Methods to evaluate perspectives of safety, independence, activity, and participation in older persons using welfare technology. A systematic review

References

• Wilhelmson K, Andersson C, Waern M. Elderly people’s perspectives on quality of life. Ageing Soc. 2005;25:585–600.
   Google Scholar
• Gooberman-Hill R, Ebrahim S. Making decisions about simple interventions: older people’s use of walking aids. Age Ageing. 2007;36:569–573.
   Google Scholar
• Wiles JL, Leibing A, Guberman N. The meaning of “aging in place” to older people. Gerontologist. 2012;52:357–366.
   Google Scholar
• Ministry of Health and Social Affairs. Socialtjchront/gn [Social Act] (2001:453).
   Google Scholar
• Larsson K. Kvarboende eller flyttning pl älytt dagar. En kunskapsgeront/g. Stockholm: Stiftelsen Stockholms Ltoc Ätockholmsro; 2006.
   Google Scholar
• United Nations Department of Economic and Social Affairs, Population Division. World population ageing 2015. (ST/ESA/SER.A/390) [cited 2018 June 26]. Available from: http://www.un.org/en/development/desa/population/publications/pdf/ageing/WPA2015_Report.pdf.
   Google Scholar
• Creighton H. Europeto ageing demography. 2014 [cited 2018 June 5]. Available from: http://www.ilcuk.org.uk/files/Europes_Ageing_Demography.pdf.
   Google Scholar
• Ministry of Health and Social Affairs. Den ljusnande framtid är vramt Delresultat frlr LEV-projektet Stockholm: Regeringskansliet; 2010 [cited 2018 march 16]. Available from: http://www.regeringen.se/contentassets/9bd244e4a3e047518b1badf231ba98ef/denljusnande-framtid-ar-vard—delresultat-fran-lev-projektet
   Google Scholar
• Great Summit Report. Geneva (Switzerland): World Health Organization; 2017.
   Google Scholar
• Nordic Centre for Welfare and Social Issues. Velferdsteknologi [Welfare Technology]. [cited 2018 Oct 23] Available from: http://www.nordicwelfare.org/PageFiles/5488/Velferdsteknologi_eng.pdf.
   Google Scholar
• Cozza M. Interoperability and convergence for welfare technology. In: Zhou J, Salvendy G, editor. Human aspects of IT for the aged population applications in health, assistance, and entertainment ITAP 2018. Cham (Switzerland): Springer; 2018. p. 13–24.
   Google Scholar
• Cozza M, Crevani L, Hallin A, et al. Future ageing: welfare technology practices for our future older selves. Futures. 2018. DOI: 10.1016/j.futures.2018.03.011
   Google Scholar
• The National Board of Health and Welfare. Ehlfar och vchlsaelechnol i kommunerna [E-health and welfare technology within municipalities]. Stockholm (Sweden): The National Board of Health and Welfare; 2016.
   Google Scholar
• The Swedish Agency for Participation. Exempel px digital teknik. 2017 [cited 2018 Jan 12]. Available from: http://www.mfd.se/kunskapsomraden/digital-teknik/om-digital-teknik/vad-innebar-digital-teknik/valfardsteknologi/
   Google Scholar
• The National Board of Health and Welfare. Hjälpmedel i kommuner och landsting – en nationell kartläggning av regler, avgifter, tillgång och förskrivning. Stockholm (Sweden): The National Board of Health and Welfare; 2015.
   Google Scholar
• Agree EM. The potential for technology to enhance independence for those aging with a disability. Disabil Health J. 2014;7:S33–S39.
   Google Scholar
• Carswell W, McCullagh PJ, Augusto JC, et al. A review of the role of assistive technology for people with dementia in the hours of darkness. Technol Health Care. 2009;17:281–304.
   Google Scholar
• Nordic Welfare Centre. Focus on welfare technology. 2010 [cited. 2018 Jun 05]. Available from: http://nvc.brandfactory.se/Files/sv-SE/9047/RelatedFiles/Velferdsteknologi_eng.pdf.
