not widely implemented to deliver public health impact. Co-designing interventions with people with lived experience of mental ill-health and other relevant stakeholders is critical to increase the likelihood of uptake and engagement with these programs.

OBJECTIVE

This study aims to (1) test the effectiveness of a co-designed help-seeking program on increasing professional help-seeking intentions in employees in a workplace setting; (2) determine whether the program reduces mental illness stigma and improves help-seeking intentions and behavior, mental health literacy, mental health symptoms, and work and activity functioning relative to the control condition; (3) explore factors that facilitate broader implementation of the co-designed program; and (4) explore the cost-effectiveness of the co-designed program compared to the control condition over 6 months.

METHODS

A 2-arm cluster randomized controlled trial will be conducted (target sample: N=900 from 30 to 36 workplaces, with n=25 to 35 participants per workplace). The trial will compare the relative effectiveness of an enhanced interactive program (intervention condition) with a standard psychoeducation-alone program (active control condition) on the primary outcome of professional help-seeking intentions as measured by the General Help-Seeking Questionnaire. Secondary outcomes include the impact on mental illness stigma; mental health literacy; help-seeking attitudes and behavior; work and activity functioning; quality of life; and symptoms of mental ill-health including depression, anxiety, and general psychological distress.

RESULTS

Facilitators of and risks to the trial are identified and addressed in this protocol. Recruitment of workplaces is scheduled to commence in the first quarter of 2024.

CONCLUSIONS

If effective, the program has the potential to be ready for rapid dissemination throughout Australia, with the potential to increase appropriate and efficient service use across the spectrum of evidence-based services.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12623000270617p; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=385376.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/55529.

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.

Momentary Depressive Feeling Detection Using X (Formerly Twitter) Data: Contextual Language Approach

BACKGROUND

Depression and momentary depressive feelings are major public health concerns imposing a substantial burden on both individuals and society. Early detection of momentary depressive feelings is highly beneficial in reducing this burden and improving the quality of life for affected individuals. To this end, the abundance of data exemplified by X (formerly Twitter) presents an invaluable resource for discerning insights into individuals' mental states and enabling timely detection of these transitory depressive feelings.

OBJECTIVE

The objective of this study was to automate the detection of momentary depressive feelings in posts using contextual language approaches.

METHODS

First, we identified terms expressing momentary depressive feelings and depression, scaled their relevance to depression, and constructed a lexicon. Then, we scraped posts using this lexicon and labeled them manually. Finally, we assessed the performance of the Bidirectional Encoder Representations From Transformers (BERT), A Lite BERT (ALBERT), Robustly Optimized BERT Approach (RoBERTa), Distilled BERT (DistilBERT), convolutional neural network (CNN), bidirectional long short-term memory (BiLSTM), and machine learning (ML) algorithms in detecting momentary depressive feelings in posts.

RESULTS

This study demonstrates a notable distinction in performance between binary classification, aimed at identifying posts conveying depressive sentiments and multilabel classification, designed to categorize such posts across multiple emotional nuances. Specifically, binary classification emerges as the more adept approach in this context, outperforming multilabel classification. This outcome stems from several critical factors that underscore the nuanced nature of depressive expressions within social media. Our results show that when using binary classification, BERT and DistilBERT (pretrained transfer learning algorithms) may outperform traditional ML algorithms. Particularly, DistilBERT achieved the best performance in terms of area under the curve (96.71%), accuracy (97.4%), sensitivity (97.57%), specificity (97.22%), precision (97.30%), and F1-score (97.44%). DistilBERT obtained an area under the curve nearly 12% points higher than that of the best-performing traditional ML algorithm, convolutional neural network. This study showed that transfer learning algorithms are highly effective in extracting knowledge from posts, detecting momentary depressive feelings, and highlighting their superiority in contextual analysis.

CONCLUSIONS

Our findings suggest that contextual language approaches-particularly those rooted in transfer learning-are reliable approaches to automate the early detection of momentary depressive feelings and can be used to develop social media monitoring tools for identifying individuals who may be at risk of depression. The implications are far-reaching because these approaches stand poised to inform the creation of social media monitoring tools and are pivotal for identifying individuals susceptible to depression. By intervening proactively, these tools possess the potential to slow the progression of depressive feelings, effectively mitigating the societal load of depression and fostering improved mental health. In addition to highlighting the capabilities of automated sentiment analysis, this study illuminates its pivotal role in advancing global public health.

