Models and frameworks for guiding assessment for aided Augmentative and Alternative communication (AAC): a scoping review

References

• Health Topics: Assistive Technology: World Health Organization. 2021. https://www.who.int/health-topics/assistive-technology#tab=tab
   Google Scholar
• Assistive Technology: World Health Organization. 2018. https://www.who.int/news-room/fact-sheets/detail/assistive-technology
   Google Scholar
• International Classification of Functioning, Disability and Health (ICF): World Health Organization. 2001. https://www.who.int/standards/classifications/international-classification-of-functioning-disability-and-health
   Google Scholar
• Hersh MA, Johnson MA. On modelling assistive technology systems – part I: modelling framework. TAD. 2008;20(3):193–215. doi:10.3233/TAD-2008-20303.
   Google Scholar
• Lancioni GE, Sigafoos J, O'Reilly MF, et al. Defining assistive technology and the target populations. In: Assistive technology. New York (NY): Springer New York; 2012. p. 1–9. doi:10.1007/978-1-4614-4229-5_1.
   Google Scholar
• Augmentative and Alternative Communication: American Speech-Language-Hearing Association (ASHA). https://www.asha.org/practice-portal/professional-issues/augmentative-and-alternative-communication/
   Google Scholar
• Beukelman D, Light J. Augmentative and alternative communication: supporting children and adults with complex communication needs. 5th ed. (Co. BP, editor.). Paul H. Brookes Publishers; 2020.
   Google Scholar
• McNaughton D, Bryen DN. AAC technologies to enhance participation and access to meaningful societal roles for adolescents and adults with developmental disabilities who require AAC. Augment Altern Commun. 2007;23(3):217–229. doi:10.1080/07434610701573856.
   PubMed Web of Science ®Google Scholar
• Burkhart LJ. What is AAC?: international Society for Augmentative and Alternative Communication. 2021. https://isaac-online.org/english/what-is-aac/
   Google Scholar
• Beukelman DR, Mirenda P. Augmentative and alternative communication: supporting children and adults with complex communication needs. 4th ed. Baltimore (MD): Paul H. Brookes Publishing Co.; 2013.
   Google Scholar
• Pitt KM, Brumberg JS. Guidelines for feature matching assessment of brain-computer interfaces for augmentative and alternative communication. Am J Speech Lang Pathol. 2018;27(3):950–964. doi:10.1044/2018_AJSLP-17-0135.
   PubMed Web of Science ®Google Scholar
• Federici S, Scherer MJ. Assistive technology assessment handbook. Boca Raton (FL): Taylor & Francis; 2017.
   Google Scholar
• Varghese MS ,Pérez E ,Schwarz AL, editors. A decision support framework for augmentative and alternative communication device selection. In: 2019 Industrial and systems engineering conference. Orlando, FL: Norcross: institute of Industrial and Systems Engineers (IISE); 2019.
   Google Scholar
• Bernd T, Van Der Pijl D, De Witte LP. Existing models and instruments for the selection of assistive technology in rehabilitation practice. Scand J Occup Ther. 2009;16(3):146–158. doi:10.1080/11038120802449362.
   PubMed Web of Science ®Google Scholar
• Arthanat S, Bauer SM, Lenker JA. Conceptualization and measurement of assistive technology usability. Disab Rehabil Assist Technol. 2007;2(4):235–248.
   PubMedGoogle Scholar
• Federici S, Borsci S. Providing assistive technology in Italy: the perceived delivery process quality as affecting abandonment. Disab Rehabil Assist Technol. 2016;11(1):22–31.
   PubMed Web of Science ®Google Scholar
• Edyburn DL. Models, theories, and frameworks: contributions to understanding special education technology. Special Educ Technol Pract. 2001;4(1):16–24.
   Google Scholar
• Mavrou K, Hoogerwerf E-J, Meletiou-Mavrotheris M, et al. A conceptual framework related to ICT-AT competence development: the theoretical foundations of ENTELIS. Stud Health Technol Inform. 2015;217:664–670.
