I. INTRODUCTION

The Healthy New Jersey 2010 State Health Issues Opinion Survey was developed by The Eagleton Institute's Center for Public Interest Polling in consultation with representatives from NJDHSS. The main objective of the survey is to provide information on the public's top health concerns.

II. QUESTIONNAIRE DEVELOPMENT

Eagleton conducted a similar survey in 1991 for NJDHSS and that instrument was used as the basis for the current survey. Representatives of NJDHSS also proposed additional questions to be addressed in the study. The questionnaire was then drafted and refined by the Eagleton research staff. The draft questionnaire was pretested with a random group of New Jersey residents and modifications were made to the survey instrument in order to increase the understandability and accuracy of the questions asked.

Besides the series of questions on identifying state health concerns and the role of different entities in addressing those concerns, some basic demographic information was obtained from all study participants in order to provide more detailed analysis of the data.

The final version of the questionnaire was programmed into a CATI (Computer Assisted Telephone Interview) system. The CATI system enables the interviewer to accurately skip over certain questions which may be irrelevant to a particular study participant, while retaining the flow and integrity of the interview process.

III. SAMPLE DESIGN

A random proportional probability sample was used to select the 804 New Jersey residents 18 years of age and older who were contacted to participate in this study. The sample was designed to make sure that each of the state's 21 counties was proportionately represented and that an equal number of men and women were interviewed. The three-digit exchange was used to match telephone numbers and geographic areas. The remaining four digits were randomly selected. This procedure insures that those with unlisted or new telephone numbers are included in the sample. Each working phone number was called a minimum of three times, at different times of the week, in an effort to reach people who were infrequently at home.

IV. WEIGHTING

While those interviewed in a survey ideally will have the same characteristics as the population they represent, samples frequently may under-represent groups that are more difficult to interview, such as the elderly or those with less than a high school education. To correct this imbalance, a statistical technique known as "weighting" is used. The weighting procedure compares New Jersey population figures for age and education based on census data with those of the sample. When there is significant difference between these two figures, the sample is weighted so it more accurately reflects the population of the state. For example, if census figures show 39 percent of New Jerseyans 18 years and older to have a high school education, and the sample consists of 32 percent with a high school education, each respondent in this category would be counted as 1.21 persons to adjust for this difference.

V. SAMPLING ERROR

The percentages obtained in a sample survey are estimates of what the distribution of responses would be if the entire population had been surveyed. "Sampling error" is a statistical term which describes the probable difference between interviewing everyone in a given population and a sample drawn from that population. For example, the sampling error associated with a sample of 804 persons is +/-3.5 percent at a 95 percent confidence interval. Thus, if 47 percent of those in a sample of 804 are found to agree with a particular statement, the percentage of agreement within the population from which the sample was drawn would be between 43.5 and 50.5 percent (47 +/-3.5%) 95 times out of 100.

Sampling error increases as the sample size is reduced. For, example, if statements are made based on a sub-group of 400 persons, the sampling error is +/-5 percent. This fact must be kept in mind when comparing the responses of different groups within a sample (e.g. men compared with women). Figure 1 in this appendix shows the relationship between sample (or group) size and sampling error.

Readers should note that sampling error does not take into account other possible sources of error inherent in any study of public opinion.

VI. DATA COLLECTION

The study involved CATI interviews with a random probability sample of 804 New Jersey residents 18 years of age and older. The CATI interviews were conducted by telephone between May 4 and May 11, 1999 by experienced professional interviewers who were trained and monitored by the Eagleton research staff.

VII. DATA PROCESSING AND ANALYSIS

The CATI system generates a computer readable data file which reduces the amount of error inherent in the coding and entry of data recorded on paper questionnaires. An SPSS (Statistical Package for the Social Sciences) computer file was developed to process the CATI information. The SPSS system enabled the Eagleton research staff to integrate the survey data so that it could be presented in aggregate form.

VIII. REGIONAL CLASSIFICATIONS

Region is classified according to county boundaries:

North -- Bergen, Essex, Hudson, Morris, Passaic, Sussex, Union, and Warren

Central -- Hunterdon, Mercer, Middlesex, Monmouth, and Somerset

South -- Atlantic, Burlington, Camden, Cape May, Cumberland, Gloucester, Ocean, and Salem

Type of Community: All municipalities in the state have been classified into one of five groups or "types," based on location, settlement patterns, population density and growth.

Major Urban Centers -- New Jersey's largest cities: Newark, Jersey City, Paterson, Elizabeth, Trenton, and Camden.

Urban Centers & Surrounding Areas -- This category is generally based on the cities of the state over 25,000, but also includes densely populated suburbs of urban areas which also have similar socio-economic characteristics. For example, all of Hudson county (outside of Jersey City), and much of Union, eastern Essex and southern Bergen counties are included in this category.

Older Towns & Suburbs -- This category includes two types of municipalities: urban suburbs which are not as densely populated and/or have significantly higher socio-economic characteristics than the nearby urban center; and densely populated towns which are not near urban centers, and have not experienced major development in the past decade.

New Suburbs -- These are primarily suburban areas which are "outside central city" proportions of the Census Bureau's Standard Metropolitan Statistical Areas and have continued to experience growth in the past 20 years. These municipalities are usually within a short distance of urban centers.

Rural -- This includes municipalities not in any of the categories above. These are small communities with scattered populations and somewhat denser small towns which are surrounded by rural areas.

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