Reflexive case studies on conducting technology implementation research in long-term care homes

Abstract

Background

Technological advancements offer the potential to address healthcare challenges, such as improving residents’ quality of life in long-term care homes (LTCHs). However, there is often a mismatch between developed technologies and the actual needs of residents and staff, leading to poor adoption. Researchers conducting research on developing and implementing technologies in LTCHs face unique challenges. Understanding these challenges is crucial for enhancing technology adoption and sustainability in LTCHs.

Methods

This qualitative reflection study is about the experiences of two technology implementation projects in British Columbia and Ontario, Canada. Researchers from the Telepresence Robot and MouvMat projects participated in four reflection sessions. Using reflexive thematic analysis, we identified themes and gained valuable insight into the experiences, lessons learned, and recommendations.

Results

Both projects faced challenges in recruitment, accommodating individual residents’ needs and routines, staff shortages and turnover, and logistics barriers due to infrastructural limitations and changing guidelines. The Telepresence Robot and the MouvMat teams implemented a range of adaptive strategies. These included frequent check-ins with families, creating appropriate training materials, co-developing tailored solutions, flexible recruitment approaches, staff engagement tactics, and personalized support.

Conclusion

The lessons learned highlighted the need for adaptive strategies in conducting research in LTCHs. The study calls for structural support and partnerships between academics and practice locally, nationally, and internationally, as well as efforts to combat ageism in technology use. Researchers need support for knowledge translation and sharing findings to highlight the value of staff participation and showcase research benefits.

Keywords

Gerontology gerontechnology senior care implementation interdisciplinary collaboration innovative solutions learning health system digital health

Background

The population of older adults over 65 is projected to reach 1.5 billion worldwide by 2050.¹ In Canada, there will be an increase of 22%–32% of the population over 65 years old in 2074.² With the increasing older population, the demand for care in long-term care homes (LTCHs) is also expected to increase. According to a recent projection by Kotschy and Bloom,³ on average, the demands for long-term care in 30 developed countries will increase from 2.9% to 4.2% of the population by 2024.

In response to these demands and the current challenges in LTCHs such as staff shortages and social isolation,⁴ various digital health interventions have been rapidly developed and implemented in LTCHs. For example, studies in Canada reported their implementation of innovations such as virtual reality and telepresence robots to promote person-centered care and virtual team-based care in LTCHs.^4–8 Globally, research in Europe, Asia, and America also explored the development and adoption of a broad spectrum of technology,⁹ varying from care robots, and tablets, to video-based exercise games to support the well-being of residents and improve workflow for care and administrative tasks.^9–17

Regardless of the emerging trend, researchers identified and reported challenges and barriers to adoption. For example, technology was not adequately or sustainably adopted by staff;^9,18 further, studies in the Netherlands, China, and Canada identified the lack of policy support to address staff's concerns in this process and enable system-wide technology adoption in LTCHs.^10,14,19 There is an urgent need for researchers to explore pressing issues, including the feasibility of the technology implementation in long-term care (LTC), the facilitators and barriers to implementation, and the adaptation of the technology for the specific needs of the older population.

It is also crucial for researchers to critically reflect and share the unique challenges, successes, and lessons learned during their research projects in LTCHs. These reflections help build resilience in the LTC research community to conduct research, maintain consistency with research designs, and continue the research projects during a crisis. A few papers highlighted and shared their experiences in the research process in LTCHs and critically reflected on the lessons they had learned. A recent study by Tremblay et al.²⁰ shared the challenges of conducting qualitative research in healthcare settings during the COVID-19 pandemic, including time constraints and physical distancing. Despite the challenges, some researchers discovered opportunities for virtual data collection through technologies. Hung et al.⁸ shared how their research team virtually used telepresence robots to conduct research in LTCHs during the COVID-19 pandemic. However, there are limited studies by researchers that reflect on the research designs, the process, and the challenges of projects regarding technology implementation in LTCHs. An evidence brief report by Gauvin et al.¹⁹ shared difficulties in implementing new technologies in LTCHs, such as the risks of negative outcomes and difficulties due to the current research infrastructure and financial support.

Our study addresses the gap in reflecting on the challenges and strategies in the research processes of two technology implementation studies in British Columbia and Ontario, Canada. The paper aims to outline the pan-Canadian researchers’ experiences in implementing innovations in LTCHs. It provides insights and guidance for those conducting implementation research in LTCHs, encourages researchers to reflect on their research process, and advocates for better support from governments and healthcare organizations for implementation research in LTC settings. Emphasizing the need for continued research efforts, we call for actions at national, provincial, organizational, and individual levels to drive positive changes and ensure that care delivery in LTCHs meets the needs of residents.

Methods

This article is a critical reflection by team members from the Telepresence Robot (LH, LR, and JW) and the MouvMat project (CC and HB) on their experiences implementing technology in LTC. Team members attended four 1-hour reflection sessions facilitated by CC and LH in person and virtually.

The reflection is guided by Rolfe et al.'s reflective model,²¹ which includes three questions: What? (What is it?), So what? (Why is it important?), And now what? (What should we do next?). In our paper, we reflected on the following questions: What challenges did we face in the technology implementation? What did the team do to overcome the obstacles? How can the technology implementation be enhanced in the future? Reflection sessions were audio-taped and transcribed.

