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/lp/ou_press/impact-of-intervention-to-improve-nursing-home-resident-staff-RWAjPYeMlk
- Publisher
- Oxford University Press
- Copyright
- Copyright © 2022 The Gerontological Society of America
- ISSN
- 0016-9013
- eISSN
- 1758-5341
- DOI
- 10.1093/geront/gny039
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- See Article on Publisher Site
Abstract
Background and Objectives: For nursing home residents, positive interactions with staff and engagement in daily life contribute meaningfully to quality of life. We sought to improve these aspects of person-centered care in an opportunistic snowball sample of six Veterans Health Administration nursing homes (e.g., Community Living Centers—CLCs) using an intervention that targeted staff behavior change, focusing on improving interactions between residents and staff and thereby ultimately aiming to improve resident engagement. Research Design and Methods: We grounded this mixed-methods study in the Capability, Opportunity, Motivation, Behavior (COM-B) model of behavior change. We implemented the intervention by (a) using a set of evidence-based prac- tices for implementing quality improvement and (b) combining primarily CLC-based staff facilitation with some researcher- led facilitation. Validated resident and staff surveys and structured observations collected pre and post intervention, as well as semi-structured staff interviews conducted post intervention, helped assess intervention success. Results: Sixty-two CLC residents and 308 staff members responded to the surveys. Researchers conducted 1,490 discrete observations. Intervention implementation was associated with increased staff communication with residents during the provision of direct care and decreased negative staff interactions with residents. In the 66 interviews, staff consistently cred- ited the intervention with helping them (a) develop awareness of the importance of identifying opportunities for engage- ment and (b) act to improve the quality of interactions between residents and staff. Discussion and Implications: The intervention proved feasible and influenced staff to make simple enhancements to their behaviors that improved resident-staff interactions and staff-assessed resident engagement. Keywords: Quality of care, Implementation science, Mixed-methods Published by Oxford University Press on behalf of The Gerontological Society of America 2018. e291 This work is written by (a) US Government employee(s) and is in the public domain in the US. Downloaded from https://academic.oup.com/gerontologist/article/58/4/e291/4990494 by DeepDyve user on 18 July 2022 e292 The Gerontologist, 2018, Vol. 58, No. 4 sustainability (Alexander & Hearld, 2011). In our previous Background and Objectives work, we examined the QI, behavior change, and imple- Nursing home residents are at great risk of not being mentation science literatures to develop a theory-driven, engaged in positive, individualized, stimulating activities user-friendly, integrated QI bundle for nursing home staff (Harper Ice, 2002; Wood, Harris, Snider, & Patchel, 2005). to improve resident-staff interactions to engage residents Yet engagement in active, expressive, social activities is (Mills et al., 2017). We identified four critical practices to associated with higher quality of life (Beerens et al., 2016). successful QI efforts: strengths-based learning, observation, Engagement of residents through positive interactions with relationship-based teams, and efficiency. We operational- staff and through behavioral interventions is, for example, ized these for use in nursing homes, creating a bundle of specifically related to positive well-being, improved affect, four practices known by their acronym, LOCK: (a) Look and extended survival (Haugan, 2014; Meeks, Shah, & for the bright spots, (b) Observe, (c) Collaborate in huddles, Ramsey, 2009; Schreiner, Yamamoto, & Shiotani, 2005). and (d) Keep it bite-sized (Mills et al., 2017)—see Figure 1. Improving resident involvement through individualized In this paper, we describe the outcomes of a LOCK-based activities has numerous positive benefits, including reduced intervention that targeted staff behavior change, focusing agitation and depression and improved mood, pleasure, on improving staff interactions with residents and thereby and interest (Beerens et al., 2018; Travers et al., 2016). ultimately aiming to improve resident engagement. Ideally, staff facilitate resident engagement in meaningful activity by interacting with residents during work activities Conceptual Model and socially, creating opportunities for residents to be occu- pied in ways and with the timing they like (Smit, de Lange, The Capability, Opportunity, Motivation, Behavior (COM- Willemse, Twisk, & Pot, 2016). While some staff may feel, B) model of behavior change (Michie, Atkins, & West, for example, that juggling multiple responsibilities within 2014; Michie, van Stralen, & West, 2011) guided imple- a short time frame impedes their ability to interact with mentation and evaluation of the LOCK model interven- and engage residents, research shows staff are capable of tion. The COM-B model describes an ongoing cycle in improving their interactions (Carpiac-Claver & Levy- which behaviors are generated by and also affect three Storms, 2007; Smith, Mathews, & Gresham, 2010; Wilson components—capability, opportunity, and motivation. & Davies, 2009). Specifically, capability is the psychological or physical abil- Quality improvement (QI) may offer feasible and sus- ity to enact a behavior, opportunity is the physical and tainable opportunities for nursing home staff to work social environment that enables a behavior, and motiva- together to improve resident engagement by piloting, tion is the automatic and reflective mechanisms that trig- observing, and refining interventions. But