1
|
Herbert C. Analyzing and computing humans by means of the brain using Brain-Computer Interfaces - understanding the user - previous evidence, self-relevance and the user's self-concept as potential superordinate human factors of relevance. Front Hum Neurosci 2024; 17:1286895. [PMID: 38435127 PMCID: PMC10904616 DOI: 10.3389/fnhum.2023.1286895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 12/11/2023] [Indexed: 03/05/2024] Open
Abstract
Brain-computer interfaces (BCIs) are well-known instances of how technology can convert a user's brain activity taken from non-invasive electroencephalography (EEG) into computer commands for the purpose of computer-assisted communication and interaction. However, not all users are attaining the accuracy required to use a BCI consistently, despite advancements in technology. Accordingly, previous research suggests that human factors could be responsible for the variance in BCI performance among users. Therefore, the user's internal mental states and traits including motivation, affect or cognition, personality traits, or the user's satisfaction, beliefs or trust in the technology have been investigated. Going a step further, this manuscript aims to discuss which human factors could be potential superordinate factors that influence BCI performance, implicitly, explicitly as well as inter- and intraindividually. Based on the results of previous studies that used comparable protocols to examine the motivational, affective, cognitive state or personality traits of healthy and vulnerable EEG-BCI users within and across well-investigated BCIs (P300-BCIs or SMR-BCIs, respectively), it is proposed that the self-relevance of tasks and stimuli and the user's self-concept provide a huge potential for BCI applications. As potential key human factors self-relevance and the user's self-concept (self-referential knowledge and beliefs about one's self) guide information processing and modulate the user's motivation, attention, or feelings of ownership, agency, and autonomy. Changes in the self-relevance of tasks and stimuli as well as self-referential processing related to one's self (self-concept) trigger changes in neurophysiological activity in specific brain networks relevant to BCI. Accordingly, concrete examples will be provided to discuss how past and future research could incorporate self-relevance and the user's self-concept in the BCI setting - including paradigms, user instructions, and training sessions.
Collapse
Affiliation(s)
- Cornelia Herbert
- Department of Applied Emotion and Motivation Psychology, Institute of Psychology and Education, Ulm University, Ulm, Germany
| |
Collapse
|
2
|
Chong MK, Hickie IB, Cross SP, McKenna S, Varidel M, Capon W, Davenport TA, LaMonica HM, Sawrikar V, Guastella A, Naismith SL, Scott EM, Iorfino F. Digital Application of Clinical Staging to Support Stratification in Youth Mental Health Services: Validity and Reliability Study. JMIR Form Res 2023; 7:e45161. [PMID: 37682588 PMCID: PMC10517388 DOI: 10.2196/45161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Revised: 05/31/2023] [Accepted: 06/26/2023] [Indexed: 09/09/2023] Open
Abstract
BACKGROUND As the demand for youth mental health care continues to rise, managing wait times and reducing treatment delays are key challenges to delivering timely and quality care. Clinical staging is a heuristic model for youth mental health that can stratify care allocation according to individuals' risk of illness progression. The application of staging has been traditionally limited to trained clinicians yet leveraging digital technologies to apply clinical staging could increase the scalability and usability of this model in services. OBJECTIVE The aim of this study was to validate a digital algorithm to accurately differentiate young people at lower and higher risk of developing mental disorders. METHODS We conducted a study with a cohort comprising 131 young people, aged between 16 and 25 years, who presented to youth mental health services in Australia between November 2018 and March 2021. Expert psychiatrists independently assigned clinical stages (either stage 1a or stage 1b+), which were then compared to the digital algorithm's allocation based on a multidimensional self-report questionnaire. RESULTS Of the 131 participants, the mean age was 20.3 (SD 2.4) years, and 72% (94/131) of them were female. Ninety-one percent of clinical stage ratings were concordant between the digital algorithm and the experts' ratings, with a substantial interrater agreement (κ=0.67; P<.001). The algorithm demonstrated an accuracy of 91% (95% CI 86%-95%; P=.03), a sensitivity of 80%, a specificity of 93%, and an F1-score of 73%. Of the concordant ratings, 16 young people were allocated to stage 1a, while 103 were assigned to stage 1b+. Among the 12 discordant cases, the digital algorithm allocated a lower stage (stage 1a) to 8 participants compared to the experts. These individuals had significantly milder symptoms of depression (P<.001) and anxiety (P<.001) compared to those with concordant stage 1b+ ratings. CONCLUSIONS This novel digital algorithm is sufficiently robust to be used as an adjunctive decision support tool to stratify care and assist with demand management in youth mental health services. This work could transform care pathways and expedite care allocation for those in the early stages of common anxiety and depressive disorders. Between 11% and 27% of young people seeking care may benefit from low-intensity, self-directed, or brief interventions. Findings from this study suggest the possibility of redirecting clinical capacity to focus on individuals in stage 1b+ for further assessment and intervention.
