Skip to content
BY 4.0 license Open Access Published by De Gruyter Open Access June 25, 2019

More than just friends: in-home use and design recommendations for sensing socially assistive robots (SARs) by older adults with depression

Natasha Randall EMAIL logo , Casey C. Bennett , Selma Šabanović , Shinichi Nagata , Lori Eldridge , Sawyer Collins and Jennifer A. Piatt

Abstract

As healthcare turns its focus to preventative community-based interventions, there is increasing interest in using in-home technology to support this goal. This study evaluates the design and use of socially assistive robots (SARs) and sensors as in-home therapeutic support for older adults with depression. The seal-like SAR Paro, along with onboard and wearable sensors, was placed in the homes of 10 older adults diagnosed with clinical depression for one month. Design workshops were conducted before and after the in-home implementation with participating older adults and clinical care staff members. Workshops showed older adults and clinicians sawseveral potential uses for robots and sensors to support in-home depression care. Long-term in-home use of the robot allowed researchers and participants to situate desired robot features in specific practices and experiences of daily life, and some user requests for functionality changed due to extended use. Sensor data showed that participants’ attitudes toward and intention to use the robot were strongly correlated with particular Circadian patterns (afternoon and evening) of robot use. Sensor data also showed that those without pets interacted with Paro significantly more than those with pets, and survey data showed they had more positive attitudes toward the SAR. Companionship, while a desired capability, emerged as insufficient to engage many older adults in long-term use of SARs in their home.

References

[1] E. Broadbent, R. Stafford, B. MacDonald, Acceptance of healthcare robots for the older population: Review and future directions, International Journal of Social Robotics, 2009, 1(4), 319– 33010.1007/s12369-009-0030-6Search in Google Scholar

[2] J. Broekens, M. Heerink, H. Rosendal, Assistive social robots in elderly care: a review, Gerontechnology, 2009, 8(2), 94–10310.4017/gt.2009.08.02.002.00Search in Google Scholar

[3] A. Tapus, M. J.Mataric, B. Scassellati, Socially assistive robotics [grand challenges of robotics], IEEE Robotics & Automation Magazine, 2007, 14(1) 35–4210.1109/MRA.2007.339605Search in Google Scholar

[4] C. C. Bennett, S. Sabanovic, J. A. Piatt, S. Nagata, L. Eldridge, N. Randall, A robot a day keeps the blues away, In: 2017 IEEE International Conference on Healthcare Informatics (ICHI), 2017, 536–54010.1109/ICHI.2017.43Search in Google Scholar

[5] H.-M. Gross et al., Robot companion for domestic health assistance: Implementation, test and case study under everyday conditions in private apartments, In: 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015, 5992–599910.1109/IROS.2015.7354230Search in Google Scholar

[6] Y. Kawaguchi, T. Shibata, K. Wada, The effects of robot therapy in the elderly facilities, Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 2010, 6(4), S13310.1016/j.jalz.2010.05.416Search in Google Scholar

[7] E. Torta et al., Evaluation of a small socially-assistive humanoid robot in intelligent homes for the care of the elderly, Journal of Intelligent & Robotic Systems, 2014 76(1), 57–7110.1007/s10846-013-0019-0Search in Google Scholar

[8] D. Fischinger et al., Hobbit, a care robot supporting independent living at home: First prototype and lessons learned, Robotics and Autonomous Systems, 2016, 75, 60–7810.1016/j.robot.2014.09.029Search in Google Scholar

[9] A. Coulourides Kogan, K. Wilber, L. Mosqueda, Moving toward implementation of person-centered care for older adults in community-based medical and social service settings: ‘You only get things done when working in concert with clients,’ Journal of the American Geriatrics Society, 2016, 64(1), e8–e1410.1111/jgs.13876Search in Google Scholar PubMed

[10] M. Dijkers, Community integration: conceptual issues and measurement approaches in rehabilitation research, Topics in Spinal Cord Injury Rehabilitation, 1998, 4(1), 1–1510.1310/BJJA-2018-45KL-0VTLSearch in Google Scholar

[11] S. A. Kolakowsky-Hayner, J. Wright, K. Shem, R. Medel, T. Duong, An effective community-based mentoring program for return to work and school after brain and spinal cord injury, NeuroRehabilitation, 2012, 31(1), 63–7310.3233/NRE-2012-0775Search in Google Scholar PubMed

[12] J. A. Piatt, M. Van Puymbroeck, M. Zahl, J. P. Rosenbluth, M. S. Wells, Examining how the perception of health can impact participation and autonomy among adults with spinal cord injury, Topics in Spinal Cord Injury Rehabilitation, 2016, 22(3), 165–17210.1310/sci2203-165Search in Google Scholar PubMed PubMed Central