   Google Scholar
• Kachouie R, Sedighadeli S, Khosla R, et al. Socially assistive robots in elderly care: a mixed-method systematic literature review. Int J Hum–nt J Humassistive. 2014;30:369–393.
   Google Scholar
• Pot AM, Willemse BM, Horjus S. A pilot study on the use of tracking technology: feasibility, acceptability, and benefits for people in early stages of dementia and their informal caregivers. Ageing Ment Health. 2012;16:127–134.
   Google Scholar
• Mitzner TL, Chen TL, Kemp CC, et al. Identifying the potential for robotics to assist older adults in different living environments. Int J Soc Robot. 2014;6:213–227.
   Google Scholar
• Khosravi P, Ghapanchi AH. Investigating the effectiveness of technologies applied to assist seniors: a systematic literature review. Int J Med Inform. 2016 Jan;85:17–26.
   Google Scholar
• The National Board of Health and Welfare. Termbanken. 2015 [cited 2018Jan12]. Available from: http://termbank.socialstyrelsen.se/showterm.php?fTid=798.
   Google Scholar
• Merriam-Webster. Safety [Dictionary]. [cited 2018 Apr 20] https://www.merriam-webster.com/dictionary/safety.
   Google Scholar
• World Health Organisation. Safety and safety promotion: conceptual and operational aspects. Quebec (Canada): WHO; 1998.
   Google Scholar
• World Health Organization. International classification of functioning, disability and health (ICF). Geneva (Switzerland): World Health Organization; 2001.
   Google Scholar
• Bailey C, Foran TG, Ni Scanaill C, et al. Older adults, falls and technologies for independent living: a life space approach. Ageing Soc. 2011;31:829–848.
   Google Scholar
• Hillcoat-Nalletamby S. The meaning of “independence” for older people in different residential settings. J Gerontol B Psychol Sci Soc Sci. 2014;69:419–430.
   Google Scholar
• Secker J, Hill R, Villeneau L, et al. Promoting independence: but promoting what and how? Ageing Soc. 2003;23:375–391.
   Google Scholar
• Harris F. Conceptual issues in the measurement of participation among wheeled mobility device users. Disabil Rehabil Assist Technol. 2007;2:137–148.
   Google Scholar
• Cook Hussey. The human, activity, assistive technology model. In: Cook AM, Hussey S, editors. Assistive technologies: principles and practice. St. Louis (MO): Mosby Elsevier; 1995.
   Google Scholar
• Brandt A, Iwarsson S. Development of an instrument for assessment of mobility-related participation outcomes: the NOMO 1.0. Technol Disabil. 2012;24:293–301.
   Google Scholar
• Salminen AL, Brandt A, Samuelsson K, et al. Mobility devices to promote activity and participation: a systematic review. J Rehabil Med. 2009;41:697–706.
   Google Scholar
• Higgins JPT, Green S. Cochrane handbook for systematic reviews of interventions version 5.1.0 [updated March 2011]: The Cochrane Collaboration; 2011. Available from: http://handbook-5-1.cochrane.org/
   Google Scholar
• Liberati A, Altman DG, Tetzlaff J, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS Med. 2009;6:e1000100.
   Google Scholar
• Agree EM, Freedman VA. A quality-of-life scale for assistive technology: results of a pilot study of aging and technology. Phys Ther. 2011;91:1780–1788.
   Google Scholar
• Bradley N, Poppen W. Assistive technology, computers and internet may decrease sense of isolation for homebound elderly and disabled persons. Technol Disabil. 2003;15:19–25.
   Google Scholar
• Chumbler NR, Quigley P, Li X, et al. Effects of telerehabilitation on physical function and disability for stroke patients: a randomized, controlled trial. Stroke. 2012;43:2168–2174.
   Google Scholar
• Chumbler NR, Rose D, Li X, et al. Home-based telerehabilitation randomized trial for stroke care: effects on falls self-efficacy and satisfaction with care. IEEE. 2014;11:4364-ba.
