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Effects of domotics on cognitive, social and personal functioning in patients with chronic stroke: A pilot study
Disability and Health Journal xxx (xxxx) xxx
Contents lists available at ScienceDirect
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Brief Report
Effects of domotics on cognitive, social and personal functioning in patients with chronic stroke: A pilot study Maria Grazia Maggio a, Giuseppa Maresca a, Margherita Russo a, Maria Chiara Stagnitti a, Smeralda Anchesi a, Carmela Casella b, Caterina Zichitella a, Alfredo Manuli a, a, * Maria Cristina De Cola a, Rosaria De Luca a, Rocco Salvatore Calabro a b
IRCCS Centro Neurolesi “Bonino Pulejo”, Messina, Italy Stroke Unit, AOU Policlinico Universitario “G Martino”, Messina, Italy
a r t i c l e i n f o
a b s t r a c t
Article history: Received 9 January 2019 Received in revised form 31 July 2019 Accepted 11 August 2019
Background: Stroke can cause severe brain lesions, leading to multiple cognitive, emotional and motor disorders. In fact, it is one of the main causes of death and disability worldwide, with a negative impact on quality of life for both patient and caregiver. Home automation (also known as domotics) could allow stroke patients to manage and improve their daily lives. Objective: The aim of our pilot study was to evaluate the effects of domotics on cognitive functions and personal/social autonomy in patients with stroke. Methods: We enrolled 40 patients affected by chronic stroke undergoing neurorehabilitation at IRCCS Centro Neurolesi (Messina, Italy), between June 2017 and March 2019. All of the patients were randomized into either the control group (undergoing traditional training based on face-to-face interaction between therapist and patient, and practical activities), or the experimental group (undergoing Home Automation training). Each participant was evaluated before and immediately after the training period. Each different training consisted of 3 sessions per week for eight weeks (i.e. a total of 24 sessions), each session lasting about 60 min. For both the conventional and experimental trainings, treatments were performed in groups, and all the patients were provided with the same amount of treatment. Results: Patients in the experimental group showed a greater improvement in cognitive and social performance, as compared to the control group. Conclusion: Our study shows that domotics could be effective in improving social and cognitive functioning, autonomy and functional recovery in patients affected by chronic stroke. © 2019 Elsevier Inc. All rights reserved.
Keywords: ADL Cognitive rehabilitation Domotics Home automation IADL
Introduction Stroke is caused by a focal interruption in cerebral blood flow due to occlusion (ischemic stroke) or rupture of a blood vessel (hemorrhagic stroke).1 Stroke can cause severe brain lesions, leading to multiple cognitive, emotional and motor disorders.2 In fact, it is one of the main causes of death and disability worldwide, with a negative impact on quality of life (QoL) for both patient and family.34 Some stroke survivors with reduced independence need family support and specialized care homes, overloading the social
* Corresponding author. IRCCS Centro Neurolesi “Bonino-Pulejo”, SS. 113, Contrada Casazza, 98124 Messina, Italy. ). E-mail address: [email protected] (R.S. Calabro
assistance system as well as increasing healthcare costs. It is therefore important to restore even partial independence in patients with stroke.5e7 Targeted rehabilitation can better address and manage post-stroke disorders, as patients do not always respond to standard therapies. Technological solutions, such as Home Automation (HA or Domotics), can help patients compensate for functional deficits.8e10 HA uses technologies in the fields of ICT (information and communication technologies), automation, architecture and ergonomics, for an innovative and user-centered service.11 HA could enable patients after a stroke to manage their daily lives, responding to care needs, through a supportive environment, which allows patients to regain an active role in everyday life. For HA to be effective, aids must have the characteristics of adaptability and simplicity to allow the easy use of normal household objects.12 Thus, HA could stimulate autonomy in
https://doi.org/10.1016/j.dhjo.2019.100838 1936-6574/© 2019 Elsevier Inc. All rights reserved.
