Mental Health IssueNCT05495126
Evaluate Treatment Outcomes For AI-Enabled Information Collection Tool For Clinical Assessments In Mental Healthcare
A study testing Standard Limbic Access pathway and Limbic Access with AI pathway in people with Mental Health Issue, run by Limbic Limited at 1 site in United Kingdom.
Trial 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. Read more about this study
- Who is it for?
- Ages 16 years and older
- Conditions the study is for
- Mental Health Issue
- What is being tested?
- Standard Limbic Access pathway and Limbic Access with AI pathway
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 5,400 participants
- Where
- 1 siteUnited Kingdom
- Study dates
- 28 Feb 2023to 1 Dec 2025
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 16 years and older
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Who may be able to join
- Participant meets minimum age requirements for the service
- Participant's registered GP is within the IAPT CCG catchment area
Who cannot join
- Participants who are in crisis (defined by requiring urgent care or being at an urgent risk of harm)
Trial locations and contacts
1 site in 1 country.
About this study
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.
Read the detailed description
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.
The AI-system consists of a machine learning model which produces a probabilistic prediction about a patient's most likely presenting problems (ranking different diagnoses based on their probability) based on standard referral information collected through Limbic Access (e.g. free-text description of the patient's symptoms, GAD-7 \& PHQ-9 etc). Based on the ML prediction, up to two additional anxiety disorder specific measures (ADSM) will be administered in order to collect additional insights about the specific mental health symptoms experienced by the patient (i.e. tailored to the specific patient). The collected ADSM scores will be attached to the final referral information in order to support and facilitate the clinical assessment and ultimately improve the diagnosis process while saving clinical time. For this trial, the AI-model will only function as a support tool for the clinical assessment by collecting additional data ahead of time.
Specifically, the investigators are interested in evaluating whether the AI supported information collection improves treatment outcomes, reliability of clinical assessment, reduces waiting and assessment times as well as reduces treatment drop out rates.
- Conditions
- Mental Health Issue
- Being tested
- Standard Limbic Access pathway, Limbic Access with AI pathway
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Standard Limbic Access pathwayDiagnostic test
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.
Limbic Access with AI pathwayDiagnostic test
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.
| Study group | Role | What they receive |
|---|---|---|
| Standard Limbic Access | Active comparator | In this arm, participants will refer through the standard pathway of Limbic Access. During this process patients provide the minimal required information (e.g. demographic information) as well as some basic information about their experienced mental health symptoms (e.g. PHQ-9 \& GAD-7). This information is attached to the referral provided to the clinician before the clinical assessment. Receives: Diagnostic Test: Standard Limbic Access pathway |
| Limbic Access with AI | Experimental | In this arm, provide all information as in the standard Limbic Access pathway. Based on this information a machine-learning model is used to predict the most likely presenting problem, based on which up to two additional anxiety specific measures are administered in order to collect more tailored information about the patients' experienced mental health symptoms. All the information is attached to the referral provided to the clinician before the clinical assessment. Receives: Diagnostic Test: Limbic Access with AI pathway |
What is being measured
The primary outcome is the main question the study is designed to answer.
Change from baseline depression score to after treatment
The primary outcome will be defined as reliable and clinically significant improvement in clinical scores after treatment. Hereby, the investigators will test for changes in depression scores using Patient Health Questionnaire-9 (PHQ-9: posttreatment scores <10 and improved by ≥6 points). PHQ-9 includes 9 questions scored between 0 and 3, with higher scores indicating more severe depression.
Measured: The definition of reliable and clinically significant improvement is based on a comparison of pre-treatment (at time of referral, on the day of consenting) and post-treatment (assessed at point of discharge, an average of 5 months) clinical score.
Change from baseline anxiety score to after treatment
The primary outcome will be defined as reliable and clinically significant improvement in clinical scores after treatment. Hereby, we will test for changes in anxiety scores using Generalised Anxiety Disorder Assessment (GAD-7: posttreatment scores <8 and improved by ≥4 points).GAD-7 includes 7 questions scored between 0 and 3, with higher scores indicating more severe anxiety.
Measured: The definition of reliable and clinically significant improvement is based on a comparison of pre-treatment (at time of referral, on the day of consenting) and post-treatment (assessed at point of discharge, an average of 5 months) clinical score.
Change in diagnosis
Improved diagnosis will be measured as the correspondence between the diagnosis at the initial clinic assessment and the diagnosis at the end of treatment. During treatment in IAPT the diagnoses will be continuously assessed during the course of treatment in order to step the treatment up or down if needed. The agreement of diagnoses at these two time points will be coded as a binary variable ("agreement" versus "disagreement").
