Systematic Review and Exploratory Meta‐Analysis of AI‐Enabled and Digital Technology‐Assisted Interventions for Dental Anxiety During Dental Treatment.
Saved in:
| Title: | Systematic Review and Exploratory Meta‐Analysis of AI‐Enabled and Digital Technology‐Assisted Interventions for Dental Anxiety During Dental Treatment. |
|---|---|
| Authors: | Saghiri, Mohammad Ali (AUTHOR), Saini, Ravinder S. (AUTHOR), Alshahrani, Ahid Amer (AUTHOR), Vaddamanu, Sunil Kumar (AUTHOR), Alqahtani, Ali (AUTHOR), Baba, Nadim Z. (AUTHOR), Bose, Chandra (AUTHOR) |
| Source: | Depression & Anxiety (1091-4269). 7/2/2026, Vol. 2026, p1-10. 10p. |
| Subjects: | Digital technology, Fear of dentists, Evidence synthesis, Machine learning, Virtual reality, Cognitive therapy |
| Abstract: | Background: Dental anxiety adversely affects receiving dental care when needed. Artificial intelligence (AI)‐enabled and digital technology‐assisted interventions have been recently explored for assessment, monitoring or alleviation of anxiety during dental treatment. The aim of this systematic review was to summarise current evidence and review effectiveness of AI‐enabled or digital technology‐assisted interventions on anxiety and treatment‐related outcomes in dentistry. Method: The review was conducted in accordance with Preferred Reporting for Systematic Reviews and Meta‐analysis (PRISMA) guidelines. Searches were conducted across ScienceDirect, PubMed, Scopus, Google Scholar and Cochrane Library. There were no date limitations applied. Search was restricted to human studies involving AI‐enabled or digital technology‐assisted interventions for dental anxiety management. Both interventional and observational studies were included for review. Data were extracted regarding study characteristics, intervention type, anxiety outcome measures, behavioural response, treatment adherence and satisfaction. Risk of bias was assessed utilising Mixed Methods Appraisal Tool (MMAT). Owing to significant clinical and methodological heterogeneity among the included studies, quantitative synthesis was limited to a small subset of comparable studies and was therefore considered exploratory. Results: Seven studies met our eligibility criteria. Eligible studies varied widely in design, population, intervention and outcome assessment modalities used. These were computerised cognitive behavioural therapy (CBT), humanoid robots, smartphone applications, machine learning (ML) approaches to assessment, AI‐linked virtual reality (VR) or biofeedback programs. Narrative synthesis suggested that several interventions were associated with reductions in dental anxiety or improvements in patient behaviour. Quantitative pooling was possible for only a few studies which were found to be comparable. Our conclusions from this exploratory meta‐analysis are limited by the small number of studies with comparison groups available and considerable heterogeneity. Conclusion: AI‐enabled and digital technology‐assisted interventions have potential to improve dental anxiety‐related outcomes and dental patient experience. The evidence is currently limited. The available studies are small and heterogeneous and methodologically limited. Future investigations should include larger, robust trials with standardised outcome measures and consistent operational definitions of AI. [ABSTRACT FROM AUTHOR] |
| Copyright of Depression & Anxiety (1091-4269) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
|
Full text is not displayed to guests.
Login for full access.
|
|
| Abstract: | Background: Dental anxiety adversely affects receiving dental care when needed. Artificial intelligence (AI)‐enabled and digital technology‐assisted interventions have been recently explored for assessment, monitoring or alleviation of anxiety during dental treatment. The aim of this systematic review was to summarise current evidence and review effectiveness of AI‐enabled or digital technology‐assisted interventions on anxiety and treatment‐related outcomes in dentistry. Method: The review was conducted in accordance with Preferred Reporting for Systematic Reviews and Meta‐analysis (PRISMA) guidelines. Searches were conducted across ScienceDirect, PubMed, Scopus, Google Scholar and Cochrane Library. There were no date limitations applied. Search was restricted to human studies involving AI‐enabled or digital technology‐assisted interventions for dental anxiety management. Both interventional and observational studies were included for review. Data were extracted regarding study characteristics, intervention type, anxiety outcome measures, behavioural response, treatment adherence and satisfaction. Risk of bias was assessed utilising Mixed Methods Appraisal Tool (MMAT). Owing to significant clinical and methodological heterogeneity among the included studies, quantitative synthesis was limited to a small subset of comparable studies and was therefore considered exploratory. Results: Seven studies met our eligibility criteria. Eligible studies varied widely in design, population, intervention and outcome assessment modalities used. These were computerised cognitive behavioural therapy (CBT), humanoid robots, smartphone applications, machine learning (ML) approaches to assessment, AI‐linked virtual reality (VR) or biofeedback programs. Narrative synthesis suggested that several interventions were associated with reductions in dental anxiety or improvements in patient behaviour. Quantitative pooling was possible for only a few studies which were found to be comparable. Our conclusions from this exploratory meta‐analysis are limited by the small number of studies with comparison groups available and considerable heterogeneity. Conclusion: AI‐enabled and digital technology‐assisted interventions have potential to improve dental anxiety‐related outcomes and dental patient experience. The evidence is currently limited. The available studies are small and heterogeneous and methodologically limited. Future investigations should include larger, robust trials with standardised outcome measures and consistent operational definitions of AI. [ABSTRACT FROM AUTHOR] |
|---|---|
| ISSN: | 10914269 |
| DOI: | 10.1155/da/8850179 |
