Digital mental health intervention for orthopedic patients with symptoms of depression and/or anxiety: Pilot feasibility study

Effect of Depression Interventions in Patients Undergoing Total Joint Arthroplasty Without a Formal Diagnosis of Depression: A Systematic Review

PURPOSE

Depression is a notable contributor to suboptimal outcomes after total joint arthroplasty (TJA). We conducted a systematic review of comparative studies to review the available evidence of interventions that affected depression scores and/or outcomes for patients undergoing TJA.

METHODS

EMBASE, Ovid MEDLINE, PubMed, and Scopus were reviewed systematically from inception until November 15, 2022. Studies that were relevant for this review included comparative studies between patients who received an intervention within 3 months before or after their primary total hip or knee arthroplasty procedure. The interventions included a wide range of modalities, which were grouped into psychotherapy, enhanced perioperative support, and pharmacotherapy. Other interventions included physiotherapy techniques with a psychological focus, art/music-based therapy, occupational therapy support, and educational interventions. Meta-analysis was conducted for psychotherapy and enhanced support.

RESULTS

The final systematic review consisted of 28 relevant studies, most of which were randomized controlled trials. A total of 3,702 patients, with a mean age of 66 years, were considered, of whom 59% were female. Most of the studies reported a notable reduction in depressive symptoms and/or scores based on the interventions being analyzed. At 3 months postoperatively, psychotherapy and enhanced support both resulted in markedly better depression and function scores compared with control subjects, with psychotherapy additionally improving pain scores.

CONCLUSIONS

Overall, a wide range of interventions aimed at psychological optimization of patients undergoing TJA can improve depressive symptoms, pain, and function, even in the absence of a formal diagnosis of depression. Specifically, cognitive-based psychotherapy and enhanced perioperative support had the best evidence. Routine pharmacotherapy plays a limited role, if any, in the care of TJA. Additional efforts to develop pragmatic, evidence-based, and reproducible interventions are warranted to continue to optimize outcomes in TJA patients.

Deep learning-based dimensional emotion recognition for conversational agent-based cognitive behavioral therapy

Internet-based cognitive behavioral therapy (iCBT) offers a scalable, cost-effective, accessible, and low-threshold form of psychotherapy. Recent advancements explored the use of conversational agents such as chatbots and voice assistants to enhance the delivery of iCBT. These agents can deliver iCBT-based exercises, recognize and track emotional states, assess therapy progress, convey empathy, and potentially predict long-term therapy outcome. However, existing systems predominantly utilize categorical approaches for emotional modeling, which can oversimplify the complexity of human emotional states. To address this, we developed a transformer-based model for dimensional text-based emotion recognition, fine-tuned with a novel, comprehensive dimensional emotion dataset comprising 75,503 samples. This model significantly outperforms existing state-of-the-art models in detecting the dimensions of valence, arousal, and dominance, achieving a Pearson correlation coefficient of r = 0.90, r = 0.77, and r = 0.64, respectively. Furthermore, a feasibility study involving 20 participants confirmed the model's technical effectiveness and its usability, acceptance, and empathic understanding in a conversational agent-based iCBT setting, marking a substantial improvement in personalized and effective therapy experiences.

Effectiveness of a Mental Health Chatbot for People With Chronic Diseases: Randomized Controlled Trial

BACKGROUND

People with chronic diseases tend to experience more mental health issues than their peers without these health conditions. Mental health chatbots offer a potential source of mental health support for people with chronic diseases.

OBJECTIVE

The aim of this study was to determine whether a mental health chatbot can improve mental health in people with chronic diseases. We focused on 2 chronic diseases in particular: arthritis and diabetes.

METHODS

Individuals with arthritis or diabetes were recruited using various web-based methods. Participants were randomly assigned to 1 of 2 groups. Those in the treatment group used a mental health chatbot app (Wysa [Wysa Inc]) over a period of 4 weeks. Those in the control group received no intervention. Participants completed measures of depression (Patient Health Questionnaire-9), anxiety (Generalized Anxiety Disorder Scale-7), and stress (Perceived Stress Scale-10) at baseline, with follow-up testing 2 and 4 weeks later. Participants in the treatment group completed feedback questions on their experiences with the app at the final assessment point.

RESULTS

A total of 68 participants (n=47, 69% women; mean age 42.87, SD 11.27 years) were included in the analysis. Participants were divided evenly between the treatment and control groups. Those in the treatment group reported decreases in depression (P<.001) and anxiety (P<.001) severity over the study period. No such changes were found among participants in the control group. No changes in stress were reported by participants in either group. Participants with arthritis reported higher levels of depression (P=.004) and anxiety (P=.004) severity than participants with diabetes over the course of the study, as well as higher levels of stress (P=.01); otherwise, patterns of results were similar across these health conditions. In response to the feedback questions, participants in the treatment group said that they liked many of the functions and features of the app, the general design of the app, and the user experience. They also disliked some aspects of the app, with most of these reports focusing on the chatbot's conversational abilities.

