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La salud de la mujer / Woman's Health

19 Abril 2007

¿Tiene depresión?... navegue por internet

La depresión es uno de los estados más frecuentes y peor diagnosticados... pero unos investigadores taiwaneses han diseñado un programa para diagnósticar la depresión online. En internet existen páginas web con información muy interesante sobre la depresión: Bluepages desde Australia, pero hay otras muchas sobre "Blue" un término asimilado a depresión, melancolía o tristeza.

Chao-Cheng Lin y otros colegas desarrollaron un programa de autoevaluación por internet. Entre septiembre de 2001 y enero de 2002 reclutaron 579 personas a través de un portal muy popular. Los voluntarios recibieron un email tras completar el primer cuestionario para visitar un psiquiatra.

Los resultados del primer test dieron 31% de participantes con trastornos depresivos mayores, 7% con un trastorno depresivo menor, 15% tenían algún síntoma depresivo que no permitían el diagnóstico de depresión, y 46% no tenían depresión.

Cuando se analiza los resultados de la entrevista personal con el profesional se comprueba que existe una alta coincidencia entre el test online y el diagnóstico clínico. La coincidencia fue menor para los trastornos depresivos menores, posiblemente porque no es un diagnóstico estable. El seguimiento por el psiquiatra demostró que el test online fue correcto en el 75% de los casos.

En cuanto a los efectos de internet sobre la depresión es muy recomendable el artículo publicado en el suplemento de salud de El Mundo.


BMC Psychiatry. 2007 Apr 10;7(1):12 [Epub ahead of print]
Click here to read
Web-based tools can be used reliably to detect patients with major depressive disorder and subsyndromal depressive symptoms.

Lin CC, Bai YM, Liu CY, Hsiao MC, Chen JY, Tsai SJ, Ouyang WC, Wu CH, Li YC.

ABSTRACT: BACKGROUND: Although depression has been regarded as a major public health problem, many individuals with depression still remain undetected or untreated. Despite the potential for Internet-based tools to greatly improve the success rate of screening for depression, their reliability and validity has not been well studied. Therefore the aim of this study was to evaluate the test-retest reliability and criterion validity of a Web-based system, the Internet-based Self-assessment Program for Depression (ISP-D). METHODS: The ISP-D to screen for major depressive disorder (MDD), minor depressive disorder (MinD), and subsyndromal depressive symptoms (SSD) was developed in traditional Chinese. Volunteers, 18 years and older, were recruited via the Internet and then assessed twice on the online ISP-D system to investigate the test-retest reliability of the test. They were subsequently prompted to schedule face-to-face interviews. The interviews were performed by the research psychiatrists using the Mini-International Neuropsychiatric Interview and the diagnoses made according to DSM-IV diagnostic criteria were used for the statistics of criterion validity. Kappa values were calculated to assess test-retest reliability. RESULTS: A total of 579 volunteer subjects were administered the test. Most of the subjects were young (mean age: 26.2 +/- 6.6 years), female (77.7%), single (81.6%), and well educated (61.9% college or higher). The distributions of MDD, MinD, SSD and no depression specified were 30.9%, 7.4%, 15.2%, and 46.5%, respectively. The mean time to complete the ISP-D was 8.89 +/- 6.77 min. One hundred and eighty-four of the respondents completed the retest (response rate: 31.8%). Our analysis revealed that the 2-week test-retest reliability for ISP-D was excellent (weighted kappa = 0.728). Fifty-five participants completed the face-to-face interview for the validity study. The sensitivity, specificity, positive, and negative predictive values for major depressive disorder were 81.8% and 72.7%, 66.7%, and 85.7% respectively. The overall accuracy was 76.4%. CONCLUSIONS: The evidence indicates the ISP-D is a reliable and valid online tool for assessing depression. Further studies should test the ISP-D in clinical settings to increase its applications in clinical environments with different populations and in a larger sample size.

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