An exploratory analysis of variance and volatility in epileptic electroencephalograms

The electroencephalogram (EEG) is a physiological time series that measures electrical activity at different locations in the brain, and plays an important role in epilepsy research. Exploring the variance and/or volatility may yield insights for seizure prediction, seizure detection and seizure propagation/dynamics.^ Maximal Overlap Discrete Wavelet Transforms (MODWTs) and ARMA-GARCH models were used to determine variance and volatility characteristics of 66 channels for different states of an epileptic EEG – sleep, awake, sleep-to-awake and seizure. The wavelet variances, changes in wavelet variances and volatility half-lives for the four states were compared for possible differences between seizure and non-seizure channels.^ The half-lives of two of the three seizure channels were found to be shorter than all of the non-seizure channels, based on 95% CIs for the pre-seizure and awake signals. No discernible patterns were found the wavelet variances of the change points for the different signals. ^

A study of nurses' judgement of and participation in decision-making for nursing home placement for the elderly

This study investigated the effects of patient variables (physical and cognitive disability, significant others' preference and social support) on nurses' nursing home placement decision-making and explored nurses' participation in the decision-making process.^ The study was conducted in a hospital in Texas. A sample of registered nurses on units that refer patients for nursing home placement were asked to review a series of vignettes describing elderly patients that differed in terms of the study variables and indicate the extent to which they agreed with nursing home placement on a five-point Likert scale. The vignettes were judged to have good content validity by a group of five colleagues (expert consultants) and test-retest reliability based on the Pearson correlation coefficient was satisfactory (average of.75) across all vignettes.^ The study tested the following hypotheses: Nurses have more of a propensity to recommend placement when (1) patients have severe physical disabilities; (2) patients have severe cognitive disabilities; (3) it is the significant others' preference; and (4) patients have no social support nor alternative services. Other hypotheses were that (5) a nurse's characteristics and extent of participation will not have a significant effect on their placement decision; and (6) a patient's social support is the most important, single factor, and the combination of factors of severe physical and cognitive disability, significant others' preference, and no social support nor alternative services will be the most important set of predictors of a nurse's placement decision.^ Analysis of Variance (ANOVA) was used to analyze the relationships implied in the hypothesis. A series of one-way ANOVA (bivariate analyses) of the main effects supported hypotheses one-five.^ Overall, the n-way ANOVA (multivariate analyses) of the main effects confirmed that social support was the most important single factor controlling for other variables. The 4-way interaction model confirmed that the most predictive combination of patient characteristics were severe physical and cognitive disability, no social support and the significant others did not desire placement. These analyses provided an understanding of the importance of the influence of specific patient variables on nurses' recommendations regarding placement. ^

A Bayesian approach to estimating the intraclass correlation coefficient

A Bayesian approach to estimating the intraclass correlation coefficient was used for this research project. The background of the intraclass correlation coefficient, a summary of its standard estimators, and a review of basic Bayesian terminology and methodology were presented. The conditional posterior density of the intraclass correlation coefficient was then derived and estimation procedures related to this derivation were shown in detail. Three examples of applications of the conditional posterior density to specific data sets were also included. Two sets of simulation experiments were performed to compare the mean and mode of the conditional posterior density of the intraclass correlation coefficient to more traditional estimators. Non-Bayesian methods of estimation used were: the methods of analysis of variance and maximum likelihood for balanced data; and the methods of MIVQUE (Minimum Variance Quadratic Unbiased Estimation) and maximum likelihood for unbalanced data. The overall conclusion of this research project was that Bayesian estimates of the intraclass correlation coefficient can be appropriate, useful and practical alternatives to traditional methods of estimation. ^

