Digital Mental Health Interventions for Depression

Exploring experiences with an internet-delivered ACT intervention among individuals with a personal history of depression: A thematic analysis

This qualitative study explored the experiences of individuals testing a novel internet-delivered acceptance and commitment therapy program (iACT) for patients with mild and moderate depressive disorder. Twelve participants, consisting of one male and 11 females with a history of depression but not currently depressed were recruited. Individual semi-structured interviews were conducted after 14 days of access to the iACT without therapist guidance. By using reflexive thematic analysis three key themes reflecting important aspects of the participants' experiences were created. 'Theme 1: I would have been too ill to benefit from the program' points to generally positive sentiments about the program among participants but raised concerns about treatment adherence during a depressive episode. 'Theme 2: It has the potential to fill gaps in healthcare services' highlighted the program's perceived role as a supplement to current health services rather than as a standalone intervention. 'Theme 3: It is not perfect for anyone' underscored the participants different views on how their personal needs would be met by this program and the lack of tailoring to individual preferences. These findings provide valuable insights for refining future internet-delivered intervention development targeting patients with depression or other mental health challenges.

Addressing global cognition and ineffective depressogenic discrimination strategies with clinical hypnosis

It is a fundamental truth in living that the quality of your decisions shapes the quality of your life. One's cognitive style determines whether one is more likely to be detailed and linear in thinking or more general and impressionistic, obvious influences on the way experiences are interpreted and reactions formed. Global thinking, also referred to as over-general thinking, has been linked to depression for several reasons. These include the lack of detail in making important discriminations that would reduce or eliminate the kind of self-injurious and depressogenic decisions described in the "stress generation" model of depression. The importance of having meaningful strategies for making effective decisions on a situation-by-situation basis cannot be overstated. Cognitive psychologists and cognitive neuroscientists use the term "discrimination" to describe the process of making distinctions between different situations that give rise to one's reactions. In this article, hypnosis is described as a vehicle for teaching global thinkers to be more skilled in making important discriminations. A sample hypnosis script is provided to illustrate the process.

Predictors of Dropout Among Psychosomatic Rehabilitation Patients During the COVID-19 Pandemic: Secondary Analysis of a Longitudinal Study of Digital Training

BACKGROUND

High dropout rates are a common problem reported in web-based studies. Understanding which risk factors interrelate with dropping out from the studies provides the option to prevent dropout by tailoring effective strategies.

OBJECTIVE

This study aims to contribute an understanding of the predictors of web-based study dropout among psychosomatic rehabilitation patients. We investigated whether sociodemographics, voluntary interventions, physical and mental health, digital use for health and rehabilitation, and COVID-19 pandemic-related variables determine study dropout.

METHODS

Patients (N=2155) recruited from 4 psychosomatic rehabilitation clinics in Germany filled in a web-based questionnaire at T1, which was before their rehabilitation stay. Approximately half of the patients (1082/2155, 50.21%) dropped out at T2, which was after the rehabilitation stay, before and during which 3 voluntary digital trainings were provided to them. According to the number of trainings that the patients participated in, they were categorized into a comparison group or 1 of 3 intervention groups. Chi-square tests were performed to examine the differences between dropout patients and retained patients in terms of sociodemographic variables and to compare the dropout rate differences between the comparison and intervention groups. Logistic regression analyses were used to assess what factors were related to study dropout.

RESULTS

The comparison group had the highest dropout rate of 68.4% (173/253) compared with the intervention groups' dropout rates of 47.98% (749/1561), 50% (96/192), and 42.9% (64/149). Patients with a diagnosis of combined anxiety and depressive disorder had the highest dropout rate of 64% (47/74). Younger patients (those aged <50 y) and patients who were less educated were more likely to drop out of the study. Patients who used health-related apps and the internet less were more likely to drop out of the study. Patients who remained in their jobs and patients who were infected by COVID-19 were more likely to drop out of the study.

