Adolescent Behavior, Distress, Emotional, Healthy, Suicide
Conditions
Keywords
Suicide Prevention, Distress, Emotional, Adolescent Behavior, Artificial Intelligence, Proteomics
Brief summary
The goal of this observational study is to validate an AI algorithm's capability to differentiate the population with suicidal ideation from a control population using various multimodal variables, including voice analysis, facial emotions, natural language, and proteomics data. The primary research question it aims to answer is: Is it possible to identify suicidal ideation and suicide risk in adolescents early and non-intrusively using multimodal data analysis through digital instruments equipped with artificial intelligence? Participants in this study will be asked to: Complete psychometric instruments to establish a gold standard for detecting suicide risk and suicidal ideation. Provide voice recordings, facial emotion data, and linguistic content in natural and specific contexts. Participate in salivary proteomics data collection. This study compares three distinct groups: Ideation: Adolescent patients with current suicidal ideation. Clinical Population: Psychological or psychiatric patients of the same age and gender without suicidal ideation. General Population: Adolescents without known psychological or psychiatric pathology of the same age and gender, without suicidal ideation. Researchers will compare these groups to determine if the AI algorithm is effective in differentiating individuals with suicidal ideation (Group 1) from both a clinical control group (Group 2) and a general population control group (Group 3) using the collected multimodal data. The study aims to assess the algorithm's ability to identify early signs of suicide risk in these distinct participant populations.
Detailed description
Introduction: The Surveillance of Suicide Ideation in Adolescents (VISIA) project is a collaborative effort involving a diverse research team encompassing experts in mental disorders and seasoned researchers in data science, specializing in intelligent services and applications across various domains. The project aims to address the shortcomings identified in existing research. The initial phase of this endeavor seeks to validate an artificial intelligence (AI) algorithm capable of distinguishing individuals with suicidal ideation from a control group by analyzing multimodal variables. These variables include voice analysis, facial emotions, natural language, and proteomics. The cases will be labeled following established protocols. Hypothesis: The primary research question driving this project is: Can early and non-intrusive identification of suicidal ideation and suicide risk in young adults be achieved using multimodal data analysis through digital instruments equipped with artificial intelligence? Objectives: The overarching objective of this proposal is to design and implement an automated system for detecting emotional distress and suicide risk in adolescents aged between 11 and 16 using AI. This detection relies on molecular profiles derived from salivary proteomics, video and audio recordings in diverse contexts, and the linguistic content generated by the study participants. The integration of molecular profiles with data from video and audio recordings promises enhanced detection capabilities, providing a competitive edge in the development of future diagnostic tools. Specific Objectives: To realize the goals outlined above and tackle the scientific and technological challenges, the following specific objectives are established: Development of a gold standard for detecting suicide risk and suicidal ideation in adolescents. Identification of biomarkers (e.g., voice, facial expressions, salivary molecular fingerprint) relevant to characterizing adolescents with regard to suicide risk. Identification of pertinent multimodal features for characterizing adolescents in relation to suicide risk. Labeling of samples and AI model training. Methodology: Design and Study Subjects: The study adopts a non-interventionist, analytical, observational, and prospective approach. It encompasses three distinct groups for comparison: Ideation: Comprising individuals with current suicidal ideation. Clinical Population: Consisting of psychological or psychiatric patients of the same age and gender, devoid of suicidal ideation. General Population: Encompassing adolescents with no known psychological or psychiatric issues, matched in age and gender, and free of suicidal ideation. All three groups will undergo assessments using psychometric instruments, serving as a gold standard for AI system training and validation. In summary, the VISIA project endeavors to leverage artificial intelligence and multimodal data analysis to detect suicidal ideation and suicide risk in adolescents, offering the potential for early and non-intrusive identification. The study's comprehensive methodology, involving diverse subject groups and rigorous data collection, is poised to contribute significantly to the field of mental health research and diagnostic tool development.
