Policy’s Role in the Use of Social Robots in Care Homes

Can policy help social robots provide ethical, dignified, and beneficial care for older adults? This question has been the subject of ongoing ethical debate concerning the use of social robots in care homes.

Around the world, the expanding population of older adults is increasing the need for care resources, straining health and aged care providers (1). The COVID-19 pandemic has further highlighted the negative consequences of overpacked and understaffed healthcare institutions (2). As governments seek solutions to reduce pressure on care homes, the use of social robots as a potential tool has been suggested.

Already, social robots have been studied in the context of older adult care to provide companionship, exercise, cognitive therapy and help with daily tasks (3). Although these studies have shown predominantly positive effects, the majority have assessed social robots in short-term situations, have had small sample sizes, or lack diversity and may not be generalizable to all cultures (3).

Studies from North America with larger sample sizes and longer time periods are showing variable results, with some older adults experiencing declines in loneliness and increased interaction with other older adults (4). Populations of care home residents with dementia also show variation in responses, suggesting that one approach to delivering care with social robots does not fit all (5). However, it is important to note that the social robot used in both of these studies is the same model that has been in use since 2003 (6). The field of social robotics is rapidly expanding, with many new types and models of robots released with a greater focus on end-users in their development (7,8). Research with such models done in care home contexts with generalizable samples is limited (3). Although more research is needed, social robots developed with users are showing promising preliminary results and could be a viable future solution to promoting well-being in the elderly (9).

To this end, social robots are showing great promise as beneficial tools in care homes. They can assist caregivers in situations where they are tired, distracted, overwhelmed, or not feeling very well (5). Social robots can be used to empower older adults to be more independent and to aid aging at-home care (2).

However, key ethical challenges in the use of social robot care assistants include autonomy, privacy, dignity, and bias (2). Autonomy can be suppressed or overridden by a social robot if, for example, a user is prevented from climbing on a chair to reach something in an effort to prevent a fall. Although the user’s safety is maintained, their autonomy and dignity may be diminished by the robot. Furthermore, the social robot’s monitoring features and social interaction with the user require data storage and use, which could interfere with the user’s privacy.

Currently, legislation around privacy and consumer protection could form the basis of government-enforced policies around social robots. However, in AI, self-regulation through developers has typically been the norm (2). Criticism to this point can be made in that self-regulation does not sufficiently protect the rights and safety of vulnerable populations such as older adults, and that manufacturers primarily protect their own interests.

This is where Johnston suggests ethics by design can ensure that ethical values of dignity, respect for autonomy and benevolence can be programmed into the robot’s behavior such that it protects the interests of the elderly. Johnston continues that to determine the “moral code” programmed into social robots and to monitor the ethical use of such systems within care home contexts, the use of clinical ethics committees can be employed. Ethics committees can provide consultation services, help in creating care home policies and procedures regarding social robots, and aid to resolve emerging ethical dilemmas. To counteract ethical biases in design, it is important that ethics committees consider multi-stakeholder perspectives. Emphasizing the voices of end-users tailors social robot functionality to the populations it will serve, and aids in user acceptance of social robots (10).

Furthermore, policies must consider both the benefits and drawbacks of using social in care home contexts (1). Potential benefits could include increased efficiency, increased welfare, physiological and psychological benefits, and increased satisfaction (1). There are, however, interesting objections to the use of social robots including the possibility that relations with robots can potentially displace human contact, that these relations could be harmful, that robot care is undignified and disrespectful, and that social robots are deceptive (1). These are ethical considerations that must be carefully balanced in a holistic policy aimed to maximize benefits for end-users while mitigating potential downsides to social robot use.

Although we are not yet at the stage where social robots can be used in a large-scale fashion across care homes in North America, it is important to anticipate their future ethical ramifications. By discussing policy-regulated ethical considerations, we are taking strides towards the responsible development and use of social robots with the goal of minimizing their potential for harm and ensuring their benefits for human care.

Bio: Anna Riminchan was born in Bulgaria, where she spent her early childhood before immigrating to Canada with her family. Anna is currently working towards a Bachelor of Science Degree, majoring in Behavioural Neuroscience and minoring in Visual Arts at the University of British Columbia. In the meantime, she is contributing to advancing research in neuroscience, after which, she plans to pursue a degree in medicine. In her spare time, you can find Anna working on her latest art piece! 


