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SCOPE: safer care for older persons (in residential) environments—a pilot study to enhance care aide-led quality improvement in nursing homes

A Correction to this article was published on 01 March 2022

This article has been updated



Nursing home residents require daily support. While care aides provide most of this support they are rarely empowered to lead quality improvement (QI) initiatives. Researchers have shown that care aide-led teams can successfully participate in a QI intervention called Safer Care for Older Persons in Residential Care Environments (SCOPE). In preparation for a large-scale study, we conducted a 1-year pilot to evaluate how well coaching strategies helped teams to enact this intervention. Secondarily, we measured if improvements in team cohesion and communication, and resident quality of care, occurred.


This study was conducted using a prospective single-arm study design, on 7 nursing homes in Winnipeg Manitoba belonging to the Translating Research in Elder Care research program. One QI team was selected per site, led by care aides who partnered with other front-line staff. Each team received facilitated coaching to enact SCOPE during three learning sessions, and additional support from quality advisors between these sessions. Researchers developed a rubric to evaluate how well teams enacted their interventions (i.e., created actionable aim statements, implemented interventions using plan-do-study-act cycles, and used measurement to guide decision-making). Team cohesion and communication were measured using surveys, and changes in unit-level quality indicators were measured using Resident Assessment Instrument-Minimum Data Set data.


Most teams successfully enacted their interventions. Five of 7 teams created adequate-to-excellent aim statements. While 6 of 7 teams successfully implemented plan-do-study-act cycles, only 2 reported spreading their change ideas to other residents and staff on their unit. Three of 7 teams explicitly stated how measurement was used to guide intervention decisions. Teams scored high in cohesion and communication at baseline, and hence improved minimally. Indicators of resident quality care improved in 4 nursing home units; teams at 3 of these sites were scored as ‘excellent’ in two or more enactment areas, versus 1 of the 3 remaining teams.


Our coaching strategies helped most care aide-led teams to enact SCOPE. Coaching modifications are needed to help teams more effectively use measurement. Refinements to our evaluation rubric are also recommended.

Peer Review reports

Key messages regarding feasibility

This pilot provides knowledge to guide future care aide-led nursing home quality improvement initiatives, by:

  • Showing that care aides can effectively lead these initiatives (e.g., enact Plan-Do-Study-Act principles that in some instances resulted in improved quality of resident care);

  • Demonstrating that PDSA training to support these initiatives should emphasize the interconnected nature of AIM development, care plan implementation, and measurement;

  • Providing insights into ways in which the SCOPE intervention could be further modified (e.g., by using less didactic teaching, providing teams with practical measurement tools), and;

  • Showing how a (draft) rubric can measure fidelity enactment and suggesting approaches to refine this tool.


Older adults are the fastest growing segment of the worldwide population [1]. As life expectancy increases so does the number of people with dementia and other co-morbid medical conditions [2,3,4,5,6]. Similarly, the care needs of nursing home residents have also increased substantially in recent years [7]. Annually, 1.7 million North Americans reside in nursing homes [8], and at least half of these residents have some form of age-related dementia often combined with additional impairments such as difficulties completing daily tasks, responsive behaviours, and frequent incontinence [9,10,11]. This vulnerable group requires complex health, personal, and social care, provided in ways that has meaning for residents [12] and that emphasize the importance of relational care and quality of life [13]. While media have highlighted the significant challenges with nursing home care during pandemic times [14,15,16], the quality of care provided in this sector has been recognized as suboptimal for decades, and many groups have called to improve nursing home structures and care processes [17,18,19,20,21].

Care aides (unregulated workers, also called personal support workers, orderlies or nursing assistants) provide 80–90% of direct care to nursing home residents in Canada [22]. These staff are best situated to observe, interpret, and respond to residents’ daily needs [23, 24], making them uniquely positioned to meaningfully participate in and, we contend, to lead quality improvement (QI) initiatives. These staff often have little formal vocational training, frequently speak English as a second language, yet conduct a wide range of care activities that are unregulated by any professional organization [25, 26]. Despite their important role, care aides are rarely included in formal care planning processes, making them feel under-valued by other care staff and emphasizing the need to create more constructive collaborative care approaches [27]. Evidence shows that empowering care aides enhances their work performance and quality of work life [28,29,30], and that improving inter-professional collaboration can enhance the quality of nursing home care [31, 32].

Given this knowledge, we previously developed an intervention called Safer Care for Older Persons in Residential Care Environments (SCOPE) [33]. SCOPE is a multi-component intervention designed to empower care aides to lead, with coaching support, QI activities that help them to use best evidence in their practice, and secondarily to improve their quality of work life and engagement. Enhancements in these areas should ultimately lead to improved quality of resident care and their associated health-related outcomes. In a previous publication, researchers have shown that care aides (1) have great interest and are willing to actively participate in SCOPE (e.g., by attending learning sessions and submitting intervention progress reports), and (2) are able to apply SCOPE principles at the resident bedside and hence contribute to quality care improvement [34].