CONCLUSIONS

The results of this study suggest that mental health chatbots can be an effective source of mental health support for people with chronic diseases such as arthritis and diabetes. Although cost-effective and accessible, these programs have limitations and may not be well suited for all individuals.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04620668; https://www.clinicaltrials.gov/study/NCT04620668.

AI-Led Mental Health Support (Wysa) for Health Care Workers During COVID-19: Service Evaluation

BACKGROUND

The impact that the COVID-19 pandemic has had on health care workers' mental health, in particular, cannot be ignored. Not only did the pandemic exacerbate mental health challenges through elevated stress, anxiety, risk of infection, and social isolation, but regulations to minimize infection additionally hindered the conduct of traditional in-person mental health care.

OBJECTIVE

This study explores the feasibility of using Wysa, an artificial intelligence-led mental health app, among health care workers.

METHODS

A national tertiary health care cluster in Singapore piloted the use of Wysa among its own health care workers to support the management of their mental well-being during the pandemic (July 2020-June 2022). The adoption of this digital mental health intervention circumvented the limitations of in-person contact and enabled large-scale access to evidence-based care. Rates and patterns of user engagement were evaluated.

RESULTS

Overall, the opportunity to use Wysa was well-received. Out of the 527 staff who were onboarded in the app, 80.1% (422/527) completed a minimum of 2 sessions. On average, users completed 10.9 sessions over 3.80 weeks. The interventions most used were for sleep and anxiety, with a strong repeat-use rate. In this sample, 46.2% (73/158) of health care workers reported symptoms of anxiety (Generalized Anxiety Disorder Assessment-7 [GAD-7]), and 15.2% (24/158) were likely to have symptoms of depression (Patient Health Questionnaire-2 [PHQ-2]).

CONCLUSIONS

Based on the present findings, Wysa appears to strongly engage those with none to moderate symptoms of anxiety. This evaluation demonstrates the viability of implementing Wysa as a standard practice among this sample of health care workers, which may support the use of similar digital interventions across other communities.

Reviewing the Potential Role of Artificial Intelligence in Delivering Personalized and Interactive Pain Medicine Education for Chronic Pain Patients

The integration of artificial intelligence (AI) in patient pain medicine education has the potential to revolutionize pain management. By harnessing the power of AI, patient education becomes more personalized, interactive, and supportive, empowering patients to understand their pain, make informed decisions, and actively participate in their pain management journey. AI tailors the educational content to individual patients' needs, providing personalized recommendations. It introduces interactive elements through chatbots and virtual assistants, enhancing engagement and motivation. AI-powered platforms improve accessibility by providing easy access to educational resources and adapting content to diverse patient populations. Future AI applications in pain management include explaining pain mechanisms, treatment options, predicting outcomes based on individualized patient-specific factors, and supporting monitoring and adherence. Though the literature on AI in pain medicine and its applications are scarce yet growing, we propose avenues where AI may be applied and review the potential applications of AI in pain management education. Additionally, we address ethical considerations, patient empowerment, and accessibility barriers.

Evaluation framework for conversational agents with artificial intelligence in health interventions: a systematic scoping review

OBJECTIVES

Conversational agents (CAs) with emerging artificial intelligence present new opportunities to assist in health interventions but are difficult to evaluate, deterring their applications in the real world. We aimed to synthesize existing evidence and knowledge and outline an evaluation framework for CA interventions.

MATERIALS AND METHODS

We conducted a systematic scoping review to investigate designs and outcome measures used in the studies that evaluated CAs for health interventions. We then nested the results into an overarching digital health framework proposed by the World Health Organization (WHO).

RESULTS

The review included 81 studies evaluating CAs in experimental (n = 59), observational (n = 15) trials, and other research designs (n = 7). Most studies (n = 72, 89%) were published in the past 5 years. The proposed CA-evaluation framework includes 4 evaluation stages: (1) feasibility/usability, (2) efficacy, (3) effectiveness, and (4) implementation, aligning with WHO's stepwise evaluation strategy. Across these stages, this article presents the essential evidence of different study designs (n = 8), sample sizes, and main evaluation categories (n = 7) with subcategories (n = 40). The main evaluation categories included (1) functionality, (2) safety and information quality, (3) user experience, (4) clinical and health outcomes, (5) costs and cost benefits, (6) usage, adherence, and uptake, and (7) user characteristics for implementation research. Furthermore, the framework highlighted the essential evaluation areas (potential primary outcomes) and gaps across the evaluation stages.

DISCUSSION AND CONCLUSION

This review presents a new framework with practical design details to support the evaluation of CA interventions in healthcare research.

PROTOCOL REGISTRATION

The Open Science Framework (https://osf.io/9hq2v) on March 22, 2021.