References

  1. Sætra HS. The foundations of a policy for the use of social robots in care. Technol Soc. 2020 Nov 1;63:101383.
  2. Johnston C. Ethical Design and Use of Robotic Care of the Elderly. J Bioethical Inq. 2022 Mar 1;19(1):11–4.
  3. Thunberg S, Ziemke T. Social Robots in Care Homes for Older Adults. In: Li H, Ge SS, Wu Y, Wykowska A, He H, Liu X, et al., editors. Social Robotics. Cham: Springer International Publishing; 2021. p. 475–86. (Lecture Notes in Computer Science).
  4. Robinson H, MacDonald B, Kerse N, Broadbent E. The Psychosocial Effects of a Companion Robot: A Randomized Controlled Trial. J Am Med Dir Assoc. 2013 Sep 1;14(9):661–7.
  5. Moyle W, Jones C, Murfield J, Thalib L, Beattie E, Shum D, et al. Using a therapeutic companion robot for dementia symptoms in long-term care: reflections from a cluster-RCT. Aging Ment Health. 2019 Mar 4;23(3):329–36.
  6. PARO Therapeutic Robot [Internet]. [cited 2022 Jul 22]. Available from: http://www.parorobots.com/
  7. Breazeal CL, Ostrowski AK, Singh N, Park HW. Designing Social Robots for Older Adults. 2019;10.
  8. Östlund B, Olander E, Jonsson O, Frennert S. STS-inspired design to meet the challenges of modern aging. Welfare technology as a tool to promote user-driven innovations or another way to keep older users hostage? Technol Forecast Soc Change. 2015 Apr 1;93:82–90.
  9. Hutson S, Lim SL, Bentley PJ, Bianchi-Berthouze N, Bowling A. Investigating the Suitability of Social Robots for the Wellbeing of the Elderly. In: D’Mello S, Graesser A, Schuller B, Martin JC, editors. Affective Computing and Intelligent Interaction. Berlin, Heidelberg: Springer; 2011. p. 578–87. (Lecture Notes in Computer Science).
  10. Hameed I, Tan ZH, Thomsen N, Duan X. User Acceptance of Social Robots. In 2016.
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Stigma around technology use by older adults

Canadians are living longer, healthier lives, resulting in a rapidly growing population of older adults. It is projected that the number of adults aged 65 and over in Canada will grow by 68% over the next two decades (1). One way to support the quality of life of this growing demographic is through technology. Assistive technologies (AT) such as blood pressure monitors (2), wheelchairs (3), and fall detectors (4) can promote the physical health of older adults. Social robots, AT that can interact with users (Figure 1), can assist older adults by improving mood (5), decreasing blood pressure (6), and reducing the need for analgesic and behavioural medication (7). Everyday information and communication technologies (EICT) – including mobile phones, computers, and email services – allow for regular communication with social contacts (3) and the ability to look up health information (8). Telemedicine provides a unique healthcare solution for older adults who face barriers to in-person care such as isolation, severe illness, and functional challenges (9).

Figure 1 – Social robots such as MiRo-E can interact with users. Adapted from MiRo-E University Research

Despite the known benefits of these technologies, there is a wide range of barriers to technology adoption by older adults. Such barriers include privacy concerns (10), inappropriate device design (11), and a lack of familiarity with technology (12). Another barrier is stigma around the use of technologies by older adults (5,10,13). Negative stereotypes of old age include increased dependency, disability, and disconnection from society (13,14). Furthermore, within technology research, ageing is often regarded as a ‘problem’ that technology may address (15). In this piece, I will summarize the literature on stigma around technology use by older adults and how we might address this issue.

