Short answer

Prioritize the clear communication of AI-CDSS benefits and ensure algorithmic transparency and user control to drive adoption in healthcare settings.

Field
Human Factors
Source
Healthcare (2025)
Method
Quantitative Research
Sample
440 participants
Evidence
Strong effect

Healthcare professionals are more likely to adopt AI-driven clinical decision support systems when they perceive significant benefits, even if there are technological costs, but this adoption is significantly hampered by a lack of transparency and control over the algorithms. This human factors research insight is drawn from a 2025 study published in Healthcare. Using Quantitative research with 440 participants, researchers explored how this design variable affects real-world outcomes. The key design takeaway: Prioritize the clear communication of AI-CDSS benefits and ensure algorithmic transparency and user control to drive adoption in healthcare settings.

Study
Human FactorsNew This WeekStrong effect

Perceived Benefits of AI-CDSSs Drive Adoption, While Cost and Lack of Transparency Hinder It

Healthcare professionals are more likely to adopt AI-driven clinical decision support systems when they perceive significant benefits, even if there are technological costs, but this adoption is significantly hampered by a lack of transparency and control over the algorithms.

Healthcare · 2025

01

Key Findings

  • 01Perceived benefits of AI-CDSSs are the strongest predictor of adoption intention.
  • 02Technology effort cost negatively impacts attitudes towards AI-CDSSs.
  • 03Social and institutional influence positively fosters acceptance.
  • 04Perceived control and transparency over AI enhance trust.
  • 05Explainable and clinician-supervised AI systems are necessary.
02

Application

Design takeaway

Prioritize the clear communication of AI-CDSS benefits and ensure algorithmic transparency and user control to drive adoption in healthcare settings.

How to apply

When designing AI-driven tools for professional use, conduct user research to identify key perceived benefits and potential barriers related to effort and transparency. Develop clear communication strategies and user interfaces that empower users with understanding and control.

Project actions

  • 01When researching user adoption of technology, consider both the perceived advantages and the potential drawbacks like complexity or lack of clarity.
  • 02Use surveys and statistical analysis to quantify user perceptions and their impact on technology acceptance.
03

Method & Evidence

AimWhat are the key determinants influencing healthcare professionals' intention to adopt Artificial Intelligence Clinical Decision Support Systems (AI-CDSSs)?
MethodQuantitative Research
ProcedureA cross-sectional study was conducted using a structured questionnaire administered to healthcare professionals. Data were analyzed using structural equation modeling (PLS-SEM) to assess the relationships between perceived benefits, technological costs, social/institutional influence, transparency/control, and the intention to adopt AI-CDSSs.
Sample440 participants
ContextHealthcare

Variables

IV["Perceived benefits","Technological effort cost","Social and institutional influence","Transparency and control of algorithms"]
DVIntention to adopt AI-CDSSs
CV["Type of healthcare professional","Experience level","Specific AI-CDSS being considered"]
04

Strengths & Limitations

Strengths

  • +Large sample size provides statistical power.
  • +Use of structural equation modeling allows for complex relationship analysis.

Limitations

Self-reported data can be biased, and the specific context of healthcare professionals might not generalize to other user groups.

Reliability & validity

The study's reliability is supported by the use of a structured questionnaire and statistical analysis. Validity is addressed through the adapted theoretical model and the examination of multiple influencing factors.

Think critically

To what extent do the 'perceived benefits' outweigh the 'technological effort cost' for different user groups within healthcare, and how can design mitigate this trade-off?

05

Design Principles

"User trust in intelligent systems is built upon perceived utility, ease of use, and understandable, controllable algorithmic processes."

Understanding the psychological and perceptual factors influencing the adoption of intelligent technologies is crucial for successful integration into clinical practice. Designers and developers must prioritize demonstrating clear utility and addressing concerns about algorithmic opacity to foster trust and encourage widespread use.

06

What This Means for Your Design

People are more likely to use new AI tools in healthcare if they see how helpful they are, but they won't use them if they are too hard to use or if they don't understand how they work.

How to use in your project

  • 1.This study can be used to justify the importance of user-centered design principles when developing AI-powered systems, emphasizing the need to address user perceptions of benefits, costs, and transparency.
07

Add to My Project

08

Quick Cite

Paragraph starter

This research demonstrates that the successful integration of AI-CDSSs in healthcare is contingent upon users perceiving significant benefits, manageable technological effort, and adequate transparency and control over the system's algorithms. These human factors directly influence adoption intention, underscoring the need for design strategies that prioritize user understanding and trust.

09

Source

Healthcare

The Digital Transformation of Healthcare Through Intelligent Technologies: A Path Dependence-Augmented–Unified Theory of Acceptance and Use of Technology Model for Clinical Decision Support Systems

journal · 2025

View source

Questions About This Research

What does the research say about perceived benefits of ai-cdsss drive adoption, while cost and lack of transparency hinder it?
Prioritize the clear communication of AI-CDSS benefits and ensure algorithmic transparency and user control to drive adoption in healthcare settings. Evidence: Healthcare (2025).
Why does "Perceived Benefits of AI-CDSSs Drive Adoption, While Cost and Lack of Transparency Hinder It" matter for design?
Understanding the psychological and perceptual factors influencing the adoption of intelligent technologies is crucial for successful integration into clinical practice. Designers and developers must prioritize demonstrating clear utility and addressing concerns about algorithmic opacity to foster trust and encourage widespread use.
How can designers apply this research?
Prioritize the clear communication of AI-CDSS benefits and ensure algorithmic transparency and user control to drive adoption in healthcare settings.
What were the main findings?
Perceived benefits of AI-CDSSs are the strongest predictor of adoption intention.. Technology effort cost negatively impacts attitudes towards AI-CDSSs.. Social and institutional influence positively fosters acceptance.. Perceived control and transparency over AI enhance trust.
What research method was used?
Quantitative Research with 440 participants.
How strong is the evidence?
Evidence strength is rated Strong effect, based on a 2025 journal from Healthcare.
What should I do differently in my next project?
When designing AI-driven tools for professional use, conduct user research to identify key perceived benefits and potential barriers related to effort and transparency. Develop clear communication strategies and user interfaces that empower users with understanding and control.
What are the limitations?
The study's findings are based on self-reported intentions and may not perfectly reflect actual adoption behavior. The cross-sectional nature limits the ability to establish causality.