to effect lasting ger or inhibit behavior. COM-B has been widely used to and meaningful improvement, QI efforts must be grounded guide implementation work, including in long-term care in a framework that fosters systemic change and long-term (Fleming, Bradley, Cullinan, & Byrne, 2014; Peiris et al., LOCK Tenet Explanation Fictional Example Data collection shows aneighborhood has an average of 35% active resident engagement over the course of a When searching for solutions to an issue, week. Staff break the data down by time of day, Look for the look for positive outliers (e.g., “positive pinpointing areas of highest engagement and bright spots deviants”) to identify instances of success investigating what contributesto those bright spots. from which to learn. This enables them to identify practices and conditions to pilot during times of less engagement. Have staff briefly step back from their Each staff member in a neighborhood is instructed to regular routines and conduct specific conduct a five minute observationof resident Observations by observations to collect data, using engagement during a meal, using a structured everyone structured tools or not.*These observations observation form. Staff cover for each other to enable provide the fodder for huddle dialogues. these short observations to take place. The charge nurse for a neighborhood uses 5-10 minutes at the start of a shift-change huddle to huddle with Conduct brief, collaborative, strengths- frontline staff and get their input on risk factors for based frontline staff huddles to discuss Collaborate in (a) risk factors for an issue, (b) what can residents not being engaged and discuss bright spots huddles of resident engagement identified through observation. be learned from bright spots, (c) results of Based on lessons learned from the bright spots, staff observations, and (d) changes to pilot. identify small action items to try over the next few days. Keep all LOCK components to 5-15 Existing meetings are shortened by 5-10 minutes to Keep it bite sized minutes. Incremental changes, rather than make room for stand-up huddles. Pilot changes are systemic overhauls, are easier to integrate. chosen to be small but meaningful. *Structured tools were used in this study. Figure 1. LOCK model in the Community Living Center or nursing home setting. Downloaded from https://academic.oup.com/gerontologist/article/58/4/e291/4990494 by DeepDyve user on 18 July 2022 The Gerontologist, 2018, Vol. 58, No. 4 e293 2015). In our study, we assumed that the LOCK-based designed to lead to deeper and potentially novel interpreta- intervention affected staff behavior by impacting their tions during and after analysis (Gibson, 2017). capability, opportunity, and motivation and that changed staff behavior would improve resident-staff interactions Setting and resident engagement. The LOCK-based intervention builds on team struc- We selected six CLCs through opportunistic and snowball tures that already exist in nursing home environments and sampling. Within each CLC, the intervention focused on achieves behavior change through observation, feedback, two neighborhoods that provided skilled nursing/rehabili- and relationship-building that fits into existing staff work- tation services and/or long-term care. Mean neighborhood flow (Mills et al., 2017). Staff identify bright spots by look- size was 23 residents (range: 10–45). The VA’s central insti- ing for positive outliers, such as extremely high occurrences tutional review board approved all study procedures. of resident engagement, and analyzing them for helpful information about how to facilitate behavior change. This conforms with the literature on the value of studying posi- Intervention and Study Design tive deviance (Bradley et al., 2009). In COM-B language, Ideal implementation of the intervention included the fol- it can alter capability by affecting understanding and lowing components. Staff looked for bright spots in resident- can affect motivation by providing evidence of existing staff interactions and resident engagement by conducting success. Observation, in turn, provides staff with opportu- structured observations using data collection templates cre- nities to study positive outliers and obtain critical informa- ated in an early phase of the study (Hartmann et al., 2017). tion about the progress of an intervention, thus potentially They discussed results of the observations in huddles that affecting capability and motivation. Collaboration through emphasized problem-solving, collaborative communication, huddles (i.e., brief, stand-up meetings at the point of care) and identifying and building on areas of strength. In the potentially alters capability, opportunity, and motivation huddles, staff determined action steps to implement lessons by promoting relationship-based team building and suc- learned from the observed bright spots and problem solved. cessful communication. Keeping all intervention activities They reviewed outcomes in subsequent huddles. confined to 5- to 15-min bursts enables easy integration Researchers and CLC staff facilitated the intervention into existing routines and can promote changes in capabil- through a team-based approach known as blended facili- ity, opportunity, and motivation by respecting staff mem- tation, in which external and internal facilitators engage bers’ busy schedules and easing the activities’ incorporation in interactive problem-solving and interpersonal support into regular routines. (Stetler et al., 2006). Researchers served as the external The study focused on Community Living Centers facilitators, as they had expertise in the intervention’s evi- (CLCs, i.e., nursing homes) within the Veterans Health dence base and implementation activities, as well as project Administration, the largest integrated health system in the and change management (Ritchie