Collapse
Affiliation(s)
- Min K Chong
- Brain and Mind Centre, University of Sydney, Camperdown, Australia
| | - Ian B Hickie
- Brain and Mind Centre, University of Sydney, Camperdown, Australia
| | | | - Sarah McKenna
- Brain and Mind Centre, University of Sydney, Camperdown, Australia
| | - Mathew Varidel
- Brain and Mind Centre, University of Sydney, Camperdown, Australia
| | - William Capon
- Brain and Mind Centre, University of Sydney, Camperdown, Australia
| | - Tracey A Davenport
- Design and Strategy Division, Australian Digital Health Agency, Sydney, Australia
| | - Haley M LaMonica
- Brain and Mind Centre, University of Sydney, Camperdown, Australia
| | - Vilas Sawrikar
- School of Health and Social Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Adam Guastella
- Brain and Mind Centre, University of Sydney, Camperdown, Australia
- Children's Hospital Westmead Clinical School, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
| | - Sharon L Naismith
- Brain and Mind Centre, University of Sydney, Camperdown, Australia
- Healthy Brain Ageing Program, University of Sydney, Sydney, Australia
| | - Elizabeth M Scott
- Brain and Mind Centre, University of Sydney, Camperdown, Australia
- St Vincent's and Mater Clinical School, The University of Notre Dame, Sydney, Australia
| | - Frank Iorfino
- Brain and Mind Centre, University of Sydney, Camperdown, Australia
| |
Collapse
|
3
|
Pilch M, van Rietschoten T, Ortiz-Catalan M, Lendaro E, van der Sluis CK, Hermansson L. Interplay Between Innovation and Intersubjectivity: Therapists Perceptions of Phantom Motor Execution Therapy and Its Effect on Phantom Limb Pain. J Pain Res 2023; 16:2747-2761. [PMID: 37577161 PMCID: PMC10422994 DOI: 10.2147/jpr.s412895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 07/12/2023] [Indexed: 08/15/2023] Open
Abstract
Purpose Interpersonal processes, including therapeutic alliance, may modulate the impact of interventions on pain experience. However, the role of interpersonal context on the effects of technology-enhanced interventions remains underexplored. This study elicited therapists' perspectives on how a novel rehabilitative process, involving Phantom Motor Execution (PME), may impact phantom limb pain. The mediating role of therapeutic alliance, and the way PME influenced its formation, was investigated. Methods A qualitative descriptive design, using a framework method, was used to explore therapists' (n=11) experiences of delivering PME treatment. Semi-structured online-based interviews were conducted. Results A 3-way interaction between therapist, patient, and the PME device was an overarching construct tying four themes together. It formed the context for change in phantom limb experience. The perceived therapeutic effects (theme 1) extended beyond those initially hypothesised and highlighted the mediating role of the key actors and context (theme 2). The therapeutic relationship was perceived as a transformative journey (theme 3), creating an opportunity for communication, collaboration, and bonding. It was seen as a cause and a consequence of therapeutic effects. Future directions, including the role of expertise-informed adaptations and enabling aspects of customised solutions, were indicated (theme 4). Conclusion This study pointed to intrapersonal, interpersonal, and contextual factors that should be considered in clinical implementation of novel rehabilitative tools. The results demonstrated that therapists have unique insights and a crucial role in facilitating PME treatment. The study highlighted the need to consider the biopsychosocial model of pain in designing, evaluating, and implementing technology-supported interventions.
