Table 1_Role reconstruction and competency requirements of emergency nurses in the human-m

A qualitative study conducted from October 2025 to January 2026, involving 22 emergency department nurses from two tertiary hospitals in Shanghai. The research, authored by Lina Chen and published on figshare in April 2026, explores role reconstruction and competency requirements for nurses working with AI and automation. It identifies three major themes and eight sub-themes related to nurses' attitudes, role transformation, and required skills.

Use Cases

• Designing clinical training curricula based on identified nurse competency requirements.
• Informing policy for role boundary definition in emergency departments based on described role transformation themes.
• Optimizing human-machine collaborative workflows in emergency care based on nurses' reported attitudes and experiences.
• Benchmarking nurse preparedness for AI integration in other hospital settings using the identified themes as a framework.

Strengths

• Data is derived from 22 participant interviews, providing qualitative depth.
• Analysis followed the structured Colaizzi seven-step method.
• The study explicitly identifies 3 major themes and 8 sub-themes from the interview data.

Limitations

• Row count and column-level documentation are absent; field semantics must be inferred after download.
• The 17.5 KB file size suggests the dataset is a summary document, not raw interview transcripts or a structured data table.
• Data reflects a specific geographic (Shanghai) and institutional (tertiary hospitals) context, which may limit generalizability.

Provenance

Source

Lina Chen via figshare.

Collection Method

Phenomenological qualitative research using semi-structured interviews, analyzed with the Colaizzi seven-step method.

Time Range

Study conducted from October 2025 to January 2026.

Freshness

Last updated 2026-04-23 05:35:11; freshness should be verified.

Geography

Shanghai, China (two tertiary hospitals).