The investigators will measure the percentage of patients for which the diagnosis at clinical assessment corresponds to the diagnoses at the end of treatment as a measure for the reliability for the initial diagnosis
Measured: The agreement score will be based on a comparison of diagnosis at the initial assessment (before first treatment session) and the diagnoses at the end of treatment (assessed at point of discharge, an average of 5 months from referral).
Clinical assessment times
Improved clinical efficiency will be indicated by reduced assessment times, measured by the average time per clinical assessment (in minutes).
Measured: This measure will be available after the clinical assessment (up to average of 1 month from consenting).
Waiting times for assessment
Patient waiting times for assessment will be measured as the time between the date of self-referral and the date of the clinical assessment.
Measured: This measure will be available after the clinical assessment (up to average of 1 month from consenting).
Waiting times for treatment
Patient waiting times for treatment will be measured as the time between the date of assessment and the date of the first treatment session
Measured: This measure will be available after the start of treatment (up to average of 4 month from consenting).
Secondary outcomes (3)
Referral Dropout Rates
Patient referral dropout will be measured as any individual who consented to participate in the study, but did not complete all requested clinical information during the referral process.
Measured: During chatbot interaction (day 1)
Assessment Dropout Rates
Clinical assessment dropout will be measured as any cancellation or "Did Not Attend" event for patients who successfully had a clinical assessment slot (eg. time and date) organised. The treatment cohort (Limbic Access with AI pathway) will be evaluated against a cohort of patients going through limbic Access' standard pathway across the same services and over the same time window as the study will be used for comparison.
Measured: At time point of treatment termination using standard IAPT definitions (assessed up to 3 months)
Treatment Dropout Rates
Treatment dropout will be measured using a "dropout" label which is added to a patient's file in the service's patient management system by the treating clinician when a dropout event occurs. The treatment cohort (Limbic Access +AI pathway) will be evaluated against a cohort of patients going through limbic Access' standard pathway across the same services and over the same time window as the study will be used for comparison.
Measured: At time point of treatment termination using standard IAPT definitions (assessed up to 3 months)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted10 Aug 2022
- Study start28 Feb 2023
- Primary completion1 Sep 2025 (estimated)
- Study completion1 Dec 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Mental Health IssueStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind
- Who is masked
- Participant, Outcomes assessor
- Enrolment
- 5,400 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Limbic Limited
- Sponsor type
- Industry (pharma, biotech, devices)
- Collaborators
- Everyturn Mental Health
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05495126
- Sponsor's protocol ID
- Limbic-303303
- Status last verified
- Apr 2025
- First submitted
- 28 Apr 2022
- Last updated
- 8 Apr 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 8 Apr 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Evaluate Treatment Outcomes For AI-Enabled Information Collection Tool For Clinical Assessments In Mental Healthcare
- ClinicalTrials.gov ID
- NCT05495126
- Acronym / sponsor ID
- Limbic-303303
- Conditions
- Mental Health Issue
- Study type
- Interventional
- Recruitment status
- Active, not recruiting
- Enrolment
- 5,400 participants (estimated)
- Lead sponsor
- Limbic LimitedIndustry (pharma, biotech, devices)
- Collaborators
- Everyturn Mental Health
- Study start
- 28 Feb 2023 (actual)
- Primary completion
- 1 Sep 2025 (estimated)
- Study completion
- 1 Dec 2025 (estimated)
- First posted
- 10 Aug 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
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.
The AI-system consists of a machine learning model which produces a probabilistic prediction about a patient's most likely presenting problems (ranking different diagnoses based on their probability) based on standard referral information collected through Limbic Access (e.g. free-text description of the patient's symptoms, GAD-7 \& PHQ-9 etc). Based on the ML prediction, up to two additional anxiety disorder specific measures (ADSM) will be administered in order to collect additional insights about the specific mental health symptoms experienced by the patient (i.e. tailored to the specific patient). The collected ADSM scores will be attached to the final referral information in order to support and facilitate the clinical assessment and ultimately improve the diagnosis process while saving clinical time. For this trial, the AI-model will only function as a support tool for the clinical assessment by collecting additional data ahead of time.
