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Using an AI memory game to detect depression and anxiety in older Brazilians

Transferability of n-back task biomarkers in ai mental health models to old-age Brazilian population

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ISRCTN
Registry ID
ISRCTN90727704
Enrollment
100
Registered
2023-11-10
Start date
2023-01-11
Completion date
Unknown
Last updated
2025-02-10

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Depressive and anxiety symptoms screening in an elderly Brazilian population (service users of a private health care provider). They may have multiple physical health comorbidities. Mental and Behavioural Disorders

Interventions

For this study, participants will take part in a series of short online activities, some of which will be repeated at regular intervals (twice a week) for 6 months. The activities can be completed on
2. Thymia research questionnaires used to gather more context and information to further develop the thymia AI model [not part of the current clinical trial]. These include a tiredness questionnaire,

Sponsors

thymia Limited
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. Over 50 years of age 2. Receiving ongoing health support via a private healthcare route at Lacos Saude 3. Normal or corrected-to-normal vision 4. Normal or corrected hearing 5. Able to read, understand, and sign the Informed Consent Form 6. Access to a laptop, smartphone, tablet, or other device and able to use them 7. Willingness to be recorded

Exclusion criteria

Exclusion criteria: 1. Under 50 years of age 2. Not receiving ongoing health support via a private healthcare route at Lacos Saude 3. No normal or corrected-to-normal vision 4. No normal or corrected hearing 5. Not able to read, understand, and sign the Informed Consent Form 6. No access to a laptop, smartphone, tablet, or other device and/or not able to use them 7. No willingness to be recorded

Design outcomes

Primary

MeasureTime frame
Measured using the thymia platform via the participant’s laptop or smart device twice a week for 6 months: 1. Area Under the Curve (AUC), specificity and sensitivity of the AI models (depression and anxiety). These are standard machine learning evaluation metrics that will help establish the performance and accuracy of a model trained on a set of data can predict accurately in an entirely new set of data collected in a clinical and completely new context. 2. PHQ-8 and GAD-7 to measure anxiety and depression

Secondary

MeasureTime frame
Measured using the thymia platform via the participant’s laptop or smart device twice a week for 6 months: 1. Average reaction time 2. Average omission errors 3. Average false positive rate (commission errors) 4. Average precision 5. Average recall from the n-Back game (1-Back and 2-Back)

Countries

Brazil

Contacts

Public ContactAlexandra-Livia Georgescu
alexandra@thymia.ai+44 7533848443

Outcome results

None listed

Source: ISRCTN (via WHO ICTRP) · Data processed: Feb 4, 2026