Original Study

The Influence of Organizational Context on Best Practice Use by Care

Aides in Residential Long-Term Care Settings

Carole A. Estabrooks PhD a,*, Janet E. Squires PhD b,c, Leslie Hayduk PhD d,Debra Morgan PhD e, f, Greta G. Cummings PhD a, Liane Ginsburg PhD g,Norma Stewart PhD f, Katherine McGilton PhD h, Sung Hyun Kang MSc a,Peter G. Norton MD i

a Faculty of Nursing, University of Alberta, Edmonton, Alberta, CanadabOttawa Hospital Research Institute, Ottawa, Ontario, Canadac School of Nursing, Faculty of Health Sciences, University of Ottawa, Ottawa, Ontario, CanadadDepartment of Sociology, University of Alberta, Edmonton, Alberta, CanadaeCanadian Center for Health and Safety in Agriculture, University of Saskatchewan, Saskatoon, Saskatchewan, CanadafCollege of Nursing, University of Saskatchewan, Saskatoon, Saskatchewan, Canadag School of Health Policy and Management, York University, Toronto, Ontario, Canadah Toronto Rehabilitation Institute-University Health Network, Toronto, Ontario, Canadai Faculty of Medicine, University of Calgary, Calgary, Alberta, Canada

Keywords:

Research use

best practice

aide

nursing home

context

Alberta Context Tool

TREC

a b s t r a c t

Objective: This study assessed individual and organizational context (work environment) factors that influ-

ence use of best practices by care aides (nursing assistants) in nursing homes. Little scientific attention has

been focused on understanding best practice use in nursing homes and almost none on care aides.

Setting and participants: A total of 1262 care aides in 25 nursing homes in the 3 Canadian prairie prov-

inces. Care aides are unregulated workers who provide 80% of direct care to residents in Canadian

nursing homes.

Method: We used hierarchical linear modeling to (1) assess the amount of variance in use of best

practices, as reported by care aides, that could be attributed to individual or organizational factors, and

(2) identify predictors of best practices use by care aides.

Results: At the individual level, statistically significant predictors of instrumental use of best practices

included sex, age, shift worked, job efficacy, and belief suspension. At the unit level, significant predictors

were social capital, organizational slack (staffing and time), number of informal interactions, and unit

type. At the facility level, ownership model and province were significant. Significant predictors of

conceptual use of best practices at the individual level included English as a first language, job efficacy,

belief suspension, intent to use research, adequate knowledge, and number of information sources used.

At the unit level, significant predictors were evaluation (feedback mechanisms), structural resources, and

organizational slack (time). At the facility level, province was significant. The R2 was 18.3% for instru-

mental use of best practices and 43.4% for conceptual use. Unit level factors added a substantial amount

of explained variance whereas facility level factors added relatively little explained variance.

Conclusions: Our study suggests that context plays an important role in care aides’ use of best practices in

nursing homes. Individual characteristics played a more prominent role than contextual factors in pre-

dicting conceptual use of best practices.

� 2015 AMDA e The Society for Post-Acute and Long-Term Care Medicine. This is an open access article

under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Funding for this study was provided by the Canadian Institutes of Health

Research (CIHR) (MOP #53107). Dr Estabrooks is supported by a Tier 1 CIHR Canada

Research Chair in Knowledge Translation. Dr Squires is supported by a CIHR new

Investigator award in Knowledge Translation. Dr Cummings is supported as a

Centennial Professor by the University of Alberta.

The authors declare no conflicts of interest.

* Address correspondence to Carole A. Estabrooks, PhD, Faculty of Nursing, Level

3, Edmonton Clinic Health Academy, 11405 87 Avenue, University of Alberta,

Edmonton, Alberta, Canada T6G 1C9.

E-mail address: carole.estabrooks@ualberta.ca (C.A. Estabrooks).

JAMDA

journal homepage: www.jamda.com

http://dx.doi.org/10.1016/j.jamda.2015.03.009

1525-8610/� 2015 AMDA e The Society for Post-Acute and Long-Term Care Medicine. This is an open access article under the CC BY-NC-ND license (http://creativecommons.

org/licenses/by-nc-nd/4.0/).

JAMDA xxx (2015) e1ee10

Although evidence-based practice was recently identified as a

high priority for international research on nursing home care,1 we

currently see little attention to knowledge translation by the care

aides who provide essential daily care and quality of life care.2 Im-

plementation science has, to date, focused almost exclusively on

professional and regulated care providers (eg, physicians, nurses, al-

lied health professions) in hospital or primary care settings. A recent

review3 of the knowledge translation literature revealed an aston-

ishingly low proportion of studies related to care of older adults and

an even lower proportion relating to care of older adults in nursing

home settings. Knowledge translation studies of the nursing home

sector or care aides in nursing homes are, with a few notable ex-

ceptions,4,5 effectively nonexistent.

Residents living in nursing homes are older and admitted later in

the trajectories of their chronic diseases than in previous decades.

Most have a diagnosis of dementia. They are, therefore, more

dependent, more frail and vulnerable, and have more complex needs,

requiring more sophisticated care.6 They have significant needs for

better care at end of life7 and for consideration of what constitutes

quality of care and quality of life at the end of their lives. In Canada

80% of direct “point of care” services to nursing home residents is

provided by a group of unregulated workers4 with various titles

including personal support workers, care aides, and nursing assis-

tants. Few reports even describe the characteristics of these frontline

members of the care team, but care aides are essential elements of

any efforts to improve quality of care and quality of life in nursing

homes.8 Encouraging the use of best practices among these care

providers is, thus, pivotal. We located only 1 (qualitative) report of a

study that examined best practice use in care aides.4 This report

described challenges for care aides in using best practice that

included a context of uncertainty resulting from the complexities and

unanticipated features of dementia care work, lack of recognition and

struggles with being valued members of the team, and high needs for

constructive peer relationships. We located no studies that consid-

ered the effects of individual and organizational factors on care aides’

use of best practices in nursing homes settings.