Based on these findings and in preparation for a larger trial, we further developed and operationalized SCOPE facilitated coaching strategies, created a rubric to measure how well teams were able to implement this initiative, and piloted the revised intervention for 1 year. The primary aim of this manuscript is to describe how well our revised coaching strategies helped teams to enact their QI interventions (i.e., to create actionable QI aim statements, implement their QI plans using plan-do-study-act [PDSA] cycles, and use measurement to guide decisions about the need to modify their intervention approaches). As a secondary aim, we also used surveys to measure improvement in team cohesion and communication during SCOPE, and used Resident Assessment Instrument-Minimum Data Set (RAI-MDS 2.0) data to describe changes in select quality indicators at the resident care unit-level.


Study design

This was a single arm prospective pilot study, lasting 1 year from 8 February 2016 to 10 February 2017.


Approval to conduct the research was provided by the University of Manitoba Health Research Ethics Committee (reference number H2015:045). This study was funded by the TREC program (grant number PS 148582). Participating homes received $3000 to offset the costs of participation such as backfilling staff who attended learning sessions.

The translating research in elder care research program

Translating Research in Elder Care (TREC) is a multilevel, longitudinal program of applied health services research designed to improve the quality of care and quality of life for nursing home residents, and also the quality of work life for their care staff [35]. TREC applies these constructs at the clinical microsystem (care units) where quality is created [36, 37]. The overall TREC cohort was created using a random sample across three Canadian provinces (Alberta, Manitoba, British Columbia), stratified by owner-operator type and size [35]. TREC data are provided on about 94 Canadian nursing homes comprised of 334 units; 5500 care aides, nurses, and other care providers; and 31000 RAI-MDS 2.0 assessments completed on 13,800 residents. Nursing homes for this pilot were selected from the Manitoba TREC cohort as described below in the Participants and Study Procedures section.

The SCOPE teaching and coaching strategies

The SCOPE intervention is based on a modified Institute for Healthcare Improvement (IHI) Breakthrough Collaborative Series model [38]. This model uses the Plan-Do-Study-Act (PDSA) approach to improving care that teaches organizations to formally develop AIM statements, to iteratively test change ideas on small groups before more fully implementing them, and to use measurement to evaluate change [38]. SCOPE is also informed by knowledge translation theory, specifically focusing on the important role that facilitation plays in implementation projects [39, 40]. Each component of the SCOPE coaching strategy is shown in Fig. 1, with further details provided elsewhere [33, 41]. These include the following:

  • ‘Getting Started’ evidence kits that provide (topic-specific) background clinical information and evidence-informed ideas for improving care;

  • Three 2-day learning sessions (i.e., workshops attended by all teams) designed to train teams about PDSA quality improvement approaches, and to provide them with peer networking and learning opportunities;

  • A quality advisor who helped to design and implement the learning session, and who supported teams using in-person visits and telephone calls regularly between learning sessions;

  • A quality coordinator who led virtual and in-person discussions to help unit and facility managers support front-line QI teams, and supported the quality advisor when needed, and;

  • A celebratory conference held at the end of the pilot.

Fig. 1
figure 1

Safer Care for Older Persons in Residential Care Environments (SCOPE) pilot study coaching strategies (February, 2016–February, 2017)

The quality advisor was the main liaison with each team. Duties included the following:

  • Meeting with each team at the beginning of SCOPE to review the ‘Getting Started’ information kit;

  • Working with the quality coordinator and research team to prepare and facilitate learning sessions;

  • Conducting face-to-face meetings with each team at least monthly, to help them enact their PDSA plans and brainstorm solutions to challenges encountered;

  • Being available for additional team consultation as needed; and,

  • Keeping a diary of team interactions and progress.

Learning sessions occurred 3 months apart (Fig. 1); the agenda for each session is provided in Appendix 1. In learning session 1, teams were coached to develop effective QI aim statements, while learning sessions 2 and 3 focused on measurement and strategies to spread effective QI strategies within each team’s unit, respectively. Coaching strategies used in the learning sessions included improv and simulation techniques, and interactive “games” designed to promote PDSA training. Time was also dedicated to help teams problem solve and share solutions to challenges that they encountered (e.g., getting buy-in from peers), to provide teams with knowledge sharing and socialization opportunities (e.g., networking sessions and team presentations sharing their PDSA experiences), and to discuss how lessons learned could be integrated into daily care routines. During the final celebratory conference, teams celebrated their achievements, discussed lessons learned, and considered next steps.

SCOPE pilot nursing homes focused their change ideas on one of three clinical areas (reducing pain, improving mobility, and reducing dementia-related responsive behaviours). As explained by Cranley et al. (2011), these areas were selected using a Delphi method applied to gerontology experts; senior decision-makers; and nursing home care aides, registered nurses, and care managers/educators [33]. At the onset of SCOPE, TREC senior decision-making partners requested that we replace one of the original priority areas (prevention and management of pressure ulcers) with responsive behaviors, to reflect clinical areas that needed improvement and where change strategies could feasibly be identified and implemented by care aides. We limited the number of clinical options offered in the pilot, to help optimize sharing and learning among teams working on the same target areas.

