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This is the published version of a paper published in Journal of Advanced Nursing.

Citation for the original published paper (version of record):

Nordin, S., McKee, K., Wijk, H., Elf, M. (2017)

The association between the physical environment and the well-being of older people in

residential care facilities: a multilevel analysis.

Journal of Advanced Nursing, 73(12): 2942-2952

https://doi.org/10.1111/jan.13358

Access to the published version may require subscription.

N.B. When citing this work, cite the original published paper.

Permanent link to this version:

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O R I G I N A L R E S E A R C H :

E M P I R I C A L R E S E A R C H — Q U A N T I T A T I V E

The association between the physical environment and the

well-being of older people in residential care facilities: A

multilevel analysis

Susanna Nordin

1,2

| Kevin McKee

1

| Helle Wijk

3,4

| Marie Elf

1,2

1

School of Education, Health and Social Studies, Dalarna University, Falun, Sweden

2

Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden

3

Sahlgrenska Academy, Institute of Health and Care Science, Gothenburg University, Gothenburg, Sweden

4

Sahlgrenska University Hospital, Gothenburg, Sweden

Correspondence

Susanna Nordin, School of Education, Health and Social Studies, Dalarna University, Falun, Sweden.

Email: snr@du.se

Funding information

The Health and Welfare research theme at Dalarna University and Institute of Health and Care Science, Gothenburg University supported this study.

Abstract

Aims: To investigate the associations between the quality of the physical

environ-ment and the psychological and social well-being of older people living in residential

care facilities.

Background: Many older people in care facilities have cognitive and physical

frail-ties and are at risk of experiencing low levels of well-being. High-quality physical

environments can support older people as frailty increases and promote their

well-being. Although the importance of the physical environment for residents

well-being is recognized, more research is needed.

Design: A cross-sectional survey of 20 care facilities from each of which 10

resi-dents were sampled. As the individual resident data were nested in the facilities, a

multilevel analysis was conducted.

Methods: Data were collected during 2013 and 2014. The care facilities were

pur-posely sampled to ensure a high level of variation in their physical characteristics.

Residents

’ demographic and health data were collected via medical records and

interviews. Residents

’ well-being and perceived quality of care were assessed via

questionnaires and interviews. Environmental quality was assessed with a structured

observational instrument.

Results: Multilevel analysis indicated that cognitive support in the physical

environ-ment was associated with residents

’ social well-being, after controlling for

indepen-dence and perceived care quality. However, no significant association was found

between the physical environment and residents

’ psychological well-being.

Conclusion: Our study demonstrates the role of the physical environment for

enhancing the social well-being of frail older people. Professionals and practitioners

involved in the design of care facilities have a responsibility to ensure that such

facilities meet high-quality specifications.

K E Y W O R D S

long-term care, multilevel modelling, nursing, older people, physical environment, residential care facility, well-being

-This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

© 2017 The Authors. Journal of Advanced Nursing Published by John Wiley & Sons Ltd.

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1

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I N T R O D U C T I O N

Throughout the world, older people living in residential care facilities (RCF) commonly suffer from cognitive frailties, such as impaired spa-tial perception and orientation together with difficulties in interpret-ing sensory input. Physical frailties and impaired mobility are also common and can be caused by pain, reduced strength or coordina-tion problems (World Health Organizacoordina-tion 2015). Co-occurrence of two or more chronic diagnoses is generally high among older people (Kone Pefoyo et al., 2015; Melis, Marengoni, Angleman, & Fratiglioni, 2014) and among people living in RCFs in particular (Schram et al., 2008) with a majority of residents having dementia or dementia-related impairments (Seitz, Purandare, & Conn, 2010).

Both psychological and social well-being are considered to be important dimensions of quality of life, together with physical health and the physical environment (World Health Organization quality of life assessment (WHOQOL) Group (1998). It is not unu-sual for older people in RCFs to experience lower well-being because of deteriorating health and decreased socialization (Smith, Borchelt, Maier, & Jopp, 2002) and previous studies have reported that residents perceived that their individual wishes were not being met and that they had little influence on their daily life (Hellstr€om & Sarvim€aki, 2007; Tuominen, Leino-Kilpi, & Suhonen, 2016). Living in a safe and supportive environment may balance these negative effects. In their ecological theory of ageing, Lawton and Nahemow (1973) stipulated that the environment will have greater influence with increasing levels of frail health. According to the theory, a per-sons’ behaviour is the function of the interplay between individual competencies such as physical and cognitive health including func-tional capabilities, resources and preferences and the demand from the environment such as the physical, personal and social environ-ment. A balance between the persons’ competences and environ-mental press will result in a positive effect such as well-being (Lawton, 1983).

