A Digital Companion, the Emma App, for Ecological Momentary Assessment and Prevention of Suicide: Quantitative Case Series Study

Smartphone-based safety plan for suicidal crisis: The SmartCrisis 2.0 pilot study

Here we present the findings of the pilot phase of the SmartCrisis 2.0 Randomized Clinical Trial. This pilot study aimed to explore the feasibility and acceptability of a safety plan contained in a smartphone app. Our sample consisted patients with a history of recent suicidal behaviour who installed a smartphone-based safety plan. To explore the satisfaction with of the safety plan, two patient satisfaction surveys were conducted: one qualitative and one quantitative. To explore the objective use of the safety plan, we gained access to texts contained in the safety plans completed by the patients. Participation rate was 77%, while 48.9% patients completed both satisfaction surveys at the end of the pilot phase. N = 105 successfully installed the safety plan. In a scale from 1 to 10, users rated the usefulness of the security plan at 7.4, the usability at 8.9, the degree to which they would recommend it to others at 8.6 and the overall satisfaction with the project including evaluations at 9.6. The most widely completed tab was warning signs. Feeling sad or lonely was the warning sign most commonly reported by patients. The second most completed tab was internal coping strategies. Walking or practicing any other exercise was the strategy most commonly resorted to. Our smartphone-based safety plan appears to be a feasible intervention. Data obtained from this pilot study showed high participation rates and high acceptability by patients. This, together with the general satisfaction with the project, supports its implementation in the clinical practice.

Evaluation of the Rosa Chatbot Providing Genetic Information to Patients at Risk of Hereditary Breast and Ovarian Cancer: Qualitative Interview Study

BACKGROUND

Genetic testing has become an integrated part of health care for patients with breast or ovarian cancer, and the increasing demand for genetic testing is accompanied by an increasing need for easy access to reliable genetic information for patients. Therefore, we developed a chatbot app (Rosa) that is able to perform humanlike digital conversations about genetic BRCA testing.

OBJECTIVE

Before implementing this new information service in daily clinical practice, we wanted to explore 2 aspects of chatbot use: the perceived utility and trust in chatbot technology among healthy patients at risk of hereditary cancer and how interaction with a chatbot regarding sensitive information about hereditary cancer influences patients.

METHODS

Overall, 175 healthy individuals at risk of hereditary breast and ovarian cancer were invited to test the chatbot, Rosa, before and after genetic counseling. To secure a varied sample, participants were recruited from all cancer genetic clinics in Norway, and the selection was based on age, gender, and risk of having a BRCA pathogenic variant. Among the 34.9% (61/175) of participants who consented for individual interview, a selected subgroup (16/61, 26%) shared their experience through in-depth interviews via video. The semistructured interviews covered the following topics: usability, perceived usefulness, trust in the information received via the chatbot, how Rosa influenced the user, and thoughts about future use of digital tools in health care. The transcripts were analyzed using the stepwise-deductive inductive approach.

RESULTS

The overall finding was that the chatbot was very welcomed by the participants. They appreciated the 24/7 availability wherever they were and the possibility to use it to prepare for genetic counseling and to repeat and ask questions about what had been said afterward. As Rosa was created by health care professionals, they also valued the information they received as being medically correct. Rosa was referred to as being better than Google because it provided specific and reliable answers to their questions. The findings were summed up in 3 concepts: "Anytime, anywhere"; "In addition, not instead"; and "Trustworthy and true." All participants (16/16) denied increased worry after reading about genetic testing and hereditary breast and ovarian cancer in Rosa.

CONCLUSIONS

Our results indicate that a genetic information chatbot has the potential to contribute to easy access to uniform information for patients at risk of hereditary breast and ovarian cancer, regardless of geographical location. The 24/7 availability of quality-assured information, tailored to the specific situation, had a reassuring effect on our participants. It was consistent across concepts that Rosa was a tool for preparation and repetition; however, none of the participants (0/16) supported that Rosa could replace genetic counseling if hereditary cancer was confirmed. This indicates that a chatbot can be a well-suited digital companion to genetic counseling.

