Practice of Do Not Resuscitate, Pros and Cons Essay

Practice of Do Not Resuscitate, Pros and Cons - Essay Example There are some cases where a medical decision to cease treatment accords with moral principles but may nevertheless invite legal censure as in the case of withholding unduly burdensome life-prolonging treatment from severely disabled newborns or severely brain-injured adults. Longitudinal Research 'describes what can be defined as the minimum common denominator of a family of those methods which tell us about change at the individual micro level" (Ruspini 3). The advantage of longitudinal data is that it suggests important cross-cultural differences in the presence of flat affect while methodological questions remain as to precisely how flat affect was assessed. The cross-cultural variation in emotional experience and expression generally and in "Do Not Resuscitate" patients specifically render the culturally valid assessment of flat affect a complicated undertaking. A medical decision to continue treating a patient may accord with a reasonable body of medical opinion, be legal (as in cases where patients have been deemed rationally incompetent under a mental health act), yet be quite unethical if the patient has expressly stated a wish not to be treated, and if this expressed wish, contrary to popular medical opinion, is not 'irrational' (Baker and Stro sberg 22). Death is of particular cultural and sociolinguistic concern insofar as the language and ethnicity of the individual conducting the psychiatric assessment may differ from those of the patient. Certainly a desire to die can be expected to vary substantially in relation to culturally constituted capacities such as self, agency, motivation, and the meaning of purposeful action. "longitudinal research is often undertaken precisely in order to identify social change and its correlates" (Bryman 71). In addition to the usual methods of cross-tabulations, comparisons of means between groups, correlation and regression analysis, there are some special methods that are particularly useful for the analysis of longitudinal data. The following are special methods which can be used to analyze data from our longitudinal studies: (a) age, period, and cohort analysis; (b) change graphs; (c) residual change analysis; and (d) longevity difference (Devine and Heath 63). A cross-sequential design is necessary to separate out the effects of age, period, and cohort. The essential steps are: first, the data must be arranged so that the time interval between times of measurement must equal the number of years in each birth cohort; second, each of the three types of differences must be measured: longitudinal (difference between earlier and later measurements on the same cohort), cross-sectional difference between cohorts at the same point in time), and time-lag (difference between earlier measurem ent on an older cohort and later measurement on a younger cohort); third, inference about the effects contained in these differences are based on the fact that each difference is composed of two effects: longitudinal difference equals age plus period; cross-sectional difference equals age plus cohort; and time-lag difference equals period minus cohort (Bryman 73). If there are no significant differences it is usually