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Journal of Intellectual & Developmental Disability
ISSN: 1366-8250 (Print) 1469-9532 (Online) Journal homepage: http://www.tandfonline.com/loi/cjid20
Implementation of active support over time in
Australia
Christine Bigby , Emma Bould & Julie Beadle-Brown
To cite this article: Christine Bigby , Emma Bould & Julie Beadle-Brown (2017): Implementation
of active support over time in Australia, Journal of Intellectual & Developmental Disability, DOI:
10.3109/13668250.2017.1353681
To link to this article: http://dx.doi.org/10.3109/13668250.2017.1353681
© 2017 The Author(s). Published by Informa
UK Limited, trading as Taylor & Francis
Group
Published online: 24 Jul 2017.
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ORIGINAL ARTICLE
Implementation of active support over time in Australia
Christine Bigby
a
, Emma Bould
a
and Julie Beadle-Brown
a,b
a
Living with Disability Research Centre, La Trobe University, Melbourne, Australia;
b
Tizard Centre, University of Kent, Kent, UK
ABSTRACT
Background: Research indicates the value of active support in achieving good outcomes across a
number of quality of life domains for people with intellectual disabilities. However, implementation
is not easy, and little research has explored why. We aimed to identify some of the factors that
impact on implementation of active support in supported accommodation services.
Methods: Data on the quality of active support, staff training and practice leadership were collected
through staff questionnaires, observations and manager interviews, for between two and four years
across six organisations.
Results: Active support improved over time for more able people with intellectual disability, but not
for people with higher support needs. There was a weak positive correlation between active support
and (1) practice leadership scores, and (2) the percentage of staff reporting active support training.
Conclusions: It is important to recognise the influence of practice leadership and staff training on the
quality of support and ensure provision for these in funding schemes.
KEYWORDS
Implementation;
engagement; active support;
practice leadership; training;
supported accommodation
“Active support”is an enabling relationship between staff
or other carers and the people they support that provides
just the right amount of assistance to enable a person to
successfully participate in meaningful activities and social
relationships, at home and in the community (Mansell &
Beadle-Brown, 2012). It is a way of working that can apply
at all times and for all people with intellectual disability.
The evidence base spans four decades, involves at least
1400 people, uses different methodologies, in different
countries, in different settings and involves different
research teams and training approaches. Studies of effec-
tiveness have ranged from small-scale pre-post training
comparisons through to larger scale observational studies
(see Bigby & Beadle-Brown, 2016;Jones,Felce,Lowe,
Bowley, Pagler, Gallagher, et al., 2001; Jones, Felce,
Lowe, Bowley, Pagler, Strong, et al., 2001; Mansell & Bea-
dle-Brown, 2012).
The consistent finding is that when well implemented,
active support improves outcomes for people with intel-
lectual disabilities across a number of domains: time
spent engaged in meaningful activities and social inter-
actions (Beadle-Brown, Hutchinson, & Whelton, 2012;
Felce et al., 2000; Felce, de Kock, & Repp, 1986;Felce,
Lowe, & Jones, 2002; Felce & Perry, 1995;Jonesetal.,
1999;Mansell,1994; Mansell, Beadle-Brown, & Bigby,
2013; Mansell, Beadle-Brown, Macdonald, & Ashman,
2003; Mansell, Beadle-Brown, Whelton, Beckett, &
Hutchinson, 2008; Thompson, Robinson, Dietrich, Farris,
&Sinclair,1996), participation in household and commu-
nity-based activities (Jones, Felce, Lowe, Bowley, Pagler,
Gallagher, et al., 2001; Stancliffe, Harman, Toogood, &
McVilly, 2007), improved skills (Felce et al., 1986;Man-
sell, Ashman, Macdonald, & Beadle-Brown, 2002;Man-
sell, McGill, & Emerson, 2001), improved choice
(Beadle-Brown, Hutchinson, et al., 2012), reduced chal-
lenging behaviour (Beadle-Brown, Hutchinson, et al.,
2012; Jones et al., 2013; Koristsas, Iacono, Hamilton &
Leighton, 2008; Stancliffe, McVilly, Radler, Mountford,
& Tomaszewski, 2010), and mental health issues such as
depression (Stancliffe et al., 2007). In a 2012 study, Bea-
dle-Brown, Beecham, et al. (2012) confirmed earlier
research and demonstrated no differences in hours of
staff or overall costs of care in services where active sup-
port was stronger compared to those where it was weaker.
Finally, regression studies looking at predictors of engage-
ment in meaningful activities have identified two variables
as most important (and in most studies, the only) –the
level of ability of the individuals supported and assistance
from staff (Felce et al., 2000; Felce et al., 1986; Felce et al.,
2002;Felce & Perry, 1995;Jones,Felce,Lowe,Bowley,
Pagler, Strong, et al., 2001; Jones et al., 1999; Mansell,
1994;Manselletal.,2003; Mansell et al., 2008;Smith,
Felce, Jones, & Lowe, 2002; Thompson et al., 1996).
When active support is well implemented the effect of
© 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group
This is an Open Access article distributed under the terms of the Creative Commons Attribution-N onCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/
4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in
any way.
CONTACT Christine Bigby c.bigby@latrobe.edu.au
JOURNAL OF INTELLECTUAL & DEVELOPMENTAL DISABILITY, 2017
https://doi.org/10.3109/13668250.2017.1353681
adaptive ability on engagement reduces (Mansell & Bea-
dle-Brown, 2012, Chapter 3).
Implementation and maintenance of active support has
proved challenging (Mansell & Beadle-Brown, 2012). As
Mansell et al. (2008) reported factors such as (1) setting
characteristics (type of setting and size), (2) staffing
(e.g., staff ratio, staff qualifications and experiences, staff
turnover, and staff attitudes), (3) organisation hygiene
(e.g., staff job satisfaction, stress, role conflict, and role
clarity), and (4) general management (e.g., the autonomy
of managers or the systems available for organising sup-
port) have not been consistently found to predict good
support. Similar to Hastings (1995), Mansell et al.
(2008) noted that factors influencing staff practice were
likely to work in combination. For example, while training
staff in active support improves the quality of support and
outcomes for people supported this needs to happen by
combining classroom and hands-on training (Jones,
Felce, Lowe, Bowley, Pagler, Gallagher, et al., 2001;
Jones, Felce, Lowe, Bowley, Pagler, Strong, et al., 2001)
and in the context of ongoing management commitment
and support (McGill & Toogood, 1994).
Mansell et al. (2008) found that most structural, organ-
isational, and managerial factors were only weakly associ-
ated with good staff performance and that higher active
support scores were predicted by a range of individual
items in combination including higher resident adaptive
behaviour and having more experienced staff, who
received supervision more than annually. They went on
to suggest that some management practices may be
more important, particularly the role of front-line man-
agers as practice leaders. Beadle-Brown et al. (2014)and
Beadle-Brown, Bigby, and Bould (2015) explored the
role of practice leadership using both staff self-rated
measures and an observed measure of practice leadership,
finding significant relationships between the quality of
practice leadership available to staff and the level of active
support. This was especially so in the presence of good
general management (Beadle-Brown et al., 2014).