Participants and study procedures

Nursing homes were randomly selected from within the Manitoba TREC cohort by one of the co-authors (PN) using a random number table without replacement. This process was stratified by owner-operator type (voluntary not for profit, public not for profit, private for profit) and facility size (small, medium, and large), ensuring that the number of sites selected in each stratum were proportional to the overall TREC cohort. While we had originally planned to recruit 8 sites, one site declined to participate stating insufficient staff levels to engage in research. No sites were lost to follow-up during this pilot.

Executive Directors from each facility received a written invitation to participate in the pilot followed by an in-person meeting to answer questions, to explain nursing home responsibilities, and to discuss available support. Following written consent to participate in the pilot, the Executive Director identified a senior sponsor (usually the Director of Care) to help promote SCOPE to other management staff, and to remove implementation barriers throughout the pilot as needed. This latter individual identified, at their discretion, one unit from their facility to participate in the pilot, and selected a unit-level team sponsor (usually a unit-level clinical nurse manager) who was responsible for supporting day-to-day project activities. Senior and Team Sponsors collaborated to select a front-line team consisting of 5–7 members. At least 2 team members were care aides with one as team lead; other care staff (e.g., social workers) were selected as needed. Sites used various strategies (decided by sponsors, team consensus based on resident need) to select one of the three clinical areas to work on.

Measures and data analysis

Treatment enactment

Enactment is an element of treatment fidelity that measures the extent to which people actually implement an intervention and differs from what is taught (treatment delivery), what is learned (treatment receipt), and the extent of its effect (treatment efficacy) [42]. Enactment is one of the most challenging aspects of treatment fidelity to measure [42, 43]. Traditional approaches to measuring it include the use of questionnaires and self-reports, structured interviews, observation, and activity logs [42].

Each team was asked to self-report their implementation progress every 2 months during the pilot, using a PDSA progress worksheet (Appendix 2). Teams used this worksheet to document (1) refinements made to their QI aim statement; (2) how well they were able to implement QI interventions using PDSA methods (e.g., starting with one or two residents, and involving other residents and/or staff depending on their success); and (3) the extent to which they used data and measurement strategies to guide team decision-making.

Researchers developed a rubric to measure “enactment” in each of these areas, based on the information that teams provided, and using a 5-point scale ranging from poor (1) to excellent (5). As one example, aim statements were scored by the extent that teams met the SMART criteria of being Specific, Measurable, Achievable, Relevant, and Timely [44]. Detailed criteria and scoring definitions for each area of enactment are provided in Table 1. Two authors (MD, LG) independently reviewed each team’s self-reported responses as documented using the PDSA progress worksheets, and provided a team score for each enactment area. Scoring discrepancies were resolved through iterative discussions.

Table 1 Scoring system used to rate team’s level of treatment enactment during SCOPE

Workgroup cohesion and communication

Each team completed these scales every 2 months as part of their self-assessment package (Appendix 2). Data are reported descriptively for months 1, 7, and 12 of the pilot.

Workgroup cohesion is the “degree to which an individual believes that the members of his or her work group are attracted to each other, are willing to work together, and are committed to completing the tasks and goals of the work group” [45]. We measured work cohesion using 8 items proposed by Riordan and Weatherly (1999). Based on the results of a cognitive debriefing exercise conducted with TREC care aides, the wording of each item was modified slightly to meet the project context, using appropriate language without losing meaning (e.g., revising the original statement ‘In my work group, there is a lot of team spirit among members’, to ‘we have a lot of team spirit among members’). Each scale item was scored on a seven-point Likert scale ranging from ‘strongly disagree’ to ‘strongly agree’. Item responses were averaged to provide an overall score ranging from 1 to 7; the latter score represents strong agreement about team cohesion, while a score of ‘4’ equals a ‘neutral’ response.

Workgroup communication is the “degree to which information is transmitted among the members of the work group” [45]. This construct was measured using 4 items, also adapted to align with the pilot (e.g., changing the original statement ‘In my work group, individuals frequently discuss work assignments with each other’ to ‘We frequently discuss resident care assignments with each other’). Scoring occurred as per workgroup cohesion. Cronbach’s alpha was high for the original versions of the workgroup cohesion ( = .92) and workgroup communication ( = .79) scales [45].

Resident quality indicators

Quality indicators were assessed using RAI-MDS 2.0 data [46]. The standard for reporting these data in Canada is set by the Canadian Institute of Health Information ( Throughout most of Canada, all nursing home residents are required to have a full-length assessment completed close to their time of admission and annually thereafter, interspersed by abbreviated quarterly assessments. Full-length assessments contain about 400 standardized items that are completed by a trained assessor (usually a nurse) using data from clinical charts and direct observations. These data are used to profile nursing home residents (e.g., by their cognitive and functional performance) and to provide indicators of quality care (e.g., the percent of residents with improved mobility or worsening pain).

