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Building Resilience Through a Virtual Coach Called Driven: Longitudinal Pilot Study and the Neuroscience of Small, Frequent Learning Tasks

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Background Digital interventions hold promise to address the global decline in mental health. Resilience is indicated as an avenue to enact preventative care. Combining resilience enhancement with a neuroscience-based learning technique may attenuate current trends. Objective This study sets out the neurobiological mechanics of small, micro-session learning (microtasks), and tested their efficacy in building resilience capacity through a digital conversive program called Driven to create lasting behavioural change. Methods Using the foundations of the microtask approach, Driven was constructed as an automated intervention to improve resilience capacity, based on the PR6 resilience framework. Real world data from a sub-clinical cohort (n=387) across four organisations were analysed using the PR6 resilience psychometric to assess resilience pre and post intervention. Usage rates of Driven and other factors were investigated through regression analyses as predictors of future resilience capacity improvement. Results Of the invited cohort, 89% (n=345/387) participated and were mostly male (74.5%, n=257/345). Median time between first and second PR6 assessment was 199 days. Of participants, 70.4% (n=245/345) completed the second assessment. Average individual improvement in resilience was 10.9% for the remeasured cohort (n=245). Results showed higher daily usage of Driven resulted in greater resilience improvements, with usage of more than once every four days resulted in a 15.6% improvement, and average usage once every two days resulted in a 24.9% improvement. Low or no usage of Driven showed no significant improvement. Further, a lower pre intervention score resulted in higher participation and higher subsequent improvement. Conclusion Delivering microtasks through a digital virtual coaching approach presents a reliable method to achieve lasting behavioural change and improve resilience capacity. Additionally, Driven displays an ability to provide effective preventative intervention to those with greater need.
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INTERNATIONAL JOURNAL OF NEUROPSYCHOTHERAPY Volume 7 Issue 2 - July 2019
Rossouw, J. G., Erieau, C. L., & Beeson, E. T. (2019). Building resilience through a virtual coach called Driven: Longitudinal pilot study and the
neuroscience of small, frequent learning tasks. International Journal of Neuropsychotherapy, 7(2), 2341. doi:10.12744/ijnpt.2019.023-041
Building Resilience Through a Virtual Coach
Called Driven: Longitudinal Pilot Study and the
Neuroscience of Small, Frequent Learning Tasks
Rossouw, Jurie G. (corresponding author, jurie@hellodriven.com); Erieau, Chelsea L; Beeson, Eric T. 2019, July
ABSTRACT
Background
Digital interventions hold promise to address the global decline in mental health. Resilience is indicated as an avenue to enact
preventative care. Combining resilience enhancement with a neuroscience-based learning technique may attenuate current
trends.
Objective
This study sets out the neurobiological mechanics of small, micro-session learning (microtasks), and tested their efficacy in
building resilience capacity through a digital conversive program called Driven to create lasting behavioural change.
Methods
Using the foundations of the microtask approach, Driven was constructed as an automated intervention to improve resilience
capacity, based on the PR6 resilience framework. Real world data from a sub-clinical cohort (n=387) across four organisations
were analysed using the PR6 resilience psychometric to assess resilience pre and post intervention. Usage rates of Driven and
other factors were investigated through regression analyses as predictors of future resilience capacity improvement.
Results
Of the invited cohort, 89% (n=345/387) participated and were mostly male (74.5%, n=257/345). Median time between first and
second PR6 assessment was 199 days. Of participants, 70.4% (n=245/345) completed the second assessment. Average
individual improvement in resilience was 10.9% for the remeasured cohort (n=245). Results showed higher daily usage of Driven
resulted in greater resilience improvements, with usage of more than once every four days resulted in a 15.6% improvement,
and average usage once every two days resulted in a 24.9% improvement. Low or no usage of Driven showed no significant
improvement. Further, a lower pre intervention score resulted in higher participation and higher subsequent improvement.
Conclusion
Delivering microtasks through a digital virtual coaching approach presents a reliable method to achieve lasting behavioural
change and improve resilience capacity. Additionally, Driven displays an ability to provide effective preventative intervention to
those with greater need.
INTRODUCTION
Worldwide, 1 in 13 people suffer from anxiety, and estimates hold
a prevalence of 4%-5% across 53 countries. In Australia, this
number increases 1 in 7, while 1 in 5 have experienced a mental
disorder in the last twelve months (ABS, 2007)
1
. 300 million
people are estimated to suffer from depression, contributing to
around 800,000 suicides each year (WHO, 2018)
2
.
Depression and anxiety alone cost the global economy an
estimated US$1 trillion in lost productivity each year
equivalent to 12 billion days or 50 million years of work
(Chisholm et al, 2016)
3
. There is an evident need for new
preventative interventions that can be more broadly applied to
de-escalate early depression and ‘inoculate’ individuals against
depression, anxiety and stress (Katz et al, 2016)
4
.
The need for this is clear when considering an estimated US$2.5-
8.5 trillion in lost output due to mental, neurological and
substance use disorders a number predicated to double by
2030 unless substantial effort is directed at the problem. In
terms of cost benefit analysis, current cost-benefit research
indicates that for every $1USD put into scaled up treatment for
mental disorders, the net benefit is up to $5.7USD return in
increased health and productivity (Chisholm et al, 2016)
5
.
Self-reported absenteeism is halved in workplaces that the
employees have reported as mentally healthy. This is important
to note when one in five Australian workers report having taken
time off for their mental health in the past twelve months in
2007 (ABS, 2007)
6
. In the UK, 12.7% of all sickness absence days
are attributable to mental health (ONS, 2014)
7
. Research by
Miller shows that 82% of employees with mental health issues
report that it affects their work, compared to 53% of people with
physical health issues (Miller, 2006)
8
.
Employees who would describe their workplace as mentally
unhealthy are four times as likely to take time off work.
