A longitudinal digital study investigating how hormonal changes, adolescence, and life-course factors influence ADHD symptoms in women using remote monitoring technologies.

Attention-Deficit Hyperactivity Disorder (ADHD) has historically been under-recognised in girls and women. While ADHD was traditionally viewed as a childhood condition predominantly affecting boys, evidence now shows that the gender ratio becomes nearly equal in adulthood. However, little research has examined why many women first meet ADHD diagnostic criteria in adulthood.  

The study investigates ADHD in women across the life course, focusing on childhood detection gaps, adolescent symptom changes, and hormonal influences such as menstrual cycle fluctuations.  

Application domain: 
Mental health research and women’s health. 

Objectives 

The project aims to: 

• Identify childhood and adolescent risk factors that predict ADHD diagnosed in adulthood. 

• Examine changes in ADHD symptom trajectories during adolescence. 

• Investigate how hormonal fluctuations during the menstrual cycle affect ADHD symptoms and medication effectiveness. 

Research design 

Mixed-methods with longitudinal cohort analysis and remote digital monitoring. 

Study instruments 

• ADHD symptom assessments 

• Hormonal measures 

• Remote monitoring of behavioural and symptom changes. 

Challenge 

Several barriers exist in studying ADHD in women: 

Scientific challenges 

• ADHD symptoms often present differently in girls and women. 

• Diagnosis may occur decades after childhood symptoms emerge. 

Data challenges 

• Longitudinal monitoring across life stages. 

• Measuring symptom variation linked to hormonal cycles. 

Operational challenges 

• Recruiting women with ADHD for intensive monitoring. 

• Capturing high-resolution behavioural data outside clinical settings. 

Solution 

The research uses remote digital monitoring technologies and wearable devices to track behavioural and physiological patterns over time. 

Key components include: 

Data collection 

• Remote symptom reporting 

• Passive physiological monitoring via wearable sensors 

• Smartphone-based data capture 

Technologies 

• Wearable device integration (e.g., smart rings) 

• Mobile monitoring platform 

• Longitudinal data analytics 

Analytics 

• Longitudinal modelling 

• Regression analysis of symptom trajectories. 

Results 

Expected outputs include: 

• Identification of developmental risk factors for ADHD in women 

• Evidence linking hormonal fluctuations to symptom severity 

• Improved diagnostic understanding of ADHD across the female life course. 

Impact 

This research may: 

• Improve recognition and diagnosis of ADHD in girls and women 

• Inform personalised treatment approaches 

Advance digital monitoring approaches for psychiatric research.