Prevalence and Sociodemographic and Academic Factors Associated with Mental Health Problems in Spanish University Students
Bibliographic record
Abstract
There has been an increase of mental problems in university students word wile. We investigated the prevalence of common mental problems in students at a public Spanish university and their associated sociodemographic and academic factors. 2,862 students completed the Patient Health Questionnaire (PHQ, PHQ-9), the Generalized Anxiety Disorder (GAD-7), and sociodemographic and academic questions. Multivariate logistic regression models were used. 69.1% screened positively for at least one evaluated problem, with generalized anxiety disorder (48.9%) and major depressive disorder (47.4%) being the most frequent. 67.6% of individuals screened for at least one problem were at risk for multiple problems. Being female, gender minority, living with housemates, and being in the first-year of undergraduate studies was associated with an increased risk of at least one mental problem. Some factors associated with individual conditions varied across conditions. Studying health sciences was associated with a lower risk of major depression and being male was associated with a higher risk of alcohol abuse. Given the high prevalence of students at risk, preventive measures aimed especially at the most vulnerable groups are necessary. Se ha evidenciado un incremento de problemas mentales en estudiantes universitarios a nivel mundial. Hemos investigado la prevalencia de problemas mentales comunes en estudiantes de una universidad pública española y su asociación con factores sociodemográficos y académicos. 2862 estudiantes completaron en línea el Cuestionario de Salud del Paciente (PHQ, PHQ-9), la Escala para el Trastorno de Ansiedad Generalizada (GAD-7) y preguntas sociodemográficas y académicas. Se utilizaron modelos de regresión logística multivariados. El 69,1% presentaron al menos uno de los problemas evaluados, siendo el trastorno de ansiedad generalizada (48,9%) y el trastorno depresivo mayor (47,4%) los más frecuentes. El 67,6% de las personas con riesgo de sufrir un problema, tenían riesgo de sufrir múltiples problemas. Ser mujer, minoría de género, vivir con compañeros, cursar primer año de grado y estar al final del semestre estaba asociado a mayor riesgo de sufrir al menos un problema. Algunos factores asociados con un problema individual variaron según el problema. Estudiar ciencias de la salud tenía un riesgo menor de depresión mayor y ser varón un mayor riesgo de consumo de alcohol. Dada la alta prevalencia de estudiantes con riesgo, medidas preventivas dirigidas especialmente a los grupos más vulnerables son necesarias.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".