   Google Scholar
• Damant J, Knapp M, Watters S, et al. The impact of ICT services on perceptions of the quality of life of older people. J Assist Technol. 2013;7:5–21.
   Google Scholar
• Gigler KL, Blomeke K, Shatil E, et al. Preliminary evidence for the feasibility of at-home online cognitive training with older adults. Gerontechnology. 2013;12:26–35.
   Google Scholar
• Hattink BJJ, Meiland FJM, Overmars-Marx T, et al. The electronic, personalizable Rosetta system for dementia care: exploring the user-friendliness, usefulness and impact. Disabil Rehabil Assist Technol. 2016;11:61–71.
   Google Scholar
• Hirani SP, Beynon M, Cartwright M, et al. The effect of telecare on the quality of life and psychological well-being of elderly recipients of social care over a 12-month period: the whole systems demonstrator cluster randomised trial. Age Ageing. 2014;43:334–341.
   Google Scholar
• Horowitz A, Brennan M, Reinhardt JP, et al. The impact of assistive device use on disability and depression among older adults with age-related vision impairments. J Gerontol B Psychol Sci Soc Sci. 2006;61:S274–S280.
   Google Scholar
• Igual R, Plaza I, Medrano C, et al. Personalizable smartphone-based system adapted to assist dependent people. J Ambient Intell Smart Environ. 2014;6:569–593.
   Google Scholar
• Kerssens C, Kumar R, Adams AE, et al. Personalized technology to support older adults with and without cognitive impairment living at home. Am J Alzheimers Dis Other Demen. 2015;30:85–97.
   Google Scholar
• Lexis M, Everink I, Van Der Heide L, et al. Activity monitoring technology to support homecare delivery to frail and psychogeriatric elderly persons living at home alone. Technol Disabil. 2013;25:189–197.
   Google Scholar
• Linder SM, Rosenfeldt AB, Reiss A, et al. The home stroke rehabilitation and monitoring system trial: a randomized controlled trial. Int J Stroke. 2013;8:46–53.
   Google Scholar
• Linder SM, Rosenfeldt AB, Bay RC, et al. Improving quality of life and depression after stroke through telerehabilitation. Am J Occup Ther. 2015;69:6902290020p1–690229002010.
   Google Scholar
• Lindqvist E, Borell L. Computer-based assistive technology and changes in daily living after stroke. Disabil Rehabil Assist Technol. 2012;7:364–371.
   Google Scholar
• Lindqvist E, Larsson TJ, Borell L. Experienced usability of assistive technology for cognitive support with respect to user goals. Neurorehabilitation. 2015;36:135–149.
   Google Scholar
• Meiland FJM, Bouman AIE, S Eman f]iS, et al. Usability of a new electronic assistive device for community-dwelling persons with mild dementia. Aging Ment Health. 2012;16:584–591.
   Google Scholar
• Nijenhuis SM, Prange GB, Amirabdollahian F, et al. Feasibility study into self-administered training at home using an arm and hand device with motivational gaming environment in chronic stroke. J Neuroeng Rehabil. 2015;12:1–12.
   Google Scholar
• Pol M, van Nes F, van Hartingsveldt M, et al. Older people’s perspectives regarding the use of sensor monitoring in their home. Gerontologist. 2016;56:485–493.
   Google Scholar
• Pripfl J, K ipfl iT, Batko-Klein D, et al. Social service robots to support independent living: experiences from. Z Gerontol Geriatr. 2016;49:282–287.
   Google Scholar
• Pripfl J, K ipfl dT, Batko-Klein D, et al. Results of a real world trial with a mobile social service robot for older adults. International Conference on HRI, Late Breaking Reports, IEEE – ACM Digital Library, 2016; Christchurch, New Zealand.
   Google Scholar
• Siegel C, Prazak-Aram B, Kropf J, et al. Evaluation of a modular scalable system for silver-ager located in assisted living homes in Austria – study protocol of the ModuLAAr ambient assisted living project. BMC Public Health. 2014;14:736–736.