Identification of Risk Factors for Suicide and Insights for Developing Suicide Prevention Technologies: A Systematic Review and Meta-Analysis

Suicide is a termite that engulfs close to seven hundred thousand people worldwide each year. Existing work on risk factors that predict suicide lacks statistical associations, does not consider most countries, and has a wide range of risk factor domains. The goal of this systematic review and meta-analysis is to enhance our current understanding of suicidality by identifying risk factors that are most strongly associated with suicide and their impact on developing technological interventions for suicide prevention. A search strategy was carried out on four databases: (1) PsycINFO, (2) IEEE Xplore, (3) the ACM Digital Library, and (4) PubMed, and twenty-five studies were included based on the inclusion criteria. Factors statistically associated with suicide are any diagnosed mental disorder, adverse life events, past suicide attempts, low education level, loneliness or high levels of isolation, bipolar disorder, depression, multiple chronic health conditions, family history of suicide, sexual trauma, and being female. Domain-wise, comorbid disorders, and behavior-related risk factors are most strongly associated with suicide. We present a new hierarchical model of risk factors for suicide that advances our understanding of suicide and its causes. Finally, we present open research directions and considerations for developing suicide prevention technologies.

Examining clinician choice to follow-up (or not) on automated notifications of medication non-adherence by clinical decision support systems

BACKGROUND

Maintaining medication adherence can be challenging for people living with mental ill-health. Clinical decision support systems (CDSS) based on automated detection of problematic patterns in Electronic Health Records (EHRs) have the potential to enable early intervention into non-adherence events ("flags") through suggesting evidence-based courses of action. However, extant literature shows multiple barriers-perceived lack of benefit in following up low-risk cases, veracity of data, human-centric design concerns, etc.-to clinician follow-up in real-world settings. This study examined patterns in clinician decision making behaviour related to follow-up of non-adherence prompts within a community mental health clinic.

METHODS

The prompts for follow-up, and the recording of clinician responses, were enabled by CDSS software (AI²). De-identified clinician notes recorded after reviewing a prompt were analysed using a thematic synthesis approach-starting with descriptions of clinician comments, then sorting into analytical themes related to design and, in parallel, a priori categories describing follow-up behaviours. Hypotheses derived from the literature about the follow-up categories' relationships with client and medication-subtype characteristics were tested.

RESULTS

The majority of clients were Not Followed-up (n = 260; 78%; Followed-up: n = 71; 22%). The analytical themes emerging from the decision notes suggested contextual factors-the clients' environment, their clinical relationships, and medical needs-mediated how clinicians interacted with the CDSS flags. Significant differences were found between medication subtypes and follow-up, with Anti-depressants less likely to be followed up than Anti-Psychotics and Anxiolytics (χ² = 35.196, 44.825; p < 0.001; v = 0.389, 0.499); and between the time taken to action Followed-up₀ and Not-followed up₁ flags (M₀ = 31.78; M₁ = 45.55; U = 12,119; p < 0.001; η² = .05).

CONCLUSION

These analyses encourage actively incorporating the input of consumers and carers, non-EHR data streams, and better incorporation of data from parallel health systems and other clinicians into CDSS designs to encourage follow-up.

Preparing a Workforce of Care Coordinators to Address Patient Mental Health Needs in the Digital Age: Training and Needs Identification

Introduction

Care coordinators (CCs) are specialized healthcare providers and often the primary point of contact for patients with multiple medical and mental health comorbidities in integrated healthcare settings. Prior work shows CCs have lower comfort addressing mental health than physical health concerns. Digital mental health interventions can support CCs' management of patient mental health needs, but training gaps must be addressed prior to a digital mental health intervention's implementation.

Methods

As part of a quality improvement initiative, a 1-hour training focused on the assessment and management of depression and suicide-related thoughts and behaviors was delivered to CCs within a large midwestern healthcare system's Division of Ambulatory Care Coordination. CCs completed online surveys prior to and following the training.

Conclusion

Training resulted in increased comfort working with clinical populations, including patients who experience suicide-related thoughts and behaviors. Gains around screening for suicide risk were modest. Brief trainings for CCs can address training gaps, however, ongoing training and case consultation may also be indicated.