et al., 2017). CLC staff, United States. Studying the implementation of the interven- particularly those designated as study points of contact tion in CLCs, we believe, provides valuable insights into or those who emerged to champion the project, served as how change can be facilitated at the local level within a internal facilitators, individuals who were familiar with the large system. CLC’s organizational structures, procedures, culture, and clinical processes (Ritchie et al., 2017). At all participating CLCs, leadership assigned designated Research Design and Methods staff to be the study points of contact. We advised leadership We nested implementation of the LOCK-based intervention to choose individuals (a) with enough authority to function within a research data collection framework. This enabled as credible project leaders and (b) who could benefit profes- two separate sets of activities to run simultaneously—QI sionally from serving in this role. At each CLC, researchers data collection and research data collection—and distin- held a series of 1-hr training pre-implementation phone calls guished the QI portion of the study from the human sub- with CLC leadership and study points of contact. They also jects research arm. Each CLC implemented LOCK-based visited each CLC at the beginning of the implementation QI projects (the intervention). Researchers collected data period to collect baseline data and provide limited train- to study the outcomes of these projects. Research data ing and support for internal facilitators. Training focused form the basis for this paper’s results and comprised (a) primarily on nursing staff, with other staff invited. Timing researcher-conducted structured observations of the CLC and length of training was dictated by each CLC to fit into neighborhood (i.e., unit) pre and post intervention, (b) staff routines (i.e., up to two 1- or 2-hr training meetings self-administered surveys of CLC staff pre and post inter- and some on-the-floor training of approximately 30 min). vention, (c) researcher-administered surveys of CLC resi- Researchers also conducted weekly 30-min check-in calls dents pre and post intervention, and (d) researcher-led over the course of the implementation period. The inter- semi-structured interviews with CLC staff post interven- vention lasted for an average of 30 weeks at a site (range: tion. Triangulating qualitative and quantitative data was 23–39 weeks). Downloaded from https://academic.oup.com/gerontologist/article/58/4/e291/4990494 by DeepDyve user on 18 July 2022 e294 The Gerontologist, 2018, Vol. 58, No. 4 Quantitative Data Collection key. Raw scores were calculated for each subscale and aver- aged separately for a CLC’s residents and staff members. Researchers visited each CLC at two time points (prior to Subscale scores varied between 0 and 10, and calculated and at the end of the intervention period) to collect quan- averages were standardized against a normative U.S.-based titative study data. During these visits, researchers used sample (Moos, 2009). the Resident-centered Assessment of Interactions with Staff and Engagement (RAISE) tool (see below) to conduct Nursing Home Certified Nurse Assistant Job Satisfaction structured observations that captured data about staff and Questionnaire resident daily routines in the CLC. They used validated The Nursing Home Certified Nurse Assistant Job survey instruments to collect data from CLC residents. Satisfaction Questionnaire JSQ; (Castle, 2010) measured Concurrent with the visits, researchers also administered CLC staff members’ satisfaction with their work envi- Internet-based and paper surveys using validated instru- ronment. This 21-item questionnaire has seven domains ments to gather data from CLC staff. describing relationships with coworkers, work demands, work content, work load, training, rewards, and quality of RAISE Tool resident care, as well as two global job satisfaction ques- We used the RAISE instrument (Snow et al., 2018) to meas- tions. The JSQ was previously administered in a study of ure the quality of interactions between staff and residents 72 nursing homes in six states (Castle, 2007). Respondents and the frequency and extent of CLC resident engagement use a 10-point visual analog scale to rate each item. Scores in meaningful activity. The RAISE is a reliable and valid for each subscale were summed to create an overall score. instrument comprising eight observation variables (Snow et al., 2018). Researchers used a time-sampling approach Survey Administration for specific physical locations. For a 20-min period, this For staff, the CPES and JSQ were administered together as involved standing in an unobtrusive public area and follow- one survey at two time points: prior to implementation of ing a cycle of observing a target individual (staff or resident) the intervention and at the conclusion of the study period. for 5 s, noting observations, then switching observation to All CLC staff were invited to complete either an Internet- the next target in a structured, left-to-right pattern (Suen & based or paper version. The survey was anonymous and col- Ary, 1989). All residents and staff in the researcher’s visual lected minimal demographic and neighborhood information field were included in data collection. Raters achieved 90% to maximize response rates and, for the same reason, did not accuracy on a series of training videos before collecting attempt to link respondents between the two time points. data. Measures derived from the RAISE instrument were We administered the CPES to residents in-person. the following: (a) percentage of actively engaged residents; Residents were required to have lived in the CLC a minimum (b) percentage of verbal or nonverbal interactions between of 7 days. Staff members gave researchers a list of all cog- staff and residents during provision of