   Google Scholar
• Silveira P, van de Langenberg R, van Het Reve E, et al. Tablet-based strength-balance training to motivate and improve adherence to exercise in independently living older people: a phase ii preclinical exploratory trial. J Med Internet Res. 2013;15:e159.
   Google Scholar
• van der Heide LA, Willems CG, Spreeuwenberg MD, et al. Implementation of CareTV in care for the elderly: the effects on feelings of loneliness and safety and future challenges. Technol Disabil. 2012;24:283–291.
   Google Scholar
• van Hoof J, Kort HS, Rutten PG, et al. Ageing-in-place with the use of ambient intelligence technology: perspectives of older users. Int J Med Inform. 2011;80:310–331.
   Google Scholar
• Willner V, Schneider C, Feichtenschlager M. eHealth 2015 special issue: effects of an assistance service on the quality of life of elderly users. Appl Clin Inform. 2015;6:429–442.
   Google Scholar
• Critical Appraisal Skills Programme. CASP cohort study checklist 2017 [cited 2017 May 29]. Available from: http://docs.wixstatic.com/ugd/dded87_5ad0ece77a3f4fc9bcd3665a7d1fa91f.pdf.
   Google Scholar
• Critical Appraisal Skills Programme. CASP qualitative research checklist 2017 [cited 2017 May 29]. Available from: http://docs.wixstatic.com/ugd/dded87_25658615020e427da194a325e7773d42.pdf.
   Google Scholar
• Steventon A, Bardsley M, Billings J, et al. Effect of telecare on use of health and social care services: findings from the whole systems demonstrator cluster randomised trial. Age Ageing. 2013;42:501–508.
   Google Scholar
• Wolf SL, Sahu K, Bay RC, et al. The HAAPI (home arm assistance progression initiative) trial: a novel robotics delivery approach in stroke rehabilitation. Neurorehabil Neural Repair. 2015;29:958–968.
   Google Scholar
• Haji SA, Sambhav K, Grover S, et al. Evaluation of the iPad as a low vision aid for improving reading ability. Clin Ophthalmol. 2015;9:17–20.
   Google Scholar
• Feldwieser F, Marchollek M, Meis M, et al. Acceptance of seniors towards automatic in home fall detection devices. J Assist Technol. 2016;10:178–186.
   Google Scholar
• Tchalla AE, Lachal F, Cardinaud N, et al. Efficacy of simple home-based technologies combined with a monitoring assistive center in decreasing falls in a frail elderly population (results of the Esoppe study). Arch Gerontol Geriatr. 2012;55:683–689.
   Google Scholar
• Stel VS, Pluijm SM, Deeg DJ, et al. A classification tree for predicting recurrent falling in community-dwelling older persons. J Am Geriatr Soc. 2003;51:1356–1364.
   Google Scholar
• Lachman ME, Howland J, Tennstedt S, et al. Fear of falling and activity restriction: the survey of activities and fear of falling in the elderly (SAFE). J Gerontol B Psychol Sci Soc Sci. 1998;53:P43–P50.
   Google Scholar
• Tinetti ME, Richman D, Powell L. Falls efficacy as a measure of fear of falling. J Gerontol. 1990;45:239–243.
   Google Scholar
• Hill H, McMeekin P, Parry SW. Does the falls efficacy scale international version measure fear of falling: a reassessment of internal validity using a factor analytic approach. Age Ageing. 2014;43:559–562.
   Google Scholar
• Yardley L, Beyer N, Hauer K, et al. Development and initial validation of the falls efficacy scale-international (FES-I). Age Ageing. 2005;34:614–619.
   Google Scholar
• Lawton M, Brody E. Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist. 1969;9:179–186.
   Google Scholar
• Graf C. The Lawton instrumental activities of daily living scale. Am J Nurs. 2008;108:52–62.
