Cognitive rehabilitation after stroke
Stroke is a leading cause of long-term acquired disability in adults [
1], predisposing patients toward institutionalization and poorer quality of life [
2].
Over the coming decades, the incidence of post-stroke disability is
expected to increase by 35% due to the rising prevalence of
cerebrovascular risk and advances in medicine which are reducing
post-stroke mortality rates [
3]. Historically, stroke rehabilitation has been focused on motor rehabilitation [
4,
5].
However, post-stroke cognitive deficits are pervasive causing
disability with major impacts on quality of life and independence on
everyday life activities [
6,
7]. In the last years, attention to the impact of cognitive deficits has been growing [
8] and finding new ways to improve cognition after stroke is considered a priority [
9].
Also, more recently, the International Stroke Recovery and
Rehabilitation Alliance 2018 working group has identified post-stroke
cognitive impairments as a research priority [
10].
Regardless
of the many new developments in cognitive rehabilitation programs and
applications, limited data on the effectiveness of cognitive
rehabilitation is available because of the heterogeneity of
participants, interventions, and outcome measures [
11].
Results from recent reviews corroborate that cognitive rehabilitation
has a positive impact on post-stroke cognitive outcomes [
12,
13], although of small magnitude (Hedges’ g = 0.48) [
12]. This result is in line with the quantitative [
14] and qualitative [
15,
16,
17] findings of previous reviews that have analyzed the effect of cognitive rehabilitation across multiple cognitive domains.
Is cognitive rehabilitation’s impact small or are we missing better cognitive rehabilitation methodologies?
Paper-and-pencil
tasks are still the most widely used methods for cognitive
rehabilitation because of their accessibility, ease of use, clinical
validity and reduced cost [
18]. In the last years, computer-based versions of these traditional tasks are also starting to become clinically accepted [
19,
20].
However, there is an absence of specific methodologies that inform
health professionals which tasks to apply and under what clinical
conditions [
21].
Consequently, rehabilitation professionals perform a selection of tasks
based on their clinical experience, missing scientific foundations [
22].
We have proposed an objective and quantitative framework for the
creation of personalized cognitive rehabilitation tasks based on a
participatory design strategy with health professionals [
23].
In this work, through computational modeling, the authors
operationalized 11 paper-and-pencil tasks and developed an Information
and Communication Technologies based tool - the Task Generator (TG) - to
tailor each of those 11 paper-and-pencil tasks to each patient in the
domains of attention, memory, language and executive functions. A
clinical evaluation of the TG with twenty stroke patients showed that
the TG is able to adapt task parameters and difficulty levels according
to patient’s cognitive assessment, and provide a comprehensive cognitive
training [
24].
However, although it has been shown that rehabilitation strategies
based on paper-and-pencil tasks can be personalized and adapted [
24,
25], this approach presents a limited transfer to performance in activities of daily living (ADL) [
18].
Over
the last years, rehabilitation methodologies based on virtual reality
(VR) have been developed as promising solutions to improve cognitive
functions [
26,
27].
VR-based tools have shown potential and to be ideal environments to
incorporate cognitive tasks within the simulation of ADL’s [
28].
A recent trial with a VR-based simulation of everyday life activities
(like going to the pharmacy, buying grocery at the supermarket, paying
the water bill) suggested that an ecologically valid intervention has
more impact than conventional methods (cognitive training using puzzles,
calculus, problem resolution and shape sorting) in cognitive
rehabilitation of stroke patients [
29]. Also, some of these VR-based systems allow the integration of motor training [
30]
and recent studies have already shown benefits of performing
simultaneous motor and cognitive training with stroke patients using VR [
31,
32]. Yet, there is still an insufficient number of rigorous trials to clinically validate VR methods [
12]
and there are difficulties associated with the limited access which
results in a low adoption by health professionals who still prefer
mostly use paper-and-pencil interventions [
33].
In general, existing ecologically-valid VR-based environments are simulations of cities [
29,
34,
35,
36,
37,
38], kitchens [
39,
40,
41,
42,
43,
44,
45], streets [
46,
47,
48,
49,
50,
51], supermarkets [
52,
53,
54,
55,
56], malls and other shopping scenarios [
57,
58,
59,
60,
61].
Of these, only rare cases take into account training personalization
according to patient cognitive profile and session-to-session adaptation
[
29,
36,
38,
41].
Additionally, the results of studies comparing VR cognitive
interventions with standard occupational therapy or neuropsychology
cognitive paper-and-pencil training are fundamentally subjective as
control interventions. OT does not consider cognition as the main
training focus, and neuropsychology paper-and-pencil training tasks are
too similar to the cognitive assessment scales; additionally, both
approaches do not incorporate personalization and dynamic adaptation to
performance. Hence, even if rehabilitation sessions last the same, these
interventions are not equivalent as they are delivered with
uncontrolled difficulty levels and cognitive demands. Personalized
rehabilitation is defined as involving an assessment of each patient’s
impairments and performing a tailored intervention to his cognitive
profile in the different domains. Instead, adaptation deals with the
dynamic adjustment of the tasks’ cognitive demands according to the
patients’ performance along the intervention sessions, therefore
avoiding boredom (tasks that are to easy to solve) or frustration (tasks
that are too difficult to solve).
Here we try to address some of
the existing limitations in the validation of VR-based cognitive
rehabilitation tools. In this study we compared two task content
equivalent rehabilitation tools developed under the same personalization
and adaptation framework [
23]:
the TG and the Reh@City v2.0. This framework allows us to make sure
that both tools deliver the same controlled adaptation and
personalization of difficulty levels, and address the same cognitive
demands. Hence, this comparison allows identifying the specific impact
of increasing ecological validity of training through VR simulations of
ADLs over the same training delivered through clinically accepted
paper-and-pencil equivalent tasks. These findings will further inform on
the specific benefits of ecologically valid environments delivered
though VR and encourage the adoption of these technologies by health
professionals.
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