Evaluating the effectiveness and cost-effectiveness of a digital, app-based intervention for depression (VMood) in community-based settings in Vietnam: Protocol for a stepped-wedge randomized controlled trial

The COVID-19 pandemic has amplified mental health problems and highlighted inequitable gaps in care worldwide. In response there has been an explosion of digital interventions such as smartphone applications ("apps") to extend care. The objective of this trial is to evaluate the effectiveness and cost-effectiveness of a digital depression intervention (VMood), delivered via a smartphone app. VMood is adapted from an in-person intervention that was delivered by non-specialist providers and shown to be effective in the Vietnamese context in our previous trial (2016-2019). A stepped-wedge, randomized controlled trial will be conducted across eight provinces in Vietnam. Adults aged 18 years and over will be recruited through community-based primary care centres and screened for depression using the embedded Patient Health Questionnaire-9 (primary outcome measure). Participants scoring 10-19, indicating depression caseness, will be randomly allocated to the intervention or control group until the target of 336 is reached. Secondary outcome measures will examine the effect of the intervention on commonly co-occuring anxiety, quality of life and work productivity, along with use of alcohol and tobacco products. Assessments will be administered through an online survey platform (REDCap) at baseline, and at every 3 months until 3 months post-intervention. Intervention-group participants will receive VMood for a 3-month period, with online support provided by social workers. Control-group participants will receive a limited version of the app until they cross into the intervention group. Generalized Linear Mixed-effect Models for clustered measures will be used for all outcomes data. We will conduct a cost-effectiveness analysis alongside the trial to capture VMood's costs and benefits. This trial will provide evidence on the effectiveness and cost-effectiveness of a digital mental health intervention adapted from an in-person intervention. This trial will also contribute important information to the growing and promising field of digital mental health. Trail regulation. Registered at ClinicalTrials.gov, identifier [NCT05783531].

Trajectories of depression symptoms in a therapist-supported digital mental health intervention: a repeated measures latent profile analysis

PURPOSE

Major depression affects 10% of the US adult population annually, contributing to significant burden and impairment. Research indicates treatment response is a non-linear process characterized by combinations of gradual changes and abrupt shifts in depression symptoms, although less is known about differential trajectories of depression symptoms in therapist-supported digital mental health interventions (DMHI).

METHODS

Repeated measures latent profile analysis was used to empirically identify differential trajectories based upon biweekly depression scores on the Patient Health Questionnaire-9 (PHQ-9) among patients engaging in a therapist-supported DMHI from January 2020 to July 2021. Multivariate associations between symptom trajectories with sociodemographics and clinical characteristics were examined with multinomial logistic regression. Minimal clinically important differences (MCID) were defined as a five-point change on the PHQ-9 from baseline to week 12.

RESULTS

The final sample included 2192 patients aged 18 to 82 (mean = 39.1). Four distinct trajectories emerged that differed by symptom severity and trajectory of depression symptoms over 12 weeks. All trajectories demonstrated reductions in symptoms. Despite meeting MCID criteria, evidence of treatment resistance was found among the trajectory with the highest symptom severity. Chronicity of major depressive episodes and lifetime trauma exposures were ubiquitous across the trajectories in a multinomial logistic regression model.

CONCLUSIONS

These data indicate that changes in depression symptoms during DMHI are heterogenous and non-linear, suggesting a need for precision care strategies to address treatment resistance and increase engagement. Future efforts should examine the effectiveness of trauma-informed treatment modules for DMHIs as well as protocols for continuation treatment and relapse prevention.