CONCLUSIONS

This study investigated the predictors of dropout in web-based studies. Different factors such as patient sociodemographics, physical and mental health, digital use, COVID-19 pandemic correlates, and study design can correlate with the dropout rate. For web-based studies with a focus on mental health, it is suggested to consider these possible dropout predictors and take appropriate steps to help patients with a high risk of dropping out overcome difficulties in completing the study.

Enhancing the effectiveness of CBT for patients with unipolar depression by integrating digital interventions into treatment: A pilot randomized controlled trial

OBJECTIVE

Blended cognitive behavioral therapy (bCBT) combines face-to-face therapy with digital elements, such as digital health apps. This pilot study aimed to explore the effectiveness and safety of a novel bCBT application for treating unipolar depression in adults combined with cognitive behavioral therapy (CBT) compared to CBT alone in routine care.

METHODS

Patients (N = 82) were randomly assigned to bCBT (n = 42) or CBT (n = 40) over 12 weeks. bCBT consisted of weekly CBT sessions accompanied by the elona therapy depression module (a bCBT application for unipolar depression) for use between sessions. Standard CBT consisted of weekly CBT sessions. Outcomes (6,12 weeks) were analyzed with linear mixed models.

RESULTS

Improvements in depressive symptoms (BDI-II, PHQ-9) were descriptively larger for the bCBT group. Yet, this difference did not reach statistical significance. bCBT was superior to standard CBT in secondary outcome measures of psychological health (d = .50) and generalized anxiety symptoms (d = -.45). In other secondary outcomes (BAI, PSWQ, GSE, WHOQOL-BREF), improvements were descriptively larger for bCBT compared to CBT.

CONCLUSION

This pilot study provided preliminary evidence that bCBT might be advantageous in comparison to CBT alone in the treatment of depression, but larger RCTs of the bCBT application are needed.

A practical development protocol for evidence-based digital integrative arts therapy content in public mental health services: digital transformation of mandala art therapy

Introduction

The fundamentals of digital transformation include the conversion of the traditional method into a digital format to develop a standardized system that collects, analyzes, and processes quantitative data. This study aims to provide a comprehensive understanding of the development process and key elements of evidence-based digital integrative arts therapy.

Methods

The "Digital Mandala" service in the "Mental Health App" produced as part of a national public mental health project for personalized depression management is adopted to explain how to convert the existing mandala art therapy into digital format. A living lab approach has been applied, which can be used to address the nation's mental health challenges by promoting collaboration, innovation, and evidence-based solutions.

Results

Evidence-based digital content requires evidence that covers the structural process, the effects of existing methods, and the components and meanings of each detailed scene. In this section, we provide five stages of the development process, including preliminary research, design, development, commercialization, and advancement. Consequently, clinical elements, integrative arts therapy features, and data factors are defined as the key principles of evidence-based digital integrative arts therapy.

Discussion

Based on the data factors found in this study, it will be possible to create an evaluation dataset of digital integrative arts therapy content for managing depression. Additionally, the large-scale public data can be analyzed through artificial intelligence technology, which is expected to be used as a basis for deriving significant results in a new form, going further than the existing evaluation method. This research is significant because it establishes the foundation for digital transformation in the field of art therapy for public mental health services and investigates its potential.

Computational Study of Photodegradation Process and Conversion Products of the Antidepressant Citalopram in Water

Citalopram (CIT) is a commonly prescribed medication for depression. However, the photodegradation mechanism of CIT has not yet been fully analyzed. Therefore, the photodegradation process of CIT in water is studied by density functional theory and time-dependent density functional theory. The calculated results show that during the indirect photodegradation process, the indirect photodegradation of CIT with ·OH occurs via OH-addition and F-substitution. The minimum activation energy of C10 site was 0.4 kcal/mol. All OH-addition and F-substitution reactions are exothermic. The reaction of ¹O₂ with CIT includes the substitution of ¹O₂ for F and an addition reaction at the C14 site. The E_a value of this process is 1.7 kcal/mol, which is the lowest activation energy required for the reaction of ¹O₂ with CIT. C-C/C-N/C-F cleavage is involved in the direct photodegradation process. In the direct photodegradation of CIT, the activation energy of the C7-C16 cleavage reaction was the lowest, which was 12.5 kcal/mol. Analysis of the E_a values found that OH-addition and F-substitution, the substitution of ¹O₂ for F and addition at the C14 site, as well as the cleavage reactions of C6-F/C7-C16/C17-C18/C18-N/C19-N/C20-N are the main pathways of photodegradation of CIT.