Interventions
None listed
Sponsors
University of Vigo
Complejo Hospitalario Universitario de Vigo
Complexo Hospitalario de Ourense
Fundacin Biomedica Galicia Sur
Servicio Gallego de Salud
Study design
Observational model
CASE_CONTROL
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
11 Years to 16 Years
Healthy volunteers
Yes
Inclusion criteria
Ideation Group * Participants must be between 11 and 16 years old. * Patients who do not meet any of the
Exclusion criteria
and whose parents (both), guardians, or legal representatives accept their voluntary participation in the study. In case of divorce, authorization from both parents will be required. * Patients receive care in child and adolescent psychiatry or psychology services and currently have suicidal ideation. * Patients may have a previous follow-up, as long as they have suicidal ideation at the present moment, or they may be new consultations and may be receiving pharmacological treatment (which will be documented in the study). Clinical Population Group * Participants must be between 11 and 16 years old. * Patients who do not meet any of the
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Proteomic and stress level analysis | through study completion, an average of 1 year | The collection of saliva is performed in a simple, non-invasive, and painless manner, allowing for the subsequent retrieval of high-quality proteins for further analysis and studies. |
| Strengths and Difficulties Questionnaire (SDQ) | through study completion, an average of 1 year | This questionnaire detects probable cases of mental and behavioral disorders in children and adolescents aged 4 to 17. A score \>19 points is considered positive in screening. |
| Mood and Feelings Questionnaire (MFQ) | through study completion, an average of 1 year | This questionnaire assesses symptoms of depression/suicide risk. Scores above 27 points are considered positive for screening. Higher values are indicative of worse outcomes. |
| Paykel Suicide Scale (PSS) | through study completion, an average of 1 year | This questionnaire asks about suicidal ideation over the past year. Scores equal to or greater than 4 are suggestive of suicidal ideation. Higher values are indicative of worse outcomes. |
| Facial microexpressions, voice and linguistic content analysis | through study completion, an average of 1 year | Participants will be asked to speak in front of a camera about their emotional state over the past week. The recording will have a minimum duration of 2 minutes and will be used for voice analysis, facial microexpressions, and natural language processing (NLP) for linguistic content analysis. Participants will also be asked to write a brief text on the computer in response to questions about how they perceive themselves and how they think others perceive them. The maximum duration for this exercise is 10 minutes. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Millon Adolescent Clinical Inventory - II (MACI-II) | through study completion, an average of 1 year | A self-report questionnaire developed to evaluate the psychological functioning of adolescents. It assesses three domains in adolescent development. The average completion time is 30 minutes and can be conducted in groups. |
| Problematic Internet Use Scale in Adolescents (EUPI-A) | through study completion, an average of 1 year | This 11-item questionnaire screens for problematic use of Internet among teenagers, ranginf fromm 0 to 44, with a cut-off for problematic use of 16 points. Higher values are indicative of worse outcomes. |
| European Bullying Intervention Project Questionnaire (EBIP-Q) and European Ciberbullying Intervention Project Questionnaire (ECIP-Q) | through study completion, an average of 1 year | This tool for jointly assessing bullying and cyberbullying cointains The European Bullying Intervention Project Questionnaire (14-items) and the European Cyberbullying Intervention Project Questionnaire (22-items), both of Likert nature that respectively evaluate behaviors related to bullying and cyber-bullying. Higher values are indicative of worse outcomes. |
Other
| Measure | Time frame | Description |
|---|---|---|
| Oviedo Response Infrequency Scale-Revised (INF-OV-R) | through study completion, an average of 1 year | Is a 10 items self-report measurement with a dichotomous response format (Yes/No) developed to detect those participants who respond randomly, pseudo-randomly, or dishonestly to the administered measuring instruments. The items on this scale are typically intermixed with questions and statements from other self-report measures that are administered together to o enable better detection. Higher values are indicative of random, pseudo-random, or dishonest answers. |
Countries
Spain
Outcome results
None listed