We analyzed our reflection data using Braun and Clarke's reflexive thematic analysis.^22–25 Our process included: (a) familiarizing ourselves with the data from the reflection sessions, (b) LR, HB and JW coding the data, discussing and resolving coding disagreement among the three members, (c) generating initial themes, (d) reviewing the preliminary themes as a whole team, discussing and comparing the relationships between themes, (e) refining and reaching consensus on the final themes as a whole team, and (f) writing and editing the results collaboratively. Table 1 shows the examples of theme generation.

Table 1.

Examples of theme generation.

Quotes	Codes	Theme
“To accommodate the busy schedules of front-line staff, our team offered flexibility by waiting for available staff or arranging meetings during their break times.” “It was challenging to engage all staff in orientations with the staff turnover. There were new staff from time to time who were not aware of the robots on the unit.”	Challenges due to staff shortages Challenges due to staff turnover Orientation and knowledge of technology Needs for research team to accommodate staff schedules	Staff shortages and high turnover
“The staff champion played an essential role in recruitment. At the initial stage of the project, when COVID was more severe, we sent the robot to the care home. Our staff champions spent time working with the telepresence robot before our team could go in to provide in-person support. They helped to identify potential participants with their preliminary understanding of the robots.” “The homes had very active family councils; research teams’ direct engagement with family members in environments where they were likely to be present and receptive to information about the study increased the likelihood of their participation.”	Recruitment strategy Recruitment challenges during the COVID-19 pandemic	Barriers to recruiting participants and delivering an in-person intervention

To ensure credibility, we provided a thick description of the two studies. Team members from diverse backgrounds and living in two different provinces in Canada practiced reflexivity and challenged each other's assumptions during the reflection process.²⁶ HB, JW, and LR are graduate student research trainees, while CC and LH are nursing researchers and the principal investigators of the MouvMat Study and the Telepresence Robot Study.

Refer to the Supplementary File for the COREQ Checklist.

Projects overview

Telepresence robot study

The telepresence robot project is a three-year study initiated in May 2021 focusing on using remotely controlled mobile robots with wheels for virtual communication and social connections in LTCHs in Vancouver, Canada. Telepresence robots (see Figure 1) allow virtual communication and are remotely controlled by family members with stable Internet connections. Family members can initiate the video call and control the robot's movements without staff assistance. The study aimed to: (a) explore staff perceptions of adopting telepresence robots in LTC, (b) identify facilitators and barriers to implementation, (c) examine residents’ and families’ experiences of using these robots, and (d) evaluate the impact of telepresence robots on residents and family caregivers. The Consolidated Framework for Implementation Science²⁷ and Caregiver Centred Model²⁸ guided our project (e.g., data collection and analysis) in exploring implementation challenges and participants’ experiences.^23,24,29

Figure 1.

A telepresence robot.

The inclusion criteria for the Telepresence Robot Study were as follows: For residents, (a) with a diagnosis of dementia (various types, from early to later stages), (b) able to speak and communicate in Chinese and English. For family members, (a) family members of residents recruited, (b) able to speak and communicate in Chinese and English. For frontline staff, (a) work on-site in frontline positions, (b) work in a full-time or part-time position. The sampling of residents, staff and family members was initially determined by the study's scope and objectives. Final sample decision was made collaboratively by the research team during data collection, based on data richness and complexity to ensure robust results for the research questions.³⁰

The research team includes patient partners living with dementia, family partners, frontline staff, community partners, trainees, and researchers following the Collaborative Action Research.³¹ A key member is a patient partner living with Alzheimer's, serving as the study's co-lead. These partners provided key support in discussing the challenges and planning mitigation strategies based on their lived experiences during the research process. The project was particularly timely due to the COVID-19 pandemic, which heightened the isolation and loneliness experienced by residents in LTCHs. While devices like phones and tablets were already used for communication by some older adults, the pandemic accelerated technology adoption. It highlighted the need for innovative solutions like telepresence robots, which can operate without staff being present for support. Staff shortages and the need for staff assistance to use the tablets have been a challenge in care settings. In response, we deployed 20 robots across five LTC settings in Vancouver, British Columbia, to improve virtual communication between residents and their families.

Mouvmat study

MouvMat (see Figure 2) is an exergaming technology with an interactive digital gaming surface that was co-designed with a user-centered design approach for older adults (OA) living in LTCHs.^6,32 The interdisciplinary research team and LTCH residents and staff first conceived of the exergaming technology during a 3-day design workshop. The technology was then designed and iterated in multiple rounds of user testing over a period of 18 months.³² The researchers aimed to conduct a multi-site pilot randomized control trial to evaluate the acceptability, efficacy, and adaptability of exergaming technology on mobility, cognitive function, and social isolation.

Figure 2.

MouvMat.