Accordingly, the environmental design of RCFs can be expected to have a crucial impact on individuals with cognitive and physical frailties and the environment must therefore be adapted to meet the needs of highly frail older persons to enhance their well-being (Law-ton & Nahemow, 1973). In this study, we investigated the associa-tion between environmental quality and the psychological and social well-being of older people living in RCFs.

1.1

|

Background

Research has demonstrated that the physical environment can have a positive impact on older people living in RCFs (Joseph, 2006; Joseph, Choi, & Quan, 2015). For example, the unit layout, sound levels and access to outdoor areas can improve sleep, orientation, activity and overall well-being (Brawley, 2001; Joseph, 2006). Moreover, contact with nature can increase well-being among residents (Bengtsson, 2015) and enhance competence for persons with dementia (Rappe & Topo, 2013). Safety aspects such as proper flooring materials, safe handrails and adequate lighting can support mobility (Brawley, 2001)

while floor plan design and environmental cues such as signage and colours have an impact on navigation for persons with dementia (Cohen-Mansfield, 2001; Marquardt, 2011). By contrast, poorly

Why is this research or review needed?

The physical environment has been shown to influence well-being and is theorized to be of particular importance for older people with high levels of frail health. Thus, it is critical to develop evidence-based knowledge regard-ing how environmental aspects can support the well-being of older residents in care facilities.

The influence of specific environmental elements on older people’s well-being remains poorly understood and this study investigated associations between environ-mental quality and psychological and social well-being of residents in care facilities.

Due to the fact that residents live in specific care facili-ties, to determine how care environments are associated with individual behaviour, statistical methods such as those employed in this study are required to model both environmental and individual-level variation.

What are the key findings?

The level of cognitive support in the physical environ-ment was found to be associated with the social well-being of older people in long-term care even after con-trolling for independence and perceived care quality.

The findings highlight the value of identifying specific elements of the physical environment in care facilities that are important to older people with frail health.

In line with ecological theories on ageing, the findings sup-port the idea that environmental design can compensate for decreasing competencies and enhance resident well-being.

How should the findings be used to influence

policy/practice/research/education?

Professionals involved in the planning and design of care facilities have a major responsibility in taking into account environmental aspects that are essential to older people with frail health.

Elements of the physical environment that support resi-dents’ cognitive functioning need to be considered in the design process and should also be given special attention in existing facilities.

Knowledge regarding how the physical environment can support older people’s cognitive functioning would enable care staff to improve care practices in residential care facilities.

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designed RCFs with an institutional character can severely reduce the potential for high-quality care and negatively influence residents’ health and well-being (McCormack & McCance, 2006).

Person-centred care has been established as an approach to improve the well-being of residents and their relatives (Koren, 2010; Sj€ogren, Lindkvist, Sandman, Zingmark, & Edvardsson, 2013) and the overall quality of care (Grabowski et al., 2014; Zimmerman, Sloane, & Reed, 2014). A persons’ participation in care and the relationship between the person and healthcare staff have been identified as core aspects of person-centred care (Kitson, Marshall, Bassett, & Zeitz, 2013) and the environment where care is delivered is also rec-ognized as an integral component (Brooker, 2003; Cowdell, 2006). For example, well-organized physical environments can be related to feelings of safety, whereas RCFs offering privacy can promote well-being (Edvardsson, Sandman, & Rasmussen, 2008). Moreover, physi-cal environments that support person-centred care can enhance the care quality and in turn the well-being of residents (Edvardsson, Winblad, & Sandman, 2008; Sj€ogren et al., 2013). High-quality care is also dependent on the organizational structure and care values including the knowledge and skills of care staff and support from management (Gibson, Carter, Helmes, & Edberg, 2010; McCormack, Dewing, & McCance, 2011). There is a growing trend towards pro-viding person-centred care in RCFs (Feinberg, 2014) and the concept has been operationalized in several assessment instruments based on theory, research and practise and targeted to different groups such as older people and care staff (Edvardsson, Koch, & Nay, 2009; Edvardsson, Sandman, et al., 2008).

Despite the recognition of the importance of the physical envi-ronment of RCFs for supporting resident well-being and person-centred care, research on their association is limited. Previous stud-ies of resident well-being in RCFs have mainly taken an individual-level or care-based perspective and not considered home-individual-level fac-tors such as the impact of the RCF environment. One reason for this could be the complexity of the interactions between the physical environment, the residents and organizational and management fac-tors, which make it difficult to isolate the impact of the environment without a substantial sample of RCFs to ensure sufficient variation in environmental features (Torrington, 2007). Another reason is the absence of instruments with demonstrated reliability and validity appropriate for assessing environmental quality in RCFs for older people (Elf, Nordin, Wijk, & McKee, 2017). Recently, however, a new instrument, the Swedish version of the Sheffield Care Environment Assessment Matrix (S-SCEAM) was developed (Nordin, Elf, McKee, & Wijk, 2015) and this instrument was used in this study.

