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Australian Journal of Dementia Care
October/November 2016 Vol 5 No 5
participants adopting a different
perspective to solving blame questions –
some of which might lead to solutions that
may cause other problems (see box p51).
Effective knowledge translation in
dementia care depends on organisational
agility and appetite for innovative
thinking at all levels. Many policy reforms
demand fast change responses and the
operational and commercial stakes may be
high, eg consumer directed care (Gill &
Cameron 2015). AI has been described as a
rapid and positive revolution for change
weary organisations. For managers and
team leaders seeking innovative
participatory approaches to facilitate
workforce engagement, AI has been
promoted as offering hope for lasting
change in organisational culture, learning,
and healthcare delivery.
Popular is not the same as effective,
however. A team from the DCRCs led by
Associate Professor Belinda Goodenough
asked the question: ‘how has AI been used
in dementia care settings, and with what
types of outcomes?’
Is AI useful?
In 2010, a review conducted onAI in aged
care identified 21 studies (Reed 2010). The
majority of these reports described
methods or proposals; none had reached
the stage of delivery. The review
concluded that, despite several papers
recommending and describingAI, more
research was required that reported
outcomes data. The DCRC team
conducted a scoping conceptual review
update of this 2010 reviewwith a focus on
dementia care.
Using keyword combinations including
‘appreciative inquiry’, ‘care’, ‘dementia’,
and ‘aged’, the team searched for literature
using indexed databases (PsycINFO,
MEDLINE), Google Scholar and manually
checking reports. They found eight more
papers has been published since the 2010
review – only four addressed dementia
care (Seebohm
et al
2010; Amador
et al
2014; Fortune
et al
2015; Scerri
et al
2015).
Apart from case reports of processes for
creating ‘team vision’, none of the reports
had compelling evaluations of KT or
sustainable change outcomes in dementia
care. One study reported that dementia
care staff enjoyed the imaginative
narrative approach, despite AI being
initially deemed ‘woolly thinking’ by a
few initially sceptical clinicians.
AI was also used in one report with
consumers as part of a participatory action
research project to learn what older people
want from care. In perhaps the only study
using quantitative outcomes analysis
(cost-effectiveness in end-of-life care),
there was some evidence of positive
changes in working relationships and
resident outcomes for use of AI processes
in a multisite study of residential care
(Amador
et al
2014).
In summary, AI has been used to broker
vision-setting conversations with staff or
consumers about the features of good
dementia care (Scerri
et al
2015). Since the
2010 review, there remains a dearth of
outcomes evidence in adequately
controlled designs. It was also not possible
from our review to confidently conclude
that the positive reports for engagement
with the AI processes were independent;
that is, whether the case report authors
included paid consultants.
Interestingly, the language of the articles
frequently suggested practice change
implications: the DCRC team inserted the
text of the four articles into a word cloud
generator and noted that phrases like
‘change’, ‘process’, and ‘culture’ featured
heavily, despite little data about outcomes
(see Figure 2).
Where to from here?
Absence of evidence is not the same as
provingAI is not effective in dementia
care. The research is simply yet to be
conducted using reliable measures of
change to determine ‘what works’
(Trajkovski
et al
2013). Likewise, there is no
evidence for adverse outcomes.
Overall, the majority of research into
strength-based approaches like AI has
been done with community-dwelling
populations who can communicate well.
Studies recruiting older people with
dementia in residential care are generally
uncontrolled case reports (Hirst
et al
2013).
It has been suggested that the AI
approach to crafting organisational culture
complements philosophies of care that
emphasise what a person retains and has
capacity to do. This contrasts with a deficit
model which starts with failure (eg
communication breakdown, knowledge
deficits, uncontrolled symptoms) (Ilifee
et
al
2015).
Against the current state of knowledge,
perhaps the more proper question is: what
are the risks for usingAI? Here are some
considerations:
• Cost – as a change philosophy, AI is
marketed as a specialist skill set: some
Australian service providers engage
paid external consultants, and this
outlay may be expensive.
• Criterion shift –AI aims to explore what
is working well and how to ‘do more’; if
‘working well’ does not include a
criterion of ‘evidence based’ as a practice
yardstick, then there is the risk of
promoting bad practice.
While awaiting relevant research, we
suggest that AI might be a useful strategy
to consider when leading change with
teams who lack cohesion. Applying the
DTSC Knowledge Translation Framework
(Figure 1), AI might assist first steps for
achieving consensus decision-making
about dementia care innovation adoption
for teams yet to reach the ‘agreement’
stage, such as:
• Innovations that touch on personal
values and philosophies of care (eg
palliative/end-of-life care, sexuality
assessment etc);
• Previous change experience has been
negative and a ‘circuit breaker’ is
needed;
• Interdisciplinary conversation
(including consumers) needing a
new/common language to describe the
vision for a ‘good outcome’;
• Promoting conversations which move
away from ‘blame’ for outcomes
towards ‘caring about caring’.
AI will likely remain a popular
consideration for supporting ‘team think
outside the square’. For organisations
facing change in dementia care delivery
and policy, “inquiry in order to appreciate
is a powerful start for a conversation”
(Scerri
et al
2015).
Acknowledgment
Preliminary results from this review project were
presented at the Dementia Research
Symposium, NHMRC National Institute for
Dementia Research, Brisbane in April 2016.
Conflict of interest declaration
None of the authors are involved with the
development or delivery of fee-for-service
consultancy in Appreciative Inquiry methods of
training.
References
Amador S, Goodman C, King D, Ng YT, Elmore
N, Mathie E
et al
(2014) Exploring resource use
and associated costs in end-of-life care for older
people with dementia in residential care homes.
International Journal of Geriatric Psychiatry
29(7) 758-766.
Caldwell SD, Liu Y (2011) Further investigating the
DCRC SPEC I AL I SSUE : THE B I G P I CTURE I N DEMENT I A RESEARCH
Figure 2: A word cloud generated on the
frequency of phrases used in four
published articles about Appreciative
Inquiry in dementia care