The inclusion criteria for the MouvMat study were as follows: (a) age ≥ 55, (b) fluent in English, (c) MMSE score ≥ 20, (d) generally attended activities and sessions at home, (e) did not have history of aggressive or violent behavior or severe dementia, (f) able to sufficiently hear and see audio and visual prompts, (g) could walk independently, use a walker or rollator, or wheelchair. Participants were excluded if they could not communicate or speak English, had an MMSE score <20, did not typically participate in recreational activities, or had severe sensory (e.g., deaf, blind) or severe to moderate cognitive impairment. The sample size for the study was based on the TUG outcome measure. It was calculated using an effect size of 0.65, power of 0.85, and alpha 0.05 (two-tailed). With a 5% attrition rate, the research team planned to recruit 56 participants; however, challenges with recruitment led to a smaller sample size.

Initially planned for April 2020, the study initiation faced delays as the research team encountered restrictions on visiting LTCHs due to COVID-19 safety measures. Consequently, the research officially commenced in late 2022 when LTCHs were willing to engage in research, with an anticipated conclusion by late 2024.

The following presents the challenges and how the research teams navigated them in implementing the telepresence robots and evaluating the MouvMat technology in LTCHs.

Results

Key challenges and mitigation strategies employed by the telepresence robot study

Challenging to recruit participants and provide in-person technical support

The telepresence robot was implemented during the COVID-19 pandemic, where researchers had challenges entering the LTCHs and recruiting participants in person. The support from the staff champion made recruiting participants smoother. A Telepresence Robot team member reflected,

The staff champion played an essential role in recruitment. At the initial stage of the project, when COVID was more severe, we sent the robot to the care home. Our staff champions spent time working with the telepresence robot before our team could go in to provide in-person support. They helped to identify potential participants with their preliminary understanding of the robots.

Besides recruitment, the Telepresence Robot team faced challenges in scheduling in-person training for family members. A team member reflected, “Many family members, such as those less familiar with using technologies, needed extra support to drive the robot back to its charging dock, and some experienced frustrations with call disconnections due to unstable WiFi at the care homes.” Therefore, the research team created an electronic form of the family package with step-by-step guides and online instructional videos to help family members.

Individual needs and routines of residents

The residents participating in the Telepresence Robot study adapted to the telepresence robots differently due to a broad spectrum of cognitive and physical impairments. For example, some residents with dementia needed more time to adapt to the robots, some residents were talking softly where the family members could not hear clearly from the other side, and some residents had hearing impairments that they could not hear clearly from the family members via the robot. Besides, as some family members had 24/7 access to the telepresence robot in the resident's room, they sometimes called in when staff provided care for residents, which might lead to an unintentional disruption of care routines.

To address these conditions, the Telepresence Robot research team conducted frequent check-ins (both virtually and in-person) with family members, residents, and staff to explore their experiences and barriers and find possible facilitators to support them. A team member elaborated on their way to navigate the needs of these residents,

The team worked with the industrial partner to figure out ways to support the optimal use of the telepresence robots. For example, we added headsets for residents with hearing impairments and asked for ways to enhance the residents’ voices captured by the robot.

The research team also facilitated conversations with staff and family members to coordinate call times. The staff agreed to cover the robots’ cameras during care activities, and family members cooperated by ending calls when staff were performing care for residents.

The mitigation strategies enhanced the calls to a more optimal volume for residents and family members. There were also fewer concerns from family members and staff about unmatched call times.

Staff shortages and high turnover

The single-site staffing order, which limited LTC employees working between nursing homes,³³ exacerbated staff shortages in LTCHs.³⁴ To drive the initial momentum of using the robot amidst the staff shortage situation, the Telepresence Robot team recruited a few champions at the sites interested in technology at the start of the project. They initially worked closely with one to two frontline staff champions in each site. Frequent communications with these staff champions allowed them to ask questions and become more comfortable with the robot in the implementation phase. Their in-person data collection and staff engagement were interrupted multiple times due to COVID-19 outbreaks at the sites. When our research team could not be on-site, staff champions were crucial in providing updates to residents and families and checking the robots. However, staff champions were sometimes unavailable due to vacations, off-hours, or weekends, making it difficult for the research team to gain support from other staff members.

For the Telepresence Robot project, the pandemic also posed challenges in relationship-building with staff members. With high staff turnover, some staff were unaware of the project, while others were concerned about what the robot could do. Some staff worried that the robots might be used to monitor or spy on their work activities. The following are some examples of staff engagement strategies in the Telepresence Robot study:

Building confidence and trust. The team coordinated remote training to address staff's concerns about the robot and anticipated implementation issues. Responding promptly to technical challenges reported by staff enhanced their trust in the research team and encouraged open discussions for problem-solving.

Visualization. The team produced training materials, including posters, infographics, and videos about the project, and shared these materials through check-ins, huddles, and interviews.

Creating positive experiences. The team disseminated success stories and positive staff experiences with the robot through monthly newsletters. The team also incorporated gamification into training sessions and awarded staff prizes to provide a sense of achievement (see Figure 3).

Acknowledgment. The team delivered greetings and small gifts and invited staff to social activities held by the research team (see Figure 4). The team created social media posts, issued certificates, and featured staff contributions, strengthening their sense of ownership and responsibility in the project.

