Measurement in an on-demand virtual mental health system: a review and viewpoint (Preprint)

2020 ◽  
Author(s):  
Sarah Kunkle ◽  
John A Naslund ◽  
Justin Hunt ◽  
Dana Udall ◽  
Erica Hayes ◽  
...  
Keyword(s):  
Mental Health ◽  
Data Science ◽  
New Technologies ◽  
Digital Health ◽  
Clinical Care ◽  
The United States ◽  
On Demand ◽  
Measurement Based Care ◽  
Multidisciplinary Perspective ◽  
Development And Management

UNSTRUCTURED Mental health is a growing public health priority in the United States and globally. Measurement-based care (MBC) has been shown to improve outcomes in clinical care, yet there are significant challenges to implementation. New technologies offer opportunities to address these obstacles and to measure new and existing constructs at a scale that was previously not possible. This paper aims to summarize existing literature on MBC, focusing on mental health and digital health. Specifically, we describe a case example called Ginger, a novel on-demand virtual system for delivering mental health services, and demonstrate how this platform aligns with core principles of MBC in mental health based on existing frameworks and findings from the literature. Additionally, we integrate feedback from multidisciplinary stakeholders (clinical practitioners, data science, product development and management, and research) to develop a perspective on key tenets of measurement in this system. To navigate the challenges of translating traditional measurement tools into new technologies in addition to developing new measurements, this multidisciplinary perspective is required. Ultimately, this will enhance our understanding of mental health and ability to develop interventions to improve outcomes.

Epidemiology of Technology Use and Mental Health in the United States

2020 ◽  
pp. 41-56
Author(s):  
Seth W. Whiting ◽  
Rani A. Hoff
Keyword(s):  
Mental Health ◽  
United States ◽  
Technology Use ◽  
New Technologies ◽  
Role Playing ◽  
The United States ◽  
Mass Scale ◽  
Online Gambling ◽  
Health Issues ◽  
Mental Health Issues

Advancements in technologies and their mass-scale adoption throughout the United States create rapid changes in how people interact with the environment and each other and how they live and work. As technologies become commonplace in society through increased availability and affordability, several problems may emerge, including disparate use among groups, which creates divides in attainment of the beneficial aspects of a technology’s use and coinciding mental health issues. This chapter briefly overviews new technologies and associated emerging applications in information communication technologies, social media networks, video games and massively multiplayer online role-playing games, and online gambling, then examines the prevalence of use among the general population and its subgroups and further discusses potential links between mental health issues associated with each technology and implications of overuse.

scholarly journals VitalSign6: A Primary Care First (PCP-First) Model for Universal Screening and Measurement-Based Care for Depression

2019 ◽  
Vol 12 (2) ◽  
pp. 71 ◽  
Author(s):  
Madhukar Trivedi ◽  
Manish Jha ◽  
Farra Kahalnik ◽  
Ronny Pipes ◽  
Sara Levinson ◽  
...  
Keyword(s):  
Mental Health ◽  
Primary Care ◽  
Mental Health Professionals ◽  
Health Professionals ◽  
Universal Screening ◽  
Primary Care Providers ◽  
The United States ◽  
Care Providers ◽  
Similar Treatment ◽  
Measurement Based Care

Major depressive disorder affects one in five adults in the United States. While practice guidelines recommend universal screening for depression in primary care settings, clinical outcomes suffer in the absence of optimal models to manage those who screen positive for depression. The current practice of employing additional mental health professionals perpetuates the assumption that primary care providers (PCP) cannot effectively manage depression, which is not feasible, due to the added costs and shortage of mental health professionals. We have extended our previous work, which demonstrated similar treatment outcomes for depression in primary care and psychiatric settings, using measurement-based care (MBC) by developing a model, called Primary Care First (PCP-First), that empowers PCPs to effectively manage depression in their patients. This model incorporates health information technology tools, through an electronic health records (EHR) integrated web-application and facilitates the following five components: (1) Screening (2) diagnosis (3) treatment selection (4) treatment implementation and (5) treatment revision. We have implemented this model as part of a quality improvement project, called VitalSign6, and will measure its success using the Reach, Efficacy, Adoption, Implementation, and Maintenance (RE-AIM) framework. In this report, we provide the background and rationale of the PCP-First model and the operationalization of VitalSign6 project.