Please cite this article as: Maggio MG et al., Effects of domotics on cognitive, social and personal functioning in patients with chronic stroke: A pilot study, Disability and Health Journal, https://doi.org/10.1016/j.dhjo.2019.100838
2
M.G. Maggio et al. / Disability and Health Journal xxx (xxxx) xxx
patients after stroke.The aim of our pilot study was to evaluate the effects of domotics on cognitive functions and personal/social autonomy in stroke patients. Materials and methods Forty patients with a diagnosis of stroke (mean ± SD age: 58 ± 8.2 years; 60.0% male and 40.0% female), who attended the Robotic and Behavioral Neurorehabilitation Unit of the IRCCS Centro Neurolesi “Bonino-Pulejo” (Messina, Italy) from June 2017 to March 2019, were enrolled in this study and randomly divided into two groups. Twenty patients constituted the control group (CG), and twenty patients the experimental group (EG). A more detailed description of the sample is in Table 1. Randomization was based on a single sequence of random assignments, i.e. simply using a coin. The testers and therapists were blind to the assignment and objectives of the study. Inclusion criteria were: i) first ever supratentorial stroke in the chronic phase (i.e. between 6 and 12 months after the event); ii) presence of mild-to moderate cognitive impairment (Mini-Mental State Examination [MMSE] from 11 to 26); and absence of disabling sensory alterations (i.e. auditory and visual loss). Exclusion criteria were: i) age >85 years; ii) presence of severe medical and psychiatric illness potentially interfering with the training. Each participant was evaluated by a neuropsychologist before (T0) and after the last training session (T1). The neuropsychological battery included: Montreal Cognitive Assessment (MoCA) to assess the general cognitive state; Weigl Test and Frontal Assessment Battery (FAB) to evaluate frontal abilities; Hamilton Rating Scale Depression (HRS-D) to assess mood; SF-12 Health Survey to evaluate QoL; Social Adaptation Self-evaluation Scale (SASS) to assess social adaptation; Activities of Daily Living (ADL), and Instrumental Activities of Daily Living Scale (IADL) to evaluate the functional state in performing daily life activities independently. Two different rehabilitative approaches were used. The CG underwent traditional training that was based on a face-to-face interaction between the therapist and small group of patients (i.e. 3e5 patients per group), practical activities and exercise with paper and pencil, whereas the EG underwent a HA Training (HAT). In traditional training, the therapist led the patient through a series of exercises promoting autonomy in daily life activities. These activities included positioning of marbles, ball exercises, and manipulation of various objects such as buttons for fastening a jacket or zippers. Conventional training is based on direct interaction and exercises with the patients (often working together), who can also use paper/pencil exercises. The purpose of the training is to facilitate homecoming even for severely disabled patients who are
Table 1 Demographics characteristics at baseline for both groups. Experimental Participants 20 Age 53.5 ± 4.8 Education 3.0 ± 0.6 Gender Male 12 (60%) Female 8 (40%) Interval from stroke Mean in months 6±1 Brain lesion site/side Cortical right 12 Subcortical right 6 Cortical left 2 Subcortical left 0
Control
All
P-value
20 54.3 ± 4.2 3.1 ± 0.5
40 53.9 ± 4.5 3.0 ± 0.5
0.36 0.76
10 (50%) 10 (50%)
22 (55%) 18 (45%)
0.97
6±1
6±1
0.99
11 7 2 0
23 13 4 0
0.99
Quantitative variables were expressed as means ± standard deviations, categorical variables as frequencies and percentages.
partially autonomous in their movements. This training allows the use of domestic environments (e.g., kitchens, bathrooms) in an easy way with strategies that permit an effective use.The EG performed the training with the help of HAT, in which the interaction with the therapist was mediated by technological tools to facilitate the achievement of the goals (Fig. 1). HAT also consisted of group activities (3e5 patients per group) in a room where there are several tools built to be easily used by the in-patients. Each tool can be adapted to the needs of the patient. Technologies make it easier to implement everyday life activities, such as cooking and personal care. This activity is performed in a “home automation room” designed for patients who participated in the rehabilitation program. The purpose of HAT is to evaluate how patients react and interact with this environment, and prepare them for a return home. The room is designed for severely disabled patients who are partially autonomous in their movements. Through a centralized control system, patients can change the environment, monitor some environmental parameters (for example, detect the presence of smoke, water or gas leaks), but also use the alarm bell. Kitchen countertops and other shelves can be adapted in height and depth. The bathroom has an adaptable toilet and shower, which can be changed by the patient. Each different training consisted of 3 sessions per week for eight weeks (i.e. a total of 24 sessions), each session lasting about 60 min. For both the conventional and experimental trainings, treatments were performed in groups, and all the patients were provided with the same amount of treatment. The present study was conducted in accordance with the 1964 Helsinki Declaration and approved by our Research Institute Ethics Committee (ID: IRCCSME 14/2017). Written informed consent was obtained from all the participants. Statistical analysis Data were analyzed using the R programming language version 3.5.0, considering a p < 0.05 as statistically significant. Descriptive statistics were presented as mean ± standard deviation or Median ± first-third quartile, as appropriate, whereas categorical variables as frequencies and percentages. Since distribution of the target variables was non-normal, a non-parametric analysis was performed. Thus, the Wilcoxon signed-rank test was used to compare each group between baseline and the end of the study (intra-group analysis), and the ManneWhitney U test was used to compare the two groups. Comparisons of categorical variables were performed by Chi-squared test. Using the car package of R, we performed the analysis of covariance (ANCOVA) to test for group difference on scores at T1, controlling for scores at baseline. Thus, any model had the test score at T1 as dependent variable, the categorical variable ‘Group’ (1 ¼ CCRG; 0 ¼ TCCR) as independent variable, and the test score at T0 as covariate. The partial ɳ2 was used as measure of effect sizes in ANCOVA and the Cliff's delta was used to compute effect sizes in group comparisons. Results All patients completed the training, and both the groups underwent the same amount of training. No significant differences were found in age (p ¼ 0.55), education (p ¼ 0.62), and in the proportion of gender between EG and CG (p ¼ 0.75). At baseline, no significant differences were detected between the scores of the two groups, except for WEIGL (p ¼ 0.02; d ¼ 0.54) and ADL (p < 0.01; d ¼ 0.79). Results showed that the type of treatment significantly influenced the examined domains. Indeed, ANCOVA controlling for the covariates at T0 revealed a medium-sized main effect on global cognitive functioning (MoCA: F ¼ 7.09; p ¼ 0.01; h2 ¼ 0.19), and a
Please cite this article as: Maggio MG et al., Effects of domotics on cognitive, social and personal functioning in patients with chronic stroke: A pilot study, Disability and Health Journal, https://doi.org/10.1016/j.dhjo.2019.100838
M.G. Maggio et al. / Disability and Health Journal xxx (xxxx) xxx
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Fig. 1. Shows a patient with stroke performing kitchen activities in the domotics context: the patient can modify the environment according to his needs and abilities, using the buttons in the shelves can monitor some environmental parameters (e.g. how to detect the presence of smoke). Furthermore, he can adapt the shelves to height and depth.
