Predicting remission following CBT for childhood anxiety disorders: a machine learning approach

These findings underscore the utility of prediction models that may indicate which children are more likely to remit or are more at risk of non-remission following CBT for childhood anxiety.

Authors

Institutions

Publication Details

Journal
Psychological Medicine
Published
2024-12-01
DOI
https://doi.org/10.1017/s0033291724002654
Citations
7
Primary Topic
Child and Adolescent Psychosocial and Emotional Development
Type
article
Field-Weighted Citation Impact
4.47

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predicting remission following CBT for childhood anxiety disorders: a machine learning approach

Mikael Thastum, Thalia Catherine Eley, Carolyn A. Schniering, Ronald M. Rapee et al.
7 citations
Psychological Medicine
Child and Adolescent Psychosocial and Emotional Development
4.47
article

Predicting remission following CBT for childhood anxiety disorders: a machine learning approach

Mikael Thastum, Thalia Catherine Eley, Carolyn A. Schniering, Ronald M. Rapee, Silvia Schneider, Catharina Annette Hartman, Jennifer L. Hudson, Tina In‐Albon, Kristian Bech Arendt, Susan M. Bögels, Cathy Creswell, Juan C. Quiroz, Lizél‐Antoinette Bertie, Carla E. Marin, Heidi J. Lyneham, Richard Meiser‐Stedman, Shlomo Berkovsky, Kerstin Thirlwall, Maaike H. Nauta, Viviana M. Wuthrich, Lauren F. McLellan, Kathryn J. Lester, Polly Waite, Jonathan R. I. Coleman, Wendy K. Silverman, Kristen L. Lavallee, Gro Janne Wergeland, Anna McKinnon, P. J. M. Cooper, Krister Fjermestadt
article en
7 citations

Abstract

These findings underscore the utility of prediction models that may indicate which children are more likely to remit or are more at risk of non-remission following CBT for childhood anxiety.

Psychological MedicineVol. 54(16)
University Medical Center Groningen (NL), University of Sussex (GB), Black Dog Institute (AU), University of Groningen (NL), King's College London (GB), University of Oslo (NO), University of Basel (CH), MRC Cognition and Brain Sciences Unit (GB), Aarhus University (DK), University of Koblenz and Landau (DE), UNSW Sydney (AU), Yale University (US), University of Oxford (GB), Universität Koblenz (DE), University of Bergen (NO), University of Reading (GB), University of Amsterdam (NL), Ruhr University Bochum (DE), Macquarie University (AU)
National Science Foundation, National Institute for Health and Care Research, King's College London, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, TrygFonden, Medical Research Council, National Health and Medical Research Council, National Institute of Mental Health
Good health and well-being
Openalex Percentile: Top 5%
Child and Adolescent Psychosocial and Emotional Development
4.47
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.