Examining Nurses' Trust and Acceptance of FAIR, an AI-powered Falls Risk Recommender
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Falls risk - Artificial Intelligence Recommender (FAIR), modified Western Health Falls Risk Assessment Tool (mWHeFRA).
- Who it may be relevant to
- Registry conditions: Falls Risk. Basic parameters: No limits · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Center list to be confirmed — check the primary protocol.
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
"You Sure or Not?" Examining the Trust, Acceptance and Adoption of Falls Risk - Artificial Intelligence Recommender (FAIR) System by Nurses
Overview
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
Detailed description
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
Interventions
- Other Falls risk - Artificial Intelligence Recommender (FAIR)
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 - Other modified Western Health Falls Risk Assessment Tool (mWHeFRA)
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 outcome measures
- Incidence of FAIR's flag acceptance [Time frame: 1 Day of Study]
- Time taken to do falls risk assessment [Time frame: 1 Day of Study]
Secondary outcome measures (2)
- Time spent looking at FAIR [Time frame: 1 Day of Study]
- Baseline and Post-Simulation Nurse trust and acceptance of FAIR [Time frame: Baseline]
Eligibility criteria
Inclusion criteria
- Practicing nurse involved in falls risk assessments of patients
Exclusion criteria
\-
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: Yes
Study design
- Allocation
- Non-randomized
- Model
- Parallel assignment
- Masking
- Open label
- Primary purpose
- Health services research
Study locations
Center list to be confirmed — check the primary protocol.
Publications
- Schulz PJ, Lwin MO, Kee KM, Goh WWB, Lam TYT, Sung JJY. Modeling the influence of attitudes, trust, and beliefs on endoscopists' acceptance of artificial intelligence applications in medical practice. Front Public Health. 2023 Nov 28;11:1301563. doi: 10.3389/fpubh.2023.1301563. eCollection 2023. PMID 38089040
Identifiers
NCT: NCT07078240 · NMRCRTF25jan-004