Development and pilot testing of internet-delivered, family-based cognitive behavioral therapy for anxiety and obsessive-compulsive disorders in autistic youth

Cognitive behavioral therapy adapted for autistic youth with anxiety and/or OCD has a strong evidence base, but few have access. A 12-week family-based, Internet-delivered cognitive behavioral therapy (iCBT) program for 7-15 year-old autistic youth with anxiety and/or OCD was developed as a potential method to address this problem. Quantitative and qualitative feedback from stakeholders (parents, youth, clinicians) was gathered on an initial draft of content before conducting a pilot trial. This feedback suggested high quality, engagement, usability, and informativeness of the material. Suggestions were incorporated into the treatment program that was tested in a pilot trial. Eight families were randomized to the iCBT program with either 1) weekly email support or 2) weekly email support plus biweekly telehealth check-ins, and seven of these families completed pre- and post-treatment assessments. An average reduction of 39% in anxiety severity was found, with six of the seven being classified as responders. Preliminary evidence suggests that family-based iCBT is an acceptable and promising treatment for autistic youth with anxiety and/or obsessive-compulsive disorders that should be further modified and tested in future work.

Self-Management of Subclinical Common Mental Health Disorders (Anxiety, Depression and Sleep Disorders) Using Wearable Devices

RATIONALE

Common mental health disorders (CMD) (anxiety, depression, and sleep disorders) are among the leading causes of disease burden globally. The economic burden associated with such disorders is estimated at $2.4 trillion as of 2010 and is expected to reach $16 trillion by 2030. The UK has observed a 21-fold increase in the economic burden associated with CMD over the past decade. The recent COVID-19 pandemic was a catalyst for adopting technologies for mental health support and services, thereby increasing the reception of personal health data and wearables. Wearables hold considerable promise to empower users concerning the management of subclinical common mental health disorders. However, there are significant challenges to adopting wearables as a tool for the self-management of the symptoms of common mental health disorders.

AIMS

This review aims to evaluate the potential utility of wearables for the self-management of sub-clinical anxiety and depressive mental health disorders. Furthermore, we seek to understand the potential of wearables to reduce the burden on the healthcare system.

METHODOLOGY

a systematic review of research papers was conducted, focusing on wearable devices for the self-management of CMD released between 2018-2022, focusing primarily on mental health management using technology.

RESULTS

We screened 445 papers and analysed the reports from 12 wearable devices concerning their device type, year, biometrics used, and machine learning algorithm deployed. Electrodermal activity (EDA/GSR/SC/Skin Temperature), physical activity, and heart rate (HR) are the most common biometrics with nine, six and six reference counts, respectively. Additionally, while smartwatches have greater penetration and integration within the marketplace, fitness trackers have the most significant public value benefit of £513.9 M, likely due to greater retention.

Using peer-support coaching to improve adherence to online ACT self-help for college mental health: A randomized controlled trial

Online self-help programs such as the Acceptance and Commitment Therapy (ACT) Guide address significant barriers to receiving therapy but suffer from low adherence rates. Peer-delivered coaching, using undergraduate students as coaches, is an innovative alternative to traditional coaching methods which may improve adherence in a more scalable format. To test the efficacy of peer-support coaching for college students using ACT Guide in a naturalistic setting, we conducted a pragmatic randomized controlled trial with three conditions (phone coaching, text message coaching, and a no support control group; N = 230). Participants were block randomized, and program adherence (i.e., number of modules completed) was the primary outcome. Participants completed significantly more ACT Guide modules in phone (M = 7.1, SD = 4.9) and text (M = 5.7, SD = 5) coaching than the no support control condition (M = 1.6, SD = 3.3, p < .001). Participants who received phone coaching experienced significant improvements across almost all measured outcomes as compared to the control group, while participants who received text coaching improved only on some outcomes compared to control (ps < .05). These results support peer-support coaching, particularly when delivered through phone calls, as an efficacious method for improving adherence to and outcomes from online self-help programs.

