CamCOPS

CamCOPS captures and manages structured assessment and experimental-task data for psychiatry, psychology, and clinical neuroscience research and clinical use.

Key Features:

• C++ client: A cross-platform C++ client supports deployment on mobile devices, tablets, laptops, and desktops.
• Online/offline data capture: Supports both online and offline (disconnected) data capture with local storage.
• Task support: Supports a wide range of tasks from simple questionnaires to complex animated experimental tasks.
• Encrypted storage: Client-side secure data storage using encryption.
• Encrypted transmission: Encrypted transmission of data to a dedicated CamCOPS server.
• Python server: Server component implemented in Python providing server-side data management.
• Clinical and research views: Server provides tailored clinical and research views and can track changes in data over time.
• Audit trail: Maintains an audit trail of data changes.
• Export and EHR integration: Export facilities with integration capabilities for primary electronic health record (EHR) systems.
• Access control: Access to structured data is controlled via authorization protocols.
• Multi-group support: Supports multiple research or clinical groups within a single server instance, each with its own identity policy.
• De-identification/pseudonymization: Supports storing data as fully identifiable, de-identified, or pseudonymized according to group policy.
• Intellectual property compliance: Incorporates mechanisms to enforce intellectual property rules for third-party tasks.
• Scheduling and remote testing: Facilitates task scheduling and remote/home testing.

Scientific Applications:

• Clinical assessment: Capture and synchronization of cognitive and psychiatric assessment data for clinical records and EHR integration.
• Experimental research: Administration and capture of questionnaire-based and animated experimental tasks for research studies.
• Longitudinal monitoring: Tracking changes in subject or patient data over time for longitudinal studies or clinical follow-up.
• Multi-group studies: Support for multi-group or multi-site studies requiring group-specific identity policies, de-identification, or intellectual property compliance.

Methodology:

Client-server architecture with a C++ client and Python server, using encrypted local storage and encrypted transmission, server-side audit trails, export facilities, authorization protocols, and support for de-identification/pseudonymization.