Anxiety, Depression - Major Depressive Disorder
Conditions
Keywords
machine learning, depression, anxiety, speech analysis
Brief summary
Major depressive disorder (MDD) and anxiety are increasingly prevalent among university student populations, yet early detection remains reliant on psychometric instruments tied to diagnostic criteria (e.g., PHQ-9, GAD). Emerging evidence suggests that depression affects both the acoustic properties and content of speech, making speech analysis a promising candidate as a digital biomarker for early screening. This study evaluates the validity of acceXible, a speech-based machine learning platform, for the detection and monitoring of depression and anxiety in the student population of the Universidad Autónoma de Querétaro, Mexico. AcceXible captures spontaneous speech through open-ended interview tasks and applies automated acoustic and linguistic analysis. The primary objective is to evaluate the validity of the acceXible spontaneous speech analysis system for depression and anxiety screening, assessed against the PHQ and GAD scales as reference standards. Secondary objectives include examining associations between speech-derived variables and other study measures, evaluating participant engagement with digital mental health resources, assessing user satisfaction with the platform, and analyzing longitudinal changes in scores across follow-up assessments.
Interventions
DEVICEAccexible
Speech analysis
Sponsors
Accexible
Universidad Autónoma de Querétaro
Study design
Observational model
OTHER
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
16 Years to 25 Years
Healthy volunteers
Yes
Inclusion criteria
* Provision of voluntary written informed consent * Age 16-25 years * Current enrollment at BUAP * Spanish language proficiency * Access to a mobile device with internet connectivity * Ability to understand and follow basic acceXible usage instructions
Exclusion criteria
* Refusal to participate * Psychomotor agitation * Sensory impairment (visual or auditory) * Cognitive impairment
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Diagnostic accuracy of acceXible for depression and anxiety screening | Baseline | Sensitivity, specificity, and positive predictive value of the acceXible speech analysis system relative to validated Spanish-language versions of the PHQ-9 and GAD-7 as reference standards. Sensitivity is defined as the probability of correctly classifying a participant with abnormal scores; specificity as the probability of correctly classifying a non-affected participant; and positive predictive value as the probability that a participant flagged by acceXible truly meets criteria for depression or anxiety. |
Countries
Mexico
Contacts
CONTACTDra. Olga Patricia García Obregón
Outcome results
None listed