The role and influence of organizational context (ie, the work envi-

ronment) in research implementation and quality improvement success

has been examined from multiple perspectives, including systematic

and general reviews on innovation and quality improvement,9e14 calls

for theory use in improvement science,15 framework and tool

development,16e22 theory development,23e25 and empirical studies

generally.26e32 Reviews by Denison,33 Dopson,34 Glisson,35 Hofstede,36

and Kaplan et al11 give starting views of the complex roles for context

in supporting or impeding best practice use and quality improvement

initiatives. The general consensus is that context has a significant role in

implementation success or failure. In the nursing home literature on

culture change, specific elements of nursing home culture are believed

to be associated with positive outcomes. Reports associate positive

outcomes with cultures that are more person-centered, less controlling,

and more relationship-based with lower rates of feeding tube

placement,37 lower restraint use,38 reduced antipsychotic prescribing,39

and higher reported and observed quality of care.40

We investigated the influence of individual and organization

context factors on use of best practices by care aides in nursing homes

in the Canadian prairie provinces. Our objectives were to (1) assess

the amount of variance in use of best practices, as reported by care

aides, that could be attributed to individual or organizational factors,

and (2) identify predictors of best practice use by care aides.

Methods

Our data are from the Translating Research in Elder Care (TREC)

program. TREC is a multilevel (provinces, regions, facilities, units

within facilities, care providers), longitudinal research program that

examines modifiable characteristics of organizational context in

nursing homes. TREC studies context in relation to knowledge trans-

lation (best practice use) by care providers and the impact of context

and knowledge translation on quality of care and staff well-being.41

Sampling

TREC is situated in nursing homes in the Canadian prairie prov-

inces of Alberta, Saskatchewan, and Manitoba. TREC phase 1

(2007e2012) selected 30 urban nursing homes using stratified (by

health care region, owner-operational model, and size) random

sampling; 6 additional nursing homes were a convenience sample

from 1 province. Our sample for analyses in this article was the 25

urban TREC nursing homes that had at least 2 resident care units.

Data Sources and Data Collection

We collected data (July 2009eJune 2010) from (1) the TREC Fa-

cility Survey (eg, number of beds); (2) the TREC Unit Survey (eg,

number of in-services provided); and (3) the TREC Provider survey

(care aides) (Figure 1). TREC Facility and Unit surveys were short

structured interviews with nursing home administrators (facility

data) and care managers (unit data). All care aides in participating

nursing homes who could be contacted were invited to complete the

Provider Survey if they (1) identified a unit where they had worked

for at least 3 months and were currently working, and (2) worked at

least 6 shifts per month on that unit. Research assistants adminis-

tered the survey to care aides with computer-assisted, structured

personal interviews.42,43 The TREC surveys measure organizational

context, best practice use, staff outcomes, and select individual fac-

tors believed to influence best practice use (Table 1).

MeasureseDependent Variables

We defined the instrumental use of best practices (instrumental

research use or IRU) as concrete application of best practiceswhere the

best practice knowledge is normally translated into a material and

useable form, such as a protocol. The best practice knowledge in this

case is used to make specific decisions or interventions.44 IRU is then,

direct and concrete use of research evidence in practice (eg, use of

guidelines)45 and was measured by a single item scored on a 5-point

frequency scale from 1 “never use” to 5 “almost always use.” The IRU

item has been shown to be acceptable.46,47 In conceptual use of best

practices (conceptual research use or CRU) the best practice knowledge

may change one’s thinking but not necessarily one’s particular action.

In this kind of use, the knowledge informs and enlightens the user.44

CRU is then the cognitive use of research; here research findings may

changeopinionormind-set about a specificpracticebutnotnecessarily

particular action.48CRUwasmeasuredwith 5 items scored on the same

scale as IRU.Overall CRU score is themeanof the5-itemscores. TheCRU

scale is acceptable, reliable and valid with care aides48,49; Cronbach’s

alpha for the CRU for this study was .870.

MeasureseIndependent Variables

Definitions of our independent variables, their measurement and

reliability are given in the Table 1. Independent variables are (1) TREC

Facility Survey: number of beds, presence of a clinical educator,

operation model, and province; (2) TREC Unit Survey: unit type (eg,

locked) and number of in-services offered on resident care; (3) TREC

(Provider) Survey: (a) 12 elements of context (leadership, culture,

evaluation, social capital, informal interactions, formal interactions,

structural resources, organizational slackestaff, organizational

C.A. Estabrooks et al. / JAMDA xxx (2015) e1ee10e2

slackespace, organizational slacketime [taken from the Alberta

Context Tool (ACT) described below], support for innovation,

adequate orientation), (b) 10 individual-level factors (bur-

nouteexhaustion, burnoutecynicism, burnouteefficacy, job satisfac-

tion, health status, attitude toward research, belief suspension, intent

to use research, information sources, adequate knowledge to do one’s

job); and (c) demographics (age, sex, education, English as first lan-

guage, shift worked, time worked on unit). All survey elements were

collected using personal structured interviews (facility and unit sur-

veys) or computer-assisted personal interviews for the care aide

surveys. Extensive quality monitoring was done during data collec-

tion.43 The ACT is embedded in the larger TREC survey and is a

validated instrument for the 10 modifiable elements of organizational

context noted above. Development and initial validation has been

previously reported.50 Validation of the nursing home version was

based on responses from 645 care aides.45 Results of confirmatory

factor analyses were consistent with the factor structure hypothe-

sized in the development of the ACT. For 8 ACT concepts, we found

significant correlations with instrumental research utilization; inter-

nal consistency reliability (Cronbach’s a � 0.70 for 8 of 10 concepts)

and acceptability e there was minimal missing data with 93.5% of the

healthcare aides providing complete data on all ACT items, and the

time to complete the ACT survey was below target with a mean of

11.08 minutes and a standard deviation of 2.93 minutes.45 Validation

of the ACT is ongoing.51 Of the 10 individual-level factors, bur-

nouteexhaustion, burnoutecynicism, and burnouteefficacy, are from

the well-used and validated Maslach Burnout Inventory.52e54 Health

status was measured using the Short Form 8 Health Survey (SF-8),55

based on the larger Short Form 36 Health Survey (SF-36) scale, which

has known reliability and validity. Attitude toward research (a 6-item

scale) and belief suspension (a 3-item scale) are scales we have

adapted (attitude56) or developed (belief suspension48,57,58) and have

used extensively.

