Fine-tuning large language models for detecting negative self-referential language in smartphone text among youth with depression.

Authors

Stewart A. Shankman (ORCID: https://orcid.org/0000-0002-8097-4483)
Katherine Durham
David Pagliaccio (ORCID: https://orcid.org/0000-0002-1214-1965)
Adela Schwartz
Isaac N. Treves (ORCID: https://orcid.org/0000-0001-7802-6145)
J. B. Spence
Nicholas B Allen
PhD Randy P. Auerbach
Paul A. Bloom (ORCID: https://orcid.org/0000-0003-3970-5721)
Libby Hod
Alexander Saul Rosenberg
Xuhai Xu
Lilian Y. Li
Esha Trivedi

Institutions

Northwestern University (US)
University of Oregon (US)
Columbia University (US)

Publication Details

Journal: Journal of Psychopathology and Clinical Science
Published: 2026-08-17
DOI: https://doi.org/10.1037/abn0001159
Primary Topic: Mental Health via Writing
Type: article
Field-Weighted Citation Impact: 0.00

Funders

National Institute of Mental Health

Controls

|||

ALL TIME

JAN

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

article

Fine-tuning large language models for detecting negative self-referential language in smartphone text among youth with depression.

Stewart A. Shankman, Katherine Durham, David Pagliaccio, Adela Schwartz et al.

Aug 17, 2026

Journal of Psychopathology and Clinical Science

Mental Health via Writing

article

Fine-tuning large language models for detecting negative self-referential language in smartphone text among youth with depression.

Stewart A. Shankman, Katherine Durham, David Pagliaccio, Adela Schwartz, Isaac N. Treves, J. B. Spence, Nicholas B Allen, PhD Randy P. Auerbach, Paul A. Bloom, Libby Hod, Alexander Saul Rosenberg, Xuhai Xu, Lilian Y. Li, Esha Trivedi

August 17, 2026article en

Abstract

No abstract available for this paper.

Journal of Psychopathology and Clinical Science

Northwestern University (US), University of Oregon (US), Columbia University (US)

National Institute of Mental Health

Quality Education

Openalex Percentile: Top 6%

Mental Health via Writing

DOI Open Access PDF OpenAlex

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.