Older adults often associate AT with negative stereotypes about ageing. For example, some older adults have stated that they are not ‘disabled’ or ‘old’ enough to require AT (16). In one research study, older adults who stated that they did not need AT recommended these devices for people who experience isolation, dependency, and disability (17). Some older adults feel that adopting AT signifies a loss of independence (4), and others experience feelings of embarrassment and incompetency when using AT (12). Furthermore, some older adults have expressed preference for items that are not necessarily ‘assistive’ or ‘medical’ in nature, such as an umbrella in place of a walking stick (2), a smartwatch with assistive features (4), or a shopping cart in place of a walker (16). On the other hand, EICT such as smartphones and computers are often regarded by older adults as a way to keep up with society, and thus older adults associate non-use of these technologies with negative ageing stereotypes (13). However, when learning to use EICT, many older adults experience embarrassment, anxiety, or fear of making mistakes (2,18). Some have reported feeling ‘older’ after encountering vision and haptic-related challenges while using EICT (13). Altogether, the literature shows that technologies often remind older adults of negative aspects of ageing. As a result, older adults are less likely to adopt these technologies.

Non-use of the technologies described above raises several issues, including a key neuroethical problem: decreased access to mental health benefits. For example, several online services that can improve mental health – such as telemedicine and tele-counselling services – are accessed through technologies such as smartphones and computers. Research has shown that interacting with social robot technologies can improve mood (5), and technologies such as smartphones allow people to stay in touch with one another (3), especially during the current COVID-19 pandemic where in-person contact is restricted. These are just a few mental health benefits that older adults who limit their use of technologies have reduced access to. As a result, there is a need to address key barriers to technology adoption, such as stigma.

One of the most important things we can do to address issues of stigma and non-use is to engage end-users in the process of device development. Older adults are often not consulted when technologies are being developed for them, leading to devices that are often misaligned with their needs and priorities (19). A study by Federici et al. found that the most common reason for device abandonment was an inappropriate device design (11). Incorporating ideas and feedback from older adults about device design, features, applications, affective considerations, and ethical concerns into the creation and implementation of technologies will likely result in devices that this population is more comfortable using.

Bio: Jaya Kailley is an Undergraduate Research Assistant under the supervision of Dr. Julie Robillard in the NEST Lab, and she is pursuing an Integrated Sciences degree in Behavioural Neuroscience and Physiology at the University of British Columbia. She currently supports research projects that aim to include end-users in the process of social robot development. Outside of work, Jaya enjoys playing the piano, reading, and spending time with her family and friends.