However, in Australia only 52% of employees said their
workplace is mentally healthy, and only five out of ten (56%)
would say their most senior leader cares about mental health
despite 91% of employees reporting that mental health is
important in the workplace (ABS, 2007)
9
. Untreated mental
health conditions lose the Australian workplace $10.9 billion
INTERNATIONAL JOURNAL OF NEUROPSYCHOTHERAPY Volume 7 Issue 2 - July 2019
Rossouw, J. G., Erieau, C. L., & Beeson, E. T. (2019). Building resilience through a virtual coach called Driven: Longitudinal pilot study and the
neuroscience of small, frequent learning tasks. International Journal of Neuropsychotherapy, 7(2), 2341. doi:10.12744/ijnpt.2019.023-041
each year - $6.1 billion in presenteeism and $146 million in
compensation claims.
Given the magnitude of the problem, more research over the last
three decades has focused on the development of resilience as a
proactive, protective measure against detrimental mental health
states (Edward, 2005; Masten et al, 2009; Rutter, 1995; Stoffel &
Cain, 2018)
10
,
11
,
12
,
13
. Resilience can be defined as “the ability to
positively adapt and thrive in the face of risk and adversity”
(Rossouw & Rossouw, 2016)
14
. Resilience is a temporal,
multidimensional concept and exists in multiple expressions
across all cultures and generations (Connor & Davidson, 2003)
15
.
It is not necessarily a personality trait; rather, it can be a learned
set of cognitive skills and beliefs that enable action and
minimise harm when affected by stressors. Resilience is an
important aspect of goal achievement, being a better predictor
than IQ or talent, and acts as a protective factor for children in
stressful environments (Garmezy, 1985a, 1985b; Tsuang,
2000)
16
,
17
,
18
. People who are more resilient make fewer career
changes than their same-age counterparts (Duckworth et al
2007)
19
and are more likely to stick with a difficult job (Eskreis-
Winkler, et al 2014)
20
. Research conclusively shows that the
psychological wellbeing of the workforce is directly related to
work-related outcomes, in both the individual and
organisational spheres (Ford, Cerasoli, Higgins & Decesare, 2011;
Taris & Schreurs, 2009)
21
,
22
.
Thus, developing resilience in the workforce and the population
at large may be an effective pathway to preventing lost
productivity and improving the psychological health of the
general population (Robertson et al, 2015)
23
. A carefully
designed, proactive intervention is much more cost effective
than a retroactive solution (Luthar & Cicchetti, 2000;
Yoshikawa, 2004; Yoshikawa & Knitzer, 1997)
24
,
25
,
26
, hence
resilience should be developed through preventative methods.
Research is emerging on the efficacy of digital intervention as a
scalable solution to wide-ranging issues including AIDS (Ybarra
& Bull, 2007)
27
, smoking cessation (Rogers, 2005)
28
, health
promotion and disease control (McFarlane et al, 2005)
29
,
contraceptive method choice (Garbers, 2012)
30
even sexual
counselling after prostate cancer treatment (Schover et al,
2012)
31
. Digital intervention has proven effective in several
mental health and somatic-related issues, including IBS
(Andersson et al, 2011)
32
, tinnitus (Kaldo et al, 2013)
33
, and
depression (Kaltenthaler et al, 2008)
34
. This represents an
interesting possibility of addressing a widescale problem quickly
at an individual and population level. Digital intervention
represents a potential avenue to developing resilience in the
workforce and the general population.
Further, people are steadily becoming digital natives. In
Australia in 2018, smartphone ownership in Australia stood at
89%, which rose from 88% in 2017 and 84% the year before
(Mobile Consumer Survey 2018)
35
. The largest usage increase is
from users 55 and over. This is close to the peak saturation point
of smart device use (predicted as 90%-95%)
36
. Engagement with
digital voice assistants has risen significantly, meaning that
people may be becoming more reliant on, and comfortable with,
automated interaction (Deloitte, 2018)
37
. Given such a large
percentage of the population have access to a common channel
for learning which is set to continue increasing it seems wise
to capitalise on that particular mode.
Murry et al. has put forward a case that digital health
interventions present an opportunity for cost-effective and
scalable solutions in a resource-scarce environment, and that an
actionable knowledge base should be created in a timely
manner to facilitate urgently needed solutions (Murray et al,
2016: p844)
38
. Our aim is to contribute to this knowledge base
by investigating the efficacy of a digital artificial intelligence (AI)
virtual coach which will be referred to as ‘Driven for the
remainder of this paper. Driven aims to provide a scalable,
accessible model of resilience training through daily activities,
using a digital format to assess and intervene.
DESIGN OF DRIVEN
Developing the concept of Microtasks
Traditional approaches to resilience development involve
workshops and in-person facilitation, commonly utilising
experiential learning (Sugarman, 1987)
39
. While this style has
particular strengths, limitations regarding budgetary and time
availability restrictions result in lower organisational
deployment. Further, resilience consists of various personal
skills (Rutter, 1985; Olsson et al, 2003)
40
,
41
that may take a longer
timeframe to develop, and is therefore not suited to one-off
training styles.
As such, in designing the style of resilience development, a
modality was sought that has a strong potential of achieving
individual behavioural change through an automated approach.
Participants would thereby have increased opportunity to
internalise the diverse set of resilience skills, allowing neural
change while at the same time achieving scalability to reach
larger audiences at lower cost. In order to design such an
approach, a review of learning approaches in combination with
neuroplasticity was conducted.
Neuroplasticity in relation to learning
Functional plasticity involves corrective processes where brain
functions are remapped following neural damage to brain tissue
(Freed et al, 1985)
42
. Structural plasticity involves synaptic gain
and elimination (restructuring) to integrate learning through
memory trace formation (Caroni, 2012)
43
. As resilience
development in subclinical populations do not involve
functional rewiring, we can generally conclude that structural
plasticity is of primary interest in facilitating long-term memory
formation and behavioural change (Lamprecht, 2004;
Chklovskii et al, 2004)
44
,
45
. Structural plasticity in association
cortices is mediated through hippocampal function that stores
short to medium-term learning for consolidation and
integration (Abraham et al, 2002; Leuner, 2010)
46
,
47
.
