ArticleBMJ open2020
Systematic survey of the causal language use in systematic reviews of observational studies: a study protocol.
Article in BMJ open, 2020. 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.
- Elaboration and validity of the Instrumento para Avaliação de Modelos metodológicos voltados ao Desenvolvimento de Tecnologias.Revista brasileira de enfermagem · 2023Article
- Causal and Associational Language in Observational Health Research: A Systematic Evaluation.American journal of epidemiology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionSometimes, observational studies may provide important evidence that allow inferences of causality between exposure and outcome (although on most occasions only low certainty evidence). Authors, frequently and perhaps usually at the behest of the journals to which they are submitting, avoid using causal language when addressing evidence from observational studies. This is true even when the issue of interest is the causal effect of an intervention or exposure. Clarity of thinking and appropriateness of inferences may be enhanced through the use of language that reflects the issue under consideration. The objectives of this study are to systematically evaluate the extent and nature of causal language use in systematic reviews of observational studies and to relate that to the actual intent of the investigation. METHODS AND ANALYSIS: We will conduct a systematic survey of systematic reviews of observational studies addressing modifiable exposures and their possible impact on patient-important outcomes. We will randomly select 200 reviews published in 2019, stratified in a 1:1 ratio by use and non-use of the Grading of Recommendations Assessment, Development, and Evaluation (GRADE). Teams of two reviewers will independently assess study eligibility and extract data using a standardised data extraction forms, with resolution of disagreement by discussion and, if necessary, by third party adjudication. Through examining the inferences, they make in their papers' discussion, we will evaluate whether the authors' intent was to address causation or association. We will summarise the use of causal language in the study title, abstract, study question and results using descriptive statistics. Finally, we will assess whether the language used is consistent with the intention of the authors. We will determine whether results in reviews that did or did not use GRADE differ. ETHICS AND DISSEMINATION: Ethics approval for this study is not required. We will disseminate the results through publication in a peer-reviewed journals. REGISTRATION: Open Science Framework (osf.io/vh8yx).
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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.