2

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T H E S T U D Y

2.1

|

Aims

The aim of the study was to investigate the associations between the quality of the physical environment and psychological and social well-being of older people living in RCFs. Specifically, we wished to determine whether the physical environment could explain variance

in resident psychological and social well-being, after controlling for the effect of resident independence and perceived quality of care.

2.2

|

Design

A cross-sectional survey design was used to investigate the quality of the physical environment in Swedish RCFs and the psychological and social well-being of residents of the facilities.

2.3

|

Sample

The study included 20 RCFs in Sweden and 200 residents living in these facilities. As the individual resident data (Level 1) is nested in the care facilities (Level 2), a multilevel analytic approach was adopted. While there are no absolute rules governing the sample size requirements for multilevel modelling, it is widely held that the number of Level 2 units should ideally be 30 or greater and should not be <10 (Hox, Moerbeek, & van de Schoot, 2010). Pragmatic restraints for our study meant that we targeted a sample of 20 RCFs, with 10 residents sampled from each facility.

RCFs were eligible for inclusion if they provided 24-hr care to older people. As the study focused on RCFs in general, specific dementia care units (SDCU) were excluded because of their special environmental design, structure and staffing. Our sampling frame was a national classification of municipalities determined by popula-tion, commuting, industry, tourism and economic structure (Swedish Association of Local Authorities and Regions 2010). From this frame, RCFs were purposively sampled to ensure a high level of variation in the RCFs’ physical characteristics, considering factors such as urban– rural location, building design, year of construction, size and type of organization. For each municipality selected for the study, the execu-tive director for social support and care of older people was pro-vided with information about the study and requested to submit a list of eligible RCFs. From these lists, RCFs were purposive selected and the managers of the facilities were contacted, informed about the study and invited to participate. Of 27 RCFs initially selected for the study, permission for data collection was received from 20, a recruitment rate of 74.1%.

The managers of the participating RCFs were provided with detailed instructions prior to data collection about the process for recruitment of participants to the study. They were asked to dis-tribute information letters describing the study to all residents, rela-tives and care staff, with an invitation to residents to participate in the study. Written informed consent was obtained from residents or their relative when they responded to the invitation that they were willing to participate. Managers of RCFs then applied our inclusion and exclusion criteria to those residents willing to participate in our study: residents were eligible for inclusion if they could express themselves verbally in Swedish and were able to hear; exclusion cri-teria were having high levels of cognitive, sensory or physical impair-ment such that the resident would be unable to give reliable data during interview or would probably be unable to complete the inter-view. The 10 residents from each facility recruited to the study were

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then selected at random by the respective facility managers from those willing to participate and meeting our inclusion and exclusion criteria.

2.4

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Data collection

Data were collected during 2013 and 2014. The data collection at each facility took place over several days. Data were collected using questionnaires and via face-to-face interviews with each residents. The interviews were supported by the use of response category cue cards (Berkman & D’Ambruoso, 2006). Resident demographic and health data were collected from the facility manager. Prior to the interview, study information was again provided to the resident and the residents’ willingness to participate was confirmed. If a resident asked to withdraw from the study during an interview, or was found to be too severely impaired to complete the interview, the interview was terminated. In due course, another resident was selected at ran-dom by the facility manager from the initial list of residents who had met our inclusion and exclusion criteria.

The S-SCEAM data were collected by the researcher via a stan-dardized walk-through of the whole facility. At each facility, three private apartments were selected for assessment from those belong-ing to the 10 residents who had participated in the study, this selec-tion being carried out purposively so that the apartments reflected the range available in the facility.

2.5

|

Instruments

2.5.1

|

Environmental quality assessment

The quality of the physical environment was assessed using S-SCEAM (Nordin et al., 2015). S-S-SCEAM is based on a theoretical model of environmental quality for RCFs that conceives of quality not only in terms of accepted building regulations and guidelines but also and primarily in terms of the environment’s capacity to support the needs of frail older people, conceptualized in terms of eight domains: cognitive support, physical support, safety, normalness, openness and integration, privacy, comfort and choice. S-SCEAM contains 210 items that describe individual elements of the physical environment, structured into sections reflecting the main locations of an RCF: overall layout, entrance and external area, garden, lounge, dining area, private apartments and communal bathroom. For exam-ple, the cognitive domain contains environmental features that are regarded as promoting an independent everyday life for older people with cognitive or sensory disabilities and those who have difficulties in orienting themselves. The following is one example of an item in the cognitive domain: Is the entrance door designed with clear contrasts?

