Evidence map›Paper›PMID 39417141›Full record

ArticlemedRxiv : the preprint server for health sciences2024

Unraveling the Associations Between Voice Pitch and Major Depressive Disorder: A Multisite Genetic Study.

Yazheng Di, Elior Rahmani, Joel Mefford, Jinhan Wang, Vijay Ravi, Aditya Gorla, Abeer Alwan, Kenneth S Kendler, Tingshao Zhu, Jonathan Flint

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Yazheng DiCAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing 100101, China.ORCID 0000-0003-2483-1696
Elior RahmaniDepartment of Computational Medicine, University of California Los Angeles, Los Angeles, CA, USA.
Joel MeffordDepartment of Neurology, University of California Los Angeles, Los Angeles, CA, USA.
Jinhan WangDepartment of Electrical and Computer Engineering, University of California Los Angeles, Los Angeles, CA, USA.
Vijay RaviDepartment of Electrical and Computer Engineering, University of California Los Angeles, Los Angeles, CA, USA.
Aditya GorlaBioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA.
Abeer AlwanDepartment of Electrical and Computer Engineering, University of California Los Angeles, Los Angeles, CA, USA.
Kenneth S KendlerVirginia Institute for Psychiatric and Behavioral Genetics, Richmond, VA, USA.
Tingshao ZhuCAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing 100101, China.
Jonathan FlintDepartment of Psychiatry and Biobehavioral Sciences, Brain Research Institute, University of California Los Angeles, Los Angeles, CA, USA.ORCID 0000-0002-9427-4429

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Major depressive disorder (MDD) often goes undiagnosed due to the absence of clear biomarkers. We sought to identify voice biomarkers for MDD and separate biomarkers indicative of MDD predisposition from biomarkers reflecting current depressive symptoms. Using a two-stage meta-analytic design to remove confounds, we tested the association between features representing vocal pitch and MDD in a multisite case-control cohort study of Chinese women with recurrent depression. Sixteen features were replicated in an independent cohort, with absolute association coefficients (beta values) from the combined analysis ranging from 0.24 to 1.07, indicating moderate to large effects. The statistical significance of these associations remained robust, with P-values ranging from 7.2 × 10

Identifiers

PMID39417141
PMCPMC11482971

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LicenceCC BY-NC-ND
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Registered trials

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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.