Figure 3.

The research team and the care team, after a telepresence robot training.

Figure 4.

A staff member upon receipt of a gift of appreciation from the research team.

After implementing these mitigation strategies, the Telepresence Robot research team observed enhanced relationships with the staff. Staff members were more engaged in supporting the use of the robots, felt it easier to voice their problems and share positive stories they observed with the research team, and were more familiar with the basic functions of the robots and how to maintain and charge them.

Logistic barriers due to limited infrastructural support

There were limitations regarding infrastructure and spaces in LTCHs in the Telepresence Robot study. An unstable internet connection often leads to disconnected or delayed calls. The lack of centralized support for the Internet and technology from the local health authority made it more challenging for the research team to address the Internet issue. Though the research team worked with staff to develop innovative coping strategies, such as providing Wi-Fi boosters, staff underscored the need for centralized IT resources to support the implementation of robots.

Furthermore, having limited spaces in care settings was challenging. Double occupancy and cluttered rooms hindered the placement and mobility of the robots, raising privacy concerns and creating distractions during virtual family calls. Family members found it challenging to drive the robot in a tight space and return it to the charging dock. The research team collaborated with staff and family members to find suitable spaces for the robots, ensuring they did not obstruct wheelchairs or care activities, which facilitated the ongoing use of robots in those rooms.

Key challenges and mitigation strategies employed by the MouvMat study

Barriers to recruiting participants and delivering an in-person intervention

The MouvMat research team encountered recruitment challenges for LTCHs as potential study sites after the heights of COVID-19 in Ontario from 2020 to 2022. These difficulties were primarily due to the outbreak of COVID-19, resulting in stringent policy changes and a notable lack of responsiveness from the LTCHs as the pandemic response required all their human resources. The recruitment and engagement of family members of the residents into the MouvMat study after COVID-19 presented substantial hurdles. Families had not yet returned to their full visitation schedules in the homes enrolled in the study.

The MouvMat research team implemented several strategic interventions. Firstly, recruitment posters were deployed within LTCHs, and presentations were delivered at family council meetings. The homes had very active family councils; research teams’ direct engagement with family members in environments where they were likely to be present and receptive to information about the study increased the likelihood of their participation. Recruitment posters and family council presentations leveraged existing community structures and communication channels within LTCHs, thus ensuring that the study's information reached a relevant audience in an impactful manner.

Secondly, the protocol for the MouvMat study was adjusted for subsequent LTCHs. A novel approach involved leaving consent forms in the residents’ rooms, specifically targeting family members visiting the LTCHs. This was a change from the RA trying to schedule a time to speak to the family member. The strategy was predicated on the assumption that providing easily accessible information in a private and familiar setting would lower barriers to engagement. The presence of consent forms in residents’ rooms allowed family members the convenience of considering participation at their own pace and within a context that directly connected them to the implications and benefits of the research. This addressed the challenge of engaging family members who may have been difficult to reach through more conventional means. This method also allowed families to engage with the researchers to build trust and understand the development of the MouvMat, potentially motivating them to participate in the study to enhance resident outcomes in this setting. These strategies increased the engagement and participation of family members in the study.

Individual needs and routines of residents

Besides the impact of the COVID-19 outbreak, the study could be impacted by individual residents’ conditions. As the MouvMat project was a physical activity intervention study designed around the concept of a prescribed “dose” of the MouvMat, participants were expected to engage in three sessions weekly over a 6-week duration. However, the feasibility of this schedule was compromised by instances where residents were unable to participate due to external commitments such as appointments, receiving visitors, or hospital stays. Under these circumstances, residents were marked absent for the missed session and were scheduled to rejoin subsequent sessions upon improvement in their condition. A team member reflected, “At times, individuals chose not to participate due to personal or emotional reasons. In such situations, we respected their autonomy and personal choice.” To mitigate this challenge, the MouvMat team followed the protocol to the best of their ability, proceeding with the planned sessions and assessments with the remaining residents. Measurement outcomes were collected within a specified “grace” period instead of a specific day to accommodate for short potential delays. However, prolonged absences due to illness or hospitalization led to the withdrawal of residents from the study if they were absent for an extended period, specifically if more than a third of the sessions were missed (beyond 2 weeks), to maintain the integrity and validity of the study.

Staff shortages and high turnover

Technology implementation studies require leaders’ support and buy-in from research site staff. Yet, it was well documented that COVID-19 exacerbated chronic structural deficiencies within the LTC sector, resulting in heavy workloads, staff shortages, high turnover, and the use of agency staff.³⁵ Given current working conditions, front-line staff at LTCHs were not readily available to participate in the study.

To mitigate these constraints, the research protocol of the MouvMat study was adapted to require the most responsible clinical staff member per resident to provide a pre- and post-intervention interview involving a staff member who could speak about more than one resident, for example, the unit's recreational therapist. A team member reflected, “To accommodate the busy schedules of front-line staff, our team offered flexibility by waiting for available staff or arranging meetings during their break times.” This approach was met with appreciation from the LTCH staff; they valued the research team's consideration and flexibility.

