Feasibility of combining spatial computing and AI for mental health support in anxiety and depression.
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ABSTRACT:
SUBMITTER: Spiegel BMR
PROVIDER: S-EPMC10817913 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Feasibility of combining spatial computing and AI for mental health support in anxiety and depression.
Spiegel Brennan M R BMR Liran Omer O Clark Allistair A Samaan Jamil S JS Khalil Carine C Chernoff Robert R Reddy Kavya K Mehra Muskaan M
NPJ digital medicine 20240126 1
The increasing need for mental health support and a shortage of therapists have led to the development of the eXtended-reality Artificial Intelligence Assistant (XAIA). This platform combines spatial computing, virtual reality (VR), and artificial intelligence (AI) to provide immersive mental health support. Utilizing GPT-4 for AI-driven therapy, XAIA engaged participants with mild-to-moderate anxiety or depression in biophilic VR environments. Speaking with an AI therapy avatar in VR was consid ...[more]
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Project description:BackgroundRecent advancements in artificial intelligence (AI) have changed the care processes in mental health, particularly in decision-making support for health care professionals and individuals with mental health problems. AI systems provide support in several domains of mental health, including early detection, diagnostics, treatment, and self-care. The use of AI systems in care flows faces several challenges in relation to decision-making support, stemming from technology, end-user, and organizational perspectives with the AI disruption of care processes.ObjectiveThis study aims to explore the use of AI systems in mental health to support decision-making, focusing on 3 key areas: the characteristics of research on AI systems in mental health; the current applications, decisions, end users, and user flow of AI systems to support decision-making; and the evaluation of AI systems for the implementation of decision-making support, including elements influencing the long-term use.MethodsA scoping review of empirical evidence was conducted across 5 databases: PubMed, Scopus, PsycINFO, Web of Science, and CINAHL. The searches were restricted to peer-reviewed articles published in English after 2011. The initial screening at the title and abstract level was conducted by 2 reviewers, followed by full-text screening based on the inclusion criteria. Data were then charted and prepared for data analysis.ResultsOf a total of 1217 articles, 12 (0.99%) met the inclusion criteria. These studies predominantly originated from high-income countries. The AI systems were used in health care, self-care, and hybrid care contexts, addressing a variety of mental health problems. Three types of AI systems were identified in terms of decision-making support: diagnostic and predictive AI, treatment selection AI, and self-help AI. The dynamics of the type of end-user interaction and system design were diverse in complexity for the integration and use of the AI systems to support decision-making in care processes. The evaluation of the use of AI systems highlighted several challenges impacting the implementation and functionality of the AI systems in care processes, including factors affecting accuracy, increase of demand, trustworthiness, patient-physician communication, and engagement with the AI systems.ConclusionsThe design, development, and implementation of AI systems to support decision-making present substantial challenges for the sustainable use of this technology in care processes. The empirical evidence shows that the evaluation of the use of AI systems in mental health is still in its early stages, with need for more empirically focused research on real-world use. The key aspects requiring further investigation include the evaluation of the use of AI-supported decision-making from human-AI interaction and human-computer interaction perspectives, longitudinal implementation studies of AI systems in mental health to assess the use, and the integration of shared decision-making in AI systems.
| S-EPMC11806275 | biostudies-literature
Project description:BackgroundThe increasing prevalence of artificial intelligence (AI)-driven mental health conversational agents necessitates a comprehensive understanding of user engagement and user perceptions of this technology. This study aims to fill the existing knowledge gap by focusing on Wysa, a commercially available mobile conversational agent designed to provide personalized mental health support.MethodsA total of 159 user reviews posted between January, 2020 and March, 2024, on the Wysa app's Google Play page were collected. Thematic analysis was then used to perform open and inductive coding of the collected data.ResultsSeven major themes emerged from the user reviews: "a trusting environment promotes wellbeing", "ubiquitous access offers real-time support", "AI limitations detract from the user experience", "perceived effectiveness of Wysa", "desire for cohesive and predictable interactions", "humanness in AI is welcomed", and "the need for improvements in the user interface". These themes highlight both the benefits and limitations of the AI-driven mental health conversational agents.ConclusionsUsers find that Wysa is effective in fostering a strong connection with its users, encouraging them to engage with the app and take positive steps towards emotional resilience and self-improvement. However, its AI needs several improvements to enhance user experience with the application. The findings contribute to the design and implementation of more effective, ethical, and user-aligned AI-driven mental health support systems.
