| Literature DB >> 24715864 |
Philippe H Robert1, Alexandra König2, Hélene Amieva3, Sandrine Andrieu4, François Bremond5, Roger Bullock6, Mathieu Ceccaldi7, Bruno Dubois8, Serge Gauthier9, Paul-Ariel Kenigsberg10, Stéphane Nave11, Jean M Orgogozo12, Julie Piano13, Michel Benoit14, Jacques Touchon15, Bruno Vellas16, Jerome Yesavage17, Valeria Manera14.
Abstract
Alzheimer's disease and other related disorders (ADRD) represent a major challenge for health care systems within the aging population. It is therefore important to develop better instruments to assess the disease severity and progression, as well as to improve its treatment, stimulation, and rehabilitation. This is the underlying idea for the development of Serious Games (SG). These are digital applications specially adapted for purposes other than entertaining; such as rehabilitation, training and education. Recently, there has been an increase of interest in the use of SG targeting patients with ADRD. However, this field is completely uncharted, and the clinical, ethical, economic and research impact of the employment of SG in these target populations has never been systematically addressed. The aim of this paper is to systematically analyze the Strengths, Weaknesses, Opportunities, and Threats (SWOT) of employing SG with patients with ADRD in order to provide practical recommendations for the development and use of SG in these populations. These analyses and recommendations were gathered, commented on and validated during a 2-round workshop in the context of the 2013 Clinical Trial of Alzheimer's Disease (CTAD) conference, and endorsed by stakeholders in the field. The results revealed that SG may offer very useful tools for professionals involved in the care of patients suffering from ADRD. However, more interdisciplinary work should be done in order to create SG specifically targeting these populations. Furthermore, in order to acquire more academic and professional credibility and acceptance, it will be necessary to invest more in research targeting efficacy and feasibility. Finally, the emerging ethical challenges should be considered a priority.Entities:
Keywords: Alzheimer's disease; SWOT analysis; frailty; mild cognitive impairment; non pharmacological treatment; recommendations; rehabilitation; serious games
Year: 2014 PMID: 24715864 PMCID: PMC3970032 DOI: 10.3389/fnagi.2014.00054
Source DB: PubMed Journal: Front Aging Neurosci ISSN: 1663-4365 Impact factor: 5.750
Questions for recommendation session.
| SG for |
| SG for |
Summary of a SWOT analysis of the use of SG in ADRD.
| Interface adapted to the user | Interface challenges |
| Gaming factors to enhance motivation, positive mood and improve assessment | Non-naturalistic interactions |
| Wires and displays | |
| Independent practice and self-assessment | Immature engineering process |
| Safe testing and training environment | Expensive equipment |
| Promoting social bonding | Poor platform compatibility |
| Enhanced ecological validity | Software difficult to use |
| Control of stimulus delivery | Lack of generalization |
| Cuing stimuli for error-free learning | Addiction |
| Performance analysis in real time | Side effects |
| Real-time feedback delivery | |
| Promoting learning processes | |
| Low-cost, duplicable environments | |
| Emerging advances in technology | Ethical challenges |
| Real time data analysis | Poor integration with the clinical practice |
| Gaming industry drivers | Lack of assessment methodology |
| Intuitive appeal to the public | Lack of feasibility and efficacy studies |
| New professions | Lack of regulation |
| Closeness between scientific, technical, and clinical communities | Lack of business model |
| Too few cost/benefit proofs | |
| SG as research instruments | Technological vs. clinical tool |
| Telerehabilitation | Aftereffects |
| Big market | The perception that the technological tools will eliminate the need for the clinician |
| Unrealistic expectations | |
| Academic and professional acceptance | |
| Technophobia |
Figure 1Results of the recommendation questions. Mean ratings provided by participants of round 1 of the recommendation session and participants of the online survey to the two general questions (light gray) and the four questions focused on ADRD (dark gray). Rating scale: 0–3 scale (0, not adapted at all; 1, not very adapted; 2, adapted; 3, very adapted).