However, despite many other hypotheses about what
supports implementation and maintains good active
support, most notably the role of culture, there is very little
research exploring these (Bigby & Beadle-Brown, 2016).
The ongoing project from which the data in this paper
are drawn is attempting to fill that gap by exploring the
organisational factors that impact on implementation
and maintenance of active support. This large scale
study involves fourteen organisations in five Australian
states. It has two components: (1) a representative sample
of services selected every year for five years to allow sub-
stantial inferential analysis on data from over 500 people
with intellectual disabilities and (2) a longitudinal cohort
study following the same service users in 6 organisations
over at least a five-year period (seven years for some
organisations involved in the pilot study reported in Man-
sell et al. (2013).
This paper presents interim data on a sub-set of vari-
ables related to active support from the study’s longitudi-
nal element, expanding data presented for four of the
organisations in Mansell et al. (2013)bytwomoreyears
and introducing data from another two organisations. It
focuses primarily on engagement, active support, practice
leadership and staff training, and explores the changes
over time. The paper is primarily descriptive, aiming
to identify some of the implementation issues experienced
in supported accommodation services
1
and consider
some of the factors that will need to be explored in
future analysis of the data when the study is completed.
Method
Design
The study is longitudinal, following a cohort of services
from six organisations. The same measures are reported
for each time point. Data are available for four years
(2009–2012) for three organisations, three years (2009,
2010, 2012) for one organisation, and two years (2011–
2012) for two organisations. The study received ethical
approval from Human Research Ethics Committee of
La Trobe University.
Organisations
Details of the six organisations that all operated in one
state and were not-for-profit agencies are presented in
Table 1. As shown, size varied from 5 to 34 services and
organisations had been implementing active support for
different periods of time, some for longer than 10 years.
Services and participants
Depending on size, all or a sub-set of services were
included in the study providing at least one of the people
Table 1. Size of each organisation and number of years since
active support first implemented at time of Year 4 data
collection.
Total number of
supported
accommodation services
provided
Total number
of people
supported
Number of years
implementing active
support
Org 1 5 23 6
Org 2 16 33 12
Org 3 5 18 11
Org 4 34 159 10
Org 5 7 29 3
Org 6 9 53 4
2C. BIGBY ET AL.
supported and the staff that worked with that person
gave consent. Some additional services were included
in Year 3 for Organisations 2 and 3, and no data were
collected in Year 3 for Organisation 4. Table 2 presents
data on the number of services and people with intellec-
tual disabilities who participated in each year. The fluc-
tuation from year to year was due to service user
movement (people leaving and/or new people moving
into a service), lack of consent or illness; however, the
percentage of people consenting from the services
increased each year (range 76–97%).
Measures
Service user needs and characteristics
A measure of service user needs and characteristics was
obtained by questionnaires completed by a staff member
who knew the individual well. These questionnaires
included the short form of the Adaptive Behavior Scale
(SABS) Part 1 (Hatton et al., 2001), the Aberrant Behavior
Checklist (ABC) (Aman, Burrow, & Wolford, 1995), and
the Quality of Social Impairment question from the Sche-
dule of Handicaps Behaviours and Skills (HBS) (Wing &
Gould, 1978). Additional questions related to gender, date
of birth, and other disabilities present. The reliability and
validity of the ABS (from which the SABS was drawn),
ABC, and the HBS have been studied and reported as
acceptable by their authors. The full-scale score for Part
1 of the Adaptive Behaviour Scale which is presented
was estimated from the SABS using the formula provided
in Hatton et al. (2001). For some analyses, participants
were categorised according to their ABS score (151 and
above, and below 151) to compare those with more severe
disabilities to those with less severe disabilities. This rela-
tively crude measure has been shown to differentiate
samples in terms of outcomes and the quality of support
(Beadle-Brown et al., 2015; Mansell et al., 2013).
Engagement in meaningful activity
The momentary time-sampling measure of engagement in
meaningful activities and relationships (EMAC-R) (Man-
sell & Beadle-Brown, 2005) was the main measure of ser-
vice user outcomes. Observers coded both social and non-
social activities (self-care, household or work, audio-visual
or leisure), assistance and other contact from staff, contact
from other service users, and challenging behaviour (self-
stimulatory, self-injurious, aggressive or destructive, or
other challenging behaviour). This measure is described
in detail in other papers (Beadle-Brown, Hutchinson,
et al., 2012; Mansell et al., 2013). Observations were car-
ried out in each house usually over a two-hour period
between 1600 hours and 1800 hours. A one-minute inter-
val was used and each service user was observed for five
minutes in rotation.
Observations were collected by a team of seven obser-
vers in Year 1, and two of those observers completed the
observations in Year 2. In Year 3, all observations were con-
ducted by just one observer (second author) and in Year 4,
there was a team of three observers. All observers were
trained by the authors. Across the four years, 54% of obser-
vations were completed by one person (second author).
Observers were given classroom-based training that
included observer discipline, the nature of engagement,
and practice observations using video clips that illus-
trated observational categories. They also conducted in
situ observations with the second or third author, during
which reliability was checked after an hour and issues
discussed. A further hour of observation was conducted
together, reliability checked and the ASM completed.
Reliability of the ASM was checked and issues discussed.
Each observer did at least one further buddy observation
with the main observer (second author).
Inter-observer reliability was used to ascertain the
degree of agreement among the seven observers involved
in Year 1 (and the two observers in Year 2). Reliability
data were available for 1120 minutes across the observers
and the mean kappa was 0.58 (range 0.11–0.82). As dis-
cussed in detail in Mansell et al. (2013), agreement was
low for unclear non-social activity and assistance.
Unclear non-social activity was only observed for 12
people, and when excluded from the analysis the kappa
was 0.68. Assistance occurred 10% or less of the time
for 91% of the sample (non-occurrence reliability was
95%), and when the kappa analysis was repeated for
the 240 minutes of reliability data available for the two
main observers there was 100% agreement that no
unclear non-social activity and assistance occurred. Fur-
thermore, contact was only recorded three times by
either observer, and the kappa across the five remaining
categories was 0.83 (range 0.78–0.92).
In Year 3 all observations were conducted by the
second author, and inter-observer reliability on the
EMAC-R was checked with the third author before
data collection began and shown to be high (kappa
0.81 over 88 minutes of observations). Across the team
of three observers in Year 4, inter-observer reliability
data were available for 720 minutes. Mean kappa value
across the 13 categories which were coded as happening
at least once was 0.92 (range 0.77–1.00).
