Qualitative data analysis with SCRINTAL || part 1 - Open Codes

Qualitative coding in SCRINTAL (SCRINTAL) can be done entirely inside the platform by turning interview excerpts into “cards” and linking them to code cards—then reorganizing those codes into broader groupings. The core payoff is a visual, traceable workflow for thematic analysis: every code remains connected to the exact text that generated it, making later theme-building more systematic and easier to audit.

The walkthrough starts with a hypothetical study of international fishing boat crews, using two interview transcripts to understand lived experiences—what challenges they face, how they cope, and what improvements might be suggested. In the first method, the analyst creates a new workspace board (e.g., “example study”), then imports each interview transcript as its own card by copying and pasting from Microsoft Word. From there, coding happens directly in SCRINTAL: selecting a passage triggers a menu option to create a link, which effectively generates a new code card. As the analyst reads through Interview 1, they create code cards such as “Having a diverse crew,” “Initial challenges,” and “Initial linguistic challenges,” plus coping-oriented codes like “Being patient and open-minded.” Each time a code is created via linked text selection, SCRINTAL connects the code card to the relevant excerpt, so hovering over text later reveals which code(s) apply.

The process repeats for Interview 2, with the analyst creating additional codes and then using color and layout changes to keep the growing set manageable. SCRINTAL’s visual organization tools—card resizing, full-screen reading, zooming, and color consistency—are treated as practical necessities once the number of codes increases. The transcript also notes that connections can occasionally become disconnected, but those links can be manually reattached.

Once initial coding is complete, the workflow shifts from “many codes” to “sense-making.” The analyst creates a second board (e.g., “coding organized”) and duplicates the code cards from the original board so changes won’t overwrite the raw coding. Then the analyst removes the interview cards from view and focuses on the code set. Next comes grouping: new heading cards like “Challenges” and “Suggestions” are created, along with broader buckets such as “Overcoming challenges.” Codes are then visually moved into these groups—for example, cultural differences and language barriers are placed under challenges, while patience and open-mindedness are placed under overcoming challenges.

Finally, the transcript previews a second approach that mixes Microsoft Word and SCRINTAL. In Word, coding is done using a two-column table: the left column holds the transcript and the right column holds codes. After coding, the analyst copies the codes into SCRINTAL, but the structure changes: instead of creating code cards from scratch inside SCRINTAL, the analyst pastes pre-made codes into interview cards and then cuts and pastes excerpts into new group cards (e.g., strategies or good practices). This hybrid method reduces the number of cards but increases the amount of text, and it still leaves the analyst with the same downstream tasks—cleaning duplicates, reconciling naming differences across interviews, and ultimately building themes in later steps.