Investigating the efficacy of digital cognitive behavioural therapy in comparison to a sleep-monitoring application via integrated diary and actigraphy: A randomised-controlled trial.

Dissemination of digital cognitive behavioural therapy is a promising approach for treating insomnia in the broad population. Current evidence supports the effectiveness of the digital format, but clinical findings are often limited by the choice of control group and lack of in-depth therapeutic measures. This study was designed to investigate the specific effects of digital cognitive behavioural therapy in comparison to a self-monitoring application. Participants meeting criteria for insomnia were randomly allocated (1:1) to 8 weeks of digital cognitive behavioural therapy or 8 weeks of digital sleep monitoring (control application). The primary outcome, insomnia severity, was assessed at baseline, 8- and 16-weeks post-randomisation. Secondary outcomes included the assessment of sleep via application-integrated sleep diaries and actigraphy. Linear-mixed models were fitted to assess between-group differences. Fifty-six participants (48 females, mean age: M = 45.55 ± 13.70 years) were randomised to either digital cognitive behavioural therapy (n = 29) or digital sleep monitoring (n = 27). At 8- and 16-weeks post-randomisation, large treatment effects (d = 0.87-1.08) indicated robust reductions (-3.70 and -2.97, respectively; p ≤ 0.003) in insomnia severity in the digital cognitive behavioural therapy arm, relative to digital sleep monitoring. Treatment effects in favour of digital cognitive behavioural therapy were also found for self-reported and actigraphy-derived sleep continuity variables, indicating that sleep improved throughout the 8-week intervention period. Our study reinforces the role of digital cognitive behavioural therapy in achieving clinical improvements for patients with insomnia, affirming previous findings and supporting the specific effects of cognitive behavioural therapy.

Emotion Regulation Self-Efficacy as a Mechanism of Alliance and Outcomes in a Brief, Transdiagnostic Digital Mental Health Intervention: L'auto-efficacité de la régulation des émotions en tant que mécanisme d'alliance et de résultats dans une brève intervention transdiagnostique numérique en santé mentale.

OBJECTIVES: Digital mental health interventions have shown promise for alleviating various forms of psychopathology, including depression and anxiety. However, the mechanisms of such interventions remain largely unexplored. The purpose of this study was to investigate a potential mechanistic process through which one hybrid digital mental health intervention (i.e., the Digital Clinic) might operate. We hypothesized that emotion regulation (ER) self-efficacy at the treatment midpoint may mediate the relationship between alliance (i.e., therapeutic alliance and digital alliance) and outcome (i.e., co-morbid symptoms of depression and anxiety) at the treatment endpoint. METHODS: Data used in this study came from the Digital Clinic, a brief transdiagnostic telehealth treatment program augmented by a dual-purpose digital phenotyping and intervention smartphone app. Recruited primarily from primary care, participants were 82 adults (73% White, 64% cisgender women, mean age 41) receiving outpatient treatment in the northeastern United States. All constructs were measured with validated scales, including The Working Alliance Inventory-Short Revised (WAI-SR) for therapeutic alliance, the Digital Working Alliance Inventory (DWAI) for digital alliance, the PROMIS Self-Efficacy for Managing Emotions Short Form scale for ER self-efficacy, and the Patient Health Questionnaire Anxiety-Depression Scale (PHQ-ADS) for co-morbid symptoms of depression and anxiety. RESULTS: Significant reductions in co-morbid symptoms of depression and anxiety and significant increases in ER self-efficacy were found from baseline to treatment endpoint. Therapeutic and digital alliance at the midpoint each predicted reductions in co-morbid symptoms of depression and anxiety at the endpoint through ER self-efficacy, controlling for baseline scores. CONCLUSIONS: Findings suggest that ER self-efficacy may be a proximal predictor of clinical improvement that may be enhanced by therapeutic and digital alliance. Future controlled research is essential to improve knowledge of the mechanisms of digital mental health interventions and to enhance their effectiveness.

Virtual Reality in Acute and Chronic Pain Medicine: An Updated Review.