Additionally, high staff turnover presented the issue of new staff members being unfamiliar with the ongoing MouvMat study, leading to confusion regarding unit activities and where the exergaming sessions occurred. For example, new staff members taking breaks in these spaces would occupy the activity areas because they were unfamiliar with the study. This made it difficult for the research team to coordinate the logistics of conducting the intervention, as LTCHs have limited physical spaces that are freely available. To address this, the research team implemented a strategy of introducing the study to each new staff member upon their arrival, which included providing detailed information about the study's requirements. The team also printed signs and placed them on the door the morning of the intervention sessions, so all staff and residents were aware, thereby ensuring continuity and clarity in the research process within the LTCH environment.

Logistic barriers due to changing guidelines

The challenges encountered in conducting research within LTCHs during the COVID-19 pandemic stemmed from restrictions occurring on multiple levels: at the home level, with varying COVID-19 protocols, and at the policy level, exemplified by the implications of Ontario Bill 7 on resident demographics.

The variability in COVID-19 protocols across LTCHs presented logistical barriers to simultaneously implementing the physical activity intervention at multiple homes. Each LTCH had differing and constantly changing testing frequencies, mask mandates, and vaccination requirements, so coordinating regular in-person sessions three times a week every week for six weeks became challenging. The Ministry of Long-Term Care in Ontario and the local public health unit frequently updated the policies.³⁶ Our compliance with these protocols was crucial for the safety of both residents and research staff, potentially limiting the frequency or format of intervention sessions. The COVID-19 policies, in addition to other infectious disease policies (e.g., influenza), prevented residents from different units from congregating at the same place. Residents needed to remain within their designated units, which limited the ability to gather participants from multiple units for group-based interventions. The MouvMat team adopted the study by conducting the intervention sessions for each unit separately with a smaller number of people at a higher frequency, which significantly increased the duration and cost of the study in terms of resources, staff availability, and logistics. The policies also resulted in complete bans on the research team in affected units, which caused delays in recruitment and the study's initial implementation.

Further, following the enactment of Ontario Bill 7,³⁷ there have been discernible shifts in the demographic makeup of residents within LTCHs, as MouvMat was co-designed with LTCH residents before COVID-19. The Bill 7 legislation mandates the transfer of hospitalized older adults needing alternative levels of care to LTCHs, as determined by hospital physicians who assess them as no longer requiring acute inpatient care. Consequently, LTCHs admitted (or readmitted) residents who were too medically complex for the LTCH environment and with greater levels of cognitive impairment, resulting in increased hospital readmission rates compared to the period prior to Bill 7. This could have resulted in reduced recruitment rates and impacted the feasibility of conducting the intervention as originally planned. Furthermore, the majority of residents were no longer eligible for the study, which impacted the feasibility of conducting the intervention as originally planned. The MouvMat research team responded by modifying the eligibility criteria, for example, including residents who were wheelchair-bound and were unable to stand for 2 minutes and conducting the study at twice the number of LTCHs that was initially intended.

Table 2 summarizes the challenges and mitigation strategies applied in the two studies and their impact.

Table 2.

A summary of challenges, mitigation strategies, and their impact.

Challenges	Mitigation strategies	Impact
Challenging to recruit participants and provide in-person technical support and intervention	Telepresence Robot Study Support from staff champions Provide e-materials for the family's orientation on using telepresence robots MouvMat Study Recruitment through posters and presentations at family council meetings Placed consent forms in residents’ rooms Modified eligibility criteria of the study by reducing the age range and including wheelchair-bound residents Instead of conducting the study at one site, recruit residents at multiple sites	Reached a relevant audience Increased engagement and participation More inclusive recruitment Increased sample size
Individual needs and routines of residents	Telepresence Robot Study Frequent check-ins to explore staff, residents’ and family members’ experiences, barriers, and possible facilitators that could support them (e.g., headsets, audio boosting function) Coordinate with staff and family members regarding call times MouvMat Study Apply flexibility, conduct assessments to ensure the resident is well enough to attend the research activities	Accommodate residents’ needs and support their participation in the MouvMat Study More optimal robot calls Fewer concerns about unmatched call times
Staff shortages and high turnover	Telepresence Robot Study Initial training for a few staff champions to build confidence and trust User-friendly materials, e.g., newsletters, posters and videos, make the education fun using gamification Acknowledge successes MouvMat Study Involved the most responsible clinical staff member who could speak about more than one resident for the interview Offered flexibility to accommodate front-line staff schedules, negotiate a time suitable for them to attend the research activity Repeated introduction of each new staff member to the study Posted signs on room doors for intervention sessions to aid communication with staff	Increased staff involvement Respect staff needs and do not disrupt daily LTCH activities Ensured clarity in the research process Enhanced relationships between the research team and staff members Staff are more familiar with robot functions
Logistic barriers due to limited infrastructural support and changing guidelines	Telepresence Robot Study Worked with staff and organization to problem solve together, e.g., explore ways to facilitate the Internet connection and find suitable spaces for robot placement MouvMat Study Followed guidelines, made adaptations to create intervention groups to deliver the intervention separately to a smaller number of people at higher frequencies	Facilitated the ongoing use of robots for residents Enhanced feasibility of the study according to the guidelines and requirements in LTCHs Negative Impact (MouvMat) Increased duration and cost of study

Discussion

Through the implementation of two distinct technologies across pan-Canadian LTCHs, we identified common challenges faced by both research teams. These include difficulties with recruitment, accommodating diverse residents’ needs and routines, delivering in-person training and interventions, managing staff shortages and turnover, and navigating logistic barriers due to limited infrastructural support and changing guidelines. While each team applied different mitigation strategies, both recognized the need for a collaborative effort to advance and support technology research in LTCHs.

