# Acceptance of voice assistant technology in dental practice: A cross sectional study with dentists and validation using structural equation modeling

**Authors:** Spencer Warren, Daniel Claman, Beau Meyer, Jin Peng, Emre Sezgin

PMC · DOI: 10.1371/journal.pdig.0000510 · 2024-05-14

## TL;DR

This study explores how dentists feel about using voice assistants in their work, finding that performance and enjoyment are key factors in adoption, while privacy concerns act as barriers.

## Contribution

This is the first study to investigate dentists' acceptance of voice assistant technology using structural equation modeling.

## Key findings

- Performance expectancy and perceived enjoyment significantly increase dentists' intention to use voice assistants.
- Perceived risk negatively influences dentists' intention to adopt voice assistant technology.
- Self-efficacy explains 35.5% of the variance in perceived enjoyment of using voice assistants.

## Abstract

Voice assistant technologies (VAT) has been part of our daily lives, as a virtual assistant to complete requested tasks. The integration of VAT in dental offices has the potential to augment productivity and hygiene practices. Prior to the adoption of such innovations in dental settings, it is crucial to evaluate their applicability. This study aims to assess dentists’ perceptions and the factors influencing their intention to use VAT in a clinical setting. A survey and research model were designed based on an extended Unified Theory of Acceptance and Use of Technology (UTAUT). The survey was sent to 7,544 Ohio-licensed dentists through email. The data was analyzed and reported using descriptive statistics, model reliability testing, and partial least squares regression (PLSR) to explain dentists’ behavioral intention (BI) to use VAT. In total, 257 participants completed the survey. The model accounted for 74.2% of the variance in BI to use VAT. Performance expectancy and perceived enjoyment had significant positive influence on BI to use VAT. Perceived risk had significant negative influence on BI to use VAT. Self-efficacy had significantly influenced perceived enjoyment, accounting for 35.5% of the variance of perceived enjoyment. This investigation reveals that performance efficiency and user enjoyment are key determinants in dentists’ decision to adopt VAT. Concerns regarding the privacy of VAT also play a crucial role in its acceptance. This study represents the first documented inquiry into dentists’ reception of VAT, laying groundwork for future research and implementation strategies.

Voice assistants, such as Siri and Alexa, have become more common in daily life, and this technology could provide increased efficiency in the dental field. Voice assistants could allow dentists to engage with computers and navigate a patient’s record via voice interaction. Since dentists are often utilizing their hands during patient care, this technology would increase productivity and hygiene during clinical practice and operations. In this research study, we aimed to investigate dentists’ perception in utilizing voice assistants in the clinic and to understand what factors influence their perception to adopt this technology. Dentists were invited to participate in an online survey. Survey findings reported that dentists perceive that voice assistants could improve their daily performance and the enjoyment of using a new technology could affect their perception. Security and privacy issues could discourage dentists from adopting voice assistants in the clinics. This research provides a foundation for features to design and implement voice assistants for the dental office.

## Full-text entities

- **Diseases:** infection (MESH:D007239), caries (MESH:D003731), BI (MESH:D014202), AI (MESH:C538142), VAT (MESH:D014832)
- **Chemicals:** VAT (-)
- **Species:** Mus musculus (house mouse, species) [taxon 10090], Homo sapiens (human, species) [taxon 9606]

## Figures

6 figures with captions in the complete paper: https://tomesphere.com/paper/PMC11093337/full.md

---
Source: https://tomesphere.com/paper/PMC11093337