Systematic review and meta-analysis of AI-based conversational agents for promoting mental health and well-being

Conversational artificial intelligence (AI), particularly AI-based conversational agents (CAs), is gaining traction in mental health care. Despite their growing usage, there is a scarcity of comprehensive evaluations of their impact on mental health and well-being. This systematic review and meta-analysis aims to fill this gap by synthesizing evidence on the effectiveness of AI-based CAs in improving mental health and factors influencing their effectiveness and user experience. Twelve databases were searched for experimental studies of AI-based CAs' effects on mental illnesses and psychological well-being published before May 26, 2023. Out of 7834 records, 35 eligible studies were identified for systematic review, out of which 15 randomized controlled trials were included for meta-analysis. The meta-analysis revealed that AI-based CAs significantly reduce symptoms of depression (Hedge's g 0.64 [95% CI 0.17-1.12]) and distress (Hedge's g 0.7 [95% CI 0.18-1.22]). These effects were more pronounced in CAs that are multimodal, generative AI-based, integrated with mobile/instant messaging apps, and targeting clinical/subclinical and elderly populations. However, CA-based interventions showed no significant improvement in overall psychological well-being (Hedge's g 0.32 [95% CI -0.13 to 0.78]). User experience with AI-based CAs was largely shaped by the quality of human-AI therapeutic relationships, content engagement, and effective communication. These findings underscore the potential of AI-based CAs in addressing mental health issues. Future research should investigate the underlying mechanisms of their effectiveness, assess long-term effects across various mental health outcomes, and evaluate the safe integration of large language models (LLMs) in mental health care.

Immersive Virtual Reality Therapy Is Supportive for Orthopedic Rehabilitation among the Elderly: A Randomized Controlled Trial

OBJECTIVE

This research aimed to determine the efficacy of VR therapy in mitigating symptoms of depression, anxiety, and stress among older adults following arthroplasty surgery and to comprehend the influence of psychological improvement on changes in functional outcomes.

METHODS

Utilizing a parallel-group randomized controlled trial design, the study involved 68 osteoarthritis patients who had recently undergone either total hip or knee arthroplasty. Subjects were split into two groups. The experimental group underwent eight VR therapy sessions during their rehabilitation, while the control group was given standard care. Assessments encompassed both psychological and functional outcomes, with tools like the Hospital Anxiety and Depression Scale, Perceived Stress Scale, and the Barthel Index, among others. The experimental group showcased notable enhancements in both psychological and functional areas compared to the control group.

RESULTS

A significant (p value of < 0.001) relationship was found between psychological progress and functional recovery, indicating that psychological factors can serve as predictors for functional outcomes.

CONCLUSIONS

The findings emphasize the promising role of VR therapy as a beneficial addition to the rehabilitation process for older adults' post-hip and knee arthroplasty. The integration of psychological interventions in standard rehabilitation practices appears valuable, but further studies are needed to ascertain the long-term advantages of such an approach.

Digitally Assisted Mindfulness in Training Self-Regulation Skills for Sustainable Mental Health: A Systematic Review

The onset of the COVID-19 pandemic has led to an increased demand for mental health interventions, with a special focus on digitally assisted ones. Self-regulation describes a set of meta-skills that enable one to take control over his/her mental health and it is recognized as a vital indicator of well-being. Mindfulness training is a promising training strategy for promoting self-regulation, behavioral change, and mental well-being. A growing body of research outlines that smart technologies are ready to revolutionize the way mental health training programs take place. Artificial intelligence (AI); extended reality (XR) including virtual reality (VR), augmented reality (AR), and mixed reality (MR); as well as the advancements in brain computer interfaces (BCIs) are ready to transform these mental health training programs. Mindfulness-based interventions assisted by smart technologies for mental, emotional, and behavioral regulation seem to be a crucial yet under-investigated issue. The current systematic review paper aims to explore whether and how smart technologies can assist mindfulness training for the development of self-regulation skills among people at risk of mental health issues as well as populations with various clinical characteristics. The PRISMA 2020 methodology was utilized to respond to the objectives and research questions using a total of sixty-six experimental studies that met the inclusion criteria. The results showed that digitally assisted mindfulness interventions supported by smart technologies, including AI-based applications, chatbots, virtual coaches, immersive technologies, and brain-sensing headbands, can effectively assist trainees in developing a wide range of cognitive, emotional, and behavioral self-regulation skills, leading to a greater satisfaction of their psychological needs, and thus mental wellness. These results may provide positive feedback for developing smarter and more inclusive training environments, with a special focus on people with special training needs or disabilities.

Behavioral Mechanisms That Mediate Mental and Physical Health Improvements in People With Chronic Pain Who Receive a Digital Health Intervention: Prospective Cohort Pilot Study

BACKGROUND

Preliminary evidence suggests that digital mental health intervention (Wysa for Chronic Pain) can improve mental and physical health in people with chronic musculoskeletal pain and coexisting symptoms of depression or anxiety. However, the behavioral mechanisms through which this intervention acts are not fully understood.