Specifically, the investigators are interested in evaluating whether the AI supported information collection improves treatment outcomes, reliability of clinical assessment, reduces waiting and assessment times as well as reduces treatment drop out rates.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind (participant, outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Standard Limbic Access | Active comparator | Diagnostic Test: Standard Limbic Access pathwayIn this arm, participants will refer through the standard pathway of Limbic Access. During this process patients provide the minimal required information (e.g. demographic information) as well as some basic information about their experienced mental health symptoms (e.g. PHQ-9 \& GAD-7). This information is attached to the referral provided to the clinician before the clinical assessment. |
| Limbic Access with AI | Experimental | Diagnostic Test: Limbic Access with AI pathwayIn this arm, provide all information as in the standard Limbic Access pathway. Based on this information a machine-learning model is used to predict the most likely presenting problem, based on which up to two additional anxiety specific measures are administered in order to collect more tailored information about the patients' experienced mental health symptoms. All the information is attached to the referral provided to the clinician before the clinical assessment. |
Who may qualify
- Ages
- 16 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
Key inclusion criteria (2 listed)
- Participant meets minimum age requirements for the service
- Participant's registered GP is within the IAPT CCG catchment area
Key exclusion criteria (1 listed)
- Participants who are in crisis (defined by requiring urgent care or being at an urgent risk of harm)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Standard Limbic Access pathwayRelevant 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 | Standard Limbic Access |
| Limbic Access with AI pathwayThe 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. | Diagnostic test | Limbic Access with AI |
Primary outcome
Change from baseline depression score to after treatment
Time frame: The definition of reliable and clinically significant improvement is based on a comparison of pre-treatment (at time of referral, on the day of consenting) and post-treatment (assessed at point of discharge, an average of 5 months) clinical score.
The primary outcome will be defined as reliable and clinically significant improvement in clinical scores after treatment. Hereby, the investigators will test for changes in depression scores using Patient Health Questionnaire-9 (PHQ-9: posttreatment scores <10 and improved by ≥6 points). PHQ-9 includes 9 questions scored between 0 and 3, with higher scores indicating more severe depression.
Change from baseline anxiety score to after treatment
Time frame: The definition of reliable and clinically significant improvement is based on a comparison of pre-treatment (at time of referral, on the day of consenting) and post-treatment (assessed at point of discharge, an average of 5 months) clinical score.
The primary outcome will be defined as reliable and clinically significant improvement in clinical scores after treatment. Hereby, we will test for changes in anxiety scores using Generalised Anxiety Disorder Assessment (GAD-7: posttreatment scores <8 and improved by ≥4 points).GAD-7 includes 7 questions scored between 0 and 3, with higher scores indicating more severe anxiety.
Change in diagnosis
Time frame: The agreement score will be based on a comparison of diagnosis at the initial assessment (before first treatment session) and the diagnoses at the end of treatment (assessed at point of discharge, an average of 5 months from referral).
Improved diagnosis will be measured as the correspondence between the diagnosis at the initial clinic assessment and the diagnosis at the end of treatment. During treatment in IAPT the diagnoses will be continuously assessed during the course of treatment in order to step the treatment up or down if needed. The agreement of diagnoses at these two time points will be coded as a binary variable ("agreement" versus "disagreement"). The investigators will measure the percentage of patients for which the diagnosis at clinical assessment corresponds to the diagnoses at the end of treatment as a measure for the reliability for the initial diagnosis
Clinical assessment times
Time frame: This measure will be available after the clinical assessment (up to average of 1 month from consenting).
Improved clinical efficiency will be indicated by reduced assessment times, measured by the average time per clinical assessment (in minutes).
Waiting times for assessment
Time frame: This measure will be available after the clinical assessment (up to average of 1 month from consenting).
Patient waiting times for assessment will be measured as the time between the date of self-referral and the date of the clinical assessment.
Waiting times for treatment
Time frame: This measure will be available after the start of treatment (up to average of 4 month from consenting).
Patient waiting times for treatment will be measured as the time between the date of assessment and the date of the first treatment session
3 secondary outcomes
Referral Dropout Rates
Time frame: During chatbot interaction (day 1)
Assessment Dropout Rates
Time frame: At time point of treatment termination using standard IAPT definitions (assessed up to 3 months)
Treatment Dropout Rates
Time frame: At time point of treatment termination using standard IAPT definitions (assessed up to 3 months)
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 8 Apr 2025.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Standard Limbic Access pathway and Limbic Access with AI pathway in people with Mental Health Issue, run by Limbic Limited at 1 site in United Kingdom.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: under way, not looking for participants, as of the sponsor's last update on 8 Apr 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United Kingdom. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Change from baseline depression score to after treatment (time frame: The definition of reliable and clinically significant improvement is based on a comparison of pre-treatment (at time of referral, on the day of consenting) and post-treatment (assessed at point of discharge, an average of 5 months) clinical score.). The study lists 6 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 8 Apr 2025.