We obtained assessment-level RAI-MDS 2.0 data for each of the SCOPE units. Data were obtained for a 3-year period, starting 2 years before SCOPE and ending at the completion of the pilot (i.e., January 2014 to March 2017). Specific to the clinical area chosen by teams, we assessed unit-level changes in the percentage of residents who showed improvements in mobility, whose responsive behavioural symptoms improved, or with pain. Resident mobility was assessed using the third generation [47] RAI-MDS 2.0 quality indicator “MOB1a” (the percentage of residents whose ability to locomote on the unit improved). This indicator excludes residents who are comatose, have six or fewer months to live, and/or who were independently mobile during their previous RAI-MDS 2.0 assessment [46]. The quality indicator entitled “BEHI4” was used to identify the percentage of residents on each unit whose behavioral symptoms (i.e., wandering, verbally abusive, physically abusive, socially inappropriate or disruptive behavior) improved from the previous RAI-MDS 2.0 assessment [46]. This indicator excludes residents who are comatose or who had missing behavioral scores in their previous assessment. Resident pain was measured using the RAI-MDS 2.0 pain scale [46]. This quality indicator assesses the percentage of residents with any amount of pain in the last seven days, excluding those with missing or conflicting (no pain frequency but with some degree of intensity) item responses.

Unit-level changes in RAI-MDS 2.0 quality indicators are presented using statistical process control (SPC) charts [48]. Data were not normally distributed and thus the following SPC zones were created using pre-SCOPE (January, 2013 to December 2016) data: (a) zone 3 = 1st–5th percentile; (b) zone 2 = 5th–34th percentile; (c) zone 1 = 34th-50th percentile; (d) zone +1 = 50th–66th percentile; (e) zone +2 = 66th–95th percentile; (f) zone +3 = 95th–99th percentile. SPC charts allow us to assess changes in processes or outcomes with time, and assume that in ‘null effect’ scenarios, data will be randomly distributed around a measure of central tendency [48]. Following the SPC Western Electric rules [49], non-random variation was detected if (a) one or more data points during the SCOPE pilot were beyond zone 3 of pre-SCOPE results, (b) two of three successive data points were beyond zone 2, or (c) four of five successive data points were beyond zone 1.


Nursing home characteristics, team composition, and QI focus

The characteristics of SCOPE nursing homes, units and team composition are found in Table 2. Five of the 7 nursing homes in the pilot were (public or voluntary) non-profit, while 2 and 4 homes were medium (80–120 beds) and large (> 120 beds), respectively. Homes had between 1 and 6 units that ranged in size from 27 to 100 beds.

Table 2 SCOPE nursing home and unit characteristics

Five of the seven SCOPE teams focused on reducing dementia-related responsive behaviors, 1 team focused on reducing pain, and 1 focused on improving resident mobility (Table 3). Team and senior sponsors were most often clinical nurse managers and Directors of Care, respectively. Team size, including the team and senior sponsor, ranged from 5 (n = 4 SCOPE sites) to 7 (n = 1 SCOPE site) individuals. With two exceptions (sites C and F), front-line SCOPE teams were comprised entirely of care aides.

Table 3 Team composition and quality improvement topic

Treatment enactment

We rated 3 of the 7 teams as creating excellent aim statements (rating of 5/5) during the pilot (Table 4), 2 teams as creating adequate aim statements (rating = 3/5), and 2 teams as creating ‘poor’ (rating = 1/5), or ‘poor-to adequate’ (rating = 2/5) aim statements. To illustrate, team D was rated as having an excellent AIM statement. This team defined responsive behavior in their aim statement (‘hitting, screaming, arguing’; specific), quantified their goals (reducing events by 60%; measurable), showed progression throughout the pilot (reducing events by 60% at month 7, and 90% by month 12; achievable and timely), and defined when the intervention would occur (during activities of daily living; relevant) (data not shown). While Team B (rated as adequate) satisfied the ‘specific’ (defined responsive behavior), ‘measurable’ (included a target goal) and ‘relevant’ (reported when the intervention would occur) SMART criteria, this team did not show progression in its aim statement, and nor did it identify a timeline for achieving intervention success. We rated team E as having a poor aim statement, as it met the ‘relevant’ SMART criteria only (defined when the intervention would occur).

Table 4 Ratings of treatment enactment during the SCOPE pilot

Each team was also rated on their intervention progress. We rated 5 teams as achieving adequate to excellent intervention progression (Table 4); however, only Teams F and G reported scaling their intervention to involve other residents and/or staff on their unit (these teams received a rating of ‘excellent’). Team F reported using ‘pain pocket card survival kits’ to remind and help unit staff to implement the intervention, and reflected on how they engaged with non-SCOPE providers on their unit to enhance their care processes. We rated teams B and E as achieving poor intervention progression; both teams reported a ‘success story’ for only one resident at the end of the pilot (data not shown).