Quality of active support
The Active Support Measure (ASM) has been described in
detail in other published papers (Beadle-Brown,
JOURNAL OF INTELLECTUAL & DEVELOPMENTAL DISABILITY 3
Hutchinson, et al., 2012;Manselletal.,2013). It was used
to determine the quality of active support provided by
staff, and completed at the end of the 2-hour observation
period for each service user observed. The ASM includes
15 items focusing on the opportunities for involvement
and the skills with which staff provided and supported
those opportunities. Each item is rated on a scale of 0
(poor, inconsistent support or performance) to 3 (good,
consistent support or performance). The maximum poss-
ible score is 45 and for each person a percentage of the
maximum was calculated. Percentage scores for each indi-
vidual were categorised according to Mansell and Beadle-
Brown (2012, Chapter 3), into strong, consistent
implementation of active support (more than 66.66%),
mixed implementation (between 33.33% and 66.66%),
and weak implementation (less than 33.33%). Percentage
agreement across the 15 items of the measure for the 7
Year 1 observers (and the 2 Year 2 observers) was 60%
on average (range 29–98%, n= 24). Kappa was on average
0.32 (discussed in detail in Mansell et al., 2013). Reliability
on the ASM was not conducted in Year 3 due to all obser-
vations being conducted by one observer. Across the team
of three observers in Year 4, percentage observer agree-
ment was 84% on average (range 73–100%, n= 15).
Kappa was on average 0.61 (range 0.21–0.80).
Staff training in active support
Support workers were asked to complete an adapted ver-
sion of the Staff Experiences and Satisfaction Question-
naire (Beadle-Brown, Gifford, & Mansell, 2005). This
includes questions on staff characteristics, training, and
experience as well as knowledge of active support, per-
son-centred planning, whether staff receive practice lea-
dership, involvement of senior management and other
motivational structures. In this paper, we present the
results from the training section of the staff questionnaire.
Practice leadership
The Observed Measure of Practice Leadership, which has
been shown to be a reliable and valid measure with good
internal consistency, inter-rater reliability, and construct
validity (see Beadle-Brown et al., 2015), was used to col-
lect the data on the quality of practice leadership provided
by front-line managers. Observers rated five core aspects
of practice leadership: (1) Overall focus on the quality of
life (QoL) of the people supported by the service; (2)
Allocating and organising staff to provide the support
people need to maximise their QoL; (3) Coaching, observ-
ing, modelling and giving feedback to staff about the
quality of their support; (4) Reviewing performance
with individual staff in supervision; and (5) Reviewing
team performance in team meetings. Ratings were made
on a five-point rating scale (with 1 being no or almost
no evidence of the element being in place to 5 being excel-
lent –could not really improve on this element), on the
basis of information from: (1) unstructured observations
of the front-line manager during the visit to the service;
(2) semi-structured interviews with the front-line man-
ager and where possible, with direct support staff, and
(3) review of paperwork associated with practice leader-
ship such as staff allocation and minutes of team meet-
ings. Interviews with front-line managers lasted
approximately one hour, all interviews were digitally
recorded, and detailed field notes were written as soon
as possible after each visit to assist in rating the five
items. Data for the practice leadership measure were col-
lected by four observers who had been trained by one of
the authors and conducted at least two visits with one
other trained observer before collecting data alone.
Procedure
Once consent had been gained, the service user question-
naires were sent to each service with requests for a staff
member who knew the individual well to complete and
return to the research team using the pre-paid envelopes
provided. The staff questionnaires were mailed to super-
visory and managerial staff associated with each house
who were asked to give a copy to each consenting mem-
ber of staff, along with a pre-paid envelope so that staff
could post them back to the research team. A researcher
visited each service to conduct the observations using the
Table 2. Number of services included and number of people consenting to participate in each organisation at each time point, plus
average observed staff: client ratio at each time point for each organisation.
Average observed staff:
client ratio
Yr 1 Yr 2 Yr 3 Yr 4
No. of service
users
No. of
services
No. of service
users
No. of
services
No. of service
users
No. of
services
No. of service
users
No. of
services
Org 1 .51 20 5 19 5 20 5 19 5
Org 2 .52 12 3 15 6 17 7 18 7
Org 3 .52 12 4 12 4 17 5 18 5
Org 4 .47 29 6 35 10 ––34 8
Org 5 .70 ––––25 7 24 7
Org 6 .39 ––––31 8 33 8
ALL .52 70 19 81 25 110 32 146 41
4C. BIGBY ET AL.
EMAC-R measure at the end of which the ASM was
completed for each person. The observation to complete
the EMAC-R and the observed measure of practice lea-
dership were carried out on different days and by differ-
ent researchers. Thus, each service had two visits
(exception being when a practice leader worked across
more than one service, and only one interview and obser-
vation were conducted in one of those services), usually
within two months of each other although in four ser-
vices, circumstances meant there was a longer gap of
three to four months.
Analysis
Descriptive statistics are presented for the overall sample
and for each organisation as a whole for each time point.
In addition, correlation analysis was used to look at the
relationship between level of adaptive behaviour and
the level of engagement and quality of active support.
For those individuals who participated at more than one
time point, exploratory analysis examined changes over
time using Wilcoxon Signed ranks tests for two time
point comparisons and effect sizes (r)werecalculated
using the methodology of Fritz, Morris, and Richler
(2012), by converting zinto rusing the formula r=the
absolute value of
y
z4
N−Ties
√. Friedman Analysis of
Variance was used for comparison of more than two
time points. Indicative differences between organisations
were explored using Mann–Whitney Utests, and effect
sizes calculated using the Fritz et al. (2012)methodology.
Univariate linear regression was used to explore the impact
of level of ability on both engagement and on the quality of
active support. Bonferroni adjustments were used in order
to reduce the risk of Type II errors and significance
reported at p< .001 (α
altered
= .05 ÷ 50).
Results
Description of participants and settings
Tables 3–6included service users’characteristics by year
and organisation. As can be seen, they had a varied
profile of needs and characteristics, with some variation
across years due to service user movement. On average
the sample was relatively able compared to other studies
of active support (Mansell et al., 2013), and just over half
the sample (53%) fell below ABS 151.
As Table 6 shows, all the organisations apart from
Organisation 3 included at least some people with severe
or profound disabilities. Compared to other organis-
ations, the sample of people from Organisation 3 was
more able and did not include any one with a physical
disability, whereas the sample from Organisation 5
only included people with severe or profound intellectual
disabilities and complex needs all of whom had a phys-
ical disability and severe communication impairments
(see Table 5).
QoL –engagement
Observational data were available for 70 people in Year 1,
81 in Year 2, 110 in Year 3, and 146 in Year 4.
Figure 1 shows the levels of any engagement, social
activity, non-social activity and challenging behaviour
across the whole sample. Table 6 presents the overall
levels of engagement for each organisation, along with
the levels of adaptive behaviour, at each time point, as
it is important that the engagement data are interpreted
with ability levels in mind. The dip in engagement over-
all in Years 3 and 4 is accounted for by the addition of
Organisation 5, which supports people with profound
and multiple disabilities and had only started to
implement active support two years previously. If we
remove Organisation 5, then engagement across the
other five organisations increased to 56% and 53% in
Years 3 and 4, respectively, and average ABS score
increases to above 155.
Table 7 compares the overall level of engagement in
Year 4 for each organisation to the figures reported in
Mansell and Beadle-Brown (2012) taking into account
average ability level of the group. As Table 7 shows
engagement levels, for most organisations, fell below
those that have been shown to be possible with good
implementation of active support. Notably, however,
some organisations have at least one person at the top
end of the range for engagement. Engagement levels did
not change significantly for the 26 people who were
included at all 4 time points (X
2
(3) = 3.957, p= .266),
neither did they change for the 87 people included at
both Years 3 and 4 (z=1.424,p=.154,r=.15).
