The Spanish validation of the Short Health Anxiety Inventory: Psychometric properties and clinical utility
Bibliographic record
Abstract
The Short Health Anxiety Inventory (SHAI) is a widely used self-report instrument to evaluate health anxiety. To assess the SHAI's factor structure, psychometric properties, and accuracy in differentiating Spanish non-clinical individuals from patients with severe health anxiety or hypochondriasis. A total of 342 community participants (61.6% women; Mage = 34.60, SD = 14.91) and 31 hypochondriacal patients (51.6% women; Mage = 32.74, SD = 9.69) completed the SHAI and other self-reports assessing symptoms of hypochondriasis, depression, anxiety sensitivity, worry, and obsessive-compulsive. The original two-factor structure was selected as the best structure, based on its parsimony and empirical support (Factor 1: Illness likelihood; Factor 2: Negative consequences of illness). Moreover, the Spanish version of the SHAI demonstrated good construct and concurrent and discriminant validity, and internal consistency. A cutoff of 40.5 (total score) accurately distinguished non-clinical individuals from patients with severe health anxiety or hypochondriasis. The SHAI is an adequate screening instrument to measure health anxiety in Spanish-speaking community adults. El Inventario Breve de Ansiedad por la Salud (SHAI, por sus iniciales en inglés) es un autoinforme ampliamente empleado para evaluar ansiedad por la salud. El objetivo es evaluar la estructura factorial del SHAI, sus propiedades psicométricas, y exactitud diferenciando entre población española no clínica y pacientes con hipocondría. Un total de 342 participantes extraídos de la población general (66% mujeres, Medad = 35, DT = 14,91) y 31 pacientes con hipocondría (51,6% mujeres; Medad = 32,74, DT = 9,69 completaron el SHAI y otros autoinformes de síntomas hipocondriacos, depresión, sensibilidad a la ansiedad, preocupaciones y obsesivo-compulsivos. La estructura de dos factores propuesta originalmente fue seleccionada como la mejor estructura debido a su parsimonia y soporte empírico (Factor 1: Probabilidad de enfermar; Factor 2: Consecuencias negativas enfermedad). La versión española del SHAI muestra una buena consistencia interna, y validez de constructo, concurrente y discriminante. El punto de corte de 40,5 (puntuación total) permite distinguir entre los individuos no clínicos y los pacientes con elevada ansiedad por la salud o hipocondría. El SHAI es un instrumento adecuado para la detección de ansiedad por la salud en población adulta hispano hablante.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".