routine care (a nitively intact residents. Researchers approached residents variable we termed, “Realized Opportunities for building using a convenience sampling method, returning to each Relationship”); (c) quality of staff interactions when present neighborhood multiple times. They screened potential par- with residents (i.e., positive, negative, or neutral); and (d) ticipants to ensure adequate cognitive ability and compre- emotional tone of observed staff or residents (i.e., positive, hension, using a standardized question-and-answer format negative, or neutral). that assessed basic orientation, alertness, and comprehension of the key elements of the informed consent form. The Community-Oriented Programs Environment Scale Resident experience and staff perception of resident expe- rience were measured for residents and staff, respectively, Qualitative Data Collection using an adaptation of the Community-Oriented Programs Environment Scale (CPES, formerly COPES) (Moos & At the end of each CLC’s intervention period, researchers Otto, 1972). The CPES was developed to measure the conducted in-person semi-structured qualitative interviews social climate of community-based residential and semi- with CLC staff members. Participants were solicited via residential programs, to ascertain whether they operate email and in-person contact. CLC leadership, clinicians, according to intended values, and to monitor social cli- nurses, nursing assistants, social workers, physical/occu- mate over time. It includes three forms, of which we used pational therapists, psychologists, pharmacists, dietary Form R (“Real”), which is used to describe the setting. We staff, chaplains, and others whose jobs related to QI were excluded the anger and aggression and system maintenance eligible to participate. The study’s conceptual framework subscales to maximize participation by keeping the number guided development and organization of interview guide. of items manageable for CLC residents and to align the Questions elicited thoughts about experiences with the content most closely with the study goal of measuring resi- project, how the project or using the observation tools dent engagement. The final adapted instrument contained influenced how staff did their jobs, impressions of huddles, 60 true/false statements. A score of 0 or 1 was assigned impressions of conducting observations, how the project to each answer based on a match with the CPES’s scoring influenced resident care, and how the environment of the Downloaded from https://academic.oup.com/gerontologist/article/58/4/e291/4990494 by DeepDyve user on 18 July 2022 The Gerontologist, 2018, Vol. 58, No. 4 e295 CLC changed as a result of the project. Follow-up probes instrument. Also across both time points and all six CLCs, focused on understanding particular elements and COM-B 62 residents completed the CPES survey; only four resi- components. Researchers recorded each interview. dents completed it at both time points. Of the 281 staff who provided information on gender, 80% were female. Among the 287 staff who provided infor- Analysis mation on job type, 39% (n = 113) were licensed nurses, Quantitative 31% (n = 88) were nursing assistants, and 30% (n = 86) All quantitative data were analyzed at the CLC level because held other jobs. And of the 273 staff who provided data data, by design, could not be linked back to respondents. on length of time having worked in the CLC, the average We used descriptive analyses to characterize resident expe- was 7 years (range: 0.1–34). Resident surveys collected no rience, staff satisfaction, and RAISE measures before and demographic information. after the intervention. For cross-sectional analyses, we com- Table 1 reports CPES and JSQ results. CLC-level mean bined all data (pre and post) and used generalized linear scores for the CPES were 46.5 for staff (range: 40.0–50.3) models to assess the association of RAISE-derived measures and 44.0 for residents (range: 38.1–50.2). The CLC-level with resident experience and staff satisfaction, adjusting for overall mean score for the JSQ, which was administered CLC-level average length of staff work tenure in the CLC. only to staff, was 7.7 (range: 6.4–8.3). For post- versus pre-intervention analyses, we used general- Researchers performed a total of 1,490 RAISE instrument ized linear models to assess the association of the interven- observations (averaging 248.3 observations per site) across 55 tion with the RAISE-derived measures, adjusting for site. observation periods prior to intervention implementation and Each of the RAISE instrument’s 5-s observation intervals 1,555 observations (averaging 259.2 per site) across 47 obser- was considered one unit of observation. A false discovery vation periods post intervention. Across all six CLCs prior to rate correction (Benjamini & Hochberg, 1995) was used implementation, 86.9% of staff had Realized Opportunities to account for multiple hypothesis testing. Statistical sig- for building Relationship with residents during provision of nificance was set at the p ≤ .05 level. All statistical analyses routine care and, among staff who were near residents (i.e., were performed using SAS 9.3 (SAS Institute, Cary, NC). within 3 ft), 6.4% were observed interacting negatively with Qualitative Table 1. Facility-Level Measures of Resident Experience and Six members of the research team with expertise in qualita- Staff Satisfaction tive methodology listened to interview recordings and coded the content, entering each participant’s data into an analytic Reported by matrix that contained a priori analytic constructs based on residents Reported by (N = 6) staff (N = 6) the LOCK model (columns) and COM-B (rows). Data were sites sites entered as verbatim quotes or summarized content. We used Resident experience (i.e., CPES) thematic content analysis (Lincoln & Guba, 