Systematic review of economic evaluations for internet- and mobile-based interventions for mental health problems

In view of the staggering disease and economic burden of mental disorders, internet and mobile-based interventions (IMIs) targeting mental disorders have often been touted to be cost-effective; however, available evidence is inconclusive and outdated. This review aimed to provide an overview of the cost-effectiveness of IMIs for mental disorders and symptoms. A systematic search was conducted for trial-based economic evaluations published before 10th May 2021. Electronic databases (including MEDLINE, PsycINFO, CENTRAL, PSYNDEX, and NHS Economic Evaluations Database) were searched for randomized controlled trials examining IMIs targeting mental disorders and symptoms and conducting a full health economic evaluation. Methodological quality and risk of bias were assessed. Cost-effectiveness was assumed at or below £30,000 per quality-adjusted life year gained. Of the 4044 studies, 36 economic evaluations were reviewed. Guided IMIs were likely to be cost-effective in depression and anxiety. The quality of most evaluations was good, albeit with some risks of bias. Heterogeneity across studies was high because of factors such as different costing methods, design, comparison groups, and outcomes used. IMIs for anxiety and depression have potential to be cost-effective. However, more research is needed into unguided (preventive) IMIs with active control conditions (e.g., treatment as usual) and longer time horizon across a wider range of disorders.Trial registration: PROSPERO Registration No. CRD42018093808.

Economic evaluation of psychological treatments for common mental disorders in low- and middle-income countries: a systematic review

Common mental disorders (CMDs) constitute a major public health and economic burden on low- and middle-income countries (LMICs). Systematic reviews of economic evaluations of psychological treatments for CMDs are limited. This systematic review examines methods, reports findings and appraises the quality of economic evaluations of psychological treatments for CMDs in LMICs. We searched a range of bibliographic databases (including PubMed, EconLit, APA-PsycINFO and Cochrane library) and the African Journals Online (AJoL) and Google Scholar platforms. We used a pre-populated template to extract data and the Drummond & Jefferson checklist for quality appraisal. We present results as a narrative synthesis. The review included 26 studies, mostly from Asia (12) and Africa (9). The majority were cost-effectiveness analyses (12), some were cost-utility analyses (5), with one cost-benefit analysis or combinations of economic evaluations (8). Most interventions were considered either cost-effective or potentially cost-effective (22), with 3 interventions being not cost-effective. Limitations were noted regarding appropriateness of conclusions drawn on cost-effectiveness, the use of cost-effectiveness thresholds and application of 'societal' incremental cost-effectiveness ratios to reflect value for money (VfM) of treatments. Non-specialist health workers (NSHWs) delivered most of the treatments (16) for low-cost delivery at scale, and costs should reflect the true opportunity cost of NSHWs' time to support the development of a sustainable cadre of health care providers. There is a 4-fold increase in economic evaluations of CMD psychological treatments in the last decade over the previous one. Yet, findings from this review highlight the need for better application of economic evaluation methodology to support resource allocation towards the World Health Organization recommended first-line treatments of CMDs. We suggest impact inventories to capture societal economic gains and propose a VfM assessment framework to guide researchers in evaluating cost-effectiveness.

Cost-effectiveness of varying degrees and models of therapist-assisted transdiagnostic internet-delivered cognitive behaviour therapy: Evidence from a randomized controlled trial

In routine care, Internet-delivered Cognitive Behaviour Therapy (ICBT) is often delivered with therapist support via emails/phone calls, but the cost-effectiveness of varying amounts of therapist support or having therapists specialized in ICBT is not known. This study compared the cost-effectiveness of specialized therapists providing ICBT support once-weekly (1WS) versus providing support once-weekly supplemented with a one-business-day response to patient emails (1W/1BD-S). We further compared the cost-effectiveness of 1W support offered by therapists employed in a specialized clinic (1WS) versus community clinics where therapists primarily deliver face-to-face therapy (1WC). Patients were randomly allocated to groups: 1WS group (n = 216), 1W/1BD-S group (n = 233), and 1WC group (n = 226). At baseline, 12, 24 and 52-week follow-up, patients completed the Treatment Inventory of Costs in Patients with Psychiatric Disorders questionnaire (TiC-P) adapted for use in Canada to assess healthcare use and productivity losses. Additionally, to assess Quality Adjusted Life Years (QALYs) gained, patients completed the EQ-5D-5L at the same time periods. We quantified uncertainties by one-way and probabilistic sensitivity analysis and reported Incremental cost-effectiveness ratios (ICER), cost-effectiveness planes and acceptability curves. Cost-effectiveness over 52 weeks was CAD 3072/QALY for 1WC, CAD 3244/QALY for 1W/1BD-S, and CAD 3528/QALY for 1WS. Our model suggests that 1WS is the best strategy since the incremental cost per QALY is below the $50,000 threshold (ICER is CAD 42,328/QALY compared to the next most effective, 1WC). 1W/1BD-S is dominated by the other strategies. The cost-effectiveness acceptability curves suggest that the 1WS group has a higher probability for cost-effectiveness (38 %) than 1W/1BD-S (30 %) and 1WC (32 %) when the willingness to pay is $50,000 per QALY. These results have important implications for health policymakers deciding on delivery of ICBT for the treatment of anxiety and/depressive disorders.