Structural plasticity is influenced by long-term potentiation
(LTP), starting with co-incident pre- and postsynaptic firing,
resulting in activation of N-methyl-d-aspartate (NMDA)-type
glutamate receptors, release of the Mg2+ blocks, influx of Ca2+,
triggering postsynaptic release of protein kinases such as
CaMKII and PKC (Lüscher & Malenka, 2012)
48
. This further
causes phosphorylation reactions that traffics postsynaptic
recycling endosomes to insert AMPA receptors into the
postsynaptic spine, rendering the synapse more sensitive to
future presynaptic firing.
In the later stage of LTP, CREB gene transcription processes are
activated via cAMP and PKA, resulting in protein synthesis that
is necessary for the production of new dendritic spines that
enables the possibility for LTP to occur (Kandel, 2001; Engert &
Bonhoeffer, 1999)
49
,
50
. Further optimisation of neural pathway
structuring is achieved through spike timing-dependent
plasticity (STDP), where LTP is only enabled where the
presynaptic terminal fires before the postsynaptic terminal
within a window of 20 milliseconds (Bi & Poo, 1998)
51
.
INTERNATIONAL JOURNAL OF NEUROPSYCHOTHERAPY Volume 7 Issue 2 - July 2019
Rossouw, J. G., Erieau, C. L., & Beeson, E. T. (2019). Building resilience through a virtual coach called Driven: Longitudinal pilot study and the
neuroscience of small, frequent learning tasks. International Journal of Neuropsychotherapy, 7(2), 2341. doi:10.12744/ijnpt.2019.023-041
Relationship map crossing from behaviour, into processing centres, into cognitive networks (the target for learning), through to neural change
mechanisms. Arrows indicate direct relationships (solid lines) and indirect effects (dashed lines). Normal extended-session learning is
presented on the left half, with mechanistic impacts on learning effectiveness presented on the right half through frequent, micro-session
learning. Plus signs indicate avenues for increased learning due to frequent, micro-session style learning.
PFC - prefrontal cortex; LTP - long term potentiation, FDP - frequency dependent plasticity, STDP - spike-timing dependent plasticity, BDNF -
brain-derived neurotrophic factor, AMPA - α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid, NMDA - N-Methyl-D-aspartic acid, SNARE
- soluble NSF attachment protein receptor, ATP - adenosine triphosphate, cAMP - cyclic adenosine monophosphate, AC - adenylyl cyclase,
PKA - protein kinase A, CREB - cAMP response element-binding protein.
INTERNATIONAL JOURNAL OF NEUROPSYCHOTHERAPY Volume 7 Issue 2 - July 2019
Rossouw, J. G., Erieau, C. L., & Beeson, E. T. (2019). Building resilience through a virtual coach called Driven: Longitudinal pilot study and the
neuroscience of small, frequent learning tasks. International Journal of Neuropsychotherapy, 7(2), 2341. doi:10.12744/ijnpt.2019.023-041
Of interest for the development of an efficient learning
mechanism is the method by which the presynaptic terminal
releases neurotransmitters into the synaptic cleft. Rapid release
and reuptake of neurotransmitters is best suited to achieve
STDP and facilitate structural plasticity. Clathrin-mediated
endocytosis may be too slow to facilitate this, however
Watanabe’s work that demonstrated ultrafast endocytosis
without the need for clathrin may be more prevalent at body
temperature, while clathrin-mediated endocytosis is more
prevalent at room temperature (Watanabe et al, 2013;
Brockmann & Rosenmund, 2016)
52
,
53
. This provides a basis for
more frequent neurotransmitter recycling, turning our
attention to exocytosis.
Recently, a process of spontaneous exocytosis from the
presynaptic terminal was described by Cho, et al. This showed
that the fusion clamp Complexin in the SNARE complex
undergoes activity-dependent phosphorylation, resulting in
increased ongoing spontaneous neurotransmitter release
following activation (Cho et al, 2015)
54
. They conclude that this
process plays a key role in structural plasticity through
facilitating formation of synaptic boutons.
This builds towards a further conclusion that frequency of
pathway activation plays a role in pathway change, which has
subsequently been demonstrated by Lea-Carnall, et al through
their work on frequency-dependent plasticity (FDP) in larger
scale networks (Lea-Carnall et al, 2017)
55
. However, the
mechanics and relevance of how FDP exactly contributes to
broader cognitive pathway change is still poorly understood at
the current stage. Nevertheless, the concept of FDP provides a
glimpse into further mechanistic explanations of how tuning of
learning frequency may enhance learning and LTP.
Many other neural structures are implicated in memory and
habit formation, such as the nucleus accumbens and ventral
tegmental area (habits, addiction, reward pathways),
cerebellum (fine motor movement, motor-related learning),
amygdala alongside the hypothalamic pituitary adrenal axis
(fear-based learning). The full neural mechanism of learning is
complex and not comprehensively understood, so for the
purpose of this review we will keep our focus to structures and
functions that are most pertinent to the concept.
Importance of BDNF for Learning
Our previous research (Rossouw & Rossouw, 2016)
56
noted the
importance of brain-derived neurotrophic factor (BDNF) for
synaptic structural plasticity (Lu et al, 2014; Leal et al, 2017)
57
,
58
,
alongside the importance of BDNF in behavioural adaptation
(Lu et al, 2013; Castrén & Rantamäki, 2010)
59
,
60
. BDNF is shown
to upregulate NDMA activation (Mizuno et al, 2003)
61
, alongside
increasing activation and expression of captive AMPA receptors
(Wu et al, 2004, Caldeira et al, 2012)
62
,
63
. Therefore we note the
importance of the presence of BDNF for structural plasticity and
neural adaptation in relation to resilience skill learning.
Various factors influence the regulation of BDNF, including
regular physical exercise which upregulates BDNF and
hippocampal function (Cotman & Berchtold, 2002; Cassilhas et
al, 2012)
64
,
65
. Poor nutrition in the form of high sugar combined
with dietary fats and alcohol has been show to downregulate
BDNF (Molteni et al, 2002; Heffernan, 2008)
66
,
67
. Sleep hygiene
is also indicated to influence BDNF levels (Giese et al, 2013;
Monteiro et al, 2017)
68
,
69
. Collectively this provides evidence for
the necessity to maintain a physiologically healthy lifestyle in
order to provide an optimal environment for plasticity to take
place.