The following section discusses and compares the common challenges with existing literature and proposes recommendations for future research and practices to empower future technology research in LTCHs. We call for national, provincial, and local structural support to strengthen the partnerships between research teams, leaders, and staff in care settings.

Infrastructural support and partnerships building for long-term care homes research

Our pan-Canadian experiences in the difficulties and advocacy for support to engage LTCH in research were similar to findings from global and local studies and reports.^38,39 Internationally, a systematic review of research conducted in LTCH across Western countries identified a significant challenge in recruiting and retaining LTCH to participate in clinical research.³⁹ Homes were reluctant to participate, making research uncommon for most LTCHs.³⁹ Similarly, recruiting LTCHs as research sites and conducting studies within them poses significant challenges for research teams.⁴⁰ The difficulties in recruiting and retaining staff and the high turnover rate of LTCH staff made it difficult for research teams to discuss ideas and sustain partnerships with LTCH management.^41–43 In addition, many LTC staff worried that the research topic may not align with their institutional policies and leadership priorities.⁴⁴ Some had concerns that the studies could lead to negative publicity.⁴⁵ Inequality among LTCHs, such as differences in internet access,⁶ also poses a challenge for research teams requiring Wi-Fi to support their technological interventions. There is also an underlying systemic issue of inadequate funding for publicly funded LTCHs and the resulting limited resources and a long waiting list for LTCH beds across many provinces in Canada.⁴⁶ Canadian scholars have suggested research and policy changes to improve the quality of care and organizational structure of LTCHs within Canada. However, no fundamental changes have been made.^47,48 Strategies can be considered at different levels for securing infrastructural support for health research and research related to technologies in LTCHs.

National level

A model that Canada could adopt is the United Kingdom's (UK) initiative called ENRICH (Enabling Research in Care Homes).⁴⁹ This model, supported by the National Institute for Health Research, aims to improve the health and well-being of older adults living in LTCHs through dedicated research efforts. It fosters collaboration with LTCH staff, residents, and researchers, facilitating a range of studies to meet their specific needs. The ENRICH initiative comprises a list of prevalent health conditions within LTCHs requiring research, outlines the advantages of conducting research in these settings, and provides guidance to researchers on how to prepare, approach, and conduct research within LTCHs, among various other resources.⁴⁹ Adopting a similar framework in Canada would make it easier for research teams to recruit LTCHs and save researchers time and resources.⁵⁰

For example, organizations at the national level, such as the Institute of Aging of the Canadian Institutes of Health Research, can set up a similar national network to pan-Canadian researchers conducting research in LTCHs, connecting care homes with researchers and connecting care homes that are interested in research opportunities nationally. Establishing organizations similar to the Research Institute for Aging and the Ontario Centres for Learning, Research and Innovation in Long-Term Care can help sustain partnerships with LTCHs for research-related projects. Besides potential funding support, this network can promote research opportunities and recruit care homes interested in partnering with researchers, ensure the readiness of care homes’ infrastructures and spaces for conducting technology studies, and allow researchers to understand the priorities of research needs of the care homes. To support research at LTCHs, literature suggested solutions, including providing continued education opportunities to frontline staff, owners, and administrators.³⁹ Research networks can assist in building capacity within LTCHs that have the resources to engage and provide opportunities for direct care staff to participate in co-designing projects and innovations. Frontline staff are well aware of the care gaps and can provide insights into the development of innovations.⁵¹

Provincial level

A report by the BC COVID-19 Strategic Research Advisory Committee provided possible solutions to address the lack of infrastructure in LTCHs to support research partnerships, including developing strategies to enable LTC leadership to participate in research effectively and engaging LTC leaders in opportunities to develop research partnerships.⁵² Local homes and academic institutes can work more closely together under the support of a national research network to support research-driven practices that improve the quality of life and care for older adults living in LTCHs.^53,54 In addition, adopting a learning health systems (LHS) model could also promote research in LTCHs by consolidating information obtained from real-world experiences and research.^55,56 Learning health systems are ecosystems that provide relevant and actionable feedback in a format that is easily understandable and applicable to the team's work.^55,56 Local health authorities’ leaders can initiate an LHS among health authorities and local LTCHs, forming a collaborative team of researchers, LTCH staff, clinicians, residents, and caregivers engaging in open dialogues on research-related topics. Such initiatives would mitigate differences and negative connotations amongst researchers and LTCHs and provide continuous growth, improvement, and learning opportunities.

