Synthetic Psychiatric Motor Activity Dataset

Dataset Features

• gender: Biological sex of the participant (Male/Female/Other).
• age: Age of the participant (string; may need type conversion).
• acc_time: Timestamp or period related to activity tracking (string).
• days: Duration of activity measurement in days (float).
• adhd: Binary indicator for Attention Deficit Hyperactivity Disorder diagnosis (0/1).
• add: Presence of Attention Deficit Disorder (Yes/No/Other).
• bipolar: Presence of bipolar disorder diagnosis (Yes/No/Other).
• unipolar: Presence of unipolar depression diagnosis (Yes/No/Other).
• anxiety: Presence of anxiety disorder (Yes/No/Other).
• substance: Substance use disorder (Yes/No/Other).
• other: Binary indicator for other psychiatric conditions (0/1).
• ct: Cognitive therapy history or indicator (Yes/No/Other).
• mdq_pos: Result of Mood Disorder Questionnaire (Positive/Negative/Null).
• wurs: Wender Utah Rating Scale score (float).
• asrs: Adult ADHD Self-Report Scale score (float).
• madrs: Montgomery–Åsberg Depression Rating Scale score (float).
• hads_a: Hospital Anxiety and Depression Scale – Anxiety subscore (float).
• hads_d: Hospital Anxiety and Depression Scale – Depression subscore (float).
• med: Current medication usage (e.g., None, Antidepressant, Stimulant).

Distribution

Usage

• Mental Health Research: Analyse correlations between motor activity and psychiatric symptoms.
• Predictive Modeling: Develop models for symptom severity or diagnostic classification.
• Digital Phenotyping: Study patterns of mental health using behavioural and questionnaire data.
• Clinical Training: Simulate psychiatric assessments using synthetic, privacy-safe data.

Coverage

License

Who Can Use It

• Psychiatrists and Clinical Psychologists: For condition modelling and digital phenotyping.
• Data Scientists and Mental Health Researchers: To build and validate analytical models.
• Educators and Students: As a realistic dataset for learning psychiatric data analysis.