[13] P. Ciechanowski et al., Community-integrated home-based depression treatment in older adults: a randomized controlled trial, Jama, 2004, 291(13), 1569–157710.1001/jama.291.13.1569Search in Google Scholar PubMed

[14] M. C. F. Plati, P. Covre, K. Lukasova, E. C. de Macedo, Depressive symptoms and cognitive performance of the elderly: relationship between institutionalization and activity programs, Revista Brasileira de Psiquiatria, 2006, 28(2), 118–12110.1590/S1516-44462006000200008Search in Google Scholar PubMed

[15] H. Robinson, B. MacDonald, N. Kerse, E. Broadbent, The psychosocial effects of a companion robot: a randomized controlled trial, Journal of the American Medical Directors Association, 2013, 14(9) 661–66710.1016/j.jamda.2013.02.007Search in Google Scholar PubMed

[16] A. Kristoffersson, A. M. Loutfi, S. Coradeschi, User-centered evaluation of robotic telepresence for an elderly population, In: 2nd International Workshop on Designing Robotic Artefacts with User-And Experience-Centered Perspectives, 2010Search in Google Scholar

[17] K. Wada, T. Shibata, T. Saito, K. Sakamoto, K. Tanie, Psychological and social effects of one year robot assisted activity on elderly people at a health service facility for the aged, In: Proceedings of the 2005 IEEE International Conference on Robotics and Automation (ICRA), 2005, 2785–2790Search in Google Scholar

[18] L. D. Riek, Healthcare robotics, Communications of the ACM, 2017, 60(11), 68–7810.1145/3127874Search in Google Scholar

[19] H. R. Lee et al., Steps toward participatory design of social robots: mutual learning with older adults with depression, In: 2017 12th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 2017, 244–25310.1145/2909824.3020237Search in Google Scholar

[20] S. Šabanović, W.-L. Chang, C. C. Bennett, J. A. Piatt, D. Hakken, A robot of my own: participatory design of socially assistive robots for independently living older adults diagnosed with depression, In: International Conference on Human Aspects of IT for the Aged Population, 2015, 104–11410.1007/978-3-319-20892-3_11Search in Google Scholar

[21] N. Randall, S. Šabanović, W. Chang, Engaging older adults with depression as co-designers of assistive in-home robots, In: Proceedings of the 12th EAI International Conference on Pervasive Computing Technologies for Healthcare, 2018, 304–30910.1145/3240925.3240946Search in Google Scholar

[22] M. R. DiMatteo, H. S. Lepper, T. W. Croghan, Depression is a risk factor for noncompliance with medical treatment: metaanalysis of the effects of anxiety and depression on patient adherence, Archives of Internal Medicine, 2000, 160(14), 2101– 210710.1001/archinte.160.14.2101Search in Google Scholar PubMed

[23] S. J. Bartels, J. A. Naslund, The underside of the silver tsunami – older adults and mental health care, New England Journal of Medicine, 2013, 368(6), 493–49610.1056/NEJMp1211456Search in Google Scholar PubMed

[24] A. T. Beekman, E. de Beurs, A. J. van Balkom, D. J. Deeg, R. van Dyck, W. van Tilburg, Anxiety and depression in later life: cooccurrence and communality of risk factors, American Journal of Psychiatry, 2000, 157(1), 89–9510.1176/ajp.157.1.89Search in Google Scholar PubMed

[25] K. B. Adams, S. Sanders, E. Auth, Loneliness and depression in independent living retirement communities: risk and resilience factors, Aging & Mental Health, 2004, 8(6), 475–48510.1080/13607860410001725054Search in Google Scholar PubMed

[26] K. M. Clark Cline, Psychological effects of dog ownership: Role strain, role enhancement, and depression, The Journal of Social Psychology, 2010, 150(2), 117–13110.1080/00224540903368533Search in Google Scholar PubMed

[27] T. Majić, H. Gutzmann, A. Heinz, U. E. Lang, M. A. Rapp, Animalassisted therapy and agitation and depression in nursing home residents with dementia: a matched case–control trial, The American Journal of Geriatric Psychiatry, 2013, 21(11), 1052– 105910.1016/j.jagp.2013.03.004Search in Google Scholar PubMed

[28] S. M. Rabbitt, A. E. Kazdin, B. Scassellati, Integrating socially assistive robotics into mental healthcare interventions: Applications and recommendations for expanded use, Clinical Psychology Review, 2015, 35, 35–4610.1016/j.cpr.2014.07.001Search in Google Scholar PubMed