Local level

A strong partnership between research teams and LTCHs benefits both parties.⁴⁰ Such partnerships facilitate researchers gaining insights into care delivery practice and generating new knowledge. However, researchers can be viewed as “outsiders” of care homes, making their goals for research activities, such as participant recruitment and data collection in care homes, challenging to achieve. Meanwhile, a key staff member or opinion leader in a care team as an “insider” can ease these processes. Congruent with the literature, our experiences demonstrated that the care home staff-researcher relationship is imperative for both parties to achieve their goals.^24,57 Consistently providing staff with sufficient training, addressing their needs, and acknowledging their work can enhance the possibility for both parties to collaboratively achieve their shared and individual goals.⁵⁸ Guided by the individual and implementation process domains of the Consolidated Framework for Implementation Research²⁷ and our reflection, we propose the C.A.R.E. Framework to foster collaboration between LTCH researchers and maintain a long-term relationship between academia and LTCHs:

Collaborating by preparing both parties with key formal and informal leader contacts to work together and build trust.

Adapting organizational culture in care homes to prioritize partnerships with researchers, especially in homes with less severe staff shortages.

Representation of the voice of staff and residents in research projects should be amplified.

Equipping staff with support and guidance in navigating shared responsibilities between care homes and researchers, including staff training, acknowledgment, and fun celebrations.

Previous studies indicated that some media reports and social media discussions related to LTCHs resulted in furthering the negative impact of LTCHs.^59–61 Such a negative impact could likely lead to a reduction in the attractiveness of the sector to individuals interested in employment in the LTC sector and erode the public trust of current and prospective residents and family caregivers. Thus, we call for researchers to expand the knowledge dissemination of their research findings in multiple forms and channels (e.g., social media, newsletters, videos, websites, blogs). Researchers should also provide direct feedback to residents and their families, for example, through the use of personalized infographics at the end of the study. Timely knowledge translation can inform improvements in health research, delivery, and outcomes in LTCHs. The LTC sector is likely to benefit from the abovementioned efforts as such efforts are likely to enhance the sector's appeal generally, boost public confidence, and streamline the knowledge translation process.

Impact of ageism in health and technology research in LTCHs

The challenges experienced in the two cases, e.g., lack of resources and staff concerns, exemplify how LTC homes are not supported in adopting technologies and echo the prevalence of ageism towards LTC and older adults in some existing literature.^62–64 Ageism is defined as “the stereotypes (how we think), prejudice (how we feel) and discrimination (how we act) directed towards others or oneself based on age” by the World Health Organization.⁶⁵^,p2 Ageism pervades different sectors, including healthcare. This institutional ageism shapes research and data collection, impacts the policies that depend on the data and statistics, and is associated with the objectification of residents, the neglect of residents’ needs, and attempts to save expenses in the LTC settings.⁶⁶ There are assumptions about residents’ preferences and capabilities. Older people are stereotyped as “needy,” “easily confused,” and “unpowered.”⁶⁵^,p4 These restricted opportunities are due to older adults’ age and residence in an LTC home. Assumptions that residents are “not technologically competent” can also manifest as digital ageism embedded in the design, deployment, and evaluation of technologies, including artificially intelligent technologies.^40,63 With digital ageism, older adults are often excluded from the development of digital technology.⁶⁷ Even if they are engaged in the development, they may not be included in all stages of research.⁶⁷ This exclusion may inadvertently lead to the development of technology-enabled interventions that are not user-friendly for residents, potentially exacerbating the digital divide and limiting the accessibility and effectiveness of technological interventions intended to improve their quality of life. There is also an example where the reduced application of digital technology intervention was associated with the negative stereotypes of healthcare professionals about older adults using digital technologies.⁶⁸ The impact of ageism on technology access and adoption can be further exacerbated by its intersection with other biases such as ableism and socio-economic status. For example, being excluded from technology research projects in LTCHs due to residents’ physical limitations and unable to participate in technology research requiring the availability of digital devices or a stable internet connection at home for residents’ families with economic hardships.

In our two projects, the lack of support in recruitment, infrastructural spaces, and human resources did not favor researchers conducting research in LTC homes. Consequently, our research teams needed extra effort and time to overcome the structural and resource challenges of conducting research in LTCHs rather than co-designing with residents and understanding the residents’ experiences using the technologies in more depth. Without time and support for research in LTCHs, it is more challenging for researchers to engage the voices of residents, family members, and LTCH staff in the broader conversations about technological advancements in LTCHs. Furthermore, user-friendly designs that adapt to the needs of residents, staff, and family care partners in the LTC settings require perspectives from these individuals.

A cultural reform against ageism in LTCHs needs to be reinforced, starting from different levels of staff to the public. With continuous technological advancements, we advocate that LTCHs have the infrastructure to support basic digital technologies.⁶ Older adults have the right to experience leisure, joy, and fun with programs and technologies suitable for their needs. Patient-oriented research on technologies to support residents’ quality of life should be included and prioritized in the LTCHs’ management agenda.

