Predicting dentists' willingness to treat HIV-infected patients

AIDS Care. 1996 Oct;8(5):581-8. doi: 10.1080/09540129650125533.

Abstract

Access to oral health care is extremely important for those infected with HIV, because oral findings can lead to early detection and improved staging and management of HIV infection. In addition, oral lesions associated with HIV infection are often debilitating, but can be managed effectively with proper oral health care. There is ample evidence that dentists have, at times, resisted accepting HIV positive patients (PHIV+). The intent of the research project described below was to develop and test a model predicting dentists' willingness to treat PHIV+. Data were collected from a sample of dentists practising in New York City. The dependent variable was a scale constructed of items measuring willingness to treat PHIV+ under varying conditions. Independent variables were entered into a multiple linear regression equation in iterative attempts to arrive at a model predicting dentists' willingness to treat PHIV+, which was both parsimonious and had explanatory power. The final model included five independent variables measuring: (1) perceived safety; (2) willingness to treat homosexuals; (3) perceived ethical obligation to treat PHIV +; (4) past experience; and (5) perceived norms of colleagues. Perceived safety and perceived norms of colleagues had by far the most predictive power of all independent variables. R2 for the model = 0.58.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Attitude of Health Personnel
  • Dental Care for Chronically Ill / psychology
  • Dental Care for Chronically Ill / statistics & numerical data*
  • Dentists / psychology*
  • Dentists / standards
  • Dentists / statistics & numerical data
  • Ethics, Dental
  • HIV Infections / psychology*
  • Health Services Accessibility / statistics & numerical data*
  • Homosexuality
  • Humans
  • Linear Models
  • Models, Psychological*
  • Multivariate Analysis
  • New York City
  • Refusal to Treat / statistics & numerical data*
  • Safety
  • Sampling Studies
  • Social Perception