The absence of change is not necessarily a negative
finding, because for some people the time spent in
more complex activities increased which may indicate
staff were providing more support to ensure success
resulting in less engagement overall. Some people spent
Table 3. Participant mean age (with range) for the sample in
each year and each organisation.
Age (mean and range)
Org 1 Org 2 Org 3 Org 4 Org 5 Org 6 All
Yr 1 39
(27–59)
39
(23–54)
44
(26–63)
36
(22–60)
––39
(22–63)
Yr 2 40
(30–61)
41
(22–59)
44
(29–64)
37
(20–61)
––40
(20–64)
Yr 3 39
(16–62)
41
(24–60)
42
(29–65)
–27
(18–42)
52
(31–76)
41
(16–76)
Yr 4 40
(17–63)
42
(25–61)
45
(30–66)
40
(24–62)
28
(19–43)
52
(32–77)
42
(17–77)
JOURNAL OF INTELLECTUAL & DEVELOPMENTAL DISABILITY 5
less time, for example, watching TV or simple self-care
activities such as eating and drinking and more time
doing household activities. For example, the engagement
level for one individual in Organisation 5 (with an ABS
score of 31), decreased from 71% to 57%, reflecting a
reduction from 69% to 11% time in audio-visual activi-
ties, and increased from 0% to 34% in more active leisure
activities, 0% to 3% in simple household or work activi-
ties and 0% to 3% in activities using gas or electrical
equipment.
Despite the overall decreases in engagement, 15
people were spending more time in household or work
activities, 5 of whom were also spending at least slightly
more time in activities involving gas or electrical equip-
ment. However, this was by no means the case for every-
one in the sample. For example, seven of those who
showed overall decreases in engagement only experi-
enced increased time spent in audio-visual activities.
As most previous studies have found, there was a sig-
nificant correlation between the level of adaptive behav-
iour and the level of engagement overall for Years 2 (ρ
= .533, n= 72, p< .001), 3 (ρ= .722, n= 102, p< .001)
and 4 (ρ= .765, n= 130, p< .001). According to Cohen’s
(1988) guidelines for interpreting coefficients (see Dunst
& Hamby, 2012; Lipsey & Wilson, 2001), these are all
large effect sizes, and show an increase over time. Further
exploration of Year 1 data showed that some of those
who were more able were experiencing almost no
engagement (often staff were stopping them getting
engaged) and a very small number of those with more
severe disabilities were very engaged.
Quality of support
In terms of the amount of facilitative support provided
by staff, over half (52%) of the sample in Year 4 received
no assistance at all to be engaged and only 9% received
assistance 14% or more of the time –the benchmark
for good support used in Mansell and Beadle-Brown
(2012).
The quality of support, measured by the ASM, is as
important, if not more so, than the amount of assistance
received. As can be seen from Figure 2 and Table 8, active
support levels had improved in all but one organisation
(Organisation 2). Although there was no change over
time for the 25 people who were involved in all four
years (X
2
(3) = 4.616, p= .202), Organisation 1 showed
a non-significant increase in active support from Year
2 onwards (X
2
= 13.38, p= .004) and Organisations 1,
5, and 6 showed non-significant increases between
Years 3 and 4 (z= 3.127, p= .002; z= 2.979, p= .003, z
= 2.015, p= .044, respectively). The level of active sup-
port had deteriorated over time for Organisation 2, but
due to the small sample (only five people were included
at all four time points) this change was not significant
(X
2
(3) = 11.449, p= .01). As Table 9 shows, by Year 4
half of the overall sample were receiving good active sup-
port (>66.6% score on ASM), but this was mainly
accounted for by two organisations (Organisations 1
and 6) (see Table 9).
Unlike other studies, active support was not the vari-
able most highly correlated with engagement. The partial
correlation between ASM and engagement (controlling
for adaptive behaviour) in this sample in Year 4 was
Table 4. Participant characteristics: score on aberrant behaviour checklist (mean and range) and gender distribution in each year and by
organisation.
ABC score (mean and range) Percentage male
Org 1 Org 2 Org 3 Org 4 Org 5 Org 6 ALL Org 1 Org 2 Org 3 Org 4 Org 5 Org 6 ALL
Yr 1 41
(0–93)
14
(0–47)
28
(0–64)
45
(4–103)
––35
(0–103)
40% 42% 82% 69% ––58%
Yr 2 25
(5–92)
19
(4–59)
30
(0–65)
38
(4–102)
––31
(0–102)
37% 33% 75% 57% ––51%
Yr 3 33
(3–87)
27
(2–110)
21
(0–81)
–17
(0–77)
18
(0–57)
22
(0–110)
25% 29% 59% –68% 39% 45%
Yr 4 31
(3–87)
27
(2–110)
22
(0–81)
34
(0–87)
15
(0–42)
18
(0–57)
25
(0–110)
26% 33% 56% 47% 67% 39% 45%
Table 5. Participant characteristics –physical disability and communication difficulties.
% with a physical impairment % non-verbal
Org 1 Org 2 Org 3 Org 4 Org 5 Org 6 All Org 1 Org 2 Org 3 Org 4 Org 5 Org 6 All
Yr 1 35% 42% 0% 23% ––26% 37% 0% 25% 12% ––19%
Yr 2 26% 40% 0% 27% ––27% 24% 21% 25% 34% ––28%
Yr 3 15% 41% 0% –100% 36% 42% 30% 24% 12% –100% 10% 36%
Yr 4 16% 39% 0% 29% 100% 30% 37% 26% 22% 11% 30% 100% 9% 33%
6C. BIGBY ET AL.
not significant (ρ= .137, n= 123, p= .64). Active support
drops out of the regression analysis, in favour of adaptive
behaviour (β= .77, t(124) = 13.405, p< .001), which
explains a significant proportion of variance (almost
60%) in engagement, R
2
= .59, F(1, 124) = 179.70, p
< .001. If we look just at the four organisations that
have been in the study the longest (β= .63, t(77) = 7.03,
p< .001), the proportion of the variance in engagement
explained by adaptive behaviour is slightly lower in
Year 4 at 40%, R
2
= .39, F(1, 77) = 49.38, p< .001.
Exploratory univariate regression analysis (using Year
4 data) found that ability level significantly predicted
active support scores, β= .60, t(124) = 8.32, p< .001.
Level of ability accounted for 35% of the variance in
the active support score, R
2
= .39, F(1, 124) = 69.15, p
< .001. This figure is slightly lower if we just include
Organisations 1–4, β= .55, t(73) = 5.65, p< .001, with
ability level accounting for 30% of the variance in the
active support score, R
2
= .30, F(1, 73) = 31.88, p< .001.
However, it is still higher than it was in Year 1, for the
same four organisations, β= .35, t(64) = 3.01, p< .004,
as ability level accounted for a non-significant pro-
portion of variance (only 12%) in the active support
score, R
2
= .12, F(1, 64) = 9.06, p< .004. This provides
further evidence that the quality of support has improved
over time for those who are more able but not necessarily
for those who need more skilled support to be engaged.
