B·RIGHT: usability and satisfaction with a mobile app for self-managing emotional crises in patients with borderline personality disorder

Examining the role of AI technology in online mental healthcare: opportunities, challenges, and implications, a mixed-methods review

Introduction

Online mental healthcare has gained significant attention due to its effectiveness, accessibility, and scalability in the management of mental health symptoms. Despite these advantages over traditional in-person formats, including higher availability and accessibility, issues with low treatment adherence and high dropout rates persist. Artificial intelligence (AI) technologies could help address these issues, through powerful predictive models, language analysis, and intelligent dialogue with users, however the study of these applications remains underexplored. The following mixed methods review aimed to supplement this gap by synthesizing the available evidence on the applications of AI in online mental healthcare.

Method

We searched the following databases: MEDLINE, CINAHL, PsycINFO, EMBASE, and Cochrane. This review included peer-reviewed randomized controlled trials, observational studies, non-randomized experimental studies, and case studies that were selected using the PRISMA guidelines. Data regarding pre and post-intervention outcomes and AI applications were extracted and analyzed. A mixed-methods approach encompassing meta-analysis and network meta-analysis was used to analyze pre and post-intervention outcomes, including main effects, depression, anxiety, and study dropouts. We applied the Cochrane risk of bias tool and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) to assess the quality of the evidence.

Results

Twenty-nine studies were included revealing a variety of AI applications including triage, psychotherapy delivery, treatment monitoring, therapy engagement support, identification of effective therapy features, and prediction of treatment response, dropout, and adherence. AI-delivered self-guided interventions demonstrated medium to large effects on managing mental health symptoms, with dropout rates comparable to non-AI interventions. The quality of the data was low to very low.

Discussion

The review supported the use of AI in enhancing treatment response, adherence, and improvements in online mental healthcare. Nevertheless, given the low quality of the available evidence, this study highlighted the need for additional robust and high-powered studies in this emerging field.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=443575, identifier CRD42023443575.

Artificial Intelligence-Based Consumer Health Informatics Application: Scoping Review

BACKGROUND

There is no doubt that the recent surge in artificial intelligence (AI) research will change the trajectory of next-generation health care, making it more approachable and accessible to patients. Therefore, it is critical to research patient perceptions and outcomes because this trend will allow patients to be the primary consumers of health technology and decision makers for their own health.

OBJECTIVE

This study aimed to review and analyze papers on AI-based consumer health informatics (CHI) for successful future patient-centered care.

METHODS

We searched for all peer-reviewed papers in PubMed published in English before July 2022. Research on an AI-based CHI tool or system that reports patient outcomes or perceptions was identified for the scoping review.

RESULTS

We identified 20 papers that met our inclusion criteria. The eligible studies were summarized and discussed with respect to the role of the AI-based CHI system, patient outcomes, and patient perceptions. The AI-based CHI systems identified included systems in mobile health (13/20, 65%), robotics (5/20, 25%), and telemedicine (2/20, 10%). All the systems aimed to provide patients with personalized health care. Patient outcomes and perceptions across various clinical disciplines were discussed, demonstrating the potential of an AI-based CHI system to benefit patients.

CONCLUSIONS

This scoping review showed the trend in AI-based CHI systems and their impact on patient outcomes as well as patients' perceptions of these systems. Future studies should also explore how clinicians and health care professionals perceive these consumer-based systems and integrate them into the overall workflow.

A systematic review and meta-analysis of digital interventions targeted at individuals with borderline personality disorder (BPD), emotionally unstable personality disorder (EUPD), and related symptoms

OBJECTIVES

The present review investigates the impact of digital interventions for individuals with features of borderline personality disorder (BPD)/emotional unstable personality disorder (EUPD) as digital interventions show promise as therapeutic tools in underserved groups. BPD/EUPD features are identified as clinically relevant, yet previous reviews on the use of digital interventions fail to include subthreshold symptomatology.

METHODS

Five online databases were searched for terminology in three categories: BPD/EUPD and related symptoms, mental-health interventions, and digital technology. Additionally, four relevant journals and two trial registers were searched for additional papers meeting the inclusion criteria.

RESULTS

Twelve articles met all inclusion criteria. Meta-analyses revealed statistically significant differences in symptom measures between intervention and control groups at postintervention and decreases in BPD/EUPD symptomatology and well-being from pre- to postintervention. Service users' engagement, satisfaction, and acceptability of interventions were high. Results support the previous literature on the value of using digital interventions in populations with BPD/EUPD.

CONCLUSION

Overall, it was identified that digital interventions show promise for successful implementation with this population.

A Systematic Review of Mobile Apps as an Adjunct to Psychological Interventions for Emotion Dysregulation

BACKGROUND

Mental health care has been enriched with the progressive use of technology during the last ten years, in particular after the COVID-19 pandemic. Mobile applications (apps) and smartphones have become the most widespread access point for many people who look for self-help in the psychological domain.

