1 Introduction
Smart homes to support mental illness are an appealing new concept but have not yet been implemented at the community level as a form of mental health care or support. Literature reviews have found that hospitalizations, burden on care providers, consultation and wait times, and health care costs can all be reduced through health monitoring technology [1]. Although new technologies are rapidly developed for the consumer market, many are not stringently tested in a mental health care setting; leading to a lack of robust literature. This rapid pace of development also means that new technological advances become obsolete quickly over time [2].
Mobile technologies such as smartphones have been utilized to support mental illnesses such as bipolar disorder [3] and schizophrenia [4]. Patient beneficence and well-being can also be supported using smart technology by providing greater access to information and resources, as well as through symptom tracking and monitoring features [5]. A systematic review of smart technology for mental illness detailed that smartphone applications were the most studied, but monitoring and adherence supports were lacking significantly [6]. A more recent systematic review also revealed that research into technological interventions based on the Internet of Things model is still lacking, with mental health data scattered and segregated depending on the vendor/platform for these devices [7]. A smart technology intervention should require minimal input and provide continuous monitoring passively that does not interfere with daily activities.
Advertisement
Physical activity can also be an indicator for changes to mental health and/or indicative of a crisis. Including physical activity into daily routines can be difficult, particularly as symptomology, motivation, experience, fatigue and poorer access to resources are common considerations for people with mental illness [8]. This is particularly pertinent during the current time with physical activity and mean peak heart rate readings decreasing significantly during COVID-19 lockdowns [9]. As such, the use of smart technology to maintain a healthy lifestyle is even more needed, particularly among vulnerable individuals who may experience barriers due to their health status, lack of accessibility or socioeconomic status.
Early inceptions of the current study, each lasting 12 months, attempted to provide supportive systems within an individual’s environment in hospital settings and transitional hospital apartments [10]. The prototype intervention provided in the hospital setting was largely successful. This study set out to establish the use of smart technology in assisting individuals with mental illness and physical comorbidities living in housing provided by the Canadian Mental Health Association (CMHA) and London-Middlesex Community Housing (LMCH). The objective of this study was to establish and evaluate smart home technology in the community to assist people with mood and psychotic disorders. We hypothesized that the smart technology would: a) increase levels of community integration; b) increase housing stability; c) decrease health, justice, and social service utilization; and d) support mental and physical health.
The study also sought to answer the following research questions: a) What are client and staff experiences of smart mental health homes? b) How do clients and staff perceive the utility of smart technologies in the home? c) What improvements to the technologies do they suggest? d) What ethical issues are identified with the use of smart mental health homes? e) What policy issues are identified with the use of smart homes? f) What commercialization issues are identified by key stakeholders in relation to smart homes?
2 Method
Design
Advertisement
This study used a within-group, mixed-methods, repeated-measures design. Interviews were conducted over three assessment timepoints conducted at baseline (Time 1), 6-month (Time 2) and 12-month (Time 3) follow-ups. The assessments included an individual interview with each participant. However, due to the COVID-19 pandemic, interviews and focus groups were switched to virtual and telephone formats, and focus groups were conducted via a one-to-one discussion instead to maintain safety as well as convenience for participants. Ethical approval was obtained through Western University’s Research Ethics Board.
Sample
The research team first recruited health care providers who then referred potential participants for the study. Participants from a range of housing types were eligible to take part. The inclusion criteria for participants were as follows: 1) Must be on a caseload of a participating health care provider; 2) Able to understand English to the degree necessary to participate; 3) Living in housing provided by the CMHA or LMCH; 4) Diagnosed with a psychotic or major mood disorder; 5) Must be between the ages of 18–85 years old; 6) Able to provide informed consent.