A CBT-based mobile intervention as an adjunct treatment for adolescents with symptoms of depression: a virtual randomized controlled feasibility trial

Background

High rates of adolescent depression demand for more effective, accessible treatment options. A virtual randomized controlled trial was used to assess the feasibility and acceptability of a 5-week, self-guided, cognitive behavioral therapy (CBT)-based mobile application, Spark, compared to a psychoeducational mobile application (Active Control) as an adjunct treatment for adolescents with depression during the COVID-19 pandemic.

Methods

A community sample aged 13-21, with self-reported symptoms of depression, was recruited nationwide. Participants were randomly assigned to use either Spark or Active Control (N_Spark = 35; N_{Active Control} = 25). Questionnaires, including the PHQ-8 measuring depression symptoms, completed before, during, and immediately following completion of the intervention, evaluated depressive symptoms, usability, engagement, and participant safety. App engagement data were also analyzed.

Results

60 eligible adolescents (female = 47) were enrolled in 2 months. 35.6% of those expressing interest were consented and all enrolled. Study retention was high (85%). Spark users rated the app as usable (System Usability Scale_mean = 80.67) and engaging (User Engagement Scale-Short Form_mean = 3.62). Median daily use was 29%, and 23% completed all levels. There was a significant negative relationship between behavioral activations completed and change in PHQ-8. Efficacy analyses revealed a significant main effect of time, F = 40.60, p < .001, associated with decreased PHQ-8 scores over time. There was no significant Group × Time interaction (F = 0.13, p = .72) though the numeric decrease in PHQ-8 was greater for Spark (4.69 vs. 3.56). No serious adverse events or adverse device effects were reported for Spark users. Two serious adverse events reported in the Active Control group were addressed per our safety protocol.

Conclusion

Recruitment, enrollment, and retention rates demonstrated study feasibility by being comparable or better than other mental health apps. Spark was highly acceptable relative to published norms. The study's novel safety protocol efficiently detected and managed adverse events. The lack of significant difference in depression symptom reduction between Spark and Active Control may be explained by study design and study design factors. Procedures established during this feasibility study will be leveraged for subsequent powered clinical trials evaluating app efficacy and safety.

Clinical Trial Registration

https://clinicaltrials.gov/ct2/show/NCT04524598.

Personalization strategies in digital mental health interventions: a systematic review and conceptual framework for depressive symptoms

Introduction

Personalization is a much-discussed approach to improve adherence and outcomes for Digital Mental Health interventions (DMHIs). Yet, major questions remain open, such as (1) what personalization is, (2) how prevalent it is in practice, and (3) what benefits it truly has.

Methods

We address this gap by performing a systematic literature review identifying all empirical studies on DMHIs targeting depressive symptoms in adults from 2015 to September 2022. The search in Pubmed, SCOPUS and Psycinfo led to the inclusion of 138 articles, describing 94 distinct DMHIs provided to an overall sample of approximately 24,300 individuals.

Results

Our investigation results in the conceptualization of personalization as purposefully designed variation between individuals in an intervention's therapeutic elements or its structure. We propose to further differentiate personalization by what is personalized (i.e., intervention content, content order, level of guidance or communication) and the underlying mechanism [i.e., user choice, provider choice, decision rules, and machine-learning (ML) based approaches]. Applying this concept, we identified personalization in 66% of the interventions for depressive symptoms, with personalized intervention content (32% of interventions) and communication with the user (30%) being particularly popular. Personalization via decision rules (48%) and user choice (36%) were the most used mechanisms, while the utilization of ML was rare (3%). Two-thirds of personalized interventions only tailored one dimension of the intervention.

Discussion

We conclude that future interventions could provide even more personalized experiences and especially benefit from using ML models. Finally, empirical evidence for personalization was scarce and inconclusive, making further evidence for the benefits of personalization highly needed.