PURPOSE OF REVIEW: This review critically analyzes the recent literature on virtual reality's (VR) use in acute and chronic pain management, offering insights into its efficacy, applications, and limitations. RECENT FINDINGS: Recent studies, including meta-analyses and randomized controlled trials, have demonstrated VR's effectiveness in reducing pain intensity in various acute pain scenarios, such as procedural/acute pain and in chronic pain conditions. The role of factors such as immersion and presence in enhancing VR's efficacy has been emphasized. Further benefits have been identified in the use of VR for assessment as well as symptom gathering through conversational avatars. However, studies are limited, and strong conclusions will require further investigation. VR is emerging as a promising non-pharmacological intervention in pain management for acute and chronic pain. However, its long-term efficacy, particularly in chronic pain management, remains an area requiring further research. Key findings highlight that VR programs vary in efficacy depending on the specificity of the origin of pain.

Rewiring care delivery through Digital Therapeutics (DTx): a machine learning-enhanced assessment and development (M-LEAD) framework.

BACKGROUND: Digital transformation has sparked profound change in the healthcare sector through the development of innovative digital technologies. Digital Therapeutics offer an innovative approach to disease management and treatment. Care delivery is increasingly patient-centered, data-driven, and based on real-time information. These technological innovations can lead to better patient outcomes and support for healthcare professionals, also considering resource scarcity. As these digital technologies continue to evolve, the healthcare field must be ready to integrate them into processes to take advantage of their benefits. This study aims to develop a framework for the development and assessment of Digital Therapeutics. METHODS: The study was conducted relying on a mixed methodology. 338 studies about Digital Therapeutics resulting from a systematic literature review were analyzed using descriptive statistics through RStudio. Machine learning algorithms were applied to analyze variables and find patterns in the data. The results of these analytical analyses were summarized in a framework qualitatively tested and validated through expert opinion elicitation. RESULTS: The research provides M-LEAD, a Machine Learning-Enhanced Assessment and Development framework that recommends best practices for developing and assessing Digital Therapeutics. The framework takes as input Digital Therapeutics characteristics, regulatory aspects, study purpose, and assessment domains. The framework produces as outputs recommendations to design the Digital Therapeutics study characteristics. CONCLUSIONS: The framework constitutes the first step toward standardized guidelines for the development and assessment of Digital Therapeutics. The results may support manufacturers and inform decision-makers of the relevant results of the Digital Therapeutics assessment.

The New Emerging Treatment Choice for Major Depressive Disorders: Digital Therapeutics.

The chapter provides an in-depth analysis of digital therapeutics (DTx) as a revolutionary approach to managing major depressive disorder (MDD). It discusses the evolution and definition of DTx, their application across various medical fields, regulatory considerations, and their benefits and limitations. This chapter extensively covers DTx for MDD, including smartphone applications, virtual reality interventions, cognitive-behavioral therapy (CBT) platforms, artificial intelligence (AI) and chatbot therapies, biofeedback, wearable technologies, and serious games. It evaluates the effectiveness of these digital interventions, comparing them with traditional treatments and examining patient perspectives, compliance, and engagement. The integration of DTx into clinical practice is also explored, along with the challenges and barriers to their adoption, such as technological limitations, data privacy concerns, ethical considerations, reimbursement issues, and the need for improved digital literacy. This chapter concludes by looking at the future direction of DTx in mental healthcare, emphasizing the need for personalized treatment plans, integration with emerging modalities, and the expansion of access to these innovative solutions globally.

Cognitive Behavioral Therapy and Mindfulness-Based Cognitive Therapy for Depressive Disorders: Enhancing Access and Tailoring Interventions in Diverse Settings.

Depressive disorders are an enormous societal burden given their high prevalence and impact on all facets of being human (e.g., relationships, emotions, motivation). There is a variety of evidence-based psychological treatments, with cognitive behavioral therapy (CBT) being the gold standard for major depression. Research has shown that mindfulness-based interventions (MBIs) such as mindfulness-based cognitive therapy (MBCT) are an effective relapse prevention and treatment for depression and that MBIs can be integrated in individual therapy. Furthermore, various delivery modes (e.g., digital-delivered therapy) and settings are offered to best meet different needs and improve accessibility: Evidence suggests that therapist-guided digital CBT, blended therapy, and, to some degree, digitalized MBIs may be an efficacious supplement to traditional face-to-face therapy. This chapter provides an overview of the principles and evidence base for CBT and MBCT as well as different delivery modes for depressive disorders in adults. Finally, chances and challenges of integration are discussed as implications for practice, as well as recommendations and ideas for future research.

