Presenting the Results of Cochrane Systematic Reviews to a Consumer Audience: A Qualitative Study
Bibliographic record
Abstract
OBJECTIVE: To develop and obtain feedback about a summary format for Cochrane reviews that is accessible to a consumer audience, without oversimplification or incorrect presentation. METHODS: We developed 3 versions of a Plain Language Summary (PLS) format of a Cochrane Systematic Review. Using a semi-structured interview guide we tested these versions among 34 members of the public in Norway, Argentina, Canada, and Australia. The authors analyzed feedback, identified problems, and generated new solutions before retesting to produce a final version of a Plain Language Summary format. RESULTS: Participants preferred results presented as words, supplemented by numbers in a table. There was a lack of understanding regarding the difference between a review and an individual study, that the effect is rarely an exact number, that evidence can be of low or high quality, and that level of quality is a separate issue from intervention effect. Participants also found it difficult to move between presentations of dichotomous and continuous outcomes. Rephrasing the introduction helped participants grasp the concept of a review. Confidence intervals were largely ignored or misunderstood. Our attempts to explain them were only partially successful. Text modifiers (''probably,'' ''may'') to convey different levels of quality were only partially understood, whereas symbols with explanations were more helpful. Participants often understood individual information elements about effect size and quality of these results, but did not always actively merge these elements. CONCLUSION: Through testing and iteration the authors identified and addressed several problems, using explanations, rephrasing, and symbols to present scientific concepts. Other problems remain, including how best to present confidence intervals and continuous outcomes. Future research should also test information elements in combination rather than in isolation. The new Plain Language Summary format is being evaluated in a randomized controlled trial.
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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 | 0.220 | 0.388 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".