Collapse
Affiliation(s)
- Monika Pilch
- Centre for Health Policy & Management, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Tijn van Rietschoten
- University of Groningen, University Medical Center Groningen, Department of Rehabilitation Medicine, Groningen, the Netherlands
- University of Groningen, Faculty of Medical Sciences, Groningen, the Netherlands
| | - Max Ortiz-Catalan
- Center for Bionics and Pain Research, Mölndal, Sweden
- Bionics Institute, Melbourne, VC, Australia
- Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden
| | - Eva Lendaro
- Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden
- Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Corry K van der Sluis
- University of Groningen, University Medical Center Groningen, Department of Rehabilitation Medicine, Groningen, the Netherlands
| | - Liselotte Hermansson
- Department of Prosthetics and Orthotics, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
- University Health Care Research Center, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| |
Collapse
|
4
|
Balcombe L, De Leo D. Evaluation of the Use of Digital Mental Health Platforms and Interventions: Scoping Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 20:ijerph20010362. [PMID: 36612685 PMCID: PMC9819791 DOI: 10.3390/ijerph20010362] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 12/22/2022] [Accepted: 12/23/2022] [Indexed: 05/28/2023]
Abstract
BACKGROUND The increasing use of digital mental health (DMH) platforms and digital mental health interventions (DMHIs) is hindered by uncertainty over effectiveness, quality and usability. There is a need to identify the types of available evidence in this domain. AIM This study is a scoping review identifying evaluation of the (1) DMH platform/s used; and (2) DMHI/s applied on the DMH platform/s. METHODS The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guided the review process. Empirical studies that focused on evaluation of the use and application of DMH platforms were included from journal articles (published 2012-2022). A literature search was conducted using four electronic databases (Scopus, ScienceDirect, Sage and ACM Digital Library) and two search engines (PubMed and Google Scholar). RESULTS A total of 6874 nonduplicate records were identified, of which 144 were analyzed and 22 met the inclusion criteria. The review included general/unspecified mental health and/or suicidality indications (n = 9, 40.9%), followed by depression (n = 5, 22.7%), psychosis (n = 3, 13.6%), anxiety and depression (n = 2, 9.1%), as well as anxiety, depression and suicidality (n = 1, 4.5%), loneliness (n = 1, 4.5%), and addiction (n = 1, 4.5%). There were 11 qualitative studies (50%), 8 quantitative studies (36.4%), and 3 mixed-methods studies (n = 3, 13.6%). The results contained 11 studies that evaluated the DMH platform/s and 11 studies that evaluated the DMHI/s. The studies focused on feasibility, usability, engagement, acceptability and effectiveness. There was a small amount of significant evidence (1 in each 11), notably the (cost-)effectiveness of a DMHI with significant long-term impact on anxiety and depression in adults. CONCLUSION The empirical research demonstrates the feasibility of DMH platforms and DMHIs. To date, there is mostly heterogeneous, preliminary evidence for their effectiveness, quality and usability. However, a scalable DMHI reported effectiveness in treating adults' anxiety and depression. The scope of effectiveness may be widened through targeted strategies, for example by engaging independent young people.