Predicting Long-Term Engagement in mHealth Apps: Comparative Study of Engagement Indices.

BACKGROUND: Digital health care apps, including digital therapeutics, have the potential to increase accessibility and improve patient engagement by overcoming the limitations of traditional facility-based medical treatments. However, there are no established tools capable of quantitatively measuring long-term engagement at present. OBJECTIVE: This study aimed to evaluate an existing engagement index (EI) in a commercial health management app for long-term use and compare it with a newly developed EI. METHODS: Participants were recruited from cancer survivors enrolled in a randomized controlled trial that evaluated the impact of mobile health apps on recovery. Of these patients, 240 were included in the study and randomly assigned to the Noom app (Noom Inc). The newly developed EI was compared with the existing EI, and a long-term use analysis was conducted. Furthermore, the new EI was evaluated based on adapted measurements from the Web Matrix Visitor Index, focusing on click depth, recency, and loyalty indices. RESULTS: The newly developed EI model outperformed the existing EI model in terms of predicting EI of a 6- to 9-month period based on the EI of a 3- to 6-month period. The existing model had a mean squared error of 0.096, a root mean squared error of 0.310, and an R2 of 0.053. Meanwhile, the newly developed EI models showed improved performance, with the best one achieving a mean squared error of 0.025, root mean squared error of 0.157, and R2 of 0.610. The existing EI exhibited significant associations: the click depth index (hazard ratio [HR] 0.49, 95% CI 0.29-0.84; P<.001) and loyalty index (HR 0.17, 95% CI 0.09-0.31; P<.001) were significantly associated with improved survival, whereas the recency index exhibited no significant association (HR 1.30, 95% CI 1.70-2.42; P=.41). Among the new EI models, the EI with a menu combination of menus available in the app's free version yielded the most promising result. Furthermore, it exhibited significant associations with the loyalty index (HR 0.32, 95% CI 0.16-0.62; P<.001) and the recency index (HR 0.47, 95% CI 0.30-0.75; P<.001). CONCLUSIONS: The newly developed EI model outperformed the existing model in terms of the prediction of long-term user engagement and compliance in a mobile health app context. We emphasized the importance of log data and suggested avenues for future research to address the subjectivity of the EI and incorporate a broader range of indices for comprehensive evaluation.

Mental Wellness Self-Care in Singapore With mindline.sg: A Tutorial on the Development of a Digital Mental Health Platform for Behavior Change.

BACKGROUND: Singapore, like the rest of Asia, faces persistent challenges to mental health promotion, including stigma around unwellness and seeking treatment and a lack of trained mental health personnel. The COVID-19 pandemic, which created a surge in mental health care needs and simultaneously accelerated the adoption of digital health solutions, revealed a new opportunity to quickly scale innovative solutions in the region. OBJECTIVE: In June 2020, the Singaporean government launched mindline.sg, an anonymous digital mental health resource website that has grown to include >500 curated local mental health resources, a clinically validated self-assessment tool for depression and anxiety, an artificial intelligence (AI) chatbot from Wysa designed to deliver digital therapeutic exercises, and a tailored version of the website for working adults called mindline at work. The goal of the platform is to empower Singapore residents to take charge of their own mental health and to be able to offer basic support to those around them through the ease and convenience of a barrier-free digital solution. METHODS: Website use is measured through click-level data analytics captured via Google Analytics and custom application programming interfaces, which in turn drive a customized analytics infrastructure based on the open-source platforms Titanium Database and Metabase. Unique, nonbounced (users that do not immediately navigate away from the site), engaged, and return users are reported. RESULTS: In the 2 years following launch (July 1, 2020, through June 30, 2022), the website received >447,000 visitors (approximately 15% of the target population of 3 million), 62.02% (277,727/447,783) of whom explored the site or engaged with resources (referred to as nonbounced visitors); 10.54% (29,271/277,727) of those nonbounced visitors returned. The most popular features on the platform were the dialogue-based therapeutic exercises delivered by the chatbot and the self-assessment tool, which were used by 25.54% (67,626/264,758) and 11.69% (32,469/277,727) of nonbounced visitors. On mindline at work, the rates of nonbounced visitors who engaged extensively (ie, spent ≥40 seconds exploring resources) and who returned were 51.56% (22,474/43,588) and 13.43% (5,853/43,588) over a year, respectively, compared to 30.9% (42,829/138,626) and 9.97% (13,822/138,626), respectively, on the generic mindline.sg site in the same year. CONCLUSIONS: The site has achieved desired reach and has seen a strong growth rate in the number of visitors, which required substantial and sustained digital marketing campaigns and strategic outreach partnerships. The site was careful to preserve anonymity, limiting the detail of analytics. The good levels of overall adoption encourage us to believe that mild to moderate mental health conditions and the social factors that underly them are amenable to digital interventions. While mindline.sg was primarily used in Singapore, we believe that similar solutions with local customization are widely and globally applicable.