Systematic Review Registration

Identifier: CRD42022357408.

Validation of the Attitudes Towards Psychological Online Interventions Questionnaire Among Black Americans: Cross-cultural Confirmatory Factor Analysis

BACKGROUND

Acceptability of digital mental health interventions is a significant predictor of treatment-seeking behavior and engagement. However, acceptability has been conceptualized and operationalized in various ways, which decreases measurement precision and leads to heterogeneous conclusions about acceptability. Standardized self-report measures of acceptability have been developed, which have the potential to ameliorate these problems, but none have demonstrated evidence for validation among Black communities, which limits our understanding of attitudes toward these interventions among racially minoritized groups with well-documented barriers to mental health treatment.

OBJECTIVE

This study aims to examine the psychometric validity and reliability of one of the first and most widely used measures of acceptability, the Attitudes Towards Psychological Online Interventions Questionnaire, among a Black American sample.

METHODS

Participants (N=254) were recruited from a large southeastern university and the surrounding metropolitan area and completed the self-report measure via a web-based survey. A confirmatory factor analysis using mean and variance adjusted weighted least squares estimation was conducted to examine the validity of the underlying hierarchical 4-factor structure proposed by the original authors of the scale. An alternative, hierarchical 2-factor structure model and bifactor model were examined for comparative fit.

RESULTS

The findings indicated that the bifactor model demonstrated a superior fit (comparative fit index=0.96, Tucker-Lewis index=0.94, standardized root mean squared residual=0.03, and root mean square error of approximation=0.09) compared with both 2- and 4-factor hierarchical structure models.

CONCLUSIONS

The findings suggest that, within a Black American sample, there may be greater utility in interpreting the Attitudes Towards Psychological Online Interventions Questionnaire subscales as attitudinal constructs that are distinct from the global acceptability factor. The theoretical and practical implications for culturally responsive measurements were explored.

Digital mental health interventions for people with epilepsy: a systematic review

OBJECTIVE

Although mental health difficulties are common in people with epilepsy, their assessment and treatment are rarely incorporated into routine medical care, with detrimental effects on quality of life. Several barriers to access traditional face to face interventions have been identified, including travel restriction and shortage of appropriately trained mental health clinicians. Digital mental health interventions offer the potential to improve access to mental health treatment. The main aim of the present study is to systematically review the empirical literature to identify what digital mental health interventions for adults, children and young people with epilepsy are currently available, as well as exploring if these interventions are effective in improving mental health and wellbeing.

METHODS

Searches were conducted using the MEDLINE, PsycINFO, Web of Science and Embase. The reference lists of papers collected were examined in order to identify any further relevant articles cited in peer-reviewed journals. A total of 1490 papers were identified; of these 11 were included in this review. The protocol was registered in the PROSPERO database (CRD42022318658) and the PRISMA 2020 statement was followed.

RESULTS

Seven digital interventions were identified. All interventions were based predominantly on CBT and mindfulness techniques and showed promising results in reducing symptoms of depression, with some studies also reporting encouraging results in reducing anxiety and improving satisfaction with life and the quality of life of adults and children and young people with epilepsy.

CONCLUSIONS

In summary, digital mental health interventions for people with epilepsy seem to be effective and have the potential to improve access to psychological interventions and reach underserved clinical populations. However, further well-powered and methodological rigorous studies are needed to confirm the effect of such interventions for people with epilepsy.

Evaluation of the Use of Digital Mental Health Platforms and Interventions: Scoping Review

BACKGROUND

The increasing use of digital mental health (DMH) platforms and digital mental health interventions (DMHIs) is hindered by uncertainty over effectiveness, quality and usability. There is a need to identify the types of available evidence in this domain.

AIM

This study is a scoping review identifying evaluation of the (1) DMH platform/s used; and (2) DMHI/s applied on the DMH platform/s.

METHODS

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guided the review process. Empirical studies that focused on evaluation of the use and application of DMH platforms were included from journal articles (published 2012-2022). A literature search was conducted using four electronic databases (Scopus, ScienceDirect, Sage and ACM Digital Library) and two search engines (PubMed and Google Scholar).

