Self-management of stress reduction in daily live of individuals with ASD with normal and above average-gifted IQs

Autism spectrum disorders (ASD) are life-long developmental disorders
characterized by social and communication impairments and restricted patterns
of behaviour and interests (American Psychiatric Association, 2013). Due to
their specific characteristics, especially their highly negative impact on the
ability to establish social relations, ASD often lead to poor social adjustment
and poor long-term outcomes with respect to independent living. This is true
even in high-functioning individuals with ASD, i.e. those without intellectual
disabilities Also, people with ASD experience high levels of stress, which
hinders their performance, and negatively affects their quality of life (QoL).
Subjective QoL has been demonstrated to be lower in individuals with ASD than
in the general population. Furthermore, it has been found that individuals with
Asperger syndrome (one of the disorders grouped within ASD) were more likely to
report depression, suicidal ideation, suicide plans and attempts compared not
only to the general population, but also to those with medical or psychic
illnesses ASD may increase the risk of experiencing stress and impair the use
of effective coping methods. since diffculties in social relations resulting
from autistic traits may hinder the use of coping styles that involve seeking
support from others.

In short, there is a need for real-time support of people with ASD in
setf-managing their stress in their daily life. Existing signalling schemes, a
solution for individuals without ASD, are not applicable to this target group.
This is because individuals with ASD lack the capability to proactively act
upon such schemes. They need more support in the self-management of their
stress. Another solution for real-time support of individuals with ASD may be
offered by means of a mental health application. There is a wide array of
mental health applications available, but recent review studies showed that the
majority these apps lack scientific evidence about their effcacy. For
individuals with ASD, who need specific ways of communication and
visualisation, multiple apps are available that help them engage in social
contact and that offer ready-made or do-it-yourself visual schedules for daily
living tasks and time management (e.g. AutThere, Daymate, Psymate). However,
none of the available digital tools developed for individuals with ASD focus on
supporting proactive self-managing of stress in daily lives. Other measurement
techniques such as heart rate and blood pressure are still not accurate enough
to incorporate in stress monitoring health apps. To conclude, further research
is required to develop and test evidence-based supportive mental health apps
for individuals with ASD.
The current project aims to develop knowledge and algorithms that can be used
in a mobile application that supports individuals with ASD in proactively
self-managing their stress in real time. The focus in treatment of individuals
with ASD should be on developing the ability to adapt to and self-regulate
daily stress levels This approach is based on the positive health movement that
defines health not as the absence of illness but as the capability to cope with
health impaiments.

The main objective of this study is to develop a prototype mobile apllication
to help patients with ADS (normal and above avarege IQ) to detect stress in
daily life. The application will not only detect stress, but will help the
patient to react o this stress. The use of this apllication will reduce stress
and as a consequence generate a better quality of life.

Phase 1: Preparation FINISHED
The design of the application and the communication in the application will be
tailored to individuals with ASD. In this phase, we explore general needs and
requirements with respect to the application by desk research, interviews and
focus groups (for a complete overview of study procedures in the co-creation
study phases see Table 1). First, we will discuss needs and requirements in a
2-hr focus group with a minimum of 5 practitioners. Second, we will conduct
30-minutes interviews with each of the 15 participating clients together with
their formal caregiver, to further discuss needs and requirements

Phase 2: Prototype development NEARLY FINISHED
In this phase, we focus on developing the prototype design and the content. The
application should be able to detect stress and provide real time feedback
adapted to individuals with ASD. To be able to detect stress and provide
feedback, we first develop a 'generic detection plan'. We determine stress
levels and corresponding behaviour (changes) and helpful stress coping
behaviours for different stress levels. The generic detection plan will be
based on desk research and two focus groups of 2 hours with practitioners,
informal caregivers and with experts in the field of stress detection. Second,
we will develop individual detection plans for ea&l of the 15 participating
individuals with ASD based on 30-minutes interviews with the individuals and
their formal caregivers.
We will then translate the stress behaviours, and behaviour changes into items
that can be measured using Ecological Momentary Assessment (EMA; Stone &
Shiffman, 1994, Shffman, Stone & Hufford, 2008). EMA is a proven method for
self-monitoring that consist of *the collection of self-reports or indices of
behaviour, cognition, or emotions in near real time in the daily lives of the
participants, ideally with electronic devices" (Trull & Ebner-Priemer, 2009).
With EMA, we are able to digitally collect daily life momentary assessments of
stress behaviour (changes) in relation to momentary context and activity. We
will select existing (items from) scales that measure stress complaints and
develop questions that focus more on individual behaviour that clients show at
the different stress levels. Scores to those items and / or scales will be
related to the different stress levels. The selection of appropriate items and
lor scales will be based on desk research and close consultation with
practitioners and informal caregivers of the selected fifteen individuals with
ASD and with experts in the field of stress detection.
With respect to the prototype design, we will develop a monitoring instrument
based on EMA that can be used for daily monitoring of stress. To provide
clients with information conceming their stress levels, we will develop expert
infomed algorithms to translate the scores on the EMA items into relevant and
accurate feedback We will imbed this algorithm in the EMA application to enable
the app to provide a feedback signal to the client in real time when stress
levels are rising. What kind of signal is given depends on the defined needs
and requirements and the technical options (e.g. visual, auditory, vibration,
etc). To assist dients in dealing with stress, a function will be developed
that can tie specific advices from the individual detection plans to different
stress levels for each participating individual. This function will be imbedded
into the app to be able to provide real time suggestions for stress reduction
after a stress signal is given. Furthermore, in this phase the communication
form of the EMA application will be specifically tailored to individuals with
ASD (and normal IQs).