References

  1. Infographic: Canada’s seniors population outlook: Uncharted territory | CIHI [Internet]. [cited 2022 Jun 16]. Available from: https://www.cihi.ca/en/infographic-canadas-seniors-population-outlook-uncharted-territory
  2. Chen K. Why do older people love and hate assistive technology? ‒ an emotional experience perspective. Ergonomics. 2020 Dec 1;63(12):1463–74.
  3. Tomšič M, Domajnko B, Zajc M. The use of assistive technologies after stroke is debunking the myths about the elderly. Topics in Stroke Rehabilitation. 2018 Jan 2;25(1):28–36.
  4. Caldeira C, Nurain N, Connelly K. “I hope I never need one”: Unpacking Stigma in Aging in Place Technology. In: CHI Conference on Human Factors in Computing Systems [Internet]. New Orleans LA USA: ACM; 2022 [cited 2022 Jun 10]. p. 1–12. Available from: https://dl.acm.org/doi/10.1145/3491102.3517586
  5. Hung L, Liu C, Woldum E, Au-Yeung A, Berndt A, Wallsworth C, et al. The benefits of and barriers to using a social robot PARO in care settings: a scoping review. BMC Geriatr. 2019 Aug 23;19(1):232.
  6. Robinson H, MacDonald B, Broadbent E. Physiological effects of a companion robot on blood pressure of older people in residential care facility: A pilot study. Australasian Journal on Ageing. 2015;34(1):27–32.
  7. Petersen S, Houston S, Qin H, Tague C, Studley J. The Utilization of Robotic Pets in Dementia Care. Journal of Alzheimer’s Disease. 2017 Jan 1;55(2):569–74.
  8. Vroman KG, Arthanat S, Lysack C. “Who over 65 is online?” Older adults’ dispositions toward information communication technology. Computers in Human Behavior. 2015 Feb 1;43:156–66.
  9. Frydman JL, Li W, Gelfman LP, Liu B. Telemedicine Uptake Among Older Adults During the COVID-19 Pandemic. Ann Intern Med. 2022 Jan;175(1):145–8.
  10. Pirzada P, Wilde A, Doherty GH, Harris-Birtill D. Ethics and acceptance of smart homes for older adults. Informatics for Health and Social Care. 2021 Jul 9;1–28.
  11. Federici S, Meloni F, Borsci S. The abandonment of assistive technology in Italy: A survey of users of the National Health Service. European journal of physical and rehabilitation medicine. 2016;52(4):516–26.
  12. Evans N, Boyd H, Harris N, Noonan K, Ingram T, Jarvis A, et al. The experience of using prompting technology from the perspective of people with Dementia and their primary carers. Aging & Mental Health. 2021 Aug 3;25(8):1433–41.
  13. Köttl H, Gallistl V, Rohner R, Ayalon L. “But at the age of 85? Forget it!”: Internalized ageism, a barrier to technology use. Journal of Aging Studies. 2021 Dec 1;59:100971.
  14. Dionigi RA. Stereotypes of Aging: Their Effects on the Health of Older Adults. Journal of Geriatrics. 2015 Nov 12;2015:1–9.
  15. Vines J, Pritchard G, Wright P, Olivier P, Brittain K. An Age-Old Problem: Examining the Discourses of Ageing in HCI and Strategies for Future Research. ACM Trans Comput-Hum Interact. 2015 Mar 4;22(1):1–27.
  16. Astell AJ, McGrath C, Dove E. ‘That’s for old so and so’s!’: does identity influence older adults’ technology adoption decisions? Ageing and Society. 2020 Jul;40(7):1550–76.
  17. Wu YH, Wrobel J, Cornuet M, Kerhervé H, Damnée S, Rigaud AS. Acceptance of an assistive robot in older adults: a mixed-method study of human–robot interaction over a 1-month period in the Living Lab setting. Clin Interv Aging. 2014 May 8;9:801–11.
  18. University of Massachusetts Lowell, McDonough CC. The Effect of Ageism on the Digital Divide Among Older Adults. GGM. 2016 Jun 16;2(1):1–7.
  19. Mannheim I, Schwartz E, Xi W, Buttigieg SC, McDonnell-Naughton M, Wouters EJM, et al. Inclusion of Older Adults in the Research and Design of Digital Technology. Int J Environ Res Public Health. 2019 Oct;16(19):3718.

The significance of non-pharmacological treatments for depression in people living with dementia

As part of my role in the Neuroscience, Engagement, and Smart Tech (NEST) Lab at Neuroethics Canada, I conducted a review of non-pharmacological interventions for mental health in people living with dementia. What are these non-pharmacological interventions, and why are researchers so interested in studying them?

Among the 50 million people worldwide with a diagnosis of dementia, roughly 32% (16 million) report symptoms of depression (1). Within this group, half will have received a formal diagnosis of major depressive disorder. You may already be familiar with pharmacological or drug-based interventions for depression (e.g., antidepressants). However, in recent years, there has been a push for non-pharmacological treatment alternatives for people living with dementia.

Non-pharmacological treatments are defined as any activity or care plan to reduce symptoms of a given ailment. These interventions are often adjustable to accommodate the needs of the recipients, something traditional drug interventions lack.

The issues surrounding pharmacological treatments for depression

Various studies highlight some of the drawbacks surrounding the drug interventions commonly used to treat major depressive disorder. The findings of a 2013 study revealed that 69% of older adults from a data sample of 2 million received a prescription psychotropic without a formal psychiatric diagnosis (2). In addition, many were found to not be receiving any type of mental health specialty care (2).

Figure 1 – Weichers et. al (2013). Percentage of mental health care utilizers and non–mental health care utilizers without a psychiatric diagnosis who filled a prescription for psychotropic medication in 2009, by age and drug class. AD, antidepressants; AP, antipsychotics; ANX, anxiolytics; STIM, stimulants; MS/AC, anticonvulsant mood stabilizers; and LITH, lithium.

These results come with caveats. Not being able to qualify for a diagnosis does not negate the existence of a medical need, nor does it address the social barriers individuals may face in obtaining a diagnosis. Experiencing symptoms can drastically impact a person’s physical health and overall quality of life (3). Symptoms are expressed in a multitude of ways (e.g., lethargy, insomnia, changes in appetite, feeling discouraged or unhappy) and in varying intensities (4). Depression manifests itself differently for each individual and depending on their given situation, clinical treatment may have been the best course of action.