Analytic Strategy

We used hierarchical linear modeling (HLM), as our data have a

natural hierarchical structure and responses of care aides within a

unit or facility may be correlated. We constructed models to examine

relationships between individual and organizational factors and care

aides’ IRU and CRU. First, we ran an unconditional (null) model for

each of IRU and CRU to fit an overall constant to the data and perform

the equivalent of a random-effects analysis of variance. Then, we ran

3 models for each of IRU and CRU. Model 1 was a 3-level model fitting

the overall constant plus individual-level (level 1) variables. It ex-

plains the variance in IRU and CRU among individuals. Model 2 was a

2-level model using individual and context (level 2) variables. Model

3 was a 3-level model using individual, context, and facility (level 3)

variables. For all models, we assumed a random effect for the inter-

cept and fixed effects for all level 1, 2, and 3 predictors. We compared

and assessed intraclass correlation to determine whether unit level

(context) and facility level variance were significantly different from

0. We assessed relative reduction in unit and facility level error

variance with respect to the null model (explained variance or R2)

using an ordinary least squares model corresponding to each HLM.

Ethics

We obtained ethics approvals for TREC from the University of

Alberta Health Research Ethics Board, University of Calgary Conjoint

Health Research Ethics Board, University of Saskatchewan Behavioral

Research Ethics Board, and University of Manitoba Fort Garry Campus

Research Ethics Board, and operational approvals from participating

organizations.

Results

Sample Characteristics

From July 2009 to June 2010, 1381 care aides completed the TREC

survey (approximately 70% of those eligible to participate). Here, we

report on 1282 of these care aides (Table 2) who worked in one of the

25 urban nursing homes that had more than 1 care unit.

Results of the HLM Analyses

Instrumental use of best practices

The null 3-level model indicates the majority of variance in IRU

may be accounted for by individual level factors. Model 3 for

IRU analyzed all predictors at 3 levels and identified 12 variables

as significant (5% level). Significant predictors at the (1) individual

level were age, sex, shift worked most often, job efficacy, and be-

lief suspension; (2) unit (context) level were social capital,

Level 3 – FacilityTREC facility survey

• Number of beds

• Presence of clinical educator

• Operation model

• Province

Level 2 – Care UnitTREC unit survey

• Unit type

• Number of in-services

Alberta Context Tool

(unit-level aggregated responses)

• Leadership

• Culture

• Evaluation

• Social Capital

• Informal Interactions

• Formal Interactions

• Structural Resources

• Organizational Slack–Staff

• Organizational Slack–Space

• Organizational Slack–Time

Additional context variables

(unit-level aggregated responses)

• Support for innovation

• Adequate orientation

TREC provider survey

Level 1 – Care ProviderProvider variables

• Burnout–exhaustion

• Burnout–cynicism

• Burnout–efficacy

• Job satisfaction

• Health status

• Attitude towards research

• Belief suspension

• Intent to use research

• Information sources

• Adequate knowledge to do job

• Age

• Sex

• Education

• English as first language

• Shift worked

• Time worked on unit

• Instrumental RU

• Conceptual RU

Level 1 – Care Provider

Independent

variables

Dependent

variables

Research utilization (best practice use)

Fig. 1. Schematic of Data Sources.

C.A. Estabrooks et al. / JAMDA xxx (2015) e1ee10 e3

Table 1

Descriptions of Independent Variables

Variable Definition Measurement Alpha

Level 1eIndividual

Age An individual’s age Asked to indicate age according to a category (eg, <20 years, 20e24, etc.) N/A

Sex An individual’s sex Asked for their sex: male or female N/A

Highest education Level of education obtained Asked if completed high school and healthcare aide certificate (both yes/no) N/A

English as first language English is a first language Asked if English was their first language (yes/no) N/A

Time worked on unit Total years worked on unit Asked for number of years and months worked on the unit N/A

Shift worked Shift worked most of the time Asked to indicate the shift they work most of the time: day, evening, or night N/A

MBI exhaustion A debilitating psychological condition brought about by

unrelieved work stress.

3 items/subscale; all scored on a 7-point Likert frequency scale (never to daily).

An overall score/subscale is derived by taking the mean of its items.

0.744

MBI cynicism 0.616

MBI efficacy 0.495

Job satisfaction An individual’s perception of whether they are “satisfied” in

their job (a healthcare aide in long-term care)

A single item scored on a 5-point Likert agreement scale (Strongly Disagree to

Strongly Agree)

N/A

SF-8 (Physical Health Status) An individual’s perception of their health status over past 4

weeks

8 items scored on 5- or 6-point scales depending on the item. Scoring is done

using a proprietary algorithm obtained when permission to use the scale is

granted to produce a summary mental and physical health score (0%e100%)

0.524

SF-8 (Mental Health Status) 0.413

Attitude toward research An individual’s perception of their attitude toward research

knowledge expressed along a continuum of negative to

positive

6 items scored on a 5-point Likert agreement scale (strongly disagree to strongly

agree). An overall score is derived by taking the mean of the 6 items

0.592

Belief suspensioneimplement An individual’s perception of the degree to which they are

able to suspend previously held beliefs to implement

research

3 items scored on a 5-point Likert frequency scale (never to almost always)

An overall belief suspension score is derived by taking the mean of the 3 items

0.777

Intent to use research An individual’s perception of their intent to use research in

the future

A single item scored on a 5-point Likert agreement scale (strongly disagree to

strongly agree)

N/A

Information sources An individual’s perception of the sources of knowledge they

used in practice on their last typical work day.

