Evidence map›Paper›PMID 26119139›Full record

ArticleJournal of anxiety disorders2015

Classification models for subthreshold generalized anxiety disorder in a college population: Implications for prevention.

Nitya Kanuri, C Barr Taylor, Jeffrey M Cohen, Michelle G Newman

Abstract read
In one paragraph

Article in Journal of anxiety disorders, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

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

  1. Pooled it
  2. Trial
  3. A randomized controlled trial of a smartphone-based application for the treatment of anxiety.Psychotherapy research : journal of the Society for Psychotherapy Research · 2021
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  9. Distinct Effects of Anxiety and Depression on Updating Emotional Information in Working Memory.International journal of environmental research and public health · 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

4 authors.

Nitya KanuriStanford University School of Medicine, Department of Psychiatry and Behavioral Sciences, United States. Electronic address: nkanuri@stanford.edu.
C Barr TaylorStanford University School of Medicine, Department of Psychiatry and Behavioral Sciences, United States; Palo Alto University, United States.
Jeffrey M CohenPGSP-Stanford PsyD Consortium, United States.
Michelle G NewmanThe Pennsylvania State University, Department of Psychology, United States.

Funding

INTERVENTIONS TO REDUCE EATING DISORDER RISK FACTORSR01MH060453 · NIMH · STANFORD UNIVERSITY · PI TAYLOR, CBARR BARR · 2001 to 2004
$2.3M
NIMH NIH HHS R01 MH060453
6 · The paper itself

Abstract

Generalized anxiety disorder (GAD) is one of the most common psychiatric disorders on college campuses and often goes unidentified and untreated. We propose a combined prevention and treatment model composed of evidence-based self-help (SH) and guided self-help (GSH) interventions to address this issue. To inform the development of this stepped-care model of intervention delivery, we evaluated results from a population-based anxiety screening of college students. A primary model was developed to illustrate how increasing levels of symptomatology could be linked to prevention/treatment interventions. We used screening data to propose four models of classification for populations at risk for GAD. We then explored the cost considerations of implementing this prevention/treatment stepped-care model. Among 2489 college students (mean age 19.1 years; 67% female), 8.0% (198/2489) met DSM-5 clinical criteria for GAD, in line with expected clinical rates for this population. At-risk Model 1 (subthreshold, but considerable symptoms of anxiety) identified 13.7% of students as potentially at risk for developing GAD. Model 2 (subthreshold, but high GAD symptom severity) identified 13.7%. Model 3 (subthreshold, but symptoms were distressing) identified 12.3%. Model 4 (subthreshold, but considerable worry) identified 17.4%. There was little overlap among these models, with a combined at-risk population of 39.4%. The efficiency of these models in identifying those truly at risk and the cost and efficacy of preventive interventions will determine if prevention is viable. Using Model 1 data and conservative cost estimates, we found that a preventive intervention effect size of even 0.2 could make a prevention/treatment model more cost-effective than existing models of "wait-and-treat."

Indexed as

AnxietyAnxiety DisordersCognitive Behavioral TherapyCost-Benefit AnalysisFemaleHumansMalePsychiatric Status Rating ScalesRisk FactorsStudentsWatchful WaitingYoung AdultCollege healthe-HealthGeneralized anxiety disorderPreventionScreeningSelf-help interventionsStepped-care models

Identifiers

PMID26119139
PMCPMC6707508

What OpenQuestion holds

Textmetadata
LicenceTDM
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.