OBJECTIVE

The purpose of this study was to identify behavioral mechanisms that may mediate changes in mental and physical health associated with use of Wysa for Chronic Pain during orthopedic management of chronic musculoskeletal pain. We hypothesized that improved behavioral activation, pain acceptance, and sleep quality mediate improvements in self-reported mental and physical health.

METHODS

In this prospective cohort, pilot mediation analysis, adults with chronic (≥3 months) neck or back pain received the Wysa for Chronic Pain digital intervention, which uses a conversational agent and text-based access to human counselors to deliver cognitive behavioral therapy and related therapeutic content. Patient-reported outcomes and proposed mediators were collected at baseline and 1 month. The exposure of interest was participants' engagement (ie, total interactions) with the digital intervention. Proposed mediators were assessed using the Behavioral Activation for Depression Scale-Short Form, Chronic Pain Acceptance Questionnaire, and Athens Insomnia Scale. Outcomes included Patient-Reported Outcomes Measurement Information System Anxiety, Depression, Pain Interference, and Physical Function scores. A mediation analysis was conducted using the Baron and Kenny method, adjusting for age, sex, and baseline mediators and outcome values. P<.20 was considered significant for this pilot study.

RESULTS

Among 30 patients (mean age 59, SD 14, years; 21 [70%] female), the mediation effect of behavioral activation on the relationship between increased intervention engagement and improved anxiety symptoms met predefined statistical significance thresholds (indirect effect -0.4, 80% CI -0.7 to -0.1; P=.13, 45% of the total effect). The direction of mediation effect was generally consistent with our hypothesis for all other proposed mediator or outcome relationships, as well.

CONCLUSIONS

In a full-sized randomized controlled trial of patients with chronic musculoskeletal pain, behavioral activation, pain acceptance, and sleep quality may play an important role in mediating the relationship between use of a digital mental health intervention (Wysa for Chronic Pain) and improved mental and physical health.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05194722; https://clinicaltrials.gov/ct2/show/NCT05194722.

Specifying the Efficacy of Digital Therapeutic Tools for Depression and Anxiety: Retrospective, 2-Cohort, Real-World Analysis

BACKGROUND

Depression and anxiety are the main sources of work and social disabilities as well as health-related problems around the world. Digital therapeutic solutions using cognitive behavioral therapy have demonstrated efficacy in depression and anxiety. A common goal of digital health apps is to increase user digital engagement to improve outcomes. However, there is a limited understanding of the association between digital platform components and clinical outcomes.

OBJECTIVE

The aim of the study is to investigate the contribution of specific digital engagement tools to mental health conditions. We hypothesized that participation in coaching sessions and breathing exercises would be associated with a reduction in depression and anxiety.

METHODS

Depression and general anxiety symptoms were evaluated in real-world data cohorts using the digital health platform for digital intervention and monitoring change. This retrospective real-world analysis of users on a mobile platform-based treatment followed two cohorts of people: (1) users who started with moderate levels of depression and completed at least 2 depression assessments (n=519) and (2) users who started with moderate levels of anxiety and completed at least 2 anxiety assessments (n=474). Levels of depression (Patient Health Questionnaire-9) and anxiety (Generalized Anxiety Disorder-7) were tracked throughout the first 16 weeks. A piecewise mixed-effects model was applied to model the trajectories of the Patient Health Questionnaire-9 and the Generalized Anxiety Disorder-7 mean scores in 2 segments (1-6 weeks and 7-16 weeks). Finally, simple slope analysis was used for the interpretation of the interactions probing the moderators: coaching sessions and breathing exercises in both depression and anxiety cohorts.

RESULTS

Analysis revealed a significant decrease in depression symptoms (β=-.37, 95% CI -0.46 to 0.28; P≤.001) during the period of weeks 1-6 of app use, which was maintained during the period of 7-16 weeks. Coach interaction significantly moderated the reduction in depression symptoms during the period of weeks 1-6 (β=-.03, 95% CI -0.05 to -0.001; P=.02). A significant decrease in anxiety symptoms (β=-.41, 95% CI -0.50 to -0.33; P≤.001) was revealed during the period of 1-6 weeks, which was maintained during the period of 7-16 weeks. Breathing exercises significantly moderated the reduction in anxiety symptoms during the period of 1-6 weeks (β=-.07, 95% CI -0.14 to -0.01; P=.04).

CONCLUSIONS

This study demonstrated general improvement followed by a period of stability of depression and anxiety symptoms associated with cognitive behavioral therapy-based digital intervention. Interestingly, engagement with a coaching session but not a breathing exercise was associated with a reduction in depression symptoms. Moreover, breathing exercise but not engagement with a coaching session was associated with a reduction of anxiety symptoms. These findings emphasize the importance of using a personalized approach to behavioral health during digital health interventions.

An artificial intelligence-powered, patient-centric digital tool for self-management of chronic pain: a prospective, multicenter clinical trial

OBJECTIVE

To investigate how a behavioral health, artificial intelligence (AI)-powered, digital self-management tool affects the daily functions in adults with chronic back and neck pain.

