Skip to main content

Table 3 Data analysis procedure

From: A qualitative study to identify barriers to deployment and student training in the use of automated external defibrillators in schools

Step 1

The interviews were transcribed (LZ) and read repeatedly by two researchers (LZ and CMH) to gain an overall impression and become familiar with the data’s diversity. The two researchers independently used open coding for each paragraph to discover categories, characteristics, and dimensions of the material [28] and thereafter met to discuss and refine the categories.

Step 2

The categories were discussed with the multidisciplinary research team that included professionals from anthropology (TTT and MHR), medicine (CMH, FF and CTP), and public health (LZ). The coding manual was developed by linking categories into major themes with subthemes (LZ, SMR, TTT, and MH). In this process, we applied the technology acceptance model [24, 25] as a framework for the empirical categories.

Step 3

The data was coded according to the manual (LZ and SMR). As such, the coding was driven by theory as it was organized according to the theoretical categories in the technology acceptance model (e.g., the perceived usefulness of AED training of students and the perceived usefulness of AED deployment at school). But the coding was also data driven as additional themes and subthemes that had emerged from the data were applied (e.g., knowledge and experience with AEDs).

Step 4

Information for each theme was extracted from all of the interviews, and quotes were selected based on how well they illustrated and elucidated the themes (LZ).

Step 5

We looked at relations between the themes