Evidence map›Paper›PMID 40208744›Full record

ArticleJournal of psychopathology and clinical science2025

Semantic signals in self-reference: The detection and prediction of depressive symptoms from the daily diary entries of a sample with major depressive disorder.

Amanda C Collins, Damien Lekkas, Matthew D Nemesure, Tess Z Griffin, George D Price, Arvind Pillai, Subigya Nepal, Michael V Heinz, Andrew T Campbell, Nicholas C Jacobson

Abstract read
In one paragraph

Article in Journal of psychopathology and clinical science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Amanda C CollinsDepartment of Psychiatry, Massachusetts General Hospital.ORCID 0000-0002-8258-2272
Damien LekkasCenter for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College.
Matthew D NemesureDigital Data Design Institute, Harvard Business School.
Tess Z GriffinDepartment of Psychiatry, Harvard Medical School.
George D PriceCenter for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College.
Arvind PillaiDepartment of Computer Science, Dartmouth College.
Subigya NepalDepartment of Computer Science, Dartmouth College.
Michael V HeinzCenter for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College.
Andrew T CampbellCenter for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College.
Nicholas C JacobsonCenter for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College.

Funding

Treatment Development & Evaluation CoreP30DA029926 · NIDA · DARTMOUTH COLLEGE · PI Lisa A. Marsch · 2011 to 2026
$21.5M
Training in the Science of Co-Occurring DisordersT32DA037202 · NIDA · DARTMOUTH COLLEGE · PI Lisa A. Marsch · 2014 to 2026
$4.7M
Personalized Deep Learning Models of Rapid Changes in Major Depressive Disorder Symptoms using Passive Sensor Data from Smartphones and Wearable DevicesR01MH123482 · NIMH · DARTMOUTH COLLEGE · PI JACOBSON, NICHOLAS CHARLES · 2020 to 2024
$2.6M
Boehringer IngelheimNIDA NIH HHS P30 DA029926NIDA NIH HHS T32 DA037202NIGMS NIH HHSNIMH NIH HHS R01 MH123482
6 · The paper itself

Abstract

Individuals with major depressive disorder (MDD) experience fewer positive and more negative emotions and use fewer positive words to describe themselves. Natural language processing techniques have been used to predict depression, with pronoun and emotion usage being identified as important features. However, it is unclear how depressed individuals use positive and negative words when writing about themselves. Individuals with MDD (

Indexed as

Major Depressive DisorderNatural Language ProcessingSelf ConceptSemanticsAdultEcological Momentary AssessmentFemaleHumansMaleMiddle AgedYoung Adult

Identifiers

PMID40208744
PMCPMC12162227

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.