Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/91231| Título: | Probability of major depression classification based on the SCID, CIDI, and MINI diagnostic interviews: a synthesis of three individual participant data meta-analyses |
| Autor(es): | Wu, Yin Levis, Brooke Ioannidis, John P. A. Benedetti, Andrea Thombs, Brett D. Figueiredo, Bárbara Tendais, Iva Alexandra Barbosa DEPRESsion Screening Data (DEPRESSD) Collaboration |
| Palavras-chave: | Depression Humans Mass screening Meta-analysis as topic Probability Psychiatric status rating scales Depressive disorder, Major Classification |
| Data: | 2021 |
| Editora: | Karger AG |
| Revista: | Psychotherapy and Psychosomatics |
| Citação: | Wu, Y., Levis, B., Ioannidis, J. P. A., Benedetti, A., Thombs, B. D., & DEPRESsion Screening Data (DEPRESSD) Collaboration. (2020, August 19). Probability of Major Depression Classification Based on the SCID, CIDI, and MINI Diagnostic Interviews: A Synthesis of Three Individual Participant Data Meta-Analyses. Psychotherapy and Psychosomatics. S. Karger AG. http://doi.org/10.1159/000509283 |
| Resumo(s): | Three previous individual participant data meta-analyses (IPDMAs) reported that, compared to the Structured Clinical Interview for the DSM (SCID), alternative reference standards, primarily the Composite International Diagnostic Interview (CIDI) and the Mini International Neuropsychiatric Interview (MINI), tended to misclassify major depression status, when controlling for depression symptom severity. However, there was an important lack of precision in the results. |
| Tipo: | Artigo |
| URI: | https://hdl.handle.net/1822/91231 |
| DOI: | 10.1159/000509283 |
| ISSN: | 0033-3190 |
| e-ISSN: | 1423-0348 |
| Versão da editora: | https://karger.com/pps/article/90/1/28/294733/Probability-of-Major-Depression-Classification |
| Arbitragem científica: | yes |
| Acesso: | Acesso aberto |
| Aparece nas coleções: | CIPsi - Artigos (Papers) |
Ficheiros deste registo:
| Ficheiro | Descrição | Tamanho | Formato | |
|---|---|---|---|---|
| 000509283.pdf | 202,63 kB | Adobe PDF | Ver/Abrir |
