Cargando…
Predicting non-improvement of symptoms in daily mental healthcare practice using routinely collected patient-level data: a machine learning approach
OBJECTIVES: Anxiety and mood disorders greatly affect the quality of life for individuals worldwide. A substantial proportion of patients do not sufficiently improve during evidence-based treatments in mental healthcare. It remains challenging to predict which patients will or will not benefit. More...
Autores principales: | Franken, Katinka, ten Klooster, Peter, Bohlmeijer, Ernst, Westerhof, Gerben, Kraiss, Jannis |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10560743/ https://www.ncbi.nlm.nih.gov/pubmed/37817829 http://dx.doi.org/10.3389/fpsyt.2023.1236551 |
Ejemplares similares
-
Validation of the Mental Health Continuum‐Short Form and the dual continua model of well‐being and psychopathology in an adult mental health setting
por: Franken, Katinka, et al.
Publicado: (2018) -
Introduction of the generic sense of ability to adapt scale and validation in a sample of outpatient adults with mental health problems
por: Franken, Katinka, et al.
Publicado: (2023) -
Gratitude as Mood Mediates the Effects of a 6-Weeks Gratitude Intervention on Mental Well-Being: Post hoc Analysis of a Randomized Controlled Trial
por: Bohlmeijer, Ernst, et al.
Publicado: (2022) -
The Model for Sustainable Mental Health: Future Directions for Integrating Positive Psychology Into Mental Health Care
por: Bohlmeijer, Ernst, et al.
Publicado: (2021) -
Exploring factors associated with personal recovery in bipolar disorder
por: Kraiss, Jannis T., et al.
Publicado: (2021)