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

The Digital Revolution in Behavioral Health

2019 ◽  
Vol 26 (1) ◽  
pp. 102-111 ◽  
Author(s):  
Michael J Hasselberg
Keyword(s):  
Mental Health ◽  
Health Care ◽  
Mental Health Care ◽  
Behavioral Health ◽  
Digital Health ◽  
Behavioral Health Care ◽  
The United States ◽  
Care Providers ◽  
Digital Revolution ◽  
The University

BACKGROUND: Technology is disrupting every modern industry, from supermarkets to car manufacturing, and is now entering the health care space. Technological innovations in psychiatry include the opportunity for conducting therapy via two-way video conferencing, providing electronic consultations, and telementoring and education of community health care providers. Use of mobile health applications is also an expanding area of interest and promise. OBJECTIVE: The purpose of this article is to review the evolution and pros and cons of technology-enabled health care since the digital movement in psychiatry began more than 50 years ago as well as describe the University of Rochester’s innovative digital behavioral health care model. METHODS: A review of the literature and recent reports on innovations in digital behavioral health care was conducted, along with a review of the University of Rochester’s model to describe the current state of digital behavioral health care. RESULTS: Given the lack of access to care and mental health professional shortages in many parts of the United States, particularly rural areas, digital behavioral health care will be an increasingly important strategy for managing mental health care needs. However, there are numerous hurdles to be overcome in adopting digital health care, including provider resistance and knowledge gaps, lack of reimbursement parity, restrictive credentialing and privileging, and overregulation at both the state and federal levels. CONCLUSIONS: Digital health innovations are transforming the delivery of mental health care services and psychiatric mental health nurses can be on the forefront of this important digital revolution.

scholarly journals What do clinicians want? Understanding frontline addiction treatment clinicians’ preferences and priorities to improve the design of measurement-based care technology

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Justin S. Tauscher ◽  
Eliza B. Cohn ◽  
Tascha R. Johnson ◽  
Kaylie D. Diteman ◽  
Richard K. Ries ◽  
...  
Keyword(s):  
Addiction Treatment ◽  
Clinical Decision Making ◽  
New Technologies ◽  
Clinical Care ◽  
Ease Of Use ◽  
Sorting Task ◽  
Multiple Use ◽  
Card Sorting ◽  
Measurement Based Care ◽  
Treatment Settings

Abstract Background Measurement-based care (MBC) is the practice of routinely administering standardized measures to support clinical decision-making and monitor treatment progress. Despite evidence of its effectiveness, MBC is rarely adopted in routine substance use disorder (SUD) treatment settings and little is known about the factors that may improve its adoptability in these settings. The current study gathered qualitative data from SUD treatment clinicians about their perceptions of MBC, the clinical outcomes they would most like to monitor in MBC, and suggestions for the design and implementation of MBC systems in their settings. Methods Fifteen clinicians from one publicly-funded and two privately-funded outpatient SUD treatment clinics participated in one-on-one research interviews. Interviews focused on clinicians’ perceived benefits, drawbacks, and ideas related to implementing MBC technology into their clinical workflows. Interviews were audio recorded, transcribed, and coded to allow for thematic analysis using a mixed deductive and inductive approach. Clinicians also completed a card sorting task to rate the perceived helpfulness of routinely measuring and monitoring different treatment outcomes. Results Clinicians reported several potential benefits of MBC, including improved patient-provider communication, client empowerment, and improved communication between clinicians. Clinicians also expressed potential drawbacks, including concerns about subjectivity in patient self-reports, limits to personalization, increased time burdens, and needing to learn to use new technologies. Clinicians generated several ideas and preferences aimed at minimizing burden of MBC, illustrating clinical changes over time, improving ease of use, and improving personalization. Numerous patient outcomes were identified as “very helpful” to track, including coping skills, social support, and motivation for change. Conclusions MBC may be a beneficial tool for improving clinical care in SUD treatment settings. MBC tools may be particularly adoptable if they are compatible with existing workflows, help illustrate gradual and nonlinear progress in SUD treatment, measure outcomes perceived as clinically useful, accommodate multiple use cases and stakeholder groups, and are framed as an additional source of information meant to augment, rather than replace, existing practices and information sources.

scholarly journals Cross cultural and global uses of a digital mental health app: results of focus groups with clinicians, patients and family members in India and the United States

2021 ◽  
Vol 8 ◽  
Author(s):  
Elena Rodriguez-Villa ◽  
Abhijit R. Rozatkar ◽  
Mohit Kumar ◽  
Vikram Patel ◽  
Ameya Bondre ◽  
...  
Keyword(s):  
Mental Health ◽  
United States ◽  
Focus Groups ◽  
Digital Health ◽  
Phase 1 ◽  
Family Members ◽  
The United States ◽  
Mental Illnesses ◽  
Human Interaction ◽  
Specific Feedback

