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TRUVACE RECORD VERSION
record: TRV-2026-2434
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-09T06:01:33.072379Z
status: published
lens: p_space
sector: health
headline: High Use, Low Preparation: A Needs Assessment to Inform Curriculum Development for AI in Residency and Fellowship Training
dek: Generative artificial intelligence (Gen-AI) has rapidly entered clinical environments, posing a risk of "cognitive offloading" that may impede the development of independent clinical judgment. This study conducted a cross-sectional survey of residents, fellows, and faculty at a large academic medical center in January 2026 to quantify Gen-AI utilization and perceptions in physical medicine and rehabilitation (PM&R) to inform curriculum development. Thirty-six trainees (95% response rate) and 11 faculty members (…
gain_title: (none)
problem_title: Generative artificial intelligence (Gen-AI) has rapidly entered clinical environments, posing a risk of "cognitive offloading" that may impede the development of independent clinical judgment.
trace_subject: (none)
gain_reading: (none)
gain_evidence: (none)
problem_reading: Generative artificial intelligence (Gen-AI) has rapidly entered clinical environments, posing a risk of "cognitive offloading" that may impede the development of independent clinical judgment.
problem_evidence: (none)
quick_read: Generative artificial intelligence (Gen-AI) has rapidly entered clinical environments, posing a risk of "cognitive offloading" that may impede the development of independent clinical judgment. This study conducted a cross-sectional survey of residents, fellows, and faculty at a large academic medical center in January 2026 to quantify Gen-AI utilization and perceptions in physical medicine and rehabilitation (PM&R) to inform curriculum development.

Thirty-six trainees (95% response rate) and 11 faculty members (30% response rate) completed the survey; 43 (91.5%) reported any Gen-AI use and formed the analytic sample. Among users, 72.1% used Gen-AI daily for clinical learning and 51.2% during patient encounters, yet 67.4% were self-taught and only 7.0% always requested citations.
limitation: 
tag: Evidence-backed problem
key_points: This study conducted a cross-sectional survey of residents, fellows, and faculty at a large academic medical center in January 2026 to quantify Gen-AI utilization and perceptions in physical medicine and rehabilitation (PM&R) to inform curriculum development. | Thirty-six trainees (95% response rate) and 11 faculty members (30% response rate) completed the survey; 43 (91.5%) reported any Gen-AI use and formed the analytic sample. | Among users, 72.1% used Gen-AI daily for clinical learning and 51.2% during patient encounters, yet 67.4% were self-taught and only 7.0% always requested citations.
rundown: Generative artificial intelligence (Gen-AI) has rapidly entered clinical environments, posing a risk of "cognitive offloading" that may impede the development of independent clinical judgment. This study conducted a cross-sectional survey of residents, fellows, and faculty at a large academic medical center in January 2026 to quantify Gen-AI utilization and perceptions in physical medicine and rehabilitation (PM&R) to inform curriculum development.

Thirty-six trainees (95% response rate) and 11 faculty members (30% response rate) completed the survey; 43 (91.5%) reported any Gen-AI use and formed the analytic sample. Among users, 72.1% used Gen-AI daily for clinical learning and 51.2% during patient encounters, yet 67.4% were self-taught and only 7.0% always requested citations.
sources:
- peer_reviewed | American Journal of Physical Medicine & Rehabilitation | https://doi.org/10.1097/phm.0000000000003198 | 2026-11-02
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a81241f073d8be2b70489fc7b690524c633e72829a4d26a4d6c7c3cf1c90fdae

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