Nevertheless, the study results suggest that the current implementation of clinical approaches to treating depression may not meet the desired standards of care (2). Also consider the high relapse rates of major depressive disorder in individuals exclusively using pharmacological therapies (5).

The efficacy of drug interventions for treating depression in people living with dementia has been challenged by various studies (6,7,8). Evidence indicates that antidepressants are associated with an increased risk of recurrent falls, whereas non-pharmacological care alternatives have the potential to be just as effective as drug treatments with fewer risks (6,7).

Certain psychological treatments can match the effectiveness of clinical approaches to mood disorders (4), and a few are somewhat more effective (6). Drug interventions alone can be an effective treatment method for many (5,6,7). However, we must also assess the ethical considerations surrounding limited catalogues of treatment options only optimal for a subset of individuals.

Thus, there is unexplored potential in the application of non-pharmacological interventions as both a supplement to drug treatments and as their own form of care.

Sociocultural and ethical considerations

The myriad of issues related to treatments for mental health in people living with dementia are complex. A discussion regarding healthcare disparities and the socioeconomic and cultural barriers to care could warrant a post of its own. Here, I will attempt to summarize a few.

  • Stigma — There may be cultural stigma surrounding mental health and treatment (8,9). Individuals who inherit cultural values from their respective culture or community may not feel comfortable with western conventions of mental health. Thus, given how drug interventions are prescribed in Canada, pharmacological treatments may not be the most effective or accessible option.
  • Economic factors — Prescription drug costs contribute to the inaccessibility of treatment. Canada is the only developed country with a universal healthcare system that does not cover the cost of prescription drugs. Older adults without private health insurance may be left in a difficult position (10).
  • Location — Individuals living in rural or remote locations may face difficulty with filling their prescriptions over an extended period (11).

There are many more issues pertaining to the limitations of drug interventions in current healthcare models. Thus, there is value in exploring non-pharmacological treatment alternatives (6).

How non-pharmacological interventions for depression can be used

In recent years, there has been growing interest in social prescribing: the act of linking patients with non-drug interventions in their community (6). While non-profit organizations such as the Alzheimer’s Society of BC are unable to prescribe medication, they can provide low or no-cost services aiming to support mental health.

Implementing these non-pharmacological interventions can also be a quite simple. Some common, low-cost interventions that are easy to implement include:

  • Reminiscence therapy — Remembering or sharing details about the past or previous positive events, either alone or with a group. Reminiscence therapy can improve quality of life, cognitive functions, and lower depression (12).
  • Exercise — Exercising the body and the mind can reduce symptoms of depression and improve the overall quality of life (6).
  • Music therapy — Listening to music regularly with a music therapist can improve symptoms of depression (13).
  • Indoor Daylight Exposure —People living with dementia at a nursing home socialized with each other in an indoor setting with ample amounts of daylight each morning. Daylight exposure was found to significantly reduce symptoms of depression (14).

These interventions do not present as very psychological or medical in nature. By framing activities that may reduce symptoms of depression in an approachable, non-clinical manner, care providers could avoid the stigmas around treatment for mental health to encourage greater use of mental health services (15). However, this does not address the issues surrounding mental health perception and discourse. More research is needed to better understand how we can effectively tackle these stigmas.

Providing evidence-based, low-complexity care can also enable people living with dementia to form deeper bonds with their local community and create their own support network. The low cost of execution makes these interventions a great option for treating mild symptoms of depression.

Complex interventions that target more severe symptoms of depression and aim to create lasting effects also exist. These require a higher degree of training from providers and thus are more costly, but evidence highlights their value as potential treatment options (6, 16, 17, 18). Examples include:

  • Cognitive-behavioral therapy (CBT) — Breaking down existing negative cognitions and replacing them with more positive functionally adaptive ones (16) can reduce symptoms of both depression and anxiety (6, 17, 18).
  • Multidisciplinary care — A care plan developed in collaboration with multiple qualified healthcare providers can match the efficacy of drug treatments (6).

