19 semi-structured interview transcripts and thematic analysis codes from stroke survivors and occupational therapists. The data was collected by Sunghoon Ivan Lee from November 2019 to September 2020 across the USA. It explores stakeholder perspectives on using wearable sensors and arm activity data in clinical practice.
Use Cases
- Analyzing stakeholder receptiveness to wearable sensors in clinical practice based on interview themes
- Identifying design considerations for wearable performance monitoring systems based on described challenges
- Exploring therapists' envisioned strategies for using patient-generated sensor data for personalized therapy
Strengths
- Includes perspectives from two key stakeholder groups: 4 stroke survivors and 15 occupational therapists
- Data collection spanned from November 2019 to September 2020, providing a temporal snapshot
- Analysis was performed using thematic analysis with ATLAS.ti Cloud and affinity sessions
Limitations
- Row count and column-level documentation are absent; field semantics must be inferred after download
- The sample size of 19 participants may limit generalizability
- Description metadata is limited; actual data quality requires manual inspection after download
Provenance
- Source
- Lee, Sunghoon Ivan; QDR Harvested Dataverse
- Collection Method
- Semi-structured interviews, audio-recorded, transcribed, and analyzed via thematic analysis
- Time Range
- Stroke survivors: November 2019 to March 2020; Occupational therapists: July 2020 to September 2020
- Freshness
- Last updated 2025-10-20 19:59:22; freshness should be verified
- Geography
- Stroke survivors recruited within Massachusetts, USA; Occupational therapists recruited across USA