A Mobile Sensing App to Monitor Youth Mental Health: A Feasibility Study (Preprint)

2020 ◽  
Author(s):  
Banuchitra Suruliraj ◽  
Dominik Gall ◽  
Lucy MacLeod ◽  
Kitti Bessenyei ◽  
Alexa Bagnell ◽  
...  
Keyword(s):  
Mental Health ◽  
Clinical Decision Making ◽  
Clinical Care ◽  
Active Role ◽  
Clinical Decision ◽  
Mobile Sensing ◽  
Clinical Monitoring ◽  
Health States ◽  
Clinical Symptomatology ◽  
Prediction Tools

BACKGROUND Current methods of predicting mental health crises usually rely on subjective symptom ratings obtained at discrete time points during routine clinical care. But clinical decision-making based on such subjective information is challenging, as changes in symptoms might be sub-threshold, context dependent, or variable over time. Therefore, novel prediction tools need to be developed meeting the highest standards of reliability, feasibility, scalability, and affordability. Smartphones might configure such prediction tools, as they are ubiquitous and afford a wide variety of types of behavioural data that can be automatically recorded by their built-in sensors. OBJECTIVE To facilitate the collection of high-quality, passive mobile sensing data, we built the Predicting Risk and Outcomes of Social InTeractions (PROSIT) tool, a mobile sensing app that runs on both Android and iOS operating systems. In addition we aimed to ensure the acceptability and usability of this tool in youth. METHODS The PROSIT tool captures multiple indices of a youth’s daily life behaviors via their naturalistic use of a smartphone. These indices include physical activity, geolocation, sleep, phone use, typed text, music choice, and acoustic vocal quality. Importantly, the PROSIT tool records most of these data passively with only minimal burden to youth. All the time-intensive, detail-rich data streams that the tool captures to make inferences about youth’s mental health states are encrypted and uploaded to a secure server at our clinic. Although other mobile data collection tools exist, the PROSIT tool places a unique emphasis on the designing the tool for youth. RESULTS In a pilot study (N=61), participants tolerated the PROSIT tool well, reporting only minimal burden. Over 85% of youth were using the tool for the whole study period, although they were suffering from severe clinical symptomatology. But not only youth accepted the PROSIT tool well, for youth under the age of 15 we requested consent of parents, which 80% of parents provided. CONCLUSIONS The PROSIT tool offers novel way for clinical monitoring in youth with mental disorder. The high acceptability rates indicate that mobile sensing technologies can successfully be used even in youth with severe clinical symptomatology. We built the PROSIT tool to assist in clinical monitoring, with the ultimate goal of leveraging individual big data to empower youth patients to take on a more active role in the management of their clinical symptomatology.

scholarly journals Artificial Intelligence: An Interprofessional Perspective on Implications for Geriatric Mental Health Research and Care

2021 ◽  
Vol 12 ◽  
Author(s):  
Brenna N. Renn ◽  
Matthew Schurr ◽  
Oleg Zaslavsky ◽  
Abhishek Pratap
Keyword(s):  
Mental Health ◽  
Artificial Intelligence ◽  
Clinical Practice ◽  
Data Science ◽  
Clinical Decision Making ◽  
Clinical Care ◽  
Clinical Status ◽  
Clinical Decision ◽  
Mental Health Research ◽  
Geriatric Mental Health

Artificial intelligence (AI) in healthcare aims to learn patterns in large multimodal datasets within and across individuals. These patterns may either improve understanding of current clinical status or predict a future outcome. AI holds the potential to revolutionize geriatric mental health care and research by supporting diagnosis, treatment, and clinical decision-making. However, much of this momentum is driven by data and computer scientists and engineers and runs the risk of being disconnected from pragmatic issues in clinical practice. This interprofessional perspective bridges the experiences of clinical scientists and data science. We provide a brief overview of AI with the main focus on possible applications and challenges of using AI-based approaches for research and clinical care in geriatric mental health. We suggest future AI applications in geriatric mental health consider pragmatic considerations of clinical practice, methodological differences between data and clinical science, and address issues of ethics, privacy, and trust.