Practice leadership
Overall, practice leadership levels remained low over the
four years, and as shown in Table 10, changed little over
time. By Year 4, average scores across all organisations
remained in the mixed range (a score of 3 and below).
However, a very small number of people (nine across
Organisations 1, 2, and 4) were living in settings where
the practice leadership was rated good to excellent (a
score of 4 or 5).
Across all organisations in Year 4, there were significant
differences between scores ondifferent domains of practice
leadership (X
2
(4) = 137.24, p< .001). The strongest
domain was team meetings and the weakest coaching
and supervision. Average scores, however, mask some
variability between organisations. For example, across
most years Organisation 2 showed the strongest practice
leadership, being significantly better overall in Year 4
Table 6. Mean engagement (with range) in meaningful activities over time and by organisation with mean level of adaptive behaviour
(and range).
Org 1 Org 2 Org 3 Org 4 Org 5 Org 6 All
Yr 1 Adaptive behaviour score 142
(57–253)
175
(48–253)
167
(74–239)
170
(64–234)
––163
(48–253)
Engagement 58%
(4–100)
63%
(0–100)
59%
(17–95)
44%
(0–100)
53%
(0–100)
Yr 2 Adaptive behaviour score 149
(48–258)
155
(62–258)
163
(64–272)
155
(48–277)
––155
(48–277)
Engagement 56%
(0–100)
61%
(20–94)
55%
(5–100)
58%
(0–100)
58%
(0–100)
Yr 3 Adaptive behaviour score 140
(34–260)
157
(50–253)
170
(76–263)
–45
(22–79)
171
(57–239)
134
(22–263)
Engagement 52%
(0–94)
64%
(27–93)
55%
(12–98)
–16%
(0–73)
59%
(0–92)
48%
(0–98)
Yr 4 Adaptive behaviour score 145
(34–260)
160
(50–253)
172
(76–263)
147
(36–249)
45
(22–79)
174
(57–251)
141
(22–263)
Engagement 46%
(0–100)
59%
(13–93)
56%
(19–82)
50%
(8–96)
11%
(0–57)
57%
(3–95)
46%
(0–100)
Table 7. Percentage of time spent engaged compared to
benchmarked figures for appropriate ABS grouping presented
in Mansell and Beadle-Brown (2012, Chapter 3 Table 3.9).
Year 4
Mean ABS
in Year 4
Benchmarked mean percentage (and
maximum) when active support is
good
Org 1 46%
(0%–100%)
145
(34–260)
61% (95%)
Org 2 59%
(13%–93%)
160
(50–253)
69% (97%)
Org 3 56%
(19%–82%)
172
(76–263)
69% (97%)
Org 4 50%
(8%–96%)
147
(36–249)
69% (97%)
Org 5 11%
(0%–57%)
45
(22–79)
43% (60%)
Org 6 57%
(3%–95%)
174
(57–251)
69% (97%)
ALL 46%
(0%–100%)
141
(22–263)
61% (95%)
Table 8. Quality of support over time for whole sample.
Yr 1 Yr 2 Yr 3 Yr 4
Active support score
(mean and range)
Org 1 38
(16–71)
38
(18–67)
45
(13–92)
68
(33–92)
Org 2 89
(72–98)
73
(46–90)
67
(26–85)
53
(8–89)
Org 3 52
(8–93)
38
(18–59)
51
(13–87)
55
(38–75)
Org 4 33
(12–74)
37
(5–69)
–62
(23–85)
Org 5 ––28
(13–53)
42
(20–77)
Org 6 ––54
(7–82)
64
(17–87)
ALL 47
(8–98)
45
(5–90)
48
(7–92)
58
(8–92)
JOURNAL OF INTELLECTUAL & DEVELOPMENTAL DISABILITY 7
than four of the five organisations –Organisation 3 (U=
4.726, p= < .001, r= .78), Organisation 4 (U= 3.634, p
<.001, r= .50), Organisation 5 (U=4.277, p= < .001, r
= .66), and Organisation 6 (U= 5.141, p<.001, r=.72).
These are all large effect sizes (Cohen, 1988).
Organisation 2 showed a slight but non-significant
decline from Years 1 to 4 –which was most noticeable
for supervision (X
2
(3) = 9.390, p= .025) and overall
manager focus on QoL (X
2
(3) = 20.642, p< .01) –see
Table 10. Conversely, Organisation 1 showed a signifi-
cant increase from Years 1 to 4 (X
2
(3) = 22.56, p= .001),
with team meetings (X
2
(3) = 12.38, p= .006) and coach-
ing (X
2
(3) = 13.64, p= .003) both showing a non-signifi-
cant increase over time.
Training in active support
The response rate for staff questionnaires ranged from
23% to 71%. Table 11 presents the percentage of staff
who reported they had never had training in active sup-
port, the percentage who said their training was provided
by someone external to the organisation and the nature
of that training. Overall, there was a slight reduction in
the percentage of staff reporting they had never had
training in active support and this was repeated for
most organisations. The most dramatic change was
Organisation 1 which went from 63% to 8% of staff
not having had any training in active support, and a
slightly higher proportion by Year 4 who had received
both classroom and hands-on training. Contrastingly,
more staff in Organisation 2 reported no training in active
support in Year 4 than had been the case in Year 1, and
Organisation 4 showed a decrease in staff reporting no
training in active support. However, 90% of these staff
had only received classroom training in Year 4, and
none reported both classroom and hands-on training.
At the overall service user level, there was only a weak
positive correlation between ASM scores and the percen-
tage of staff in that service reporting active support train-
ing in Year 2 (ρ= .443, n= 65, p= .001), and no significant
relationships between ASM score and the percentage of
staff reporting both classroom and hands-on training or
the percentage of staff reporting only classroom training.
Finally, at a staff level, there were no significant associ-
ations between services coded as providing weak, mixed
or good active support and percentage of staff reporting
both classroom and hands-on training. However, for
most years the number of services in the good ASM
Figure 1. For overall sample, percentage of time (mean and range) spent in engagement overall, in social and non-social activity and in
self-stimulatory or other repetitive or inappropriate behaviour (does not include aggression, destruction or self-injurious behaviour
which were rarely observed).
Table 9. Percentage of people in each organisation receiving
good active support at each time point and across the whole
sample.
Yr 1 Yr 2 Yr 3 Yr 4
Org 1 11% 6% 17% 65%
Org 2 100% 60% 65% 47%
Org 3 38% 0% 40% 25%
Org 4 10% 3% –55%
Org 5 ––0% 17%
Org 6 ––38% 75%
ALL 30% 14% 30% 50%
8C. BIGBY ET AL.
group was low and very few staff had reported both class-
room and hands-on training. Even in Year 4 where 36 out
of 56 staff were working in services rated as having a good
ASM level, only 10 staff had reported both classroom and
hands-on training, although interestingly 7 of those were
in services with good ASM scores.