S-SCEAM is scored by an assessor via a walk-through of the facility during which each item is observed and indicated as present (1) or absent (0). Item scores are added together to obtain an overall score and in domains to get domain scores, standardized to get scores with a range of 0–100. Higher scores reflect greater environ-mental quality.

2.5.2

|

Residents

’ demographic and health data

Data on residents’ age, gender, main diagnoses and independence (higher scores indicate greater independence) (Mahoney, 1965) were obtained partially from the facility manager via residents’ medical records and partially via resident interviews. To assess residents cognitive status the Mini Mental State Examination (Folstein, Fol-stein, & McHugh, 1975), Swedish revision (MMSE-SR) was used (Palmqvist, Terzis, Strobel, & Wallin, 2011). Because several residents were unable to complete some items due to physical impairments, a percentage score (calculated as the number of correct reliably com-pleted items divided by the total number of reliably comcom-pleted items) was used during analyses; higher scores indicate greater cognitive functioning.

2.5.3

|

Psychological and social well-being

Residents’ psychological well-being was assessed by the World Health Organisation-5 Well-being Index (WHO-5) (Heun, Bonsignore, Barkow, & Jessen, 2001), a five-item scale producing a score range 0–25, with higher scores indicating greater psychological well-being.

Residents’ social well-being was assessed by the Pleasant Events Schedule-AD (PES-AD) (Logsdon & Teri, 1997). The PES-AD contains 20 items describing common activities such as listening to music, watching television, having dinner with friends or family and going on outings. A proxy assessor (in our study the resident’s key worker) indicates the frequency with which a resident participates in each activity (scored 0= never, 1 = sometimes and 2 = often) and addi-tionally whether the resident enjoys the activity (0= no, 1 = yes). A score on each item is calculated as the product of frequency and enjoyment and can be rated from 0 to 2, with item product scores summed to get a scale with a range 0–40 with higher scores indicat-ing greater social well-beindicat-ing.

2.5.4

|

Perceived quality of care

Quality of care from the resident’s perspective was measured by the Person-Centred Climate Questionnaire—Patient version (PCQ-P) (Edvardsson, Sandman, et al., 2008). This instrument measures the extent to which the care in a care facility is perceived by the resi-dents to be person centred. The PCQ-P contains 17 items that are composed as statements and these are scored on three subscales: safety, everydayness and hospitality. The scoring for each item reflects the level of a respondent’s agreement with the statement from 1= No, I disagree completely - 6 = Yes, I agree completely. Higher scores indicate higher levels of agreement that the care climate of the facility is person centred.

2.6

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Ethical considerations

The study was approved by a regional ethical review board for research in Sweden (Ref No. 2011/323). Written informed consent was obtained from care home managers, residents or their relatives.

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2.7

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Data analysis

The data were coded and analysed using the Statistical Package for Social Science (SPSS) for Windows v. 21.0. Descriptive statistics were generated as appropriate for each variable. Pearson product– moment correlation coefficients were determined for the bivariate associations among the study variables, both at an individual level (Level 1) and home level (Level 2). Using these analyses and given the restrictions imposed by the home-level sample size, the S-SCEAM domain with the strongest association with resident psycho-logical and social well-being when aggregated at the home level was selected for use in multilevel linear regression models examining the relationships between the home environment, resident indepen-dence, perceived quality of care and resident psychological and social well-being, with predictor variables grand mean centred. The significance level for each individual-level analysis and home-level bivariate analysis was set at p< .05. Statistical significance for the multilevel model was assessed with a two-taileda < 0.10. This level of alpha was chosen because the attained sample size was lower than optimal. With an underpowered analysis, the risk of Type II error is inflated and alpha was set to counter this problem. To test for a statistical difference between the fit of two competing models, the change in the log-likelihood ratio was determined (D 2LL), with a < .05 for each test. Residual plots, Cook’s Distance, Mahalanobis Distance and Centred Leverage Value were used to check the model assumptions of linearity, normality and constant variance and to examine the effects of outlying values. No adjustment of experimen-tala was made for multiple testing: therefore, the potential for an inflated Type I error rate for Level 1 analyses should be noted.