Figure 1 presents a relationship map of the various factors as
they interact. This diagram shows a comparison of how
frequent, micro-session learning can impact and improve
learning compared to longer, single-session learning. Various
mechanistic pathways provide potential for increased learning,
enabling further research to consider the extent to which each
factor contribute most strongly.
We also note an inverse relationship between cortisol and BDNF
(Issa et al, 2010; Naveen et al, 2016)
70
,
71
, indicating the likelihood
of reduced learning under stress. This link between elevated
cortisol levels and reduced learning has been noted in previous
studies (Dinse et al, 2017; Vogel & Schwabe, 2016)
72
,
73
. The
implication of this effect of cortisol was considered in the
intervention design.
Intervention conceptual design
The collection of evidence above was consequently considered
in the design of the resilience development training
intervention. Given the nature of STDP and FDP, combined with
spontaneous exocytosis following pathway activation, it
followed that shorter, more frequent training activities would
provide increased potential for behavioural change. Providing
these on a daily schedule may also assist in utilising BDNF
replenishment through sleep processes.
Writing notes when learning has been found to improve
retention, particularly when written by hand rather than typing
due to handwriting usually involving contextual re-
interpretation while typing is more often verbatim (Mueller &
Oppenheimer, 2014)
74
. Therefore, utilising a format within
which learning is adapted to the individual and driving
interaction to require contextual re-interpretation can allow us
to utilise on-hand technology such as smartphones to improve
retention. Using technology in this context further enables
uniquely defined paths based on participant interaction, using
decision-trees and natural language processing techniques to
categorise input and provide deeper contextualised training.
Improved learning may indeed arise from convergent activation
of relevant neural pathways through recruitment of language
areas (Broca’s and Wernicke’s) and motor cortices (mechanistic
typing actions), combined with interpretation, memory
retrieval, contextual re-interpretation which has been suggested
as a mechanism that improves learning (Smoker et al, 2009)
75
.
In concert, the combined process of interactive training result
in more acute activation of resilience skills areas being trained,
resulting in greater STDP and FDP.
From here, the method for resilience skills education builds on
the original concepts of micro learning (Hug, 2005; Buchem &
Hamelmann, 2010)
76
,
77
. With the addition of digitally-enabled
contextual re-interpretation requirements of learning activities
to improve retention and cognitive integration, we distinguish
this modality from micro learning and establish the concept of
‘microtasks’.
The microtask modality therefore suggests a mechanism that
may assist in achieving greater learning through more structural
plasticity changes than would be achieved through single
condensed learning sessions. This concept can be summarised
by this example: Practicing the piano each day for seven days is
better for learning than practicing one session that is seven
times as long. Even if the same amount of time in total is spent
INTERNATIONAL JOURNAL OF NEUROPSYCHOTHERAPY Volume 7 Issue 2 - July 2019
Rossouw, J. G., Erieau, C. L., & Beeson, E. T. (2019). Building resilience through a virtual coach called Driven: Longitudinal pilot study and the
neuroscience of small, frequent learning tasks. International Journal of Neuropsychotherapy, 7(2), 2341. doi:10.12744/ijnpt.2019.023-041
practicing, more synaptic change takes place when the task is
broken up. This is due to the increased spontaneous vesicle
fusion following each practice session that continues to drive
synaptic structural plasticity, combined with the effects of FDP
and BDNF replenishment each day.
Defining ‘microtasks’
Given this context, we can define a microtask as a short (up to
10 minutes, or more) interactive task that requires active
participation through contextual reinterpretation of the
learning content. In other words, this means the learner takes
the learning content and re-interprets it in their personal
context to further engage the mechanisms of structural
plasticity to achieve long-term behavioural change.
While we are defining this concept, we do not propose to be the
inventors of this. Our interest with this review is to further
understand the potential mechanistic learning pathways. This
understanding may serve to further improve program design
aiming to achieve behavioural change with individuals in
various contexts.
Bottom-up approach
Regarding the impact of cortisol and stress on learning, Driven
employs a simple initial emotional state / stress check to
determine participant receptiveness to learning. If emotional
distress was reported, alternate interventions were proposed to
assist in enhancing individual composure. These interventions
included breathing exercises, reappraisal exercises and
mediations. This ‘bottom-up’ approach to facilitate limbic brain
downregulation was employed at the start of each microtask
session in an effort to improve potential for new skill and
knowledge integration.
Hypothesis
Our hypothesis is that regular adherence to completion of
resilience-related microtasks predicts greater improvement in
resilience scores. The objective of this study is to test for this
effect through the application of Driven within an
organisational context.
METHOD
Participants
The cohort includes data from four organisations that
implemented Driven soon after its introduction in late 2017, as
well as having completed both pre and post intervention
resilience assessment. To best represent a natural ‘real world’
implementation, all participants were included from these
organisations that were included in both the pre and post
assessment. These are generally the full population of a
particular organisational department that were nominated for
the program as requested by the organisation.
The full cohort (n=387) was invited by their respective
organisations to participate in the Driven resilience program.
Participants were 25.5% female (n=88) and 74.5% male (n=257).
No further gender data was available.
The implementation of Driven within these organisations were
requested by the organisations themselves and were therefore
not externally manipulated for research purposes. This setting
provides a basis for a longitudinal observational study,
providing insight into a ‘real world’ implementation of Driven
within organisations. Given this setting, comprehensive
demographic data on participants were not available, and
available data is reported on.
Ethics is controlled through agreed-to service Terms and
Conditions, as well as a Privacy Policy (available on
https://hellodriven.com/) that ensures individual
confidentiality and allows for use of de-identified and
aggregated data for research purposes. All participants are
provided with contact information for queries related to privacy
and to request removal of data.
Given that program implementation was made at arms-length,
there was no compensation provided to program participants.