There are many other approaches: animal-assisted activities, psychotherapy, cognitive stimulation, and environmental modification, to name a few (6). Non-pharmacological interventions also have the advantage of being flexible and adjustable to one’s individual needs. For example, Shiatsu could be an interesting approach for people with dementia of East Asian descent.

  • Shiatsu — A holistic complementary practice that draws on the principles of traditional Chinese medicine. By applying pressure to certain pressure points, symptoms of depression were reduced when utilized in combination with exercise (19).
Figure 2 – a man performs Shiatsu therapy (left) with a focus on key acupressure points (right).
Credit: Shiatsu Tokyo School, 2021.

Many treatment options exist where traditional drug-based interventions are not appropriate. Individuals could develop a personalized care plan with careful guidance from a qualified medical professional.

There is still an important need for drug interventions. For a subset of the population, it remains quite effective (5,6).

The value in exploring various non-pharmacological treatments has much to do with the agency it gives the individual and how it makes mental health care more attainable to people of all socioeconomic and cultural backgrounds.

Looking to the future

Non-pharmacological interventions may reduce the burden of depressive symptoms in older adults with dementia. Within the next few decades, the global population will continue to age and the number of people living with dementia is expected to increase to 152.8 million cases by 2050 (20). Thus, the need for programs supporting the well-being of older (and younger!) adults with dementia is greater than ever.

In neuroethics research, the way non-pharmacological interventions are received and their overall effectiveness can be studied to highlight healthcare disparities and bring insight into public discussions surrounding brain health and aging. This research may inform initiatives that aim to address the gap in services related to mental health in people living with dementia.

By deepening our understanding of how people living with dementia respond to non-pharmacological interventions, we can improve current treatment approaches and the standard of care. Every individual should have the option to receive the type of care that best suits their specific medical needs.

Special thanks to Dr. Julie Robillard and Viorica Hrincu from the NEST Lab for all their guidance and support in the last year!

Bio: Yu Fei Jiang is a 4th-year undergraduate student studying Behavioural Neuroscience at the University of British Columbia. Her research interests primarily lie in the interaction between technology use in patient care and neuroscience research. She’s also very passionate about science communication and sharing knowledge with others. Outside of work, Yu Fei enjoys all things nerdy; you’ll probably find her either reading books of wildly different genres or playing video games late into the night.


References

1. Goodarzi ZS, Mele BS, Roberts DJ, Holroyd-Leduc J. (2017). Depression Case Finding in Individuals with Dementia: A Systematic Review and Meta-Analysis. J Am Geriatric Society, 65, 937-48. Doi.org/10.1111/jgs.14713

2. Wiechers, I. R., Leslie, D. L., Rosenheck, R. A. (2013). Prescribing of psychotropic medications to patients without a psychiatric diagnosis. Psychiatric Services, 64(12), 1243–1248. https://doi.org/10.1176/appi.ps.201200557

3. Ruo, B., Rumsfeld, J. S., Hlatky, M. A., Liu, H., Browner, W. S., & Whooley, M. A. (2003). Depressive symptoms and health-related quality of life: the Heart and Soul Study. Jama, 290(2), 215-221.

4. Spitzer, R. L., Kroenke, K., Williams, J. B., Patient Health Questionnaire Primary Care Study Group, & Patient Health Questionnaire Primary Care Study Group. (1999). Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study. Jama282(18), 1737-1744.

5. Beck, A. T., & Alford, B. A. (2009). Depression: Causes and treatment. University of Pennsylvania Press.

6. Watt J A, Goodarzi Z, Veroniki A A, Nincic V, Khan P A, Ghassemi M et al. (2021). Comparative efficacy of interventions for reducing symptoms of depression in people with dementia: systematic review and network meta-analysis BMJ; 372 :n532 doi:10.1136/bmj.n532

7. Marcum, Z. A., Perera, S., Thorpe, J. M., Switzer, G. E., Castle, N. G., Strotmeyer, E. S., Simonsick, E. M., Ayonayon, H. N., Phillips, C. L., Rubin, S., Zucker-Levin, A. R., Bauer, D. C., Shorr, R. I., Kang, Y., Gray, S. L., Hanlon, J. T., & Health ABC Study (2016). Antidepressant Use and Recurrent Falls in Community-Dwelling Older Adults: Findings From the Health ABC Study. The Annals of pharmacotherapy50(7), 525–533. https://doi.org/10.1177/1060028016644466

8. Ng, C. H. (1997). The stigma of mental illness in Asian cultures. Australian & New Zealand Journal of Psychiatry, 31(3), 382-390.