The Effectiveness of Mobile Apps for Monitoring and Management of Suicide Crisis: A Systematic Review of the Literature

Suicide risk is a multifaceted phenomenon, and many risk factors are involved in its complexity. In the last few decades, mental health apps have spread, providing economic and affordable strategies to prevent suicide. Therefore, the aim of this review is to identify original studies on mobile apps that target suicidal crises. The review follows PRISMA guidelines, searching through four major electronic databases (PubMed/MEDLINE, Scopus, PsycInfo and Web of Science) for relevant titles/abstracts published from January 2010 to May 2022. It includes original studies that explicitly analyze mobile apps for suicide prevention. A total of 32 studies met the inclusion criteria. Sixteen studies assessed the feasibility and acceptability of mobile apps, ten studies assessed the efficacy of mobile apps in preventing suicide, and six studies described randomized control trial protocols not yet implemented. Generally, the apps were judged by participants to be acceptable and helpful, and several improvements to enhance the functionality of apps were suggested. The efficacy of mobile apps, although limited and assessed with very heterogenous methods, was confirmed by most of the studies. Mobile apps could represent a helpful supplement to traditional prevention tactics, providing real-time monitoring of at-risk persons, personalized tools to cope with suicidal crises, and immediate access to specific support.

Smartphone-based Ecological Momentary Intervention for secondary prevention of suicidal thoughts and behaviour: protocol for the SmartCrisis V.2.0 randomised clinical trial

INTRODUCTION

Suicide is one of the leading public health issues worldwide. Mobile health can help us to combat suicide through monitoring and treatment. The SmartCrisis V.2.0 randomised clinical trial aims to evaluate the effectiveness of a smartphone-based Ecological Momentary Intervention to prevent suicidal thoughts and behaviour.

METHODS AND ANALYSIS

The SmartCrisis V.2.0 study is a randomised clinical trial with two parallel groups, conducted among patients with a history of suicidal behaviour treated at five sites in France and Spain. The intervention group will be monitored using Ecological Momentary Assessment (EMA) and will receive an Ecological Momentary Intervention called 'SmartSafe' in addition to their treatment as usual (TAU). TAU will consist of mental health follow-up of the patient (scheduled appointments with a psychiatrist) in an outpatient Suicide Prevention programme, with predetermined clinical appointments according to the Brief Intervention Contact recommendations (1, 2, 4, 7 and 11 weeks and 4, 6, 9 and 12 months). The control group would receive TAU and be monitored using EMA.

ETHICS AND DISSEMINATION

This study has been approved by the Ethics Committee of the University Hospital Fundación Jiménez Díaz. It is expected that, in the near future, our mobile health intervention and monitoring system can be implemented in routine clinical practice. Results will be disseminated through peer-reviewed journals and psychiatric congresses. Reference number EC005-21_FJD. Participants gave informed consent to participate in the study before taking part.

TRIAL REGISTRATION NUMBER

NCT04775160.

Digital tools for the assessment of pharmacological treatment for depressive disorder: State of the art

Depression is an invalidating disorder, marked by phenotypic heterogeneity. Clinical assessments for treatment adjustments and data-collection for pharmacological research often rely on subjective representations of functioning. Better phenotyping through digital applications may add unseen information and facilitate disentangling the clinical characteristics and impact of depression and its pharmacological treatment in everyday life. Researchers, physicians, and patients benefit from well-understood digital phenotyping approaches to assess the treatment efficacy and side-effects. This review discusses the current possibilities and pitfalls of wearables and technology for the assessment of the pharmacological treatment of depression. Their applications in the whole spectrum of treatment for depression, including diagnosis, treatment of an episode, and monitoring of relapse risk and prevention are discussed. Multiple aspects are to be considered, including concerns that come with collecting sensitive data and health recordings. Also, privacy and trust are addressed. Available applications range from questionnaire-like apps to objective assessment of behavioural patterns and promises in handling suicidality. Nonetheless, interpretation and integration of this high-resolution information with other phenotyping levels, remains challenging. This review provides a state-of-the-art description of wearables and technology in digital phenotyping for monitoring pharmacological treatment in depression, focusing on the challenges and opportunities of its application in clinical trials and research.

Boamente: A Natural Language Processing-Based Digital Phenotyping Tool for Smart Monitoring of Suicidal Ideation

People at risk of suicide tend to be isolated and cannot share their thoughts. For this reason, suicidal ideation monitoring becomes a hard task. Therefore, people at risk of suicide need to be monitored in a manner capable of identifying if and when they have a suicidal ideation, enabling professionals to perform timely interventions. This study aimed to develop the Boamente tool, a solution that collects textual data from users’ smartphones and identifies the existence of suicidal ideation. The solution has a virtual keyboard mobile application that passively collects user texts and sends them to a web platform to be processed. The platform classifies texts using natural language processing and a deep learning model to recognize suicidal ideation, and the results are presented to mental health professionals in dashboards. Text classification for sentiment analysis was implemented with different machine/deep learning algorithms. A validation study was conducted to identify the model with the best performance results. The BERTimbau Large model performed better, reaching a recall of 0.953 (accuracy: 0.955; precision: 0.961; F-score: 0.954; AUC: 0.954). The proposed tool demonstrated an ability to identify suicidal ideation from user texts, which enabled it to be experimented with in studies with professionals and their patients.

