1
|
Del Bene VA, Walker KA. From Practice to Public Health: Broadening Neuropsychology's Reach & Value-An Introduction to the National Academy of Neuropsychology's 2022 Annual Conference Special Issue. Arch Clin Neuropsychol 2024; 39:273-275. [PMID: 38520366 DOI: 10.1093/arclin/acae012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Accepted: 02/07/2024] [Indexed: 03/25/2024] Open
Abstract
This special issue is centered around presentations from the National Academy of Neuropsychology 2022 Annual Conference. The theme of the conference, "From Practice to Public Health: Broadening Neuropsychology's Reach & Value" is pivotal for the field's future. With an ever-shifting technological landscape and recent changes in clinical practice post-COVID, we are left wondering how neuropsychology will develop. How will we use biomedical and technological advances, such as blood-based Alzheimer's disease biomarkers or passive digital recordings, to improve clinical care and further expand our understanding of disease mechanisms? As neuropsychologists, how can we use our expertise to empirically inform public health policy? The diagnosis and treatment of post-acute sequelae of COVID-19, the identification and characterization of post-pandemic educational setbacks, and the adaptation of new technological and diagnostic advances into clinical practice workflows represent a vital set of new challenges and opportunities poised to disrupt traditional modes of practice. The articles in this special issue convey the role of neuropsychology in addressing these emerging issues and illustrate how and why neuropsychology is well positioned to be at the forefront of clinical practice and scientific advancements.
Collapse
Affiliation(s)
- Victor A Del Bene
- Department of Neurology, The University of Alabama at Birmingham, Heersink School of Medicine, Birmingham, AL, USA
| | - Keenan A Walker
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Intramural Research Program, Baltimore, MD, USA
| |
Collapse
|
2
|
Liu AA, Barr WB. Overlapping and distinct phenotypic profiles in Alzheimer's disease and late onset epilepsy: a biologically-based approach. Front Neurol 2024; 14:1260523. [PMID: 38545454 PMCID: PMC10965692 DOI: 10.3389/fneur.2023.1260523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 12/18/2023] [Indexed: 04/05/2024] Open
Abstract
Due to shared hippocampal dysfunction, patients with Alzheimer's dementia and late-onset epilepsy (LOE) report memory decline. Multiple studies have described the epidemiological, pathological, neurophysiological, and behavioral overlap between Alzheimer's Disease and LOE, implying a bi-directional relationship. We describe the neurobiological decline occurring at different spatial in AD and LOE patients, which may explain why their phenotypes overlap and differ. We provide suggestions for clinical recognition of dual presentation and novel approaches for behavioral testing that reflect an "inside-out," or biologically-based approach to testing memory. New memory and language assessments could detect-and treat-memory impairment in AD and LOE at an earlier, actionable stage.
Collapse
Affiliation(s)
- Anli A. Liu
- Langone Medical Center, New York University, New York, NY, United States
- Department of Neurology, School of Medicine, New York University, New York, NY, United States
- Neuroscience Institute, Langone Medical Center, New York University, New York, NY, United States
| | - William B. Barr
- Department of Neurology, School of Medicine, New York University, New York, NY, United States
| |
Collapse
|
3
|
Possemis N, ter Huurne D, Banning L, Gruters A, Van Asbroeck S, König A, Linz N, Tröger J, Langel K, Blokland A, Prickaerts J, de Vugt M, Verhey F, Ramakers I. The Reliability and Clinical Validation of Automatically-Derived Verbal Memory Features of the Verbal Learning Test in Early Diagnostics of Cognitive Impairment. J Alzheimers Dis 2024; 97:179-191. [PMID: 38108348 PMCID: PMC10789344 DOI: 10.3233/jad-230608] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/10/2023] [Indexed: 12/19/2023]
Abstract
BACKGROUND Previous research has shown that verbal memory accurately measures cognitive decline in the early phases of neurocognitive impairment. Automatic speech recognition from the verbal learning task (VLT) can potentially be used to differentiate between people with and without cognitive impairment. OBJECTIVE Investigate whether automatic speech recognition (ASR) of the VLT is reliable and able to differentiate between subjective cognitive decline (SCD) and mild cognitive impairment (MCI). METHODS The VLT was recorded and processed via a mobile application. Following, verbal memory features were automatically extracted. The diagnostic performance of the automatically derived features was investigated by training machine learning classifiers to distinguish between participants with SCD versus MCI/dementia. RESULTS The ICC for inter-rater reliability between the clinical and automatically derived features was 0.87 for the total immediate recall and 0.94 for the delayed recall. The full model including the total immediate recall, delayed recall, recognition count, and the novel verbal memory features had an AUC of 0.79 for distinguishing between participants with SCD versus MCI/dementia. The ten best differentiating VLT features correlated low to moderate with other cognitive tests such as logical memory tasks, semantic verbal fluency, and executive functioning. CONCLUSIONS The VLT with automatically derived verbal memory features showed in general high agreement with the clinical scoring and distinguished well between SCD and MCI/dementia participants. This might be of added value in screening for cognitive impairment.