Intervention
This study consisted of two interactive platforms, the Lawson Integrated Database (LIDB) and the Collaborative Health Record (CHR). The LIDB is an information management platform that collates and manages health data and is protected behind the St.Joseph’s Health Care hospital firewall [11]. It is a web-based application that can be accessed by health care professionals and research staff via secure log-in. The LIDB connects to the clouds of health monitoring devices and is able to automatically export data from each cloud encrypted authentication keys and SSL connectivity. The CHR allows health care providers to send questionnaires (“Qnaires®”), both standardized or customized, as an SMS text message, email or both to participants. The link then opens to a custom webpage with the questionnaire for participants to complete. The platform has the additional feature of videoconferencing and instant messaging. Care providers were able to securely log-in to the LIDB and CHR to view data from their participant’s health monitoring devices and Qnaires® respectively.
Screen devices offered included smartphones (Samsung J3®) and wall-mounted touch-screen computer monitors powered by a Raspberry Pi-3 B+® mini-computer. The latter were developed by the research team programmer who also designed and customized the interface. These devices received and responded to prompts from the LIDB to assist participants experiencing cognitive deficits and to facilitate self-care. Participants were able to “acknowledge” prompts and reminders on the touchscreen monitors by pushing a “Got It” button on screen which sent an automated email to the care providers who set that reminder. Additionally, a button which says “Please get in touch with me” was included, which sent a message to the participant’s care team requesting them to schedule a meeting.
Health monitoring devices that were offered to participants included a Withings Nokia Body+® smart weigh scale, a Fitbit Charge 3® activity tracker and a Karie® automated medication dispenser developed by Ace Age. Apps for each of these devices were added to the participants’ smartphones so that they could also track and monitor their own data. Although activity logs for device usage were not recorded, health care providers could observe the measurements provided by the health devices through the LIDB thereby providing an idea as to frequency of device usage.
Procedure
The research team met with prospective participants and after obtaining informed consent, participants selected the equipment they felt they needed and completed the baseline interview. Interviews were conducted one-to-one with a member of the research team either in-person or virtually. Equipment selections were then verified and approved by the participant’s health care provider before being installed by the research team’s programmer. Training on the equipment was provided by the research team programmer as well as the research coordinator. Technological literacy was measured at baseline through the demographics measure of the interview. Health care providers also received training on how to use the devices, CHR and LIDB by the research coordinator. The research coordinator contacted the participants monthly to check in on any potential technical difficulties and offered assistance if issues arose. Calls and emails were made to health care providers to offer support and troubleshooting with the LIDB, CHR and any general concerns regarding the devices.
Focus groups with participants and health care providers were conducted separately to avoid one group from influencing the other. These were conducted in a group format prior to the COVID-19 pandemic but then switched to virtual groups or a one-to-one discussion via telephone or teleconferencing software.
Instruments
The following assessments tools were utilized for the semi-structured interviews conducted with participants: Community Integration Questionnaire - Revised (CIQ-R) [12], Short-Form 36 (SF36) [13], the Health, Social and Justice Service Utilization (HSJSU) questionnaire [14], EuroQol-5 Dimension-3 Level (EQ-5D3L) [15], and a Perception of Smart Technology Questionnaire. The latter was a researcher-developed measure that assessed participants’ attitudes and opinions of the devices provided. Demographic and housing history data were also collected during each interview. The CIQ-R was the primary outcome measure. Open-ended qualitative questions regarding the use of the devices and software platforms were utilized during the focus groups and one-to-one discussions.
Data Analysis
The participants’ health, housing, service utilization and community integration were assessed using the instruments. Descriptive statistics are provided for the outcome measures. Due to the small sample size, comparative analyses across timepoints were not possible, and generalization beyond the sample is limited by its size. Qualitative data was analyzed using a thematic ethnographic approach [16] to ascertain collective experiences and implications. Data collected from the health devices and the Qnaires® were not obtained for analysis by the research team in order to maintain participant privacy and not to interfere with the patient-provider therapeutic relationship.
3 Results
A total of 13 participants were interviewed at baseline. Table 1 summarizes the demographic characteristics of the sample. Nine participants completed the full 12-month study; two passed away due to natural causes before Time 2. At Time 3, one declined to complete the interview while the other participant could not be reached. No participants experienced housing instability throughout the course of the study. Two participants were eventually moved from group homes to independent apartments. The vast majority of participants were single or never married (n = 10), indicating that these participants may need additional support if they are living alone.
Table 1.
