ArticleDrugs in R&D2015
Use of adjectives in abstracts when reporting results of randomized, controlled trials from industry and academia.
Article in Drugs in R&D, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- The rise of promotional rhetoric in the Discussion Sections of an interdisciplinary field: a diachronic perspective.Frontiers in psychology · 2025Article
- Misrepresentation and distortion of research in biomedical literature.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveAccurate representation of study findings is crucial to preserve public trust. The language used to describe results could affect perceptions of the efficacy or safety of interventions. We sought to compare the adjectives used in clinical trial reports of industry-authored and non-industry-authored research.
methodsWe included studies in PubMed that were randomized trials and had an abstract. Studies were classified as "non-industry-authored" when all authors had academic or governmental affiliations, or as "industry-authored" when any of the authors had industry affiliations. Abstracts were analyzed using a part-of-speech tagger to identify adjectives. To reduce the risk of false positives, the analysis was restricted to adjectives considered relevant to "coloring" (influencing interpretation) of trial results. Differences between groups were determined using exact tests, stratifying by journal.
resultsA total of 306,007 publications met the inclusion criteria. We were able to classify 16,789 abstracts; 9,085 were industry-authored research, and 7,704 were non-industry-authored research. We found a differential use of adjectives between industry-authored and non-industry-authored reports. Adjectives such as "well tolerated" and "meaningful" were more commonly used in the title or conclusion of the abstract by industry authors, while adjectives such as "feasible" were more commonly used by non-industry authors.
conclusionsThere are differences in the adjectives used when study findings are described in industry-authored reports compared with non-industry-authored reports. Authors should avoid overusing adjectives that could be inaccurate or result in misperceptions. Editors and peer reviewers should be attentive to the use of adjectives and assess whether the usage is context appropriate.
Indexed as
Identifiers
What OpenQuestion holds
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.