large-sized main effect on QoL (SF12 Total: F ¼ 17.01; p < 0.001; h2 ¼ 0.46), both Mental (SF12-MH: F ¼ 34.99; p < 0.001; h2 ¼ 0.94) and Physical (SF12-Ph: F ¼ 18.60; p < 0.001; h2 ¼ 0.50) Health, as well as in social adaption (SASS: F ¼ 9.73; p < 0.01; h2 ¼ 0.26). The highest effect was found on the IADL scales evaluating performance in daily life activities (F ¼ 151.85; p < 0.001; h2 ¼ 4.10), as reported in Table 2. The assumption of homogeneity of regression slopes was not met in some covariate models: HRS-D (F ¼ 16.28; p < 0.001), FAB (F ¼ 12.69; p < 0.01), WEIGL (F ¼ 5.68; p ¼ 0.02) and ADL (F ¼ 12.03; p < 0.01). Thus, for these tests it was not possible to perform ANCOVA. However, we found large effect significant changes in HRS-D (p < 0.01; d ¼ 0.99) and FAB (p ¼ 0.01; d ¼ 0.49) scores between EG and CG at T1, although the scores for these scales were not different at baselines.
Discussion Our study shows that HAT could be effective in improving social functioning, perception of QoL with regard to mental well-being, instrumental life skills (IADL), and functional recovery in patients with chronic stroke impairments. The introduction of new technologies in the home environment, such as robots and sensors, combined with innovative tools, permits the creation of intelligent spaces, in which patient's autonomy can be enhanced.11e13 Improvement in functional independence can positively affect QoL, overall cognitive status, and social/emotional abilities in patients recovering from a stroke.14 Some features of domotics, such as modularity, personalization of skills, system implementation, can encourage patient's compliance to treatment as well as promote greater well-being and better autonomy, especially for his/her
Table 2 Median and interquartile range (IR) of clinical scores at baseline (T0) and follow-up (T1), for both experimental (EG) and control (CG) groups. Clinical assessment
MoCA HRS-D SASS SF-12 TOT SF-12 MH SF-12 Ph FAB WEIGL ADL IADL
Experimental Group
Control Group
ANCOVA Group variable
T0
T1
T0
T1
F value
p value
ɳ2
23.5 (23.0e24.0) 8.0 (5.7e10.0) 42.0 (40.7e52.0) 28.0 (24.0e30.0) 20.0 (11.5e21.5) 12.5 (10.0e14.0) 12.0 (6.0e8.6) 6.5 (8.0e15.9) 3.0 (2.0e3.0) 3.0 (2.7e4.0)
25.5 (25.0e27.2) 5.5 (4.0e6.2) 55.0 (44.0e60.2) 34.0 (29.0e35.2) 28.0 (21.7e29.0) 21.0 (18.0e28.5) 16.3 (14.6e18.0) 14.3 (12.3e15.0) 6.0 (6.0e6.0) 7.0 (6.7e7.2)
24.0 (22.0e24.0) 7.5 (6.0e14.0) 42.0 (35.0e48.5) 29.0 (24.2e32.0) 19.5 (10.0e22.2) 14.5 (10.0e20.0) 12.8 (11.5e14.2) 6.5 (4.6e6.5) 3.0 (3.0e4.0) 3.0 (3.0e4.0)
25.0 (25.0e26.0) 7.5 (6.0e11.0) 42.0 (32.2e53.0) 30.0 (24.7e33.0) 20.0 (10.0e23.2) 15.0 (12.7e20.5) 14.0 (13.7e15.3) 6.5 (5.6e7.5) 4.0 (3.0e4.2) 4.0 (3.0e4.0)
7.09 NA 9.73 17.01 34.99 18.60 NA NA NA 151.85
0.01
0.19
<0.01 <0.001 <0.001 <0.001
0.26 0.46 0.94 0.50
<0.001
4.10
Legend: Activities of Daily Living (ADL); Frontal Assessment Battery (FAB); Hamilton Rating Scale for Depression (HRS-D); Instrumental Activities of Daily Living Scale (IADL); Montreal Cognitive Assessment (MoCA); Short Form-12 Health Survey Total (SF-12 TOT); Short Form-12 Health Survey Mental Health (SF-12 MH); Short Form-12 Health Survey Physical (SF-12 Ph); Social Adaptation Self-Evaluation Scale (SASS); Weigl Test (WEIGL); Not Applicable (NA).