2.8

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Reliability and validity

S-SCEAM has been shown to have good validity and good test –ret-est and inter-rater reliability (Nordin et al., 2015). WHO-5 has demonstrated adequate psychometric properties in several countries (Bech, Olsen, Kjoller, & Rasmussen, 2003; Heun et al., 2001; Topp, Østergaard, Søndergaard, & Bech, 2015) including Sweden (L€ove, Andersson, Moore, & Hensing, 2014). Due to missing data for some residents in our study, a mean score was calculated for all residents with at least four items validly completed, samplea = .85. The origi-nal version of the proxy instrument PES-AD has been shown to have good reliability and validity (Logsdon & Teri, 1997). In this study, PES-AD was translated into Swedish and pilot tested. A mean score was calculated for all residents with at least 13 items completed, samplea = .71. The PCQ-P instrument has previously demonstrated satisfactory reliability and validity (Edvardsson, Sandman, et al., 2008, 2009). Due to missing PCQ data for some residents in our sample, a mean score was calculated for all residents with at least five items completed on the Safety subscale, samplea = .87; and at least two items completed on the Everydayness subscale, sample a = .68. However, the Hospitality subscale was found to have unsat-isfactory internal consistency reliability (a = .33); thus this subscale was not used in further analysis.

3

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R E S U L T S

3.1

|

Descriptive results

3.1.1

|

Residential care facilities

The majority of RCFs (n= 15) were municipality owned and located in urban municipalities (n= 9). The oldest RCF was built 117 years ago, whereas the newest RCF was 1 year old. The number of floors in the facilities ranged from one to seven, with half of the RCFs hav-ing two floors. All the RCFs offered private en suite apartments for each of their residents, nearly all had a lounge and most (n= 16) had gardens, while only a minority (n= 5) offered communal bath-rooms. The number of residents per facility ranged from 23-68.

3.1.2

|

The quality of the physical environment

The results of the S-SCEAM assessment are presented in Table 1. The mean overall score was 71.33 (SD 3.78, range 65.27–80.43). Across the RCFs, the Safety domain had the highest mean score, although there was considerable variation across RCFs with mean scores ranging from 65.55 to 93.33. The Cognitive Support (mean= 60.05; SD 12.75) and Privacy (mean = 60.59; SD = 12.18) domains had the lowest mean scores, but again there was consider-able variation across RCFs.

3.1.3

|

Resident characteristics

The mean age of the residents was 87.35 years, a majority was female (n= 140) and the mean duration of residence was 2 years. Most of the residents had multiple diseases and chronic conditions, the main categories of which were cognitive impairments, muscular-skeletal conditions, mental conditions, cardio-vascular diseases, respi-ratory diseases and functional losses. The mean score for indepen-dence was 72.42 and the mean score for cognitive functioning was 76.41. The assessments of resident psychological well-being and social well-being showed scores above the midpoint of the scales. The PCQ-P Safety and Everydayness subscale scores were substan-tially above their respective midpoints (Table 2).

T A B L E 1 S-SCEAM overall and domain scores for residential care facilities (N= 20)

Domain Mean SD Range Safety 80.35 6.77 65.55–93.33 Comfort 76.67 8.64 53.03–90.79 Openness and integration 74.39 7.18 60.00–86.67 Physical support 73.95 6.89 63.94–89.34 Normalness 73.59 11.91 45.83–95.24 Choice 71.07 9.64 51.04–87.50 Privacy 60.59 12.18 41.13–88.28 Cognitive support 60.05 12.75 43.56–86.67 Overall score 71.33 3.78 65.27–80.43

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3.2

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Bivariate associations

3.2.1

|

Individual level

Neither resident age nor gender was correlated with other resident characteristics, although female gender was associated with greater age. Residents who had been living in the RCF for a longer time were less independent and had lower cognitive functioning and lower social well-being. The remaining bivariate associations for resi-dent characteristics are presented in Table 3.

There were significant positive bivariate associations among most resident assessments, although most effect sizes were small (e.g. social well-being and PCQ-safety, r[196]= .15, p = .035) or small to moderate (e.g. PCQ-safety and PCQ-everydayness, r[197]= .63, p< .001). However, cognitive functioning was significantly associ-ated with social well-being (r[193]= .31, p < .001) and indepen-dence (r[194]= .17, p = .017) only.

3.2.2

|

Home level

There were no significant associations between S-SCEAM domain scores and characteristics of the RCFs. Higher scores on the Choice domain were associated with higher scores on privacy (r[18]= .476, p= .034), while higher safety was associated with higher cognitive support (r[18]= .532, p = .016). When aggregated at the home level, resident independence was associated with resident PCQ-P scores,

both for Safety (r[18]= .60, p = .005) and Everydayness (r[18] = .48, p= .034), while PCQ-P Safety and Everydayness were also signifi-cantly associated (r[18]= .64, p = .002); but these were the only significant associations in resident characteristics.

