Parameter and model uncertainty in a life-table model for fine particles (PM2.5): a statistical modeling study

<p>Abstract</p> <p>Background</p> <p>The estimation of health impacts involves often uncertain input variables and assumptions which have to be incorporated into the model structure. These uncertainties may have significant effects on the results obtained with model, and, thus, on decision making. Fine particles (PM_2.5) are believed to cause major health impacts, and, consequently, uncertainties in their health impact assessment have clear relevance to policy-making. We studied the effects of various uncertain input variables by building a life-table model for fine particles.</p> <p>Methods</p> <p>Life-expectancy of the Helsinki metropolitan area population and the change in life-expectancy due to fine particle exposures were predicted using a life-table model. A number of parameter and model uncertainties were estimated. Sensitivity analysis for input variables was performed by calculating rank-order correlations between input and output variables. The studied model uncertainties were (i) plausibility of mortality outcomes and (ii) lag, and parameter uncertainties (iii) exposure-response coefficients for different mortality outcomes, and (iv) exposure estimates for different age groups. The monetary value of the years-of-life-lost and the relative importance of the uncertainties related to monetary valuation were predicted to compare the relative importance of the monetary valuation on the health effect uncertainties.</p> <p>Results</p> <p>The magnitude of the health effects costs depended mostly on discount rate, exposure-response coefficient, and plausibility of the cardiopulmonary mortality. Other mortality outcomes (lung cancer, other non-accidental and infant mortality) and lag had only minor impact on the output. The results highlight the importance of the uncertainties associated with cardiopulmonary mortality in the fine particle impact assessment when compared with other uncertainties.</p> <p>Conclusion</p> <p>When estimating life-expectancy, the estimates used for cardiopulmonary exposure-response coefficient, discount rate, and plausibility require careful assessment, while complicated lag estimates can be omitted without this having any major effect on the results.</p

Patient empowerment in long-term conditions: development and preliminary testing of a new measure

BACKGROUND: Patient empowerment is viewed by policy makers and health care practitioners as a mechanism to help patients with long-term conditions better manage their health and achieve better outcomes. However, assessing the role of empowerment is dependent on effective measures of empowerment. Although many measures of empowerment exist, no measure has been developed specifically for patients with long-term conditions in the primary care setting. This study presents preliminary data on the development and validation of such a measure. METHODS: We conducted two empirical studies. Study one was an interview study to understand empowerment from the perspective of patients living with long-term conditions. Qualitative analysis identified dimensions of empowerment, and the qualitative data were used to generate items relating to these dimensions. Study two was a cross-sectional postal study involving patients with different types of long-term conditions recruited from general practices. The survey was conducted to test and validate our new measure of empowerment. Factor analysis and regression were performed to test scale structure, internal consistency and construct validity. RESULTS: Sixteen predominately elderly patients with different types of long-term conditions described empowerment in terms of 5 dimensions (identity, knowledge and understanding, personal control, personal decision-making, and enabling other patients). One hundred and ninety seven survey responses were received from mainly older white females, with relatively low levels of formal education, with the majority retired from paid work. Almost half of the sample reported cardiovascular, joint or diabetes long-term conditions. Factor analysis identified a three factor solution (positive attitude and sense of control, knowledge and confidence in decision making and enabling others), although the structure lacked clarity. A total empowerment score across all items showed acceptable levels of internal consistency and relationships with other measures were generally supportive of its construct validity. CONCLUSION: Initial analyses suggest that the new empowerment measure meets basic psychometric criteria. Reasons concerning the failure to confirm the hypothesized factor structure are discussed alongside further developments of the scale