Please cite this article as: Maggio MG et al., Effects of domotics on cognitive, social and personal functioning in patients with chronic stroke: A pilot study, Disability and Health Journal, https://doi.org/10.1016/j.dhjo.2019.100838
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M.G. Maggio et al. / Disability and Health Journal xxx (xxxx) xxx
return to home environment.15e17 Our study suggests that for patients after a stroke it is possible to obtain a greater perception of QoL in daily activities using specific rehabilitation sessions in the HA environment. In fact, the EG got a greater improvement in QoL, and cognitive and behavioral status, as compared to traditional therapy. Patients with stroke may have various symptoms, depending on the location and extent of the lesion. Specifically, post stroke prefrontal syndrome affects executive and visuospatial abilities, as noted in our sample. These skills consist of planning, spatial management, organization, problem-solving, assessment and abstract thinking. Consequently, executive functions are essential for managing everyday life and taking care of oneself (for example, going to the supermarket, planning meals and taking medication). In our sample, we observed an improvement in executive abilities, especially in planning, categorizing and cognitive flexibility. These skills can allow the patients to better control their behavior and organize it in a functional way, in order to achieve their goals with positive repercussions in the IADL.18 Indeed, at the end of treatment, a significant difference emerged between the two groups in the capacity of social adaptation, IADL, and perception of one's physical and mental health. This highlights how HAT may lead to an improvement of the social and personal self-management of these patients, with an increase in their sense of well-being. In line with Abascal et al. work, our data demonstrated that people with sensory, physical or cognitive disabilities may benefit from intelligent environments, as the accessibility and autonomy in daily activities have positive repercussions on the emotional and cognitive level of the patients.19 Indeed, as shown by Riva et al., HA represents a new paradigm that enable people to boost their skills, thanks to a digital environment that is adaptable and responsive to their needs, habits, gestures, and emotions.20 Limitation of the study and conclusion The main limitation of the study is the small sample size, and therefore it should be considered as a pilot study. However, information collected in this study may be useful to plan future trials with a larger sample and long-term follow-up to observe if and to what extent the functional gain is maintained. In conclusion, our results suggest that HAT could be a useful approach for the rehabilitation of patients after stroke, leading to better outcomes in social and cognitive functioning, autonomy and QoL. Authors' contributions All authors substantially participated in the acquisition of data and revision of the manuscript. All authors determined the design, interpreted the data and drafted the manuscript. All authors read and gave-final approval for the version submitted for publication. Declaration of conflicting interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this
article. Funding The authors received no financial support for the research, authorship, and/or publication of these authors. Acknowledgement The authors wish to thank Dr Antonina Donato for English editing. References 1. Coupland AP, Thapar A, Qureshi MI, Jenkins H, Davies AH. The definition of stroke. J R Soc Med. 2017;110(1):9e12. 2. Torrisi M, De Luca R, Pollicino P, et al. Poststroke delusions: what about the neuroanatomical and neurofunctional basis? Appl Neuropsychol Adult. 2018;19: 1e5. 3. Hekmatpou D, Mohammad Baghban E, Mardanian Dehkordi L. The effect of patient care education on burden of care and the quality of life of caregivers of stroke patients. J Multidiscip Healthc. 2019 Mar 20;12:211e217. 4. Maggio MG, De Luca R, Torrisi M, et al. Is there a correlation between family functioning and functional recovery in patients with acquired brain injury? An exploratory study. Appl Nurs Res. 2018;41:11e14. 5. De Luca R, Leonardi S, Spadaro L, et al. Improving cognitive function in patients with stroke: can computerized training Be the future? J Stroke Cerebrovasc Dis. 2018;27(4):1055e1060. 6. Schwamm LH. Digital health strategies to improve care and continuity within stroke systems of care in the United States. Circulation. 2019;139(2):149e151. 7. Krishnan S, Pappadis MR, Weller SC, et al. Needs of stroke survivors as perceived by their caregivers: a scoping review. Am J Phys Med Rehab. 2017;96(7):487. 8. Wolbring G, Lashewicz B. Home care technology through an ability expectation lens. J Med Internet Res. 2014;16(6):e155. 9. Maggio MG, Latella D, Maresca G, et al. Virtual reality and cognitive rehabilitation in people with stroke: an overview. Innovat J Neurosci Nurs. 2019;51(2): 101e105. 10. Poli P, Morone G, Rosati G, Masiero S. Robotic technologies and rehabilitation: new tools for stroke patients' therapy. BioMed Res Int. 2013:153872. 11. Jung JW, Do JH, Kim YM, et al. Advanced robotic residence for the elderly/the handicapped: realization and user evaluation. In: Rehabilitation Robotics. 9th International Conference on Rehabilitation Robotics. Piscataway IEEE; 2005: 492e495. 12. Miori V, Russo D, Concordia C. Meeting people's needs in a fully interoperable domotic environment. Sensors. 2012;12(6):6802e6824. 13. Kanemura A, Morales Y, Kawanabe M, et al. A waypoint-based framework in brain-controlled smart home environments: brain interfaces, domotics, and robotics integration. In: Intellig Robots Syst (IROS). IEEE/RSJ (International Conference on 2013; 2013:865e870. 14. Kamel Boulos MN, Lou RC, Anastasiou A, et al. Connectivity for healthcare and well-being management: examples from six European projects. Int J Environ Res Public Health. 2009;6(7):1947e1971. 15. Meulendijk M, Van De Wijngaert L, Brinkkemper S, et al. AmI in good care? Developing design principles for ambient intelligent domotics for elderly. Inf Health Soc Care. 2011;36(2):75e88. n C, Paya n A, García A, Bosquet F. Domotics project housing block. Sensors. 16. Moro 2016;16(5). 17. Bolzani CA, Montagnoli C, Netto ML. Domotics over ieee 802.15. 4-a spread spectrum home automation application. In: Ninth International Symposium on Spread Spectrum Techniques and Applications. 28. 2006:396e400. 18. Alosco ML, Spitznagel MB, Raz N, et al. Executive dysfunction is independently associated with reduced functional independence in heart failure. J clinical nurs. 2014;23(5-6):829e836. 19. Abascal J. Ambient Intelligence for people with disabilities and elderly people. Vienna: ACM. In: SIGNS Ambient Intelligence Workshop for Scientific Discovery. 2004. 20. Riva G. Ambient intelligence in health care. Cyber Psych Behav. 2003;6: 295e300.