Internet- and mobile-based intervention for depression in adults with chronic back pain: A health economic evaluation

BACKGROUND

Depression and comorbid chronic back pain (CBP) lead to high personal and economic burden. Internet- and mobile-based interventions (IMI) might be a cost-effective adjunct to established interventions.

METHODS

A health economic evaluation was embedded into an observer-blinded, multicenter RCT (societal and health care perspective). We randomly assigned participants (≥18 years) with CBP and diagnosed depression from 82 orthopedic clinics across Germany to intervention (IG + treatment as usual [TAU]) or TAU control group (CG). The IG received a guided IMI. Primary outcomes were depression response and quality-adjusted life years (QALYs) at 6-months follow-up. Multiple imputation was used to address missing data. Incremental cost-effectiveness/cost-utility ratios (ICER/ICUR) and the probability of being cost-effective at different willingness-to-pay thresholds were calculated. Statistical uncertainty was estimated using bootstrapping techniques (N = 10,000).

RESULTS

Between October 2015 and July 2017 210 participants were randomly assigned to IG (n = 105) and CG (n = 105). Depression response did not differ significantly between groups. QALYs were significantly higher in the IG compared to the CG. Taking the societal perspective and assuming a commonly used willingness-to-pay of €34,000/QALY, the intervention's likelihood of being cost-effective was 64%.

LIMITATIONS

The main limitation is that the study was powered to detect clinical but not health economic differences between groups.

CONCLUSION

The IMI is considered cost-effective (vs. CG) for individuals with depression and CBP (societal perspective). These results are promising when considering the high individual and economic burden of this patient group. Further research is needed to adequately inform political decision makers before implementation into routine care.

Anxiety/Depression Predominance in Liaison-Psychiatry Users of a South-East Mexico Tertiary Hospital

Patients at tertiary hospitals may find themselves in need of mental health support due to the distress associated with the illness that may or not lead to a psychiatric condition. Here is an overview of the clinical cases treated by the liaison psychiatry service of a public tertiary hospital from Southeast Mexico during its first years of operation (2008–2018), with the purpose of gathering information about the status and needs of this population. A sample of 304 clinical records of patients treated for the first time by the psychiatry service was reviewed, and the distribution by demographic characteristics, diagnosis of mental illness and medical area of reference was analyzed. Anxiety and depression symptoms were the most frequent. Most patients were women, lived in Merida and returned after the first appointment. The neurology service referred most patients, yet most attended directly. General tertiary hospitals should prioritize integrating ad hoc mental and physical health care. Adult women with a profile of anxiety and/or depression would be the first target group. Some areas of opportunity for further research and improvement of mental health services are: preventive services for anxiety and depression, follow-up of patients, attention to relatives of patients at intensive care units, implementation of telehealth alternatives, training on mental health screening and inter- and intra-institutional collaboration.

Synthesizing Stakeholders Perspectives on Online Psychological Interventions to Improve the Mental Health of the Italian Population during the COVID-19 Pandemic: An Online Survey Study