Teams D, F, and G specifically reported how they used measurement tools (e.g., mobility tracking tools, use of RAI-MDS 2.0 data) to help make decisions throughout the pilot, and hence we rated these teams as ‘excellent’ in this category (Table 4). Teams A, B, and E vaguely referred to measurement (e.g., conducting baseline assessments) without providing details, and were rated as ‘adequate’. Team C did not make any reference to using measurement to guide decisions.

Workgroup cohesion and communication

Team cohesion and communication results are shown in Table 5. Most teams moderately (an average score of ‘6’ across all scale questions) or strongly (an average score of ‘7’ across all questions) agreed with statements about their cohesion and communication throughout the pilot. As the only exception, team C provided a score of 3.8 (a neutral opinion) for team cohesion at month 12 of the pilot.

Table 5 Self-reported measures of workgroup cohesion and communication during the pilot

Resident quality indicators

SPC charts for quality indicators are shown in Fig. 2. Patterns of quality care indicator data were non-random for sites D and E (responsive behaviors; one data point beyond zone +3), showing improvements in responsive behaviours for two of the five sites that worked on this clinical area during the SCOPE pilot. SPC results also show improvements for Site G that worked on improving mobility (this site had one data point beyond zone +3 towards the end of the SCOPE pilot), and site F that worked on improving pain (this site had 4 consecutive data points beyond zone 1 during the SCOPE pilot). We noted that the improvement pattern for site F commenced pre-SCOPE. During follow-up discussions, site F leaders disclosed that this was at least partly due to changes in their pain assessment approach (i.e., all residents receiving an analgesic were originally deemed as having pain). Three of the 4 teams (sites D, F, G) who showed improved quality care also received a score of ‘excellent’ in at least 2 of the treatment enactment areas reported in Table 4, versus only 1 of 3 teams with random changes in quality care (while Site A was rated as creating an excellent aim statement, changes in responsive behavior for this unit were coded as random).

Fig. 2
figure 2

Unit-level clinical outcomes prior to and during the SCOPE pilot


This pilot demonstrated that the bundle of SCOPE teaching and coaching strategies—a “getting started” information kit, structured learning sessions, quality advisor guidance, and discussions to help senior and team sponsors support front-line teams—effectively supported most care aide-led teams’ to enact their QI strategies. Five of the seven teams provided adequate or excellent aim statements during the pilot, five teams reported achieving at least adequate intervention progress (i.e., showed learning and refinement through PDSA cycles), and three teams specifically discussed how they used measurement to guide intervention decision making processes during the pilot. Teams that scored high in one enactment area tended to do so in others (e.g., site G received a score of ‘excellent’ in each of the enactment areas, sites D and F received this score in two of three areas), while conversely, teams that scored poorly in one enactment area tended to consistently do so (see site E in Table 4). As discussed by Kilo (1998), this pattern of results emphasizes the need for PDSA training to reflect the interconnected nature of AIM development, care plan implementation, and measurement [38].

Additionally, while this pilot was not powered to detect statistically significant differences in measures of treatment efficacy, it is important to note that (1) some trends for improvement in quality indicators were noted at the resident care-unit level, and (2) these trends occurred more often amongst teams who successfully enacted SCOPE. These results help demonstrate that successfully facilitated coaching strategies have the potential to impact resident care, which hence provides support to further adapt and refine the SCOPE intervention in future studies.

Our pilot study contributes to existing nursing home quality improvement and implementation research [50, 51] in three ways. First, our results contribute to the growing body of literature showing that care aides can successfully lead QI initiatives, with the proper support. This is important, given care aides’ essential role in providing day-to-day nursing home support coupled with their high degree of knowledge about the wants and needs of residents [22,23,24]. Actively engaging with care aides is important to enhance nursing home quality of care, particularly given the need to balance effective medical care with relational and social approaches [12, 13]. Several researchers have demonstrated the benefits of meaningfully engaging both care staff [28,29,30] and residents [52, 53] during care processes.

Second, these findings contribute to our understanding of how facilitated coaching can help to support quality improvement interventions. As proposed by Rycroft-Malone and colleagues [40, 54], our pilot results suggest that a combination of technical (e.g., Getting Started kits that provide teams with important background clinical information and examples of evidence-informed interventions), educational (e.g., structured learning sessions that show teams how to apply PDSA models ), and ongoing facilitated coaching strategies (e.g., quality advisors that help teams to integrate their care plans into daily care activities and to overcome barriers as they arise) are all required to support complex QI interventions. These findings are complemented by an earlier qualitative study conducted by Ginsburg et al. (2018) who analyzed data from 6 focus groups conducted during our final SCOPE celebratory conference [41]. While care aides in this study felt that all components of SCOPE were important, they also reported considerable challenges with measurement, recommended less didactic teaching, and asked us to include more pragmatic examples of measurement tools in the Getting Started kits.