Please cite this article as: Maggio MG et al., Effects of domotics on cognitive, social and personal functioning in patients with chronic stroke: A pilot study, Disability and Health Journal, https://doi.org/10.1016/j.dhjo.2019.100838
Contents lists available at ScienceDirect
Disability and Health Journal journal homepage: www.disabilityandhealthjnl.com
Brief Report
Effects of domotics on cognitive, social and personal functioning in patients with chronic stroke: A pilot study Maria Grazia Maggio a, Giuseppa Maresca a, Margherita Russo a, Maria Chiara Stagnitti a, Smeralda Anchesi a, Carmela Casella b, Caterina Zichitella a, Alfredo Manuli a, a, * Maria Cristina De Cola a, Rosaria De Luca a, Rocco Salvatore Calabro a b
IRCCS Centro Neurolesi “Bonino Pulejo”, Messina, Italy Stroke Unit, AOU Policlinico Universitario “G Martino”, Messina, Italy
a r t i c l e i n f o
a b s t r a c t
Article history: Received 9 January 2019 Received in revised form 31 July 2019 Accepted 11 August 2019
Background: Stroke can cause severe brain lesions, leading to multiple cognitive, emotional and motor disorders. In fact, it is one of the main causes of death and disability worldwide, with a negative impact on quality of life for both patient and caregiver. Home automation (also known as domotics) could allow stroke patients to manage and improve their daily lives. Objective: The aim of our pilot study was to evaluate the effects of domotics on cognitive functions and personal/social autonomy in patients with stroke. Methods: We enrolled 40 patients affected by chronic stroke undergoing neurorehabilitation at IRCCS Centro Neurolesi (Messina, Italy), between June 2017 and March 2019. All of the patients were randomized into either the control group (undergoing traditional training based on face-to-face interaction between therapist and patient, and practical activities), or the experimental group (undergoing Home Automation training). Each participant was evaluated before and immediately after the training period. Each different training consisted of 3 sessions per week for eight weeks (i.e. a total of 24 sessions), each session lasting about 60 min. For both the conventional and experimental trainings, treatments were performed in groups, and all the patients were provided with the same amount of treatment. Results: Patients in the experimental group showed a greater improvement in cognitive and social performance, as compared to the control group. Conclusion: Our study shows that domotics could be effective in improving social and cognitive functioning, autonomy and functional recovery in patients affected by chronic stroke. © 2019 Elsevier Inc. All rights reserved.
Keywords: ADL Cognitive rehabilitation Domotics Home automation IADL
Introduction Stroke is caused by a focal interruption in cerebral blood flow due to occlusion (ischemic stroke) or rupture of a blood vessel (hemorrhagic stroke).1 Stroke can cause severe brain lesions, leading to multiple cognitive, emotional and motor disorders.2 In fact, it is one of the main causes of death and disability worldwide, with a negative impact on quality of life (QoL) for both patient and family.34 Some stroke survivors with reduced independence need family support and specialized care homes, overloading the social
* Corresponding author. IRCCS Centro Neurolesi “Bonino-Pulejo”, SS. 113, Contrada Casazza, 98124 Messina, Italy. ). E-mail address: [email protected] (R.S. Calabro
assistance system as well as increasing healthcare costs. It is therefore important to restore even partial independence in patients with stroke.5e7 Targeted rehabilitation can better address and manage post-stroke disorders, as patients do not always respond to standard therapies. Technological solutions, such as Home Automation (HA or Domotics), can help patients compensate for functional deficits.8e10 HA uses technologies in the fields of ICT (information and communication technologies), automation, architecture and ergonomics, for an innovative and user-centered service.11 HA could enable patients after a stroke to manage their daily lives, responding to care needs, through a supportive environment, which allows patients to regain an active role in everyday life. For HA to be effective, aids must have the characteristics of adaptability and simplicity to allow the easy use of normal household objects.12 Thus, HA could stimulate autonomy in
https://doi.org/10.1016/j.dhjo.2019.100838 1936-6574/© 2019 Elsevier Inc. All rights reserved.