10 items scored on a 5-point Likert frequency scale (never to almost always)

Each item score is recoded as ‘0’ (not used) or ‘1’ (used). An overall score is

derived by taking a count of the 10 recoded scores

0.790

Adequate knowledge An individual’s perception of whether they have enough

information to do their job

A single item scored on a 5-point Likert agreement scale (strongly disagree to

strongly agree)

N/A

Level 2eUnit Context (as assessed by care aides)

ACT leadership The actions of formal leaders in an organization (unit) to

influence change and excellence in practice, items

generally reflect emotionally intelligent leadership

6 items scored on a 5-point Likert agreement scale (strongly disagree to strongly

agree). An overall score is derived by taking the mean of the 6 items

0.838

ACT culture The way that “we do things’ in our organizations and work

units, items generally reflect a supportive work culture

6 items scored on a 5-point Likert agreement scale (strongly disagree to strongly

agree). An overall score is derived by taking the mean of the 6 items

0.771

ACT evaluation The process of using data to assess group/team performance

and to achieve outcomes in organizations or units

6 items scored on a 5-point Likert agreement scale (strongly disagree to strongly

agree). An overall score is derived by taking the mean of the 6 items

0.796

ACT social capital The stock of active connections among people. These

connections are of 3 types: bonding, bridging, and linking

6 items scored on a 5-point Likert agreement scale (strongly disagree to strongly

agree). An overall score is derived by taking the mean of the 6 items

0.744

ACT organizational slackestaff Organizational slack refers to the cushion of actual or

potential resources which allows an organization (unit) to

adapt successfully to internal pressures for adjustments or

to external pressures for changes

3 items scored on a 5-point Likert agreement scale (strongly disagree to strongly

agree). An overall score is derived by taking the mean of the 3 items

0.927

ACT organizational slacketime 4 items scored on a 5-point Likert agreement scale (strongly disagree to strongly

agree). An overall score is derived by taking the mean of the 4 items

0.854

ACT organizational slackespace 2 items scored on a 5-point Likert agreement scale (strongly disagree to strongly

agree). An overall is derived by taking the mean of the 2 items

0.849

ACT formal interactions The formal exchanges that occur between individuals

working within an organization (unit) through scheduled

activities that can promote the transfer of knowledge

4 items scored on a 5-point Likert frequency scale (never to almost always with

a “not available” option). Recode each of the 4 item scores to ‘0’ (no

interaction) e 1’ (interaction). An overall score is derived by taking a count of

the 4 recoded items.

0.397

ACT informal interactions The informal exchanges that occur between individuals

working within an organization (unit) that can promote

the transfer of knowledge

9 items scored on a 5-point Likert frequency scale (never to almost always)

Recode each of the 9 item scores to ‘0’ (no interaction) e 1’ (interaction). An

overall score is derived by taking a count of the 9 recoded items

0.695

ACT structural resources The structural elements of an organization (unit) that

facilitate the ability to use knowledge

7 items scored on a 5-point Likert frequency scale (never to almost always)

Recode each of the 7 item scores to ‘0’ (no resource) e 1’ (resource). An overall

score is derived by taking a count of the 7 recoded items

0.773

Unit type* Type of care unit Asked to indicate if unit was general, secure, other N/A

C.A.Esta

brookset

al./JAMDAxxx

(2015

)e1

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e4

organizational slackestaff, organizational slacketime, number of

informal interactions, and unit type; and (3) facility level were

operational model and province. R2 (explained variance using ordi-

nary linear regression) was 7.5% for model 1 (constant þ individual

variables), 16.7% for model 2 (constant þ individual þ unit variables),

and 18.3% for model 3 (all levels of variables). Table 3.

Conceptual use of best practices

The null 3-level model indicates the majority of variance in CRU

may also be accounted for by individual level factors. Model 3 for CRU

identified 10 variables as significant (5% level). Significant predictors

at the (1) individual level e English as a first language, job efficacy,

belief suspension, intent to use research, number of information

sources used, and adequate knowledge; (2) unit (context) level e

evaluation (feedback processes on unit), organizational slacketime

and structural resources; and (3) facility level e province. R2 (ex-

plained variance) was 32.6% for model 1, 42.3% for model 2, and 43.4%

for model 3. Table 4.

Discussion

Individual characteristics explained a substantial proportion of

the variance in best practice use by care aides. This is consistent with

reports for other healthcare providers, particularly registered nur-

ses.31,32,59,60 Unit level context within nursing homes also influences

the use of best practices by care aides. This is consistent with a focus

on the resident care unit in nursing homes as an important focus of

quality of care improvement efforts.61,62 Our models explain much

higher levels of variance in CRU compared with IRU.

The Continued Relevance of Individual Characteristics

Individual care aide characteristics that predicted CRU differed

from characteristics predicting IRU. Job efficacy and belief suspension

predicted both IRU and CRU, but working day shift predicted only IRU.

Fewer practice change opportunities may emerge during the day

when residents are most active and requiring attention. Two vari-

ables, intent to use research and knowledge (access to information

sources, adequate knowledge), predict CRU but not IRU, which makes

intuitive sense. Further research may explain why having English as a

first language predicts CRU but not IRU.

We based our selection of individual variables on theoretical

considerations from the knowledge translation and organizational

literature,21,60,63,64 but did not use constructs from psychology

or decision science. We did not attempt to measure personality

types,65,66 learning styles,67 clinical decision-making,68,69 cognitive

styles of clinical reasoning70,71 or critical thinking.72,73 Some of these

constructs might contribute additionally to explaining care aides’

reports of IRU.

Slack time was a significant predictor for both CRU and IRU,

perhaps validating calls for increased staffing levels in nursing homes.

Important predictors for IRU were staffing and relationships/

interactions with peers and other health professionals, whereas

feedback and access to structural resources were important pre-

dictors for CRU. Thinking may be influenced by information re-

sources, but changing practice requires greater interpersonal links

and supports.

