Evidence map›Paper›PMID 34236411›Full record

ArticleJAMA network open2021

Development and Validation of Computerized Adaptive Assessment Tools for the Measurement of Posttraumatic Stress Disorder Among US Military Veterans.

Lisa A Brenner, Lisa M Betthauser, Molly Penzenik, Anne Germain, Jin Jun Li, Ishanu Chattopadhyay, Ellen Frank, David J Kupfer, Robert D Gibbons

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in JAMA network open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07664631 (Effects of Stimulant Medications in PTSD), which is not on this map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.0field-weighted citation impact, top 21% 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.

NCT07664631 phase1not yet recruitingnot on this mapstarted 2026, after this paper: background citation

Effects of Stimulant Medications in PTSD

TypeinterventionalSponsorUniversity of ChicagoRan2026 to 2027Enrolled40ConditionsAdderall, PTSD, Post Traumatic Stress DisorderArmsPlacebo, Adderall
3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Optimizing Symptom Surveys with Machine Learning to Predict PTSD One Year Post-trauma....IEEE...International Conference on Connected Health: Applications, Systems and Engineering Technologies. IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies · 2026
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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 at 4 institutions in 1 country.

Lisa A BrennerVA Rocky Mountain Mental Illness Research, Education and Clinical Center, Rocky Mountain Regional Veterans Affairs Medical Center, Eastern Colorado Health Care System, Aurora.
Lisa M BetthauserVA Rocky Mountain Mental Illness Research, Education and Clinical Center, Rocky Mountain Regional Veterans Affairs Medical Center, Eastern Colorado Health Care System, Aurora.
Molly PenzenikVA Rocky Mountain Mental Illness Research, Education and Clinical Center, Rocky Mountain Regional Veterans Affairs Medical Center, Eastern Colorado Health Care System, Aurora.
Anne GermainPittsburgh School of Medicine, Pittsburgh, Pennsylvania.
Jin Jun LiDepartment of Medicine, University of Chicago, Chicago, Illinois.
Ishanu ChattopadhyayDepartment of Medicine, University of Chicago, Chicago, Illinois.
Ellen FrankPittsburgh School of Medicine, Pittsburgh, Pennsylvania.
David J KupferPittsburgh School of Medicine, Pittsburgh, Pennsylvania.
Robert D GibbonsDepartment of Medicine, University of Chicago, Chicago, Illinois.
University of Chicago · USUniversity of Pittsburgh · USVA Eastern Colorado Health Care System · USUniversity of Colorado Anschutz Medical Campus · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Veterans from recent and past conflicts have high rates of posttraumatic stress disorder (PTSD). Adaptive testing strategies can increase accuracy of diagnostic screening and symptom severity measurement while decreasing patient and clinician burden. Objective: To develop and validate a computerized adaptive diagnostic (CAD) screener and computerized adaptive test (CAT) for PTSD symptom severity. Design, Setting, and Participants: A diagnostic study of measure development and validation was conducted at a Veterans Health Administration facility. A total of 713 US military veterans were included. The study was conducted from April 25, 2017, to November 10, 2019. Main Outcomes and Measures: The participants completed a PTSD-symptom questionnaire from the item bank and provided responses on the PTSD Checklist for Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) (PCL-5). A subsample of 304 participants were interviewed using the Clinician-Administered Scale for PTSD for DSM-5. Results: Of the 713 participants, 585 were men; mean (SD) age was 52.8 (15.0) years. The CAD-PTSD reproduced the Clinician-Administered Scale for PTSD for DSM-5 PTSD diagnosis with high sensitivity and specificity as evidenced by an area under the curve of 0.91 (95% CI, 0.87-0.95). The CAT-PTSD demonstrated convergent validity with the PCL-5 (r = 0.88) and also tracked PTSD diagnosis (area under the curve = 0.85; 95% CI, 0.79-0.89). The CAT-PTSD reproduced the final 203-item bank score with a correlation of r = 0.95 with a mean of only 10 adaptively administered items, a 95% reduction in patient burden. Conclusions and Relevance: Using a maximum of only 6 items, the CAD-PTSD developed in this study was shown to have excellent diagnostic screening accuracy. Similarly, using a mean of 10 items, the CAT-PTSD provided valid severity ratings with excellent convergent validity with an extant scale containing twice the number of items. The 10-item CAT-PTSD also outperformed the 20-item PCL-5 in terms of diagnostic accuracy. The results suggest that scalable, valid, and rapid PTSD diagnostic screening and severity measurement are possible.

Indexed as

AdultAgedComputerized Adaptive TestingFemaleHumansMaleMass ScreeningMiddle AgedStress Disorders, Post-TraumaticSurveys and QuestionnairesUnited StatesVeterans

Identifiers

PMID34236411
PMCPMC8267606
OpenAlexW3178649380

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.