DESIGN

Eligible subjects were enrolled in a 12-week prospective, multicenter, single-arm, open-label study and instructed to use the digital coach daily. Primary outcome was a change in Patient-Reported Outcomes Measurement Information Systems (PROMIS) scores for pain interference. Secondary outcomes were changes in PROMIS physical function, anxiety, depression, pain intensity scores and pain catastrophizing scale (PCS) scores.

METHODS

Subjects logged daily activities, using PainDrainerTM, and data analyzed by the AI engine. Questionnaire and web-based data were collected at 6 and 12 weeks and compared to subjects' baseline.

RESULTS

Subjects completed the 6- (n = 41) and 12-week (n = 34) questionnaires. A statistically significant Minimal Important Difference (MID) for pain interference was demonstrated in 57.5% of the subjects. Similarly, MID for physical function was demonstrated in 72.5% of the subjects. A pre- to post-intervention improvement in depression score was also statistically significant, observed in 100% of subjects, as was the improvement in anxiety scores, evident in 81.3% of the subjects. PCS mean scores was also significantly decreased at 12 weeks.

CONCLUSION

Chronic pain self-management, using an AI-powered, digital coach anchored in behavioral health principles significantly improved subjects' pain interference, physical function, depression, anxiety, and pain catastrophizing over the 12-week study period.

Understanding the impact of an AI-enabled conversational agent mobile app on users' mental health and wellbeing with a self-reported maternal event: a mixed method real-world data mHealth study

Background

Maternal mental health care is variable and with limited accessibility. Artificial intelligence (AI) conversational agents (CAs) could potentially play an important role in supporting maternal mental health and wellbeing. Our study examined data from real-world users who self-reported a maternal event while engaging with a digital mental health and wellbeing AI-enabled CA app (Wysa) for emotional support. The study evaluated app effectiveness by comparing changes in self-reported depressive symptoms between a higher engaged group of users and a lower engaged group of users and derived qualitative insights into the behaviors exhibited among higher engaged maternal event users based on their conversations with the AI CA.

Methods

Real-world anonymised data from users who reported going through a maternal event during their conversation with the app was analyzed. For the first objective, users who completed two PHQ-9 self-reported assessments (n = 51) were grouped as either higher engaged users (n = 28) or lower engaged users (n = 23) based on their number of active session-days with the CA between two screenings. A non-parametric Mann-Whitney test (M-W) and non-parametric Common Language effect size was used to evaluate group differences in self-reported depressive symptoms. For the second objective, a Braun and Clarke thematic analysis was used to identify engagement behavior with the CA for the top quartile of higher engaged users (n = 10 of 51). Feedback on the app and demographic information was also explored.

Results

Results revealed a significant reduction in self-reported depressive symptoms among the higher engaged user group compared to lower engaged user group (M-W p = .004) with a high effect size (CL = 0.736). Furthermore, the top themes that emerged from the qualitative analysis revealed users expressed concerns, hopes, need for support, reframing their thoughts and expressing their victories and gratitude.

Conclusion

These findings provide preliminary evidence of the effectiveness and engagement and comfort of using this AI-based emotionally intelligent mobile app to support mental health and wellbeing across a range of maternal events and experiences.

Multi-stakeholder perspectives regarding preferred modalities for mental health intervention delivered in the orthopedic clinic: a qualitative analysis

BACKGROUND

Although depressive and anxious symptoms negatively impact musculoskeletal health and orthopedic outcomes, a gap remains in identifying modalities through which mental health intervention can realistically be delivered during orthopedic care. The purpose of this study was to understand orthopedic stakeholders' perceptions regarding the feasibility, acceptability, and usability of digital, printed, and in-person intervention modalities to address mental health as part of orthopedic care.

METHODS

This single-center, qualitative study was conducted within a tertiary care orthopedic department. Semi-structured interviews were conducted between January and May 2022. Two stakeholder groups were interviewed using a purposive sampling approach until thematic saturation was reached. The first group included adult orthopedic patients who presented for management of ≥ 3 months of neck or back pain. The second group included early, mid, and late career orthopedic clinicians and support staff members. Stakeholders' interview responses were analyzed using deductive and inductive coding approaches followed by thematic analysis. Patients also performed usability testing of one digital and one printed mental health intervention.

RESULTS

Patients included 30 adults out of 85 approached (mean (SD) age 59 [14] years, 21 (70%) women, 12 (40%) non-White). Clinical team stakeholders included 22 orthopedic clinicians and support staff members out of 25 approached (11 (50%) women, 6 (27%) non-White). Clinical team members perceived a digital mental health intervention to be feasible and scalable to implement, and many patients appreciated that the digital modality offered privacy, immediate access to resources, and the ability to engage during non-business hours. However, stakeholders also expressed that a printed mental health resource is still necessary to meet the needs of patients who prefer and/or can only engage with tangible, rather than digital, mental health resources. Many clinical team members expressed skepticism regarding the current feasibility of scalably incorporating in-person support from a mental health specialist into orthopedic care.

