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Group's Core Theoretical Foundation

Last modified by Sofia Kostakonti on 2022/04/04 12:17

For this project, we wanted to figure out a way to truly help People with Dementia (PwD) in their everyday life. Since our background was not strong enough in that field of study, we based most of our decisions on literature, which is presented below.

Dementia

People with Dementia, while their disease progresses, want more than anything to maintain their autonomy. One way to do that is to engage in meaningful activities and routines they have held for years, or at least before their diagnosis (Han et al., 2016). It has been observed that people who suffer from dementia often forget to eat and hydrate properly (Al-Anssari et al., 2021), leading to malnutrition, dehydration, and multiple other health issues that stem from a disrupted, unbalanced diet. Furthermore, it can lead to a faster progression of the disease in people with Alzheimer's (Kigozi et al., 2021). Therefore, our goal is to improve the well-being of people with dementia by reminding and encouraging them to eat. Up until now, this responsibility falls to members of the family or caregivers, but it is often too tiresome and time-consuming for them, or even mentally taxing for the PwD who might get irritated and refuse to eat ("Poor appetite and dementia", 2022). This can also create a lot of friction and exhaustion between the family members or spouses (van Wijngaarden et al., 2018), so another goal of ours is to alleviate some of the burdens from the caregivers.

Music

There are also many studies that include music in treatments for people with dementia. Music can create associations, which we plan to exploit to connect certain songs with tasks such as preparing food, eating, drinking, etc (Istvandity, 2017). However, music has also been shown to have a positive effect on the mental state of PwDs. That can be either short-term, calming them down at times when they are feeling especially anxious or irritated, or even long-term, preventing depression and improving their quality of life (Moreno-Morales et al., 2020). Thus, it is evident that the inclusion of music will greatly assist our goals.

Evaluation

For our evaluation, we opted for already existing questionnaires, that have been previously validated, for measuring the robot's pleasantness and the participants' mood, in combination with some of our own questions that consider food and music.
A subset of the EVEA (Sanz, 2001) questionnaire was used to assess the participant's mood before and after each interaction, whereas a subset of the Godspeed (Bartneck et al., 2009) questionnaire was given to the participants to rate how pleasant and intelligent they found the robot to be. A few additional questions were used to determine the relation of the participant with the food and the music, either before or during the interaction, and we also asked some questions in an interview-style to gather qualitative data.

For statistical interpretation of the numerical results, a paired Wilcoxon signed-rank test was used (Wilcoxon, 1945). The test is a non-parametrical statistical test than can be used to compare paired samples, such as the before-after distributions, or the distributions of the same question with two versions of the robot. The test was used to test three different null-hypotheses; the hypothesis that the first distribution median is larger/different/smaller than the median of the second distribution.

  1. Kigozi, E., Egwela, C., Kamoga, L., Nalugo Mbalinda, S., & Kaddumukasa, M. (2021). Nutrition Challenges of Patients with Alzheimer’s Disease and Related Dementias: A Qualitative Study from the Perspective of Caretakers in a Mental National Referral Hospital. Neuropsychiatric Disease And Treatment, Volume 17, 2473-2480. https://doi.org/10.2147/ndt.s325463
  2. Han, A., Radel, J., McDowd, J. M., & Sabata, D. (2016). Perspectives of people with dementia about meaningful activities: a synthesis. American Journal of Alzheimer's Disease & Other Dementias®, 31(2), 115-123.
  3. Al-Anssari, H., Al-Anssari, H., Abdel-Qader, I., Abdel-Qader, I., Mickus, M., & Mickus, M. (2021). Food Intake Vision-Based Recognition System via Histogram of Oriented Gradients and Support Vector Machine for Persons With Alzheimer's Disease. International Journal Of Healthcare Information Systems And Informatics, 16(4), 1-19. https://doi.org/10.4018/ijhisi.295817
  4. Poor appetite and dementia. Alzheimer's Society. (2022). Retrieved 2 April 2022, from https://www.alzheimers.org.uk/get-support/daily-living/poor-appetite-dementia#:~:text=A%20person%20with%20dementia%20may%20lose%20interest%20in%20food.,loss%20and%20less%20muscle%20strength.
  5. van Wijngaarden, E., van der Wedden, H., Henning, Z., Komen, R., & The, A. M. (2018). Entangled in uncertainty: The experience of living with dementia from the perspective of family caregivers. PloS one, 13(6), e0198034. https://doi.org/10.1371/journal.pone.0198034
  6. Lauren Istvandity, Combining music and reminiscence therapy interventions for wellbeing in elderly populations: A systematic review, Complementary Therapies in Clinical Practice, Volume 28, 2017, Pages 18-25, ISSN 1744-3881, https://doi.org/10.1016/j.ctcp.2017.03.003. 
  7. Moreno-Morales, C., Calero, R., Moreno-Morales, P., & Pintado, C. (2020). Music Therapy in the Treatment of Dementia: A Systematic Review and Meta-Analysis. Frontiers in medicine, 7, 160. https://doi.org/10.3389/fmed.2020.00160
  8. Sanz, J. (2001). SCALE FOR MOOD ASSESSMENT (EVEA).
  9. Bartneck, C., Kulić, D., Croft, E., & Zoghbi, S. (2009). Measurement instruments for the anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety of robots. International journal of social robotics, 1(1), 71-81.
  10. Wilcoxon, F. (1945). Individual Comparisons by Ranking Methods. Biometrics Bulletin, 1(6), 80–83. https://doi.org/10.2307/3001968