A scoping review of comparisons between abstracts and full reports in primary biomedical research
Bibliographic record
Abstract
BACKGROUND: Evidence shows that research abstracts are commonly inconsistent with their corresponding full reports, and may mislead readers. In this scoping review, which is part of our series on the state of reporting of primary biomedical research, we summarized the evidence from systematic reviews and surveys, to investigate the current state of inconsistent abstract reporting, and to evaluate factors associated with improved reporting by comparing abstracts and their full reports. METHODS: We searched EMBASE, Web of Science, MEDLINE, and CINAHL from January 1st 1996 to September 30th 2016 to retrieve eligible systematic reviews and surveys. Our primary outcome was the level of inconsistency between abstracts and corresponding full reports, which was expressed as a percentage (with a lower percentage indicating better reporting) or categorized rating (such as major/minor difference, high/medium/low inconsistency), as reported by the authors. We used medians and interquartile ranges to describe the level of inconsistency across studies. No quantitative syntheses were conducted. Data from the included systematic reviews or surveys was summarized qualitatively. RESULTS: Seventeen studies that addressed this topic were included. The level of inconsistency was reported to have a median of 39% (interquartile range: 14% - 54%), and to range from 4% to 78%. In some studies that separated major from minor inconsistency, the level of major inconsistency ranged from 5% to 45% (median: 19%, interquartile range: 7% - 31%), which included discrepancies in specifying the study design or sample size, designating a primary outcome measure, presenting main results, and drawing a conclusion. A longer time interval between conference abstracts and the publication of full reports was found to be the only factor which was marginally or significantly associated with increased likelihood of reporting inconsistencies. CONCLUSIONS: This scoping review revealed that abstracts are frequently inconsistent with full reports, and efforts are needed to improve the consistency of abstract reporting in the primary biomedical community.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.425 | 0.811 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.014 | 0.020 |
| Bibliometrics | 0.095 | 0.090 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.018 | 0.019 |
| Open science | 0.006 | 0.011 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".