Literature Retrieval: The current focus of ADHD research is primarily on children, with fewer studies devoted to adults In 2020, researchers Pan Wei et al. conducted a bibliometric analysis of adult ADHD literature from 2015 to 2019 using the Web of Science database, which found a total of 836 publications with no significant increase in the number of publications over the years, averaging 167 publications per year. Compared to the literature search excluding “adult” under similar conditions for ADHD, which yielded 9,911 publications, it suggests a predominant focus of ADHD research on children.
Characteristic Symptoms of Adult ADHD The analysis of the co-occurrence network for "adult ADHD" keywords shows that adults with ADHD not only exhibit symptoms of inattention, impulsivity, and hyperactivity, but also have a higher proportion of comorbidities with other disorders. Anastopoulos et al. found that college students with a confirmed diagnosis of ADHD have a high overall comorbidity rate, with 55.0% of patients having at least one comorbid diagnosis and 31.8% having two or more comorbid disorders. Taking the comorbidity study of ADHD-Learning Disability (ADHD-LD) reviewed by DuPaul et al. as an example, the average comorbidity rate of ADHD-LD is 45.1%. The comorbidity of adult ADHD can lead to the simultaneous manifestation of symptoms such as mood disorders, alcohol dependency, substance abuse, anxiety, and depression in patients, and in severe cases, even antisocial and criminal behaviors.
ConclusionConsidering these findings, the target population of the project is defined as adult ADHD patients, with the aim of providing them with auxiliary treatment methods for their symptoms. It is essential to note that the term "patients" may carry a negative connotation, and alternative descriptors can be explored to ensure a more positive and inclusive approach.
The table above compares and analyzes various demographic and clinical features of ADHD onset in childhood and adulthood, including body mass index (BMI), educational level, and evaluates lifetime major depressive disorder, bipolar disorder, and substance use disorder according to DSM-5 criteria. Additionally, researchers also assessed excessive daytime sleepiness in all patients using the Epworth Sleepiness Scale (ESS).
.User Research
Understanding User Interviewed two ADHD patients and empathized with and understood them through their daily lives.User 1Cora is a high school senior, diagnosed with ADHD less than two months ago. Lately her floating mind has caused her some trouble in her relationship with her parents, her classmates, and worst of all, with herself. She tells herself to get together every morning but ends up frustrated the same as the day before.
User 2 Kevin is 28 years old, diagnosed with moderate depression and ADHD a year ago.
It was figuratively hitting the bottom for Kevin at the end of last year. First he got laid off, then was asked to move by his landlady, and just when he thought it could not have got any worse than that, his parents got divorced.
Desktop Research.
How is ADHD diagnosed?
ADHD can only be diagnosed by a licensed clinician who interviews the parent or caregiver and/or patient to document criteria for the disorder (American Psychiatric Association, 2013; Chinese Society of Psychiatry, 2001; Faraone et al., 2015; Feldman and Reiff, 2014; Pearl et al., 2001; Stein, 2008; World Health Organization, 2018). It cannot be diagnosed by rating scales alone, neuropsychological tests, or methods for imaging the brain.
Which medications are safe and effective for treating ADHD?
As determined by governmental regulatory agencies around the world, several medications are safe and effective for treating ADHD symptoms as determined by randomized controlled clinical trials that typically study patients for several weeks. These medications, which are as efficacious, or more efficacious, than many medications used for non-psychiatric disorders (Leucht et al., 2012), are classified as either stimulants (methylphenidate and amphetamine) or non-stimulants (atomoxetine, extended release guanfacine, and extended release clonidine).
Which non-medication treatments are safe and effective for ADHD?
Many non-medical treatments have been proposed for ADHD. Most of those offered on the Internet have not been tested or have been shown not to be effective. Due to the way these therapies are implemented and recorded in the medical record, large scale naturalistic studies of longer-term outcomes are not possible. For instance, Behavioral treatments for ADHD are diverse in nature and have a different content and focus depending on the age of the patient. For adolescents and adults, therapy helps patients improve their organizational skills.
What is the economic burden of ADHD?
Given the many adverse outcomes associated with ADHD, it will come as no surprise to readers that these effects have a substantial economic cost to individual patients, families, and society. A systematic review of seven European studies of hundreds of thousands of participants estimated total ADHD-related costs in the Netherlands as €9860 to €14,483 per patient per year, with annual national costs more than €1 billion (Le et al., 2014).