9. Ciftci, A., Jones, N., & Corrigan, P. W. (2013). Mental health stigma in the Muslim community. Journal of Muslim Mental Health, 7(1).

10. Morgan, S. G., & Boothe, K. (2016). Universal prescription drug coverage in Canada: Long-promised yet undelivered. Healthcare management forum, 29(6), 247–254. https://doi.org/10.1177/0840470416658907

11. Hippe, J., Maddalena, V., Heath, S., Jesso, B., McCahon, M., & Olson, K. (2014). Access to health services in Western Newfoundland, Canada: Issues, barriers and recommendations emerging from a community-engaged research project. Gateways: International Journal of Community Research and Engagement, 7(1), 67-84.

12. Lök, N., Bademli, K., & Selçuk‐Tosun, A. (2019). The effect of reminiscence therapy on cognitive functions, depression, and quality of life in Alzheimer patients: Randomized controlled trial. International journal of geriatric psychiatry, 34(1), 47-53.

13. Li, H. C., Wang, H. H., Lu, C. Y., Chen, T. B., Lin, Y. H., & Lee, I. (2019). The effect of music therapy on reducing depression in people with dementia: A systematic review and meta-analysis. Geriatric Nursing, 40(5), 510-516.

14. Konis, K., Mack, W. J., & Schneider, E. L. (2018). Pilot study to examine the effects of indoor daylight exposure on depression and other neuropsychiatric symptoms in people living with dementia in long-term care communities. Clinical interventions in aging, 13, 1071.

15. Corrigan, P. (2004). How stigma interferes with mental health care. American psychologist59(7), 614.

16. Taylor, F. G., & Marshall, W. L. (1977). Experimental analysis of a cognitive-behavioral therapy for depression. Cognitive Therapy and Research, 1(1), 59-72.

17. García-Alberca, J. M. (2017). Cognitive-behavioral treatment for depressed patients with Alzheimer’s disease. An open trial. Archives of gerontology and geriatrics, 71, 1-8.

18. Tay, K. W., Subramaniam, P., & Oei, T. P. (2019). Cognitive behavioural therapy can be effective in treating anxiety and depression in persons with dementia: a systematic review. Psychogeriatrics, 19(3), 264-275.

19. Lanza, G., Centonze, S. S., Destro, G., Vella, V., Bellomo, M., Pennisi, M., … & Ciavardelli, D. (2018). Shiatsu as an adjuvant therapy for depression in patients with Alzheimer’s disease: A pilot study. Complementary therapies in medicine, 38, 74-78.

20. Nichols, Emma, et al. (2022). Estimation of the Global Prevalence of Dementia in 2019 and Forecasted Prevalence in 2050: An Analysis for the Global Burden of Disease Study 2019. The Lancet Public Health. 7(2):105–25.

Novel Epilepsy Treatments: Factors That Matter the Most to Parents and Doctors

This blog post discusses some of the key findings from a poster presentation for the 2021 annual meeting of the American Academy of Neurology (abstract here) and published in the Journal of Child Neurology (2021, paper here).

Neurotechnologies that can change certain functions of the brain may help children with a type of epilepsy that responds poorly to anti-seizure medication (drug-resistant epilepsy). However, there are important differences in the way that parents and doctors make treatment decisions about them.

For parents and caregivers of children with drug-resistant epilepsy (1), treatment choice goes beyond just the direct effect of the treatment on the child’s seizures. They also consider their child in context of the world and their overall quality of life (2). For doctors, treatment choice focuses on the evidence of effectiveness and the seizures themselves (3,4). Understanding both the shared and different decision-making priorities for these groups requires deeper insight into the values that drive them.

The promise and uncertainty of neurotechnologies

Neurotechnologies use innovative techniques to alter brain activity in two main ways: electrical stimulation (i.e., neuromodulation) or the removal of diseased tissue. Modern examples include responsive neurostimulation and laser interstitial thermal therapy. These treatments are gaining in popularity because of their perceived benefits, such as reversibility and limited invasiveness.