[29] M. R. Banks, L. M. Willoughby, W. A. Banks, Animal-assisted therapy and loneliness in nursing homes: use of robotic versus living dogs, Journal of the American Medical Directors Association, 2008, 9(3), 173–17710.1016/j.jamda.2007.11.007Search in Google Scholar PubMed

[30] S. C. Kramer, E. Friedmann, P. L. Bernstein, Comparison of the effect of human interaction, animal-assisted therapy, and AIBOassisted therapy on long-term care residents with dementia, Anthrozoös, 2009, 22(1), 43–5710.2752/175303708X390464Search in Google Scholar

[31] G. Colombo, M. D. Buono, K. Smania, R. Raviola, D. De Leo, Pet therapy and institutionalized elderly: a study on 144 cognitively unimpaired subjects, Archives of Gerontology and Geriatrics, 2006, 42(2), 207–21610.1016/j.archger.2005.06.011Search in Google Scholar PubMed

[32] M. C. Le Roux, R. Kemp, Effect of a companion dog on depression and anxiety levels of elderly residents in a long-term care facility, Psychogeriatrics, 2009, 9(1), 23–2610.1111/j.1479-8301.2009.00268.xSearch in Google Scholar

[33] S. D. Hollon, R. B. Jarrett, A. A. Nierenberg, M. E. Thase, M. Trivedi, A. J. Rush, Psychotherapy and medication in the treatment of adult and geriatric depression: which monotherapy or combined treatment?, The Journal of Clinical Psychiatry, 2005, 66(4), 455–46810.4088/JCP.v66n0408Search in Google Scholar

[34] S. Pampallona, P. Bollini, G. Tibaldi, B. Kupelnick, C. Munizza, Combined pharmacotherapy and psychological treatment for depression: a systematic review, Archives of General Psychiatry, 2004, 61(7), 714–71910.1001/archpsyc.61.7.714Search in Google Scholar PubMed

[35] H.-M. Gross et al., Progress in developing a socially assistive mobile home robot companion for the elderly with mild cognitive impairment, In: 2011, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2011, 2430–243710.1109/IROS.2011.6094770Search in Google Scholar

[36] K. Wada, T. Shibata, T. Asada, T. Musha, Robot therapy for prevention of dementia at home, Journal of Robotics and Mechatronics, 2007, 19(6), 691–69710.20965/jrm.2007.p0691Search in Google Scholar

[37] A. Liang et al., A pilot randomized trial of a companion robot for people with dementia living in the community, Journal of the American Medical Directors Association, 2017, 18(10), 871–87810.1016/j.jamda.2017.05.019Search in Google Scholar PubMed

[38] S. Coradeschi et al., Giraffplus: Combining social interaction and long term monitoring for promoting independent living, In: 2013 6th International Conference on Human System Interactions (HSI), 2013, 578–58510.1109/HSI.2013.6577883Search in Google Scholar

[39] B. Graf, M. Hans, R. D. Schraft, Care-O-bot II—Development of a next generation robotic home assistant, Autonomous Robots, 2004, 16(2), 193–20510.1023/B:AURO.0000016865.35796.e9Search in Google Scholar

[40] A. M. Adami, M. Pavel, T. L. Hayes, C. M. Singer, Detection of movement in bed using unobtrusive load cell sensors, IEEE Transactions on Information Technology in Biomedicine, 2010, 14(2), 481–49010.1109/TITB.2008.2010701Search in Google Scholar PubMed

[41] H. Aghajan, J. C. Augusto, C. Wu, P. McCullagh, J.-A. Walkden, Distributed vision-based accidentmanagement for assisted living, In: International Conference on Smart Homes and Health Telematics, 2007, 196–20510.1007/978-3-540-73035-4_21Search in Google Scholar

[42] M. R. Song, Y.-S. Lee, J.-D. Baek, M. Miller, Physical activity status in adults with depression in the National Health and Nutrition Examination Survey, 2005–2006, Public Health Nursing, 2012, 29(3), 208–21710.1111/j.1525-1446.2011.00986.xSearch in Google Scholar PubMed

[43] C. Galambos, M. Skubic, S.Wang, M. Rantz,Management of dementia and depression utilizing in-home passive sensor data, Gerontechnology: International Journal on the Fundamental Aspects of Technology to Serve the Ageing Society, 2013, 11(3), 457–46810.4017/gt.2013.11.3.004.00Search in Google Scholar

[44] K. Wild, L. Boise, J. Lundell, A. Foucek, Unobtrusive in-home monitoring of cognitive and physical health: Reactions and perceptions of older adults, Journal of Applied Gerontology, 2008, 27(2), 181–20010.1177/0733464807311435Search in Google Scholar

[45] M. E. Pollack et al., Autominder: An intelligent cognitive orthotic system for people with memory impairment, Robotics and Autonomous Systems, 2003, 44(3-4), 273–28210.1016/S0921-8890(03)00077-0Search in Google Scholar