Demographics (N = 13)
Age (mean (SD)) | 43 (15) |
|---|---|
Sex | |
Female | 8 |
Male | 5 |
Marital Status | |
Single/Never Married | 10 |
Separated/Divorced | 2 |
Widowed | 1 |
Housing Status | |
Independent Apartment | 9 |
Group Home | 4 |
Psychiatric Diagnoses | |
Anxiety Disorder | 9 |
Mood Disorder | 7 |
Psychotic Disorder | 5 |
Disorder of childhood/adolescence | 3 |
Personality Disorder | 3 |
Substance-related disorder | 1 |
Physical Diagnoses | |
Fibromyalgia | 3 |
Back Pain | 2 |
Diabetes/Endometriosis/Hemorrhoids/Hepatitis B/Hypertension/ Irritable Bowel Syndrome/Peripheral Vasculitis/Polycystic Ovary Syndrome/Sleep Apnea/Ulcer (Foot) | 1 for each |
In terms of technological literacy, the participants were asked at baseline to score their experience with devices (see Fig. 1). The sample overall indicated they were comfortable with technology. Participants largely rated that they were comfortable with technology in general. Three participants reported they were “extremely comfortable”, six reported they were “comfortable”, and two participants each reported they were “slightly comfortable” and “slightly uncomfortable” respectively.
Quantitative Findings
Community Integration Questionnaire - Revised. The mean scores on all CIQ-R subscales and CIQ-R Total score across all 3 timepoints are reported in Table 2. The CIQ-R asked participants how often they completed certain activities and whether someone else assisted or completed these activities.
Table 2.
Community Integration Mean Scores
Time 1 (N = 13) Mean (SD) | Time 2 (N = 11) Mean (SD) | Time 3 (N = 9) Mean (SD) | |
|---|---|---|---|
CIQ-R Total (/35)
| 20.7 (5.69) | 21.7 (4.67) | 21.6 (4.99) |
Missing (n) | 2 | 2 | 1 |
Home Integration (/12)
| 8.81 (2.25) | 9.56 (1.61) | 8.63 (2.25) |
Missing (n) | 1 | 2 | 1 |
Social Integration (/10)
| 5.92 (2.06) | 6.00 (2.21) | 5.78 (2.86) |
Missing (n) | 0 | 1 | 0 |
Productivity (/7)
| 2.33 (1.78) | 2.27 (2.10) | 2.22 (1.79) |
Missing (n) | 1 | 0 | 0 |
Electronic Social
Networking (/6)
| 3.23 (1.48) | 3.00 (1.95) | 3.78 (1.79) |
Missing (n) | 0 | 0 | 0 |
Short Form 36.
The mean scores on all SF-36 subscales across all 3 timepoints are reported in Table 3. Subscales are scored on a scale of 0–100, with higher scores representing better health outcomes.
Table 3.
Short form 36 mean scores
SF-36 Subscale | Time 1 (N = 13) | Time 2 (N = 11) | Time 3 (N = 9) |
|---|---|---|---|
Physical Functioning | 53.1 (34.3) | 51.7 (33.3) | 53.9 (37.6) |
Role limitations due to physical health | 51.9 (42.6) | 47.5 (50.6) | 36.1 (41.7) |
Role limitations due to emotional problems | 46.2 (44.2) | 23.3 (35.3) | 55.6 (47.1) |
Energy/fatigue | 43.5 (17.0) | 34.3 (16.8) | 49.4 (26.4) |
Emotional well-being | 59.1 (19.2) | 54.0 (21.9) | 57.8 (21.6) |
Social functioning | 52.9 (22.9) | 46.3 (22.9) | 59.7 (35.2) |
General health | 41.9 (18.8) | 38.5 (21.2) | 44.4 (27.9) |
Health, Social and Justice Service Utilization.
A variety of health and social services were accessed throughout the study. Table 4 maps out the utilization of these services.
Table 4.