Efficacy of Mobile App-Based Cognitive Behavioral Therapy for Insomnia: Multicenter, Single-Blind Randomized Clinical Trial.

BACKGROUND: Cognitive behavioral therapy for insomnia (CBTi) is the first-line therapy for chronic insomnia. Mobile app-based CBTi (MCBTi) can enhance the accessibility of CBTi treatment; however, few studies have evaluated the effectiveness of MCBTi using a multicenter, randomized controlled trial design. OBJECTIVE: We aimed to assess the efficacy of Somzz, an MCBTi that provides real-time and tailored feedback to users, through comparison with an active comparator app. METHODS: In our multicenter, single-blind randomized controlled trial study, participants were recruited from 3 university hospitals and randomized into a Somzz group and a sleep hygiene education (SHE) group at a 1:1 ratio. The intervention included 6 sessions for 6 weeks, with follow-up visits over a 4-month period. The Somzz group received audiovisual sleep education, guidance on relaxation therapy, and real-time feedback on sleep behavior. The primary outcome was the Insomnia Severity Index score, and secondary outcomes included sleep diary measures and mental health self-reports. We analyzed the outcomes based on the intention-to-treat principle. RESULTS: A total of 98 participants were randomized into the Somzz (n=49, 50%) and SHE (n=49, 50%) groups. Insomnia Severity Index scores for the Somzz group were significantly lower at the postintervention time point (9.0 vs 12.8; t95=3.85; F2,95=22.76; ηp2=0.13; P<.001) and at the 3-month follow-up visit (11.3 vs 14.7; t68=2.61; F2,68=5.85; ηp2=0.03; P=.01) compared to those of the SHE group. The Somzz group maintained their treatment effect at the postintervention time point and follow-ups, with a moderate to large effect size (Cohen d=-0.62 to -1.35; P<.01 in all cases). Furthermore, the Somzz group showed better sleep efficiency (t95=-3.32; F2,91=69.87; ηp2=0.41; P=.001), wake after sleep onset (t95=2.55; F2,91=51.81; ηp2=0.36; P=.01), satisfaction (t95=-2.05; F2,91=26.63; ηp2=0.20; P=.04) related to sleep, and mental health outcomes, including depression (t95=2.11; F2,94=29.64; ηp2=0.21; P=.04) and quality of life (t95=-3.13; F2,94=54.20; ηp2=0.33; P=.002), compared to the SHE group after the intervention. The attrition rate in the Somzz group was 12% (6/49). CONCLUSIONS: Somzz outperformed SHE in improving insomnia, mental health, and quality of life. The MCBTi can be a highly accessible, time-efficient, and effective treatment option for chronic insomnia, with high compliance. TRIAL REGISTRATION: Clinical Research Information Service (CRiS) KCT0007292; https://cris.nih.go.kr/cris/search/detailSearch.do?seq=22214&search_page=L.

Preliminary Efficacy of a Digital Intervention for Adolescent Depression: Randomized Controlled Trial.