The Importance of Context

Several unit-level contextual variables significantly influence use of

best practices by care aides despite the null model reports of little

required unit-level variance. Social capital, organizational slack

(staffing and time), number of informal interactions, and unit type all

Support

innovation

Anindividual’sperceptionofsu

pport

fornew

ideasontheir

unit

Asingle

item

scoredona5-pointLikert

agreementscale

(strongly

disagreeto

strongly

agree)

N/A

Adequate

Orientation

Anindividual’sperceptionofwhethertheyhavehad

enoughorientationto

carryouttheirjobeffectively

and

safely.

Asingle

item

scoredona5-pointLikert

agreementscale

(strongly

disagreeto

strongly

agree)

N/A

In-servicesresidentcare*

In-servicesrelatedto

7differentresidentcare

areas

Askedifeach

in-servicewasofferedin

last

12month

(yes/no).Anoverall

in-servicesresidentcare

score

isderivedbytakingaco

untofallin-services(0

e7)

N/A

Level3eFacility

(NursingHome)

Bedsin

facility

zTotalnumberofbedsforresidents

infacility

Askedfortotalnumberoflong-term

care

andnon-long-term

care

bedsin

the

facility.Anoverallvaluefortotalbedsnumberis

derivedbysu

mminglong-

term

care

andnon-long-term

care

beds

N/A

Clinicaleducatory

Existence

ofaclinicaleducatorin

thehome

Askediftheyhaveeducatorin

thefacility

(yes/no)

N/A

Owner/operatormodelz

Ownership

andoperationmodelofthefacility

Private

forprofit,publicnotforprofit,orvoluntary

(eg,faith-based)notfor

profit

NA

Province

zProvince

inwhichthenursinghomeis

located

Alberta,Saskatchewan,orManitoba

N/A

MBI,Maslach

Burn

outInventory.

*From

theunitsu

rveyco

mpletedbycare

managers.

yFrom

thefacility

surveyco

mpletedbyfacility

administrators.

zSamplingstrata.

C.A. Estabrooks et al. / JAMDA xxx (2015) e1ee10 e5

influence IRU. Evaluation (feedbackmechanisms), structural resources,

and organizational slack (time) influence CRU. Both unit and facility

level context variables contribute to explained variance in small but

statistically significant ways, unit context variables more so for IRU.

Modifiable elements of context should, thus, be considered in

designing strategies to increase use of best practices by care aides. Our

results extend and clarify the qualitative observations of Janes et al4 on

the relevance of context to care aides’ use of research (best practices).

Reviews by Kaplan et al11 and others10,14 support the influence of

context on using research to improve quality of care in clinical settings.

Table 2

Descriptive Statistics for Dependent and Independent Variables (N ¼ 1262 Care Aides)

Variables Overall (N ¼ 1262) Alberta (N ¼ 751) Saskatchewan (N ¼ 175) Manitoba (N ¼ 336) P Value*

Dependent Variables

Use of best practices (mean, SD)

IRU 4.322 (0.796) 4.410 (0.721) 4.086 (0.976) 4.247 (0.822) <.001

CRU 3.871 (0.833) 3.963 (0.766) 3.346 (0.963) 3.936 (0.805) <.001

Independent Variables

Age (N, %)

<20 years 10 (0.8) 7 (0.9) 1 (0.6) 2 (0.6) .337

20e29 years 152 (12.0) 92 (12.3) 30 (17.1) 30 (8.9)

30e39 years 280 (22.2) 164 (21.8) 38 (21.7) 78 (23.2)

40e49 years 397 (31.5) 240 (32.0) 54 (30.9) 103 (30.7)

50e59 years 324 (25.7) 194 (25.8) 36 (20.6) 94 (28.0)

60e69 years 98 (7.8) 54 (7.2) 16 (9.1) 28 (8.3)

>70 years 1 (0.1) 0 (0.0) 0 (0.0) 1 (0.3)

Sex (N, %)

Female 1159 (91.9) 692 (92.1) 169 (96.6) 298 (89.0) .011

Highest education (N, %)

No high school 93 (7.4) 59 (7.9) 15 (8.6) 19 (5.7) <.001

High school but no healthcare aide certificate 181 (14.3) 117 (15.6) 41 (23.4) 23 (6.8)

Healthcare aide certificate alone or with high school 988 (78.3) 575 (76.6) 119 (68.0) 294 (87.5)

English as first language (N, %)

Yes 630 (50.0) 359 (47.8) 133 (76.4) 138 (41.1) <.001

Time worked on uniteyears (mean, SD) 4.745 (5.435) 4.337 (4.926) 6.244 (6.977) 4.875 (5.477) <.001

Shift worked (N, %)

Day shift 614 (48.7) 361 (48.1) 88 (50.3) 165 (49.1) .013

Evening shift 494 (39.1) 315 (41.9) 64 (36.6) 115 (34.2)

Night shift 154 (12.2) 75 (10.0) 23 (13.1) 56 (16.7)

MBI exhaustion (mean, SD) 2.501 (1.613) 2.361 (1.609) 2.815 (1.643) 2.652 (1.572) <.001

MBI cynicism (mean, SD) 2.204 (1.582) 2.024 (1.500) 2.557 (1.744) 2.428 (1.618) <.001

MBI efficacy (mean, SD) 5.224 (0.882) 5.303 (0.840) 4.942 (0.991) 5.196 (0.885) <.001

Job satisfaction (mean, SD) 4.090 (0.804) 4.132 (0.781) 3.811 (0.961) 4.143 (0.735) <.001

SF-8 (physical health status) (mean, SD) 49.386 (7.857) 49.624 (8.016) 47.780 (8.126) 49.699 (7.259) .014

SF-8 (mental health status) (mean, SD) 51.034 (8.651) 51.675 (8.717) 47.952 (8.570) 51.226 (8.216) <.001

Attitude toward research (mean, SD) 4.016 (0.489) 4.027 (0.474) 4.140 (0.489) 3.927 (0.506) <.001

Belief suspensioneimplement (mean, SD) 3.859 (0.832) 3.859 (0.846) 3.710 (0.795) 3.938 (0.810) .015