CONCLUSIONS

Although digital intervention offers implementation-related advantages over printed and in-person mental health interventions, a subset of often underserved patients will not currently be reached using exclusively digital intervention. Future research should work to identify combinations of effective mental health interventions that provide equitable access for orthopedic patients.

TRIAL REGISTRATION

Not applicable.

Evaluating a Digital Mental Health Intervention (Wysa) for Workers' Compensation Claimants: Pilot Feasibility Study

OBJECTIVE

This study examines the feasibility and acceptability of an AI-led digital mental health intervention in a Workers' Compensation (WC) program, Wysa for Return to Work.

METHODS

Self-reported demographic data and responses to psychosocial screening questions were analyzed alongside participants' app usage through which four key outcomes were measured: recruitment rate, onboarding rate, retention, and engagement.

RESULTS

The data demonstrated a high need for psychosocial interventions among injured workers, especially women, young adults, and those with high severity injuries. Those with more psychosocial risk factors had a higher rate of onboarding, retention, and engagement, and those with severe injuries had higher retention.

CONCLUSIONS

Our study concluded that Wysa for Return to Work, the AI-led digital mental health intervention that delivers a recovery program using a digital conversational agent, is feasible and acceptable for a return-to-work population.

Multi-stakeholder perspectives regarding preferred modalities for mental health intervention delivered in the orthopedic clinic: A qualitative analysis

BACKGROUND

Although depressive and anxious symptoms negatively impact musculoskeletal health and orthopedic outcomes, a gap remains in identifying modalities through which mental health intervention can realistically be delivered during orthopedic care. The purpose of this study was to understand orthopedic stakeholders' perspectives regarding the feasibility, acceptability, and usability of digital, printed, and in-person intervention modalities to address mental health as part of orthopedic care.

METHODS

This single-center, qualitative study was conducted within the orthopedic department of a tertiary care center. Semi-structured interviews were conducted between January and May 2022. Two stakeholder groups were interviewed using a purposive sampling approach until thematic saturation was reached. The first group included adult orthopedic patients who presented for management of ≥ 3 months of neck or back pain. The second group included early, mid, and late career orthopedic clinicians and support staff members. Stakeholders' interview responses were analyzed using deductive and inductive coding approaches followed by thematic analysis. Patients also performed usability testing of one digital and one printed mental health intervention.

RESULTS

Patients included 30 adults out of 85 approached (mean (SD) age 59 (14) years, 21 (70%) women, 12 (40%) non-White). Clinical team stakeholders included 22 orthopedic clinicians and support staff members out of 25 approached (11 (50%) women, 6 (27%) non-White). Clinical team members perceived a digital mental health intervention to be feasible and scalable to implement, and many patients appreciated that the digital modality offered privacy, immediate access to resources, and the ability to engage during non-business hours. However, stakeholders also expressed that a printed mental health resource is still necessary to meet the needs of patients who prefer and/or can only engage with tangible, rather than digital, mental health resources. Many clinical team members expressed skepticism regarding the current feasibility of scalably incorporating in-person mental health support into orthopedic care.

CONCLUSIONS

Although digital intervention offers implementation-related advantages over printed and in-person mental health interventions, a subset of often underserved patients will not currently be reached using exclusively digital intervention. Future research should work to identify combinations of effective mental health interventions that provide equitable access for orthopedic patients.

TRIAL REGISTRATION

Not applicable.

Understanding Digital Mental Health Needs and Usage With an Artificial Intelligence-Led Mental Health App (Wysa) During the COVID-19 Pandemic: Retrospective Analysis

BACKGROUND

There has been a surge in mental health concerns during the COVID-19 pandemic, which has prompted the increased use of digital platforms. However, there is little known about the mental health needs and behaviors of the global population during the pandemic. This study aims to fill this knowledge gap through the analysis of real-world data collected from users of a digital mental health app (Wysa) regarding their engagement patterns and behaviors, as shown by their usage of the service.

OBJECTIVE

This study aims to (1) examine the relationship between mental health distress, digital health uptake, and COVID-19 case numbers; (2) evaluate engagement patterns with the app during the study period; and (3) examine the efficacy of the app in improving mental health outcomes for its users during the pandemic.

METHODS

This study used a retrospective observational design. During the COVID-19 pandemic, the app's installations and emotional utterances were measured from March 2020 to October 2021 for the United Kingdom, the United States of America, and India and were mapped against COVID-19 case numbers and their peaks. The engagement of the users from this period (N=4541) with the Wysa app was compared to that of equivalent samples of users from a pre-COVID-19 period (1000 iterations). The efficacy was assessed for users who completed pre-post assessments for symptoms of depression (n=2061) and anxiety (n=1995) on the Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7) test measures, respectively.