1985) to fit the Overall 44.0 ± 4.3 46.5 ± 3.7 data into the matrix and examine emerging themes across Autonomy 42.2 ± 5.9 44.1 ± 3.8 respondents within the a priori constructs. Data could have Involvement 45.7 ± 6.4 45.1 ± 5.5 more than one code, and the matrix structure allowed for Practical orientation 42.9 ± 6.5 46.5 ± 5.2 change during the coding process. Initial interviews were Personal problem orientation 39.0 ± 3.3 44.4 ± 2.4 independently coded by two people and reviewed as a team Support 46.8 ± 6.2 46.1 ± 4.4 until consistent agreement was reached (n = 6); subsequently, Spontaneity 47.2 ± 3.6 53.7 ± 3.3 interviews were coded individually. The team met regularly b Staff satisfaction (i.e., JSQ) to review the coding for each interview and discuss discrep- c Overall 7.7 ± 0.7 ancies, resolving them by reaching consensus. The team Global 7.4 ± 0.8 wrote detailed notes to serve as an audit trail (Bradley, Curry, Relationships with coworkers 7.6 ± 1.2 & Devers, 2007). Analyses included all four COM-B con- Work demands 7.2 ± 0.9 cepts, but this paper presents only the Behavior outcomes. Work content 8.5 ± 0.3 Workload 7.6 ± 0.5 Training 8.6 ± 0.6 Results Rewards 6.0 ± 1.0 Quality of resident care 8.7 ± 0.6 Quantitative Staff surveys had overall response rates of 29.8% (range: Note: Mean score (standardized for CPES, unadjusted raw mean for JSQ) 24.1%–37.5%) pre implementation and 30.7% (range: ± SD shown. CPES = Community-Oriented Programs Environment Scale; 9.1%–54.9%) post implementation. Because we employed JSQ = Nursing Home Certified Nurse Assistant Job Satisfaction Questionnaire. convenience sampling, resident surveys had no response CPES (N = 62, N = 308). Higher score = better experience. residents staff Measured by the JSQ (N = 306). Higher score = more job satisfaction. rates. Across both time points and all CLCs, 308 staff com- Calculated based on the mean of subscale scores. pleted the CPES survey and 306 staff completed the JSQ Downloaded from https://academic.oup.com/gerontologist/article/58/4/e291/4990494 by DeepDyve user on 18 July 2022 e296 The Gerontologist, 2018, Vol. 58, No. 4 them (Table 2). After intervention implementation, more with residents (β = −0.035, 95% CI: −0.062 to −0.009, than 96% of staff had Realized Opportunities for building adjusted p = .0288). Relationship with residents and, among staff who were near residents, 2.3% interacted negatively with them. Qualitative Findings Across all CLCs, we conducted 66 interviews (range: 5–23). Cross-sectional Relationship Between RAISE Measures Qualitative analysis focused on describing staff impressions and CPES of how the intervention affected their behaviors (as per Positive emotional tone as measured by the RAISE instru- the COM-B model). Behaviors grouped into two themes: ment was positively associated in generalized linear models “Identifying Opportunities for Engagement” and “Quality with overall resident experience (resident-reported, β = 28.3, of Interactions Between Residents and Staff.” 95% CI: 1.1–55.4, p = .046; staff-reported, β = 33.1, 95% CI: 5.1–61.1, p = .033) and staff perceptions of residents’ Identifying Opportunities for Engagement involvement in CLC life (β = 49.4, 95% CI: 9.2–89.6, Conducting observations of life in the CLC as part of the p = .030), autonomy (β = 34.9, 95% CI: 16.8–53.0, p = .009), intervention helped staff notice opportunities for engage- and practical orientation (β = 45.8, 95% CI: 6.4–85.2, ment with residents. They became particularly aware of p = .034). Resident engagement as measured by the RAISE times when residents were waiting for events or when there instrument was positively associated with residents’ involve- were no formal recreational activities planned. A nurse ment in CLC life (β = 0.33, 95% CI: 0.10–0.56, p = .019). practitioner described her initial experience of recognizing opportunities for engagement: Cross-sectional Relationship Between RAISE Measures and JSQ “You feel bad when you… actually see nothing is going on.” Staff satisfaction was high across all six CLCs, with a facility- Staff also frequently noted recognizing previously missed level mean calculated overall score of 7.7 (range: 6.4–8.3). opportunities to engage with residents during care activi- Scores were similarly high for the relationships with cowork- ties, particularly around the process of handing out ers, work demands, work content, workload, training, rewards, medications: and quality of resident care subscales, and global job satisfac- tion items. Positive emotional tone was positively associated “I’ve noticed people really trying to connect with with staff satisfaction with training (β = 5.1, 95% CI: 0.3–9.8, patients instead of just handing out meds. They can do p = .042) and rewards (β = 8.0, 95% CI: 1.2–14.7, p = .033). their job and interact with people. [Observing] shows nurses or RNs that they can do more than just meds.” Post- versus Pre-intervention Association of the LOCK- (Recreational Therapist) Based Intervention With RAISE Measures Across all six CLCs, implementation of the LOCK-based Several participants described how staff, as they became intervention was significantly associated with increased aware of times of lower activity, initiated activities and Realized Opportunities for Relationship between staff spent more time interacting with residents to improve and residents (β = 0.083, 95% CI: 0.04–0.126, adjusted engagement. This nurse manager shared her surprise at the p = .0012; Table 3) and decreased negative staff interactions change she observed among her staff: Table 2. RAISE Measures Before and After Implementation of the LOCK-Based Intervention Before LOCK intervention, % (95% CI) After LOCK intervention, % (95% CI) Resident engagement, active 58.6 (54.6–62.7) 62.5 (59.0–65.9) Realized opportunities for relationship 86.9 (82.7–91.0) 96.2 (94.0–98.4) Quality of staff