When aggregated at the home level, the number of residents living at the RCFs was associated with independence (r[18]= .55, p= .012) as was number of units (r[18] = .53, p = .016), while num-ber of floors was associated with psychological well-being (r [18]= .58, p = .008). Scores on S-SCEAM Normalness were associ-ated with PCQ-P Everydayness, (r[18]= .53, p = .017), while cogni-tive functioning was associated with both Choice (r[18]= .55, p= .011) and Privacy (r[18] = 0.50, p = .025) (Table 4).

3.3

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Multilevel analysis

Of the S-SCEAM domains, Cognitive Support had the most consis-tent, strong associations with residents’ psychological and social well-being (r= .391 and .375, respectively, Table 4). Thus, this variable was selected as the home-level (Level 2) variable for use in multilevel models of the association between environmental quality and resident well-being.

3.3.1

|

Psychological well-being

Before any predictors were added to the model of psychological well-being, an unconditional (intercept-only) model was fit to parti-tion variance. This baseline model had a 2LL statistic of 615.7, with a residual (individual-level) variance estimate of 1.244 and an inter-cept (home-level) variance estimate of .031, providing an ICC(1) statistic of .024. Thus, only 2.4% of the variance in resident psycho-logical well-being was attributable to home-level grouping, below the level requiring a multilevel analysis (Kreft, Kreft, & de Leeuw, 1998). We therefore did not proceed further with this model.

3.3.2

|

Social well-being

The results of the multilevel model of social well-being are presented in Table 5. The ICC(1) statistic for the baseline model was .108, thus 10.8% of the variance in resident social well-being was attributable to home-level grouping. Taken together with a significant intercept T A B L E 2 Resident demographic, health and care characteristics

(N= 200)

Variable n Mean SD Range Age in years 200 87.35 7.67 57–102 Duration of residence in months 200 23.97 22.39 0–100 Independencea 200 72.42 10.75 46.00–84.50 Cognitive functioningb 144 76.41 6.27 64.44–87.60

Perceived care qualityc(Safety) 199 5.12 0.26 4.38–5.50

Perceived care qualityc

(Everydayness)

199 4.86 0.33 4.11–5.31 Psychological well-beingd 200 3.21 0.40 2.60–3.94

Social well-beinge 199 1.26 0.13 0.87–1.43 aBarthel Index;bMMSE-SR;cPCQ-P;dWHO-5;ePES-AD.

T A B L E 3 Bivariate associations among resident variables (N = 200)

Variable 1 2 3 4 5 6

1. Psychological well-beinga 0.260** 0.277** 0.002 0.391** 0.457**

2. Social well-beingb – 0.349** 0.307** 0.150* 0.226** 3. Independencec 0.170* 0.267** 0.220**

4. Cognitive functioningd 0.045 0.031

5. Perceived care qualitye(Safety) 0.631**

6. Perceived care qualitye(Everydayness) – Note: n size for each association will vary due to missing data.aWHO-5;bPES-AD;cBarthel Index;dMMSE-SR;ePCQ-P.

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variance term (.0083, Wald Z= 1.71, p = .087), there was sufficient evidence for a multilevel approach to continue with the model.

Independence was the next variable entered into the model (D 2LL = 26.76(1), p < .001), producing a 13.1% reduction in resid-ual (individresid-ual-level) variance and a 4.82% reduction in intercept (home-level) variance.

At the next step in the model, resident perceived quality of care (PCQ-P Safety and Everydayness subscales) was added to the model (D 2LL = 11.77(2), p = .001), producing a 5.4% reduction in residual (individual-level) variance and a 13.9% reduction in intercept (home-level) variance. In the final step in the model, S-SCEAM Cognitive Support was entered (D 2LL = 3.08(1), p = .048), producing a 25.0% reduction in intercept (home-level) variance. Thus, the model was significantly improved at each step, all predictors were significant in the final model except PCQ-P Safety: B= .000, t(197.3)= .022, p = .982.

4

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D I S C U S S I O N

4.1

|

Main findings

This is the first study to use S-SCEAM to evaluate the quality of the physical environment and its influence on the well-being of older people living in RCFs. Our findings indicate that the physical envi-ronment has an impact on the well-being of residents in long-term care and highlights the value of identifying specific environmental aspects of importance to this vulnerable group. Based on Lawton and Nahemow’ (1973) ecological theory of ageing we argue that the

design of the physical environment can compensate for decreasing functions and enhance opportunities for well-being by means of housing solutions and new technologies that can support declining competencies.

