Predicting Dropout in Psychotherapy for Major Depressive Disorder: A Machine Learning Approach to Identifying At‐Risk Patients
- DOI
- 10.1002/cpp.70320
- Published
- 2026-07
- Container
- Clinical Psychology & Psychotherapy
- Publisher
- Wiley
- Open access
- unknown
Credibility signals
uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- supportingDOI registered: A matching record was returned by Crossref.
- supportingDOI resolves: A matching record was returned by Crossref.
- not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredOpen access status: Not checked or no result supplied; no credibility inference made.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- supportingMetadata completeness: All 6 scored descriptive metadata groups are present.
Cite this work
BibTeX
@article{allodium:10.1002/cpp.70320,
title = {Predicting Dropout in Psychotherapy for Major Depressive Disorder: A Machine Learning Approach to Identifying At‐Risk Patients},
author = {Susanne Bremer‐Hoeve and Suzanne C. van Bronswijk and Aartjan T. F. Beekman and Maartje Miggiels and Sanne J. E. Bruijniks and Maarten K. van Dijk},
year = {2026},
journal = {Clinical Psychology \& Psychotherapy},
doi = {10.1002/cpp.70320},
url = {https://doi.org/10.1002/cpp.70320}
}RIS
TY - JOUR TI - Predicting Dropout in Psychotherapy for Major Depressive Disorder: A Machine Learning Approach to Identifying At‐Risk Patients AU - Susanne Bremer‐Hoeve AU - Suzanne C. van Bronswijk AU - Aartjan T. F. Beekman AU - Maartje Miggiels AU - Sanne J. E. Bruijniks AU - Maarten K. van Dijk PY - 2026 JO - Clinical Psychology & Psychotherapy DO - 10.1002/cpp.70320 UR - https://doi.org/10.1002/cpp.70320 ER -
APA
Bremer‐Hoeve, S., Bronswijk, S. C. V., Beekman, A. T. F., Miggiels, M., Bruijniks, S. J. E., & Dijk, M. K. V. (2026). Predicting Dropout in Psychotherapy for Major Depressive Disorder: A Machine Learning Approach to Identifying At‐Risk Patients. Clinical Psychology & Psychotherapy. https://doi.org/10.1002/cpp.70320
Source records
- crossref · retrieved 2026-09-25T01:13:22.393Z