Services accessed at all timepoints
Services in past month | Response | Time 1 (N = 13) | Time 2 (N = 11) | Time 3 (N = 9) |
|---|---|---|---|---|
Seen a healthcare or social service provider at their office | Yes No Sum | 12 1 49 | 8 3 23 | 2 7 18 |
Talked on the phone with health or social service provider | Yes No Sum | 6 7 24 | 6 5 33 | 5 4 14 |
Visited by healthcare or social service provider | Yes No Sum | 6 7 69 | 3 8 19 | 2 7 41 |
Past 6 Months | ||||
Outpatient services at hospital | Yes No Declined Sum | 6 7 0 18 | 4 6 1 28 | 2 7 0 10 |
Called Crisis Line | Yes No Declined Sum | 3 10 0 2 | 5 5 1 192 | 4 5 0 22 |
Visited by Crisis Team | Yes No Declined Sum | 1 12 0 - | 1 9 1 180 | 1 8 0 10 |
Emergency Room Visits | Yes No Sum | 7 6 22 | 8 3 40 | 4 5 12 |
Been in an Ambulance | Yes No Sum | 6 7 10 | 7 4 15 | 3 6 6 |
EQ-5D-3L.
The Visual Analogue Scale revealed participant’s mean self-report ratings of their overall health, physical health and mental health from Time 1 to 3 on a scale of 0 (lowest health) to 100 (best health) (see Table 5).
Table 5.
EQ-5D-3L visual analogue scale scores
Time 1 (N = 13) M(SD) | Time 2 (N = 11) M(SD) | Time 3 (N = 9) M(SD) | ||
|---|---|---|---|---|
Visual Analogue Scale | Overall Health | 68.5(12.7) | 64.1(15.8) | 58.2(26.6) |
Mental Health | 68.1(15.2) | 64.6(22.0) | 67.8(17.3) | |
Physical Health | 60.4(16.6) | 54.6(18.5) | 55.2(29.3) |
Perception of Smart Technology.
Three key questions from the questionnaire are reported below. The first inquired as to whether participants felt the technologies improved their health care (see Fig. 1). This was asked at Times 2 and 3 after the technologies had been implemented. The second focused on acceptability of the technologies in the home. The majority of participants responded favourably at Time 2 – Mixed (1), Mostly Satisfied (2), Pleased (4) and Delighted (4). At Time 3 there was a slight increase in positive ratings – Mostly Satisfied (1), Pleased (3), Delighted (5).
Fig. 1.
Perception of improvements to health care following the use of smart technologies.
The third key question focused on recommendations for what devices should be added to future interventions. The suggestions were evenly spread with a blood pressure cuff receiving the most recommendations (2), followed by a tablet, a smart television, smart glucometer, a Google Home® device and a newer model of Fitbit® (all 1). However, the most frequent answer was “Nothing else/None” (3) as participants felt the devices offered as part of this study provided suitable coverage for their needs.
Qualitative Findings
Several themes pertaining to healthy living were discussed by the participants. Participants noted that they were motivated to be healthier through exercising and maintaining a healthy weight. The health data on the apps on their smartphones allowed them to track their progress which provided a level of accountability.
The scale especially um it, it, it allowed me to keep track of what was happening as far as weight and things like that went and um yea it didn’t, it has motivated me um to start watching my diet and things like that.
Health care providers also reported that their clients were becoming more motivated to use the devices provided to lead healthier lifestyles and, in some cases, assist with symptoms of pre-existing physical conditions.
Uh, I definitely noticed, um, that she was able to maintain a healthy lifestyle, um, in term, or I guess a healthy weight. There was, you know, only small fluctuations in their weight, but it was nice to see that. Cause I know they, they talk about that a lot. Um, just wanting to, because they have another, um, illness related to their weight, like polycystic ovarian syndrome. So they were, it was more of like an important thing to focus on managing or getting, you know, getting to be a healthy weight so that the symptoms of that are minimized.
Other participants noted benefits to their mental health through this new ability to be healthier and through the cognitive supports the technology offered.
I have issues with memory and being able to have reminders to drink water. Um, how, cause instead of feeling more lethargic and fatigued from not drinking water, um, I felt less lethargic, less fatigued. Therefore it increased my mood because I wasn’t sleeping all the time. And for me, a trigger for depression is sleeping all the time.
