# Memory Monitoring Recognition Test (MMRT), a new measurement of stimular source monitoring: Software and comprehension

## TL;DR

A new computerized test called MMRT helps evaluate reality monitoring, which is important for detecting early signs of schizophrenia.

## Contribution

The MMRT is a computerized tool for assessing reality monitoring with cross-platform accessibility and cloud-based data storage.

## Key findings

- The MMRT detects memory monitoring errors and tracks long-term and working memory performance.
- Preliminary results suggest the MMRT can identify early cognitive markers of schizophrenia.
- The tool uses open-source technology and is adaptable for various platforms.

## Abstract

Reality monitoring allows the evaluation and monitoring of reality through the assignment of information to internal or external sources, which is crucial to differentiate real events from imaginary ones. In schizophrenics, monitoring seems to be related to an error in the allocation processes, giving rise to false perceptions such as visual hallucinations, which are associated with a poor prognosis. This error can appear almost imperceptibly at an early age in life, making carrying out predictive or evaluation tests with paper and pencil unattractive. The computerization of technical resources that allow the monitoring of reality offers a new tool to evaluate the attribution process, in an effective and agile way and with easy understanding of cognitive deficits in a friendly environment.

Computerize the Memory Monitoring and Recognition Test (MMRT) evaluate reality monitoring through verbal memory tasks, improving its implementation, optimizing interaction with the user and perfecting the recording of memory errors that could indicate psychotic symptoms.

The MMRT was developed using Python and Kivy, facilitating the creation of cross-platform user interfaces. The test is structured in stages, allows voice accessibility for people with visual disabilities and provides comprehensive user management. The test data is stored in the cloud using MongoDB as the database system. Additionally, the software incorporates speech recognition using the gTTS library and generates a performance report in PDF format, documenting external, internal and global attribution errors.

The computerized version of the MMRT allowed the detection of specific errors in memory monitoring, as well as the performance of repeated measurements to evaluate long-term memory and working memory.

Preliminary applications suggest its usefulness in identifying early cognitive markers of schizophrenia, facilitating the measurement of reality monitoring through attribution errors. Developed with open-source technology and an interface adaptable to various platforms, the MMRT represents an accessible and efficient tool for psychological evaluation, with innovative potential in the study of reality monitoring.