Discussion
Implementing and maintaining active support is
hard
This is the first longitudinal study of active support in
Australia and the key finding from this study was
essentially that active support is hard to maintain over
time. This supports earlier work by Mansell and Bea-
dle-Brown (2012) and others in the UK. Most organis-
ations showed at least some improvements in active
support over time but none, including those that had
been implementing active support for over 10 years,
were achieving the engagement levels commensurate
with those found to be possible in other research for
people of similar levels of ability (Mansell & Beadle-
Brown, 2012). The fragile nature of good support and
vagaries of sustaining it over time were illustrated by
Organisation 2, which had the highest levels of active
support at Year 1 but by Year 4 both quality of support
and engagement levels had fallen. In contrast, however,
Figure 2. Average (and range) scores on the ASM and the percentage of time (mean and range) receiving any contact, and assistance.
JOURNAL OF INTELLECTUAL & DEVELOPMENTAL DISABILITY 9
Organisation 1 showed steady but non-significant
increases from Years 2 to 4 which importantly, related
to people with both severe and less severe disabilities.
Despite these overall trends, levels of engagement and
active support varied substantially within organisations
and within services. Even in services where active sup-
port was generally higher, scores were still “mixed”indi-
cating that sometimes individuals received good support
and sometimes they did not. For the most part the varia-
bility was explained by ability levels of service users.
People who were more able were in general most
engaged and received more appropriate and consistent
support. For many of these people the appropriate
change needed was for staff to stand back and let them
do things themselves with minimal assistance, rather
than staff doing things for them. This finding provides
further support for the suggestion from an earlier
paper from this study (Mansell et al., 2013) and from
another study of those living independently with drop-
in support (Bigby, Bould, & Beadle-Brown, 2017), that
a significant sub-group of people in supported accom-
modation services do not require the level of support
provided in those services and have considerable poten-
tial to live more independently.
For people with higher support needs, providing more
intensive and skilled hand over hand assistance where
needed, appeared to be hardest for staff. A core area on
which organisations need to focus is ensuring staff pro-
vide just the right amount, and type of assistance to
each individual. The quality of the assistance is as impor-
tant, if not more so, than the amount of assistance
received. For instance, people with both severe and less
severe intellectual disability need assistance from staff
to be constructively occupied in more complex activities,
but despite observations occurring in the lead up to the
evening meal some people were not involved in meal
preparation and spent significant time in solitary activi-
ties that do not require staff support (i.e., audio-visual).
What might be needed for success
So, what might explain this variability and what is
needed for successful implementation and maintenance
of active support over time? This study explored just
two potential factors that have been highlighted in pre-
vious research –practice leadership and staff training.
Although analysis was limited by the small number of
services in each organisation, the findings indicate that
these variables will be important to include in the analy-
sis of the data set that will include a larger number of ser-
vices from more organisations when the study is
completed. With regards to practice leadership, there
appears to be a relationship between increasing practice
leadership and quality of support, as shown by Organis-
ation 1. The inverse was apparent for Organisation 2
where the slight decrease in practice leadership may at
least partly explain the decrease in active support.
In terms of training in active support, there also
appeared to be a tentative relationship between the pro-
portion of staff reporting training in active support and
the quality of support. For example, the capacity to
increase the quality of support over time demonstrated
by Organisation 1 may be linked to the increased levels
of staff reporting training over time. In contrast, the
increase in staff reporting no training in active support
in Organisation 2 could be linked to the decline in active
support. Although not many staff reported hands-on
training (which had been found to be important in
other studies such as Jones, Felce, Lowe, Bowley, Pagler,
Gallagher, et al., 2001; Jones, Felce, Lowe, Bowley, Pagler,
Strong, et al., 2001), those that did were more likely to be
working in services where active support was good. A
possible confounding factor is that not all organisations
directly labelled training as active support although
active support principles were included in training as
part of an overall practice framework. As such staff did
not always know that they had had training in “active
support”. This raises a number of issues worth exploring
further about the importance of explicitly naming active
support in training or practice frameworks. It is possible
Table 10. Observed practice leadership scores –mean and range
overall for all organisations and mean score on each domain for
organisations 1, 2, and 3.
Yr 1 Yr 2 Yr 3 Yr 4
Overall practice leadership (observed)
score Mean rating (range) median
Org 1 1.90
(1–3)
2.70
(2–3)
2.40
(1–3)
2.80
(1–4)
Org 2 3.70
(3–4)
2.93
(3–3)
3.48
(2–5)
3.37
(2–5)
Org 3 2.47
(2–3)
2.60
(1–4)
1.30
(1–2)
1.75
(1–3)
Org 4 2.58
(2–4)
3.00
(2–4)
–2.54
(1–5)
Org 5 ––2.40
(2–3)
2.45
(2–3)
Org 6 ––2.29
(1–4)
2.10
(1–3)
ALL 2.53
(1–4)
2.85
(1–4)
2.41
(1–5)
2.52
(1–5)
Managers overall focus on QoL Mean
rating (range) median
Org 1 2.25 3.00 2.00 3.00
Org 2 4.50 3.00 3.40 3.67
Org 3 2.33 2.33 1.25 2.00
Allocating staff Mean rating (range)
median
Org 1 1.50 2.25 2.50 3.00
Org 2 3.00 3.33 4.20 3.67
Org 3 2.67 3.00 1.25 1.75
Coaching staff Mean rating (range)
median
Org 1 1.50 2.75 2.50 2.60
Org 2 3.50 2.33 3.20 3.00
Org 3 2.33 2.67 1.00 1.25
Supervision Mean rating (range)
median
Org 1 2.00 2.75 2.25 1.60
Org 2 3.00 2.33 2.80 2.50
Org 3 2.00 2.33 1.25 1.25
Team meetings Mean rating (range)
median
Org 1 2.25 2.75 2.75 3.80
Org 2 4.50 3.67 3.80 4.00
Org 3 3.00 2.67 1.75 2.50
10 C. BIGBY ET AL.
that naming active support in this way is necessary for
staff to understand why active support is important
and to help them be motivated to do it, as well as ensur-
ing their verbal and practice competency in this way of
working. For these reasons, it may be worth including ques-
tions to staff about the components of the training rather
than just asking “did you have training in active support?”
The findings about staff training also illustrate the ongoing
managerial attention required to implement active support
and how basic elements such as staff training can fall away
overtime,eveninorganisations,suchasthoseinourstudy,
which have invested significant resources in active support
research and practice development.
Three additional rounds of data collection remain for
the larger study from which these data were drawn, pro-
viding opportunities for further information to be col-
lected on organisational structures and support for
practice leadership as well as the nature of training
staff receive. This will allow further exploration of the
roles practice leadership and training have in ensuring
staff can provide active support. Further analysis will
also include factors relating to organisational culture
using the Group Home Culture Scale developed as part
of this study (Humphreys, Bigby, Iacono, & Bould,
2016), and processes such as methods of monitoring
practice quality, and recruitment practices including
position descriptions, selection criteria, induction, as
well as awareness of active support at different organis-
ational levels.
One difficulty of identifying factors supporting
implementation and maintenance of active support
is that only small numbers of people consistently receive
good active support. An inherent risk of the larger
study from which these data were drawn, is that
numbers receiving good active support do not increase
substantially over time or good active support is limited
to one organisation or to people with lower support
needs. However, hopefully the trend of improvements
in active support for Organisations 5 and 6 in this sub-
set of the data will continue over the next three years.
