A rapid screening test for depression in junior high school children
| Autor: | Hsien-jane Chiu, Hui-Ping Cheng, Wei-Che Huang, Chieh-Nan Lin, Wen-Jung Sun, Chien-Cheng Kuo, Ming-Shun Chung, Pesus Chou, Ying-Sheue Chen |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2011 |
| Předmět: |
Male
medicine.medical_specialty Time Factors Psychomotor agitation Adolescent media_common.quotation_subject education Screening tool Validity Rapid screening test Surveys and Questionnaires Insomnia Medicine Humans Psychiatry Suicidal ideation Disease burden Depression (differential diagnoses) media_common Medicine(all) Depressive Disorder Depressive Disorder Major lcsh:R5-920 business.industry Depression General Medicine medicine.disease Logistic Models Feeling ROC Curve Major depressive disorder Female medicine.symptom business lcsh:Medicine (General) School-based |
| Zdroj: | Journal of the Chinese Medical Association, Vol 74, Iss 8, Pp 363-368 (2011) |
| ISSN: | 1726-4901 |
| Popis: | Background Depression generates a remarkable disease burden. Early onset of depression in young people is associated with a poor prognosis. This has precipitated developing a screening instrument for early detection of depression in Taiwan adolescents. Methods We recruited 662 junior high school students who completed the Screening Test for Depression (STD) designed using diagnostic and statistical manual-IV diagnostic criteria of major depressive disorder for assessing depressive symptoms. The students were then interviewed by psychiatrists who used the Mini International Neuropsychiatric Interview-Kid to verify the validity of the soon-to-be-developed Rapid STD (RSTD). Multiple logistic regression analysis of the STD results was used to extract items for the RSTD. Results We extracted four items for the RSTD: “insomnia or hypersomnia”, “recurrent thoughts of death or recurrent suicidal ideation”, “feelings of worthlessness or excessive or inappropriate guilt”, and “psychomotor agitation or retardation”. Any two of the first three yielded the best-balanced algorithm for major depressive disorder, which had a sensitivity of 75.0%, specificity of 92.9%, positive predictive value of 28.6%, and negative predictive value of 99.0%. Any two of the four yielded the best-balanced algorithm for depressive disorders, which had a sensitivity of 71.4%, specificity of 92.0%, the positive predictive value of 33.3%, and the negative predictive value of 98.3%. Conclusion The RSTD, a 4-item tool for junior high school children, can be easily used to assess fluctuating risks of major depressive disorder and depressive disorders at any time. |
| Databáze: | OpenAIRE |
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