BACKGROUND: Adolescent depression is a significant public health concern; however, access to effective mental health care is limited. Digital therapeutics (DTx) can improve access to evidence-based interventions; however, their efficacy in adolescents is sparsely documented. OBJECTIVE: This study aims to examine the efficacy of a mobile app DTx versus an active control as an adjunct treatment for adolescent depression symptoms. METHODS: An internet-based open-label randomized control trial was conducted nationwide with a partial crossover design, and 168 adolescents aged 13 to 21 years with symptoms of depression were recruited between November 2020 and September 2021. Participants were randomized (1:1) to the cognitive behavioral therapy-based treatment app (Spark) or to a psychoeducational control app (control), which they would use for a duration of 5 weeks. The primary outcome was a between-group (Spark vs control) difference in the change in depression symptoms from baseline to postintervention, as measured by the Patient Health Questionnaire-8 (PHQ-8) using a linear mixed-effects analysis. The PHQ-8 ranges from 0 to 24, with scores of 5 to 9 indicating mild depression symptoms, scores of 10 to 14 indicating moderate symptoms, scores of 15 to 19 indicating moderately severe symptoms, and scores of 20 to 24 indicating severe symptoms. A minimal clinically important difference (5-point reduction between baseline and postintervention) in the Spark arm and group differences in remission and treatment response rates based on the PHQ-8 at postintervention were also investigated. RESULTS: A total of 160 participants were randomized, 80 in the Spark arm (mean age 16.89, SD 2.5 y) and 80 in the control arm (mean age 16.79, SD 2.59 y). Data from 121 participants (Spark: n=63; control: n=58) with moderate to severe (PHQ-8≥10) symptoms at baseline were included in the primary analyses following a modified intention-to-treat principle. A linear mixed-effect analysis revealed a nonsignificant difference between the study arms in depression symptom change over the intervention period. The Spark arm met a minimal clinically important difference threshold (mean -5.08, 95% CI -6.72 to -3.42). The remission rate in the Spark arm was significantly higher than that in the control arm (11/63, 17% vs 2/58, 3%; χ21=6.2; P=.01; false discovery rate-adjusted P=.03). The treatment response rates were not significantly different between the study arms (P=.07; false discovery rate-adjusted P=.16). Post hoc analyses including participants with mild to severe (PHQ-8 score ≥5) symptoms at baseline revealed promising evidence that Spark is effective in those with mild to severe symptoms. CONCLUSIONS: There is initial evidence that a self-guided, cognitive behavioral therapy-based DTx intervention may effectively treat mild to severe depression symptoms in adolescents. DTx may improve access to mental health care for adolescents or serve as an important adjunct to the standard of care. TRIAL REGISTRATION: ClinicalTrials.gov NCT04524598; https://clinicaltrials.gov/study/NCT04524598.

The Digital Therapeutics Real-World Evidence Framework: An Approach for Guiding Evidence-Based Digital Therapeutics Design, Development, Testing, and Monitoring.

Digital therapeutics (DTx) are a promising way to provide safe, effective, accessible, sustainable, scalable, and equitable approaches to advance individual and population health. However, developing and deploying DTx is inherently complex in that DTx includes multiple interacting components, such as tools to support activities like medication adherence, health behavior goal-setting or self-monitoring, and algorithms that adapt the provision of these according to individual needs that may change over time. While myriad frameworks exist for different phases of DTx development, no single framework exists to guide evidence production for DTx across its full life cycle, from initial DTx development to long-term use. To fill this gap, we propose the DTx real-world evidence (RWE) framework as a pragmatic, iterative, milestone-driven approach for developing DTx. The DTx RWE framework is derived from the 4-phase development model used for behavioral interventions, but it includes key adaptations that are specific to the unique characteristics of DTx. To ensure the highest level of fidelity to the needs of users, the framework also incorporates real-world data (RWD) across the entire life cycle of DTx development and use. The DTx RWE framework is intended for any group interested in developing and deploying DTx in real-world contexts, including those in industry, health care, public health, and academia. Moreover, entities that fund research that supports the development of DTx and agencies that regulate DTx might find the DTx RWE framework useful as they endeavor to improve how DTxcan advance individual and population health.

Effects of game-based digital therapeutics on attention deficit hyperactivity disorder in children and adolescents as assessed by parents or teachers: a systematic review and meta-analysis.

