2 resultados para Autonomy support

em DigitalCommons@The Texas Medical Center


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Public preferences for policy are formed in a little-understood process that is not adequately described by traditional economic theory of choice. In this paper I suggest that U.S. aggregate support for health reform can be modeled as tradeoffs among a small number of behavioral values and the stage of policy development. The theory underlying the model is based on Samuelson, et al.'s (1986) work and Wilke's (1991) elaboration of it as the Greed/Efficiency/Fairness (GEF) hypothesis of motivation in the management of resource dilemmas, and behavioral economics informed by Kahneman and Thaler's prospect theory. ^ The model developed in this paper employs ordered probit econometric techniques applied to data derived from U.S. polls taken from 1990 to mid-2003 that measured support for health reform proposals. Outcome data are four-tiered Likert counts; independent variables are dummies representing the presence or absence of operationalizations of each behavioral variable, along with an integer representing policy process stage. Marginal effects of each independent variable predict how support levels change on triggering that variable. Model estimation results indicate a vanishingly small likelihood that all coefficients are zero and all variables have signs expected from model theory. ^ Three hypotheses were tested: support will drain from health reform policy as it becomes increasingly well-articulated and approaches enactment; reforms appealing to fairness through universal health coverage will enjoy a higher degree of support than those targeted more narrowly; health reforms calling for government operation of the health finance system will achieve lower support than those that do not. Model results support the first and last hypotheses. Contrary to expectations, universal health care proposals did not provide incremental support beyond those targeted to “deserving” populations—children, elderly, working families. In addition, loss of autonomy (e.g. restrictions on choice of care giver) is found to be the “third rail” of health reform with significantly-reduced support. When applied to a hypothetical health reform in which an employer-mandated Medical Savings Account policy is the centerpiece, the model predicts support that may be insufficient to enactment. These results indicate that the method developed in the paper may prove valuable to health policy designers. ^

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This study addressed two purposes: (1) to determine the effect of person-environment fit on the psychological well-being of psychiatric aides and (2) to determine what role the coping resources of social support and control have on the above relationship. Two hundred and ten psychiatric aides working in a state hospital in Texas responded to a questionnaire pertaining to these issues.^ Person-environment fit, as a measure of occupational stress, was assessed through a modified version of the Work Environment Scale (WES). The WES subscales used in this study were: involvement, autonomy, job pressure, job clarity, and physical comfort. Psychological well-being was measured with the General Well-Being Schedule which was developed by the National Center for Health Statistics. Co-worker and supervisor support were measured through the WES and finally, control was assessed through Rotter's Locus of Control Scale.^ The results of this study were as follows: (1) all person-environment (p-e) dimensions appeared to have linear relationships with psychological well-being; (2) the p-e fit - well-being relationship did not appear to be confounded by demographic factors; (3) all p-e fit dimensions were significantly related to well-being except for autonomy; (4) p-e fit was more strongly related to well-being than the environmental measure alone; (5) supervisor support and non-work related support were found to have additive effects on the relationship between p-e fit and well-being, however no interaction or buffering effects were observed; (6) locus of control was found to have additive effects in the prediction of well-being and showed interactive effects with work pressure, involvement and physical comfort; and (7) the testing of the overall study model which included many of the components mentioned above yielded an R('2) = .27.^ Implications of these findings are discussed, future research suggested and applications proposed. ^