| S-EPMC11304096 | biostudies-literature
Project description:IntroductionMost people suffering from depression and anxiety disorders are entirely treated in primary care. Due to growing challenges in ageing societies, for example, patients' immobility and multimorbidity, the transition to specialised care becomes increasingly difficult. Although the co-location of general practitioners and mental health specialists improves the access to psychosocial care, integrated in-person approaches are not practical for rural and single-doctor practices with limited personnel and financial resources. Treating primary care patients via internet-based video consultations by remotely located mental health specialists bears the potential to overcome structural barriers and provide low-threshold care. The aim of this randomised controlled feasibility trial is to investigate the feasibility of implementing of mental health specialist video consultations in primary care practices.Methods and analysisFifty primary care patients with significant depression and/or anxiety symptomatology will be randomised in two groups receiving either the treatment as usual as provided by their general practitioner or up to five video consultations conducted by a mental health specialist. The video consultations focus on (1) systematic diagnosis plus proactive monitoring using validated clinical rating scales, (2) the establishment of an effective working alliance and (3) a stepped-care algorithm within integrated care adjusting treatments based on clinical outcomes. We will investigate the following outcomes: effectiveness of the recruitment strategies, patient acceptance of randomisation, practicability of the technical and logistical processes related to implementing video consultations in the practices' workflows, feasibility of the data collection and clinical parameters.Ethics and disseminationThis trial has undergone ethical scrutiny and has been approved by the Medical Faculty of the University of Heidelberg Ethics Committee (S-634/2018). The findings will be disseminated to the research community through presentations at conferences and publications in scientific journals. This feasibility trial will prepare the ground for a large-scale, fully powered randomised controlled trial.Trial registration numberDRKS00015812.
| S-EPMC6731787 | biostudies-literature
Project description:BackgroundSymptoms of depression and anxiety commonly coexist with chronic musculoskeletal pain, and when this occurs, standard orthopedic treatment is less effective. However, mental health intervention is not yet a routine part of standard orthopedic treatment, in part because of access-related barriers. Digital mental health intervention is a potential scalable resource that could be feasibly incorporated into orthopedic care.ObjectiveThis study's primary purpose was to assess the feasibility of introducing a digital mental health intervention (Wysa) in an outpatient orthopedic setting to patients with coexisting symptoms of depression and/or anxiety. The secondary purpose was to perform a preliminary effectiveness analysis of the intervention.MethodsIn this single-arm, prospective cohort study, participants included adult patients (18 years and older) who presented to a nonsurgical orthopedic specialist at a single tertiary care academic center for evaluation of a musculoskeletal condition and who self-reported symptoms of depression and/or anxiety (Patient-Reported Outcomes Measurement Information System [PROMIS] Depression and/or Anxiety score ≥55). Face-to-face enrollment was performed by a research coordinator immediately after the participant's encounter with an orthopedic clinician. Participants were provided 2 months of access to a mobile app called Wysa, which is an established, multicomponent digital mental health intervention that uses chatbot technology and text-based access to human counselors to deliver cognitive behavioral therapy, mindfulness training, and sleep tools, among other features. For this study, Wysa access also included novel, behavioral activation-based features specifically developed for users with chronic pain. Primary feasibility outcomes included the study recruitment rate, retention rate, and engagement rate with Wysa (defined as engagement with a therapeutic Wysa tool at least once during the study period). Secondary effectiveness outcomes were between-group differences in mean longitudinal PROMIS mental and physical health score changes at 2-month follow-up between high and low Wysa users, defined by a median split.ResultsThe recruitment rate was 29.3% (61/208), retention rate was 84% (51/61), and engagement rate was 72% (44/61). Compared to low users, high users reported greater improvement in PROMIS Anxiety scores (between-group difference -4.2 points, 95% CI -8.1 to -0.2; P=.04) at the 2-month follow-up. Between-group differences in PROMIS Depression (-3.2 points, 95% CI -7.5 to 1.2; P=.15) and Pain Interference scores (-2.3 points, 95% CI -6.3 to 1.7; P=.26) favored high users but did not meet statistical significance. Improvements in PROMIS Physical Function scores were comparable between groups.ConclusionsDelivery of a digital mental health intervention within the context of orthopedic care is feasible and has the potential to improve mental health and pain-related impairment to a clinically meaningful degree. Participants' engagement rates exceeded industry standards, and additional opportunities to improve recruitment and retention were identified. Further pilot study followed by a definitive, randomized controlled trial is warranted.Trial registrationClinicalTrials.gov NCT04640090; https://clinicaltrials.gov/ct2/show/NCT04640090.