The final data set will include over 500 people and if
only one-fifth of people are receiving good support this
would be sufficient to allow inferential analysis. In
addition, a larger data set including more services pro-
viding good active support will make it possible to
explore any changes in the nature and complexity of
activities in which people are engaged as active support
is implemented and maintained. For example, although
very able people might be engaged quite a lot of the
time, some evidence suggests much of this engagement
is simple, passive and relatively solitary. With good
implementation of active support over time, it might
be surmised that people would have more opportunities
to take part in activities that involve gas or electrical
equipment, in jobs and in volunteering and social activi-
ties in the community.
One of the limitations of this study is cluster effects.
Data for the most part have been analysed at the individ-
ual participant level which means that some of the staff
and service level variables are repeated within the data
set for people in the same service, thus creating a possible
clustering effect. Analysis of the final data set will allow
any findings at service user or staff level to be checked
at service level as many more services will be available
within the data set. We will also be able to look more clo-
sely at clustering by organisation or by type and nature of
accommodation setting, which will shed light on how
different approaches and models used in different organ-
isations might be affecting outcomes for those they
support.
Table 11. Reported staff training in active support.
% staff reporting never had
training in active support
% staff reporting training in active
support was delivered by a trainer
external to the organisation
% staff reporting BOTH classroom
based and hands-on training in
active support
% staff reporting only classroom-
based training in active support
Yr 1 Yr 2 Yr 3 Yr 4 Yr 1 Yr 2 Yr 3 Yr 4 Yr 1 Yr 2 Yr 3 Yr 4 Yr 1 Yr 2 Yr 3 Yr 4
Org 1 63% 53% 53% 8% 43% 80% 50% 33% 0% 0% 0% 33% 83% 75% 67% 67%
n=24 n=19 n=17 n=12 n=7 n=5 n=6 n=9 n=6 n=4 n=6 n=6 n=6 n=4 n=6 n=6
Org 2 7% 0% 14% 29% 10% 13% 7% 9% 29% 0% 8% 27% 43% 57% 85% 73%
n=15 n=10 n=21 n=21 n=10 n=8 n=15 n=11 n=7 n=7 n=13 n=11 n=7 n=7 n=13 n=11
Org 3
a
14% 40% 0% 17% ––––––––––––
n=7 n=5 n=4 n=6
Org 4 25% 24% –7% 53% 41% –15% 13% 5% –0% 81% 80% –90%
n=28 n=34 n=14 n=17 n=22 n=13 n=16 n=20 n=10 n=16 n=20 n=10
Org 5 ––33% 31% ––42% 7% ––10% 25% ––60% 50%
n=21 n=26 n=12 n=14 n=10 n=16 n=10 n=16
Org 6 ––6% 14% ––17% 0% ––8% 0% ––83% 89%
n=16 n=14 n=12 n=7 n=12 n=9 n=12 n=9
ALL 32% 29% 25% 20% 46% 38% 29% 16% 12% 3% 7% 18% 70% 74% 70% 67%
n=74 n=68 n=79 n=93 n=3
9n=37 n=49 n=58 n=33 n=31 n=44 n=55 n=33 n=31 n=44 n=55
a
NB return rate for Org3 was very low across (max. 7 in any one year), with 3–4 completing the follow-on questions about training. As such the percentages have
been omitted from the table percentages based on such low numbers would be misleading.
JOURNAL OF INTELLECTUAL & DEVELOPMENTAL DISABILITY 11
Conclusion
The findings from this study confirm the difficulties
highlighted in previous work on implementing and
maintaining active support, despite the evidence of the
benefits to service users’QoL of this approach. The
role of hands-on training and practice leadership con-
tinue to emerge as important but also not, it appears,
easy to put into place. The importance of these factors
to provision of quality support will need to be carefully
factored into future funding schemes for service users
of shared supported accommodation. Particularly for
service users with higher support needs who rely on a
team of staff available round the clock. These factors
do not lend themselves easily to individualised solutions
but rather need to be embedded within organisational
processes and structures. Further research needs to
explore the models that work best in different settings
to make these important facilitative factors a reality.
Finally, the findings illustrate the need for continuing
attention to the quality of staff practice given its precar-
ious nature even in organisations that can demonstrate
good practice at any one point in time. They suggest
that any system that aims at measuring service user out-
comes and the quality of support they receive needs to
include repeated and robust observations of these fac-
tors. In Australia under the reformed market for disabil-
ity services envisaged by the National Disability
Insurance Scheme it should not be sufficient for organis-
ations to make claims about the quality of their support
but rather will need to demonstrate continued fidelity
through such observational data on staff practice and
service user outcomes.
Note
1. For the purposes of this study supported accommo-
dation services are defined as services which support
1–6 people in ordinary houses dispersed in the commu-
nity with 24-hour support available or on call. For the
most part the housing is provided by the organisation
who also provides support.
Acknowledgements
Thanks are extended to the disability services participating in
this study, and to research assistants Louise Phillips, Samuel
Murray, Emma Caruana, and Lincoln Humphreys.
Disclosure statement
No potential conflict of interest was reported by the authors.
Funding
Funding support was from the Australian Research Council
Linkage [grant LP130100189] and partner disability services.
ORCID
Christine Bigby http://orcid.org/0000-0001-7001-8976
Emma Bould http://orcid.org/0000-0003-3108-2072
Julie Beadle-Brown http://orcid.org/0000-0003-2306-8801
References
Aman, M. G., Burrow, W. H., & Wolford, P. L. (1995). The
aberrant behavior checklist–community: Factor validity
and effect of subject variables for adults in group homes.
American Journal on Mental Retardation,100, 293–292.
Beadle-Brown, J., Beecham, J., Mansell, J., Baumker, T., Leigh,
J., Whelton, R., & Richardson, L. (2012). Outcomes and costs
of skilled support for people with severe or profound intellec-
tual disability and complex needs. London: NIHR.
Beadle-Brown, J., Bigby, C., & Bould, E. (2015). Observing
practice leadership in intellectual and developmental dis-
ability services. Journal of Intellectual Disability Research,
59, 1081–1093.
Beadle-Brown, J., Gifford, J., & Mansell, J. (2005). Staff experi-
ence and satisfaction questionnaire (learning disability).
Canterbury: Tizard Centre.
Beadle-Brown, J., Hutchinson, A., & Whelton, B. (2012).
Person–centred active support –increasing choice, promot-
ing independence and reducing challenging behaviour.
Journal of Applied Research in Intellectual Disabilities,25,
291–307.
Beadle-Brown, J., Mansell, J., Ashman, B., Ockenden, J., Iles,
R., & Whelton, B. (2014). Practice leadership and active
support in residential services for people with intellectual
disabilities: An exploratory study. Journal of Intellectual
Disability Research,58, 838–850.
Bigby, C., & Beadle-Brown, J. (2016). Improving quality of life
outcomes in supported accommodation for people with
intellectual disability: What makes a difference? Journal of
Applied Research in Intellectual Disabilities. Advance online
publication. doi:10.1111/jar.12291
Bigby, C., Bould, E., & Beadle-Brown, J. (2017). Comparing
costs and outcomes of supported living with group home
in Australia. Journal of Intellectual & Developmental
Disabilities. Advance online publication. doi:10.3109/
13668250.2017.1299117
Cohen, J. (1988). Statistical power analysis for the behavioral
sciences (2nd ed.). Hillsdale, NJ: Erlbaum.