Attention-deficit/hyperactivity disorder (ADHD) is a childhood-onset disorder characterized by pharmacological and non-pharmacological interventions. Despite the available treatment options and prevention measures, conventional treatments have several limitations. Digital therapeutics (DTx) like EndeavorRx® is an emerging alternative to overcome these limitations. EndeavorRx® is the first FDA-approved, game-based DTx approved for the treatment of pediatric ADHD. We investigated the effects of game-based DTx in randomised controlled trials (RCTs) on children and adolescents with ADHD. In this systematic review and meta-analysis, we searched PubMed, Embase, and PsycINFO databases up to January 2022. The protocol was registered (CRD42022299866). The assessor was defined as parents and teachers. The primary outcome was differences in inattention reported by the assessor, and the secondary outcome was differences in hyperactivity and hyperactivity/impulsivity reported by the assessor and the relative comparisons between game-based DTx, medicine, and control with indirect meta-analysis. Game-based DTx improved inattention more than the control upon assessment by assessors (standard mean difference (SMD) 0.28, 95% confidence interval (CI) 0.14-0.41; SMD 0.21, 95% CI 0.03-0.39, respectively), while medication improved inattention more than game-based DTx (SMD - 0·62, 95% CI - 1·04 to - 0·20) upon assessment by the teacher. Game-based DTx improved hyperactivity/impulsivity than the control upon assessment by assessors (SMD 0.28, 95% CI 0.03-0.53; SMD 0.30, 95% CI 0.05-0.55, respectively), and medication improved hyperactivity/impulsivity significantly than game-based DTx upon assessment by the teacher. Hyperactivity has not been reported extensively. As a result, game-based DTx had a more significant effect than the control, however medication was more effective.

sEMG Biofeedback for Episodic Migraines: A Pilot Randomized Clinical Trial.

The aim of this study was to assess the feasibility and potential effectiveness of a 6-week virtual sEMG biofeedback intervention for patients with episodic migraines. Patients with episodic migraines were randomized to treatment with a novel surface EMG (sEMG) at-home biofeedback device or a treatment as usual control group; they completed validated baseline and post-intervention assessments of migraine related disability (migraine-specific quality of life, anxiety and depression). Participants also underwent a series of Quantitative Sensory Testing (QST) procedures referring to several different tests that quantitatively assess responses to mechanical stimuli during two separate visits (baseline and post intervention). No adverse events were reported during the study. Compared to the treatment as usual comparison group, patients in the sEMG biofeedback group reported lower migraine disability (p < 0.05). Compared to baseline, participants in the sEMG biofeedback group demonstrated statistically significant reductions in anxiety (p < 0.01), and significant increases in quality of life (p < 0.001), and significant decreases in temporal summation (p < 0.05) assessed by QST. No significant changes were observed in any of the outcomes in the control comparison group (p > 0.05). No significant changes were observed in migraine frequency in either of the two groups (p > 0.05). In addition, mediation analyses revealed that changes in migraine related quality of life mediated group effects on changes in migraine disability. Virtual sEMG biofeedback shows promise as a potential therapy for reducing disability, anxiety and depression and improving quality of life in individuals with episodic migraines. These results demonstrate the feasibility of a digital intervention for migraines and set the basis for conducting a future, larger scale randomized controlled trial to confirm these preliminary findings.

[Digital medicine in neurological research-Between hype and evidence]. / Digitale Medizin in der neurologischen Forschung ­ zwischen Hype und Evidenz.

BACKGROUND: The rapid advancement of digital medicine and health technologies in neurology offers both significant potential and challenges. This article outlines fundamental aspects of digital medicine related to neurological research and highlights application examples of digital technologies in neurological research. AIM: To provide a comprehensive overview of current digital developments in neurology and their impact on neurological research. MATERIAL AND METHODS: In this narrative review articles from various sources and references related to digital medicine and health technologies in neurology were compiled and analyzed. RESULTS AND DISCUSSION: The data presented indicate that digital health technologies and digital therapeutics have the potential to decisively shape neurological care and research; however, it is emphasized that a critical evaluation and evidence-based approach to these technologies are essential to determine their actual value in neurology.

[Get used to digital therapeutics (DTx) : they will take the scene in health care !] / La médecine du futur. Habituez-vous aux moyens de traitements digitaux : ils arrivent !

Digital therapeutics are making headways in medical treatment at large. They are used alone or in combination with standard medical treatment in various fields, aiming at essentially behavioral changes. As we are facing a growing imbalance between demand and resources, these digital treatments offer a powerful way for patient empowerment.

