Artificial intelligence in clinical occupational therapy: Current and future applications and practitioner insights

Area of Science:

• Occupational therapy
• Artificial intelligence
• Health informatics

Background:

• Occupational therapy practitioners (OTPs) are increasingly adopting artificial intelligence (AI) tools.
• Barriers to AI adoption include insufficient training, high costs, and ethical considerations.
• Understanding AI usage patterns and influencing factors is crucial for its advancement in occupational therapy.

Purpose of the Study:

• To explore current AI utilization among OTPs.
• To identify anticipated future AI applications in occupational therapy.
• To examine the relationship between AI adoption, professional experience, and practice environments.

Main Methods:

• A descriptive quantitative survey was employed.
• Data collected included years of practice, practice settings, AI exposure, and AI use.
• Participants were occupational therapists and occupational therapy assistants.

Main Results:

• Over 60% of participants were familiar with AI, but only 17% had formal training.
• Common AI applications included documentation software, wearables, and large language models.
• Familiarity with AI correlated with a positive outlook on its impact, with younger clinicians expecting more frequent future use.

Conclusions:

• Increasing AI familiarity among OTPs presents opportunities for practice enhancement.
• Gaps in formal training and generational differences in expected AI use necessitate tailored educational strategies.
• Effective AI integration requires addressing current barriers and leveraging growing familiarity to advance the profession.