   PubMedGoogle Scholar
• Zabala J, editor. The SETT framework: critical areas to consider when making informed assistive technology decisions. In: Florida assistive technology impact conference and technology and media division of council for exceptional children, ERIC, Orlando, FL, 1995.
   Google Scholar
• Federici S ,Borsci S ,Mele ML, editors. Environmental evaluation of a rehabilitation aid interaction under the framework of the ideal model of assistive technology assessment process. Human-Computer interaction. In: Human-Centred Design Approaches, Methods, Tools, and Environments: 15th International Conference, HCI International 2013, Springer, Las Vegas, NV, Berlin, Germany. 2013.
   Google Scholar
• Hourcade J, Everhart Pilotte T, West E, et al. A history of augmentative and alternative communication for individuals with severe and profound disabilities. Focus Autism Other Dev Disabl. 2004;19(4):235–244. doi:10.1177/10883576040190040501.
   Google Scholar
• Lasker JP, Bedrosian JL. Promoting acceptance of augmentative and alternative communication by adults with acquired communication disorders. AAC Augment Alternat Commun. 2001;17:141–153.
   Google Scholar
• Lasker JP, Bedrosian JL. Acceptance of AAC by adults with acquired disorders. Augmentative and alternative communication for adults with acquired neurologic disorders. Augment Altern Commun. 2001;17(3):141–153. doi:10.1080/aac.17.3.141.153.
   Google Scholar
• Giesbrecht E. Application of the human activity assistive technology model for occupational therapy research. Aust Occup Ther J. 2013;60(4):230–240. doi:10.1111/1440-1630.12054.
   PubMed Web of Science ®Google Scholar
• Andersen TC. Individuals with disabilities, assistive computer technology, and empowerment: the human factors ProQuest Dissertations Publishing, University of Southern California. 1994.
   Google Scholar
• Lynch Y, Murray J, Moulam L, et al. Decision-making in communication aid recommendations in the UK: cultural and contextual influencers. Augment Altern Commun. 2019;35(3):180–192. doi:10.1080/07434618.2019.1599066.
   PubMed Web of Science ®Google Scholar
• Murray J, Lynch Y, Meredith S, et al. Professionals’ decision-making in recommending communication aids in the UK: competing considerations. Augment Altern Commun. 2019;35(3):167–179. doi:10.1080/07434618.2019.1597384.
   PubMed Web of Science ®Google Scholar
• Lenker JA, Paquet VL. A new conceptual model for assistive technology outcomes research and practice. Assist Technol. 2004;16(1):1–10. doi:10.1080/10400435.2004.10132069.
   PubMed Web of Science ®Google Scholar
• Ajzen I. Perceived behavioral control, Self-Efficacy, locus of control, and the theory of planned behavior. J Appl Soc Psychol. 2002;32(4):665–683. doi:10.1111/j.1559-1816.2002.tb00236.x.
   Web of Science ®Google Scholar
• Rogers EM. Diffusion of innovations. 4th ed. New York (NY): Free Press; 1995.
   Google Scholar
• Haynes S, Bruce C, Sanford J, editors. Model integrating assistive technology use and human performance for people with disabilities. In: Human Factors and Ergonomics Society Annual Meeting; 2009.
   Google Scholar
• Scherer MJ, Jutai JW, Fuhrer MJ, et al. A framework for modelling the selection of assistive technology devices (ATDs). Disab Rehabil Assist Technol. 2007;2(1):1–8.
   PubMedGoogle Scholar
• Lawton, M P, Nahemow, L, Tsong-Min-Yeh,. Neighborhood environment and the wellbeing of older tenants in planned housing.Int J Aging Hum Dev. 1980;11(3):211–227. doi:10.2190/2BQ7-71JT-V7NN-J9V6.
   PubMed Web of Science ®Google Scholar
• Bailey RW. Human performance engineering: using human factors/ergonomics to achieve computer system usability. 2nd ed. Englewood Cliffs (NJ): Prentice-Hall; 1989.