interactions with residents Positive 72.0 (68.0–76.0) 79.0 (75.0–82.3) Neutral 21.6 (17.9–25.3) 19.0 (15.5–22.6) Negative 6.4 (4.2–8.6) 2.3 (1.0–3.7) Emotional tone Positive 33.8 (31.2–36.4) 34.2 (31.6–36.9) Neutral 65.0 (62.4–67.6) 64.8 (62.1–67.5) Negative 1.0 (0.05–1.6) 0.7 (0.03–1.2) Note: Individual-level percentage (95% CI) shown. CI = confidence interval; RAISE = Resident-centered Assessment of Interactions with Staff and Engagement. Based on observations of residents (N = 337; N = 484). pre-intervention post-intervention Verbal/nonverbal staff interactions with residents, based on observations of staff providing routine care to residents (N = 259; N = 289). pre-intervention post-intervention Based on observations of staff who were verbally/nonverbally interacting with residents (N = 889; N = 1,254). pre-intervention post-intervention Based on observations of staff and residents (N = 1,290; N = 1,206). pre-intervention post-intervention Downloaded from https://academic.oup.com/gerontologist/article/58/4/e291/4990494 by DeepDyve user on 18 July 2022 The Gerontologist, 2018, Vol. 58, No. 4 e297 Table 3. Post- vs Pre-intervention Association of the LOCK-Based Intervention With RAISE Measures, Adjusting for Site a a β 95% CI FDR adjusted p value Resident engagement, active 0.017 −0.034 to 0.069 .585 Realized opportunities for relationship 0.083 0.040–0.126 .0012 Quality of staff interactions with residents Positive 0.055 0.000–0.111 .1 Negative −0.035 −0.062 to −0.009 .0288 Emotional tone Positive 0.011 −0.027 to 0.048 .585 Negative −0.003 −0.011 to 0.004 .5625 Note: CI = confidence interval; FDR = false discovery rate; RAISE = Resident-centered Assessment of Interactions with Staff and Engagement. FDR adjusted p values to account for multiple hypothesis testing. Verbal/nonverbal staff interactions with residents, based on observations of staff providing routine care to residents. Based on observations of staff who were verbally/nonverbally interacting with residents. Based on observations of staff and residents. “Last week my CNA […] saw the residents just sitting there members, including one registered nurse, reported adapting waiting for lunch. She […] brought out some games to get their interactions with residents to be more engaging: people engaged while they were waiting for their meal. That “The tool is good to make people more cognizant of their had never occurred before. She just got them all involved behavior. It gets staff more engaged with the residents while they were waiting and took away the distraction of rather than hanging out and gossiping with each other.” the residents’ trays being late…CNAs normally did not Participants reported a variety of ways they modified their take initiative, and now I see them taking more initiative.” behavior, including increased physical touch, brief acknowl- Many participants shared that observing the outcomes of edgements, and conversation (e.g., during meal times, direct improved resident-staff engagement motivated staff to con- care activities, and medication distribution). Many par- tinue their efforts in the project. In some cases, the positive ticipants felt they were able to learn more about resident outcomes led to wider change that included staff not par- preferences, particularly around food, activities, and verbal/ ticipating directly in the study. A registered nurse described nonverbal communication styles, through the increased how improved engagement with residents became a habit engagement. As one registered nurse described, learning how and improved the quality of care residents received: to better engage residents was also personally rewarding: “It becomes an instinct. When they see someone walk- “Observing the relationships allowed them to learn ing around on his own, they just go over and meet them things about the residents or about the families […] It in the middle and hold their hand and walk together was educational just to see how they [residents] can instead of letting him wander around. You think it’s just communicate – not only verbally, but body language, a very small thing, but those are the ones that prevent and getting residents to smile and talk back and interact. bigger things from happening.” It was really rewarding from that standpoint.” Several participants, such as this ward clerk, described how Several CLC staff reported that the increased knowledge non-nursing staff also became involved in the efforts to of resident preferences, derived from improved engage- improve resident engagement: ment, created the sense that their work day was easier. One “The biggest impact is to encourage everyone, from all licensed practical nurse described her experience: walks of life, different staff, to pay close attention to the “It eases the workload, because when you have an residents. […] You don’t have to be a nurse. As a house- engaged person who’s not bored out of their mind, keeper or secretary you can see things. It also encourages us they’re calmer and you’re not running back and forth to engage with the guys. Before we were like, ‘Fragile popu- to the room.” lation, I don’t want to do anything to hurt them.’ Now you can go in there and interact with them and they like that. It’s A neighborhood clerk described how even small gestures really nice. Before I would wave to them, but now I can go could improve resident engagement: in there and crack a joke or tell a silly story and open up.” “Lately, when we got them up and stuff, and we got a free moment, and we see the patient just sitting there, Quality of Interactions Between Residents and Staff somebody will go interact with them. And it brought The act of doing observations also challenged many par- life to them. They will offer them a snack or give them a ticipants’ perceptions of how well they were engaging little conversation and that seems to make them bright with residents. As a result of a new awareness, many staff up more. And it really did.” Downloaded from https://academic.oup.com/gerontologist/article/58/4/e291/4990494 by DeepDyve user on 18 July 2022 e298 The Gerontologist, 2018, Vol. 58, No. 4 This was also true for residents with dementia. One assis- & Herman, 2011). Our findings are also consistent with tant nurse manager reported that learning more about the other studies demonstrating that staff respond positively to preferences of a new resident with advanced dementia and interventions to improve resident-staff interactions (Meeks, aphasia led to the resident being more cooperative during Van Haitsma, Schoenbachler, & Looney, 2015; Passalacqua direct care because he felt more comfortable with the staff. & Harwood, 2012). Another nurse manager said: We developed the concept of Realizing Opportunities for building Relationship to highlight the possibility of staff “I believe that even though they are not aware, they do using existing time to improve their relationships with resi- have that sense of emotion. If you’re in a good mood, dents through interactions in the course of daily routines. they’re in a good mood.” By interacting positively while working within a residents’ personal space, busy staff can increase resident engagement Several participants felt that sharing information about by using opportunities that are already present. In a major residents in huddles improved interactions and the quality evaluation of the Green House model of person-centered of care residents received. A nurse educator noticed that care, aides were observed spending almost five times as long huddling helps the staff identify “who’s more in tune with engaging with residents compared with traditional nursing certain residents” so they could provide care for that resi- home aides. Multitasking played an important role in this dent more regularly or be called in for challenging situa- engagement success, with one-third of the total engagement tions. The huddles also encouraged staff to be mindful of time occurring while aides performed other activities, such as engagement on a regular basis, as described by a licensed preparing a meal or folding laundry (Sharkey, Hudak, Horn, practical nurse: James, & Howes, 2011). The potential impact of such mul- “It made everyone more aware [of engagement]. […] the titasking is highlighted by the large amount of time residents huddles where they were able to talk about it, that really spend receiving personal care (18% in one time-sampling helped.” study [Harper Ice, 2002]) that could involve resident engage- ment and by the compelling evidence from time-sampling studies that nursing home residents do not receive enough Discussion interaction with staff and spend most of their time unen- We built the LOCK-based intervention on the evidence- gaged (Kolanowski & Litaker, 2006; Schreiner et al., 2005). based premise that, for nursing home residents, positive One study reported that multitasking of resident interaction interactions with staff and engagement in daily life con- with hygiene and nutrition duties occurred in less than 20% tribute meaningfully to quality of life outcomes (Lawrence, of observed care encounters (Munyisia, Yu, & Hailey, 2011). Fossey, Ballard, Moniz-Cook, & Murray, 2012; Sullivan & Such non-communicative encounters are likely fraught with Asselin, 2013). Although the positive effects of improving potential for negative outcomes such as resident distress, agi- resident-staff interactions and increasing resident engage- tation, and aggression. ment are well established (Kolanowski, Litaker, Buettner, The bite-size nature of Realized Opportunities for build- Moeller, & Costa, 2011; Schreiner et al., 2005), it has been ing Relationship is also consistent with the science of habit, challenging to move beyond researcher-delivered interven- which underscores that behavior changes are most likely to tions to internally facilitated interventions that are feasible be sustained when they can be repeated regularly (Lally & and sustainable beyond the life of the research endeavor. Gardner, 2013). The brief nature of interactions during direct We aimed to achieve improvements in staff interactions care may have contributed to staff success with incorporat- with residents while relying primarily on internal facilita- ing Realized Opportunities for building Relationship behav- tion for intervention delivery and sustainment. Our data ior change. Changes focused on Realized Opportunities for suggest the intervention was successful in several respects. building Relationship may also have a positive economic Quantitative analyses indicated increased staff behaviors impact because they require no changes in staffing ratios—a related to Realized Opportunities for building Relationship potentially fruitful area for future research. and decreased negative staff interactions with residents post- Internal facilitators proved key to the success of our inter- intervention. Our qualitative data supported these findings. vention. Research staff provided some external support, but Staff consistently reported a newly developed increased it was largely up to the CLC-based internal facilitators to understanding of the impact of resident-staff interaction, deliver the intervention to their staff. Staff themselves col- an appreciation of the importance of resident engagement, lected engagement and interaction data using short obser- sensitivity to instances of lack of resident engagement, and vational QI tools. It was expected that the observation an increased awareness of times staff were and were not experiences along with the feedback provided by the data engaging with residents. The finding that negative staff would be among the active behavior change ingredients of interactions with residents decreased is noteworthy, given the intervention. Although