   Google Scholar
• Orgeta V, Lo Sterzo E, Orrell M. Assessing mental well-being in family carers of people with dementia using the Warwick–Edinburgh mental well-being scale. Int Psychogeriatr. 2013;25:1–5.
   Google Scholar
• Stewart-Brown SL, Platt S, Tennant A, et al. The Warwick–Edinburgh mental well-being scale (WEMWBS): a valid and reliable tool for measuring mental well-being in diverse populations and projects. J Epidemiol Community Health. 2011;65:A38–A39.
   Google Scholar
• Diehl MK, Marsiske M, Horgas AL, et al. The revised observed tasks of daily living: a performance-based assessment of everyday problem solving in older adults. J Appl Gerontol. 2005;24:211–230.
   Google Scholar
• Fugl-Meyer AR, Jaasko L, Norlin V. The post-stroke hemiplegic patient. II. Incidence, mortality, and vocational return in Goteborg, Sweden with a review of the literature. Scand J Rehabil Med, Suppl. 1975;7:73–83.
   Google Scholar
• Gladstone DJ, Danells CJ, Black SE. The Fugl-Meyer assessment of motor recovery after stroke: a critical review of its measurement properties. Neurorehabil Neural Repair. 2002;16:232–240.
   Google Scholar
• Deakin A, Hill H, Pomeroy VM. Rough guide to the Fugl–Meyer assessment: upper limb section. Physiotherapy. 2003;89:751–763.
   Google Scholar
• Sayers SP, Jette AM, Haley SM, et al. Validation of the late-life function and disability instrument. J Am Geriatr Soc. 2004;52:1554–1559.
   Google Scholar
• Hand C, Richardson J, Letts L, et al. Construct validity of the late life function and disability instrument for adults with chronic conditions. Disabil Rehabil. 2010;32:50–56.
   Google Scholar
• Skavberg Roaldsen K, Halvarsson A, Sarlija B, et al. Self-reported function and disability in late life – cross-cultural adaptation and validation of the Swedish version of the late-life function and disability instrument. Disabil Rehabil. 2014;36:813–817.
   Google Scholar
• Smith PM, Illig SB, Fiedler RC, et al. Intermodal agreement of follow-up telephone functional assessment using the functional independence measure in patients with stroke. Arch Phys Med Rehabil. 1996;77:431–435.
   Google Scholar
• Fillenbaum GG. Multidimensional functional assessment of older adults: the Duke older Americans resources and services procedures. Hilldale (NJ): Lawrence Erlbaum Publishers; 1998.
   Google Scholar
• Cox Collier I. Assessing functional status of the elderly. Rev Lit. 1988;1:45–52.
   Google Scholar
• van der Lee JH, Beckerman H, Knol DL, et al. Clinimetric properties of the motor activity log for the assessment of arm use in hemiparetic patients. Stroke. 2004;35:1410–1414.
   Google Scholar
• Winstein CJ, Miller JP, Blanton S, et al. Methods for a multisite randomized trial to investigate the effect of constraint-induced movement therapy in improving upper extremity function among adults recovering from a cerebrovascular stroke. Neurorehabil Neural Repair. 2003;17:137–152.
   Google Scholar
• Morris DM, Uswatte G, Crago JE, et al. The reliability of the wolf motor function test for assessing upper extremity function after stroke. Arch Phys Med Rehabil. 2001;82:750–755.
   Google Scholar
• Wolf SL, Catlin PA, Ellis M, et al. Assessing Wolf motor function test as outcome measure for research in patients after stroke. Stroke. 2001;32:1635–1639.
   Google Scholar
• Yozbatiran N, Der-Yeghiaian L, Cramer SC. A standardized approach to performing the action research arm test. Neurorehabil Neural Repair. 2008;22:78–90.
   Google Scholar
• Platz T, Pinkowski C, van Wijck F, et al. Reliability and validity of arm function assessment with standardized guidelines for the Fugl-Meyer test, action research arm test and box and block test: a multicentre study. Clin Rehabil. 2005;19:404–411.