Third, these study findings highlight the need to develop more detailed process evaluation techniques that allows us to better understand both how and why interventions succeed or fail [55]. While intervention fidelity is traditionally measured using self-report strategies [42], these data are prone to information bias [56], and techniques are required to differentiate between what an intervention has taught (fidelity delivery), what is learned (fidelity receipt), and what is implemented by teams (fidelity enactment). Enactment was measured from one data source in the present study (researcher coding of care aide self-reports). Future studies would benefit from using a range of data sources and methods, including care aide and sponsor self-reports and external assessments (e.g., quality advisor diaries and/or researcher observations). Our research team continues to refine the enactment rubric used in this pilot, both to expand the tool measurement domains (e.g., differentiating between treatment receipt and enactment) and to create more refined scoring criteria, for use in future endeavours.


SCOPE teams were recruited from a single Canadian health region, and hence lessons learned should be applied cautiously to other jurisdictions and countries. We also did not investigate how site leaders selected SCOPE team members and their intervention foci, which may have influenced study outcomes. Teams provided self-reported scores of treatment enactment without explaining how these assessments were decided (e.g., by team consensus, by one person on behalf of the team). More detailed and objective approaches to assessing fidelity enactment will help to provide more robust data on this important construct. Similarly, data on team cohesion and communication showed potential ceiling effects; these data were self-reported at the team level and social desirability or selection bias may explain the high scores on these measures. In future research, individual team-member responses may provide more accurate data. Alternative measures of team dynamics should also be explored and considered for use, and/or qualitative methods of inquiry could be used, to more richly assess that ways in which team dynamics influences intervention enactment.


This pilot provides knowledge to guide future care aide-led nursing home quality improvement initiatives by (1) showing that care aides can effectively lead QI initiatives; (2) illustrating that PDSA training to support these initiatives should emphasize the interconnected nature of AIM development, care plan implementation, and measurement; (3) providing insights into the ways in which SCOPE could be modified in future research, and; 4) developing and implementing a rubric to assess fidelity enactment. Modifications to this tool are required to measure additional enactment domains (fidelity receipt) while incorporating different sources of data.

Availability of data and materials

The data that support the findings of this study are available from Translating Research in Elder Care, c/o Dr. Carole Estabrooks, but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of Dr. Carole Estabrooks.

Change history



Quality improvement


Safer Care for Older Persons in Residential Care Environments


Translating Research in Elder Care




Institute for Healthcare Improvement


Statistical process control


  1. United Nations. 2019 Revision of world population prospects 2019 [Available from:

  2. Stephan BCM, Birdi R, Tang EYH, et al. Secular trends in dementia prevalence and incidence worldwide: a systematic review. J Alzheimers Dis. 2018;66(2):653–80.

    Article  PubMed  Google Scholar 

  3. World Health Organization. Dementia: fact sheet 2017 [Available from:].

  4. 2020 Alzheimer’s disease facts and figures. Alzheimers Dement 2020.

  5. Chatterji S, Byles J, Cutler D, Seeman T, Verdes E. Health, functioning, and disability in older adults-present status and future implications. Lancet. 2015;385(9967):563–75.

    Article  PubMed  Google Scholar 

  6. Prince MJ, Wu F, Guo Y, et al. The burden of disease in older people and implications for health policy and practice. Lancet. 2015;385(9967):549–62.

    Article  PubMed  Google Scholar 

  7. Fashaw SA, Thomas KS, McCreedy E, Mor V. Thirty-year trends in nursing home composition and quality since the passage of the Omnibus Reconciliation Act. J Am Med Dir Assoc. 2020;21(2):233–9.

    Article  PubMed  Google Scholar 

  8. Organisation for Economic Co-operation and Development. Long-term care resources and utilisation: long-term care recipients 2020 [Available from:].

    Google Scholar 

  9. Slaughter SE, Jones CA, Eliasziw M, et al. The changing landscape of continuing care in Alberta: staff and resident characteristics in supportive living and long-term care. Healthc Policy. 2018;14(1):44–56.

    PubMed  PubMed Central  Google Scholar 

  10. Doupe M, St. John P, Chateau D, et al. Profiling the multidimensional needs of new nursing home residents: evidence to support planning. J Am Med Dir Assoc. 2012;13(5):487–17.

    Article  PubMed  Google Scholar 

  11. Canadian Institute for Health Information. Dementia in Canada Ottawa, Ontario 2018 [Available from:].

    Google Scholar 

  12. White DL, Tunalilar O, Hasworth S, Winfree J. The resident view in nursing homes. Gerontol Geriatr Med. 2019;5:2333721419877975.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Armstrong P, Armstrong H, Banerjee A, et al. Negotiating tensions in long-term residential care: ideas worth sharing. 1500 Saint-Patrick, Montréal QC H3K 0A3: RR Donnelley; 2018.

  14. Canada’s National Observer. Long-term care homes were in crisis well before politicians woke up to the problem 2020 [Available from:].

    Google Scholar 

  15. The New York Times. How to improve and protect nursing homes from outbreaks 2020 [Available from:].

    Google Scholar 

  16. The Washington Post. Canada’s nursing home crisis: 81 percent of coronavirus deaths are in long-term care facilities 2020 [Available from:].