Our key finding was that the level of cognitive support in the facility environment explained a significant amount of the variance in residents’ social well-being, after controlling for resident indepen-dence and perceived quality of care. However, this association between cognitive support in the environment and well-being was not replicated in our model of psychological well-being, as only a small proportion of the variance in psychological well-being was related to the residents’ co-location.

Why should the environment influence social well-being but not psychological well-being? A plausible explanation could be that psy-chological well-being is highly dependent on residents’ current life situation, mental and physical health and recent events such as con-tact with family or friends. Hence, psychological well-being might be more sensitive to emotions and mood experienced by the resident at any given moment. By contrast, the physical environment might be expected to facilitate or hinder the social activities and interac-tions such as those assessed by our measure of social well-being, e.g. going on outings, helping around the RCF or listening to music.

Our findings reflect the multidimensional nature of both the physical environment and the well-being concept (World Health Organization 2015). For example, cognitive support, physical support and comfort are different aspects of the environment and therefore may be related to different aspects of well-being. By means of the comprehensive S-SCEAM instrument (Nordin et al., 2015), T A B L E 4 Bivariate associations between building domain scores and resident variables (N = 20)

Instrument Psychol. well-beinga Social well-beingb Independencec Cognitive functioningd Perceived care qualitye(Safety) Perceived care qualitye(Everydayness) 1. Safety 0.394 0.062 0.352 0.099 0.274 0.266 2. Comfort 0.119 0.140 0.294 0.082 0.395 0.035 3. Openness and integration 0.144 0.053 0.195 0.231 0.071 0.210 4. Physical support 0.416 0.041 0.112 0.400 0.112 0.078 5. Normalness 0.344 0.104 0.379 0.071 0.318 0.526* 6. Choice 0.163 0.025 0.031 0.554* 0.144 0.287 7. Privacy 0.210 0.225 0.427 0.500* 0.258 0.181 8. Cognitive support 0.391 0.375 0.059 0.079 0.187 0.126 Note:aWHO-5;bPES-AD;cBarthel Index;dMMSE-SR;ePCQ-P.

*p < .05 (two-tailed).

T A B L E 5 Multilevel model of social well-beinga(N

= 20)

Model step and variable entered 2LL, d.f.

Change in 2LL, d.f. p Level 1 variance Level 2 variance 1. Baseline 47.095, 1 – – .0685 .0083 2. Independenceb 20.332, 2 26.763, 1 p< .001 .0596 .0079

3. Care quality (Safety and Everydayness)c 8.563, 4 11.769, 2 p= .001 .0564 .0068

4. Cognitive supportd 5.488, 5 3.075, 1 p= .048 .0564 .0051 Note:aPES-AD;bBarthel Index;cPCQ-P;dS-SCEAM.

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associations between different aspects of environmental quality and well-being can be explored.

Other aspects of our findings also testified to the importance of the environment for the life of residents: the number of floors in a facility was associated with residents’ psychological well-being, while the S-SCEAM domain Normalness was associated with PCQ-P Everydayness, supporting the idea that the physical environment might play a role in facilitating good quality care.

4.2

|

Environmental support for cognitive frailties

There was substantial variation across the 20 RCFs in our sample with regard to environmental quality, although the overall quality was high. However, scores on the Cognitive Support domain were rela-tively low when compared with the other domains. This is a worrying finding; our own results point to the importance of environmental support for cognitive frailty and other studies have indicated that res-idents of care facilities are vulnerable to poorly designed RCFs, where, for example a monotonous environment can cause confusion and anxiety among persons who have difficulties with orientation and navigation (Joseph, 2006). Previous research has demonstrated several environmental deficits in RCFs for people with cognitive frail-ties, e.g. poor signage and lack of access to safe outside spaces (Had-jri, Faith, & McManus, 2012). Thus, there is an urgent need for well-designed environments emphasizing features such as logical layout and reference points to promote a sense of safety and promote inde-pendence. Cognitive aspects should be considered early in the plan-ning and desigplan-ning process of care facilities to meet residents’ needs (Brawley, 2001; Day, Carreon, & Stump, 2000).

Evaluating existing RCFs after they have been occupied is also important to identify environmental features in need of change or adjustments (Barnes, 2002). This is likely to be even more important in the near future due to the increasing number of older people with cognitive impairment in need of moving to a RCFs (Seitz et al., 2010). Once built, care facilities are not easily changed. However, modification does not necessarily require comprehensive and expen-sive investment as minor environmental changes, such as colour cod-ing and clear walkcod-ing paths with landmarks, can offer valuable support for older persons with cognitive frailties (Geboy, 2009; Mar-quardt, 2011; MarMar-quardt, Bueter, & Motzek, 2014).