   Google Scholar
• Hsieh CL, Hsueh IP, Chiang FM, et al. Inter-rater reliability and validity of the action research arm test in stroke patients. Age Ageing. 1998;27:107–113.
   Google Scholar
• Reynolds T, Thornicroft G, Abas M, et al. Camberwell assessment of need for the elderly (CANE). Development, validity and reliability. Br J Psychiatry. 2000;176:444–452.
   Google Scholar
• Finch AP, Brazier JE, Mukuria C. What is the evidence for the performance of generic preference-based measures? A systematic overview of reviews. Eur J Health Econ. 2017; 19(4):557–570.
   Google Scholar
• Ware JE, Kosinski M, Keller SD. SF-12: how to score the SF-12 physical and mental health summary scores. Boston (MA): The Health Institute, New England Medical Center; 1995.
   Google Scholar
• Ware JE Jr, Koskinski M, Turner-Bowker DM, et al. Userer manual for the SF-12v2 health survey with a supplement documenting SF-12 health survey. Lincoln (RI): Quality Metric Incorporated; 2002.
   Google Scholar
• Brod M, Stewart AL, Sands L, et al. Conceptualization and measurement of quality of life in dementia: the dementia quality of life instrument (DQOL). Gerontologist. 1999;39:25–35.
   Google Scholar
• Logsdon RG, Gibbons LE, McCurry SM, et al. Assessing quality of life in older adults with cognitive impairment. Psychosom Med. 2002;64:510–519.
   Google Scholar
• Selai CE, Trimble MR, Rossor MN, et al. The quality of life assessment schedule (QOLAS) – a new method for assessing quality of life (QOL) in dementia. In: Albert SM, Logsdon RG, editors. Assessing quality of life in Alzheimerta disease. New York (NY): Springer Publishing Company; 2000. p. 31–48.
   Google Scholar
• WHO Division of Mental Health and Prevention of Substance Abuse. WHOQOL – measuring quality of life; 1997.
   Google Scholar
• The WHO Quality of Life Group. WHOQOL-100. World Health Organisation quality of life instrument. Geneva (Switzerland): The WHO Quality of Life Group, Division of Mental Health; 1998.
   Google Scholar
• Chachamovich E, Fleck MP, Trentini C, et al. Brazilian WHOQOL-OLD module version: a Rasch analysis of a new instrument. Rev Saúde Pública. 2008;42:308–316.
   Google Scholar
• Fleck MP, Chachamovich E, Trentini C. Development and validation of the Portuguese version of the WHOQOL-OLD module. Rev Saude Publica. 2006;40:785–791.
   Google Scholar
• Eser S, Saatli G, Eser E. The reliability and validity of the Turkish version of the World Health Organization quality of life instrument e > Eduardadults module (WHOQOL-Old). Turk J Psychiatr. 2010;21:37–48.
   Google Scholar
• Halvorsrud L, Kalfoss M, Diseth A. Reliability and validity of the Norwegian WHOQOL-OLD module. Scand J Caring Sci. 2008;22:292–305.
   Google Scholar
• Bowling A. The psychometric properties of the older peoples quality of life questionnaire, compared with the CASP-19 and the WHOQOL-OLD. Curr Gerontol Geriatr Res. 2009;2009:1.
   Google Scholar
• Duncan PW, Wallace D, Lai SM, et al. The stroke impact scale version 2.0. Evaluation of reliability, validity, and sensitivity to change. Stroke. 1999;30:2131–2140.
   Google Scholar
• Van Leeuwen KM, Bosmans JE, Jansen ADP, et al. Comparing measurement properties of the EQ-5D-3L, ICECAP-O, and ASCOT in frail older adults. Value Health. 2015;18:35–43.
   Google Scholar
• Coast J, Flynn T, Natarajan L, et al. Valuing the ICECAP capability index for older people. Soc Sci Med. 2008;67:874–882.