Abstract Background Despite significant advancements in healthcare technology, digital health solutions – especially those for serious mental illnesses – continue to fall short of their potential across both clinical practice and efficacy. The utility and impact of medicine, including digital medicine, hinges on relationships, trust, and engagement, particularly in the field of mental health. This paper details results from Phase 1 of a two-part study that seeks to engage people with schizophrenia, their family members, and clinicians in co-designing a digital mental health platform for use across different cultures and contexts in the United States and India. Methods Each site interviewed a mix of clinicians, patients, and their family members in focus groups (n = 20) of two to six participants. Open-ended questions and discussions inquired about their own smartphone use and, after a demonstration of the mindLAMP platform, specific feedback on the app's utility, design, and functionality. Results Our results based on thematic analysis indicate three common themes: increased use and interest in technology during coronavirus disease 2019 (COVID-19), concerns over how data are used and shared, and a desire for concurrent human interaction to support app engagement. Conclusion People with schizophrenia, their family members, and clinicians are open to integrating technology into treatment to better understand their condition and help inform treatment. However, app engagement is dependent on technology that is complementary – not substitutive – of therapeutic care from a clinician.

Characteristic Latent Features for Analyzing Digital Mental Health Interaction and Improved Explainability (Preprint)

2021 ◽  
Author(s):  
Max-Marcel Theilig ◽  
Ashley A Knapp ◽  
Jennifer M Nicholas ◽  
Rüdiger Zarnekow ◽  
David C Mohr
Keyword(s):  
Mental Health ◽  
Data Science ◽  
Digital Health ◽  
A Priori ◽  
User Interaction ◽  
User Engagement ◽  
Behavioral Strategies ◽  
Data Set ◽  
Public Data ◽  
Latent Features

BACKGROUND Using mobile health technology has sparked a broad engagement of data science and machine learning methods to leverage the complex, assorted amount of data for mental health purposes. Despite many studies, there is a reported underdevelopment of user engagement concepts, and the desire for high accuracy or significance has shown to lead to low explicability and irreproducibility. OBJECTIVE To overcome such reasons of poor analysis input and facilitate the reproducibility and credibility of artificial intelligence applications, we aim to explore principal characteristics of user interaction with digital mental health. METHODS We generated five latent features based on previous research, expert opinions from digital mental health, and informed by data. The features were analyzed with descriptive statistics and data visualization. We carried out two rounds of evaluations with data from 12,400 users of IntelliCare, a mental health platform with 12 apps. First, we focused to proof concept and second, we assessed reproducibility by drawing conclusion from distribution differences. User data was drawn from both research trials and public deployment on Google Play. RESULTS Our algorithms showed advantages over commonly used concepts and reproduce in our public data set with different underlying behavioral strategies. These measures relate to the distribution of a user’s allocated attention, users’ circadian behavior, their consecutive commitment to a specific strategy, and users’ interaction trajectory. Because distributions between research trial and public deployment were similar, consistency was implied regarding the underlying behavioral strategies: psychoeducation and goal setting are used as a catalyst to overcome the users’ primary obstacles, sleep hygiene is addressed most regularly, while regular self-reflective thinking is avoided. Relaxation as well as cognitive reframing have increased variance in commitment among public users, indicating the challenging nature of these apps. The relative course of users’ engagement is similar in research and public data. CONCLUSIONS We argue that deliberate, a-priori feature engineering is essential for reproducible, tangible, and explainable study analyses. Our features enable improved results as well as interpretability, providing an increased understanding of how people engage with multiple mental health apps over time. Since we based the generation of features on generic interaction, these methods are applicable to further methods of study analysis and digital health.

scholarly journals The COVID Pandemic and Surgical Innovation in the United States

2021 ◽  
pp. 155335062110053
Author(s):  
Toby Gordon
Keyword(s):  
New Product Development ◽  
Success Factors ◽  
New Technologies ◽  
Clinical Care ◽  
Insurance Coverage ◽  
The United States ◽  
Product Development Process ◽  
Surgical Innovation ◽  
Regulatory Review ◽  
Corporate Funding

The SARS-COVID-2019 pandemic of 2020 severely weakened the surgical innovation pipeline and ecosystem, primarily due to factors that include lack of a coordinated federal response, weakened health insurance coverage, a politicized approach to public health and safety, and disruption of the US economy. A successful bench to bedside innovation requires trust in the scientific research, open research and clinical facilities, and participation of patients in clinical studies. In addition, stay-at-home orders and the shutdown of elective medical and surgical care and research laboratories diminished opportunities for the informal interactions that are part of the new product development process. The pandemic and how it was managed prolonged the length of time for creation, adoption, and diffusion of new products and services into the market. Furthermore, the loss of hospital revenues from canceled elective care translates into a much smaller market for new technologies. Looking forward, critical success factors for innovation include federal policy that supports science and offers access and insurance coverage for health care, including addressing social determinants of health. Any further shutdowns of research and clinical care will hinder necessary collaborations between scientists, clinicians, and patients. Economic recovery is required to ensure federal and corporate funding for research and development. Trust in science must be restored to ensure support of necessary regulatory review processes and sufficient participation in clinical trials. Surgical discoveries have brought about lifesaving and life-extending cures, and the pipeline of these discoveries must continue without interruption.