Implications for future research

Future research can adapt and evaluate the suggested mitigation strategies with mixed-methods evidence when working on relevant research regarding technology use in LTCHs. Potentially, researchers can examine the sustained technology use post-study to evaluate the long-term impact of the mitigation strategies. Researchers can also explore adapting, adopting, and implementing national and regional infrastructures similar to the UK's ENRICH program to support research within LTCHs. Future studies are suggested to continue the investigation on effective engagement with staff and establish and continue partnerships with the care team. Furthermore, research about various methodologies, such as co-design, should be done in LTCHs across provinces to combat ageism among staff, residents, and family members. As our study is based on metropolitan LTCHs, researchers working in rural LTCHs can further explore the adaptation and build on the proposed mitigation strategies to enhance residents’ quality of life in different areas.

Strengths and limitations

Some of the challenges we faced and the strategies taken to engage staff have not been reported in the literature. This article contributes unique perspectives from two research teams in Canada conducting technology research to improve residents’ quality of life during the COVID-19 pandemic. Few studies have discussed the impact of researchers’ virtual education and relationship-building with staff on their motivation and confidence to use technology in their work. Limited literature also mentions adopting different training materials developed by the research team during COVID-19 to facilitate the staff's understanding of the project, the technology, and its benefits. This makes the study relevant and timely in the context of the pandemic. Further, innovative approaches to increasing staff's interest in training, acknowledging their contribution to implementing technology, and enhancing peer influence have been underexplored. Our experiences were drawn across different types of LTCHs that we collaborated with, including public, non-profit, and private. Lastly, the pan-Canadian nature of the study incorporates diverse perspectives and promotes nation-level coordination.

Our reflection was based on and limited to the two types of technology we implemented in LTCHs, which are a telepresence robot and a co-designed exergaming platform, MouvMat. The implementation of other types of technologies in LTCHs (e.g., virtual reality) was not included, as our focus was on understanding the implementation of these two emerging technologies in LTCHs. Our LTCHs were in metropolitan areas, which is not representative of the rural LTC settings in terms of different infrastructural and resource challenges. Further adaptation of implementation and mitigation strategies in relevant research projects in these areas may be needed. Our reflection on the partnered LTCHs is potentially subject to survivorship bias. LTCHs willing to participate in our studies may demonstrate different strengths and challenges from those care homes that declined or were not included in our studies. Both research teams did not perform a formal mixed-methods or longitudinal evaluation on the impact of the mitigation strategies on the sustained use of technology due to constraints regarding research resources and the scope of qualitative reflection.

Conclusion

This article contributes to understanding the challenges in conducting technology research in LTCHs and how two research teams overcame those hurdles during and post-COVID. The two distinct pan-Canadian teams reflected and outlined the challenges faced and the mitigation approaches they employed to implement two technology-based interventions (i.e., Telepresence Robots and MouvMat) in LTCHs. The teams proposed actionable items at national, provincial, and local levels to build partnerships and support research environments for research teams, leaders, staff, residents, and family members in LTC settings. Diverse parties can collaborate to maximize the potential of technologies and enhance the care and quality of life of residents in LTCHs. Research teams need to acknowledge and navigate potential biases related to ageism throughout the research process and in LTC environments. Future research can examine the sustained impact of the mitigation strategies and the adaptation of these strategies in LTCHs located in diverse contexts.

Supplemental Material

sj-docx-1-dhj-10.1177_20552076251354904 - Supplemental material for Reflexive case studies on conducting technology implementation research in long-term care homes

Supplemental material, sj-docx-1-dhj-10.1177_20552076251354904 for Reflexive case studies on conducting technology implementation research in long-term care homes by Lillian Hung, Joey Oi Yee Wong, Haniya Bharucha, Lily Haopu Ren and Charlene Chu in DIGITAL HEALTH

Footnotes

Abbreviations

ORCID iDs

Lillian Hung

Joey Oi Yee Wong

Haniya Bharucha

Lily Haopu Ren

Charlene Chu

Ethical considerations

Ethics approval for the Telepresence Robot project was granted from the Research Ethics Board at the University of British Columbia (H21-00844). The MouvMat study received ethical approval from the University of Toronto (#41220). The trial is registered in ClinicalTrials.gov (NCT05130203 on November 23, 2021). Informed consent to participate was obtained from all of the participants in the two studies.

Consent to participate

Written informed consent to participate was obtained from all of the participants in the two studies.

Consent to publication

Written informed consent to publish information was obtained from all study participants.

Author contributions

All team members attended four 1-hour reflection sessions facilitated by CC and LH in person and virtually. LR, HB, and JW analyzed and interpreted the reflection data and generated initial themes. The whole team reviewed and refined the preliminary themes. LR, HB, and JW drafted the manuscript. CC and LH supervised, reviewed, and revised the manuscript. All authors read and approved the final manuscript.

Funding

The work of the Telepresence Robot Study was supported by funding from the Vancouver Foundation Participatory Action Research (PAR) Grant [Grant Number: GR019971], Vancouver General Hospital Foundation, and Richmond Hospital Foundation. The work of the MouvMat Study was funded by CC's grants from the Center of Aging and Brain Health and the New Frontiers Research Fund.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability statement

The datasets used and analyzed during the current study are available from the corresponding author upon reasonable request.

Supplemental material

Supplemental material for this article is available online.

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