Propiedades psicométricas del Inventario de Ansiedad de Beck (BAI, Beck Anxiety Inventory) en población general de México
Bibliographic record
Abstract
Una de las escalas más utilizadas para evaluar la ansiedad es el BAI ( Beck Anxiety Inventory ) que ha mostrado adecuadas propiedades psicométricas; sin embargo, no hay consenso sobre su estructura interna. Este trabajo tuvo como objetivo estudiar la estructura interna del BAI haciendo uso del Análisis Factorial Confirmatorio (AFC) por primera vez en México, así como la bondad de los ítems que la componen y su consistencia interna. Además, se presentan datos descriptivos de los niveles de ansiedad en población general de Michoacán (México). Se administró la escala BAI al mismo tiempo que se solicitaron datos sociodemográficos (sexo, edad, estado civil y escolaridad) a 1,245 personas adultas. Primero, se realizó un Análisis Factorial Exploratorio (AFE) con la mitad de la muestra; posteriormente, con la segunda mitad de la muestra y a través de un AFC, se pusieron a prueba los modelos factoriales obtenidos en estudios mexicanos previos, la solución unifactorial, así como el modelo obtenido en el AFE. Se observó una elevada consistencia interna de la escala total (α = .911); sin embargo, ningún modelo de los probados en el AFC resultó satisfactorio. Puede concluirse que el BAI, a pesar de mostrar una estructura interna inestable, es adecuado para evaluar la presencia de sintomatología de ansiedad en población general de Michoacán (México). Es importante señalar que hasta un 24.9% de la muestra presentó niveles de ansiedad moderada o severa. One of the most widely used scales to assess anxiety is the BAI (Beck Anxiety Inventory) that has shown adequate psychometric properties; however, there is no consensus on its internal structure. This work aimed to study the internal structure of the BAI using Confirmatory Factor Analysis (AFC) for the first time in Mexico, as well as the goodness of the items that make it up and its internal consistency. In addition, descriptive data of anxiety levels in the general population of Michoacán (Mexico) are presented. The BAI was administered and the sociodemographic data (sex, age, marital status, and education) were requested from 1,245 adults. First, an Exploratory Factor Analysis (EFA) was carried out with half the sample. Using the second half of the sample, the factorial models obtained in previous Mexican studies, the single factor solution and the model obtained in the AFE were tested through a CFA. A high internal consistency of the total scale was observed (α = .911); however, no model of those tested in the CFA was satisfactory. It can be concluded that the BAI, despite showing an unstable internal structure, can adequately assess the presence of anxiety symptoms in the general population of Michoacán (Mexico). It is important to note that up to 24.9% of the sample presented moderate or severe anxiety levels.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".