Collapse
Affiliation(s)
- Nina Possemis
- Alzheimer Centre Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Daphne ter Huurne
- Alzheimer Centre Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Leonie Banning
- Maastricht University Medical Centre+ (MUMC+), Department of Psychiatry & Psychology, Maastricht, The Netherlands
| | | | - Stephanie Van Asbroeck
- Alzheimer Centre Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Alexandra König
- National Institute for Research in Computer Science and Automation (INRIA), Valbonne, Sophia Antipolis, France
- ki:elements, Saarbrücken, Germany
| | | | | | - Kai Langel
- Janssen Clinical Innovation, Beerse, Belgium
| | - Arjan Blokland
- Faculty of Psychology and Neuroscience, Department of Neuropsychology & Psychopharmacology, EURON, Maastricht University, Maastricht, The Netherlands
| | - Jos Prickaerts
- School for Mental Health and Neuroscience, Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, The Netherlands
| | - Marjolein de Vugt
- Alzheimer Centre Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht University Medical Centre+ (MUMC+), Department of Psychiatry & Psychology, Maastricht, The Netherlands
| | - Frans Verhey
- Alzheimer Centre Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht University Medical Centre+ (MUMC+), Department of Psychiatry & Psychology, Maastricht, The Netherlands
| | - Inez Ramakers
- Alzheimer Centre Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht University Medical Centre+ (MUMC+), Department of Psychiatry & Psychology, Maastricht, The Netherlands
| |
Collapse
|
4
|
Brown T, Zakzanis KK. A review of the reliability of remote neuropsychological assessment. APPLIED NEUROPSYCHOLOGY. ADULT 2023:1-7. [PMID: 38000083 DOI: 10.1080/23279095.2023.2279208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/26/2023]
Abstract
The provision of clinical neuropsychological services has predominately been undertaken by way of standardized administration in a face-to-face setting. Interpretation of psychometric findings in this context is dependent on the use of normative comparison. When the standardization in which such psychometric measures are employed deviates from how they were employed in the context of the development of its associated norms, one is left to question the reliability and hence, validity of any such findings and in turn, diagnostic decision making. In light of the current COVID-19 pandemic and resultant social distancing direction, face-to-face neuropsychological assessment has been challenging to undertake. As such, remote (i.e., virtual) neuropsychological assessment has become an obvious solution. Here, and before the results from remote neuropsychological assessment can be said to stand on firm scientific grounds, it is paramount to ensure that results garnered remotely are reliable and valid. To this end, we undertook a review of the literature and present an overview of the landscape. To date, the literature shows evidence for the reliability of remote administration and the clinical implications are paramount. When and where needed, neuropsychologists, psychometric technicians and examinees may no longer need to be in the same physical space to undergo an assessment. These findings are most relevant given the physical distancing practices because of COVID-19. And whilst remote assessment should never supplant face-to-face neuropsychological assessments, it does serve as a valid alternative when necessary.
