A software‐based observational coding approach for evaluating paediatric dental pain, anxiety, and fear

BACKGROUND: Dental practitioners desire non-pharmacological methods to alleviate anxiety, fear, and pain in children receiving dental care; high-quality evidence, however, is required to evaluate methods' efficacy. AIM: This study aimed to develop and validate an observation-based coding approach (paediatric dental pain, anxiety, and fear coding approach [PAFCA]) to evaluate non-pharmacological behavior management techniques for anxiety, fear, and pain. DESIGN: Objective (video-based) and subjective (self-reported) anxiety, fear, and pain data were collected from a pilot clinical trial evaluating animal-assisted therapy (AAT) in paediatric dentistry, in which 37 children aged 7-14 were assigned to AAT or control before dental treatment (restorations or extractions). A coding approach utilizing a codebook, a gold standard calibration video, and a user training guide was developed. Trained examiners coded the gold standard video for inter-rater agreement, and masked, calibrated examiners analyzed videos using the Noldus Observer XT software. RESULTS: A novel, software-based coding approach was developed, with moderately high inter-rater agreement. Using PAFCA, we found children reporting higher levels of pain, fear, and anxiety exhibited treatment-interfering behaviors, including crying/moaning, attempts to dislodge instruments, and more upper and lower body movements. CONCLUSION: PAFCA shows promise as a reliable tool for assessing anxiety, pain, and fear in behavioral research for paediatric dentistry.

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Publication Details

Journal
UNC Libraries
Published
2024-09-14
DOI
https://doi.org/10.17615/arm3-vx66
Primary Topic
Empathy and Medical Education
Type
article
Field-Weighted Citation Impact
0.00

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article

A software‐based observational coding approach for evaluating paediatric dental pain, anxiety, and fear

Allen Rapolla, Clare Bocklage, Olivia TumSuden, Katelyn Cass et al.
UNC Libraries
Empathy and Medical Education
article

A software‐based observational coding approach for evaluating paediatric dental pain, anxiety, and fear

Allen Rapolla, Clare Bocklage, Olivia TumSuden, Katelyn Cass, Christina Graves, Laura Anne Jacox, Eric A. Hodges, Jeannie Ginnis, Timothy J. Strauman, Caroline M. Sawicki, Kimon Divaris, Eleanor Nanney, Jessica Lee, Raven Selden
article en

Abstract

BACKGROUND: Dental practitioners desire non-pharmacological methods to alleviate anxiety, fear, and pain in children receiving dental care; high-quality evidence, however, is required to evaluate methods' efficacy. AIM: This study aimed to develop and validate an observation-based coding approach (paediatric dental pain, anxiety, and fear coding approach [PAFCA]) to evaluate non-pharmacological behavior management techniques for anxiety, fear, and pain. DESIGN: Objective (video-based) and subjective (self-reported) anxiety, fear, and pain data were collected from a pilot clinical trial evaluating animal-assisted therapy (AAT) in paediatric dentistry, in which 37 children aged 7-14 were assigned to AAT or control before dental treatment (restorations or extractions). A coding approach utilizing a codebook, a gold standard calibration video, and a user training guide was developed. Trained examiners coded the gold standard video for inter-rater agreement, and masked, calibrated examiners analyzed videos using the Noldus Observer XT software. RESULTS: A novel, software-based coding approach was developed, with moderately high inter-rater agreement. Using PAFCA, we found children reporting higher levels of pain, fear, and anxiety exhibited treatment-interfering behaviors, including crying/moaning, attempts to dislodge instruments, and more upper and lower body movements. CONCLUSION: PAFCA shows promise as a reliable tool for assessing anxiety, pain, and fear in behavioral research for paediatric dentistry.

UNC Libraries
University of North Carolina at Chapel Hill (US)
National Institutes of Health, National Center for Advancing Translational Sciences
Openalex Percentile: Top 79%
Empathy and Medical Education
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