This paper describes the simultaneous co-development of Oral Health Behavior Social Support (OHBSS) scales in English and Spanish. OHBSS scales assess social support for toothbrushing, flossing, and dental care utilization, which are targets for interpersonal-level interventions to promote oral health among Hispanic/Latino adults. The focus was on Mexican-origin adults, who comprise the largest United States Hispanic/Latino subgroup and experience a high oral disease burden. All participants self-identified as Mexican-origin adults (ages 21-40 years old), living along the California-Arizona-Mexico border. Independent samples were recruited for each study partnering with Federally Qualified Health Centers. First, we conducted semi-structured interviews about social support for oral health behaviors in August to November 2018 (Study 1, N = 72). Interviews were audio recorded, transcribed (in original language, Spanish or English), and qualitative data were coded and analyzed in Dedoose following three topical codebooks; excerpts were used to co-create the large bilingual item data bank (OHBSSv1). The item bank was pre-tested via 39 cognitive interviews between December 2019 to March 2020, reviewed by an expert panel with several bilingual members, reduced to 107 Spanish/109 English items (OHBSSv2), then pilot tested in January to December 2021 (Study 2, N = 309). Pilot survey data were analyzed through Exploratory Factor Analysis and Horn's parallel analysis, overall and by language, to examine response patterns and inform item selection (OHBSSv3). The scales queried social support for toothbrushing, flossing, and dental care utilization across 39 items from three sources (family, health providers, others/friends), plus up to nine optional dental care-related items (Study 3, conducted April 2022 to February 2023, N = 502). Confirmatory Factor Analysis (CFA) assessed model fit, overall and by language (multiple group CFA). Final OHBSS scales include 37 items, plus seven optional items. Acceptable model fit for three-factor structures for each oral health behavior was found, providing evidence of the scales' construct validity. Cronbach's alphas and McDonald's omegas were tabulated; all were above 0.95, overall and by language, supporting scales' internal consistency.
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Rev Med Virol
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Department of Periodontics, University of Illinois Chicago, Chicago, Illinois, USA.
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Adjunct Professor, Department of Dental Medicine, Faculty of Medicine and Dentistry, University of Valencia, Valencia, Spain.
Statement Of Problem: Extraoral photogrammetry (PG) systems can record implant positions in 1 scan or in 2 scans that are then merged. However, the accuracy of implant positions recorded in 2 partial photogrammetry scans is unknown.
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Int Dent J
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Oral Health Programme, Department of Noncommunicable Diseases, Rehabilitation and Disability, World Health Organization, Geneva, Switzerland. Electronic address:
Int Dent J
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Department of Restorative Dentistry, College of Dentistry, Ajman University, Ajman, United Arab Emirates; Centre of Medical and Bio-allied Health Sciences Research, Ajman University, Ajman, United Arab Emirates.
Artificial intelligence (AI) holds immense promise in revolutionising dentistry, spanning, diagnostics, treatment planning and educational realms. This narrative review, in two parts, explores the fundamentals and the multifaceted potential of AI in dentistry. The current article explores the profound impact of AI in dentistry, encompassing diagnostic tools, treatment planning, and patient care.
View Article and Find Full Text PDFSemin Fetal Neonatal Med
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Iron deficiency is a highly prevalent nutritional deficiency and the most common cause of anemia worldwide. Pregnant individuals are particularly susceptible due to increased demands to support expanding maternal blood volume and fetal growth. Iron deficiency and iron deficiency anemia are associated with maternal and neonatal morbidity, including preterm birth, preeclampsia, postpartum hemorrhage, and low birth weight.
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