Transitioning towards official clinical guidelines for the diagnostics and treatment of severe behavioural problems in children across Europe: current state and future directions.

2017 ◽  
Author(s):  
Alexandra-Raluca Gatej ◽  
Audri Lamers ◽  
Robert Vermeiren ◽  
Lieke van Domburgh
Keyword(s):  
Mental Health ◽  
Clinical Guidelines ◽  
Clinical Decision Making ◽  
Daily Practice ◽  
Clinical Decision ◽  
European Guidelines ◽  
Current State ◽  
Assessment And Treatment ◽  
Evidence Based Treatments ◽  
Multifactorial Approach

Severe behaviour problems (SBPs) in early childhood include oppositional and aggressive behaviours and predict negative mental health outcomes later in life. Although effective treatments for this group are available and numerous clinical practice guidelines have been developed to facilitate the incorporation of evidence-based treatments in clinical decision-making (NICE, 2013), many children with SBPs remain unresponsive to treatment (Lahey & Waldman, 2012). At present, it is unknown how many countries in Europe possess official clinical guidelines for SBPs diagnosis and treatment and what is their perceived utility. The aim was to create an inventory of clinical guidelines (and associated critical needs) for the diagnostics and treatment of SBPs in youth mental health across Europe according to academic experts and mental health clinicians’ opinions. To investigate the aim, two separate online semi-structured questionnaires were used, one directed at academics (N=28 academic experts; 23 countries), and the other at clinicians (N=124 clinicians; 24 countries). Three key results were highlighted. First, guidelines for SBPs are perceived as beneficial by both experts and clinicians. However, their implementation needs to be reinforced and content better adapted to daily practice. Improvements may include taking a multifactorial approach to assessment and treatment, involving the systems around the child, and multidisciplinary collaboration. Second, academic experts and clinicians support the need for further developing national / European guidelines. Finally, future guidelines should address current challenges identified by clinicians to be more applicable to daily practice.

scholarly journals Correction to: Using behavioral insights to design implementation strategies in public mental health settings: a qualitative study of clinical decision-making

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Briana S. Last ◽  
Simone H. Schriger ◽  
Carter E. Timon ◽  
Hannah E. Frank ◽  
Alison M. Buttenheim ◽  
...  
Keyword(s):  
Mental Health ◽  
Decision Making ◽  
Qualitative Study ◽  
Clinical Decision Making ◽  
Public Mental Health ◽  
Implementation Strategies ◽  
Clinical Decision ◽  
Mental Health Settings

An amendment to this paper has been published and can be accessed via the original article.

scholarly journals An evidence-based approach to routine outcome assessment

2012 ◽  
Vol 18 (3) ◽  
pp. 180-182 ◽  
Author(s):  
Mike Slade
Keyword(s):  
Mental Health ◽  
Mental Health Services ◽  
Health Services ◽  
Clinical Decision Making ◽  
Academic Discipline ◽  
Community Mental Health Services ◽  
Clinical Decision ◽  
Successful Implementation ◽  
Frontline Workers ◽  
Routine Outcome Assessment

SummaryRoutine use of Health of the Nation Outcome Scales (HoNOS) has not produced the anticipated benefits for people using mental health services. Four HoNOS-specific reasons for this are: low relevance to clinical decision-making; not reflecting service user priorities; being staff-rated; and having a focus on deficits. More generally, the imposition of a centrally chosen measure on the mental health system leads to a clash of cultures, since frontline workers do not need a standardised measure to treat individuals. A better approach might be to use research from the emerging academic discipline of implementation science to inform the routine use of a standardised measure that is chosen by the people who will use it and hence is more concordant with existing clinical processes. This is illustrated using a case study of successful implementation of the Camberwell Assessment of Need (CAN) in community mental health services across Ontario, Canada.