Measures
The Predictive 6 Factor Resilience Scale (PR6) psychometric
measurement tool was used for pre and post intervention
assessment. The PR6 is a validated psychometric that measures
resilience across six domains spanning both mental and
physiological health factors (Rossouw et al, 2017)
78
. Using a
standard 5-point Likert scale across 16 items, the PR6 has shown
strong internal consistency (alpha) of 0.84 in previous research.
The six domains of resilience reported in the PR6 have been
shown alongside their neurobiological correlates, and are
summarised as follows:
Vision a measure of sense of purpose and clarity of
personal goals
Composure ability to manage stress and regulation of
emotional impulses
Reasoning ability to solve problems, be resourceful,
and anticipate and plan for future adversity
Tenacity ability to maintain persistence, motivation
and bounce back from adversity
Collaboration maintenance and formation of support
networks and personal relationships
Health physiological health, including good nutrition,
quality sleep and regular exercise
Given this context, resilience is presented as a collection of skills
that coalesce into resilience capacity. Domains within the PR6
are designed as areas that can be learned and improved upon,
setting it apart from personality traits which are expected to be
stable over time.
The pre-intervention assessment was conducted as the very first
interaction that the participant had with the program, providing
a robust starting score that is not influenced by any training
content. Participants completed the PR6 assessment online on
the Driven platform through an internet-connected device, such
as a laptop or smartphone. On completion, participants received
a resilience reports that displayed scores across the six domains.
From there they were able to continue to the training content.
Intervention
The Driven resilience development program employs
approximately 200 microtasks to facilitate resilience skills
building, enabled through a virtual coaching approach that uses
an AI-powered chatbot alongside decision trees and a mix of
interactive content.
Resilience domains of the PR6 provided the basis for the
development of microtasks provided through Driven. Each
microtask activity is based on research conducted into relevant
psychological and neuroscience concepts that support the
relevant resilience domain.
Content includes a mix of new research alongside time-tested
strategies to provide comprehensive approach to build
resilience capacity. Resilience training content include
INTERNATIONAL JOURNAL OF NEUROPSYCHOTHERAPY Volume 7 Issue 2 - July 2019
Rossouw, J. G., Erieau, C. L., & Beeson, E. T. (2019). Building resilience through a virtual coach called Driven: Longitudinal pilot study and the
neuroscience of small, frequent learning tasks. International Journal of Neuropsychotherapy, 7(2), 2341. doi:10.12744/ijnpt.2019.023-041
education on the effects of personal interpretation bias and
mitigation (Kleim et al, 2014; Berna et al, 2011)
79
,
80
, education on
emotional granularity and mood restoration techniques
alongside practice (Tugade et al, 2004; Fredrickson & Branigan
2005)
81
,
82
, motivation techniques through goal setting (Clarke et
al, 2014)
83
including Duckworth’s work on grit (Duckworth,
2007)
84
, mindfulness techniques to aid in managing and
preventing depressive symptomology (Teasdale et al, 2000;
Mason & Hargreaves, 2001)
85
,
86
, alongside various CBT-style
activities, drawing on the well-established nature of CBT and
recent evidence suggesting the effectiveness of digitally-
delivered intervention (Jakobsen et al, 2017)
87
.
Relating to physiological health, content includes general
education on constructing a home environment conducive to
good sleep, nutrition education information and activities,
exercise suggestions and content to encourage physical fitness,
alongside journaling activities to promote self-monitoring of
change (Hollis et al, 2008)
88
.
Further to the sample of research listed above and other
research consulted relating to the development of the
microtasks, the PR6 and Driven is also supported by a science
advisory board and is also used by over 200 psychologists,
counsellors and coaches who have provided feedback into the
program itself. Content is prioritised based on how the
participant scored in the pre-assessment, focusing initial user
activity on lowest-scoring domains.
Participants were free to interact with Driven as often as they
liked, and received periodic notifications to suggest
continuation with the training, such as one notification after 24
hours, and if there is no activity, another after 48 hours, and so
on. These notifications could be disabled if needed, and also
subside over time if there is a lack of participation.
To maintain confidentiality of data and data control, Driven is
delivered through a proprietary platform that can be accessed
on any internet-enabled device. This contrasts with other
services that use delivery platforms such as Slack and Facebook
Messenger where the data is also owned by the delivery platform
through their own terms of service.
At the start of the program, it is explained to participants that
Driven is not a crisis service, and is not intended as a
replacement for medical advice or in-person therapy. Should a
participant require immediate help, crisis helplines are provided
across various help types to assist in finding appropriate
assistance.
In essence, Driven is developed as an evidence-based resilience
building platform with validated psychometrics built in to
create meaningful change over time. Given the potential of
digital interventions like Driven to build resilience at scale and
function as a preventative intervention against depression and
anxiety, we consider the results of this study to carry
importance.
Organisational application
At a point in time, generally around six to seven months, chosen
by the organisation, a re-assessment was initiated. These varied
per organisation and within organisations as different teams
were enrolled and assessed at different times. This took the form
of a notification sent to all participants still with the
organisation at the time, after which the assessment was
GRAPH 1: Higher usages increase PR6 score
PR6 - First Predictive 6 Factor Resilience Scale Assessment, PR6-6 - Second PR6 Assessment, NU - No Usage, LU - Low Usage, MU - Moderate
Usage, HU - High Usage, RU - Recommended Usage. Blue arrows show no significant change, Green arrows show larger change.
INTERNATIONAL JOURNAL OF NEUROPSYCHOTHERAPY Volume 7 Issue 2 - July 2019
Rossouw, J. G., Erieau, C. L., & Beeson, E. T. (2019). Building resilience through a virtual coach called Driven: Longitudinal pilot study and the
neuroscience of small, frequent learning tasks. International Journal of Neuropsychotherapy, 7(2), 2341. doi:10.12744/ijnpt.2019.023-041
unlocked, and participants had the opportunity to complete the
PR6 again to measure change since the previous assessment.
Natural attrition arose here due to employees who had left the
company, employees on annual or sick or other leave, or
employees who chose not to participate in the re-assessment.