| S-EPMC8902664 | biostudies-literature
Project description:BackgroundMental health workers are subject to high levels of occupational stress which is associated with poorer health and wellbeing and impaired patient outcomes. For individuals operating in high stress environments, reducing challenge at home, in particular around parenting, has been found to generalize into improvements in the professional domain. The present study sought to investigate the effectiveness and feasibility of brief targeted workplace intervention to support workers in terms of their parental role.Design/methodologyAn uncontrolled evaluation of a series of three-session parenting-focused courses delivered to employees of a large Mental Health Trust. A pre-post-follow-up design was used to investigate effects on outcomes including parenting practice and experience, wellbeing, stress, and occupational self-efficacy. Intervention feasibility and acceptably was also evaluated.FindingsData from 15 participants who completed measures pre-post indicates the courses were associated with improved parenting practice and experience at a p < 0.005 level. Improvements were reported at 6-month follow up. Participant satisfaction and course acceptability was highly rated by 100% of participants.
| S-EPMC9262046 | biostudies-literature
Project description:BackgroundMost people affected by depression or anxiety disorders are treated solely by their primary care physician. Access to specialized mental health care is impeded by patients' comorbidity and immobility in aging societies and long waiting times at the providers' end. Video-based integrated care models may leverage limited resources more efficiently and provide timely specialized care in primary care settings.ObjectiveThe study aims to evaluate the feasibility of mental health specialist video consultations with primary care patients with depression or anxiety disorders.MethodsParticipants were recruited by their primary care physicians during regular practice visits. Patients who had experienced at least moderate symptoms of depression and/or anxiety disorders were considered eligible for the study. Patients were randomized into 2 groups receiving either treatment-as-usual as provided by their general practitioner or up to 5 video consultations conducted by a mental health specialist. Video consultations focused on systematic diagnosis and proactive monitoring using validated clinical rating scales, the establishment of an effective working alliance, and a stepped-care algorithm within integrated care adjusting treatments based on clinical outcomes. Feasibility outcomes were recruitment, rate of loss to follow-up, acceptability of treatment, and attendance at sessions. Effectiveness outcomes included depression (Patient Health Questionnaire-9), anxiety (Generalized Anxiety Disorder-7), burden of specific somatic complaints (Somatic Symptom Disorder-B Criteria Scale-12), recovery (Recovery Assessment Scale-German [RAS-G]), and perception of chronic illness care (Patient Assessment of Chronic Illness Care), which were measured at baseline and 16 weeks postallocation by assessors blinded to the group allocation.ResultsA total of 50 patients with depression and/or anxiety disorders were randomized, 23 in the intervention group and 27 in the treatment-as-usual group. The recruitment yield (number randomized per number screened) and the consent rate (number randomized per number eligible) were 69% (50/73) and 86% (50/58), respectively. Regarding acceptability, 87% (20/23) of the participants in the intervention group completed the intervention. Of the 108 planned video consultations, 102 (94.4%) were delivered. Follow-up rates were 96% (22/23) and 85% (23/27) for the intervention and control groups, respectively. The change from baseline scores at postmeasurement for the No Domination by Symptoms domain of recovery (RAS-G) was somewhat higher in the intervention group than in the control group (Mann-Whitney U test: rank-biserial r=0.19; 95% CI -0.09 to 0.46; P=.18). We did not detect any notable differences between the intervention and control groups in terms of other effectiveness outcomes. We did not observe any serious adverse events related to the trial.ConclusionsThe intervention and study procedures were found to be feasible for patients, primary care practice staff, and mental health specialists. A sufficiently powered pragmatic trial on mental health specialist video consultations should be conducted to investigate their effectiveness in routine care.Trial registrationGerman Clinical Trials Register DRKS00015812; https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00015812.
