Network analysis in evaluation: some words of caution

Network analysis, a methodology derived from general systems' theory, can be utilized as a community mental health administrative-evaluation procedure. Evaluation parameters derived from analysis of patient data as they “flow” through a network of agency services, provide measures of systemic functioning. These parameters include “longest paths” and various ratio relationships as evaluation measures of service delivery. The limitations of network analysis are examined by means of conceptual analyses, and phenomena that emerged from research experience. The necessity for both quantitative and qualitative data to ensure a meaningful evaluation of mental health services is explained. Conclusions about the value of the network analysis approach are considered.     

The hospitals and population growth: The voluntary general hospitals, mortality and local populations in the English provinces in the eighteenth and nineteenth centuries part 2

Summary In the second part of this article the number and nature of hospital cases treated in the light of physical, medical and surgical limitations are examined. Each hospital's records of treatment are summarised and discussed. Whether or not the hospitals were able to tackle successfully some of the major diseases and causes of death and thereby exert a positive influence in reducing mortality rates is then considered. Two main conclusions are drawn. First, that the hospitals had a positive role to play within their patient catchment areas, but that this was insufficient to affect national mortality trends decisively. Secondly, the hospitals' influence was of greater importance before the mid-nineteenth century. Despite advances in medical knowledge and techniques, population pressure, overcrowding and the growing incidence of serious cases in hospitals coupled with outbreaks of 'hospital diseases' meant that the results of hospital treatment may have become less impressive. But even then, mortality levels in the hospitals were low and the hospitals did not merit their reputation of being 'gateways to death' or as institutions 'which positively did harm'.     

Seasonal patterns of fertility measures: theory and data

The distribution of births by month exhibits a seasonal pattern in most populations. The monthly marital fertility rate for an area of Bangladesh provides a good example of the seasonal periodicity. Seasonal patterns of measures of reproduction in a population of married women are considered. Equations are developed that predict the seasonal patterns of these alternative measures under the assumption that the fertility rate (R) follows a trigonometric curve. This is followed by an empirical analysis of the measures in a Bangladesh population that has a pronounced seasonal fertility. The investigation is intended both to validate the theoretical framework developed in the 1st part of the paper as well as to determine whether seasonal variation in actual populations is sufficiently large to affect the alternative measures significantly. 4 measures are considered: pregnancy prevalence (PP)--the proportion of married women who are pregnant at the survey date; mean open birth interval (MOI)--the time from the last live birth to the date of the survey for parous women and from the time of marriage to the date of the survey for nulliparous women; mean closed interval-birth (MCIB)--the mean interval between the last 2 live births for married women who have a birth in the period immediately preceding the survey date; and mean closed interval-woman (MCIW)--the mean interval between the last 2 live births for women who have had at least 2 children by the time of the survey. It is assumed that the seasonal pattern of the fertility rate of a population follows a cosine curve and that there is no trend in annual fertility from year to year. The lag and relative variability of the other measures are considered in comparison with the fertility rate curve. The predictions from this theoretical effort, when compared with observed patterns and trigonometric regression results for each measure in data from Bangladesh, are shown to be quite accurate. The figure and regression results show that R, PP, and MOI have definite seasonal periodicity, but MCIB and MCIW do not display any seasonal patterns. If there is a secular trend in fertility in addition to seasonality, these relationships between the seasonal patterns of the measures may no longer hold. There is a disadvantage to using closed interval measures, for they are unable to detect effects of limiting of childbearing in a population since they are based only on information from women who have births.     

Regional patterns of nuptiality in Europe, 1870-1960

Abstract This paper is a study of changes in nuptiality by province in Europe between 1870 and 1960: nuptiality is measured by I(m) a summary measure of the proportions married among women of childbearing age. In each of the approximately 500 provinces of Europe the level of nuptiality increased between 1870 and 1960. In addition, in most countries the differences among provinces diminished over the period, so that the countries were more homogeneous with respect to provincial nuptiality in 1960 than they had been in 1870. Despite this tendency to convergence, traditional regional differences, linked to a common regional history, were often maintained, though within a narrower range.     

Regression of area mortality rates on explanatory variables: what weighting is appropriate?

"One can often gain insight into the aetiology of a disease by relating mortality rates in different areas to explanatory variables. Multiple regression techniques are usually employed, but unweighted least squares may be inappropriate if the areas vary in population size. Also, a fully weighted regression, with weights inversely proportional to binomial sampling variances, is usually too extreme. This paper proposes an intermediate solution via maximum likelihood which takes account of three sources of variation in death rates: sampling error, explanatory variables and unexplained differences between areas. The method is also adapted for logit (death rates), standardized mortality ratios (SMRs) and log (SMRs). Two [United Kingdom] examples are presented."     

Family limitation among the Old Order Amish

Summary This paper shows that the Indiana Amish, a high-fertility Anabaptist population, regulate their marital fertility according to their family finances. We linked demographic data from the Indiana Amish Directory with personal property tax records at 5, 15 and 25 years after marriage and found fertility differences by occupation and wealth. Correlations between family size and wealth at the beginning, middle and end of childbearing years were positive. Wealthier women exhibited higher marital fertility, had longer first birth intervals, were older at the birth of their last child, and had larger families than poorer women. Over the past 30 years, marital fertility has remained constant among older women; but birth rates among younger women have been rising rapidly.     

More people - more energy: it seems obvious enough,but Carter plan ignores population

In President Carter's National Energy Plan, there are variable factors, including the coal production rate, standards for home insulation and auto mileage, various taxes, but not the population growth rate. The latter factor is considered to be beyond the influence of public policy; it is a constant. This seems irrational to zero population growth proponents, for there are alternatives to continued U.S. population growth, and these alternatives are more readily attainable than some of the elements in Carter's plan. With some national initiatives in population planning, energy use would be considerably less. Thus, the question remains - Why would Carter not deal with the population factor? 1 reason for this is the fact that population planning is a long-term approach; the results are indirect and not reflected immediately in energy comsumption. Yet, a start must be made in the short-term if there are ever to be long-term benefits. Russell Peterson has suggested that Carter could be ignoring the population factor because of "political sensitivity." Carter's people have ignored the population issue, and press coverage following Carter's energy pronouncements has excluded the population factor. In a situation such as this there seems little hope for increased public awareness of the population factor in energy or other public concerns.