Once again, on completion the participant received a report that
then compared the previous score to the new score to assist in
identifying change. As there are many factors that influence
resilience, a natural variance is expected in scores, particularly
since these are domains designed to be improvable.
Data for analysis
Observational data included pre and post intervention PR6
resilience scores, duration between assessments, gender
demographics, company of participants, alongside usage data to
determine completion of microtasks.
De-identified data was extracted from the Driven platform to
conduct statistical analysis. Data was tested for normality,
internal consistency of the pre and post PR6 assessments was
conducted, ANOVA and T-tests were conducted to determine
statistical significance. Single and multiple regression analyses
were conducted to investigate potential predictive factors.
RESULTS
Of the full cohort, 345 (89.1%) participated in the initial
assessment and 42 (10.9%) did not.
First assessment
PR6 resilience score achieved for the all participants in the first
assessment (n=345) was 0.69 (StDev 0.134), assessing resilience
between 0 (lowest resilience) and 1 (highest resilience). Using
the Ryan-Joiner normality test, normality was confirmed with a
RJ value of 0.996 (p-value = 0.045).
Starting PR6 scores ANOVA testing showed no statistically
significant differences (p-value = 0.161) between genders, with
females scoring (PR6=0.67, StDev=0.134, n=88), and males
(PR6=0.7, StDev=0.134, n=257). Internal consistency of the PR6
was strong with an alpha of 0.7815 (n=345). Differences were
noted in the starting points of the four companies, notably with
company 4 (C4) displaying a higher starting point (PR6 = 0.79,
95% CI = 0.75 to 0.82), which when removed eliminated any
significant difference and also improved overall results.
However, to avoid overspecialisation and display broader
generalisability of the results, C4 data was included in further
analysis.
Second assessment
Following the initial assessment, organisations triggered second
assessments at various times according to their own
requirements. Median time between assessments was 199 days,
with a mean of 193 days (StDev = 61 days). This provided
considerable data to measure longitudinal adherence to a digital
platform, where often studies are very short-term oriented due
to high attrition rates.
Of the initial participants, 70.4% (n=245) completed the second
assessment. Attrition reasons included participants that left the
company, was on leave, or chose not to participate. Data on
reason was not available. ANOVA testing of those who
completed the first assessment only (PR6 score = 0.693) and
those who participated in re-assessment (PR6 score = 0.688)
showed no significant difference in starting scores (p-value =
0.771). Ryan-Joiner normality test again confirmed normality for
the second assessment with a RJ value of 0.989 (p-value = <0.01).
PR6 Remeasurement (PR6-R) overall score for participants
(n=245) was 0.75 (StDev 0.13), indicating an overall relative
increase in resilience of 8.3% regardless of usage. ANOVA
confirmed significance of the overall increase in resilience (p-
value = <0.001, Cohen’s d = 0.27). When analysing by gender, no
statistical significance (p-value = 0.53) was found between
females (PR6-R=0.738, StDev=0.112, n=72) and males (PR6-
GRAPH 2: Change in domains scores for MU, HU and RU combined
PR6 - Predictive 6 Factor Resilience Scale, 1 - First PR6Assessment, 2 - Second PR6 Assessment, VIS - Vision, COM - Composure, RES -
Reasoning, TEN - Tenacity, COL - Collaboration, HLT - Health. Green arrows show larger change.
INTERNATIONAL JOURNAL OF NEUROPSYCHOTHERAPY Volume 7 Issue 2 - July 2019
Rossouw, J. G., Erieau, C. L., & Beeson, E. T. (2019). Building resilience through a virtual coach called Driven: Longitudinal pilot study and the
neuroscience of small, frequent learning tasks. International Journal of Neuropsychotherapy, 7(2), 2341. doi:10.12744/ijnpt.2019.023-041
R=0.748, StDev=0.133, n=173). Internal consistency of the PR6-R
was strong with an alpha of 0.7964 (n=245).
When analysing by individual change experienced, we find an
average increase of 10.7% (StDev = 0.23) across the reassessment
cohort (n=245). As this value is higher than the absolute
increase, we consider greater increase experienced by those who
scored lower initially.
Gender-based improvement
Comparing by gender, we see females experience on average a
16% improvement (StDev=0.28), while males experience on
average an 8.4% improvement (StDev=0.2). This difference was
found to be statistically significant (p-value = 0.036).
Usage rates
Completion rates of Driven microtasks were recorded and were
used to calculate average engagement ratios. For analysis
purposes, these were condensed into five usage groups:
Recommended Usage (RU), indicating sustained used
of Driven on average once per day
High Usage (HU), indicating usage of Driven on average
once every two days
Moderate Usage (MU), indicating average usage once
every four days
Low Usage (LU), indicating average usage less than MU
No Usage (NU), indicating no usage other than
completing pre and post assessments
Through this approach, LU and NU serve as control groups
against generally higher usage groups MU, HU and RU.
Comparing difference between usage patterns should provide
insight into the hypothesis of more microtask completion
leading to further increase in resilience scores.
Compared to starting scores, we see a clear upward trend in
score improvement based on participation rate. ANOVA
analysis confirmed statistical significance of resilience
improvement compared to usage (p=<0.001)
TABLE 1: Usage Rates and Change
Usage
PR6-R
Improvement
P-value
NU
0.711
1.8%
0.562
LU
0.722
2.4%
0.483
MU
0.778
12.7%
<0.001
HU
0.787
24.9%
<0.001
RU
0.75
26.5%
0.198
NU - No Usage, LU - Low Usage, MU - Moderate Usage, HU - High
Usage, RU - Recommended Usage.
Across these we observe groupings with largest participation in
MU (n=85), followed by LU (n=66), and NU (n=65), then HU
(n=24) and RU (n=5). NU and LU groups showed minor
improvement, however these groups did not achieve
significance (NU p=0.562, Cohen’s d = 0.06, LU p=0.483, Cohen’s
d = 0.08). MU and HU shows a clear progressive trend that
resilience scores increase from higher usage (MU p=<0.001,
Cohen’s d = 0.41, HU p=<0.001, Cohen’s d = 0.73). Due to the
lower number of participants in RU, the P-value didn’t achieve
significance, however the general trend hold with this pilot
evidence (Cohen’s d = 0.73).