Collapse
Affiliation(s)
- Tyler Brown
- Graduate Department of Psychological Clinical Science, University of Toronto, Toronto, ON, Canada
| | - Konstantine K Zakzanis
- Graduate Department of Psychological Clinical Science, University of Toronto, Toronto, ON, Canada
- Department of Psychology, University of Toronto, Scarborough, ON, Canada
| |
Collapse
|
5
|
Stricker JL, Corriveau-Lecavalier N, Wiepert DA, Botha H, Jones DT, Stricker NH. Neural network process simulations support a distributed memory system and aid design of a novel computer adaptive digital memory test for preclinical and prodromal Alzheimer's disease. Neuropsychology 2023; 37:698-715. [PMID: 36037486 PMCID: PMC9971333 DOI: 10.1037/neu0000847] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
OBJECTIVE Growing evidence supports the importance of learning as a central deficit in preclinical/prodromal Alzheimer's disease. The aims of this study were to conduct a series of neural network simulations to develop a functional understanding of a distributed, nonmodular memory system that can learn efficiently without interference. This understanding is applied to the development of a novel digital memory test. METHOD Simulations using traditional feed forward neural network architectures to learn simple logic problems are presented. The simulations demonstrate three limitations: (a) inefficiency, (b) an inability to learn problems consistently, and (c) catastrophic interference when given multiple problems. A new mirrored cascaded architecture is introduced to address these limitations, with support provided by a series of simulations. RESULTS The mirrored cascaded architecture demonstrates efficient and consistent learning relative to feed forward networks but also suffers from catastrophic interference. Addition of context values to add the capability of distinguishing features as part of learning eliminates the problem of interference in the mirrored cascaded, but not the feed forward, architectures. CONCLUSIONS A mirrored cascaded architecture addresses the limitations of traditional feed forward neural networks, provides support for a distributed memory system, and emphasizes the importance of context to avoid interference. These process models contributed to the design of a digital computer-adaptive word list learning test that places maximum stress on the capability to distinguish specific episodes of learning. Process simulations provide a useful method of testing models of brain function and contribute to new approaches to neuropsychological assessment. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
Collapse
Affiliation(s)
- John L. Stricker
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Information Technology, Mayo Clinic, Rochester, Minnesota, USA
| | | | | | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - David T. Jones
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Nikki H. Stricker
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota, USA
| |
Collapse
|
6
|
DuBord AY, Paolillo EW, Staffaroni AM. Remote Digital Technologies for the Early Detection and Monitoring of Cognitive Decline in Patients With Type 2 Diabetes: Insights From Studies of Neurodegenerative Diseases. J Diabetes Sci Technol 2023:19322968231171399. [PMID: 37102472 DOI: 10.1177/19322968231171399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/28/2023]
Abstract
Type 2 diabetes (T2D) is a risk factor for cognitive decline. In neurodegenerative disease research, remote digital cognitive assessments and unobtrusive sensors are gaining traction for their potential to improve early detection and monitoring of cognitive impairment. Given the high prevalence of cognitive impairments in T2D, these digital tools are highly relevant. Further research incorporating remote digital biomarkers of cognition, behavior, and motor functioning may enable comprehensive characterizations of patients with T2D and may ultimately improve clinical care and equitable access to research participation. The aim of this commentary article is to review the feasibility, validity, and limitations of using remote digital cognitive tests and unobtrusive detection methods to identify and monitor cognitive decline in neurodegenerative conditions and apply these insights to patients with T2D.
Collapse
Affiliation(s)
- Ashley Y DuBord
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
- Diabetes Technology Society, Burlingame, CA, USA
| | - Emily W Paolillo
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Adam M Staffaroni
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| |
Collapse
|
7
|
McLean E, Cornwell MA, Bender HA, Sacks-Zimmerman A, Mandelbaum S, Koay JM, Raja N, Kohn A, Meli G, Spat-Lemus J. Innovations in Neuropsychology: Future Applications in Neurosurgical Patient Care. World Neurosurg 2023; 170:286-295. [PMID: 36782427 DOI: 10.1016/j.wneu.2022.09.103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 09/22/2022] [Indexed: 02/11/2023]
Abstract
Over the last century, collaboration between clinical neuropsychologists and neurosurgeons has advanced the state of the science in both disciplines. These advances have provided the field of neuropsychology with many opportunities for innovation in the care of patients prior to, during, and following neurosurgical intervention. Beyond giving a general overview of how present-day advances in technology are being applied in the practice of neuropsychology within a neurological surgery department, this article outlines new developments that are currently unfolding. Improvements in remote platform, computer interface, "real-time" analytics, mobile devices, and immersive virtual reality have the capacity to increase the customization, precision, and accessibility of neuropsychological services. In doing so, such innovations have the potential to improve outcomes and ameliorate health care disparities.