   Google Scholar
• Cook AM, Hussey SM. Assistive technologies: principles and practice. 2nd ed. St. Louis (MO): Mosby; 2002.
   Google Scholar
• Smith RO, editor. Assistive technology outcome assessment prototypes: measuring “INGO” variables of “outcomes. In Simpson R, editor. Proceedings of the RESNA 25th Annual Conference; 2002: Minneapolis: RESNA Press; 2002. p. 239–341.
   Google Scholar
• Fuhrer MJ, Jutai JW, Scherer MJ, et al. A framework for the conceptual modelling of assistive technology device outcomes. Disab Rehabil. 2003;25(22):1243–1251. doi:10.1080/09638280310001596207.
   PubMed Web of Science ®Google Scholar
• Aniyamuzaala JR, Layton N. International classification of functioning, disability and health and the convention on the rights of persons with disabilities as a framework for at classification and categorization. Technol Disabil. 2019;31(1 Suppl):S177–S182.
   Google Scholar
• Bartfai A, Boman I-L. A multiprofessional client-centred guide to implementing assistive technology for clients with cognitive impairments. TAD. 2014;26(1):11–21. doi:10.3233/TAD-140400.
   Google Scholar
• Light JC, Roberts B, Dimarco R, et al. Augmentative and alternative communication to support receptive and expressive communication for people with autism. J Commun Disord. 1998;31(2):153–180. doi:10.1016/s0021-9924(97)00087-7.
   PubMed Web of Science ®Google Scholar
• Steel E, Gelderblom GJ, de Witte LP. Development of an at selection tool using the ICF model. TAD. 2011;23(1):1–6. doi:10.3233/TAD-2011-0299.
   Google Scholar
• Beukelman DR, Mirenda P. Augmentative and alternative communication: management of severe communication disorders in children and adults. Baltimore (MD): Paul H. Brookes Publishing Co.; 1992.
   Google Scholar
• Scherer MJ. Matching person and technology. Webster, NY: Institute for Matching Person & Technology; 1998.
   Google Scholar
• Federici S, Scherer MJ. The assistive technology assessment model and basic definitions. In: Federici S, and Scherer MJ, editors. Assistive technology assessment handbook. Boca Raton (FL): CRC Press; 2012. p. 1–10.
   Google Scholar
• Scherer MJ, Craddock G. Matching person and technology (MPT) assessment process. TAD. 2002;14(3):125–131. doi:10.3233/TAD-2002-14308.
   Google Scholar
• EUSTAT Consortium. Go for it!: a manual for users of assistive technology. Milan: European Commission; 1999.
   Google Scholar
• de Witte LP, Knops H, Pyfers L, et al. European service delivery systems in rehabilitation technology: HEART line C. Hoensbroek: IRv, Institute for Rehabilitation Research; 1994.
   Google Scholar
• Choi BCK, Pak AWP. Multidisciplinarity, interdisciplinarity and transdisciplinarity in health research, services, education and policy: 1. Definitions, objectives, and evidence of effectiveness. Clin Ivestig Med. 2006;29(6):351–364.
   PubMed Web of Science ®Google Scholar
• How is AAC supported?: international Society for Augmentative and Alternative Communication; 2022. https://isaac-online.org/english/what-is-aac/how-is-aac-supported/
   Google Scholar
• Lenker JA, Paquet VL. A review of conceptual models for assistive technology outcomes research and practice. Assist Technol. 2003;15(1):1–15. doi:10.1080/10400435.2003.10131885.
   PubMed Web of Science ®Google Scholar
• Bromley BE, editor Assistive technology assessment: a comparative analysis of five models technology & persons with disabilities conference, Northridge (CA). 2001.
   Google Scholar
• Cook AM, Hussey SM. Assistive technologies: principles and practice. St. Louis (MO): Mosby; 1995.
   Google Scholar
• Cook AM, Polgar JM, Hussey SM. Cook & hussey’s assistive technologies: principles and practice 3. St. Louis (MO): Mosby Elsevier; 2008.