RESULTS

A total of 6874 nonduplicate records were identified, of which 144 were analyzed and 22 met the inclusion criteria. The review included general/unspecified mental health and/or suicidality indications (n = 9, 40.9%), followed by depression (n = 5, 22.7%), psychosis (n = 3, 13.6%), anxiety and depression (n = 2, 9.1%), as well as anxiety, depression and suicidality (n = 1, 4.5%), loneliness (n = 1, 4.5%), and addiction (n = 1, 4.5%). There were 11 qualitative studies (50%), 8 quantitative studies (36.4%), and 3 mixed-methods studies (n = 3, 13.6%). The results contained 11 studies that evaluated the DMH platform/s and 11 studies that evaluated the DMHI/s. The studies focused on feasibility, usability, engagement, acceptability and effectiveness. There was a small amount of significant evidence (1 in each 11), notably the (cost-)effectiveness of a DMHI with significant long-term impact on anxiety and depression in adults.

CONCLUSION

The empirical research demonstrates the feasibility of DMH platforms and DMHIs. To date, there is mostly heterogeneous, preliminary evidence for their effectiveness, quality and usability. However, a scalable DMHI reported effectiveness in treating adults' anxiety and depression. The scope of effectiveness may be widened through targeted strategies, for example by engaging independent young people.

Digital mental health interventions for chronic serious mental illness: Findings from a qualitative study on usability and scale-up of the Life Goals app for bipolar disorder

The Life Goals (LG) application is an evidence-based self-management tool intended to help individuals with bipolar disorder (BD) by aligning symptom coping strategies with personal goals. The program has traditionally been offered in-person or via the web, but has recently been translated into an individualized, customizable mobile intervention to improve access to care and reduce provider burden. The LG app previously showed acceptability with ease of use and satisfaction with user interface, but less success in encouraging self-management. To better understand patient needs, our team conducted semi-structured interviews with 18 individuals with BD who used the LG app for 6 months. These interviews also investigated participant interest in sharing LG app data with their provider through an online dashboard. Using affinity mapping, a collaborative, qualitative data analysis technique, our team identified emerging common themes in the interviews. Through this process, team members identified 494 pieces of salient information from interviews that were mapped and translated into three main findings: (1) many participants found Mood Monitoring and LG modules helpful/interesting and stated the app overall had positive impacts on their mental health, (2) some components of the app were too rudimentary or impersonal to be beneficial, and (3) feedback was mixed regarding future implementation of an LG provider dashboard, with some participants seeing potential positive impacts and others hesitating due to perceived efficacy and privacy concerns. These findings can help researchers improve app-based interventions for individuals with BD by increasing app usage and improving care overall.

Study protocol: A randomized controlled trial of Raising Our Spirits Together, an entertaining, group-based technology-assisted cognitive behavioral therapy for depression, tailored for rural adults and delivery by clergy

This paper presents a methodological description of a randomized controlled trial (RCT) testing the effect of Raising Our Spirits Together (ROST), a technology-assisted cognitive behavioral therapy (T-CBT) for depression, tailored for the rural context and for delivery by clergy, compared to an enhanced control condition. Depression is among the most common mental health conditions; yet the majority of adults with depression do not receive needed treatment due to limited access to mental health professionals, treatment-associated costs, distance to care, and stigma. These barriers are particularly salient in rural areas of the United States. T-CBT with human support is an accessible and effective treatment for depression; however, currently available T-CBTs have poor completion rates due to the lack of tailoring and other features to support engagement. ROST is a T-CBT specifically tailored for the rural setting and delivery by clergy, who are preferred, informal providers. ROST also presents core CBT content in a simple, jargon-free manner that supports multiple learning preferences. ROST is delivered virtually in a small group format across 8 weekly sessions via videoconferencing software consistent with other clergy-based programs, such as Bible studies or self-help groups. In this study, adults with depressive symptoms recruited from two rural Michigan counties will be randomized to receive ROST versus an enhanced control condition (N = 84). Depressive symptoms post-treatment and at 3 months follow-up according to the Patient Health Questionnaire (PHQ-9) will be the primary outcome. Findings will determine whether ROST is effective for improving depression symptoms in underserved, under resourced rural communities.