Intent to use research (mean, SD) 4.282 (0.680) 4.304 (0.654) 4.316 (0.743) 4.215 (0.702) .108

Information sources (mean, SD) 9.483 (0.989) 9.557 (0.843) 9.133 (1.351) 9.500 (1.035) <.001

Adequate knowledge (mean, SD) 4.139 (0.750) 4.216 (0.692) 3.920 (0.919) 4.080 (0.751) <.001

ACT leadership (mean, SD) 3.901 (0.627) 3.990 (0.566) 3.557 (0.747) 3.881 (0.626) <.001

ACT culture (mean, SD) 3.963 (0.545) 4.017 (0.506) 3.673 (0.648) 3.992 (0.525) <.001

ACT evaluation (mean, SD) 3.523 (0.663) 3.523 (0.668) 3.330 (0.718) 3.625 (0.595) <.001

ACT social capital (mean, SD) 4.023 (0.507) 4.089 (0.488) 3.938 (0.478) 3.915 (0.539) <.001

ACT informal interactions (mean, SD) 4.128 (1.545) 4.277 (1.539) 4.377 (1.417) 3.654 (1.528) <.001

ACT formal interactions (mean, SD) 1.336 (0.738) 1.343 (0.731) 1.297 (0.657) 1.342 (0.974) .752

ACT structural resources (mean, SD) 2.718 (1.582) 2.969 (1.579) 1.842 (1.447) 2.608 (1.480) <.001

ACT organizational slackestaff (mean, SD) 2.786 (1.192) 2.982 (1.165) 1.834 (0.897) 2.845 (1.152) <.001

ACT organizational slackespace (mean, SD) 3.326 (1.320) 3.316 (1.332) 2.880 (1.391) 3.584 (1.187) <.001

ACT organizational slacketime (mean, SD) 3.358 (0.878) 3.467 (0.897) 2.911 (0.693) 3.347 (0.847) <.001

Adequate orientation (mean, SD) 4.096 (0.817) 4.142 (0.806) 3.777 (0.984) 4.158 (0.701) <.001

Support for innovation (mean, SD) 3.678 (0.865) 3.799 (0.768) 3.198 (1.035) 3.654 (0.889) <.001

Operation model (N, %)

Public 372 (29.5) 338 (45.0) 34 (19.4) 0 (0.0) <.001

Private for profit 259 (20.5) 123 (16.4) 35 (20.0) 101 (30.1)

Voluntary 631 (50.0) 290 (38.6) 106 (60.6) 235 (69.9)

Unit type (N, %)

General long-term care 880 (69.7) 446 (59.4) 131 (74.9) 303 (90.2) <.001

Secure 382 (30.3) 305 (40.6) 44 (25.1) 33 (9.8)

Beds in facility (mean, SD) 150.88 (86.880) 177.00 (111.25) 107.80 (34.802) 138.62 (55.407) .302

Educator (N, %)

Yes 985 (78.1) 660 (87.9) 35 (20.0) 290 (86.3) <.001

Nurse practitioner (N, %)

Yes 160 (12.7) 29 (3.9) 0 (0.0) 131 (39.0) <.001

Access to allied services (mean, SD) 9.28 (2.04) 9.74 (2.13) 6.73 (1.56) 9.46 (1.17) <.001

In-services, resident care (mean, SD) 4.84 (2.11) 4.89 (2.22) 2.64 (1.26) 5.89 (1.11) <.001

MBI, Maslach Burnout Inventory; SD, standard deviation.

Statistically significant numbers are bolded.

*For categorical variables (age, sex, highest education, etc.), P values assessing provincial differences are from a c2 test, and for continuous variables (IRU, CRU, time on unit,

etc.), the P values are from ANOVA.

C.A. Estabrooks et al. / JAMDA xxx (2015) e1ee10e6

Our findings reveal the relevance of contextual factors to an additional,

large groupdunregulated care aides in nursing home settings.

More Explained Variation in CRU than IRU

The explained variance in our 2 outcome variables differed

remarkably; our overall model explained 43% of variance in CRU and

18% of variance in IRU. Several factors may recommend different sets

of explanatory variables for IRU than CRU. Many change theorists

argue that beliefs and knowledge (CRU) must change before practice

(IRU).74 As well, behavior change to increase IRU is more difficult than

changing thinking (CRU). Thus, the explanatory model we use here

may be less well suited to IRU than CRU. The specific variables to add

to the IRU model remains open to further investigation.

Table 3

HLM: Instrumental Use of Best Practices by Care Aides

Variable Null Model Model 1 Model 2 Model 3

Beta (SE) P Value Beta (SE) P Value Beta (SE) P Value Beta (SE) P Value

Constant 4.297 (0.043) <.0001 2.396 (0.437) <.0001 2.304 (0.445) <.0001 2.408 (0.447) <.0001

Age �0.038 (0.011) .001 �0.043 (0.011) .000 �0.042 (0.011) <.001

Sex (ref ¼ female) �0.176 (0.084) .049 �0.214 (0.081) .016 �0.217 (0.081) .015

Educationeno high school (ref ¼ healthcare

aide certificate alone)

�0.063 (0.088) .477 �0.105 (0.086) .231 �0.133 (0.086) .131

Educationehigh school but no healthcare

aide certificate

0.036 (0.066) .590 0.021 (0.065) .745 0.021 (0.065) .750

English as first language (ref ¼ English as

additional language)

�0.018 (0.053) .738 �0.011 (0.053) .842 �0.014 (0.053) .800

Shift workededay (ref ¼ night) �0.103 (0.074) .168 �0.144 (0.075) .061 �0.157 (0.075) .042

Shift workedeevening �0.124 (0.075) .105 �0.140 (0.075) .069 �0.147 (0.075) .056

Time worked on unit 0.006 (0.005) .202 0.003 (0.005) .488 0.005 (0.005) .291

MBI exhaustion 0.007 (0.019) .704 0.012 (0.019) .536 0.011 (0.019) .544

MBI cynicism �0.004 (0.018) .804 �0.014 (0.018) .446 �0.010 (0.018) .589

MBI efficacy (job efficacy) 0.101 (0.027) .000 0.065 (0.027) .015 0.067 (0.027) .013

