Psychiatrists' Attitudes Toward Disruptive New Technologies: Mixed-Methods Study.

Area of Science:

• Digital Health
• Clinical Decision Support Systems (CDSSs)
• Psychiatry

Background:

• Advancements in machine learning (ML), Ecological Momentary Assessment (EMA), computerized adaptive testing (CAT), digital phenotyping, imaging, and biomarkers are transforming medicine.
• These technologies are paving the way for a new era in medical practice and patient care.

Purpose of the Study:

• To explore psychiatrists' perspectives on emerging clinical decision support systems (CDSSs).
• To assess the acceptability of new technologies like EMA, CAT, digital phenotyping, and ML-based diagnostics.
• To identify factors influencing the acceptability of these CDSSs among psychiatrists.

Main Methods:

• A quantitative web-based survey was administered to a sample of psychiatrists.
• The screenplay method was used, presenting 3 scenarios featuring EMA/CAT, digital phenotype (wristband), and ML-based blood tests/MRI.
• Acceptability was evaluated across usefulness, usability, reliability, and risk domains.

Main Results:

• Overall acceptability of new CDSSs was moderate among psychiatrists.
• Magnetic resonance imaging (MRI) with ML was perceived as most useful; connected wristbands were least useful.
• All systems were perceived as risky (79.6%), and acceptability was significantly influenced by gender, age, and theoretical approach.

Conclusions:

• This study highlights moderate acceptability of new CDSSs, primarily due to a lack of knowledge rather than outright rejection.
• Acceptability profiles strongly correlate with psychiatrists' professional culture and socio-epidemiological variables.
• Addressing medical, forensic, and ethical concerns (e.g., data security, privacy) and providing training are crucial for successful integration.