Evidence map›Paper›PMID 28131628›Full record

ArticleJournal of affective disorders2017

Latent variable analysis of positive and negative valence processing focused on symptom and behavioral units of analysis in mood and anxiety disorders.

Martin P Paulus, Murray B Stein, Michelle G Craske, Susan Bookheimer, Charles T Taylor, Alan N Simmons, Natasha Sidhu, Katherine S Young, Boyang Fan

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In one paragraph

Article in Journal of affective disorders, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Moving beyond descriptive nosology: an argument for negative valence systems disorder.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024
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  10. Age-Related Enhancements in Positive Emotionality across The Life Span: Structural Equation Modeling of Brain and Behavior.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2022
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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

9 authors.

Martin P PaulusDepartment of Psychiatry, University of California San Diego, La Jolla, CA, USA; Laureate Institute for Brain Research, Tulsa, Oklahoma, USA. Electronic address: mpaulus@laureateinstitute.org.
Murray B SteinDepartment of Psychiatry, University of California San Diego, La Jolla, CA, USA.
Michelle G CraskeDepartment of Psychology, Psychiatry and Biobehavioral Sciences, University of California Los Angeles, USA.
Susan BookheimerDepartment of Psychology, Psychiatry and Biobehavioral Sciences, University of California Los Angeles, USA.
Charles T TaylorDepartment of Psychiatry, University of California San Diego, La Jolla, CA, USA.
Alan N SimmonsDepartment of Psychiatry, University of California San Diego, La Jolla, CA, USA.
Natasha SidhuDepartment of Psychiatry, University of California San Diego, La Jolla, CA, USA.
Katherine S YoungDepartment of Psychology, Psychiatry and Biobehavioral Sciences, University of California Los Angeles, USA.
Boyang FanDepartment of Psychology, Psychiatry and Biobehavioral Sciences, University of California Los Angeles, USA.

Funding

Latent Constructs: Negative-Positive Valence Domains in Anxiety and DepressionR01MH101453 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PAULUS, MARTIN P. · 2013 to 2016
$1.9M
NIMH NIH HHS R01 MH101453
6 · The paper itself

Abstract

backgroundMood and anxiety disorders are highly heterogeneous and their underlying pathology is complex. The Research Domain Criteria (RDoC) approach seeks to establish dimensionally and neuroscience-based descriptions of psychopathology that may inform better classification and treatment approaches. The current investigation sought to determine the latent variables underlying positive and negative valence processing in terms of symptoms and behavioral units of analysis.

methodAs part of an ongoing study, individuals with mood and anxiety problems were recruited largely from primary care clinics at UCLA (n=62) and UCSD (n=58). These participants underwent a comprehensive symptomatic and behavioral assessment. An implicit approach avoidance task and a modified dot probe detection task were used to measure positive and negative valence processing.

resultsPrincipal components analysis with varimax rotation identified four symptom components, three behavioral components for the dot probe task, and two behavioral components for the implicit approach avoidance task. These components yielded two meta-components consisting of: negative valence symptoms, negative approach bias, and high sustained, selective attention; and positive valence symptoms, positive approach bias, and slow selective or sustained attention. The components did not differ between males and females, nor by age or medication status. LIMITATIONS: The limitations are: (1) relatively small sample, (2) exploratory analysis strategy, (3) no test/re-test data, (4) no neural circuit analysis, and (5) limited reliability of behavioral data.

conclusionsThese preliminary data show that positive and negative valence processing domains load on independent dimensions. Taken together, multi-level assessment approaches combined with advanced statistical analyses may help to identify distinct positive and negative valence processes within a clinical population that cut across traditional diagnostic categories.

Indexed as

EmotionsAdultAnxiety DisordersAttentionBiasFemaleHumansMaleMood DisordersPrincipal Component AnalysisPsychopathologyAnxiety disordersMood disordersNegative valence processingPositive valence processingPrincipal components analysisResearch domain criteria

Identifiers

PMID28131628
PMCPMC5471118

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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.