Job satisfaction 0.046 (0.032) .150 0.007 (0.034) .832 0.006 (0.033) .854

SF-8 (physical health status) 0.000 (0.003) .956 0.001 (0.003) .798 0.001 (0.003) .811

SF-8 (mental health status) 0.001 (0.003) .829 �0.002 (0.003) .500 �0.003 (0.003) .392

Attitude toward research 0.086 (0.052) .097 0.053 (0.051) .295 0.055 (0.051) .280

Belief suspensioneimplement 0.121 (0.028) <.001 0.059 (0.028) .038 0.062 (0.028) .029

Intent to use research �0.017 (0.036) .632 �0.053 (0.035) .132 �0.051 (0.035) .144

Information sources 0.066 (0.024) .006 0.009 (0.025) .709 0.009 (0.025) .730

Adequate knowledge 0.025 (0.032) .446 �0.002 (0.035) .943 �0.003 (0.035) .926

ACT leadership 0.043 (0.042) .306 0.030 (0.043) .478

ACT culture �0.065 (0.058) .263 �0.065 (0.058) .260

ACT evaluation 0.034 (0.041) .406 0.046 (0.041) .263

ACT social capital 0.233 (0.055) <.0001 0.234 (0.055) <.001

ACT organizational slacke staff �0.059 (0.025) .019 �0.071 (0.025) .005

ACT organizational slacke space �0.018 (0.020) .378 �0.012 (0.019) .554

ACT organizational slacketime 0.125 (0.036) .000 0.135 (0.035) <.001

ACT formal interaction 0.041 (0.035) .242 0.051 (0.035) .140

ACT informal interaction 0.050 (0.017) .004 0.049 (0.017) .005

ACT structural resources 0.041 (0.019) .033 0.035 (0.019) .070

Unit type (ref ¼ general long-term care) 0.158 (0.056) .013 0.132 (0.053) .025

Support for innovation �0.014 (0.032) .668 �0.018 (0.032) .567

Adequate orientation 0.035 (0.033) .281 0.031 (0.032) .342

In-services, resident care 0.025 (0.015) .106 0.017 (0.014) .240

Beds in facility 0.000 (0.000) .455

Clinical educator (ref ¼ no) 0.044 (0.075) .568

Operation modele public (ref ¼ voluntary) �0.046 (0.064) .480

Operation modele private for profit �0.137 (0.063) .043

ProvinceeAlberta (ref ¼ Manitoba) 0.129 (0.074) .098

Province eSaskatchewan �0.221 (0.102) .043

Variance component-error terms (SE)

Individual level 0.601 (0.025)* 0.576 (0.025)* 0.529 (0.023)* 0.530 (0.023)*

Unit level 0.003 (0.008) 0.006 (0.010) 0.006 (0.010) 0.004 (0.007)

Facility level 0.031 (0.014)y 0.020 (0.011)* 0.010 (0.010) 0.000 (.)z

Total variance 0.636 0.601 0.546 0.533

Other Statistics (ICC and Deviance)

�2 log-likelihood 2975.7 2681.4 2517.8 2501.1

ICC (individual level)x 94.6% 95.7% 96.9% 99.3%

ICC (unit level) 0.5% 1.0% 1.1% 0.7%

ICC (facility level) 4.9% 3.3% 1.9% 0.0%

R2 using ordinary least squares

corresponding to HLM

N/A 0.075 0.167 0.183

ICC, intraclass correlation; MBI, Maslach Burnout Inventory; SE, standard error.

Statistically significant numbers are bolded.

*Significant at 1% level.ySignificant at 5% level.zZero bounded estimate which was reported as 0.0000.xICC (individual)¼ se

2/(su2þ ss

2þ se2), ICC (unit)¼ su

2/(su2þ ss

2þ se2), and ICC (facility)¼ ss

2/(su2þ ss

2þ se2), where se

2, su2, and ss

2 is individual, unit, and facility level

variance in error terms for 3-level model, respectively.

C.A. Estabrooks et al. / JAMDA xxx (2015) e1ee10 e7

Provincial Differences

Reports from Saskatchewan care aides differed significantly on

nearly all measures. Differences may be rooted in systematically

lower resource levels, policy or regulatory environments, or funda-

mentally different philosophical and value orientations of the nursing

home industry.

Conclusions

Our findings offer early insights into best practice patterns among

care aides in nursing homes, and substantively support the influence

of modifiable elements of organizational context on their best prac-

tice use. This work, thus, has important practical implications in using

research to improve resident quality of care. Modifiable contextual

Table 4

HLM: Conceptual Use of Best Practices by Care Aides

Variable Null Model Model 1 Model 2 Model 3

Beta (SE) P Value Beta (SE) P Value Beta (SE) P Value Beta (SE) P Value

Constant 3.801 (0.066) <.0001 �1.019 (0.388) .015 �0.990 (0.381) .016 �0.808 (0.383) .049

Age �0.002 (0.010) .839 �0.004 (0.009) .639 �0.003 (0.009) .769

Sex (ref ¼ female) �0.113 (0.074) .146 �0.129 (0.070) .079 �0.137 (0.069) .063

Educationeno high school (ref ¼ healthcare

aide certificate alone)

0.020 (0.078) .803 �0.005 (0.074) .949 �0.030 (0.074) .684

Educatione high school but no healthcare

aide certificate

0.014 (0.059) .817 0.000 (0.056) .994 0.010 (0.056) .865

English as first language (ref ¼ English as

additional language)

�0.233 (0.047) <.0001 �0.191 (0.046) .000 �0.185 (0.045) .001

Shift workede day (ref ¼ night) 0.074 (0.065) .266 0.014 (0.065) .828 0.004 (0.064) .957