4.3

|

Considering normalness and homeliness in

care facilities

Our study found that the S-SCEAM Normalness domain was associ-ated with PCQ-P Everydayness: those RCFs with more environmen-tal elements that minimized institutional characteristics and contributed to a sense of homeliness had residents who perceived greater opportunities to talk about things other than medical condi-tions, more aesthetic surroundings and experienced homely feelings despite being in an institution. This is an interesting association, given that PCQ-Everydayness was significant in the model of social well-being, whereas PCQ-Safety was not. Taken together, these

findings suggest that homeliness and familiarity in the environment have the potential to support at least one aspect of person-centred care and to contribute to residents’ well-being. Other studies have emphasized the importance of familiar belongings (van Hoof et al., 2016) and with a home-like non-institutional design for supporting older people with high levels of frail health (Joseph et al., 2015). For example, residents decorated their private rooms with photographs and furniture that represented personal histories (Lewinson, Robin-son-Dooley, & Grant, 2012) and this might be of particular impor-tance for those residents with dementia as they tend to recall distant past over recent past (Fleming, Fay, & Robinson, 2012).

In recent years, there has been a policy emphasis on providing small-scale environments that are perceived to be more homely (Rabig, 2009) and studies have indicated that smaller-scale units can result in positive outcomes for both residents (Joseph et al., 2015) and staff (Verbeek et al., 2014). These smaller units are separate entities but can be a part of larger buildings (Kane, Lum, Cutler, Degenholtz, & Yu, 2007). The value of home-like and small-scale environments is central in a person-centred care approach (Zeisel, 2013) and can contribute to older peoples’ autonomy, social interactions and privacy (Verbeek, Zwakhalen, van Rossum, Kempen, & Hamers, 2012; Zeisel, 2013).

4.4

|

Study strengths and limitations

This study had several strengths. Both the sample of a diverse range of RCFs and the use of a reliable and valid environmental assess-ment instruassess-ment allowed for a very detailed exploration of environ-mental variation in RCFs. This in turn provided the opportunity for a multilevel analysis of how different aspects of the environment are associated with different aspects of resident well-being. However, our study had some limitations. The sample size of 20 RCFs is smal-ler than would be optimal for a multilevel analysis and larger-scale studies are required to explore more complex models that contain more home-level factors and individual-level factors. Our cross-sec-tional design means that causal effects could not be evaluated. Although the facility managers were provided with clear instructions to select residents at random from those willing to participate and meeting our inclusions and exclusion criteria, it is possible that not all managers fulfilled their instructions; if so this may have caused a selection bias for our sample. However, relatively few residents per RCF were willing to participate and also met our inclusion and exclu-sion criteria and so even an attempt to consciously bias the study sample on the part of a facility manager would probably have had lit-tle effect given the restricted pool of residents from which selection could be made. Finally, as one of the subscales in the PCQ instru-ment was not reliable in this study, our study was limited to analys-ing only two dimensions of perceived person-centred care.

5

|

C O N C L U S I O N

This study demonstrates associations between the quality of cogni-tive support in the environment of RCFs and the social well-being of

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residents. By means of the detailed environmental assessment instrument S-SCEAM, we could obtain a deeper understanding of the associations between specific environmental domains and resi-dent well-being. Our results show the importance of high-quality environmental design of RCFs for supporting highly frail older peo-ple, who spend a majority of their time in the facility and for whom the environment can have a significant impact on well-being. Build-ing designers, architects and other professionals involved in plannBuild-ing and designing care facilities for older people therefore have a major responsibility to consider the impact of the physical environment on the well-being of residents and our study supports the idea that environmental elements that give cognitive support should be afforded a special focus. Knowledge and awareness about the bene-fits of cognitive support as an aspect of physical environments may also contribute to improvements regarding care practices in long-term care. There is a need for more well-designed studies using lar-ger samples that focuses on how environmental factors can affect well-being among older people with different levels of cognitive dis-abilities.

A C K N O W L E D G E M E N T

We are grateful to the older people who participated in this study and shared their perceptions.

C O N F L I C T O F I N T E R E S T

The authors declare that they have no conflicting interests.

A U T H O R C O N T R I B U T I O N S

All authors have agreed on the final version and meet at least one of the following criteria [recommended by the ICMJE (http://www. icmje.org/recommendations/)]:

substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data;

drafting the article or revising it critically for important intellectual content.

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How to cite this article: Nordin S, McKee K, Wijk H, Elf M. The association between the physical environment and the well-being of older people in residential care facilities: A multilevel analysis. J Adv Nurs. 2017;73:2942–2952.

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