Please cite this article as: Maggio MG et al., Effects of domotics on cognitive, social and personal functioning in patients with chronic stroke: A pilot study, Disability and Health Journal, https://doi.org/10.1016/j.dhjo.2019.100838
2
M.G. Maggio et al. / Disability and Health Journal xxx (xxxx) xxx
patients after stroke.The aim of our pilot study was to evaluate the effects of domotics on cognitive functions and personal/social autonomy in stroke patients. Materials and methods Forty patients with a diagnosis of stroke (mean ± SD age: 58 ± 8.2 years; 60.0% male and 40.0% female), who attended the Robotic and Behavioral Neurorehabilitation Unit of the IRCCS Centro Neurolesi “Bonino-Pulejo” (Messina, Italy) from June 2017 to March 2019, were enrolled in this study and randomly divided into two groups. Twenty patients constituted the control group (CG), and twenty patients the experimental group (EG). A more detailed description of the sample is in Table 1. Randomization was based on a single sequence of random assignments, i.e. simply using a coin. The testers and therapists were blind to the assignment and objectives of the study. Inclusion criteria were: i) first ever supratentorial stroke in the chronic phase (i.e. between 6 and 12 months after the event); ii) presence of mild-to moderate cognitive impairment (Mini-Mental State Examination [MMSE] from 11 to 26); and absence of disabling sensory alterations (i.e. auditory and visual loss). Exclusion criteria were: i) age >85 years; ii) presence of severe medical and psychiatric illness potentially interfering with the training. Each participant was evaluated by a neuropsychologist before (T0) and after the last training session (T1). The neuropsychological battery included: Montreal Cognitive Assessment (MoCA) to assess the general cognitive state; Weigl Test and Frontal Assessment Battery (FAB) to evaluate frontal abilities; Hamilton Rating Scale Depression (HRS-D) to assess mood; SF-12 Health Survey to evaluate QoL; Social Adaptation Self-evaluation Scale (SASS) to assess social adaptation; Activities of Daily Living (ADL), and Instrumental Activities of Daily Living Scale (IADL) to evaluate the functional state in performing daily life activities independently. Two different rehabilitative approaches were used. The CG underwent traditional training that was based on a face-to-face interaction between the therapist and small group of patients (i.e. 3e5 patients per group), practical activities and exercise with paper and pencil, whereas the EG underwent a HA Training (HAT). In traditional training, the therapist led the patient through a series of exercises promoting autonomy in daily life activities. These activities included positioning of marbles, ball exercises, and manipulation of various objects such as buttons for fastening a jacket or zippers. Conventional training is based on direct interaction and exercises with the patients (often working together), who can also use paper/pencil exercises. The purpose of the training is to facilitate homecoming even for severely disabled patients who are
Table 1 Demographics characteristics at baseline for both groups. Experimental Participants 20 Age 53.5 ± 4.8 Education 3.0 ± 0.6 Gender Male 12 (60%) Female 8 (40%) Interval from stroke Mean in months 6±1 Brain lesion site/side Cortical right 12 Subcortical right 6 Cortical left 2 Subcortical left 0
Control
All
P-value
20 54.3 ± 4.2 3.1 ± 0.5
40 53.9 ± 4.5 3.0 ± 0.5
0.36 0.76
10 (50%) 10 (50%)
22 (55%) 18 (45%)
0.97
6±1
6±1
0.99
11 7 2 0
23 13 4 0
0.99
Quantitative variables were expressed as means ± standard deviations, categorical variables as frequencies and percentages.
partially autonomous in their movements. This training allows the use of domestic environments (e.g., kitchens, bathrooms) in an easy way with strategies that permit an effective use.The EG performed the training with the help of HAT, in which the interaction with the therapist was mediated by technological tools to facilitate the achievement of the goals (Fig. 1). HAT also consisted of group activities (3e5 patients per group) in a room where there are several tools built to be easily used by the in-patients. Each tool can be adapted to the needs of the patient. Technologies make it easier to implement everyday life activities, such as cooking and personal care. This activity is performed in a “home automation room” designed for patients who participated in the rehabilitation program. The purpose of HAT is to evaluate how patients react and interact with this environment, and prepare them for a return home. The room is designed for severely disabled patients who are partially autonomous in their movements. Through a centralized control system, patients can change the environment, monitor some environmental parameters (for example, detect the presence of smoke, water or gas leaks), but also use the alarm bell. Kitchen countertops and other shelves can be adapted in height and depth. The bathroom has an adaptable toilet and shower, which can be changed by the patient. Each different training consisted of 3 sessions per week for eight weeks (i.e. a total of 24 sessions), each session lasting about 60 min. For both the conventional and experimental trainings, treatments were performed in groups, and all the patients were provided with the same amount of treatment. The present study was conducted in accordance with the 1964 Helsinki Declaration and approved by our Research Institute Ethics Committee (ID: IRCCSME 14/2017). Written informed consent was obtained from all the participants. Statistical analysis Data were analyzed using the R programming language version 3.5.0, considering a p < 0.05 as statistically significant. Descriptive statistics were presented as mean ± standard deviation or Median ± first-third quartile, as appropriate, whereas categorical variables as frequencies and percentages. Since distribution of the target variables was non-normal, a non-parametric analysis was performed. Thus, the Wilcoxon signed-rank test was used to compare each group between baseline and the end of the study (intra-group analysis), and the ManneWhitney U test was used to compare the two groups. Comparisons of categorical variables were performed by Chi-squared test. Using the car package of R, we performed the analysis of covariance (ANCOVA) to test for group difference on scores at T1, controlling for scores at baseline. Thus, any model had the test score at T1 as dependent variable, the categorical variable ‘Group’ (1 ¼ CCRG; 0 ¼ TCCR) as independent variable, and the test score at T0 as covariate. The partial ɳ2 was used as measure of effect sizes in ANCOVA and the Cliff's delta was used to compute effect sizes in group comparisons. Results All patients completed the training, and both the groups underwent the same amount of training. No significant differences were found in age (p ¼ 0.55), education (p ¼ 0.62), and in the proportion of gender between EG and CG (p ¼ 0.75). At baseline, no significant differences were detected between the scores of the two groups, except for WEIGL (p ¼ 0.02; d ¼ 0.54) and ADL (p < 0.01; d ¼ 0.79). Results showed that the type of treatment significantly influenced the examined domains. Indeed, ANCOVA controlling for the covariates at T0 revealed a medium-sized main effect on global cognitive functioning (MoCA: F ¼ 7.09; p ¼ 0.01; h2 ¼ 0.19), and a
Please cite this article as: Maggio MG et al., Effects of domotics on cognitive, social and personal functioning in patients with chronic stroke: A pilot study, Disability and Health Journal, https://doi.org/10.1016/j.dhjo.2019.100838
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Fig. 1. Shows a patient with stroke performing kitchen activities in the domotics context: the patient can modify the environment according to his needs and abilities, using the buttons in the shelves can monitor some environmental parameters (e.g. how to detect the presence of smoke). Furthermore, he can adapt the shelves to height and depth.