Interestingly, we also see a trend that lower scores correlate to a
higher usage rates alongside greater increase experienced
through the program. Usage rates and percentage of individual
change from PR6 starting score to PR6-R is summarised in Table
1, showing a general upward trend in improvement by usage.
This effect is illustrated by the box plots in Graph 1, showing pre
and post intervention assessment for each usage group.
Analysing across genders, no statistically significant difference
in usage was found (p-value = 0.716).
PR6 domain improvement
Comparing across individual domain scores, we see a similar
trend of greater increases achieved with higher participation. In
particular, MU, HU and RU groups together showed
significance in score increases across all domains, gaining
particularly on Composure (23.4% increase), Vision (19.9%
increase) and Health (15.1% increase).
Table 2 summarises domain-level results achieved for the full
cohort that participated in re-measurement, alongside results
limited to groups MU, HU and RU. Statistical significance is
indicated for each factor. A visual summary is presented in
Graph 2.
Comparing gender across the full cohort, females showed a
23.2% relatively larger increase in Composure improvement
than males (p-value = <0.05), as well as a 9.1% greater increase
in Tenacity (p-value = <0.05), and a 20.2% greater increase in
Collaboration (p-value = <0.05). This follows from previous
results showing that females improved more than males on
average.
TABLE 2: Domain Score Improvement
Improvement across full cohort, n=245
Domain
PR6
PR6-R
Improvement
P-value
PR6
0.68823
0.74512
8.3%
<0.001
Vision
0.6903
0.7612
10.3%
<0.001
Composure
0.6255
0.7184
14.9%
<0.001
Reasoning
0.7143
0.773
8.2%
0.001
Tenacity
0.7883
0.8337
5.8%
0.005
Collaboration
0.6556
0.676
3.1%
0.262
Health
0.6258
0.6801
8.7%
0.007
Improvement for MU, HU and RU, n=114
PR6
0.6731
0.7784
15.6%
<0.001
Vision
0.6678
0.8004
19.9%
<0.001
Composure
0.5998
0.7401
23.4%
<0.001
Reasoning
0.693
0.7971
15.0%
<0.001
Tenacity
0.7763
0.8596
10.7%
0.001
Collaboration
0.636
0.6985
9.8%
0.02
Health
0.648
0.7456
15.1%
<0.001
PR6 - Predictive 6 Factor Resilience Scale, MU - Moderate Usage, HU
- High Usage, RU - Recommended Usage.
Health factor change
The PR6 Health domain items assess aspects, including overall
perceptions of health, sleep quality, exercise frequency, and
adherence to healthy nutrition patterns (adherence to a diet low
in sugar and high in whole foods). These aspects were
investigated for significance across the full cohort and the MU,
HU and RU cohorts.
INTERNATIONAL JOURNAL OF NEUROPSYCHOTHERAPY Volume 7 Issue 2 - July 2019
Rossouw, J. G., Erieau, C. L., & Beeson, E. T. (2019). Building resilience through a virtual coach called Driven: Longitudinal pilot study and the
neuroscience of small, frequent learning tasks. International Journal of Neuropsychotherapy, 7(2), 2341. doi:10.12744/ijnpt.2019.023-041
Results for the full cohort showed that, even though there were
improvements across all aspects, the one aspect with statistical
significance was improvement in healthy nutrition adherence.
Confining data to MU, HU and RU groups showed statistically
significant improvements across all fields. This includes a 12.5%
relative improvement in sleep quality (p-value = <0.05), a 16.6%
relative improvement in exercise frequency (p-value = <0.05), a
19.5% relative improvement in healthy nutrition adherence (p-
value = <0.001), contributing to a 12.1% relative improvement in
perception of overall health (p-value = <0.05). These values are
summarised in Table 3, with an interval plot mapping
improvement for this cohort in Graph 3.
Gender analysis across both the full cohort and limited cohort
of MU, HU and RU only found no statistically significant
differences in health aspect improvements.
TABLE 3: Health factor improvement
Domain
1
2
P-value
Overall
0.6864
0.769725
<0.05
Sleep
0.66875
0.75225
<0.05
Exercise
0.6075
0.70825
<0.05
Nutrition
0.629375
0.7522
<0.001
Overall - General perception of health, 1 - First measurement, 2 -
Second measurement.
GRAPH 3: Health factor change for MU, HU and RU combined
Interval plot - individual standard deviations used to calculate intervals.
Overall - General perception of health, 1 - First measurement, 2 -
Second measurement.
Regression analysis
Predictors of resilience improvement was investigated through
regression analysis across variables. Usage provided a
statistically significant positive relationship to improvement in
post-PR6 measurement (R-sq = 11.55%, p-value = <0.001).
Further, starting PR6 score provided an unexpected predictor of
resilience improvement, displaying an inverse relationship to
improvement in resilience scores (R-sq = 15.12%, p-value =
<0.001).
Multiple regression combining usage ratio and starting PR6
scores provided the strongest prediction of improvement,
showing R-sq = 24.52% (p-value = <0.001). Further improvement
in multiple regression R-sq of starting PR6 and usage ratio was
possible through removal of NU and LU, providing an R-sq of
35.97%. Controlling by gender or removal of C4 did not yield any
further improvement in prediction model accuracy.
Individual domain starting scores were investigated for
predictive properties regarding overall improvement. Multiple
regression combining Reasoning starting score and Usage ratio
provided a slightly higher R-sq (25.7% compared to 24.52% for
PR6 multiple regression) for the overall prediction in
improvement, however a lower R-sq(pred) = 13.5% value
indicates potential over-fit of this model to this dataset. The
overall PR6 score consisting of all domains provide a more
robust assessment tool that allows for greater generalisability
across various cohorts.