Collapse
Affiliation(s)
- Erin McLean
- Department of Psychology, Hofstra University, Hempstead, New York, USA; Department of Neurological Surgery, Weill Cornell Medicine, New York, New York, USA
| | - Melinda A Cornwell
- Department of Neurological Surgery, Weill Cornell Medicine, New York, New York, USA
| | - H Allison Bender
- Department of Neurological Surgery, Weill Cornell Medicine, New York, New York, USA.
| | | | - Sarah Mandelbaum
- Department of Neurological Surgery, Weill Cornell Medicine, New York, New York, USA; Department of Clinical Psychology with Health Emphasis, Ferkauf Graduate School of Psychology, Yeshiva University, Bronx, New York, USA
| | - Jun Min Koay
- Department of Neurological Surgery, Weill Cornell Medicine, New York, New York, USA; Department of Psychiatry and Psychology, Mayo Clinic, Jacksonville, Florida, USA
| | - Noreen Raja
- Department of Neurological Surgery, Weill Cornell Medicine, New York, New York, USA; Graduate School of Applied and Professional Psychology, Rutgers University, Piscataway, New Jersey, USA
| | - Aviva Kohn
- Department of Neurological Surgery, Weill Cornell Medicine, New York, New York, USA; Department of Clinical Psychology with Health Emphasis, Ferkauf Graduate School of Psychology, Yeshiva University, Bronx, New York, USA
| | - Gabrielle Meli
- Department of Neurological Surgery, Weill Cornell Medicine, New York, New York, USA; Department of Human Ecology, Cornell University, Ithaca, New York, USA
| | - Jessica Spat-Lemus
- Department of Neurological Surgery, Weill Cornell Medicine, New York, New York, USA
| |
Collapse
|
8
|
Singh S, Strong R, Xu I, Fonseca L, Hawks Z, Grinspoon E, Jung L, Li F, Weinstock R, Sliwinski M, Chaytor N, Germine L. Reliability and Validity of Ecological Momentary Assessment of Cognition in Type 1 Diabetes and Community Samples (Preprint). J Med Internet Res 2022. [DOI: 10.2196/45028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/31/2023] Open
|
9
|
Chen MH, Leow A, Ross MK, DeLuca J, Chiaravalloti N, Costa SL, Genova HM, Weber E, Hussain F, Demos AP. Associations between smartphone keystroke dynamics and cognition in MS. Digit Health 2022; 8:20552076221143234. [PMID: 36506490 PMCID: PMC9730018 DOI: 10.1177/20552076221143234] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 11/17/2022] [Indexed: 12/12/2022] Open
Abstract
Objective Examine the associations between smartphone keystroke dynamics and cognitive functioning among persons with multiple sclerosis (MS). Methods Sixteen persons with MS with no self-reported upper extremity or typing difficulties and 10 healthy controls (HCs) completed six weeks of remote monitoring of their keystroke dynamics (i.e., how they typed on their smartphone keyboards). They also completed a comprehensive neuropsychological assessment and symptom ratings about fatigue, depression, and anxiety at baseline. Results A total of 1,335,787 keystrokes were collected, which were part of 30,968 typing sessions. The MS group typed slower (P < .001) and more variably (P = .032) than the HC group. Faster typing speed was associated with better performance on measures of processing speed (P = .016), attention (P = .022), and executive functioning (cognitive flexibility: P = .029; behavioral inhibition: P = .002; verbal fluency: P = .039), as well as less severe impact from fatigue (P < .001) and less severe anxiety symptoms (P = .007). Those with better cognitive functioning and less severe symptoms showed a stronger correlation between the use of backspace and autocorrection events (P < .001). Conclusion Typing speed may be sensitive to cognitive functions subserved by the frontal-subcortical brain circuits. Individuals with better cognitive functioning and less severe symptoms may be better at monitoring their typing errors. Keystroke dynamics have the potential to be used as an unobtrusive remote monitoring method for real-life cognitive functioning among persons with MS, which may improve the detection of relapses, evaluate treatment efficacy, and track disability progression.