It was noted that the technologies were also able to support mental health through a biofeedback approach with the devices monitoring physical activity.
...and like as I say the, the Fitbit, especially the pulse um the heart rate um is, is really helpful because um if I’m having problems with my mental state sometimes, I need to look at, especially with anxiety, I need to look at my pulse and, and sort of be aware of it and help, it can help me bring it down...
Enhanced communication was also seen as a major benefit of the study. Participants noted they were able to maintain communication with their friends, family, and health care providers during the pandemic.
Um, well being connected with your family definitely helps you with your mental health and like being able to follow-up with appointments and stuff like that. Um, yeah and I also have been able to like, find resources about my mental health like on CAMH and stuff like that and um meditation resources as well.
Many health care providers also spoke of the social benefits of providing participants with a smartphone but also noted that the technology enhanced communication with the care providers as well as flexibility in communicating with them.
...Like some clients especially like with mental health, they find it easier for them to, instead of talking to someone over the phone, to text and communicate that way.
There were numerous instances of participants noting that the reminders and prompts from the technology provided them with the support needed to maintain healthy lifestyles and live safely in their own homes. In particular, participants with the medication dispenser noted that they no longer missed doses.
Having the ability to monitor um the, the medication was a problem and the technology just sort of took that problem away because it replaced the need for me to keep track of things.
With technological interventions, there are also some limitations and barriers to overcome. One such issue is device reliability. There were some issues regarding the accuracy of their readings and difficulties with connectivity.
Yeah, um, but when I switched phones it was very difficult to get um, to get my Fitbit to sync over Bluetooth.
A precipitating factor for technical difficulties could be the lack of technological literacy and understanding how specific devices worked. Although monthly refreshers were provided by the research team, health care providers highlighted that frequent retraining would be recommended.
I think there was, um, a few items that like the clients weren’t really familiar with or like, knew how to use our troubleshoot, even though like, I don’t know, maybe I’m just the younger generation. I know how to use it. Like the Fitbit. They don’t really know how to like sync it or look at their data on their, on the app, on the phones and stuff.
It is also recommended that alternative devices are available for participants who require additional assistance with using technology.
Like I said, I have hand tremors, so takes me awhile to get it to work.
In terms of future improvements for commercialization, the health care providers suggested simplifying the approach to a single integrated database or as an app.
You’ll have to be streamlined through a maybe single-handed maybe app? ... that will probably be uh better, for future reference, and it could be uh quite heavily used then.
Ethical Analyses.
This project's findings suggest that the use of the technologies advances equity and fairness by increasing access to care for people experiencing mental illness and physical comorbidities. During the COVID-19 pandemic, participants were able to access care from the safety of their own home using the technologies provided by the study. Another ethical advantage of this project was that it enhanced autonomy of participants, reducing their dependence on some health services such as by using the medication dispenser device. Overall, this project's findings are promising from an ethical perspective and suggest the need for larger scale research on such technological interventions.
Policy Analyses.
It was felt that it would be purposeful to propose an amendment to the Assistive Devices Act to incorporate smart technologies as assistive devices for mental health. Devices aimed at supporting mental health are not currently covered by the Assistive Devices Act. Individuals with mental illness or agencies supporting this population would have to purchase the devices themselves. For individuals in other jurisdictions, amending current policy to provide funding for technological innovations in the home to support mental illness would be advantageous.
×
![]()
4 Discussion
There is a lack of literature on community-integrated research that utilizes a systems-level novel approach to health and smart technology. Smart technology interventions, such as this study, should be designed to provide support a range of physical and mental health conditions [17]. This study positions itself as a foundation for future research among individuals with mental illness to build upon. As there was a small sample size, it would be difficult to argue that this intervention represents a definitive approach to mental health care, but provides an impetus for new research to cover some of the gaps currently in the literature. Data from the Perception of Smart Technology questionnaire supported that the technologies were well-accepted and used by participants of different age groups. As the majority of participants were single or never married, this intervention may be a needed support for individuals living along without immediate assistance. The connectivity of the intervention with care providers could help to mitigate potential risks that may arise due to isolation or a lack of communication.