DISCUSSION
Results support the hypothesis that completion of more
microtasks facilitated greater improvement in resilience and
long-lasting behavioural change. Results also support a
conclusion that Driven provides a valid pathway to enhance
resilience capacity through a digital virtual coaching format
using microtasks as a daily intervention approach. The NU and
LU groups served as control groups for comparison, showing no
significant change in resilience compared to the higher usage
groups (MU, HU and RU). Within these usage groups, it was
evident that higher usage predicted greater improvement in
resilience capacity.
Regarding the mechanistic functioning of microtasks, analogous
functioning has been found elsewhere in human physiology. For
example, the finding the high-intensity interval training (HIIT),
which involves short bursts of physical exercise, has greater fat
burning capabilities than endurance training (Astorino &
Schubert, 2014)
89
, and results in an increased metabolic rate for
24 hours after training (Treuth et al, 1996)
90
. Given the
similarities in extended neural change following short bursts of
learning, perhaps a way to think of this is that the microtask
concept delivered through Driven is like HIIT for the brain.
The PR6 resilience psychometric showed strong internal
consistency with both pre and post intervention assessments,
supporting its use as a resilience diagnostic tool. This follows
our previous validation results within organisational use
(Rossouw et al, 2017)
91
. Improvements in domain scores showed
Driven had particular strength in helping individuals improve
stress management, gain a sense of purpose, and improve
various physiological health aspects. Within the Health domain,
we noted improvements in exercise frequency,
While the hypothesis of increased completion of microtasks
would lead to an increase in resilience is shown to be valid, this
study revealed an unexpected relationship between initial PR6
starting score and subsequent improvement. Indeed, we see that
receiving a lower initial score predicts a greater level of
participation and subsequent improvement.
This finding is significant, as it indicates that those in most need
of resilience improvement are indeed the ones that participate
the most in the program, and therefore improve the most. In
effect, Driven helps those who need it most. This may stem from
an ‘awareness effect’, as each participant received a resilience
report that indicated their current level of resilience. Once
aware of their status of being below employee benchmarks, this
may then spur interest within the individual to persist with the
program and improve.
We hypothesise that these individuals may already be aware
that their resilience isn’t at a preferred level, and the receipt of
a report then triggers an initiative to improve. This effect,
combined with instant access to a relevant training program (in
this case, Driven) that provides a methodology to build
resilience, appears to presents the right opportunity at the right
INTERNATIONAL JOURNAL OF NEUROPSYCHOTHERAPY Volume 7 Issue 2 - July 2019
Rossouw, J. G., Erieau, C. L., & Beeson, E. T. (2019). Building resilience through a virtual coach called Driven: Longitudinal pilot study and the
neuroscience of small, frequent learning tasks. International Journal of Neuropsychotherapy, 7(2), 2341. doi:10.12744/ijnpt.2019.023-041
time to lead to completion persistence and eventual lasting
improvement.
Capitalising on this effect can yield significant improvements in
population health through broader applications in government,
large organisations and insurance formats to reach wider
audiences to providing help to those who need it. As a
preventative approach to mental and physical health, Driven
demonstrates a scalable intervention that may be applied to
broad effect.
Gender differences
Higher stigma in males appear to start in early life (Chandra &
Minkovitz, 2006)
92
, carry through as students (Eisenberg et al,
2006)
93
, and persist into adulthood (Corrigan & Watson, 2007)
94
.
This phenomenon may influence studies that recruit volunteers
for intervention research in mental health, skewing results
towards that experienced by females which appear naturally
more interested in engaging with and implementing new
psychological strategies.
Results found in this study noted that, indeed, females improved
more than males while using the course. However, participation
and usage rates between males and females did not differ
significantly. Thus, we note as a strength of this cohort broader
male participation to provide insight into organisation-provided
tools relating to mental health. Here it may well be the
application of a novel and fully confidential digital tool that
enables males to increase self-disclosure, which has long been
indicated as a strength of digital interventions (Weisband &
Kiesler, 1996)
95
.
Limitations
The only psychometric test used in this review was the PR6,
while additional testing in future would provide additional
insight into impact on depression, stress, anxiety, and other
mental health disorders. Mitigating this limitation is extensive
existing research that links resilience as a valid strategy to
manage these mental disorders (Edward, 2005; Masten et al,
2009; Rutter, 1995; Stoffel & Cain, 2018)
96
,
97
,
98
,
99
.
Conducting randomised controlled trials that include broader
psychometric assessments is a potential next step to continue
validation of the program an investigate applicability as a digital
intervention for common psychological disorders.
Real world generalisability
In the views of the authors, these results are significant as they
include a cohort that did not participate out of explicit interest
to be part of research, but instead shows a real-world application
within organisations interested in improving the resilience of
employees. This means that participants were not encumbered
by any potential perceptual influences or performance anxiety
due to research oversight, but rather is subjected only to the
influences that can be expected by the default application of this
program within organisations. We believe this research to
therefore show results that can be more widely replicated as a
result.
Furthermore, as a longitudinal study that include pre and post
assessments of an intervention that lasted over 6 months, we see
potential for sustained improvements that can lead to long-term
benefits for employees, employers, and in personal and clinical
settings. The authors note that comparable research in the field
of digital interventions (particularly chatbots) tend to be shorter
in nature, and therefore requires more longitudinal research to
validate results
100
. We therefore see the length of this study as a
strength to confirm that the Driven resilience program can
indeed assist in improving resilience over a longer timeframe,
potentially mitigating or preventing the formation of
depression, anxiety or stress through improvements across the
six resilience domains.
Declaration of interest
Jurie Rossouw is a director of Hello Driven Pty Ltd, alongside
Chelsea Erieau who is an employee of Hello Driven Pty Ltd. Dr
Eric Beeson serves at The Family Institute at Northwestern
University.
Cite as: Rossouw, J. G., Erieau, C. L., & Beeson, E. T. (2019).
Building resilience through a virtual coach called Driven:
Longitudinal pilot study and the neuroscience of small, frequent
learning tasks. International Journal of Neuropsychotherapy,
7(2), 2341. doi:10.12744/ijnpt.2019.023-041
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