the published literature includes the evidence that negative staff interactions are linked with examples of many engagement and interaction interven- negative resident outcomes such as increased resistiveness to tions that yielded positive results when the investigator care (Lann-Wolcott, Medvene, & Williams, 2011; Williams team themselves delivered the intervention (e.g., Barbosa, Downloaded from https://academic.oup.com/gerontologist/article/58/4/e291/4990494 by DeepDyve user on 18 July 2022 The Gerontologist, 2018, Vol. 58, No. 4 e299 Marques, Sousa, Nolan, & Figueiredo, 2016; Coleman, support activities were also those who conducted the inter- Medvene, & Van Haitsma, 2013), studies using internal views. We also did not include residents with cognitive impair- facilitators are rarer and typically include intensive, multi- ments as respondents for the resident survey due to concerns day trainings provided by external facilitators (Roberts, about adequate informed consent and used a convenience Morley, Walters, Malta, & Doyle, 2015; Stein-Parbury et al., sample of residents due to the time constraints imposed by a 2012; van Weert et al., 2006). To the best of our knowledge, short site visit comprising many components. This may have the intensity of our external facilitation was less than that resulted in a response bias. Although multiple attempts were described in any other published nursing home interaction made to contact all residents on the lists we received, resi- or engagement intervention. We posit that the sustainability dents who were continually out of the CLC were less likely of interventions such as ours, with more limited external to be interviewed, and these may have included some of the facilitation, will be greater than that experienced by prior highest functioning residents. Finally, because of the mixed- studies and hope to investigate this in the future. methods nature of the study, findings presented from each set of analyses are missing some richness and detail. Limitations Implications Several limitations are worthy of note. Our study used a staff-focused intervention that was designed, through This study provides preliminary support for a new approach changes in staff behavior, to affect resident engagement. But to improving resident–staff interaction and resident engage- primary data collection from residents was only through a ment that relies on the LOCK model. We found that nurs- survey, and our main measure of resident engagement was ing home staff were favorably impacted by experiences in from structured observations. Future work of this type which they positively engaged with residents and by the would ideally assess resident engagement through longi- opportunity to witness, as a consequence of their actions, tudinal qualitative data collection from residents, such what they perceived as meaningful and pleasant engage- as through interviews, PhotoVoice, etc. In addition, the ment on the part of the residents they cared for. Using the researchers’ structured observations may have produced combination of observations, huddles, and a focus on the a Hawthorne effect, although the observation interval per positive to support staff in discovering the causal relation- target individual was only 5 s, and our extensive work with ship between resident engagement and resident well-being the RAISE instrument suggests that the short actual obser- proved effective. Larger tests of this LOCK-based interven- vation interval for each target, combined with the 20-min tion or similar relational team-based approaches for other data collection timeframe—which allows the observer to outcomes or combinations of outcomes would be a logical blend more into the landscape—reduces this possibility. extension of this work. In addition, any effect would likely have been the same for both pre- and post-implementation observations. Our Funding opportunistic and snowball sampling methodology meant that the CLCs participating in this study, while coming This work was supported by the Department of Veterans Affairs, from different areas of the country, may not be representa- Veterans Health Administration, Office of Research and Development, Health Services Research and Development (I01HX000797) and tive of CLCs in general. Our results, however, were indica- Department of Veterans Affairs, Veterans Health Administration, tive of the potential for success of the intervention across Office of Research and Development, Rehabilitation Research and different CLC types and, in consequence, the entire pro- Development (IK2RX001241 to W. L. Mills). gram described here and elsewhere (Hartmann et al., 2017; Mills et al., 2017) was rolled out nationally to all CLCs in the Veterans Health Administration system. Conflict of Interest The staff survey had a somewhat low response rate but None reported. one that is comparable to or better than other surveys per- formed in VA (Linsky, Meterko, Stolzmann, & Simon, 2017; Sullivan et al., 2013). In addition, to ameliorate some effects Acknowledgement of potential biases, we triangulated data sources, having both The views expressed in this article are those of the authors and do residents and staff respond to the same survey instrument. not necessarily represent the views of the Department of Veterans However, due to limited sample sizes, our quantitative analy- Affairs. ses were at the CLC level rather than neighborhood level and did not control for CLC characteristics such as size or resi- References dent case-mix. Future studies with larger sample sizes would be useful to investigate differential effects of such variables. Alexander, J. A., & Hearld, L. R. (2011). 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Journal
The Gerontologist – Oxford University Press
Published: Jul 13, 2018
Keywords: internship and residency; medical residencies; nursing homes; community