Skip to main content
OpenTrials
Not Yet Recruiting

NCT Number: NCT07078240

Examining Nurses' Trust and Acceptance of FAIR, an AI-powered Falls Risk Recommender

An exploratory mixed-method study will be conducted to test acceptance and trust of an AI-powered falls risk predictor system by inpatient hospital nurses

Not Yet Recruiting

Trial opening soon.

Get Notified

Key information

Conditions

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

About this study

This protocol covers the trial component of a 4-year PhD research study covering focus group discussions with nurses on AI risk systems, workshops to gather feedback on the AI system and feasibility testing in a simulated environment and clinical environment

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Practicing nurse involved in falls risk assessments of patients

Exclusion criteria

-

Treatment and study plan

Falls risk - Artificial Intelligence Recommender (FAIR)

Other

FAIR is an alert system built into the hospital's electronic medical record system. It is an adaptation of a machine learning model for fall risk calculation built in another hospital in Singapore. FAIR combines multiple patient-specific variables to identify if a patient is at increased risk of falling during their inpatient stay, marking them as a 'falls risk'.

Based on the 'flag' raised, the nurse will be instructed to prioritise her falls risk assessment of the patient (If deemed 'high risk') or to do so subsequently as a lower priority once other pressing patient care issues are resolved (if deemed 'low risk').

That way, it ensures the requirements of each patient receiving a falls risk assessment as scored through mWHeFRA are still met, with FAIR allowing nurses to better prioritise their focus and attention on the patient that most needs the assessment at point of admission,

modified Western Health Falls Risk Assessment Tool (mWHeFRA)

Other

The mWHeFRA is the hospital's standard falls risk assessment tool. All nurses are expected to be proficient in its use to guide their risk assessment of patients

Primary outcomes

  1. Incidence of FAIR's flag acceptance

    Time frame: 1 Day of Study

    Examination of how often the flags raised by FAIR are accepted by nurses, and whether they are accepted or ignored correctly.

  2. Time taken to do falls risk assessment

    Time frame: 1 Day of Study

    The time taken by the nurses to perform their falls risk assessment will be recorded

Secondary outcomes

  1. Time spent looking at FAIR

    Time frame: 1 Day of Study

    The time each nurses takes looking at the FAIR falls risk assessment will be assessed

  2. Baseline and Post-Simulation Nurse trust and acceptance of FAIR

    Time frame: Baseline

    Measured by the adapted Unified Theory of Acceptance and Use of Technologies and System Usability Survey, adjusted to better capture the key predictors of nurse acceptance

Study contacts

Contact information is provided by the study sponsor or research team.

George Glass, PhD Student

CONTACT

[email protected]

+65 6903-5384

Sponsors and collaborators

Lead sponsor

Tan Tock Seng Hospital

Other

Collaborators

  • Marquette University
  • Nanyang Technological University

Registry information

Official study title

"You Sure or Not?" Examining the Trust, Acceptance and Adoption of Falls Risk - Artificial Intelligence Recommender (FAIR) System by Nurses

Important dates

Study start
2027
Primary completion
2027
Study completion
2029
First posted
Jul 22, 2025
Registry last updated
Jul 22, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.