.Research Conclusion
Pain
Points
Difficulty in Task Management: Both Cora and Kevin struggle with organizing tasks and managing time effectively due to their ADHD. They find it challenging to maintain a structured routine.
Memory Issues: Forgetfulness and memory lapses impact their daily lives, from forgetting important tasks to overlooking essential items needed for everyday activities.
Emotional Regulation: Managing emotions and mood swings is a significant concern. Both Cora and Kevin experience mood fluctuations that impact their daily functioning and relationships.
Social Stigma and Support Isolation: Feelings of isolation due to societal stigma around ADHD and challenges in finding a supportive community.
Information Overload on ADHD: Difficulty navigating through excessive information about ADHD treatments and lifestyle adjustments.
Task Manager with Visual Cues: An app that incorporates visual cues or timelines to break down tasks into smaller, manageable steps. It could use color-coded tags or progress bars to help users organize and prioritize tasks effectively.
Reminisce Nexus with Contextual Cues: Develop a system that not only alerts users but also provides context.
Emotional Regulation Tools: Create features that assist in emotional regulation, such as mindfulness exercises, mood tracking, or quick access to calming techniques like breathing exercises or guided meditations.
Social Stigma and Support Isolation: Feelings of isolation due to societal stigma around ADHD and challenges in finding a supportive community.
Personalized Therapy Paths: Implement an AI-driven feature to analyze user progress and tailor therapy recommendations, ensuring a more personalized and effective therapeutic journey. Integrate a feature that suggests cost-effective treatment options based on user preferences, location, and financial considerations.
Design Opportunities
Iterations.
Information Architecture
1st iteration 2nd iteration
.Final Concept
Main UI Sarah received a job offer during a cafe meetup with her former boss. She was asked to translate a Russian literature on gender equality within five days. This was a significant challenge for her, as she often struggled to concentrate. Therefore, she opened the Mindful Stride app and used its features to plan her daily tasks. Adding a new project
Adding project information
AI generation
Upon completing the task, Sarah opens her personal page to check her recent efficiency and focus. To her delight, she discovers that she has received numerous rewards!
Inspired by the popularity of mystery box culture, after user research, I believe that it can be a motivation allowing users to trade the points they earned from completing tasks for opportunities to open a mystery box.Personal page (1)
Personal page (2)
Personal page (3)
But actually, Sarah's day didn't start off very smoothly. In the morning, she tried to make coffee but ended up burning it and missed the bus. She recorded all of these incidents in her mobile app.
The FER + dataset enhances the original Facial Expression Recognition dataset by adding refined labels, including neutral and contempt, to the existing six emotions. The Single Shot Multibox Detector (SSD) model, using the lightweight RFB-320, detects faces efficiently for emotion recognition. This model, trained on WIDER FACE, is optimized for edge computing with high precision and low computational needs. A custom VGG13 architecture in the emotion recognition model classifies emotions in grayscale images, using convolutional layers, max pooling, dropout, and softmax output to effectively categorize eight emotions.
Experimental results of the facial emotion recognition algorithm.
In the afternoon, Sarah wanted to clean the bedroom. She remembered that the coffee at home was running out, so she went out to buy some coffee beans. Unexpectedly, when she returned home and opened the door, she saw a terrible mess in the living room. She couldn't remember what had happened, but she had a faint feeling that it was related to herself. So, she opened the app to retrace this incident.
After reconstructing the scene within the app,
Sarah finally remembered that she wanted to vacuum the carpet, but the coffee table was blocking her way. So she did something unexpected - she actually unscrewed one leg of the coffee table, causing the coffee cup to fall and shatter on the floor, spilling coffee everywhere. That's when Sarah remembered that she needed to go out to buy coffee. All of this truly made her laugh and cry at the same time! Luckily, she had this app; otherwise, she might have ended up causing a scene at the police station, which would have been embarrassing!
I implemented this part of the app in Unity. Below is a simple demonstration.
Before going to bed, Sarah reflected on the ups and downs of her day and decided to make an appointment to see a doctor tomorrow. She successfully scheduled an appointment and sent the doctor her recent emotional data and self-assessment report for review. After completing everything, Sarah slowly fell asleep and entered into a sweet dream.