Shift workede evening 0.065 (0.067) .334 0.008 (0.065) .897 0.007 (0.064) .912

Time worked on unit �0.007 (0.004) .076 �0.008 (0.004) .039 �0.006 (0.004) .131

MBI exhaustion 0.017 (0.017) .319 0.030 (0.016) .060 0.027 (0.016) .086

MBI cynicism 0.011 (0.016) .479 �0.005 (0.015) .732 �0.002 (0.015) .879

MBI efficacy (job efficacy) 0.119 (0.024) <.0001 0.071 (0.023) .002 0.069 (0.023) .003

Job satisfaction 0.122 (0.028) <.0001 0.026 (0.029) .369 0.029 (0.029) .310

SF-8 (physical health status) 0.000 (0.003) .963 0.001 (0.003) .823 0.001 (0.003) .828

SF-8 (mental health status) 0.006 (0.003) .020 0.003 (0.003) .240 0.002 (0.003) .410

Attitude toward research 0.036 (0.046) .437 0.038 (0.044) .385 0.040 (0.043) .355

Belief suspensioneimplement 0.214 (0.025) <.0001 0.158 (0.024) <.0001 0.156 (0.024) <.001

Intent to use research 0.120 (0.032) .000 0.082 (0.030) .007 0.091 (0.030) .003

Information sources 0.222 (0.021) <.0001 0.128 (0.022) <.0001 0.128 (0.021) <.001

Adequate knowledge �0.028 (0.029) .325 �0.062 (0.030) .039 �0.064 (0.030) .031

ACT leadership 0.088 (0.036) .016 0.072 (0.037) .051

ACT culture 0.066 (0.050) .186 0.062 (0.050) .212

ACT evaluation 0.197 (0.035) <.0001 0.206 (0.035) <.001

ACT social capital 0.041 (0.048) .393 0.048 (0.048) .317

ACT organizational slacke staff 0.005 (0.022) .805 �0.007 (0.022) .734

ACT organizational slackespace �0.003 (0.017) .871 0.002 (0.017) .913

ACT organizational slacketime 0.101 (0.030) .001 0.109 (0.030) <.001

ACT formal interaction 0.021 (0.030) .488 0.031 (0.030) .307

ACT Informal interaction 0.022 (0.015) .136 0.025 (0.015) .092

ACT structural resources 0.063 (0.017) .000 0.057 (0.017) .001

Unit type (ref ¼ general long-term care) 0.097 (0.047) .058 0.081 (0.044) .086

Support for innovation �0.016 (0.028) .557 �0.021 (0.028) .451

Adequate orientation 0.023 (0.028) .402 0.015 (0.028) .595

In-services, resident care 0.012 (0.011) .265 �0.002 (0.012) .881

Beds in facility 0.000 (0.000) .392

Clinical educator (ref ¼ no) 0.001 (0.062) .993

Operation modele public (ref ¼ voluntary) �0.027 (0.053) .611

Operation modeleprivate for profit �0.003 (0.052) .959

ProvinceeAlberta (ref ¼ Manitoba) 0.042 (0.061) .505

ProvinceeSaskatchewan �0.280 (0.084) .004

Variance componenteerror terms (SE)

Individual level 0.603 (0.024)* 0.452 (0.020)* 0.394 (0.017)* 0.393 (0.017)*

Unit level 0.000 (.)y 0.006 (0.008) 0.008 (0.007) 0.000 (.)

Facility level 0.094 (0.030)* 0.014 (0.009) 0.000 (.) 0.000 (.)

Total variance 0.697 0.472 0.401 0.393

Other Statistics (ICC and Deviance)

�2 log-likelihood 2970.1 2388.8 2170.4 2150.5

ICC (individual level)z 86.6% 95.8% 98.1% 100.0%

ICC (unit level) 0.0% 1.3% 1.9% 0.0%

ICC (facility level) 13.4% 3.0% 0.0% 0.0%

R2 (using ordinary least squares

corresponding to HLM)xN/A 0.326 0.423 0.434

ICC, intraclass correlation; MBI, Maslach Burnout Inventory; SE, standard error.

Statistically significant numbers are bolded.

*Significant at 1% level.yZero bounded estimate which was reported as 0.0000.zICC (individual)¼ se

2/(su2þ ss

2þ se2), ICC (unit)¼ su

2/(su2þ ss

2þ se2), and ICC (facility)¼ ss

2/(su2þ ss

2þ se2), where se

2, su2, and ss

2 is individual, unit, and facility level

variance in error terms for 3-level model, respectively.xR2generated from OLS (Ordinary Least Square) model corresponding to each HLM.

C.A. Estabrooks et al. / JAMDA xxx (2015) e1ee10e8

factors (eg, formal interaction patterns such as care aides participa-

tion in shift reports, resident and family conferences) in the nursing

home environment could, if optimized, contribute positively to care

aides’ ability to use best practices.

Acknowledgments

The authors wish to thank the staff and administrators who

participated in the TREC study. The authors also acknowledge the

Translating Research in Elder Care (TREC) team for its contributions to

this study. At the time of this work the TREC Team included Carole A.

Estabrooks (PI), Investigators: Greta G. Cummings, Lesley Degner, Sue

Dopson, Heather Laschinger, Kathy McGilton, Verena Menec, Debra

Morgan, Peter Norton, Joanne Profetto-McGrath, Jo Rycroft-Malone,

Malcolm Smith, Norma Stewart, and Gary Teare. Decision-makers:

Caroline Clarke, Gretta Lynn Ell, Belle Gowriluk, Sue Neville, Cor-

inne Schalm, Donna Stelmachovich, Gina Trinidad, Juanita Tremeer,

and Luana Whitbread. Collaborators: David Hogan Chuck Humphrey,

Michael Leiter, Charles Mather. Special advisors: Judy Birdsell, Phyllis

Hempel (deceased), Jack Williams, and Dorothy Pringle (Chair, Sci-

entific Advisory Committee). The authors thank Dr Cathy McPhalen,

Ferenc Toth, and Dr Matthias Hoben for their assistance in prepara-

tion of this manuscript.

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