Dunst, C. J., & Hamby, D. W. (2012). Guide for calculating and
interpreting effect sizes and confidence intervals in intellec-
tual and developmental disability research studies. Journal
of Intellectual & Developmental Disability,37,89–99.
Felce, D., Bowley, C., Baxter, H., Jones, E., Lowe, K., &
Emerson, E. (2000). The effectiveness of staff support:
Evaluating active support training using a conditional prob-
ability approach. Research in Developmental Disabilities,21,
243–255.
Felce, D., de Kock, U., & Repp, A. (1986). An eco-behavioral
analysis of small community-based houses and traditional
12 C. BIGBY ET AL.
large hospitals for severely and profoundly mentally handi-
capped adults. Applied Research in Mental Retardation,7,
393–408.
Felce, D., Lowe, K., & Jones, E. (2002). Association between the
provision characteristics and operation of supported hous-
ing services and resident outcomes. Journal of Applied
Research in Intellectual Disabilities,15, 404–418.
Felce, D., & Perry, J. (1995). The extent of support for ordinary
living provided in staffed housing: The relationship between
staffing levels, resident characteristics, staff:resident inter-
actions and resident activity patterns. Social Science and
Medicine,40, 799–810.
Fritz, C. O., Morris, P. E., & Richler, J. J. (2012). Effect size esti-
mates: Current use, calculations, and interpretation. Journal
of Experimental Psychology: General,141(1), 2–18. doi:10.
1037/a0024338
Hastings, R. P. (1995). Understanding factors that influence
staff responses to challenging behaviours: An exploratory
interview study. Mental Handicap Research,8, 296–320.
Hatton, C., Emerson, E., Robertson, J., Gregory, N.,
Kessissoglou, S., Perry, J., …Hillery, J. (2001). The adaptive
behavior scale–residential and community (part I): Towards
the development of a short form. Research in Developmental
Disabilities,22, 273–288.
Humphreys, L., Bigby, C., Iacono, T., & Bould, E. (2016,
August). Development of a scale to measure organisational
culture in group homes. Paper presented at the
International Association for the Scientific Study of
Intellectual & Developmental Disabilities. Melbourne,
Australia [Abstract published in Journal of Applied
Research in Intellectual Disabilities,60(7–8), 685].
Jones,E.,Felce,D.,Lowe,K.,Bowley,C.,Pagler,J.,
Gallagher,B.,&Roper,A.(2001). Evaluation of the disse-
mination of active support training in staffed community
residences. American Journal on Mental Retardation,106,
344–358.
Jones, E., Felce, D., Lowe, K., Bowley, C., Pagler, J., Strong, G.,
…Kurowska, K. (2001). Evaluation of the dissemination of
active support training and training trainers. Journal of
Applied Research in Intellectual Disabilities,14,79–99.
Jones, E., Lowe, K., Brown, S., Albert, L., Saunders, C., Haake,
N., & Leigh, H. (2013). Active support as a primary preven-
tion strategy for challenging behaviour. International
Journal of Positive Behavioural Support,3,16–30.
Jones, E., Perry, J., Lowe, K., Felce, D., Toogood, S., Dunstan,
F., …Pagler, J. (1999). Opportunity and the promotion of
activity among adults with severe intellectual disability liv-
ing in community residences: The impact of training staff
in active support. Journal of Intellectual Disability
Research,43, 164–178.
Koritsas, S., Iacono, T., Hamilton, D., & Leighton, D. (2008).
The effect of active support training on engagement, oppor-
tunities for choice, challenging behaviour and support
needs. Journal of Intellectual & Developmental Disability,
33, 247–256.
Lipsey, M. W., & Wilson, D. B. (2001). Practical meta–analysis
(Applied Social Research Methods Series Vol. 49).
Thousand Oaks, CA: Sage.
Mansell, J. (1994). Specialized group homes for persons with
severe or profound mental retardation and serious problem
behaviour in England. Research in Developmental
Disabilities,15, 371–388.
Mansell, J., Ashman, B., Macdonald, S., & Beadle-Brown,
J. (2002). Residential care in the community for adults
with intellectual disabilities: Needs, characteristics and
services. Journal of Intellectual Disability Research,46,
625–633.
Mansell, J., & Beadle-Brown, J. (2005). Engagement in mean-
ingful activity and relationships: An observational measure.
Canterbury: Tizard Centre.
Mansell, J., & Beadle-Brown, J. (2012). Active support:
Enabling and empowering people with intellectual disabil-
ities. London: Jessica Kingsley.
Mansell, J., Beadle-Brown, J., & Bigby, C. (2013).
Implementation of active support in Victoria, Australia:
An exploratory study. Journal of Intellectual &
Developmental Disability,38,48
–58.
Mansell, J., Beadle-Brown, J., Macdonald, S., & Ashman, B.
(2003). Resident involvement in activity in small com-
munity homes for people with learning disabilities.
Journal of Applied Research in Intellectual Disabilities,
16,63–74.
Mansell, J., Beadle-Brown, J., Whelton, R., Beckett, C., &
Hutchinson,A.(2008). Effect of service structure
and organisation on staff care practices in small commu-
nity homes for people with intellectual disabilities. Journal
of Applied Research in Intellectual Disabilities,21,
398–413.
Mansell, J., McGill, P., & Emerson, E. (2001). Development
and evaluation of innovative residential services for people
with severe intellectual disability and serious challenging
behaviour. In L. Glidden (Ed.), International review of
research in mental retardation (Vol. 24, pp. 245–298).
New York, NY: Academic Press.
McGill, P., & Toogood, S. (1994). Organizing community pla-
cements. In E. Emerson, P. McGill, & J. Mansell (Eds.),
Severe learning disabilities and challenging behaviours:
Designing high quality services (pp. 232–259). London:
Chapman & Hall.
Smith, C., Felce, D., Jones, E., & Lowe, K. (2002). Differential
responsiveness to staff support: Evaluating the impact of
individual characteristics on the effectiveness of Active
Support Training using a conditional probability approach.
Journal of Intellectual Disability Research,46, 594–604.
Stancliffe, R., Harman, A., Toogood, S., & McVilly, K. (2007).
Australian implementation and evaluation of active sup-
port. Journal of Applied Research in Intellectual
Disabilities,20, 211–227.
Stancliffe, R., McVilly, K., Radler, G., Mountford, L., &
Tomaszewski, P. (2010). Active support, participation and
depression. Journal of Applied Research in Intellectual
Disabilities,23, 312–321.
Thompson, T., Robinson, J., Dietrich, M., Farris, M., &
Sinclair, V. (1996). Interdependence of architectural fea-
tures and program variables in community residences for
people with mental retardation. American Journal on
Mental Retardation,101, 315–327.
Wing, L., & Gould, J. (1978). Systematic recording of behaviors
and skills of retarded and psychotic children. Journal of
Autism and Childhood Schizophrenia,8,79–97.
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