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Evaluate Treatment Outcomes For AI-Enabled Information Collection Tool For Clinical Assessments In Mental Healthcare

NCT05495126 · Status: ACTIVE_NOT_RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 5400

Last updated 2025-04-08

No results posted yet for this study

Summary

In the proposed study, the investigators aim to test an AI-prototype which adaptively collects information about a patient's mental health symptoms at the time of referral in order to support and facilitate the clinical assessment.

Conditions

  • Mental Health Issue

Interventions

DIAGNOSTIC_TEST

Standard Limbic Access pathway

Relevant information for clinical referral (e.g. demographics) and basic clinical information (e.g. PHQ-9 \& Gad-7 scores) are collected during the self-referral process which is then attached to the referral notes in order to facilitate the clinical assessment conducted by the clinician.

DIAGNOSTIC_TEST

Limbic Access with AI pathway

The same information as in the Limbic Access pathway is collected. However, additional information (i.e. disorder specific questionnaires) are collected for the most likely problem descriptors based on the ML-model predictions. All information is attached to the referral in order to facilitate the clinical assessment conducted by the clinician.

Sponsors & Collaborators

  • Everyturn Mental Health

    collaborator UNKNOWN

  • Limbic Limited

    lead INDUSTRY

Study Design

Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
DOUBLE
Model
PARALLEL

Eligibility

Min Age
16 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-02-28
Primary Completion
2025-09-01
Completion
2025-12-01

Countries

  • United Kingdom

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05495126 on ClinicalTrials.gov