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Mimoso I, Figueiredo T, Midão L, Carrilho J, Henriques DV, Alves S, Duarte N, Bessa MJ, Facal D, Felpete A, Fidalgo JM, Costa E. Co-Creation in the Development of Digital Therapeutics: A Narrative Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2024; 21:1589. [PMID: 39767430 PMCID: PMC11675753 DOI: 10.3390/ijerph21121589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/15/2024] [Revised: 11/19/2024] [Accepted: 11/25/2024] [Indexed: 01/11/2025]
Abstract
Digital therapeutics (DTx) are transforming healthcare delivery through personalised, evidence-based interventions that offer a cost-effective approach to health management. However, their widespread adoption faces significant barriers including privacy concerns, usability issues, and integration challenges within healthcare systems. This review assesses the current evidence on DTx, with a particular focus on the role of co-creation in enhancing design and usability. A narrative review was conducted to identify studies exploring co-creation in DTx development. Three studies were selected for in-depth analysis, demonstrating that co-creation processes significantly improve the usability and effectiveness of DTx interventions. Findings underscore challenges in DTx implementation, including complex regulatory processes, digital inequality, high development costs, and difficulties in integrating with existing healthcare systems. Despite the existence of discrete examples of co-creation in DTx and its acknowledged value in the healthcare domain, systematic research in this field remains markedly limited. Future studies should prioritise establishing best practises for co-creation, with particular emphasis on methods to enhance data privacy and security, standardisation protocols, and patient engagement strategies to optimise DTx adoption and effectiveness. This review contributes to the growing body of literature on DTx by highlighting the potential of co-creation while also identifying critical areas for future research.
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Affiliation(s)
- Inês Mimoso
- CINTESIS@RISE, Biochemistry Lab, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal; (I.M.); (T.F.); (L.M.); (J.C.)
- Department of Biological Sciences, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
- Porto4Ageing—Competences Centre on Active and Healthy Ageing, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
| | - Teodora Figueiredo
- CINTESIS@RISE, Biochemistry Lab, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal; (I.M.); (T.F.); (L.M.); (J.C.)
- Department of Biological Sciences, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
- Porto4Ageing—Competences Centre on Active and Healthy Ageing, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
| | - Luís Midão
- CINTESIS@RISE, Biochemistry Lab, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal; (I.M.); (T.F.); (L.M.); (J.C.)
- Department of Biological Sciences, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
- Porto4Ageing—Competences Centre on Active and Healthy Ageing, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
| | - Joana Carrilho
- CINTESIS@RISE, Biochemistry Lab, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal; (I.M.); (T.F.); (L.M.); (J.C.)
- Department of Biological Sciences, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
- Porto4Ageing—Competences Centre on Active and Healthy Ageing, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
| | - Diogo Videira Henriques
- CINTESIS@RISE, Biochemistry Lab, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal; (I.M.); (T.F.); (L.M.); (J.C.)
- Department of Biological Sciences, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
- Porto4Ageing—Competences Centre on Active and Healthy Ageing, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
| | - Sara Alves
- CINTESIS@RISE, Instituto de Ciências Biomédicas Abel Salazar, University of Porto, 4050-313 Porto, Portugal
- Santa Casa da Misericórdia de Riba D’Ave/CIDIFAD—Centro de Investigação, Diagnóstico, Formação e Acompanhamento das Demências, 4765-220 Riba D’Ave, Portugal
| | - Natália Duarte
- CINTESIS@RISE, Instituto de Ciências Biomédicas Abel Salazar, University of Porto, 4050-313 Porto, Portugal
- Santa Casa da Misericórdia de Riba D’Ave/CIDIFAD—Centro de Investigação, Diagnóstico, Formação e Acompanhamento das Demências, 4765-220 Riba D’Ave, Portugal
| | - Maria João Bessa
- UPTEC-Science and Technology Park, University of Porto, 4200-135 Porto, Portugal
| | - David Facal
- Department of Developmental Psychology, University of Santiago de Compostela, 15705 Santiago de Compostela, Spain; (D.F.)
| | - Alba Felpete
- Department of Developmental Psychology, University of Santiago de Compostela, 15705 Santiago de Compostela, Spain; (D.F.)
| | - José María Fidalgo
- ACIS-Agencia Gallega para la Gestión del Conocimiento en Salud, 15707 Santiago de Compostela, Spain
| | - Elísio Costa
- CINTESIS@RISE, Biochemistry Lab, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal; (I.M.); (T.F.); (L.M.); (J.C.)