Suicide Prevention in Your Pocket: A Systematic Review of Ecological Momentary Interventions for the Management of Suicidal Thoughts and Behaviors

BACKGROUND

This study reviews the evidence on ecological momentary interventions (EMIs) for managing and preventing suicidal thoughts and behaviors.

METHODS

This review follows the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Its protocol was registered in the PROSPERO database. We conducted a systematic literature search of five databases: PubMed, EMBASE, Web of Science, PsycInfo, and Cochrane library. The most recent search date was 10 September 2021.

RESULTS

After screening and full-text review, 27 studies were included, totaling 19 different interventions. Many of the available interventions have not yet been clinically tested. Those that have undergone effectiveness evaluation (10 interventions) showed good rates of effectiveness and feasibility, with some exceptions. The most widely used intervention model is the safety plan, which allows the user to implement coping and distracting strategies in case of suicidal ideation.

CONCLUSIONS

Ecological momentary interventions provide certain advantages, such as their wide availability, versatility, and potential for customization. These interventions can be useful complements to traditional care, especially in situations in which face-to-face care is not possible. Evidence on the effectiveness of such interventions is still scarce. Furthermore, barriers limiting implementation in clinical practice remain. The constant advance of technology means that these interventions have great potential for improvement in the coming years.

Ecological momentary assessment of mental health in adults at suicide risk: An observational study protocol

AIMS

To describe the research protocol for an ecological momentary assessment (EMA) designed to examine patterns of suicidal ideation and relevant psychosocial stress indicators in adults at risk for suicide.

DESIGN

This observational and longitudinal study will collect data for 28 consecutive days.

METHODS

A total of 150 adults at risk for suicide will be recruited from a single suicide prevention centre and an outpatient clinic in Korea. Self-report questionnaires will be administrated during weeks 0, 1, 3 and 5. Participants will receive text messages three times a day for 4 weeks prompting them to access an online survey link for daily mood survey including depression, anxiety, stress and suicidal ideation. In addition, for the first 2 weeks, they will wear an actigraphy device designed to collect actigraphic data in terms of sleep patterns and physical activity. Data analyses such as descriptive statistics, independent t-tests, one-way ANOVA, chi-squared statistics and time-series and correlation analyses will be performed using IBM SPSS 26.0 and SAS version 9.3. The study received funding from National Research Foundation of Korea in February 2020. Institutional Review Board approval for our study was obtained in April 2021.

DISCUSSIONS

This study will yield fundamental information about daily patterns of suicide ideation and psychosocial stress indicators to develop preventive interventions for adults at risk for suicide.

IMPACT

Our study will contribute to the development of EMAs and interventions for adults at risk for suicide aimed at providing timely and individualized mental health services in a community setting.

TRIAL REGISTRATION

The trial is registered with the Clinical Research Information Service (CRIS). CRIS Registration Number: KCT0006165.

Acceptability and satisfaction with emma, a smartphone application dedicated to suicide ecological assessment and prevention

BACKGROUND

As mHealth may contribute to suicide prevention, we developed emma, an application using Ecological Momentary Assessment and Intervention (EMA/EMI).

OBJECTIVE

This study evaluated emma usage rate and acceptability during the first month and satisfaction after 1 and 6 months of use.

METHODS

Ninety-nine patients at high risk of suicide used emma for 6 months. The acceptability and usage rate of the EMA and EMI modules were monitored during the first month. Satisfaction was assessed by questions in the monthly EMA (Likert scale from 0 to 10) and the Mobile App Rating Scale (MARS; score: 0-5) completed at month 6. After inclusion, three follow-up visits (months 1, 3, and 6) took place.

RESULTS

Seventy-five patients completed at least one of the proposed EMAs. Completion rates were lower for the daily than weekly EMAs (60 and 82%, respectively). The daily completion rates varied according to the question position in the questionnaire (lower for the last questions, LRT = 604.26, df = 1, p-value < 0.0001). Completion rates for the daily EMA were higher in patients with suicidal ideation and/or depression than in those without. The most used EMI was the emergency call module (n = 12). Many users said that they would recommend this application (mean satisfaction score of 6.92 ± 2.78) and the MARS score at month 6 was relatively high (overall rating: 3.3 ± 0.87).