THE MEASUREMENT OF HUMANISTIC AND DEHUMANISTIC BEHAVIORS IN HOSPITAL NURSING ENVIRONMENTS

The purpose of this investigation was to develop a reliable scale to measure the social environment of hospital nursing units according to the degree of humanistic and dehumanistic behaviors as perceived by nursing staff in hospitals. The study was based on a conceptual model proposed by Jan Howard, a sociologist. After reviewing the literature relevant to personalization of care, analyzing interviews with patients in various settings, and studying biological, psychological, and sociological frames of reference, Howard proposed the following necessary conditions for humanized health care. They were the dimensions of Irreplaceability, Holistic Selves, Freedom of Action, Status Equality, Shared Decision Making and Responsibility, Empathy, and Positive Affect.^ It was proposed that a scale composed of behaviors which reflected Howard's dimensions be developed within the framework of the social environment of nursing care units in hospitals. Nursing units were chosen because hospitals are traditionally organized around nursing care units and because patients spend the majority of their time in hospitals interacting with various levels of nursing personnel.^ Approximately 180 behaviors describing both patient and nursing staff behaviors which occur on nursing units were developed. Behaviors which were believed to be humanistic as well as dehumanistic were included. The items were classified under the dimensions of Howard's model by a purposively selected sample of 42 nurses representing a broad range of education, experience, and clinical areas. Those items with a high degree of agreement, at least 50%, were placed in the questionnaire. The questionnaire consisted of 169 items including six items from the Marlowe Crowne Social Desirability Scale (Short Form).^ The questionnaire, the Social Environment Scale, was distributed to the entire 7 to 3 shift nursing staff (603) of four hospitals including a public county specialty hospital, a public county general and acute hospital, a large university affiliated hospital with all services, and a small general community hospital. Staff were asked to report on a Likert type scale how often the listed behaviors occurred on their units. Three hundred and sixteen respondents (52% of the population) participated in the study.^ An item analysis was done in which each item was examined in relationship to its correlation to its own dimension total and to the totals of the other dimensions. As a result of this analysis, three dimensions, Positive Affect, Irreplaceability, and Freedom of Action were deleted from the scale. The final scale consisted of 70 items with 26 in Shared Decision Making and Responsibility, 25 in Holistic Selves, 12 in Status Equality, and seven in Empathy. The alpha coefficient was over .800 for all scales except Empathy which was .597.^ An analysis of variance by hospital was performed on the means of each dimension of the scale. There was a statistically significant difference between hospitals with a trend for the public hospitals to score lower on the scale than the university or community hospitals. That the scale scores should be lower in crowded, understaffed public hospitals was not unexpected and reflected that the scale had some discriminating ability. These differences were still observed after adjusting for the effect of Social Desirability.^ In summary, there is preliminary evidence based on this exploratory investigation that a reliable scale based on at least four dimensions from Howard's model could be developed to measure the concept of humanistic health care in hospital settings. ^

THE APPLICATION OF PATH ANALYSIS TO ASSESSMENT OF IRON NUTRITIONAL STATUS IN MAN

Path analysis has been applied to components of the iron metabolic system with the intent of suggesting an integrated procedure for better evaluating iron nutritional status at the community level. The primary variables of interest in this study were (1) iron stores, (2) total iron-binding capacity, (3) serum ferritin, (4) serum iron, (5) transferrin saturation, and (6) hemoglobin concentration. Correlation coefficients for relationships among these variables were obtained from published literature and postulated in a series of models using measures of those variables that are feasible to include in a community nutritional survey. Models were built upon known information about the metabolism of iron and were limited by what had been reported in the literature in terms of correlation coefficients or quantitative relationships. Data were pooled from various studies and correlations of the same bivariate relationships were averaged after z- transformations. Correlation matrices were then constructed by transforming the average values back into correlation coefficients. The results of path analysis in this study indicate that hemoglobin is not a good indicator of early iron deficiency. It does not account for variance in iron stores. On the other hand, 91% of the variance in iron stores is explained by serum ferritin and total iron-binding capacity. In addition, the magnitude of the path coefficient (.78) of the serum ferritin-iron stores relationship signifies that serum ferritin is the most important predictor of iron stores in the proposed model. Finally, drawing upon known relations among variables and the amount of variance explained in path models, it is suggested that the following blood measures should be made in assessing community iron deficiency: (1) serum ferritin, (2) total iron-binding capacity, (3) serum iron, (4) transferrin saturation, and (5) hemoglobin concentration. These measures (with acceptable ranges and cut-off points) could make possible the complete evaluation of all three stages of iron deficiency in those persons surveyed at the community level. ^