Evidence map›Paper›PMID 31448183›Full record

ArticleClinical psychological science : a journal of the Association for Psychological Science2019

Probabilistic Learning by Positive and Negative Reinforcement in Generalized Anxiety Disorder.

Lucas S LaFreniere, Michelle G Newman

Open access · greenAbstract read
In one paragraph

Article in Clinical psychological science : a journal of the Association for Psychological Science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.1field-weighted citation impact, top 19% of its field
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

8 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Examining social reinforcement learning in social anxiety.Journal of behavior therapy and experimental psychiatry · 2023
    Article
  7. Article
  8. 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

2 authors at 1 institution in 1 country.

Lucas S LaFreniereDepartment of Psychology, The Pennsylvania State University.ORCID 0000-0001-9714-0760
Michelle G NewmanDepartment of Psychology, The Pennsylvania State University.
Pennsylvania State University · US

Funding

Harnessing Mobile Technology to Reduce Mental Health Disorders in College PopulationsR01MH115128 · NIMH · WASHINGTON UNIVERSITY · PI EISENBERG, DANIEL, NEWMAN, MICHELLE G · 2018 to 2022
$4.1M
NIMH NIH HHS R01 MH115128
6 · The paper itself

Abstract

This experiment examined learning tendencies in generalized anxiety disorder (GAD) using reinforcement feedback for probabilistic outcomes. One hundred sixty-six GAD and 105 non-GAD participants were randomized to a computerized probabilistic learning task that used either negative or positive reinforcement. Participants chose between stimuli with specific probabilities of reinforcement to learn which of each pair had the highest probability. Reinforced choices either removed an angry face (negative reinforcement) or made a happy face appear (positive reinforcement). Results showed that those with GAD learned the correct probabilistic choices at a slower rate over time and to a lesser degree than control participants regardless of reinforcement type. Estimations of the likelihood of receiving a good outcome posttask were also more inaccurate for those with GAD, especially when true likelihoods were high. Furthermore, compared with control participants, those with GAD reported lower perceived reinforcement sensitivity, higher behavioral inhibition sensitivity, and higher undesirable feelings toward probabilistic learning.

Indexed as

generalized anxiety disorderoperant conditioningprobabilistic learningprobability estimationreinforcement

Identifiers

PMID31448183
PMCPMC6707536
OpenAlexW2901667260

What OpenQuestion holds

Textmetadata
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Read underepoch 390

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.