OBJECTIVE

We focused on a systematic review of mobile apps for mental health, focusing on the blending of apps with psychotherapy contexts, with a specific focus on emotional dysregulation.

METHODS

A comprehensive literature search (January 2017 to August 2022) in PubMed, PsycInfo, Web of Science, and the Cochrane Library was conducted. Abstracts were included if they described mental health mobile apps targeting emotional dysregulation and their use during ongoing psychological or psychotherapy treatment for adults and adolescents.

RESULTS

In total, 397 abstracts were identified; of these, 19 publications describing apps targeting borderline personality disorder, depression, anxiety, suicidal behaviors, and post-traumatic stress disorders met the inclusion criteria.

CONCLUSIONS

App-enhanced psychotherapy might be a winning combination in many scenarios, but at the same time, many issues must still be faced in this yet emerging scientific field. In conclusion, we tried to put together some major guidelines for mental health mobile app development in the context of psychological treatments.

The Use of Computer-Driven Technologies in the Treatment of Borderline Personality Disorder: A Systematic Review

The objective of this study was to perform a systematic review of the effectiveness of computer-driven technologies for treatment of patients suffering from BPD. A systematic literature review was conducted using the Pubmed, EMBASE, PsycNET (PsycINFO), CINAHL and Google Scholar electronic databases for the period from their inception dates until 2022. Thirty studies were selected for abstract screening. Seven studies were excluded for not meeting inclusion criteria. The remaining 23 studies were fully assessed, and 12 were excluded. Therefore, 11 studies were included in the analysis of the effectiveness of computer-driven technologies, which encompassed mobile applications, telehealth interventions, internet-based interventions, virtual reality MBT and dialogue-based integrated interventions. Computer-driven interventions are showing signs of effectiveness in the treatment of BPD symptoms. The limited number of articles found on the subject demonstrates a need for further exploration of this subject.

User perceptions of mobile digital apps for mental health: Acceptability and usability - An integrative review

WHAT IS KNOWN ON THE SUBJECT?: Mobile mental health apps are increasingly being used by both mental health nurses to promote individual self-managemental of mental health conditions and by consumers. Perceptions about specific apps are known, but the overarching acceptability and usability of mental health apps in general less understood. WHAT THE PAPER ADDS TO EXISTING KNOWLEDGE?: This paper identified consumer perceptions of mobile mental health apps. Six key areas were identified that future mobile app developers should consider to maximize consumer engagement with mental health apps. Consumers also highlighted that apps do not replace traditional mental health nursing-rather these supplement existing care. WHAT ARE THE IMPLICATIONS FOR PRACTICE?: This review found that mental health apps are generally viewed positively by consumers; however, factors such as ease of use, usefulness of content and privacy need to be considered to maximise and sustain app engagement. ABSTRACT: Introduction There is increasing interest in the use of mobile mental health applications (apps) to manage mental health conditions. Understanding user perceptions is key to maximise app engagement and inform how apps can be used to support mental health nursing care. Aim This integrative review explores consumers' perceptions of mobile mental health apps to gain insight into user preferences and acceptability. Methods This integrative review was based on searching four databases: CINAHL, EMBASE, Medline, PsycInfo. Inclusion criteria were: (i) articles published after 2000; (ii) focused on apps for mental health disorders; (iii) explored consumers' perception of using a mental health app. Abstracts were screened and eligible papers reviewed. Data on user perceptions were extracted and analysed thematically. Results Seventeen articles were identified. Overall, consumers did not feel that app use replaced traditional health care. Six themes were identified: "Helpfulness," "Improvements/enhancements," "Technical issues," "Easy to use," "Satisfaction with the app" and "Perceived issues." Consumers indicated a preference for personalization for the app to meet individual needs. Discussion and Implications for Practice Mental health apps are generally viewed positively by consumers; however, factors such as ease of use, usefulness of content and privacy need to be considered to maximise and sustain app engagement.

E-Mental Health for People with Personality Disorders: A Systematic Review

PURPOSE OF REVIEW

Provision of mental health services through digital technologies (e-mental health) can potentially expand access to treatments for personality disorders (PDs). We evaluated studies on e-mental health for PDs published over the last 3 years (2019-2022).

RECENT FINDINGS

Studies published in English that used e-mental health to treat people with PDs or PD-related symptoms were identified. We identified 19 studies, including four randomized controlled trials and one meta-analysis. Most interventions were based on Dialectical Behavior Therapy and delivered through smartphone applications for adults with Borderline Personality Disorder [BPD] or related symptoms. User experiences of the interventions were generally positive. Evidence for efficacy was limited. The current literature on e-mental health for PDs is limited in scope. Research in understudied populations and randomized controlled trials designed to establish efficacy are warranted. It is not yet clear whether e-mental health may be helpful for the treatment of PDs.