Oral Health Behaviors for Young Low-Income Urban Children during the COVID-19 Pandemic: A Mixed Methods Analysis.

This research assessed oral health behaviors changes in urban families with young children during the stay-at-home period of the COVID-19 pandemic (Nov 2020-August 2021). Survey data on oral health behaviors were collected in homes at three points before COVID-19, and via phone during COVID-19. A subset of parents and key informants from clinics and social service agencies completed in-depth interviews via video/phone. Of the 387 parents invited, 254 completed surveys in English or Spanish (65.6%) during COVID-19. Fifteen key informant interviews (25 participants) and 21 family interviews were conducted. The mean child age was 4.3 years. Children identified as mainly Hispanic (57%) and Black race (38%). Parents reported increased child tooth brushing frequency during the pandemic. Family interviews highlighted changes in family routines that impacted oral health behaviors and eating patterns, suggesting less optimal brushing and nutrition. This was linked to changed home routines and social presentability. Key informants described major disruptions in oral health services, family fear, and stress. In conclusion, the stay-at-home period of the COVID-19 pandemic was a time of extreme routine change and stress for families. Oral health interventions that target family routines and social presentability are important for families during times of extreme crisis.

Association between neighborhood disadvantage and children's oral health outcomes in urban families in the Chicago area.

Purpose: The prevalence of childhood caries in urban Chicago, compared with national and state data, indicates that neighborhood context influences oral health. Our objective was to delineate the influence of a child's neighborhood on oral health outcomes that are predictive of caries (toothbrushing frequency and plaque levels). Methods: Our study population represents urban, Medicaid-enrolled families in the metropolitan Chicago area. Data were obtained from a cohort of participants (child-parent dyads) who participated in the Coordinated Oral Health Promotion (CO-OP) trial at 12 months of study participation (N = 362). Oral health outcomes included toothbrushing frequency and plaque levels. Participants' neighborhood resource levels were measured by the Area Deprivation Index (ADI). Linear and logistic regression models were used to measure the influence of ADI on plaque scores and toothbrushing frequency, respectively. Results: Data from 362 child-parent dyads were analyzed. The mean child age was 33.6 months (SD 6.8). The majority of children were reported to brush at least twice daily (n = 228, 63%), but the mean plaque score was 1.9 (SD 0.7), classified as "poor." In covariate-adjusted analyses, ADI was not associated with brushing frequency (0.94, 95% CI 0.84-1.06). ADI was associated with plaque scores (0.05, 95% CI 0.01-0.09, p value = 0.007). Conclusions: Findings support the hypothesis that neighborhood-level factors influence children's plaque levels. Because excessive plaque places a child at high risk for cavities, we recommend the inclusion of neighborhood context in interventions and policies to reduce children's oral health disparities. Existing programs and clinics that serve disadvantaged communities are well-positioned to support caregivers of young children in maintaining recommended oral health behaviors.

Oral health behaviors for young low-income urban children during the COVID-19 pandemic: a mixed methods analysis.

This research assessed oral health behaviors changes in urban families with young children during the stay-at-home period of the COVID-19 pandemic. Survey data on oral health behaviors were collected in homes at three points over one year before COVID-19, and then via phone during COVID-19. Multivariate logistic regression was used to model tooth brushing frequency. A subset of parents completed in-depth interviews via video/phone that expanded on oral health and COVID-19. Key informant interviews via video/phone were also conducted with leadership from 20 clinics and social service agencies. Interview data were transcribed and coded, and themes were extracted. COVID-19 data collection went from Nov 2020 - August 2021. Of the 387 parents invited, 254 completed surveys in English or Spanish (65.6%) during COVID-19. Fifteen key informant (25 participants) and 21 parent interviews were conducted. The mean child age was approximately 4.3 years. Children identified as mainly Hispanic (57%) and Black race (38%). Parents reported increased child tooth brushing frequency during the pandemic. Parent interviews highlighted significant changes in family routines that impacted oral health behaviors and eating patterns, suggesting less optimal brushing and nutrition. This was linked to changed home routines and social presentability. Key informants described major disruptions in their oral health services and significant family fear and stress. In conclusion, the stay-at-home period of the COVID-19 pandemic was a time of extreme routine change and stress for families. Oral health interventions that target family routines and social presentability are important for families during times of extreme crisis.

Calibration and reliability testing of a novel asynchronous photographic plaque scoring system in young children.