The COVID-19 pandemic is expected to significantly increase the prevalence of mental health problems, thus raising the need for psychological support interventions around the world. Online psychological interventions have already been shown to be an effective solution to promote psychological treatments. Nevertheless, planning and developing an online intervention, involving possible stakeholders, might facilitate the dissemination of, willingness to use, and success of the future intervention. This study aims to explore and compare the experiences that Italians living in Italy and abroad had with available support services during the COVID-19 pandemic, their needs, and attitudes, as well as possible barriers to online psychological interventions. A sample of 1024 Italians (F = 69.8%; mean age = 41.3; SD = 15.3) was recruited through social media platforms and personal contacts and they were asked to complete an online survey. Results showed that perceived psychological distress during the COVID-19 pandemic improved. In Europe, psychological support was delivered mainly in person (69.0%), while online interventions were primarily used in extra-European countries (57%). Then, only 44% of the total sample was interested in trying an online psychological intervention. Various advantages and disadvantages were defined by stakeholders: The main advantages were the reduction in geographical distances, economic reasons, and the reduction in the waiting list; The main disadvantages were problems with technology, low motivation of users, and privacy/safety reasons. These data made it possible to improve the knowledge regarding the views and attitudes that Italians have about online psychological interventions, and shed light on how to increase the uptake of digital health.

Development of a Framework for the Implementation of Synchronous Digital Mental Health: Realist Synthesis of Systematic Reviews

BACKGROUND

The use of technologies has served to reduce gaps in access to treatment, and digital health interventions show promise in the care of mental health problems. However, to understand what and how these interventions work, it is imperative to document the aspects related to their challenging implementation.

OBJECTIVE

The aim of this study was to determine what evidence is available for synchronous digital mental health implementation and to develop a framework, informed by a realist review, to explain what makes digital mental health interventions work for people with mental health problems.

METHODS

The SPIDER (Sample, Phenomenon of Interest, Design, Evaluation, and Research type) framework was used to develop the following review question: What makes digital mental health interventions with a synchronous component work on people with mental health problems, including depression, anxiety, or stress, based on implementation, economic, quantitative, qualitative, and mixed methods studies? The MEDLINE, EBM Reviews, PsycINFO, EMBASE, SCOPUS, CINAHL Complete, and Web of Science databases were searched from January 1, 2015, to September 2020 with no language restriction. A Measurement Tool to Assess Systematic Reviews-2 (AMSTAR-2) was used to assess the risk of bias and Confidence in Evidence from Reviews of Qualitative Research (CERQual) was used to assess the confidence in cumulative evidence. Realist synthesis analysis allowed for developing a framework on the implementation of synchronous digital mental health using a grounded-theory approach with an emergent approach.

RESULTS

A total of 21 systematic reviews were included in the study. Among these, 90% (n=19) presented a critically low confidence level as assessed with AMSTAR-2. The realist synthesis allowed for the development of three hypotheses to identify the context and mechanisms in which these interventions achieve these outcomes: (1) these interventions reach populations otherwise unable to have access because they do not require the physical presence of the therapist nor the patient, thereby tackling geographic barriers posed by in-person therapy; (2) these interventions reach populations otherwise unable to have access because they can be successfully delivered by nonspecialists, which makes them more cost-effective to implement in health services; and (3) these interventions are acceptable and show good results in satisfaction because they require less need of disclosure and provide more privacy, comfortability, and participation, enabling the establishment of rapport with the therapist.

CONCLUSIONS

We developed a framework with three hypotheses that explain what makes digital mental health interventions with a synchronous component work on people with mental health problems. Each hypothesis represents essential outcomes in the implementation process.

TRIAL REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews CRD42020203811; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020203811.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.12688/f1000research.27150.2.

Changes in healthcare costs following engagement with a virtual mental health system: a matched cohort study of healthcare claims data

The COVID-19 pandemic has exacerbated the pressing need for mental health services. Digital mental health interventions could increase access to care and be an effective approach to reducing anxiety and depression at scale; however, research on their impact on healthcare expenditure is in the nascent stage and requires further investigation. The current study used claims data to examine the associations between use of an on-demand digital mental health platform and healthcare utilization costs compared to a matched control cohort. The study found that there were no significant differences between cohorts in total healthcare costs and pharmacy costs. There was a 16.8% reduction in outpatient costs (p=.08). On-demand digital mental health interventions can serve as a scalable approach to addressing the current mental health demands and potentially lower outpatient costs.