RESULTS

Our findings demonstrate a significant positive correlation between the increase in the number of installs of the Wysa mental health app and the peaks of COVID-19 case numbers in the United Kingdom (P=.02) and India (P<.001). Findings indicate that users (N=4541) during the COVID period had a significantly higher engagement than the samples from the pre-COVID period, with a medium to large effect size for 80% of these 1000 iterative samples, as observed on the Mann-Whitney test. The PHQ-9 and GAD-7 pre-post assessments indicated statistically significant improvement with a medium effect size (PHQ-9: P=.57; GAD-7: P=.56).

CONCLUSIONS

This study demonstrates that emotional distress increased substantially during the pandemic, prompting the increased uptake of an artificial intelligence-led mental health app (Wysa), and also offers evidence that the Wysa app could support its users and its usage could result in a significant reduction in symptoms of anxiety and depression. This study also highlights the importance of contextualizing interventions and suggests that digital health interventions can provide large populations with scalable and evidence-based support for mental health care.

Comparison of online and in-person cognitive behavioral therapy in individuals diagnosed with major depressive disorder: a non-randomized controlled trial

Objective

The increased prevalence of major depressive disorder (MDD) amid the COVID-19 pandemic has resulted in substantial growth in online mental health care delivery. Compared to its in-person counterpart, online cognitive behavioral therapy (e-CBT) is a time-flexible and cost-effective method of improving MDD symptoms. However, how its efficacy compares to in-person CBT is yet to be explored. Therefore, the current study compared the efficacy of a therapist-supported, electronically delivered e-CBT program to in-person therapy in individuals diagnosed with MDD.

Methods

Participants (n = 108) diagnosed with MDD selected either a 12 week in-person CBT or an asynchronous therapist-supported e-CBT program. E-CBT participants (n = 55) completed weekly interactive online modules delivered through a secure cloud-based online platform (Online Psychotherapy Tool; OPTT). These modules were followed by homework in which participants received personalized feedback from a trained therapist. Participants in the in-person CBT group (n = 53) discussed sessions and homework with their therapists during one-hour weekly meetings. Program efficacy was evaluated using clinically validated symptomatology and quality of life questionnaires.

Results

Both treatments yielded significant improvements in depressive symptoms and quality of life from baseline to post-treatment. Participants who opted for in-person therapy presented significantly higher baseline symptomatology scores than the e-CBT group. However, both treatments demonstrated comparable significant improvements in depressive symptoms and quality of life from baseline to post-treatment. e-CBT seems to afford higher participant compliance as dropouts in the e-CBT group completed more sessions on average than those in the in-person CBT group.

Conclusion

The findings support e-CBT with therapist guidance as a suitable option to treat MDD. Future studies should investigate how treatment accessibility is related to program completion rates in the e-CBT vs. in-person group.

Clinical Trial Registration

ClinicalTrials.Gov Protocol Registration and Results System (NCT04478058); clinicaltrials.gov/ct2/show/NCT04478058.

Adherence and Engagement with a Cognitive Behavioral Therapy Based Conversational Agent (Wysa) in Adults with Chronic Pain: Survival Analysis

BACKGROUND

Digital applications are commonly used to support mental health and well-being. However, successfully retaining and engaging users to complete digital interventions is challenging, and comorbidities such as chronic pain further reduce user engagement. Digital conversational agents may improve user engagement by applying engagement principles that have been implemented within in-person care settings.

OBJECTIVE

To evaluate user retention and engagement with an artificial intelligence (AI)-led digital mental health application (app) that is customized for individuals managing mental health symptoms and coexisting chronic pain (Wysa for Chronic Pain).

METHODS

In this ancillary survival analysis of a clinical trial, participants included 51 adults who presented to a tertiary care center for chronic musculoskeletal pain, who endorsed coexisting symptoms of depression and/or anxiety (PROMIS Depression and/or Anxiety score ≥ 55), and initiated onboarding to an 8-week subscription of Wysa for Chronic Pain. The study outcomes were user retention, defined as revisiting the app each week and the last day of engagement, and user engagement, defined by the number of sessions the user completed.

RESULTS

Users engaged in a cumulative mean of 33.3 sessions during the eight-week study period. The survival analysis depicted a median user retention period (i.e., time to complete disengagement) of 51 days, with the usage of a morning check-in feature statistically significant in its relationship with a longer retention period (p = .001).

CONCLUSIONS

Our findings suggest that the user retention and engagement with a CBT-based conversational agent which is built for users with chronic pain is higher than standard industry metrics. These results have clear implications for addressing issues of suboptimal engagement of digital health interventions and improving access to care for chronic pain. Future work should use these findings to inform the design of evidence-based interventions for individuals with chronic pain and to enhance user retention and engagement of digital health interventions more broadly.

CLINICALTRIAL

NCT04640090, Clinicaltrials.gov.

