Capitalizing on natural language processing (NLP) to automate the evaluation of coach implementation fidelity in guided digital cognitive-behavioral therapy (GdCBT)
NLP and ML tools could help clinical supervisors automate monitoring of coaches' implementation fidelity to GdCBT. These tools could maximize allocation of scarce resources by reducing the personnel time needed to measure fidelity, potentially freeing up more time for high-quality clinical care.
Authors
- C. Barr Taylor (ORCID: https://orcid.org/0000-0002-4564-6548)
- Elsa E. Rojas-Ashe (ORCID: https://orcid.org/0000-0002-8563-3696)
- Ellen E. Fitzsimmons‐Craft (ORCID: https://orcid.org/0000-0001-7064-3835)
- Denise E. Wilfley (ORCID: https://orcid.org/0000-0002-3599-8689)
- Michelle Gayle Newman (ORCID: https://orcid.org/0000-0003-0873-1409)
- Nur Hani Zainal (ORCID: https://orcid.org/0000-0002-2023-3173)
- Gavin N. Rackoff (ORCID: https://orcid.org/0000-0003-3525-3975)
- Regina Eckhardt
- Burkhardt Funk (ORCID: https://orcid.org/0000-0001-5855-2666)
- Daniel Eisenberg (ORCID: https://orcid.org/0000-0001-5597-7925)
Institutions
- Leuphana University of Lüneburg (DE)
- Pennsylvania State University (US)
- University of California, Los Angeles (US)
- National University of Singapore (SG)
- Palo Alto University (US)
- Washington University in St. Louis (US)
- Technical University of Munich (DE)
- Stanford University (US)
Publication Details
- Journal
- Psychological Medicine
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1017/s0033291725000340
- Citations
- 4
- Primary Topic
- Digital Mental Health Interventions
- Type
- article
- Field-Weighted Citation Impact
- 6.18
Funders
- University of Pennsylvania
- Pennsylvania State University
- National University of Singapore
- National Institute of Mental Health