scholarly journals Storytelling, Safeguarding, Treatment, and Responsibility: attributes of recovery in psychiatric intensive care units

2014 ◽  
Vol 11 (02) ◽  
pp. 105-118 ◽  
Author(s):  
Karleen Gwinner ◽  
Louise Ward
Keyword(s):  
Mental Health ◽  
Decision Making ◽  
Mental Illness ◽  
Intensive Care ◽  
Lived Experience ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Review Of Literature ◽  
Psychiatric Distress ◽  
Nurse Knowledge

AbstractBackground and aimIn recent years, policy in Australia has endorsed recovery-oriented mental health services underpinned by the needs, rights and values of people with lived experience of mental illness. This paper critically reviews the idea of recovery as understood by nurses at the frontline of services for people experiencing acute psychiatric distress.MethodData gathered from focus groups held with nurses from two hospitals were used to ascertain their use of terminology, understanding of attributes and current practices that support recovery for people experiencing acute psychiatric distress. A review of literature further examined current nurse-based evidence and nurse knowledge of recovery approaches specific to psychiatric intensive care settings.ResultsFour defining attributes of recovery based on nurses’ perspectives are shared to identify and describe strategies that may help underpin recovery specific to psychiatric intensive care settings.ConclusionThe four attributes described in this paper provide a pragmatic framework with which nurses can reinforce their clinical decision-making and negotiate the dynamic and often incongruous challenges they experience to embed recovery-oriented culture in acute psychiatric settings.

scholarly journals Probability and loss: two sides of the risk assessment coin

2011 ◽  
Vol 35 (11) ◽  
pp. 413-418 ◽  
Author(s):  
Matthew M. Large ◽  
Olav B. Nielssen
Keyword(s):  
Mental Health ◽  
Risk Assessment ◽  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
The Other ◽  
Current Form ◽  
Mental Health Settings ◽  
Future Harm ◽  
Two Sides

SummaryRisk assessment has been widely adopted in mental health settings in the hope of preventing harms such as violence to others and suicide. However, risk assessment in its current form is mainly concerned with the probability of adverse events, and does not address the other component of risk – the extent of the resulting loss. Although assessments of the probability of future harm based on actuarial instruments are generally more accurate than the categorisations made by clinicians, actuarial instruments are of little assistance in clinical decision-making because there is no instrument that can estimate the probability of all the harms associated with mental illness, or estimate the extent of the resulting losses. The inability of instruments to distinguish between the risk of common but less serious harms and comparatively rare catastrophic events is a particular limitation of the value of risk categorisations. We should admit that our ability to assess risk is severely limited, and make clinical decisions in a similar way to those in other areas of medicine – by informed consideration of the potential consequences of treatment and non-treatment.

scholarly journals Integrating Patient-Generated Health Data Into Clinical Care Settings or Clinical Decision-Making: Lessons Learned From Project HealthDesign

2016 ◽  
Vol 3 (2) ◽  
pp. e26 ◽  
Author(s):  
Deborah J Cohen ◽  
Sara R Keller ◽  
Gillian R Hayes ◽  
David A Dorr ◽  
Joan S Ash ◽  
...  
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Care ◽  
Clinical Decision ◽  
Health Data ◽  
Lessons Learned

scholarly journals ACADEMIA’S ROLE TO DRIVE CHANGE IN THE ORTHOTICS AND PROSTHETICS PROFESSION

2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Géza Kogler ◽  
Christopher Hovorka
Keyword(s):  
Technology Use ◽  
Clinical Training ◽  
Clinical Decision Making ◽  
New Technologies ◽  
Clinical Care ◽  
Clinical Decision ◽  
The United States ◽  
Academic Program ◽  
Number Of Patients ◽  
Curricular Emphasis