    Google Scholar 

  17. Mechanic D. Challenges in long-term care policy. Health Aff (Millwood). 1987;6(2):22–34.

    Article  CAS  Google Scholar 

  18. Armstrong P. Long-term care problems: both residents and care providers denied fair treatment more, better-paid staff key to improved long-term care. Ottawa: Canadian Centre for Policy Alternatives; 2009. [Available from:]

    Google Scholar 

  19. Tolson D, Rolland Y, Andrieu S, et al. International Association of Gerontology and Geriatrics: a global agenda for clinical research and quality of care in nursing homes. J Am Med Dir Assoc. 2011;12(3):184–9.

    Article  PubMed  Google Scholar 

  20. McGilton KS, Bowers BJ, Heath H, et al. Recommendations from the International Consortium on Professional Nursing Practice in Long-Term Care Homes. J Am Med Dir Assoc. 2016;17(2):99–103.

    Article  PubMed  Google Scholar 

  21. Estabrooks CA, Straus S, Flood C, et al. Restoring Trust: COVID-19 and the future of long-term care: Royal Society of Canada; 2020.

    Google Scholar 

  22. Price Waterhouse Coopers. Report on a study to review the levels of service and responses to need in a sample of Ontario long-term care facilities and selected comparators. 2001 [Available from:].

  23. Boockvar K, Brodie HD, Lachs M. Nursing assistants detect behavior changes in nursing home residents that precede acute illness: development and validation of an illness warning instrument. J Am Geriatr Soc. 2000;48(9):1086–91.

    Article  CAS  PubMed  Google Scholar 

  24. Kontos PC, Miller KL, Mitchell GJ, Cott CA. Dementia care at the intersection of regulation and reflexivity: a critical realist perspective. J Gerontol B Psychol Sci Soc Sci. 2011;66(1):119–28.

    Article  PubMed  Google Scholar 

  25. Hewko SJ, Cooper SL, Huynh H, et al. Invisible no more: a scoping review of the health care aide workforce literature. BMC Nurs. 2015;14:38.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Caspar S, Ratner PA, Phinney A, MacKinnon K. The influence of organizational systems on information exchange in long-term care facilities: an institutional ethnography. Qual Health Res. 2016;26(7):951–65.

    Article  PubMed  Google Scholar 

  27. Janes N, Sidani S, Cott C, Rappolt S. Figuring it out in the moment: a theory of unregulated care providers’ knowledge utilization in dementia care settings. Worldviews Evid-Based Nurs. 2008;5(1):13–24.

    Article  PubMed  Google Scholar 

  28. Barry TT, Brannon D, Mor V. Nurse aide empowerment strategies and staff stability: effects on nursing home resident outcomes. Gerontologist. 2005;45(3):309–17.

    Article  PubMed  Google Scholar 

  29. Hamann DJ. Does empowering resident families or nursing home employees in decision making improve service quality? J Appl Gerontol. 2014;33(5):603–23.

    Article  PubMed  Google Scholar 

  30. Yeatts DE, Cready CM. Consequences of empowered CNA teams in nursing home settings: a longitudinal assessment. Gerontologist. 2007;47(3):323–39.

    Article  PubMed  Google Scholar 

  31. Hamelin Brabant L, Lavoie-Tremblay M, Viens C, Lefrançois L. Engaging health care workers in improving their work environment. J Nurs Manag. 2007;15(3):313–20.

    Article  PubMed  Google Scholar 

  32. Caspar S, Cooke HA, O'Rourke N, MacDonald SW. Influence of individual and contextual characteristics on the provision of individualized care in long-term care facilities. Gerontologist. 2013;53(5):790–800.

    Article  PubMed  Google Scholar 

  33. Cranley LA, Norton PG, Cummings GG, Barnard D, Estabrooks CA. SCOPE: Safer care for older persons (in residential) environments: a study protocol. Implement Sci. 2011;6:71.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Norton P, Cranley L, Cummings G, Estabrooks C. Report of a pilot study of quality improvement in nursing homes led by healthcare aides. European Journal for Person Centered Healthcare. 2012;1(1):255–64.

    Article  Google Scholar 

  35. Estabrooks CA, Squires JE, Cummings GG, Teare GF, Norton PG. Study protocol for the translating research in elder care (TREC): building context - an organizational monitoring program in long-term care project (project one). Implement Sci. 2009;4:52.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Estabrooks CA, Morgan DG, Squires JE, et al. The care unit in nursing home research: evidence in support of a definition. BMC Med Res Methodol. 2011;11:46.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Norton PG, Murray M, Doupe MB, et al. Facility versus unit level reporting of quality indicators in nursing homes when performance monitoring is the goal. BMJ Open. 2014;4(2):e004488.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Kilo CM. A framework for collaborative improvement: lessons from the Institute for Healthcare Improvement's Breakthrough Series. Qual Manage Health Care. 1998;6(4):1–13.