scholarly journals “It’s all about delivery”: researchers and health professionals’ views on the moral challenges of accessing neurobiological information in the context of psychosis

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Paolo Corsico
Keyword(s):  
Mental Health ◽  
Health Care ◽  
Mental Health Professionals ◽  
Health Professionals ◽  
Data Science ◽  
Clinical Care ◽  
Moral Obligations ◽  
Individual Interviews ◽  
Health Care Intervention ◽  
Registration Number

Abstract Background The convergence of neuroscience, genomics, and data science holds promise to unveil the neurobiology of psychosis and to produce new ways of preventing, diagnosing, and treating psychotic illness. Yet, moral challenges arise in neurobiological research and in the clinical translation of research findings. This article investigates the views of relevant actors in mental health on the moral challenges of accessing neurobiological information in the context of psychosis. Methods Semi-structured individual interviews with two groups: researchers employed in the National Health Service (NHS) or a university in England (n = 14), and mental health professionals employed in NHS mental health services (n = 14). This article compares results in the two groups (total n = 28). Results This article presents findings around three conceptual areas: (1) research ethics as mostly unproblematic, (2) psychosis, neurobiological information, and mental health care, and (3) identity, relationships, and the future. These areas are drawn from the themes and topics that emerged in the interviews across the two groups of participants. Researchers and health professionals provided similar accounts of the moral challenges of accessing—which includes acquisition, communication, and use of—neurobiological information in the context of psychosis. Acquiring neurobiological information was perceived as mostly unproblematic, provided ethical safeguards are put in place. Conversely, participants argued that substantive moral challenges arise from how neurobiological information is delivered—that is, communicated and used—in research and in clinical care. Neurobiological information was seen as a powerful tool in the process through which individuals define their identity and establish personal and clinical goals. The pervasiveness of this narrative tool may influence researchers and health professionals’ perception of ethical principles and moral obligations. Conclusions This study suggests that the moral challenges that arise from accessing neurobiological information in the context of psychosis go beyond traditional research and clinical ethics concerns. Reflecting on how accessing neurobiological information can influence individual self-narratives will be vital to ensure the ethical translation of neuroscience and genomics into mental health. Trial registration The study did not involve a health care intervention on human participants. It was retrospectively registered on 11 July 2018, registration number: researchregistry4255.

scholarly journals Characteristic Latent Features for Analyzing Digital Mental Health Interaction and Improved Explainability

2020 ◽  
Author(s):  
Max-Marcel Theilig ◽  
Ashley Arehart Knapp ◽  
Jennifer Nicholas ◽  
Rüdiger Zarnekow ◽  
David Curtis Mohr
Keyword(s):  
Mental Health ◽  
Data Science ◽  
Digital Health ◽  
A Priori ◽  
Sensor Technology ◽  
User Engagement ◽  
Behavioral Strategies ◽  
Data Set ◽  
Public Data ◽  
Latent Features

Abstract Background: Using smartphones and wearable sensor technology has sparked a broad engagement of data science and machine learning methods to leverage the complex, assorted amount of data. Despite verified processes, there is a reported underdevelopment of user engagement concepts, and the desire for high accuracy or significance has shown to lead to low explicability and irreproducibility. To overcome these issues, we aim to analyze principal characteristics of everyday behavior in digital mental health. Methods: We generated five latent features based on previous research, expert opinions from digital mental health, and informed by data. The features were analyzed with descriptive statistics and data visualization. We carried out two rounds of evaluations with data from 12,400 users of IntelliCare, a mental health platform with 12 apps. First, we focused to proof concept and second, we assessed reproducibility by drawing conclusion from distribution differences. User data was drawn from both research trials and public deployment on Google Play. Results: Our algorithms showed increased rationale for the basic usage of apps with different underlying behavioral strategies. Measures of the distribution of user’s allocated attention, the user’s circadian behavior, their consecutive commitment to a specific strategy, and users’ interaction trajectory are perceived as transferable to the public data set. Because distributions between research trial and public deployment were similar, consistency was shown regarding the underlying behavioral strategies: psychoeducation and goal setting are used as a catalyst to overcome the users’ primary obstacles, sleep hygiene is addressed most regularly, while regular self-reflective thinking is avoided. Relaxation as well as cognitive reframing have increased variance in commitment among public users, indicating the challenging nature of these apps. The relative course of the engagement (learning curve) is similar in research and public data. Conclusions: The deliberate, a-priori engineered features were reproducible across app users from both data sets. These features led to improved results as well as increased interpretability, providing an increased understanding of how people engage with multiple mental health apps over time. Since we based the generation of features on generic interaction proxies, these methods are applicable to other cases in artificial intelligence and digital health.

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