Exploring the acceptability of a lip-reading app in acute and critical care: perspectives from patients with tracheostomies, relatives and healthcare professionals

Aims
Effective communication with patients with tracheostomies presents a significant clinical challenge. Speech Recognition Application for the Voice Impaired (SRAVI) is a digital lip-reading app that converts silent speech into text and audio, supporting communication between patients, relatives and healthcare professionals. Despite its potential, the acceptability of SRAVI among users remains unknown, limiting understanding of its real-world implementation. This study aimed to explore the acceptability of SRAVI among patients with tracheostomies, their relatives and staff in acute and critical care.

Methods
A qualitative exploratory design was employed, using semi-structured interviews and focus groups with patients, relatives and healthcare professionals who had used SRAVI. Analysis was guided by the Theoretical Framework of Acceptability (TFA), which conceptualises acceptability across seven constructs- affective attitude, burden, ethicality, intervention coherence, opportunity costs, perceived effectiveness and self-efficacy. Saliency analysis was applied to weight constructs according to importance and recurrence.

Findings
49 participants (35 healthcare professionals, 9 patients, 5 relatives) contributed data. Burden and perceived effectiveness were the most influential drivers of engagement with SRAVI. Ethical and affective factors influenced willingness to use the app, while confidence and ability moderated uptake. Staff highlighted time constraints and workflow challenges, whereas patients and relatives emphasised meaningful communication. Acceptability varied according to perceived effectiveness, burden, user confidence and clinical context, with technological and practical limitations contributing to negative experiences.

Conclusions
SRAVI's acceptability was shaped by practical demands, value-based considerations, perceived effectiveness and user confidence. Addressing these factors through simplified setup, training, tailoring to patient capability, and demonstrating benefits may support successful implementation. Saliency-informed TFA analysis provides a structured approach to prioritising refinements and adoption strategies.

Implications for clinical practice
Iterative, TFA-informed development aligned with patient needs and acuity, alongside established communication methods, may enhance acceptability and communication quality in real-world clinical contexts.