| S-EPMC7998325 | biostudies-literature
Project description:Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory lung disease characterized by progressive and only partially reversible symptoms. Worldwide, the incidence of COPD presents a disturbing continuous increase. Anxiety and depression are remarkably common in COPD patients, but the evidence about optimal approaches for managing psychological comorbidities in COPD remains unclear and largely speculative. Pharmacological treatment based on selective serotonin reuptake inhibitors has almost replaced tricyclic antidepressants. The main psychological intervention is cognitive behavioral therapy. Of particular interest are pulmonary rehabilitation programs, which can reduce anxiety and depressive symptoms in these patients. Although the literature on treating anxiety and depression in patients with COPD is limited, we believe that it points to the implementation of personalized strategies to address their psychopathological comorbidities.
| S-EPMC4755471 | biostudies-literature
Project description: Not available
| S-EPMC11352929 | biostudies-literature
Project description:BackgroundRates of perinatal depression and anxiety increased during the COVID-19 pandemic. It remains unclear how the COVID-19 pandemic influenced risk perception and help-seeking behaviours among pregnant and postpartum individuals.ObjectivesTo explore pregnant and postpartum individuals' decision-making process about when and how to seek support for feelings of depression and/or anxiety during the COVID-19 pandemic.DesignA qualitative descriptive design was used.MethodsThe current study is a secondary analysis of qualitative data collected for a larger mixed-methods project that recruited participants who gave birth from 1 May 2020, to 1 December 2021, in Ontario and British Columbia, Canada, using maximum variation and purposive sampling. Seventy-three semi-structured interviews were conducted over Zoom or telephone. This analysis focuses on 56 individuals who discussed their self-identified feelings of prenatal or postpartum depression and/or anxiety. Conventional (inductive) content analysis was employed with iterative stages of open coding, focused coding and cross-checking themes.ResultsMost participants recognized their need to seek help for their feelings of depression and/or anxiety through discussions with a mental health professional or someone within their social circle. Nearly all participants accessed informal social support for these feelings, which sometimes entailed social contact in contravention of local COVID-19 public health policies. Many also attempted to access formal mental healthcare, encountering barriers both related and unrelated to the pandemic. Participants described the pandemic as having the dual effect of causing or exacerbating their feelings of depression and/or anxiety while also constraining their ability to access timely professional care.ConclusionParticipants struggled to address their feelings of perinatal depression and anxiety during the COVID-19 pandemic, with many describing a lack of readily available resources and limited access to professional mental healthcare. This study highlights the need for improved provision of instrumental mental health support for pregnant and postpartum populations.
| S-EPMC11439165 | biostudies-literature
Project description:BackgroundArtificial intelligence (AI) has been increasingly recognized as a potential solution to address mental health service challenges by automating tasks and providing new forms of support.ObjectiveThis study is the first in a series which aims to estimate the current rates of AI technology use as well as perceived benefits, harms, and risks experienced by community members (CMs) and mental health professionals (MHPs).MethodsThis study involved 2 web-based surveys conducted in Australia. The surveys collected data on demographics, technology comfort, attitudes toward AI, specific AI use cases, and experiences of benefits and harms from AI use. Descriptive statistics were calculated, and thematic analysis of open-ended responses were conducted.ResultsThe final sample consisted of 107 CMs and 86 MHPs. General attitudes toward AI varied, with CMs reporting neutral and MHPs reporting more positive attitudes. Regarding AI usage, 28% (30/108) of CMs used AI, primarily for quick support (18/30, 60%) and as a personal therapist (14/30, 47%). Among MHPs, 43% (37/86) used AI; mostly for research (24/37, 65%) and report writing (20/37, 54%). While the majority found AI to be generally beneficial (23/30, 77% of CMs and 34/37, 92% of MHPs), specific harms and concerns were experienced by 47% (14/30) of CMs and 51% (19/37) of MHPs. There was an equal mix of positive and negative sentiment toward the future of AI in mental health care in open feedback.ConclusionsCommercial AI tools are increasingly being used by CMs and MHPs. Respondents believe AI will offer future advantages for mental health care in terms of accessibility, cost reduction, personalization, and work efficiency. However, they were equally concerned about reducing human connection, ethics, privacy and regulation, medical errors, potential for misuse, and data security. Despite the immense potential, integration into mental health systems must be approached with caution, addressing legal and ethical concerns while developing safeguards to mitigate potential harms. Future surveys are planned to track use and acceptability of AI and associated issues over time.
| S-EPMC11488652 | biostudies-literature