PURPOSE: This study attempts to provide insight on how the treatment preference for a mandible fracture and treatment received and its consequences are related to the patient's risk tolerance, as measured by the Standard Gamble (SG). PATIENTS AND METHODS: Data from a prospective cohort study of 203 subjects receiving treatment at the former King/Drew Medical Center in Los Angeles, CA, for either a mandible fracture (n = 98) or third molar removal (n = 105) were examined. Subjects were interviewed at 4 time points: on admission to the medical center and at 3 monthly follow-up visits. Risk tolerance for hypothetical treatment scenarios is measured by use of the SG, a health-value utility measure assessing the tradeoff between good outcomes and serious complications associated with treatment. Separate regression analyses with subsets of predictors (sociodemographic, psychosocial health, and clinical characteristics) were conducted and then synthesized by use of the significant predictors in separate analyses. RESULTS: For fracture subjects, there was a noticeable rise in the SG reports from admission to the 1-month follow-up. Their greater risk tolerance was associated with being older, receiving surgery, having a lower post-traumatic stress disorder score, and having a swollen jaw or face. For third molar subjects, SG did not change substantively over the course of the study. Predictors of greater risk tolerance for third molar subjects included the jaw or face being swollen and having to use less pain medication. CONCLUSIONS: Findings from this study show a preference for less invasive treatment, with the majority of both groups preferring wiring, and support the theory that treatment choices differ between subjects with different health states. Factors associated with risk tolerance include the patient's age, treatment received, psychosocial health state, experience with previous treatment, and value for oral health quality of life.
PURPOSE: This study attempts to provide insight on how the treatment preference for a mandible fracture and treatment received and its consequences are related to the patient's risk tolerance, as measured by the Standard Gamble (SG). PATIENTS AND METHODS: Data from a prospective cohort study of 203 subjects receiving treatment at the former King/Drew Medical Center in Los Angeles, CA, for either a mandible fracture (n = 98) or third molar removal (n = 105) were examined. Subjects were interviewed at 4 time points: on admission to the medical center and at 3 monthly follow-up visits. Risk tolerance for hypothetical treatment scenarios is measured by use of the SG, a health-value utility measure assessing the tradeoff between good outcomes and serious complications associated with treatment. Separate regression analyses with subsets of predictors (sociodemographic, psychosocial health, and clinical characteristics) were conducted and then synthesized by use of the significant predictors in separate analyses. RESULTS: For fracture subjects, there was a noticeable rise in the SG reports from admission to the 1-month follow-up. Their greater risk tolerance was associated with being older, receiving surgery, having a lower post-traumatic stress disorder score, and having a swollen jaw or face. For third molar subjects, SG did not change substantively over the course of the study. Predictors of greater risk tolerance for third molar subjects included the jaw or face being swollen and having to use less pain medication. CONCLUSIONS: Findings from this study show a preference for less invasive treatment, with the majority of both groups preferring wiring, and support the theory that treatment choices differ between subjects with different health states. Factors associated with risk tolerance include the patient's age, treatment received, psychosocial health state, experience with previous treatment, and value for oral health quality of life.
Authors: Michael S Yi; Maria T Britto; Robert W Wilmott; Uma R Kotagal; Mark H Eckman; Dennis W Nielson; Vikki L Kociela; Joel Tsevat Journal: J Pediatr Date: 2003-02 Impact factor: 4.406
Authors: Todd B Brown; Stacey S Cofield; Anand Iyer; Robin Lai; Hugh Milteer; Brannon Queen; Mark H Schwab; Michael Menchine; David L Schriger Journal: J Emerg Med Date: 2009-05-05 Impact factor: 1.484