This position paper outlines the important role of academia in shaping the orthotics and prosthetics (O&P) profession and preparing for its future. In the United States, most healthcare professions including O&P are under intense pressure to provide cost effective treatments and quantifiable health outcomes. Pivotal changes are needed in the way O&P services are provided to remain competitive. This will require the integration of new technologies and data driven processes that have the potential to streamline workflows, reduce errors and inform new methods of clinical care and device manufacturing. Academia can lead this change, starting with a restructuring in academic program curricula that will enable the next generation of professionals to cope with multiple demands such as the provision of services for an increasing number of patients by a relatively small workforce of certified practitioners delivering these services at a reduced cost, with the expectation of significant, meaningful, and measurable value. Key curricular changes will require replacing traditional labor-intensive and inefficient fabrication methods with the integration of newer technologies (i.e., digital shape capture, digital modeling/rectification and additive manufacturing). Improving manufacturing efficiencies will allow greater curricular emphasis on clinical training and education – an area that has traditionally been underemphasized. Providing more curricular emphasis on holistic patient care approaches that utilize systematic and evidence-based methods in patient assessment, treatment planning, dosage of O&P technology use, and measurement of patient outcomes is imminent. Strengthening O&P professionals’ clinical decision-making skills and decreasing labor-intensive technical fabrication aspects of the curriculum will be critical in moving toward a digital and technology-centric practice model that will enable future practitioners to adapt and survive. Article PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/36673/28349 How To Cite: Kogler GF, Hovorka CF. Academia’s role to drive change in the orthotics and prosthetics profession. Canadian Prosthetics & Orthotics Journal. 2021; Volume 4, Issue 2, No.21. https://doi.org/10.33137/cpoj.v4i2.36673 Corresponding Author: Géza F. KoglerOrthotics and Prosthetics Unit, Kennesaw State University.E-Mail: [email protected] ID: https://orcid.org/0000-0003-0212-5520

Mental Health Clinical Decision Support Exploiting Big Data

2019 ◽  
pp. 160-184 ◽  
Author(s):  
Jan Kalina
Keyword(s):  
Mental Health ◽  
Decision Making ◽  
Big Data ◽  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Clinical Decision Making ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision

The complexity of clinical decision-making is immensely increasing with the advent of big data with a clinical relevance. Clinical decision systems represent useful e-health tools applicable to various tasks within the clinical decision-making process. This chapter is devoted to basic principles of clinical decision support systems and their benefits for healthcare and patient safety. Big data is crucial input for clinical decision support systems and is helpful in the task to find the diagnosis, prognosis, and therapy. Statistical challenges of analyzing big data in psychiatry are overviewed, with a particular interest for psychiatry. Various barriers preventing telemedicine tools from expanding to the field of mental health are discussed. The development of decision support systems is claimed here to play a key role in the development of information-based medicine, particularly in psychiatry. Information technology will be ultimately able to combine various information sources including big data to present and enforce a holistic information-based approach to psychiatric care.

Clinical outcome assessment in mental health

2018 ◽  
pp. 191-200
Author(s):  
Skye P. Barbic ◽  
Stefan J. Cano
Keyword(s):  
Mental Health ◽  
Decision Making ◽  
Clinical Outcome ◽  
Outcome Assessment ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Evidence Based ◽  
Measurement Issues ◽  
Health Disorders ◽  
Based Medicine

Clinical outcome assessment (COA) in mental health is essential to inform patient-centred care and clinical decision-making. In this chapter, the reader is introduced to COA as it is evolving in the field of mental health. Multiple approaches to COA are presented, but emphasis is placed on approaches that generate clinically meaningful data. Understanding COA can position clinicians and stakeholders to better evaluate their own practice and to contribute to the ongoing evolution of COA research and evidence-based medicine. This chapter begins with the definitions of assessment and measurement. Conceptual frameworks and models of COA development and testing are then presented. These are followed by a discussion of measurement in practice that reviews measurement issues related to clinical decision-making, programme evaluation, and clinical trials. Finally, this chapter highlights the contribution of metrology to improving health outcomes of individuals who experience mental health disorders.

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