Collapse
Affiliation(s)
- Michelle H Chen
- Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, USA,Department of Neurology, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA,Michelle H Chen, Institute for Health, Health Care Policy and Aging Research, Rutgers University, 112 Paterson St, New Brunswick,
NJ 08901, USA.
Alex Leow, Department of Psychiatry, University of Illinois at Chicago, 1601 W. Taylor St., SPHPI MC 912, Chicago, IL 60612, USA.
| | - Alex Leow
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA
| | - Mindy K Ross
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA
| | - John DeLuca
- Kessler Foundation, East Hanover, NJ, USA,Department of Physical Medicine and Rehabilitation, New Jersey Medical School, Rutgers University, Newark, NJ, USA
| | - Nancy Chiaravalloti
- Kessler Foundation, East Hanover, NJ, USA,Department of Physical Medicine and Rehabilitation, New Jersey Medical School, Rutgers University, Newark, NJ, USA
| | - Silvana L Costa
- Kessler Foundation, East Hanover, NJ, USA,Department of Physical Medicine and Rehabilitation, New Jersey Medical School, Rutgers University, Newark, NJ, USA
| | - Helen M Genova
- Kessler Foundation, East Hanover, NJ, USA,Department of Physical Medicine and Rehabilitation, New Jersey Medical School, Rutgers University, Newark, NJ, USA
| | - Erica Weber
- Kessler Foundation, East Hanover, NJ, USA,Department of Physical Medicine and Rehabilitation, New Jersey Medical School, Rutgers University, Newark, NJ, USA
| | - Faraz Hussain
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA
| | - Alexander P Demos
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA
| |
Collapse
|
10
|
Driskell LD, Del Bene VA, Sperling SA. What makes for a competitive fellowship candidate? A survey of clinical neuropsychology postdoctoral training directors. Clin Neuropsychol 2022; 36:2041-2060. [PMID: 34429020 DOI: 10.1080/13854046.2021.1967451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
To obtain objective data about the factors that clinical neuropsychology postdoctoral training directors (TDs) look for and prioritize in their review and selection of fellowship candidates. We identified 167 TDs who were overseeing postdoctoral training programs that provided training consistent with the Houston Conference Guidelines. We invited all TDs to complete an anonymous online survey that assessed their expectations as they relate to the selection of fellowship candidates. Eighty-eight TDs completed the survey in full. We used descriptive statistics to analyze the data and investigate potential between-group differences in TDs' responses across patient populations, training settings, and APPCN member program status. TDs ranked the intensity of candidates' neuropsychology education and training experiences, their fellowship interviews, and letters of recommendation as most important. Increasing the representation of under-represented minorities and other factors were ranked lower. Minimum benchmarks related to candidates' scholarly productivity, dissertation progress, and the time they spent engaged in clinical neuropsychology activities during internship were revealed. There were relatively few differences in TDs' responses when compared across patient populations, training settings, or APPCN member program status. Students may increase their competitiveness for clinical neuropsychology fellowships by obtaining intensive education and training experiences in the specialty, which includes clinical training and coursework, and by producing scholarly work. Students may also benefit from improving their interviewing skills, completing an internship with at least 40% of time spent in neuropsychological activities, and at minimum by having their dissertation data collected before their fellowship interviews.