- Department of Biological Sciences, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
- Porto4Ageing—Competences Centre on Active and Healthy Ageing, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
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Denecke K, Gabarron E. The ethical aspects of integrating sentiment and emotion analysis in chatbots for depression intervention. Front Psychiatry 2024; 15:1462083. [PMID: 39611131 PMCID: PMC11602467 DOI: 10.3389/fpsyt.2024.1462083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/09/2024] [Accepted: 10/18/2024] [Indexed: 11/30/2024] Open
Abstract
Introduction Digital health interventions specifically those realized as chatbots are increasingly available for mental health. They include technologies based on artificial intelligence that assess user's sentiment and emotions for the purpose of responding in an empathetic way, or for treatment purposes, e.g. for analyzing the expressed emotions and suggesting interventions. Methods In this paper, we study the ethical dimensions of integrating these technologies in chatbots for depression intervention using the digital ethics canvas and the DTx Risk Assessment Canvas. Results As result, we identified some specific risks associated with the integration of sentiment and emotion analysis methods into these systems related to the difficulty to recognize correctly the expressed sentiment or emotion from statements of individuals with depressive symptoms and the appropriate system reaction including risk detection. Depending on the realization of the sentiment or emotion analysis, which might be dictionary-based or machine-learning based, additional risks occur from biased training data or misinterpretations. Discussion While technology decisions during system development can be made carefully depending on the use case, other ethical risks cannot be prevented on a technical level, but by carefully integrating such chatbots into the care process allowing for supervision by health professionals. We conclude that a careful reflection is needed when integrating sentiment and emotion analysis into chatbots for depression intervention. Balancing risk factors is key to leveraging technology in mental health in a way that enhances, rather than diminishes, user autonomy and agency.
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Affiliation(s)
- Kerstin Denecke
- AI for Health, Institute Patient-centered Digital Health, Bern University of Applied Sciences, Biel, Switzerland
| | - Elia Gabarron
- Department of Education, ICT and Learning, Østfold University College, Halden, Norway
- Norwegian Centre for E-health Research, University Hospital of North Norway, Tromsø, Norway
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Blobel B. Selected Papers from the pHealth 2022 Conference, Oslo, Norway, 8-10 November 2022. J Pers Med 2024; 14:947. [PMID: 39338201 PMCID: PMC11433537 DOI: 10.3390/jpm14090947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2024] [Accepted: 08/28/2024] [Indexed: 09/30/2024] Open
Abstract
This Special Issue of the Journal of Personalized Medicine presents extended versions of selected contributions to pHealth 2022, the 19th International Conference on Wearable Micro and Nano Technologies for Personalized Health, held on 8-10 November 2022 in Oslo, Norway [...].
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Affiliation(s)
- Bernd Blobel
- Medical Faculty, University of Regensburg, 93053 Regensburg, Germany;
- First Medical Faculty, Charles University Prague, 12800 Prague, Czech Republic
- Department of Informatics, Bioengineering, Robotics and System Engineering, University of Genoa, 16145 Genoa, Italy
- Faculty European Campus Rottal-Inn, Deggendorf Institute of Technology, 94469 Deggendorf, Germany
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Denecke K, May R, Rivera-Romero O. Transformer Models in Healthcare: A Survey and Thematic Analysis of Potentials, Shortcomings and Risks. J Med Syst 2024; 48:23. [PMID: 38367119 PMCID: PMC10874304 DOI: 10.1007/s10916-024-02043-5] [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: 11/17/2023] [Accepted: 02/10/2024] [Indexed: 02/19/2024]
Abstract
Large Language Models (LLMs) such as General Pretrained Transformer (GPT) and Bidirectional Encoder Representations from Transformers (BERT), which use transformer model architectures, have significantly advanced artificial intelligence and natural language processing. Recognized for their ability to capture associative relationships between words based on shared context, these models are poised to transform healthcare by improving diagnostic accuracy, tailoring treatment plans, and predicting patient outcomes. However, there are multiple risks and potentially unintended consequences associated with their use in healthcare applications. This study, conducted with 28 participants using a qualitative approach, explores the benefits, shortcomings, and risks of using transformer models in healthcare. It analyses responses to seven open-ended questions using a simplified thematic analysis. Our research reveals seven benefits, including improved operational efficiency, optimized processes and refined clinical documentation. Despite these benefits, there are significant concerns about the introduction of bias, auditability issues and privacy risks. Challenges include the need for specialized expertise, the emergence of ethical dilemmas and the potential reduction in the human element of patient care. For the medical profession, risks include the impact on employment, changes in the patient-doctor dynamic, and the need for extensive training in both system operation and data interpretation.
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Affiliation(s)
- Kerstin Denecke
- Institute Patient-centered Digital Health, Bern University of Applied Sciences, Quellgasse 21, Biel, 2502, Switzerland.
| | - Richard May
- Harz University of Applied Sciences, Friedrichstraße 57-59, 38855, Wernigerode, Germany
| | - Octavio Rivera-Romero
- Instituto de Ingeniería Informática (I3US), Universidad de Sevilla, Sevilla, Spain
- Department of Electronic Technology, Universidad de Sevilla, Avda Reina Mercedes s/n, ETSI Informática, G1.43, Sevilla, 41012, Spain
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