Collapse
|
5
|
Balcombe L, De Leo D. Linking music streaming platform advertisements with a digital mental health assessment and interventions. Front Digit Health 2022; 4:964251. [PMID: 36419871 PMCID: PMC9677233 DOI: 10.3389/fdgth.2022.964251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 10/13/2022] [Indexed: 11/09/2022] Open
Abstract
Accessibility issues and low rates of help-seeking hinder engagement with mental health resources and treatment. Pragmatic, (cost-)effective solutions are required to increase engagement with efficacious digital mental health interventions (DMHIs) including for hard-to-reach individuals. As an example, music-based interventions have been positively used in health care to reduce stress, anxiety and depression through music medicine, music therapy and recreational use. Although, enhanced mental health awareness from music listening has yet to be converted into engagement with a DMH assessment (DMHA) and DMHIs. Therefore, a new study is proposed to place linked advertisements on Spotify, the most used music streaming platform. MindSpot's vetted DMHA is suitable to use as an example for linking unto because it measures depression, anxiety, general mental well-being problems and psychological distress in Australian adults and provides access to DMHIs. The primary aim is to provide a convenient, robust and scalable consumer pathway to reduce engagement barriers and maximize facilitation to a vetted DMHA and DMHIs. The proposed study is important because it addresses notorious help-seeking difficulties in the adult population (e.g., young people and men). It also expands outreach to the underserved and the unserved and streamlines the integration of digital solutions with mental health services.
Collapse
|
6
|
Development of Computational Thinking Using Microcontrollers Integrated into OOP (Object-Oriented Programming). SUSTAINABILITY 2022. [DOI: 10.3390/su14127218] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Nowadays, the theme of computer thinking is a common topic for educational research. The scientific literature on the subject has gradually appeared, in which psychologists emphasize the need for the development of thinking of children. Research often relates only to the development of computational thinking at elementary and high schools. Nowadays, almost everything is digitalized, so it is important to also develop the computational thinking skills of students at higher levels. In our study, we present the results of the conducted data analysis in which we examined the development of students’ efficiency. On the basis of the results, we propose a possible solution for the development of computational thinking. Using data research processes, we examined the results of the object-oriented (OO) planning and programming subject of Budapest Business School, going back 5 years. The results show that the level of particular computational thinking could be measured using the exam results, and teacher advancement (experience) improved the level of particular computational thinking. Today, education has been greatly influenced by COVID-19, challenging not only teachers but also students. The production of particular computational thinking under COVID-19 or online is much more effective than the pursuit of full computational thinking through traditional teaching.
Collapse
|
7
|
Kellogg KC, Sadeh-Sharvit S. Pragmatic AI-augmentation in mental healthcare: Key technologies, potential benefits, and real-world challenges and solutions for frontline clinicians. Front Psychiatry 2022; 13:990370. [PMID: 36147984 PMCID: PMC9485594 DOI: 10.3389/fpsyt.2022.990370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Accepted: 08/19/2022] [Indexed: 11/13/2022] Open
Abstract
The integration of artificial intelligence (AI) technologies into mental health holds the promise of increasing patient access, engagement, and quality of care, and of improving clinician quality of work life. However, to date, studies of AI technologies in mental health have focused primarily on challenges that policymakers, clinical leaders, and data and computer scientists face, rather than on challenges that frontline mental health clinicians are likely to face as they attempt to integrate AI-based technologies into their everyday clinical practice. In this Perspective, we describe a framework for "pragmatic AI-augmentation" that addresses these issues by describing three categories of emerging AI-based mental health technologies which frontline clinicians can leverage in their clinical practice-automation, engagement, and clinical decision support technologies. We elaborate the potential benefits offered by these technologies, the likely day-to-day challenges they may raise for mental health clinicians, and some solutions that clinical leaders and technology developers can use to address these challenges, based on emerging experience with the integration of AI technologies into clinician daily practice in other healthcare disciplines.
Collapse
Affiliation(s)
- Katherine C Kellogg
- Department of Work and Organization Studies, MIT Sloan School of Management, Cambridge, MA, United States
| | - Shiri Sadeh-Sharvit
- Eleos Health, Cambridge, MA, United States.,Center for M2Health, Palo Alto University, Palo Alto, CA, United States
| |
Collapse
|