large-sized main effect on QoL (SF12 Total: F ¼ 17.01; p < 0.001; h2 ¼ 0.46), both Mental (SF12-MH: F ¼ 34.99; p < 0.001; h2 ¼ 0.94) and Physical (SF12-Ph: F ¼ 18.60; p < 0.001; h2 ¼ 0.50) Health, as well as in social adaption (SASS: F ¼ 9.73; p < 0.01; h2 ¼ 0.26). The highest effect was found on the IADL scales evaluating performance in daily life activities (F ¼ 151.85; p < 0.001; h2 ¼ 4.10), as reported in Table 2. The assumption of homogeneity of regression slopes was not met in some covariate models: HRS-D (F ¼ 16.28; p < 0.001), FAB (F ¼ 12.69; p < 0.01), WEIGL (F ¼ 5.68; p ¼ 0.02) and ADL (F ¼ 12.03; p < 0.01). Thus, for these tests it was not possible to perform ANCOVA. However, we found large effect significant changes in HRS-D (p < 0.01; d ¼ 0.99) and FAB (p ¼ 0.01; d ¼ 0.49) scores between EG and CG at T1, although the scores for these scales were not different at baselines.
Discussion Our study shows that HAT could be effective in improving social functioning, perception of QoL with regard to mental well-being, instrumental life skills (IADL), and functional recovery in patients with chronic stroke impairments. The introduction of new technologies in the home environment, such as robots and sensors, combined with innovative tools, permits the creation of intelligent spaces, in which patient's autonomy can be enhanced.11e13 Improvement in functional independence can positively affect QoL, overall cognitive status, and social/emotional abilities in patients recovering from a stroke.14 Some features of domotics, such as modularity, personalization of skills, system implementation, can encourage patient's compliance to treatment as well as promote greater well-being and better autonomy, especially for his/her
Table 2 Median and interquartile range (IR) of clinical scores at baseline (T0) and follow-up (T1), for both experimental (EG) and control (CG) groups. Clinical assessment
MoCA HRS-D SASS SF-12 TOT SF-12 MH SF-12 Ph FAB WEIGL ADL IADL
Experimental Group
Control Group
ANCOVA Group variable
T0
T1
T0
T1
F value
p value
ɳ2
23.5 (23.0e24.0) 8.0 (5.7e10.0) 42.0 (40.7e52.0) 28.0 (24.0e30.0) 20.0 (11.5e21.5) 12.5 (10.0e14.0) 12.0 (6.0e8.6) 6.5 (8.0e15.9) 3.0 (2.0e3.0) 3.0 (2.7e4.0)
25.5 (25.0e27.2) 5.5 (4.0e6.2) 55.0 (44.0e60.2) 34.0 (29.0e35.2) 28.0 (21.7e29.0) 21.0 (18.0e28.5) 16.3 (14.6e18.0) 14.3 (12.3e15.0) 6.0 (6.0e6.0) 7.0 (6.7e7.2)
24.0 (22.0e24.0) 7.5 (6.0e14.0) 42.0 (35.0e48.5) 29.0 (24.2e32.0) 19.5 (10.0e22.2) 14.5 (10.0e20.0) 12.8 (11.5e14.2) 6.5 (4.6e6.5) 3.0 (3.0e4.0) 3.0 (3.0e4.0)
25.0 (25.0e26.0) 7.5 (6.0e11.0) 42.0 (32.2e53.0) 30.0 (24.7e33.0) 20.0 (10.0e23.2) 15.0 (12.7e20.5) 14.0 (13.7e15.3) 6.5 (5.6e7.5) 4.0 (3.0e4.2) 4.0 (3.0e4.0)
7.09 NA 9.73 17.01 34.99 18.60 NA NA NA 151.85
0.01
0.19
<0.01 <0.001 <0.001 <0.001
0.26 0.46 0.94 0.50
<0.001
4.10
Legend: Activities of Daily Living (ADL); Frontal Assessment Battery (FAB); Hamilton Rating Scale for Depression (HRS-D); Instrumental Activities of Daily Living Scale (IADL); Montreal Cognitive Assessment (MoCA); Short Form-12 Health Survey Total (SF-12 TOT); Short Form-12 Health Survey Mental Health (SF-12 MH); Short Form-12 Health Survey Physical (SF-12 Ph); Social Adaptation Self-Evaluation Scale (SASS); Weigl Test (WEIGL); Not Applicable (NA).