   Google Scholar
• Woods B. Promoting well-being and independence for people with dementia. Int J Geriatr Psychiatry. 1999;14:97–105.
   Google Scholar
• Nilsen P, Hudson DS, Kullberg A, et al. Making sense of safety. Inj Prev. 2004;10:71–73.
   Google Scholar
• Levasseur M, Desrosiers J, Whiteneck G. Accomplishment level and satisfaction with social participation of older adults: association with quality of life and best correlates. Qual Life Res. 2010;19:665–675.
   Google Scholar
• Perenboom RJ, Chorus AM. Measuring participation according to the international classification of functioning, disability and health (ICF). Disabil Rehabil. 2003;25:577–587.
   Google Scholar
• Jette AM, Haley SM, Kooyoomjian JT. Are the ICF activity and participation dimensions distinct? J Rehabil Med. 2003;35:145–149.
   Google Scholar
• Jette AM, Tao W, Haley SM. Blending activity and participation sub-domains of the ICF. Disabil Rehabil. 2007;29:1742–1750.
   Google Scholar
• Pettersson I, Ahlstrss G, T lstrsso K. The value of an outdoor powered wheelchair with regard to the quality of life of persons with stroke: a follow-up study. Assist Technol. 2007;19:143–153.
   Google Scholar
• Korczyn AD, Davidson M. Quality of life in Alzheimer’s disease. Eur J Neurol. 1999;6:487–489.
   Google Scholar
• Silva SM, Correa FI, Pereira GS, et al. Construct validity of the items on the stroke specific quality of life (SS-QOL) questionnaire that evaluate the participation component of the international classification of functioning, disability and health. Disabil Rehabil. 2018;40:225–231.
   Google Scholar
• Boger J, Quraishi M, Turcotte N, et al. The identification of assistive technologies being used to support the daily occupations of community-dwelling older adults with dementia: a cross-sectional pilot study. Disabil Rehabil Assist Technol. 2014;9:17–30.
   Google Scholar
• Bartneck C, Kulic D, Croft E, et al. Measurement instruments for the anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety of robots. Int J Soc Robotics. 2009;1:71–81.
   Google Scholar
• Koumpouros Y. A systematic review on existing measures for the subjective assessment of rehabilitation and assistive robot devices. J Healthc Eng. 2016;2016:1.
   Google Scholar
• Czarnuch S, Ricciardelli R, Mihailidis A. Predicting the role of assistive technologies in the lives of people with dementia using objective care recipient factors. BMC Geriatr. 2016;16:143.
   Google Scholar
• Doughty K, Williams G. New models of assessment and prescription of smart assisted living technologies for personalised support of older and disabled people. J Assist Technol. 2016;10:39–50.
   Google Scholar
• Desmond D, Layton N, Bentley J, et al. Assistive technology and people: a position paper from the first global research, innovation and education on assistive technology (GREAT) summit. Disabil Rehabil Assist Technol. 2018;13:437–444.
   Google Scholar
• Prince M, Bryce R, Albanese E, et al. The global prevalence of dementia: a systematic review and metaanalysis. Alzheimers Dement. 2013;9:63–75.
   Google Scholar
• Ripat J, Woodgate R. The intersection of culture, disability and assistive technology. Disabil Rehabil Assist Technol. 2011;6:87–96.
   Google Scholar
• Meiland FJM, DrMla RM. Experienced autonomy list. Amsterdam (The Netherlands): VU University Medical Center; 2006.
   Google Scholar
• Miedema I, Ormel J, Molenaar W. The assessment of disability with the Groningen activity restriction scale. Conceptual framework and psychometric properties. Soc Sci Med. 1996;43:1601–1610.
   Google Scholar
• Kempen GIJM, Doeglas DM, Stuurmeijer TPBM. Measuring problems concerning self-reliance on caring and domestic tasks with the Groninger activity restriction scale (GARS). A manual. Groningen (The Netherlands): Northern Centre for Health Care Research; 1993.
   Google Scholar