2. About Me
A Brief History
Case Study 1
Gazing of Infants Developing
Autism Spectrum Disorder
Case Study 2
Smartx Med Reminder
Python Project
SQL2Excel
JavaScript Project
To-Do List
Contact Details
How to Stay in Touch
3. ABOUT ME
- I am an aspiring UX researcher with experience in multiple
research methods
- Developing skills in Python, SQL, and JavaScript
- I was trained in Brain and Behavioral Sciences at Purdue
University and was involved in research projects for
Concordance Health Solutions and Purdue University
- In my spare time I enjoy going on new adventures with my
dog, Cooper, as well as riding my horse, Mr. Pickle.
- Enjoy my portfolio!
4. Case Study 1
I N F A N T S D E V E L O P I N G A U T I S M
5. Project Overview
Why complete this study? Parents and healthcare providers want to know as soon as possible
if a newborn child is at an increased risk for developing Autism, but it’s usually not diagnosable until
the child is at least 12-18 months old.
HYPOTHESIS:
Signs of autism can be earliest
detected with social gazes towards
faces, response times, and engagement.
Screening methods in the early stages of
symptom onset can allow for early
intervention before the full disorder
has developed
Two cohorts of infants
with high and low risk of
developing autism were
recruited and followed
between 6 and 36 months
of age
Cohort 1
Infant gazing was
recorded and coded during
each routine developmental
assessment
Cohort 2
Infant gazing was
recorded and coded during
play interaction
6. How I Contributed to the Research
- Cameras recorded each session with the children in both cohorts.
- I was responsible for coding the recorded videos of both cohorts, which included when
a child’s gaze was oriented on the examiner, and when the child’s gaze was focused on
other things
- The coding began when the child’s gaze was oriented to the examiner’s face, and was terminated
when the child looked away. When the child’s gaze was not focused on the examiner's face,
I was responsible for determining whether the gaze was toward objects in the room or
something else, and code the action appropriately.
- We used generalized mixed-effects models to analyze the coded behavior data, which included
comparing other coder’s data entry of the same video. This allowed us to examine
developmental trajectories.
Skills I gained:
1. Observational user study
2. Coding video data
3. Data analysis of video data
7. The Results
- The screening methods used in this research incorporated a trajectory-based approach, which was able to
identify children in the early stages of developing autism. This could also potentially allow children who might
not yet meet criteria for a full diagnosis of ASD to be identified as likely to benefit from early intervention.
What could have gone better?
Although we used mixed methods, there was still human error when coding such small and complicated facial
movements. This could lead to skewed results as each individual coder may have interpreted the video/data
differently.
.
https://pubmed.ncbi.nlm.nih.gov/33615438/
Child’s gaze to a face in minutes vs age
Group A: Cohort 1 Group B: Cohort 2
Red line: estimated trajectory for
Autism Spectrum Disorder (ASD)
Blue line: Children with low risk of
developing Autism
Grey line: Children with high risk of
developing Autism
9. Project Overview
What was done to overcome this problem?
The Smartx Med Reminder system was created to encourage its users to take their medication
daily, as well as monitor how they were doing. It includes electronic caps that fits standard
prescription drug bottles, a smartphone app that communicated with the caps, and an online
cloud platform that kept tabs on drug usage, sent out reminders, and provided guidance.
Many people don’t
take their medication
consistently, even if it’s
vital to their health and
survival
WHY?
1. Busy lifestyles
2. Multiple prescriptions that lead
to confusion
3. Medical conditions that cause
memory or physical impairments
10. Target Demographics
While there was no set age, there was an eligibly checklist that was followed when
recruiting.
Subjects had to meet one or more of the following:
1. Taking multiple
different medications
daily
2. A condition where it
was difficult to
remember taking
medication (Alzheimer's,
ADHD, etc.)
3. Taking heart related
medication (Lisinopril,
Atorvastatin, Coumadin,
etc.)
Focus was put on participants taking heart related medication(s) as it was vital for them to be
taking it consistently for survival. Because of these specific qualifications, the population that
was recruited was shifted more towards the older generation.
11. How I Contributed to the Research
- I analyzed data for the project quantitatively, which included pulling and organizing the data
through MySQL on daily participant usage.
– I analyzed data qualitatively which included participant interviews and diary studies.
- I recruited participants, discovered the pain-points users were experiencing with the app and device,
what they liked, and what they would like to see changed.
Skills I gained:
1. User interviews/User recruiting
2. Diary studies
3. MySQL
4. Data analyzing and organizing
5. Data presenting
The SmartX Med Reminder app and vile cap. The app shows the last time the
participant took their medication, and when to take it next (app records when
the cap is taken off the vile via Bluetooth)
12. The Results
Participants who completed the study showed an overall
improvement in daily medication use and improvement in
health.
What could have gone better?
Many participants dropped the study because of complications
with the app being too complicated (see right) and the cap not
connecting well.
What are my goals in the future?
Because user experience is so vital, I want to take the next step
in future studies and create a more user-friendly platform based
on the research I gathered and target demographics. This would
make the project more successful and keep participants
engaged.
https://www.concordancehealth.com/?p=3
The SmartX Med Reminder app which at first glance
is very busy, especially for older individuals
14. Why I Chose This Project
I created Python code to automatically run the query against a MySQL data base and
put the results in an excel spreadsheet. I was doing this manually at Concordance
Health, which was time consuming and frustrating. While I am no longer working there,
this project can help current researchers who are in the same position.
Next step for this project?
I want to focus on learning and creating a front-end website where I can put
in a MySQL query and have the data be put into an excel sheet from there.
Below is my GitHub account to show more detail about the code:
https://github.com/allyscott15/SQL2excel
16. Why I Chose This Project
Below is my GitHub account to show more detail about the code:
https://github.com/allyscott15/To-Do-List
1
My weeks become
busy, and it’s easy
to forget about
tasks
2
I created code in
JavaScript for a to-
do list
3
The project has
simple web
design and user
interface
4
Next step for this
project?
5
Learning to make
the to-do list more
interactive and
aesthetically
pleasing to users
Additional things added:
- An “X” button that would appear next to each task that will remove the task when completed.
- When typing the task in the box, you can either use the add button, or click ”enter” on your
keyboard to add the task to the list.
17. Thank You!
Do you have any questions?
Please reach out and ask!
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