ArticlePrimary health care research & development2019
Analysis of evidence appraisals for interventional studies in family medicine using an informatics approach.
Article in Primary health care research & development, 2019. 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.
- PubMed captures more fine-grained bibliographic data on scientific commentary than Web of Science: a comparative analysis.BMJ health & care informatics · 2024Article
- A comment-driven evidence appraisal approach to promoting research findings into practice when only uncertain evidence is available.Health research policy and systems · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
This study reports the first assessment of published comments in the family medicine literature using structured codes, which produced commentary annotations that will be the foundation of a knowledge base of appraisals of family medicine trials. Evidence appraisal occurs in a variety of formats and serves to shed light on the quality of research. However, scientific discourse generally and evidence appraisal in particular has not itself been analyzed for insights. A search strategy was devised to identify all journal comments indexed in PubMed linked to controlled intervention studies published in a recent 15-year period in major family medicine journals. A previously developed structured representation in the form of a list of appraisal concepts was used to formally annotate and categorize the journal comments through an iterative process. Trends in family medicine evidence appraisal were then analyzed. A total of 93 comments on studies from five journals over 15 years were included in the analysis. Two thirds of extracted appraisals were negative criticisms. All appraisals of measurement instruments were negative (100%). The participants baseline characteristics, the author discussions, and the design of the interventions were also criticized (respectively 91.7%, 84.6% and 83.3% negative). In contrast, appraisals of the scientific basis of the studies were positive (81.8%). The categories with the most appraisals were, most generally, those focused on the study design, and most specifically, those focused on the scientific basis. This study provides a new data-driven approach to review scientific discourse regarding the strengths and limitations of research within academic family medicine. This methodology can potentially generalize to other medical domains. Structured appraisal data generated here will enable future clinical, scientific, and policy decision-making and broader meta-research in family medicine.
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.