Phase 3: Pilot SUBMISSION INCLUDES PHASE 3-5
In the pilot phase, we will test the developed EMA application. The 15
individuals with ASD will be asked to use the app for a period of one week.
Subsequently, we will evaluate the process and tie usability by using both
objective compliance data (e.g. entry completion) and 30-minutes interviews
with the 15 participating individuals with ASD and their formal caregivers (and
if needed with a focus group with informal caregivers). In t*te interviews we
focus on user-friendliness and EMA interference . Based on the outcomes of this
evaluation, we will further tailor the design and content of the application to
the target group.

Phase 4: Implementation
Using a multiple, or aggregated, systemic N = 1 approach means t-vat we will
follow several individuals with ASD who belong to the target group and compare
the results of each individual. The target group will consist of 15 case
studies (i.e. 15 individuals with ASD). We will aim for maximum variation
between these individuals with ASD to represent the current target group as
much as possible. These 15 partidpants will take part in the user-centered
design approach (phases 1-3) and will be asked to use the app for four
subsequent weeks (phase 4). During this period they will be supervised by their
caregiver in the use of the app. Questionnaires and observation checklists
regarding stress management of the participant will be administered among the
participant and his or her (in)formal network at three measurement moments:
before (baseline control condition). during
(intervention phase) and after (post-measurement) the 4th week use of the app.
The results of the 15 cases will be aggregated and compared

Phase 5: Evaluation
To determine intervention effectiveness (phase 5), we use an aggregated,
systemic single-case approadl. A single-case or N = 1 approach is a
client-oriented approach, in which behavioral change of a dient is compared to
earlier behavior of the same client rather than to norm groups. In other words,
the dient is his or her own *norm group". As such, this method can be used to
detect intra-individual effects of an intervention on behavioral change.The
systemic approach is expressed in tete role of the network Cthe circle') around
the client. This network can consist of both formal (involved practitioners)
and informal (family, neighbors, friends) network members. In a systemic N = 1
study, the network members of the client function as observers of the behavior
of the dient outside the subject-therapeutic setting. The dient and his or her
network members report changes at repeated measurement moments with validated
questionnaires. All parties involved report to what extent the clients behavior
has changed compared to the starting level of the same dient.

The use of the prototype of the mobile application which detects stress and
suggests behavioral interventions.

The app will ask questions about:
the state of mind / affect of the patient at the moment
a question about the patient's state of mind / affect in the past 3-4 hours
a question about stress signals in the last 3-4 hours: behaviors / thoughts /
physical complaints of the patient during the last 3-4 hours (based on a
signaling plan made by the patient (and treatment provider) at the different
stress levels)
activities / context: what activities have you done in the last 3-4 hours? how
did you feel (affect) in those activities? who were you with where were you?

These questions are personalized based on the patients' own signals and will
not be the same for all patients
The app will ask the patient 4 times a day at a predetermined time (these are
personalized times and are different for each test subject) and these questions
will take 1 to 2 minutes at a time. At the end of each day, the app provides
personalized feedback about the day that has been. The patient has the option
to pause the app to postpone the questions for an hour and the patient has the
option to add an extra questionnaire moment with a diary function to write down
why.

Using the app, filling in the questions multiple times a day and getting
feedback=the intervention

A burden could be that individuals with ASD and their families have to invest
time into this project to get a tailor made application. A risk may be that the
individuals become more aware of the stressful things in their lives due to
participation in this project. This could negatively affect their state of
mind. On the other hand individuals get tools to cope with this daily stress
and the opportunity to improve their resilience and their coping strategies
with respect to daily experienced stress.
Patients will be asked during a period of seven moths to drop by for 7
interviews and 3 sessions in which they will fill in questionnaires. They also
will test the prototype of the application for one week. After their feedback
is processed they will work with the new version of the prototype for four
weeks.
We estimate the risks and burden as minimal.