PubMed · 10258236
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M Magnet. 1983-02-21. Here come McDentists.. https://pubmed.ncbi.nlm.nih.gov/10258236/
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PURPOSE: This study was undertaken to determine what smoking cessation services dental professionals in Ontario's Wellington-Dufferin-Guelph Health Unit (WDGHU) provide before disseminating a smoking cessation information package. METHODS: Data were collected with 540 self-administered questionnaires mailed to 60 local dental offices. Replies were requested from all dentists, dental hygienists, dental assistants and other dental staff working in each dental office. RESULTS: Completed responses were obtained from 126 dental personnel in 28 (47%) of the 60 dental offices surveyed. The proportion of dental offices, dentists and hygienists providing cessation services to most patients was as follows: asking patients about tobacco-use status, 46%, 31% and 32%; advising tobacco users to quit, 46%, 32% and 29%; assessing tobacco users' interest in quitting, 46%, 25% and 19%; and assisting interested patients to quit, 25%, 6% and 13%, respectively. CONCLUSION: This survey indicates that most dental professionals in the WDGHU do not provide proven smoking cessation services. An opportunity exists to increase the proportion of dental professionals providing proven smoking cessation interventions as part of routine patient services.
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Observational studies continue to be recognized as viable alternatives to randomized trials when making treatment group comparisons, in spite of drawbacks due mainly to selection bias. Sample selection models have been proposed in the economics literature, and more recently in the medical literature, as a method to adjust for selection bias due to observed and unobserved confounders in observational studies. Application of these models has been limited to cross-sectional observational data and to outcomes that are continuous in nature. In this paper we extend application of these models to include longitudinal studies and binary outcomes. We apply a two-stage probit model using GEE to account for correlated longitudinal binary chewing difficulty outcomes. Chewing difficulty was measured every six months during a 24-month period between two groups of subjects: those either receiving or not receiving dental care. Dental care use was measured at six-month intervals as well. Results from our proposed model are compared to results using a standard GEE model that ignores the potential selection bias introduced by unobserved confounders. In this application, accounting for selection bias made a major difference in the substantive conclusions about the outcomes of interest. This is due in part to an adverse selection phenomenon in which those most in need of treatment (and consequently most likely to benefit from it) are actually the ones least likely to seek treatment. Our application of sample selection models to binary longitudinal observational outcome data should serve as impetus for increased utilization of this promising set of models to other health outcomes studies.