The study I will be conducting is based on uncertainty; the uncertainty individuals have on whether they should visit the doctor even when they know they should. There have been previous studies on this similar topic. For instance, there was a study conducted on a longitudinal Web- based survey that assessed participants’ level of relational uncertainty, degree of intimacy, and the openness of communication about relational uncertainty. In selecting a time frame of 6 weeks, they were informed by previous longitudinal and retrospective studies of relationship development (Theiss & Solomon 2008). Uncertainty and its management hold a prominent place in the study of interpersonal communication. In particular, uncertainty, information seeking, and uncertainty reduction are highlighted as core mechanisms in the development of interpersonal relationships. For instance, this study con intersect with the study I will be conducting because in my study there is an uncertainty on the individuals themselves on whether they should go to the doctor or not, and an uncertainty on their doctors. There was another similar study done and it had two purposes: to determine the factors that affect the doctor's knowledge of the patient's problems and to find out if such knowledge has a bearing on the patient's recovery and satisfaction with care (Stewart, McWhinney & Buck, 1979). They studied 299 chronically ill patients, they examined the doctor/patient relationship by asking two questions: first, what factors affect the quality of the relationship and secondly, does the doctor/patient relationship affect outcome for the patient? Indicators of the doctor’s awareness of the patient’s problems measured the doctor/patient relationship (Stewart, McWhinney & Buck, 1979). Finally, the last study I looked at was based on the number of visits to the doctor. They figured that the frequency of doctor consultations has direct consequences for health care budgets, yet little statistical analysis of the determinants of doctor visits has been reported. They considered the distribution of the number of visits to the doctor and, in particular, they model its dependence on a number of demographic factors. Examination of the Australian 1995 National Health Survey data reveals that generalized linear Poisson or negative binomial models are inadequate for modeling the mean as a function of covariates, because of excessive zero counts, and a mean-variance relationship that varies enormously over covariate values (Berzel, Heller, & Zucchini 2006).
My hypothesis for this research is: men are more likely than women to avoid doctor visits even when they suspect they should. My alternative hypothesis is: women are more likely than men to avoid doctor visits even when they suspect they should. My research question is what age group between males and females are more likely to avoid doctor visits even when they suspect they should?
The variables I choose out of the hints...