Evaluation of spin in the abstracts of systematic reviews and meta-analyses relating to postoperative nausea and vomiting
Bibliographic record
Abstract
INTRODUCTION: Spin - the beautification of study results to emphasise benefits or minimise harms - is a deceptive reporting strategy with the potential to affect clinical decision-making adversely. Few studies have investigated the extent of spin in systematic reviews. Here, we sought to address this gap by evaluating the presence of the nine most severe forms of spin in the abstracts of systematic reviews on treatments for postoperative nausea and vomiting (PONV). PONV has the potential to increase hospital costs and patient burden, adversely affecting outcomes. METHODS: We developed search strategies for MEDLINE and Embase to identify systematic reviews focused on PONV. Following title and abstract screening of the reviews identified during the initial search, those that met inclusion criteria were evaluated for the presence of spin and received a revised AMSTAR-2 (A Measurement Tool to Assess Systematic Reviews) appraisal by two investigators in a masked, duplicate manner. Study characteristics for each review were also extracted in duplicate. RESULTS: Our systematic search returned 3513 studies, of which 130 systematic reviews and meta-analyses were eligible for data extraction. We found that 29.2% of included systematic reviews contained spin (38/130). Eight of the nine types of spin were identified, with spin type 3 ('selective reporting of or overemphasis on efficacy outcomes or analysis favouring the beneficial effect of the experimental intervention') being the most common. Associations were found between spin and funding source. Spin was more likely in the abstracts of privately funded than nonfunded studies, odds ratio (OR) 2.81 [95% confidence interval (CI), 0.66 to 11.98]. In the abstracts of studies not mentioning funding spin was also more likely than in nonfunded studies, OR 2.30 (95% CI, 0.61 to 8.70). Neither of these results were statistically significant. Significance was found in the association between the presence of spin and AMSTAR-2 ratings: 'low' quality studies were less likely to contain spin than 'high' quality, OR 0.24 (95% CI, 0.07 to 0.88): 'critically low' studies were also less likely to contain spin than 'high' quality studies, OR 0.21 (95% CI, 0.07 to 0.65). There were no other associations between spin and the remaining extracted study characteristics or AMSTAR-2 ratings. CONCLUSION: Spin was present in greater than 29% of abstracts of systematic reviews and meta-analyses regarding PONV. Various stakeholders must take steps to improve the reporting quality of abstracts on PONV.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.026 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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; a candidate call from one teacher head, not a consensus.
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".