Les traitements numériques font irruption dans l'arsenal thérapeutique. Ils sont utilisés seuls ou en association avec des approches médicamenteuses classiques. Ils visent souvent des changements comportementaux dont on souligne de plus en plus l'importance dans différents domaines de la santé. Vu l'augmentation significative des besoins en soins de santé, dans un contexte tendu de limitations de ressources, ils offrent un moyen d'autonomisation de la prise en charge par les patients.

Effectiveness of personalized treatment stage-adjusted digital therapeutics in colorectal cancer: a randomized controlled trial.

BACKGROUND: Colorectal cancer survivors often experience decline in physical performance and poor quality of life after surgery and during adjuvant therapies. In these patients, preserving skeletal muscle mass and high-quality nourishment are essential to reduce postoperative complications and improve quality of life and cancer-specific survival. Digital therapeutics have emerged as an encouraging tool for cancer survivors. However, to the best of our knowledge, randomized clinical trials applying personalized mobile application and smart bands as a supportive tool to several colorectal patients remain to be conducted, intervening immediately after the surgical treatment. METHODS: This study is a prospective, multi-center, single-blinded, two-armed, randomized controlled trial. The study aims to recruit 324 patients from three hospitals. Patients will be randomly allocated to two groups for one year of rehabilitation, starting immediately after the operation: a digital healthcare system rehabilitation (intervention) group and a conventional education-based rehabilitation (control) group. The primary objective of this protocol is to clarify the effect of digital healthcare system rehabilitation on skeletal muscle mass increment in patients with colorectal cancer. The secondary outcomes would be the improvement in quality of life measured by EORTC QLQ C30 and CR29, enhanced physical fitness level measured by grip strength test, 30-sec chair stand test and 2-min walk test, increased physical activity measured by IPAQ-SF, alleviated pain intensity, decreased severity of the LARS, weight, and fat mass. These measurements will be held on enrollment and at 1, 3, 6 and 12 months thereafter. DISCUSSION: This study will compare the effect of personalized treatment stage-adjusted digital health interventions on immediate postoperative rehabilitation with that of conventional education-based rehabilitation in patients with colorectal cancer. This will be the first randomized clinical trial performing immediate postoperative rehabilitation in a large number of patients with colorectal cancer with a tailored digital health intervention, modified according to the treatment phase and patient condition. The study will add foundations for the application of comprehensive digital healthcare programs focusing on individuality in postoperative rehabilitation of patients with cancer. TRIAL REGISTRATION: NCT05046756. Registered on 11 May 2021.

Behavior change, health, and health disparities 2023: Contingency management for treating substance use disorders and promoting health in vulnerable populations.

This Special Issue (SI) of Preventive Medicine is the 10th in a series on behavior change, health, and health disparities. This issue focuses on Contingency Management (CM), a highly efficacious behavior-change intervention for substance use disorders (SUDs) and other behavioral health conditions wherein patients receive material incentives (e.g., vouchers exchangeable for retail items) contingent on objectively verified behavior change. Despite substantial support for its efficacy, CM remains largely unavailable in U.S. community SUD treatment facilities and other healthcare settings. This is especially concerning regarding stimulant use disorder for which CM is the only reliably efficacious intervention in controlled studies and yet is unavailable to the vast majority of those in need. This SI details recent promising developments in efforts to surmount longstanding implementation obstacles while also detailing other promising advances from meta-analyses and controlled trials examining CM's efficacy in treating other difficult-to-treat problems including smoking among pregnant women and mothers of young children as well among those as those experiencing homelessness and alcohol use disorder, the promise of digital CM, and a potential new application in promoting adherence with SUD medications.

Acceptability and Feasibility of a Mobile Phone Application to Support HIV Pre-exposure Prophylaxis Among Women with Opioid Use Disorder.

