The 12-item version of the SOAPP-R has potential as a short risk screener and should be tested prospectively.

Background The Screener and Opioid Assessment for Patients with Pain-Revised (SOAPP-R) is a 24-item self-report instrument that was developed to aid providers in predicting aberrant medication-related behaviors among chronic pain patients. Although the SOAPP-R has garnered widespread use, certain patients may be dissuaded from taking it because of its length. Administrative barriers associated with lengthy questionnaires further limit its utility. Objective To investigate the extent to which two techniques for computer-based administration (curtailment and stochastic curtailment) reduce the average test length of the SOAPP-R without unduly affecting sensitivity and specificity. Design Retrospective study Setting Pain management centers Subjects Four hundred and twenty-eight chronic non-cancer pain patients Methods Subjects had taken the full-length SOAPP-R and been classified by the Aberrant Drug Behavior Index (ADBI) as having engaged or not engaged in aberrant medication-related behavior. Curtailment and stochastic curtailment were applied to the data in post-hoc simulation. Sensitivity and specificity with respect to the ADBI, as well as average test length, were computed for the full-length test, curtailment, and stochastic curtailment. Results The full-length SOAPP-R exhibited a sensitivity of 0.745 and a specificity of 0.671 for predicting the ADBI. Curtailment reduced the average test length by 26% while exhibiting the same sensitivity and specificity as the full-length test. Stochastic curtailment reduced the average test length by as much as 65% while always exhibiting sensitivity and specificity for the ADBI within 0.035 of those of the full-length test. Conclusions Curtailment and stochastic curtailment have potential to improve the SOAPP-R’s efficiency in computer-based administrations.

Introduction The spread of coronavirus disease 2019 (COVID-19) in the spring of 2020 resulted in the temporary suspension of elective dental procedures and clinical dental education in academic institutions. This study describes the utilization of the Tufts University School of Dental Medicine (TUSDM) emergency dental clinic during the peak surge in COVID-19 cases in Massachusetts, highlighting the number of endodontic emergencies. Methods Aggregate data from clinical encounters and call records to an emergency triage phone line from March 30 through May 8, 2020 were used to describe the characteristics of dental emergencies, clinical encounters and procedures performed. Results A total of 466 patient interactions occurred during this period, resulting in 199 patients advised by phone and 267 clinical encounters. The most common dental emergencies were severe dental pain from pulpal inflammation (27.7% of clinical encounters) followed by surgical post-operative visit (13.1%). The most frequent procedures were extractions (13.9% of clinical encounters) and surgical follow up (13.5%). 50.2% of the clinical encounters were categorized as aerosol-generating, and 86.1% of encounters would have required treatment in a hospital emergency department if dental care was not available. There were no known transmissions of SARS-CoV-2 among clinic providers, patients, or staff during this period. Conclusions These results highlight the importance of endodontic diagnosis and treatment in the provision of emergency dental care during a pandemic, and demonstrates that dental treatment can be provided in a manner that minimizes the risk of viral transmission, maintaining continuity of care for a large patient population.

The findings of a subjective questionnaire showed that an experimental moisturizing mouthwash provided greater relief than water only from dry mouth symptoms over 8 days.

The use of surveys is popular in dental education research. However, designing and conducting a survey can have many pitfalls. This article aims to prepare a new researcher or one with little experience to undertake survey research. It covers points such as survey design (including question construction), pilot testing for validity and reliability, sampling strategy, methods to increase response rates, logistical considerations, and items to include when writing the manuscript. Careful consideration of a survey from beginning to end can help one design and conduct a successful study that meets its research aims and adds valuable evidence to the literature.

Few clinical datasets exist in dentistry to conduct secondary research. Hence, a novel dental data repository called BigMouth was developed, which has grown to include 11 academic institutions contributing Electronic Health Record data on over 4.5 million patients. The primary purpose for BigMouth is to serve as a high-quality resource for rapidly conducting oral health-related research. BigMouth allows for assessing the oral health status of a diverse US patient population; provides rationale and evidence for new oral health care delivery modes; and embraces the specific oral health research education mission. A data governance framework that encouraged data sharing while controlling contributed data was initially developed. This transformed over time into a mature framework, including a fee schedule for data requests and allowing access to researchers from noncontributing institutions. Adoption of BigMouth helps to foster new collaborations between clinical, epidemiological, statistical, and informatics experts and provides an additional venue for professional development.

Objectives were to combine computer-based stopping rules with the 12-item form of the Screener and Opioid Assessment for Patients with Pain-Revised (SOAPP-R), and to compare this combined procedure with the fulllength (24-item) SOAPP-R, the computer-based stopping rules alone, and the 12-item short form alone. Three datasets were analyzed, including data from 428 subjects from the initial or cross-validation studies of the SOAPP-R; 84 patients from a pain center; and 110 primary care patients.Subjects completed the full-length SOAPP-R and were assessed for aberrant medication-related behaviors. A realdata simulation was conducted to determine the screening characteristics and mean test length of each version of the SOAPP-R. One procedure combining stochastic curtailment with the 12-item short form reduced the mean length by 37% to 42% compared to the short form alone; by 42% to 45% compared to stochastic curtailment alone;and by 68% to 71% compared to the full-length form. The combined procedure had lower mean test lengths, and

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