A key strength for this intervention was the use of non-clinical devices that are accessible to the public. Data from the clouds of these devices were able to be transmitted and collated in one database, the LIDB. Health care providers were able to access all the data in one location as opposed to individual databases or independent datasets. This allowed for a tailored approach where each participant could have a customized intervention. Participants were also able to connect their smartphone (either their own, or one provided as part of the study) to their devices and access the data themselves using the devices’ apps. An implication for future research is to measure the effects of smart technology among a larger sample with other mental and physical health conditions. It would be highly beneficial for potential researchers to track health data (i.e. weight, steps, activity, heart rate, etc.) empirically to assess the impact on health behaviours and physical condition.
There is also the opportunity to utilize this intervention to support physical conditions that may benefit from activity and weight tracking and notifications from a health care team. This study found that smart technology was able to promote healthy lifestyle choices. Based on the qualitative findings, the devices acted as an accountability tool which provided encouragement and motivation for healthier living. Frequent observation and self-monitoring of health data using personal digital assistants and daily feedback messages have been linked with weight loss [18].
A systematic review by Liu et al. [19] reported there is no evidence that technology tracking and monitoring biometric data resulted in improvements to quality of life or disability. However, the qualitative findings of this study suggest that the feedback from the health adjunct devices and their respective apps on the smartphones can be helpful. The use of an activity tracker to encourage physical activity and exercise may have been the most contributory piece of equipment in this regard. Participants reported how the technologies supported mental health such as mood and anxiety through greater communication and the ability to monitor physical health more easily. Cognitive support was also described in assisting participants to remember tasks such as taking and tracking medications. There was some discussion among participants that the weigh scale and the activity tracker may have occasionally given inaccurate readings. Future studies would be advised to frequently check devices for accuracy during the course of the study and allay participant concerns.
The COVID-19 pandemic meant lockdowns were enforced during the course of the study. Individuals with mental illness and physical conditions are especially vulnerable to the negative outcomes of isolation and distancing [20]. The COVID-19 pandemic meant that virtual and telephone interviews were conducted instead. Although participants were satisfied with these arrangements, some participants were difficult to contact and required multiple sessions to complete the interview. The technician for this study provided technical support where possible but opportunities to visit the participant and check the devices were limited.
Due to the small sample in this study, regression analyses were not conducted; thus, findings should be interpreted with consideration to this. However, the data collected from questionnaires are pertinent as it provides better understanding of the characteristics of individuals with mental and physical health diagnoses who may benefit from smart technology use. Notably, it was observed through questionnaire scores that there was high heterogeneity in our sample and in participants responses (e.g., frequency of service utilization). Further research into the use of smart technology with individuals who have mental illness with a larger sample is warranted. All participants from this study were recruited from the same, moderate-sized, city. A larger study with a variety of locations including more rural-based individuals may reveal different experiences and learnings.
5 Conclusion
This study establishes that a smart home technological intervention is a feasible, reliable, and safe way to provide additional support in the home. The provision of commercially available devices may provide a suitable alternative or an additional option for in-home support. These technologies can supplement healthy living behaviours which could lead to other health benefits such as weight loss, as supported by the qualitative analyses. Participants noted a self-reported increase in physical activity, diet tracking and greater access to mental health support. The COVID-19 pandemic likely impacted health, social and justice service utilization therefore studies exploring this, including this study, needs to be interpreted with caution. This study can act as a foundation for future research to build upon by exploring other applications and populations with this intervention. Future studies and technological innovations would be advised to offer in-home technologies that can be easily implemented into the living environment and to address gaps currently in the literature.
Acknowledgments
We would like to acknowledge Lawson Health Research Institute, St. Joseph’s Health Care, London Health Sciences Centre, Canadian Mental Health Association and London Middlesex Community Housing for facilitating the research environment. We would like to thank the participants and care providers for their voluntary participation. Finally, we would also like to acknowledge the granting agency, Canada Mortgage and Housing Corporation, for funding this project.
Conflicts of Interest
The authors declare no conflict of interest.
Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.