Development and delivery cost of digital health technologies for mental health: Application to the Narrative Experiences Online Intervention

BACKGROUND

The increasing development and use of digital health interventions requires good quality costing information to inform development and commissioning choices about resource allocation decisions. The Narrative Experiences Online (NEON) Intervention is a web-application that delivers recorded mental health recovery narratives to its users. Two randomized controlled trials are testing the NEON Intervention in people with experience of psychosis (NEON) and people experiencing non-psychosis mental health problems (NEON-O).

AIM

This study describes and estimates the cost components and total cost of developing and delivering the NEON Intervention.

MATERIALS AND METHODS

Total costs for the NEON Trial (739 participants) and NEON-O Trial (1,024 participants) were estimated by: identifying resource use categories involved in intervention development and delivery; accurate measurement or estimation of resource use; and a valuation of resource use to generate overall costs, using relevant unit costs. Resource use categories were identified through consultation with literature, costing reporting standards and iterative consultation with health researchers involved in NEON Intervention development and delivery. Sensitivity analysis was used to test assumptions made.

RESULTS

The total cost of developing the NEON Intervention was £182,851. The largest cost components were software development (27%); Lived Experience Advisory Panel workshops (23%); coding the narratives (9%); and researchers' time to source narratives (9%). The total cost of NEON Intervention delivery during the NEON Trial was £118,663 (£349 per NEON Intervention user). In the NEON-O Trial, the total delivery cost of the NEON Intervention was £123,444 (£241 per NEON Intervention user). The largest cost components include updating the narrative collection (50%); advertising (19%); administration (14%); and software maintenance (11%). Uncertainty in the cost of administration had the largest effect on delivery cost estimates.

CONCLUSION

Our work shows that developing and delivering a digital health intervention requires expertise and time commitment from a range of personnel. Teams developing digital narrative interventions need to allocate substantial resources to curating narrative collections.

IMPLICATIONS FOR PRACTICE

This study identifies the development and delivery resource use categories of a digital health intervention to promote the consistent reporting of costs and informs future decision-making about the costs of delivering the NEON Intervention at scale.

TRIAL REGISTRATION

NEON Trial: ISRCTN11152837, registered 13 August 2018, http://www.isrctn.com/ISRCTN11152837. NEON-O Trial: ISRCTN63197153, registered 9 January 2020, http://www.isrctn.com/ISRCTN63197153.

Assessing costs of developing a digital program for training community health workers to deliver treatment for depression: A case study in rural India

Digital technology has emerged as a promising approach for training and building capacity of community health workers in low-income and middle-income countries (LMICs). Little is known about the cost of developing digital training programs in LMICs, which hinders the adoption, implementation, and scaling up of the programs in routine primary care settings. This study assessed the costs of developing a digital program for training community health workers to deliver a psychological treatment for depression in a rural district of Madhya Pradesh, India. We developed survey instruments to document required resources in development, including involved personnel (their roles, responsibilities, time spent, and salaries or payments), information technologies (e.g., smartphones, software programs), and infrastructure-related costs (e.g., vehicle, office space, utilities). Costs were estimated from an accounting perspective. Over a 10-month developmental period, the total costs were 208,814 USD, with the largest portion on human resources (61%, with 14% on management and supervision), followed by information technologies (33%), and infrastructure-related costs (6%). These findings could inform policymakers in LMICs on costs of developing online-training programs, which will be especially useful during the COVID-19 pandemic.

The growing field of digital psychiatry: current evidence and the future of apps, social media, chatbots, and virtual reality

As the COVID-19 pandemic has largely increased the utilization of telehealth, mobile mental health technologies - such as smartphone apps, vir-tual reality, chatbots, and social media - have also gained attention. These digital health technologies offer the potential of accessible and scalable interventions that can augment traditional care. In this paper, we provide a comprehensive update on the overall field of digital psychiatry, covering three areas. First, we outline the relevance of recent technological advances to mental health research and care, by detailing how smartphones, social media, artificial intelligence and virtual reality present new opportunities for "digital phenotyping" and remote intervention. Second, we review the current evidence for the use of these new technological approaches across different mental health contexts, covering their emerging efficacy in self-management of psychological well-being and early intervention, along with more nascent research supporting their use in clinical management of long-term psychiatric conditions - including major depression; anxiety, bipolar and psychotic disorders; and eating and substance use disorders - as well as in child and adolescent mental health care. Third, we discuss the most pressing challenges and opportunities towards real-world implementation, using the Integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) framework to explain how the innovations themselves, the recipients of these innovations, and the context surrounding innovations all must be considered to facilitate their adoption and use in mental health care systems. We conclude that the new technological capabilities of smartphones, artificial intelligence, social media and virtual reality are already changing mental health care in unforeseen and exciting ways, each accompanied by an early but promising evidence base. We point out that further efforts towards strengthening implementation are needed, and detail the key issues at the patient, provider and policy levels which must now be addressed for digital health technologies to truly improve mental health research and treatment in the future.

