Do tempo or mode of change vary with abundance of items, an equivalent of population size?
Future research investigating the potential for time-varying, and even change in, SRH measures to predict other major health outcomes, such as functional disability and health care utilisation, may extend the application of SRH items for indicators of population health.
To test the validity of these findings among the broader New Zealand population we developed a novel survey instrument which incorporated items from previous surveys of population beliefs, as well as items specifically developed for the instrument.
We recruited participants from the general population and followed standard methodology for quality of life instrument development (identification of population, item selection, n = 24; item reduction, n = 81; item presentation, n = 12; pretesting of questionnaire and initial validation, n = 2576; construct validation n = 128; and test-retest reliability n = 20).
The items were area percentages of population affected by social aid, being unemployed, receiving disability pension, having no academic college or university education, and average taxable income in the areas.
Our data collection forms will include the following items: study design, description of population, interventions, outcomes, characteristics of candidate instruments (eg, generic or disease specific), characteristics of independent anchor measures, critiques/commentary on methods to estimate MID s), and credibility criteria for method(s) to estimate MIDs.
Elsewhere, the cutoff will vary based on the prevalence of each of the 20 items in the population of interest, the method of the scale's administration (whether as a self report or interviewer administered), and the extent of adaptation (e.g. translation into another language before administration) that goes into making the CES-D contextually relevant.
In England in 2011 an average of 18.7 prescription items were dispensed per head of population [ 5].
Under the independence assumption, we have the indicator function IAB ~ Bernoulli (p1· p2).. Let n, nA, nB and nAB be the total number of items in the population, the total number of items in A, the total number of items in B, and the total number of items in both A and B, respectively.
We describe the process of item development, the population of students who responded to these items, and our analytic approach in the sections below.
