Evidence map›Paper›PMID 37063460›Full record

ArticleCommunication methods and measures2022

Communication Quality Analysis: A user-friendly observational measure of patient-clinician communication.

Lauren Jodi Van Scoy, Allison M Scott, Michael J Green, Pamela D Witt, Emily Wasserman, Vernon M Chinchilli, Benjamin H Levi

Abstract read
In one paragraph

Article in Communication methods and measures, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

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

  1. Pooled it
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  3. Reply to WalterATS scholar · 2025
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  8. Observational
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

7 authors.

Lauren Jodi Van ScoyDepartments of Medicine, Penn State College of Medicine, Hershey, USA.
Allison M ScottDepartment of Communication; University of Kentucky, Lexington, USA.
Michael J GreenDepartments of Medicine, Penn State College of Medicine, Hershey, USA.
Pamela D WittDepartments of Medicine, Penn State College of Medicine, Hershey, USA.
Emily WassermanDepartment of Public Health Sciences, Penn State College of Medicine, Hershey, USA.
Vernon M ChinchilliDepartment of Public Health Sciences, Penn State College of Medicine, Hershey, USA.
Benjamin H LeviDepartment of Humanities, Penn State College of Medicine, Hershey, USA.

Funding

Communication quality analysis of end-of-life discussions by cliniciansR21NR017259 · NINR · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI VAN SCOY, LAUREN JODI · 2018 to 2019
$442k
NINR NIH HHS R21 NR017259
6 · The paper itself

Abstract

Communication Quality Analysis (CQA) is a rigorous transcript-based coding method for assessing clinical communication quality. We compared the resource-intensive transcript-based version with a streamlined real-time version of the method with respect to feasibility, validity, reliability, and association with traditional measures of communication quality. Simulated conversations between 108 trainees and 12 standardized patients were assessed by 7 coders using the two versions of CQA (transcript and real-time). Participants also completed two traditional communication quality assessment measures. Real-time CQA was feasible and yielded fair to excellent reliability, with some caveats that can be addressed in future work. CQA ratings were moderately correlated with traditional measures of communication quality, suggesting that CQA captures different aspects of communication quality than do traditional measures. Finally, CQA did not exhibit the ceiling effects observed in the traditional measures of communication quality. We conclude that real-time CQA is a user-friendly method for assessing communication quality that has the potential for broad application in training, research, and intervention contexts and may offer improvements to traditional, self-rated communication measures.

Indexed as

Communication research methodsconversation analysisintercoder reliabilityobservational research methods

Identifiers

PMID37063460
PMCPMC10104441

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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.