A comparison between the clinical significance and growth mixture modelling early change methods at predicting negative outcomes.
Psychother Res
; 29(7): 947-958, 2019 10.
Article
em En
| MEDLINE
| ID: mdl-29722613
ABSTRACT
Objective:
Routine outcome monitoring benefits treatment by identifying potential no change and deterioration. The present study compared two methods of identifying early change and their ability to predict negative outcomes on self-report symptom and wellbeing measures.Method:
1467 voluntary day patients participated in a 10-day group Cognitive Behaviour Therapy (CBT) program and completed the symptom and wellbeing measures daily. Early change, as defined by (a) the clinical significance method and (b) longitudinal modelling, was compared on each measure.Results:
Early change, as defined by the simpler clinical significance method, was superior at predicting negative outcomes than longitudinal modelling. The longitudinal modelling method failed to detect a group of deteriorated patients, and agreement between the early change methods and the final unchanged outcome was higher for the clinical significance method.Conclusions:
Therapists could use the clinical significance early change method during treatment to alert them of patients at risk for negative outcomes, which in turn could allow therapists to prevent those negative outcomes from occurring.Palavras-chave
clinical significance; cognitive behaviour therapy; empirical prediction; group psychotherapy; metodologia estatística; outcome research; pesquisa de resultados; previsão empírica; psicoterapia de grupo; significância clínica; statistical methodology; terapia cognitiva comportamental; åé«å¿çæ²»ç; 實徵é 測; ææç 究; çµ±è¨æ¹æ³; è¨åºé¡¯ èæ§; èªç¥è¡çºæ²»ç
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Satisfação Pessoal
/
Terapia Cognitivo-Comportamental
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Avaliação de Resultados em Cuidados de Saúde
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Autorrelato
Tipo de estudo:
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Adult
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Female
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Humans
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Male
Idioma:
En
Ano de publicação:
2019
Tipo de documento:
Article