Digital Mental Health Services: Moving From Promise to Results

The papers in this special issue make a compelling case for the value of digital mental health services (DMHS; including technology-based interventions, assessments, and prevention programs) to help address some of the currently unmet needs in mental health care. At the same time, the papers highlight the work that needs to be accomplished for DMHS to fulfill their promise. We review the papers' contributions in terms of (a) the imperative to increase access to evidence-informed, high-quality care, especially for underserved populations, both in the United States and globally; (b) ways to use DMHS to improve the ways that clinical care is provided to make treatment provision more effective and efficient; and (c) the current state of the research on DMHS for emotional disorders. We then consider lessons learned and recommendations to move the field forward, such as increasing (and making transparent) the research base on DMHS, adopting regulatory standards for DMHS, attending carefully to training issues for DMHS and best practices for dissemination and implementation, designing specifically for digital platforms, and being intentional about efforts to reduce disparities regarding who benefits from DMHS.

Technology-Assisted Psychosocial Interventions for Childhood, Adolescent, and Young Adult Cancer Survivors: A Systematic Review and Meta-Analysis

Purpose: Technology-assisted interventions are essential in supporting cancer survivors' psychosocial outcomes, especially for childhood, adolescent, and young adult (AYA) cancer survivors, a tech-savvy generation. This study aims to systematically evaluate review and meta-analyze technology-assisted interventions for childhood and AYA cancer survivors. Methods: Following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines, the study team used a pre-set of key words and searched studies across 11 electronic databases and 4 professional websites, and conducted a manual search of reference lists from published reviews. Meta-analysis of small sample size corrected Hedges' g was conducted using meta-regression with robust variance estimation. Results: Final analysis included a total of 28 clinical trials, including 237 effect sizes reported an overall statistically significant treatment effect of technology-assisted psychosocial interventions for childhood and AYA cancer survivors, g = 0.382, 95% confidence interval (CI) 0.243 to 0.521, p < 0.0001. Subgroup analysis revealed that distraction-based interventions and interventions for psychosocial and emotional health were overall statistically significant, whereas interventions for childhood and AYA cancer survivors' cancer knowledge outcomes and physical and functional health outcomes were statistically nonsignificant. Moderator analysis found intervention target was a significant moderator. Conclusions: Technology-assisted interventions for childhood and AYA cancer survivors were overall effective across domains of survivorship outcomes. Favorable evidence was found primarily for childhood cancer survivors with limited support for AYA cancer survivors. Implications for Cancer Survivors: Although existing technology-assisted interventions are overall promising, research support for cancer survivors from different age groups and with different psychosocial challenges varies and should be considered individually.

Technology-Assisted, Group-Based CBT for Rural Adults' Depression: Open Pilot Trial Results

Purpose

This pilot study assesses the association of Raising Our Spirits Together (ROST), a technology-assisted, group-based cognitive behavioral therapy for depression, with rural adults' depressive symptoms and anxiety.

Method

Nine adults from rural Michigan participated in an open pilot of ROST. Clergy facilitated pilot groups. The pilot began in February 2020 in-person. Due to COVID-19, the pilot was completed virtually.

Results

Mean depressive symptom scores, based on the PHQ-9, significantly decreased from pre-treatment (M = 14.4) to post-treatment (M = 6.33; t (8) = 6.79; P < .001). Symptom reduction was maintained at 3-month follow-up (M = 8.00), with a significant pattern of difference in depressive symptoms over time (F(2) = 17.7; P < .001; eta-squared = .689). Similar patterns occurred for anxiety based on the GAD-7. Participants attended an average of 7.33 of 8 sessions. Fidelity ratings were excellent.

Discussion

ROST is a potentially feasible intervention for rural adults' depressive symptoms. ROST offers a promising model for increasing treatment access and building capacity in rural areas.

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.