Rayyan supports several approaches to organizing screening work across a team. The right method depends on your dataset size, team size, and review protocol. This article covers four methods — choose the one that fits your workflow.
| Method | Best for | Works with Blind Mode? |
|---|---|---|
| Everyone screens everything | Small teams following a standard systematic review protocol | Yes |
| Data Sampling | Larger datasets — randomized division of work | Yes |
| Min/Max Decisions filter | Teams that want to limit how many times each reference is screened | Yes |
| Label-based division | Teams that want explicit assignment of reference groups | No — requires Blind Mode off |
Method 1 — Everyone screens everything
The default Rayyan workflow. Two or more reviewers screen all references independently, with Blind Mode on. This method requires no special setup and works best for smaller datasets and when independent dual screening is a protocol requirement.
- Invite your team and assign roles — see How to Invite and Manage Review Members in Rayyan
- Keep Blind Mode on so each reviewer screens independently
- Once screening is complete, turn Blind Mode off and use the Conflict filter to identify disagreements
- Resolve conflicts as a team — see How to Resolve Screening Conflicts in Rayyan
Method 2 — Data Sampling
Data Sampling lets you create randomized subsets of your references and assign each subset to a different team member. This is the recommended approach for larger datasets. Samples do not restrict access — any member can still see all references, so the owner is responsible for communicating which sample each team member should work on. Data Sampling is available on all plans; Free and Essential plans are limited to 1 sample per review, Advanced and higher offer unlimited sample creation.
- Go to the Review data or Screening page and click Samples
- Choose your data source — All References or Filtered
- Select a sampling setting — Randomized is recommended to reduce selection bias
- Create one sample per team member or group, setting the percentage for each (e.g., 50% each for two screeners)
- Share each sample name with the corresponding team member — they filter the Screening stage using the Sampled Data facet in the Filters panel to find their assigned references
Method 3 — Min/Max Decisions filter
The Min/Max Decisions filter lets you control how many reviewer decisions each reference must receive before it is considered fully screened. This approach lets teams divide work organically without needing to pre-assign references. It works with Blind Mode on and is useful for larger teams where pre-assigning specific subsets is impractical.
- In the Screening stage, use the At least / At most filter in the Filters panel to show references that have received fewer than the target number of decisions
- Each reviewer picks up unscreened or partially screened references and works through them
- Once a reference reaches the target decision count, it naturally drops out of the filtered view
Method 4 — Label-based division
Label-based division gives you explicit control over which team member screens which group of references.
- Before screening begins, apply labels to groups of references — for example, Group A, Group B, or by database source
- Turn Blind Mode off — labels are not visible to other reviewers when Blind Mode is on
- Assign each team member to screen references with their designated label using the Labels facet in the Filters panel
Continue to: How to Resolve Screening Conflicts in Rayyan