[46] K. Caine, S. Šabanovic, M. Carter, The effect of monitoring by cameras and robots on the privacy enhancing behaviors of older adults, In: Proceedings of the Seventh Annual ACM/IEEE International Conference on Human-Robot Interaction (HRI), 2012, 343–35010.1145/2157689.2157807Search in Google Scholar

[47] C. T. Gualtieri, L. G. Johnson, Age-related cognitive decline in patients with mood disorders, Progress in Neuro- Psychopharmacology and Biological Psychiatry, 2008, 32(4), 962–96710.1016/j.pnpbp.2007.12.030Search in Google Scholar

[48] R. C. Kessler, K. A. McGonagle, M. Swartz, D. G. Blazer, C. B. Nelson, Sex and depression in the National Comorbidity Survey I: Lifetime prevalence, chronicity and recurrence, Journal of Affective Disorders, 1993, 29(2), 85–9610.1016/0165-0327(93)90026-GSearch in Google Scholar

[49] M. M. Weissman, G. L. Klerman, Sex differences and the epidemiology of depression, Archives of General Psychiatry, 1977, 34(1), 98–11110.1001/archpsyc.1977.01770130100011Search in Google Scholar PubMed

[50] W.-L. Chang, S. Šabanović, Interaction expands function: Social shaping of the therapeutic robot PARO in a nursing home, In: Proceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction, 2015, 343–35010.1145/2696454.2696472Search in Google Scholar

[51] C. Bartneck, D. Kulić, E. Croft, S. Zoghbi, Measurement instruments for the anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety of robots, International Journal of Social Robotics, 2009, 1(1), 71–8110.1007/s12369-008-0001-3Search in Google Scholar

[52] M. Heerink, B. Kröse, V. Evers, B. Wielinga, Assessing acceptance of assistive social agent technology by older adults: the Almere model, International Journal of Social Robotics, 2010, 2(4), 361–37510.1007/s12369-010-0068-5Search in Google Scholar

[53] H. R. Lee, Collaborative Design for Intelligent Technologies, PhD Thesis, Indiana University, 2017Search in Google Scholar

[54] J. Guiry, P. Van de Ven, J. Nelson, Multi-sensor fusion for enhanced contextual awareness of everyday activities with ubiquitous devices, Sensors, 2014, 14(3), 5687–570110.3390/s140305687Search in Google Scholar PubMed PubMed Central

[55] K. Lee, M.-P. Kwan, Physical activity classification in free-living conditions using smartphone accelerometer data and exploration of predicted results, Computers, Environment and Urban Systems, 2018, 67, 124–13110.1016/j.compenvurbsys.2017.09.012Search in Google Scholar

[56] I. H. Witten, E. Frank, M. A. Hall, C. J. Pal, Data Mining: PracticalMachine Learning Tools and Techniques, Morgan Kaufmann, 201610.1016/B978-0-12-804291-5.00010-6Search in Google Scholar

[57] C. Bennett, T. Doub, Data mining and electronic health records: Selecting optimal clinical treatments in practice, DMNI, 2010Search in Google Scholar

[58] I. Kononenko, Estimating attributes: analysis and extensions of RELIEF, In: European Conference on Machine Learning, 1994, 171–18210.1007/3-540-57868-4_57Search in Google Scholar

[59] H. Robinson, B.MacDonald, E. Broadbent, The role of healthcare robots for older people at home: A review, International Journal of Social Robotics, 2014, 6(4), 575–59110.1007/s12369-014-0242-2Search in Google Scholar

[60] N. Randall, S. Šabanović, W. Chang, Engaging older adults with depression as co-designers of assistive in-home robots, In: Proceedings of the 12th EAI International Conference on Pervasive Computing Technologies for Healthcare, 2018, 304–30910.1145/3240925.3240946Search in Google Scholar

[61] C.-A. Smarr, A. Prakash, J. M. Beer, T. L. Mitzner, C. C. Kemp, W. A. Rogers,Older adults’ preferences for and acceptance of robot assistance for everyday living tasks, In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 2012, 56, 153–15710.1177/1071181312561009Search in Google Scholar PubMed PubMed Central

[62] H. Hutchinson et al., Technology probes: inspiring design for and with families, In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2003, 17–2410.1145/642611.642616Search in Google Scholar

Received: 2018-02-28
Accepted: 2019-05-15
Published Online: 2019-06-25

© 2019 Natasha Randall et al., published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 Public License.

Downloaded on 28.11.2022 from frontend.live.degruyter.dgbricks.com/document/doi/10.1515/pjbr-2019-0020/html
Scroll Up Arrow