Related Experiment Video
Updated: Jan 13, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
Published on: December 6, 2024
Physical therapists' perspectives on a large language model-powered knowledge translation tool for guideline
Diane Rosen1,2, Dorian Zwanzig3, Barbara Vogel4
1Department of Health and Education, Alice Salomon University of Applied Sciences Berlin, Berlin, Germany.
Background:
Clinical practice guidelines support healthcare professionals in making evidence-based decisions, yet guideline adherence among physical therapists remains inconsistent. To address this gap, a prototype digital knowledge translation tool powered by a large language model (LLM) was developed, with content based on two exemplary high-quality German national guidelines.
Objective:
To (1) explore the experiences of German physical therapists using the tool, (2) assess their perspectives on its utilization in clinical practice, and (3) compare perceptions between outpatient and inpatient settings.
Methods:
Six focus group interviews were conducted: three in a university hospital inpatient setting and three in outpatient physical therapy practices. Discussions were analyzed using qualitative content analysis with inductive and deductive coding.
Results:
Twenty physical therapists (11 inpatient, 9 outpatient) participated. Overall experiences were positive, though prolonged response times were criticized. Utilization was thought to depend on time availability and workplace digitization. The tool's potential assisting with clinical questions was highlighted. No considerable differences in experiences across settings were noted. Inpatient therapists envisioned using the tool between sessions for personal knowledge enhancement, whereas outpatient therapists anticipated utilization during sessions for patient education.
Conclusion:
LLM-based knowledge translation tools may contribute to improving guideline adherence among physical therapists. Successful implementation requires assessment of digital infrastructure, relevance to clinical needs, and users' digital literacy. Further research should evaluate the quality of LLM-generated summaries to ensure validity and trustworthiness, and optimize the tools' usability regarding speed and content. Development should also prompt ethical considerations about their role in clinical decision-making and patient care.
More Related Videos
06:16Involving Individuals with Developmental Language Disorder and Their Parents/Carers in Research Priority Setting
Published on: June 6, 2020
05:47Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
Related Concept Videos
Methods of Documentation VI: Case Management Model
For example, a patient with a chronic...
Modeling in Therapy
Participant Modeling
Participant modeling involves therapists demonstrating calm and effective behaviors in...
Improving Translational Accuracy