Gender differences in adapting driving behavior to accommodate visual health limitations.

This study investigated whether men and women are equally likely to adapt their driving behaviors in response to visual limitations. Participants were 376 (222 women and 154 men) pre-surgical cataract patients from the Shiley Eye Center in La Jolla, California. All participants completed the National Eye Institute Visual Functioning Questionnaire, which assesses self-reported visual symptoms, functional limitations, and behaviors including driving during the day, at night, or in difficult conditions. Visual acuity was assessed using the log of the minimal angle of resolution (LogMAR) scale. There were no significant differences in LogMAR visual acuity between men and women who reported either that they stopped driving at night because of visual impairment or reported having no difficulty driving at night. Of participants who reported having difficulty driving at night, mean weighted LogMAR scores indicated significantly better visual acuity for women than men. There were no significant differences in LogMAR visual acuity between women and men in any of the difficult driving condition categories. Significantly more women than men reported that they stopped driving in difficult conditions because of eyesight, despite the lack of gender differences in visual acuity for this sample. We found no evidence that cataract disease had different effects on the visual acuity of older adult men and women. However, there was a significant difference between genders in self-reported driving behavior. It is possible that some women are more cautious or have less need to drive. However, failing to adapt driving behaviors to accommodate visual limitations may represent a potential behavioral public health risk for men.

Minimally important differences of the gout impact scale in a randomized controlled trial.

OBJECTIVE: The Gout Impact Scale (GIS) is a gout-specific quality of life instrument that assesses impact of gout during an attack and impact of overall gout. The GIS has five scales and each is scored from 0 to 100 (worse health). Our objective was to assess minimally important differences (MIDs) for the GIS administered in a randomized controlled trial (RCT) assessing rilonacept vs placebo for prevention of gout flares during initiation of allopurinol therapy. METHODS: Trial subjects (n = 83) included those with two or more gout flares (self-reported) in the past year. Of these, 73 had data for Weeks 8 vs 4 and formed the MID analysis group and were analysed irrespective of the treatment assignment. Subjects completed the GIS and seven patient-reported anchors. Subjects with a one-step change (e.g. from very poor to poor) were considered as the MID group for each anchor. The mean change in GIS scores and effect size (ES) was calculated for each anchor's MID group. The average of these created the overall summary MID statistics for each GIS. An ES of 0.2-0.5 was considered to represent MID estimates. Results. Trial subjects (n = 73) were males (96.0%), White (90.4%), with mean age of 50.5 years and serum uric acid of 9.0 mg/dl. The mean change score for the MID improvement group for scales ranged from -5.24 to -7.61 (0-100 scale). The ES for the MID improvement group for the four scales ranged from 0.22 to 0.38. CONCLUSION: The MID estimates for GIS scales are between 5 and 8 points (0-100 scale). This information can aid in interpreting the GIS results in future gout RCTs. Trial Registration. Clinicaltrials.gov, www.clinicaltrials.gov, NCT00610363.

Predictors of doctor-rated and patient-rated gout severity: gout impact scales improve assessment.

RATIONALE, AIMS AND OBJECTIVES: Our objective was to describe the factors associated with doctor-rated and patient-rated gout severity to explain how doctor assessment involving patient-reported outcomes can improve the clinical management of gout. METHODS: Patients completed a newly validated gout-specific health-related quality of life instrument, the Gout Impact Scale (GIS) and other questions regarding their gout. Both patients and their doctors gave an overall gout severity assessment. We conducted correlation analyses between each predictor of interest and the two different severity ratings (doctor-rated severity and patient-rated severity). Stepwise multiple regressions were performed to determine the best predictors for doctor-rated and patient-rated severity, respectively. RESULTS: Doctor-rated severity more closely correlated with objective clinical and laboratory findings, particularly the presence of tophi, which was not a leading factor in patient-rated severity assessments. Patient-rated severity more closely correlated with the domains of the GIS, which expressed the impact of gout on health-related quality of life. CONCLUSION: Doctors might have a better understanding of their patients' level of disease impact if they incorporate an instrument such as the GIS in their evaluation of gout severity and their decisions regarding aggressiveness of treatment. The increased use of patient-reported outcomes measures has the potential to improve quality of care and patient satisfaction, as well as reduce costs of health care utilization.