Collapse
Affiliation(s)
- Lucas D Driskell
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Victor A Del Bene
- Department of Neurology, University of Alabama at Birmingham School of Medicine, Birmingham, AL, USA
| | - Scott A Sperling
- Center for Neurological Restoration, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
| |
Collapse
|
11
|
Dincelli E, Yayla A. Immersive virtual reality in the age of the Metaverse: A hybrid-narrative review based on the technology affordance perspective. JOURNAL OF STRATEGIC INFORMATION SYSTEMS 2022. [DOI: 10.1016/j.jsis.2022.101717] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
|
12
|
Gagnon Shaigetz V, Proulx C, Cabral A, Choudhury N, Hewko M, Kohlenberg E, Segado M, Smith MSD, Debergue P. An Immersive and Interactive Platform for Cognitive Assessment and Rehabilitation (bWell): Design and Iterative Development Process. JMIR Rehabil Assist Technol 2021; 8:e26629. [PMID: 34730536 PMCID: PMC8600432 DOI: 10.2196/26629] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2020] [Revised: 07/13/2021] [Accepted: 07/27/2021] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND Immersive technologies like virtual reality can enable clinical care that meaningfully aligns with real-world deficits in cognitive functioning. However, options in immersive 3D environments are limited, partly because of the unique challenges presented by the development of a clinical care platform. These challenges include selecting clinically relevant features, enabling tasks that capture the full breadth of deficits, ensuring longevity in a rapidly changing technology landscape, and performing the extensive technical and clinical validation required for digital interventions. Complicating development, is the need to integrate recommendations from domain experts at all stages. OBJECTIVE The Cognitive Health Technologies team at the National Research Council Canada aims to overcome these challenges with an iterative process for the development of bWell, a cognitive care platform providing multisensory cognitive tasks for adoption by treatment providers. METHODS The team harnessed the affordances of immersive technologies while taking an interdisciplinary research and developmental approach, obtaining active input from domain experts with iterative deliveries of the platform. The process made use of technology readiness levels, agile software development, and human-centered design to advance four main activities: identification of basic requirements and key differentiators, prototype design and foundational research to implement components, testing and validation in lab settings, and recruitment of external clinical partners. RESULTS bWell was implemented according to the findings from the design process. The main features of bWell include multimodal (fully, semi, or nonimmersive) and multiplatform (extended reality, mobile, and PC) implementation, configurable exercises that pair standardized assessment with adaptive and gamified variants for therapy, a therapist-facing user interface for task administration and dosing, and automated activity data logging. bWell has been designed to serve as a broadly applicable toolkit, targeting general aspects of cognition that are commonly impacted across many disorders, rather than focusing on 1 disorder or a specific cognitive domain. It comprises 8 exercises targeting different domains: states of attention (Egg), visual working memory (Theater), relaxation (Tent), inhibition and cognitive control (Mole), multitasking (Lab), self-regulation (Butterfly), sustained attention (Stroll), and visual search (Cloud). The prototype was tested and validated with healthy adults in a laboratory environment. In addition, a cognitive care network (5 sites across Canada and 1 in Japan) was established, enabling access to domain expertise and providing iterative input throughout the development process. CONCLUSIONS Implementing an interdisciplinary and iterative approach considering technology maturity brought important considerations for the development of bWell. Altogether, this harnesses the affordances of immersive technology and design for a broad range of applications, and for use in both cognitive assessment and rehabilitation. The technology has attained a maturity level of prototype implementation with preliminary validation carried out in laboratory settings, with next steps to perform the validation required for its eventual adoption as a clinical tool.
Collapse
Affiliation(s)
- Vincent Gagnon Shaigetz
- Simulation and Digital Health, Medical Devices Research Centre, National Research Council Canada, Boucherville, QC, Canada
| | - Catherine Proulx
- Simulation and Digital Health, Medical Devices Research Centre, National Research Council Canada, Boucherville, QC, Canada
| | - Anne Cabral
- Simulation and Digital Health, Medical Devices Research Centre, National Research Council Canada, Boucherville, QC, Canada
| | - Nusrat Choudhury
- Simulation and Digital Health, Medical Devices Research Centre, National Research Council Canada, Boucherville, QC, Canada
| | - Mark Hewko
- Simulation and Digital Health, Medical Devices Research Centre, National Research Council Canada, Winnipeg, MB, Canada
| | - Elicia Kohlenberg
- Simulation and Digital Health, Medical Devices Research Centre, National Research Council Canada, Winnipeg, MB, Canada
| | - Melanie Segado
- Simulation and Digital Health, Medical Devices Research Centre, National Research Council Canada, Boucherville, QC, Canada
| | - Michael S D Smith
- Simulation and Digital Health, Medical Devices Research Centre, National Research Council Canada, Winnipeg, MB, Canada
| | - Patricia Debergue
- Simulation and Digital Health, Medical Devices Research Centre, National Research Council Canada, Boucherville, QC, Canada
| |
Collapse
|