    Article  CAS  Google Scholar 

  39. Berta W, Cranley L, Dearing JW, et al. Why (we think) facilitation works: insights from organizational learning theory. Implement Sci. 2015;10:141.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Harvey G, Kitson A. PARIHS revisited: from heuristic to integrated framework for the successful implementation of knowledge into practice. Implement Sci. 2016;11:33.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Ginsburg L, Easterbrook A, Berta W, et al. Implementing frontline worker-led quality improvement in nursing homes: getting to “how”. Jt Comm J Qual Patient Saf. 2018;44(9):526–35.

    PubMed  Google Scholar 

  42. Bellg AJ, Borrelli B, Resnick B, et al. Enhancing treatment fidelity in health behavior change studies: best practices and recommendations from the NIH Behavior Change Consortium. Health Psychol. 2004;23(5):443–51.

    Article  PubMed  Google Scholar 

  43. Ginsburg LR, Hoben M, Easterbrook A, et al. Fidelity is not easy! Challenges and guidelines for assessing fidelity in complex interventions. Trials. 2021;22(1):372.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Bjerke MB, Renger R. Being smart about writing SMART objectives. Eval Program Plann. 2017;61:125–7.

    Article  PubMed  Google Scholar 

  45. Riordan CM, Weatherly EW. Defining and measuring employees’ identification with their work groups. Educ Psychol Meas. 1999;59(2):310–24.

    Article  Google Scholar 

  46. Canadian Institute for Health Information. Continuing Care Reporting System RAI-MDS 2.0 Output Specifications, 2016-2017. Ottawa, Ontario; 2017.

  47. Jones RN, Hirdes JP, Poss JW, et al. Adjustment of nursing home quality indicators. BMC Health Serv Res. 2010;10:96.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Anhøj J, Wentzel-Larsen T. Sense and sensibility: on the diagnostic value of control chart rules for detection of shifts in time series data. BMC Med Res Methodol. 2018;18(1):100.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Western Electric Company. Statistical quality control handbook 1958 [Available from:].

    Google Scholar 

  50. van der Zijpp TJ, Niessen T, Eldh AC, et al. A bridge over turbulent waters: illustrating the interaction between managerial leaders and facilitators when implementing research evidence. Worldviews Evid-Based Nurs. 2016;13(1):25–31.

    Article  PubMed  Google Scholar 

  51. Abrahamson K, DeCrane S, Mueller C, Davila HW, Arling G. Implementation of a nursing home quality improvement project to reduce resident pain: a qualitative case study. J Nurs Care Qual. 2015;30(3):261–8.

    Article  PubMed  Google Scholar 

  52. Schoberer D, Leino-Kilpi H, Breimaier HE, Halfens RJ, Lohrmann C. Educational interventions to empower nursing home residents: a systematic literature review. Clin Interv Aging. 2016;11:1351–63.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Wang J, Wang J, Cao Y, Jia S, Wu B. Perceived empowerment, social support, and quality of life among chinese older residents in long-term care facilities. J Aging Health. 2018;30(10):1595–619.

    Article  PubMed  Google Scholar 

  54. Rycroft-Malone J, Seers K, Chandler J, et al. The role of evidence, context, and facilitation in an implementation trial: implications for the development of the PARIHS framework. Implement Sci. 2013;8:28.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Ginsburg LR, Hoben M, Easterbrook A, et al. Examining fidelity in the INFORM trial: a complex team-based behavioral intervention. Implement Sci. 2020;15(1):78.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Althubaiti A. Information bias in health research: definition, pitfalls, and adjustment methods. J Multidiscip Healthc. 2016;9:211–7.

    Article  PubMed  PubMed Central  Google Scholar 

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The authors acknowledge the Translating Research in Elder Care (TREC) 2.0 team for its contributions to this study. Independent research funding was provided by partners in the Ministries of Health in Manitoba, Alberta, and British Columbia, as well as, regional health authorities in these participating regions.


This study was funded by the TREC program (grant number PS 148582).

Author information

Authors and Affiliations



AW, CE, PN, JK-S, LG, WB and MD conceived the study, implemented the pilot, and/or collected study data. MD, TB and CE led in preparing the manuscript, and all authors contributed to interpreting results and preparing the manuscript. All authors have read and approved the final manuscript.

Corresponding author

Correspondence to Malcolm Doupe.

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Ethics approval and consent to participate

This study was approved by the University of Manitoba Health Research Ethics Committee (reference number H2015:045).

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Not applicable.

Competing interests

The authors declare that they have no competing interests.

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The original online version of this article was revised: the authors reported an error in Fig. 2.

Supplementary Information

Additional file 1: Appendix 1.

This file provides the daily agendas for each SCOPE Learning Session.

Additional file 2: Appendix 2.

This file shows the SCOPE Quality Improvement Team Assessment Form, completed bi-monthly during pilot. Responses to this form were used to score team enactment.

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Doupe, M., Brunkert, T., Wagg, A. et al. SCOPE: safer care for older persons (in residential) environments—a pilot study to enhance care aide-led quality improvement in nursing homes. Pilot Feasibility Stud 8, 26 (2022).

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  • Nursing homes
  • Quality improvement
  • Pilot study
  • Care aide-led intervention
  • Facilitated coaching
  • Enactment