Given the special developmental needs of children, we wanted to better understand the trade-offs of benefit and risk. We talked to parents and doctors caring for children with drug-resistant epilepsy across Canada and the USA. We asked them to identify the most important factors they consider when weighing novel neurotechnologies against traditional neurosurgery.

For parents, quality of life is key

When asked about new forms of neurotechnology to treat their child’s epilepsy, parents highlight the benefits including – but also beyond – seizures. Specifically, parents identify quality of life as a crucial factor. This includes life factors such as independence and freedom from the side effects of medication.

“Can they [our child] hold down a job? Can they have a house? Can they get married and have a life? To me, that was important,” said one parent.

Doctors mainly discuss seizure freedom as a measure of success. As one doctor stated, it’s important to consider multiple factors, including quality of life, but that “the big [measure] is seizure control, decreased seizure frequency, and then seizure freedom.”

Not all information is equal

For doctors, scientific evidence is the main factor in considering a new procedure, and to prioritize safety and trust. Introducing novel treatments is therefore challenging (5), because they lack clear evidence while they are being studied, especially in children.

Parents struggle to meet all kinds of information needs. They describe spending hours learning online from a range of sources–from academic articles to blog posts. The credibility and readability of these online resources varies greatly, and they report that reliable sources of information are sometimes difficult to identify.

One parent commented, “[Once the information is] on the internet …we have to decipher whether it’s real.”

Many parents suggest that it would be helpful to receive objective materials directly from hospitals or epilepsy centers.

Preserving trust for novel treatment decisions

Novel treatments disrupt conventional decision-making paradigms. Understanding the different ways medical professionals and parents approach treatment decisions can ease the experience of choosing treatment.

Parents maintain a high degree of trust in their doctors and medical team. Incorporating the different perspectives of families, young patients, and physicians preserves trust and supports inclusive clinical practice.

See the poster above for an overview of the results.

For an overview of neurotechnologies in pediatric epilepsy, see this blog post.
For the views of youth on neurotechnology, see Udwadia et al.’s paper.

Acknowledgements to the leaders of this work Dr. Judy Illes (PI) and Dr. Patrick McDonald (Co-PI). I thank our collaborators Dr. Mary B. Connolly, Dr. Mark Harrison, Dr. George M. Ibrahim, Dr. Robert Naftel, and Dr. Winston Chiong, Dr. Urs Ribary and other members of the Neuroethics Canada team. This work is supported by: the National Institutes of Health grant (JI) 1RF1 # MH117805, Canada Research Chairs Program (JI), and the UBC Alcan Chair in Neurosciences (PJM).

References

  1. Kwan P, Arzimanoglou A, Berg AT, Brodie MJ, Hauser WA, Mathern G, et al. Definition of drug resistant epilepsy: Consensus proposal by the ad hoc Task Force of the ILAE Commission on Therapeutic Strategies. Epilepsia. 2010;51(6):1069–77.
  2. Hrincu V, McDonald PJ, Connolly MB, Harrison MJ, Ibrahim GM, Naftel RP, et al. Choice and Trade-offs: Parent Decision Making for Neurotechnologies for Pediatric Drug-Resistant Epilepsy. J Child Neurol. 2021 Jun 2;08830738211015010.
  3. McDonald PJ, Hrincu V, Connolly MB, Harrison MJ, Ibrahim GM, Naftel RP, et al. Novel Neurotechnological Interventions for Pediatric Drug-Resistant Epilepsy: Physician Perspectives. J Child Neurol. 2020 Oct 28;0883073820966935.
  4. Kaal KJ, Aguiar M, Harrison M, McDonald PJ, Illes J. The Clinical Research Landscape of Pediatric Drug-Resistant Epilepsy. J Child Neurol. 2020 Jun 16;0883073820931255.
  5. Iserson KV, Chiasson PM. The Ethics of Applying New Medical Technologies. Semin Laparosc Surg. 2002 Dec 1;9(4):222–9.

Viorica Hrincu, MSc is doing her PhD in Experimental Medicine at the University of British Columbia in the Neuroscience Engagement and Smart Tech (NEST) lab.