OBJECTIVES: The Simplified Oral Hygiene Index for Maxillary Incisors (OHI-MIS) is a novel plaque scoring system adapted for young children. This study describes calibration training and testing used to establish the inter- and intra-rater reliability for OHI-MIS measured from clinical photographs. METHODS: Two raters from the Coordinated Oral Health Promotion Chicago (CO-OP) and one from the Behavioral EConomics for Oral health iNnovation (BEECON) randomized controlled trials (RCTs) underwent calibration with gold standard raters, followed by annual re-calibration. Raters from CO-OP also completed inter-rater reliability testing; all three raters completed intra-rater reliability testing rounds. Photographs were obtained from children aged 9-39 months. RESULTS: All three raters achieved greater than 0.77 Lin's Concordance Correlation (LCC) versus gold standard consensus during calibration. All three raters had LCC ≥0.83 at recalibration 1 year later. CO-OP trial raters scored 604 photos (151 sets of 4 photographs); mostly both raters were somewhat/very confident in their scoring (≥89%), describing the most photos as "clear" (90% and 81%). The CO-OP inter-rater LCC for total OHI-MIS score was 0.86, changing little when low quality or confidence photos were removed. All three raters demonstrated high intra-rater reliability (≥0.83). CONCLUSIONS: The OHI-MIS plaque scoring system on photos had good reliability within and between trials following protocol training and calibration. OHI-MIS provides a novel asynchronous plaque scoring system for use in young children. Non-clinicians in field or clinical settings can obtain photographs, offering new opportunities for research and clinical care.

The Impact of the Covid-19 Pandemic on Applicants to Advanced Education in Pediatric Dentistry Programs and Recommendations for Virtual Interviews.

Purpose:To assess the impact of the Covid-19 pandemic on applicants for advanced education programs in pediatric dentistry in the United States and provide recom- mendations for virtual interviews (VI).
Methods:A cross-sectional survey was emailed to pediatric dentistry applicants in the 2020-2021 cycle.
Results:One hundred seventy-five applicants responded. Virtual interviews were the universal format during this timeframe. Forty-four percent admitted to applying to programs they were not initially strongly considering and 42 percent accepted inter- views they would have declined if they had to travel. Applicants found social events with residents only (80 percent), a program overview presentation (86 percent), a virtual tour (77 percent) and a question-and-answer session with residents (85 percent) to be helpful. One-on-one or paired faculty interviews were the most preferred inter- view method. More than half (55 percent) thought programs were not able to learn about them as effectively through virtual compared to an in-person format.
Conclusions: VI caused different applicant behavior due to the low time and financial investment. Applicants valued their time with residents to learn about programs, but were split in their preferences for virtual, in-person or hybrid interviews. Programs can use findings from this study to plan future recruitment cycles.

Assessment of automatic cephalometric landmark identification using artificial intelligence.

OBJECTIVE: To compare the accuracy of cephalometric landmark identification between artificial intelligence (AI) deep learning convolutional neural networks (CNN) You Only Look Once, Version 3 (YOLOv3) algorithm and the manually traced (MT) group. SETTING AND SAMPLE POPULATION: The American Association of Orthodontists Federation (AAOF) Legacy Denver collection was used to obtain 110 cephalometric images for this study. MATERIALS AND METHODS: Lateral cephalograms were digitized and traced by a calibrated senior orthodontic resident using Dolphin Imaging. The same images were uploaded to AI software Ceppro DDH Inc The Cartesian system of coordinates with Sella as the reference landmark was used to extract x- and y-coordinates for 16 cephalometric points: Nasion (Na), A point, B point, Menton (Me), Gonion (Go), Upper incisor tip, Lower incisor tip, Upper incisor apex, Lower incisor apex, Anterior Nasal Spine (ANS), Posterior Nasal Spine (PNS), Pogonion (Pg), Pterigomaxillary fissure point (Pt), Basion (Ba), Articulare (Art) and Orbitale (Or). The mean distances were assessed relative to the reference value of 2 mm. Student paired t-tests at significance level of P < .05 were used to compare the mean differences in each of the x- and y-components. SPSS (IBM-vs. 27.0) software was used for the data analysis. RESULTS: There was no statistical difference for 12 out of 16 points when analysing absolute differences between MT and AI groups. CONCLUSION: AI may increase efficiency without compromising accuracy with cephalometric tracings in routine clinical practice and in research settings.