CONCLUSION

Emma can target and involve patients at high risk of suicide. Given the promising users' satisfaction level, emma could rapidly evolve into a complementary tool for suicide prevention.

SIMON: A Digital Protocol to Monitor and Predict Suicidal Ideation

Each year, more than 800,000 persons die by suicide, making it a leading cause of death worldwide. Recent innovations in information and communication technology may offer new opportunities in suicide prevention in individuals, hereby potentially reducing this number. In our project, we design digital indices based on both self-reports and passive mobile sensing and test their ability to predict suicidal ideation, a major predictor for suicide, and psychiatric hospital readmission in high-risk individuals: psychiatric patients after discharge who were admitted in the context of suicidal ideation or a suicidal attempt, or expressed suicidal ideations during their intake. Specifically, two smartphone applications -one for self-reports (SIMON-SELF) and one for passive mobile sensing (SIMON-SENSE)- are installed on participants' smartphones. SIMON-SELF uses a text-based chatbot, called Simon, to guide participants along the study protocol and to ask participants questions about suicidal ideation and relevant other psychological variables five times a day. These self-report data are collected for four consecutive weeks after study participants are discharged from the hospital. SIMON-SENSE collects behavioral variables -such as physical activity, location, and social connectedness- parallel to the first application. We aim to include 100 patients over 12 months to test whether (1) implementation of the digital protocol in such a high-risk population is feasible, and (2) if suicidal ideation and psychiatric hospital readmission can be predicted using a combination of psychological indices and passive sensor information. To this end, a predictive algorithm for suicidal ideation and psychiatric hospital readmission using various learning algorithms (e.g., random forest and support vector machines) and multilevel models will be constructed. Data collected on the basis of psychological theory and digital phenotyping may, in the future and based on our results, help reach vulnerable individuals early and provide links to just-in-time and cost-effective interventions or establish prompt mental health service contact. The current effort may thus lead to saving lives and significantly reduce economic impact by decreasing inpatient treatment and days lost to inability.

Ecological momentary interventions for mental health: A scoping review

BACKGROUND

The development of mobile computing technology has enabled the delivery of psychological interventions while people go about their everyday lives. The original visions of the potential of these "ecological momentary interventions" were presented over a decade ago, and the widespread adoption of smartphones in the intervening years has led to a variety of research studies exploring the feasibility of these aspirations. However, there is a dearth of research describing the different dimensions, characteristics, and features of these interventions, as constructed.

OBJECTIVE

To provide an overview of the definitions given for "ecological momentary interventions" in the treatment of common mental health disorders, and describe the set of technological and interaction possibilities which have been used in the design of these interventions.

METHODS

A systematic search identified relevant literature published between 2009 and 2020 in the PubMed, PsycInfo, and ACM Guide to the Computing Literature databases. Following screening, data were extracted from eligible articles using a standardized extraction worksheet. Selected articles were then thematically categorized.

RESULTS

The search identified 583 articles of which 64 met the inclusion criteria. The interventions target a range of mental health problems, with diverse aims, intervention designs and evaluation approaches. The studies employed a variety of features for intervention delivery, but recent research is overwhelmingly comprised of studies based on smartphone apps (30 of 42 papers that described an intervention). Twenty two studies employed sensors for the collection of data in order to provide just-in-time support or predict psychological states.

CONCLUSIONS

With the shift towards smartphone apps, the vision for EMIs has begun to be realised. Recent years have seen increased exploration of the use of sensors and machine learning, but the role of humans in the delivery of EMI is also varied. The variety of capabilities exhibited by EMIs motivates development of a more precise vocabulary for capturing both automatic and human tailoring of these interventions.

[Let's be more ambitious in treating suicide]

Suicide is a major public health problem. It becomes necessary and essential to identify persons at risk and to offer them an appropriate care. Entry in the DSM 5 of suicidal behavior (SB) as a disease to study is a first step in its recognition as an independent disease with its own physiopathology. Long time considered as a consequence or as a symptom of others psychiatric diseases, there is actually no specific treatment of SB. Nevertheless, new ways of understanding of mechanisms underlying SB are emerging and could consequently lead to find new specific therapeutics. Understanding the role played by psychological pain in SB seems to be a good approach to decipher the physiopathology of SB. Furthermore, we are witnessing the emergence of potential specific therapeutics such as ketamine that has shown promising results in treating SB.