Delivery of a Mental Health Intervention for Chronic Pain Through an Artificial Intelligence-Enabled App (Wysa): Protocol for a Prospective Pilot Study

BACKGROUND

Patients with chronic pain often suffer from coexisting, long-term and debilitating mental health comorbidities such as depression and anxiety. Artificial Intelligence Supported Cognitive Behavioral Therapy or AI-CBT interventions could offer cost-effective, accessible, and potentially effective resources to tackle this problem. However, there is not enough research conducted about the efficacy of AI-CBT interventions for chronic pain.

OBJECTIVE

This prospective cohort study aims to examine the efficacy and usage of an AI-CBT intervention for chronic pain (Wysa for Chronic Pain app), using a conversational agent (with no human intervention). To the best of our knowledge, this is the first such study for chronic pain using a fully-automated, free-text-based conversational agent (CA).

METHODS

Participants with self-reported chronic pain (N = 500) will be recruited online on a rolling basis from April 2022 through posts on US-based internet communities within this prospective cohort. Informed consent is taken from the participants within the app and the Wysa intervention is delivered remotely for 8 weeks. Outcome measures including NPRS (Numeric Pain Rating Scale), PROMIS PI (Patient-Reported Outcomes Measurement Information System Pain Interference), GAD-7 (Generalized Anxiety Disorder), and PHQ-9 (Patient Health Questionnaire) questionnaires will be administered to test the effectiveness of the intervention on reducing levels of pain interference, depression, and anxiety. The therapeutic alliance created with the conversational agent will be assessed through the WAI-SR (Working Alliance Inventory-Short Revised). Retention and usage statistics will be observed for adherence and engagement.

RESULTS

The study will open for recruitment in April 2022 and data collection is expected to be completed by August 2022. The results for the primary outcomes are expected to be published by late-2022.

CONCLUSIONS

Mental health conversational agents driven by artificial intelligence (AI) could be effective in helping patients with chronic pain learn to self-manage their pain and deal with common comorbidities like depression and anxiety. The Wysa for Chronic Pain app is one such digital intervention that can potentially serve as a solution to the problems of affordability and scalability associated with interventions with a human therapist in loop. This prospective study examines the efficacy of the app as a treatment solution for chronic pain. It aims to inform future practices and digital mental health interventions for individuals with chronic pain.

CLINICALTRIAL

Digital Mental Health Intervention Plus Usual Care Compared to Usual Care Only and Usual Care Plus In-Person Psychological Counseling for Orthopedic Patients with Symptoms of Depression and/or Anxiety: Cohort Study (Preprint)

Background

Depression and anxiety frequently coexist with chronic musculoskeletal pain and can negatively impact patients’ responses to standard orthopedic treatments. Nevertheless, mental health is not routinely addressed in the orthopedic care setting. If effective, a digital mental health intervention may be a feasible and scalable method of addressing mental health in an orthopedic setting.

Objective

We aimed to compare 2-month changes in mental and physical health between orthopedic patients who received a digital mental health intervention in addition to usual orthopedic care, those who received usual orthopedic care only (without a specific mental health intervention), and those who received in-person care with a psychologist as part of their orthopedic treatment plan.

Methods

In this single-center retrospective cohort study involving ancillary analysis of a pilot feasibility study, 2-month self-reported health changes were compared between a cohort of orthopedic patients who received access to a digital mental health intervention (Wysa) and 2 convenience sample comparison cohorts (patients who received usual orthopedic care without a specific mental health intervention and patients who received in-person care with a psychologist as part of their orthopedic treatment plan). All patients were 18 years or older and reported elevated symptoms of depression or anxiety at an orthopedic clinic visit (Patient-Reported Outcomes Measurement Information System [PROMIS] Depression or Anxiety score ≥55). The digital intervention was a multi-component mobile app that used chatbot technology and text-based access to human counselors to provide cognitive behavioral therapy, mindfulness training, and sleep tools, among other features, with an emphasis on behavioral activation and pain acceptance. Outcomes of interest were between-cohort differences in the 2-month longitudinal changes in PROMIS Depression and Anxiety scores (primary outcomes) and PROMIS Pain Interference and Physical Function scores (secondary outcomes).

Results

Among 153 patients (mean age 55, SD 15 years; 128 [83.7%] female; 51 patients per cohort), patients who received the digital mental health intervention showed clinically meaningful improvements at the 2-month follow-up for all PROMIS measures (mean longitudinal improvement 2.8-3.7 points; P≤.02). After controlling for age and BMI, the improvements in PROMIS Depression, Pain Interference, and Physical Function were meaningfully greater than longitudinal changes shown by patients who received usual orthopedic care (mean between-group difference 2.6-4.8 points; P≤.04). Improvements in PROMIS Physical Function were also meaningfully greater than longitudinal changes shown by patients who received in-person psychological counseling (mean between-group difference 2.4 points; P=.04).

Conclusions

Patients who received a digital mental health intervention as part of orthopedic care reported greater 2-month mean improvements in depression, pain interference, and physical function than patients who received usual orthopedic care. They also reported a greater mean improvement in physical function and comparable improvements in depression, anxiety, and pain interference compared with orthopedic patients who received in-person psychological counseling.