Despite evidence supporting HIV pre-exposure prophylaxis (PrEP) effectiveness, very few women with opioid use disorder (OUD) take PrEP. Interventions that improve medication assisted treatment (MAT) uptake and adherence may also be beneficial for PrEP. The reSET-O mobile phone app is a component of the evidence-based Therapeutic Education System, which improves retention and abstinence for people with OUD. To better understand use of this mobile health tool as a support for PrEP among women with OUD, pre-implementation contextual inquiry is needed. Therefore, we set out to assess target user characteristics, implementation barriers, feasibility, and acceptability of reSET-O. We recruited women with OUD receiving care from a community-based organization in Philadelphia to complete semi-structured interviews. All participants were prescribed reSET-O. We interviewed 20 participants (average age 37 years; 70% white, 15% Hispanic, 5% Black) from 5/2021 to 2/2022. We used an integrated analysis approach combining modified grounded theory and implementation science constructs. Half reported recent injection drug use, and 6 were taking buprenorphine. Mental health symptoms were common, and half described engaging in transactional sex. The majority expressed strong interest in PrEP. Participants reported the app would be highly acceptable for PrEP and MAT adherence support, but only two redeemed the prescription. The most common barriers included phone and internet access. Our findings highlight potential implementation challenges for the use of such an app to support PrEP use in this population. Poor uptake of the app at follow-up indicates that initial prescription redemption is a major barrier to reSET-O implementation.

Cost-effectiveness analysis of digital therapeutics for home-based cardiac rehabilitation for patients with chronic heart failure: model development and data analysis.

BACKGROUND: In recent years, numerous guidelines and expert consensus have recommended the inclusion of digital technologies and products in cardiac rehabilitation. Digital therapeutics (DTx) is an evidence-based medicine that uses digital means for data collection and monitoring of indicators to control and optimize the treatment, management, and prevention of disease. OBJECTIVE: This study collected and reviewed real-world data and built a model using health economics assessment methods to analyze the potential cost-effectiveness of DTx applied to home-based cardiac rehabilitation for patients with chronic heart failure. From the perspective of medical and health decision-makers, the economic value of DTx is evaluated prospectively to provide the basis and reference for the application decision and promotion of DTx. METHODS: Markov models were constructed to simulate the outcomes of DTx for home-based cardiac rehabilitation (DT group) compared to conventional home-based cardiac rehabilitation (CH group) in patients with chronic heart failure. The model input parameters were clinical indicators and cost data. Outcome indicators were quality-adjusted life years (QALYs) and incremental cost-effectiveness ratios (ICERs). The robustness of the evaluation methods and results was tested using sensitivity analyses. Clinical indicators, cost data, and health utility values were obtained from real-world data, including clinical study data, published literature, and public website information. RESULTS: The Markov model simulated a time span of 10 years, with a cycle set at one month, for 120 cycles. The results showed that the per capita cost of the CH group was 38,442.11 CNY/year, with a QALY of 0.7196 per person per year. The per capita cost of the DT group was 42,300.26 CNY/year, with a QALY of 0.81687 per person per year. The ICER per person was 39,663.5 CNY/QALY each year, which was below the willingness-to-pay threshold of 85,698 CNY (China's GDP per capita in 2022). CONCLUSIONS: DTx for home-based cardiac rehabilitation is an extremely cost-effective rehabilitation option compared with conventional home-based cardiac rehabilitation. DTx for home-based cardiac rehabilitation is potentially valuable from the perspective of healthcare decision-makers.

Digital health technologies and major depressive disorder.

There is an urgent need to improve the clinical management of major depressive disorder (MDD), which has become increasingly prevalent over the past two decades. Several gaps and challenges in the awareness, detection, treatment, and monitoring of MDD remain to be addressed. Digital health technologies have demonstrated utility in relation to various health conditions, including MDD. Factors related to the COVID-19 pandemic have accelerated the development of telemedicine, mobile medical apps, and virtual reality apps and have continued to introduce new possibilities across mental health care. Growing access to and acceptance of digital health technologies present opportunities to expand the scope of care and to close gaps in the management of MDD. Digital health technology is rapidly evolving the options for nonclinical support and clinical care for patients with MDD. Iterative efforts to validate and optimize such digital health technologies, including digital therapeutics and digital biomarkers, continue to improve access to and quality of personalized detection, treatment, and monitoring of MDD. The aim of this review is to highlight the existing gaps and challenges in depression management and discuss the current and future landscape of digital health technology as it applies to the challenges faced by patients with MDD and their healthcare providers.