   Google Scholar
• Guevara A. The need to reimagine disability rights law because the medical model of disability fails us all. Wisconsin Law Rev. 2021;2021(2):269–292.
   Google Scholar
• Goering S. Rethinking disability: the social model of disability and chronic disease. Curr Rev Musculoskelet Med. 2015;8(2):134–138. doi:10.1007/s12178-015-9273-z.
   PubMed Web of Science ®Google Scholar
• Hogan AJ. Social and medical models of disability and mental health: evolution and renewal. CMAJ. 2019;191(1):E16–E18. doi:10.1503/cmaj.181008.
   PubMed Web of Science ®Google Scholar
• World Health Organization (WHO). Towards a Common Language for Functioning, Disability and Health: ICF. Geneva: World Health Organization; 2002.
   Google Scholar
• Batorowicz B, Shepherd TA. Teamwork in AAC: examining clinical perceptions. Augment Altern Commun. 2011;27(1):16–25. doi:10.3109/07434618.2010.546809.
   PubMed Web of Science ®Google Scholar
• Patel DR, Pratt HD, Patel ND. Team processes and team care for children with developmental disabilities. Pediatr Clin North Am. 2008;55(6):1375–1390, ix. doi:10.1016/j.pcl.2008.09.002.
   PubMed Web of Science ®Google Scholar
• Nash JM. Transdisciplinary training: key components and prerequisites for success. Am J Prev Med. 2008;35(2 Suppl):S133–S140. doi:10.1016/j.amepre.2008.05.004.
   PubMed Web of Science ®Google Scholar
• Batorowicz B, Shepherd TA. Measuring the quality of transdisciplinary teams. J Interprof Care. 2008;22(6):612–620. doi:10.1080/13561820802303664.
   PubMed Web of Science ®Google Scholar
• Angelo DH, Jones S, Kokoska S. Family perspective on augmentative and alternative communication: families of young children. Augment Altern Commun. 1995;11(3):193–202. doi:10.1080/07434619512331277319.
   Google Scholar
• King G, Batorowicz B, Shepherd TA. Expertise in research-informed clinical decision making: working effectively with families of children with little or no functional speech. Evid Based Commun Assess Intervent. 2008;2(2):106–116. doi:10.1080/17489530802296897.
   Google Scholar
• Angelo DH. Impact of augmentative and alternative communication devices on families. Augment Alternat Commun. 2000;16(1):37–47. doi:10.1080/07434610012331278894.
   Google Scholar
• Scherer MJ. Connecting to learn: educational and assistive technology for people with disabilities. 1st ed. Washington (DC): American Psychological Association; 2004.
   Google Scholar
• Scherer MJ. Living in the state of stuck: How assistive technology impacts the lives of people with disabilities. 4th ed. Brookline (MA): Brookline Books; 2005.
   Google Scholar
• Scherer MJ. Assistive technologies and other supports for people with brain impairment. New York (NY): Springer Pub Co.; 2012.
   Google Scholar
• Ebrahim RM, Razmi J, Haleh H. Scatter search algorithm for supplier selection and order lot sizing under multiple price discount environment. Adv. Eng. Softw. 2009;40(9):766–776. doi:10.1016/j.advengsoft.2009.02.003.
   Web of Science ®Google Scholar
• Pang K-W, Chan H-L. Data mining-based algorithm for storage location assignment in a randomised warehouse. Int. J. Prod. Res. 2017;55(14):4035–4052. doi: 10.1080/00207543.2016.1244615
   Web of Science ®Google Scholar
• Crosson B, Barco PP, Velozo CA, et al. Awareness and compensation in postacute head injury rehabilitation. Journal of Head Trauma Rehabilitation. 1989;4(3):46–54. doi: 10.1097/00001199-198909000-00008
   Google Scholar
• Roelands M, Van Oost P, Depoorter A, et al. A social-cognitive model to predict the use of assistive devices for mobility and self-care in elderly people. Gerontologist. 2002;42(1):39–50. doi: 10.1093/geront/42.1.3911815698
   PubMed Web of Science ®Google Scholar