Evaluating Training Effectiveness for a Technology-Driven Pain Assessment Application: A Cross-Sectional Study

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PURPOSE: Appropriate pain assessment of adults is critical for effective pain management. Technology-driven tools can contribute to improved pain assessments. Training is vital when integrating new clinical digital tools. Minimal studies have evaluated post-training outcomes. The aim of this study was to evaluate the training provided to clinical staff on the use of a pain assessment application for hospitalized adult patients. DESIGN: A cross-sectional study utilizing The Kirkpatrick Model of Training Evaluation. METHODS: Clinical staff (nurses and physiotherapists) on an acute metropolitan hospital orthopedic ward in Western Australia were invited to face-to-face training of PainChek Universal, a pain assessment application using artificial intelligence. One-hour training used didactic delivery and hands-on practice. Training effectiveness was evaluated against Kirkpatrick's Levels 1 and 2 via a 43-item survey, including two open-ended questions. Data were analyzed using SPSS 25 and content analysis of open-ended responses. RESULTS: A total of 44 staff attended training 19 (43.2%) completed the post-training survey. Most respondents were satisfied with the training and confident to use the application (94.7%). Ten participants (52.6%) desired additional post-training support post-training and 14 (73.7%) agreed the application appears easy to use. Eighteen (94.7%) felt it would be a positive addition to pain assessment. Staff's correct knowledge scores varied (36.8% to 84.2%), indicating a need for further education. CONCLUSIONS AND CLINICAL IMPLICATIONS: Training of a technology-driven application for pain assessment is essential for effective implementation to improve care. Training enabled staff to acquire knowledge and skills, develop user confidence, and understand usability and utility of the application.

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