Investigating the utility of clinical assessments to predict success with presbyopic contact lens correction

PURPOSE: To determine the utility of a range of clinical and non-clinical indicators to aid the initial selection of the optimum presbyopic contact lens. In addition, to assess whether lens preference was influenced by the visual performance compared to the other designs trialled (intra-subject) or compared to participants who preferred other designs (inter-subject). METHODS: A double-masked randomised crossover trial of Air Optix Aqua multifocal, PureVision 2 for Presbyopia, Acuvue OASYS for Presbyopia, Biofinity multifocal and monovision was conducted on 35 presbyopes (54.3±6.2years). Participant lifestyle, personality, pupil characteristics and aberrometry were assessed prior to lens fitting. After 4 weeks of wear, high and low contrast visual acuity (VA) under photopic and mesopic conditions, reading speed, Near Activity Visual Questionnaire (NAVQ) rating, subjective quality-of-vision scoring, defocus curves, stereopsis, halometry, aberrometry and ocular physiology were quantified. RESULTS: After trialling all the lenses, preference was mixed (n=12 Biofinity, n=10 monovision, n=7 Purevision, n=4 Air Optix Aqua, n=2 Oasys). Lens preference was not dependent on personality (F=1.182, p=0.323) or the hours spent working at near (p=0.535) or intermediate (p=0.759) distances. No intersubject or strong intrasubject relationships emerged between lens preference and reading speed, NAVQ rating, halo size, aberrometry or ocular physiology (p>0.05). CONCLUSIONS: Participant lifestyle and personality, ocular optics, contact lens visual performance and ocular physiology provided poor indicators of the preferred lens type after 4 weeks of wear. This is confounded by the wide range of task visual demands of presbyopes and the limited optical differences between current multifocal contact lens designs.

Analyzing evacuation decisions using multi-attribute utility theory (MAUT)

Emergency managers are faced with critical evacuation decisions. These decisions must balance conflicting objectives as well as high levels of uncertainty. Multi-Attribute Utility Theory (MAUT) provides a framework through which objective trade-offs can be analyzed to make optimal evacuation decisions. This paper is the result of data gathered during the European Commission Project, Evacuation Responsiveness by Government Organizations (ERGO) and outlines a preliminary decision model for the evacuation decision. The illustrative model identifies levels of risk at which point evacuation actions should be taken by emergency managers in a storm surge scenario with forecasts at 12 and 9 hour intervals. The results illustrate how differences in forecast precision affect the optimal evacuation decision. Additional uses for this decision model are also discussed along with improvements to the model through future ERGO data-gathering.