Please cite this article as: Maggio MG et al., Effects of domotics on cognitive, social and personal functioning in patients with chronic stroke: A pilot study, Disability and Health Journal, https://doi.org/10.1016/j.dhjo.2019.100838
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M.G. Maggio et al. / Disability and Health Journal xxx (xxxx) xxx
return to home environment.15e17 Our study suggests that for patients after a stroke it is possible to obtain a greater perception of QoL in daily activities using specific rehabilitation sessions in the HA environment. In fact, the EG got a greater improvement in QoL, and cognitive and behavioral status, as compared to traditional therapy. Patients with stroke may have various symptoms, depending on the location and extent of the lesion. Specifically, post stroke prefrontal syndrome affects executive and visuospatial abilities, as noted in our sample. These skills consist of planning, spatial management, organization, problem-solving, assessment and abstract thinking. Consequently, executive functions are essential for managing everyday life and taking care of oneself (for example, going to the supermarket, planning meals and taking medication). In our sample, we observed an improvement in executive abilities, especially in planning, categorizing and cognitive flexibility. These skills can allow the patients to better control their behavior and organize it in a functional way, in order to achieve their goals with positive repercussions in the IADL.18 Indeed, at the end of treatment, a significant difference emerged between the two groups in the capacity of social adaptation, IADL, and perception of one's physical and mental health. This highlights how HAT may lead to an improvement of the social and personal self-management of these patients, with an increase in their sense of well-being. In line with Abascal et al. work, our data demonstrated that people with sensory, physical or cognitive disabilities may benefit from intelligent environments, as the accessibility and autonomy in daily activities have positive repercussions on the emotional and cognitive level of the patients.19 Indeed, as shown by Riva et al., HA represents a new paradigm that enable people to boost their skills, thanks to a digital environment that is adaptable and responsive to their needs, habits, gestures, and emotions.20 Limitation of the study and conclusion The main limitation of the study is the small sample size, and therefore it should be considered as a pilot study. However, information collected in this study may be useful to plan future trials with a larger sample and long-term follow-up to observe if and to what extent the functional gain is maintained. In conclusion, our results suggest that HAT could be a useful approach for the rehabilitation of patients after stroke, leading to better outcomes in social and cognitive functioning, autonomy and QoL. Authors' contributions All authors substantially participated in the acquisition of data and revision of the manuscript. All authors determined the design, interpreted the data and drafted the manuscript. All authors read and gave-final approval for the version submitted for publication. Declaration of conflicting interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this
article. Funding The authors received no financial support for the research, authorship, and/or publication of these authors. Acknowledgement The authors wish to thank Dr Antonina Donato for English editing. References 1. Coupland AP, Thapar A, Qureshi MI, Jenkins H, Davies AH. The definition of stroke. J R Soc Med. 2017;110(1):9e12. 2. Torrisi M, De Luca R, Pollicino P, et al. Poststroke delusions: what about the neuroanatomical and neurofunctional basis? Appl Neuropsychol Adult. 2018;19: 1e5. 3. Hekmatpou D, Mohammad Baghban E, Mardanian Dehkordi L. The effect of patient care education on burden of care and the quality of life of caregivers of stroke patients. J Multidiscip Healthc. 2019 Mar 20;12:211e217. 4. Maggio MG, De Luca R, Torrisi M, et al. Is there a correlation between family functioning and functional recovery in patients with acquired brain injury? An exploratory study. Appl Nurs Res. 2018;41:11e14. 5. De Luca R, Leonardi S, Spadaro L, et al. Improving cognitive function in patients with stroke: can computerized training Be the future? J Stroke Cerebrovasc Dis. 2018;27(4):1055e1060. 6. Schwamm LH. Digital health strategies to improve care and continuity within stroke systems of care in the United States. Circulation. 2019;139(2):149e151. 7. Krishnan S, Pappadis MR, Weller SC, et al. Needs of stroke survivors as perceived by their caregivers: a scoping review. Am J Phys Med Rehab. 2017;96(7):487. 8. Wolbring G, Lashewicz B. Home care technology through an ability expectation lens. J Med Internet Res. 2014;16(6):e155. 9. Maggio MG, Latella D, Maresca G, et al. Virtual reality and cognitive rehabilitation in people with stroke: an overview. Innovat J Neurosci Nurs. 2019;51(2): 101e105. 10. Poli P, Morone G, Rosati G, Masiero S. Robotic technologies and rehabilitation: new tools for stroke patients' therapy. BioMed Res Int. 2013:153872. 11. Jung JW, Do JH, Kim YM, et al. Advanced robotic residence for the elderly/the handicapped: realization and user evaluation. In: Rehabilitation Robotics. 9th International Conference on Rehabilitation Robotics. Piscataway IEEE; 2005: 492e495. 12. Miori V, Russo D, Concordia C. Meeting people's needs in a fully interoperable domotic environment. Sensors. 2012;12(6):6802e6824. 13. Kanemura A, Morales Y, Kawanabe M, et al. A waypoint-based framework in brain-controlled smart home environments: brain interfaces, domotics, and robotics integration. In: Intellig Robots Syst (IROS). IEEE/RSJ (International Conference on 2013; 2013:865e870. 14. Kamel Boulos MN, Lou RC, Anastasiou A, et al. Connectivity for healthcare and well-being management: examples from six European projects. Int J Environ Res Public Health. 2009;6(7):1947e1971. 15. Meulendijk M, Van De Wijngaert L, Brinkkemper S, et al. AmI in good care? Developing design principles for ambient intelligent domotics for elderly. Inf Health Soc Care. 2011;36(2):75e88. n C, Paya n A, García A, Bosquet F. Domotics project housing block. Sensors. 16. Moro 2016;16(5). 17. Bolzani CA, Montagnoli C, Netto ML. Domotics over ieee 802.15. 4-a spread spectrum home automation application. In: Ninth International Symposium on Spread Spectrum Techniques and Applications. 28. 2006:396e400. 18. Alosco ML, Spitznagel MB, Raz N, et al. Executive dysfunction is independently associated with reduced functional independence in heart failure. J clinical nurs. 2014;23(5-6):829e836. 19. Abascal J. Ambient Intelligence for people with disabilities and elderly people. Vienna: ACM. In: SIGNS Ambient Intelligence Workshop for Scientific Discovery. 2004. 20. Riva G. Ambient intelligence in health care. Cyber Psych Behav. 2003;6: 295e300.
Please cite this article as: Maggio MG et al., Effects of domotics on cognitive, social and personal functioning in patients with chronic stroke: A pilot study, Disability and Health Journal, https://doi.org/10.1016/j.dhjo.2019.100838