Meta-analytic review of online guided self-help interventions for depressive symptoms among college students

OBJECTIVE

This meta-analysis examines the effect of online guided self-help interventions for depressive symptoms among college students.

METHODS

We searched studies through PubMed, Embase, Web of Science, PsycINFO, and Cochrane Central. Effect estimates were reported as standardized mean differences (SMD) and data were pooled using random-effects models. Subgroup analyses were conducted to investigate the differential effects of these interventions by sample type, level of contact, use of incentive, length of intervention, and program content.

RESULTS

24 comparisons (n = 3074) deriving from 19 trials were included in the meta-analysis. Intervention participants (n = 1620) indicated significant reductions in depressive symptoms at post-intervention compared to non-active control conditions (n = 1454). The weighted effect size was 0.46 (95% CI: 0.28-0.64), which dropped to 0.36 (95% CI: 0.26-0.45) after an outlier was removed. Subgroup analyses showed that the effects were significant among interventions using both selective and universal samples; among interventions of shorter (≤4 weeks), moderate (4-8 weeks), and greater length (≥8 weeks); among interventions with high, moderate, and low levels of contact; among interventions with and without incentive; and among interventions employing cognitive-behavioral therapy (CBT) and third-wave CBT.

CONCLUSION

This meta-analysis reinforces evidence to support the effectiveness of online guided self-help interventions in reducing depressive symptoms among college students. However, because of the generally variable and limited quality of current evidence, further research applying rigorous methods is needed to confirm and extend the findings of this meta-analysis.

Economic evaluations of psychological treatments for common mental disorders in low- and middle-income countries: protocol for a systematic review

BACKGROUND

Common mental disorders (CMDs) are highly prevalent conditions that constitute a major public health and economic burden on society in low- and middle-income countries (LMICs). Despite the increased demand for economic evidence to support resource allocation for scaled-up implementation of mental health services in these contexts, economic evaluations of psychological treatments for CMDs remain scarce.

OBJECTIVE

The proposed systematic review aims to synthesize findings on methods and outcomes of economic evaluations of psychological treatments for CMDs in LMICs and appraise quality.

METHODS

We will identify, select, and extract data from published economic evaluations of psychological interventions for CMDs conducted in LMICs. We will search bibliographic databases (PubMed, EMBASE, CINAHL, Web of Science, EconLit, PsycINFO, Africa-Wide Information, Cochrane library, Centre for Reviews and Dissemination (CRD), Cost Effectiveness Analysis (CEA) Registry), and the African Journals Online (AJOL) and Google Scholar platforms. Only full economic evaluations (Cost-Effectiveness Analysis (CEA), Cost-Utility Analysis (CUA), Cost-Consequence Analysis (CCA), or Cost-Benefit Analysis (CBA)) of psychological treatments for CMDs (defined as depressive, anxiety, and substance use disorders) conducted in LMICs will be included. There will be no restrictions based on date of publication, perspective, follow-up duration or sample size. Data extraction will be guided by the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist.

RESULTS

The results presented will be examined using a narrative synthesis approach. The quality of included studies will be assessed using the Drummond & Jefferson checklist.

CONCLUSION

The fledgling evidence base in this area provides an opportunity to promote improved economic evaluation methods in line with repeated calls for economic evidence alongside effectiveness evidence in these settings. A rigorously developed economic evaluation evidence base will support resource allocation decisions for scaled up implementation of psychological interventions in LMIC settings.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42020185277.