Health Services Research Methods 3rd Edition by Leiyu Shi - Test Bank

Health Services Research Methods 3rd Edition by Leiyu Shi - Test Bank   Instant Download - Complete Test Bank With Answers     Sample Questions Are Posted Below   Chapter 5 Answer Key   What is the difference between secondary analysis and primary research? Secondary analysis refers to analysis of data or information collected by …

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Health Services Research Methods 3rd Edition by Leiyu Shi – Test Bank

 

Instant Download – Complete Test Bank With Answers

 

 

Sample Questions Are Posted Below

 

Chapter 5

Answer Key

 

  1. What is the difference between secondary analysis and primary research?

Secondary analysis refers to analysis of data or information collected by another researcher or organization, including the analysis of data sets collated from a variety of sources to create time-series or area-based data sets. It differs from primary research in that primary research involves the firsthand collection of data or information by the researchers or research team. The data are gathered through the research and did not exist prior to the study. By contrast, secondary analysis uses available data or information collected by others, for similar or different purposes, whether research-oriented or not. Secondary analysis can also be additional analysis of a data set collected by the researcher, but to answer questions other than the one initially studied. Not all secondary data analysis studies involve data from external entities. Since most secondary analysis does not require researchers to have contact with subjects, it is sometimes referred to as nonreactive or unobtrusive research.

 

  1. What are the major types of secondary analysis?

There are several ways to classify the types of secondary analysis. When considering the number of databases used, secondary analysis may be classified as a cross-sectional study or a longitudinal study. Cross-sectional studies capture one moment in time. Exploratory and descriptive studies are often cross-sectional. Longitudinal studies are designed to allow for observations over an extended period of time, and include trend studies, cohort studies, and panel studies. Trend studies investigate changes within a general population over time, cohort studies examine specific subpopulations over time, and panel studies are similar to trend or cohort studies, but investigate the same set of people each time.

 

Secondary analysis can also be classified by the sources of data. Research-oriented secondary data include all data sets collected by others for research rather than other purposes. Nonresearch-oriented secondary data include publicly available documents, official records, private documents and records, media, and physical nonverbal materials. The fundamental difference between research-oriented and nonresearch-oriented secondary data has to do with quality in terms of both data collection and documentation. Research-oriented data sets are generally collected according to strict procedures of sampling and measurement, while nonresearch-oriented data sets are comparatively less strict on both accounts.

 

Another way to classify the types of secondary analysis is by method. Content analysis is a research method appropriate for studying human communication and aspects of social behavior, and is typically used with archival records. The basic goal is to take a verbal, nonquantitative document and transform it into quantitative data. The units of analysis include words, paragraphs, books, pictures, advertisements, and television episodes, and contents can be manifest or latent. A second method is analyzing published statistics, which are aggregate information that cannot be traced to the individual level from which the aggregation is made. The unit of analysis is an aggregate element, such as a county, region, state, country, or city. The third method is historical analysis, which involves attempts to reconstruct past events and the use of historical evidence to generate and test theories. The basic evidence primarily consists of authentic documents, such as testimony and organizational records.

 

  1. What are the secondary data sources you can identify?

Answers will vary. Examples of research-oriented secondary data sources include the Area Resource File, National Ambulatory Medical Care Survey, National Health Interview Survey, National Hospital Discharge Survey, Medical Expenditure Panel Survey, HRSA Geospatial Data Warehouse, Uniform Data System (UDS), Pregnancy Risk Assessment Monitoring System (PRAMS), National Survey of Children with Special Health Care Needs, Medical Expenditure Panel Survey (MEPS), Healthcare Cost and Use Project (HCUP), Medicare Current Beneficiary Survey (MCBS), National Health Care Survey (NHCS), National Health Interview Survey (NHIS), Cardiovascular Health Study (CHS), National Sample Survey of Registered Nurses, and Medicaid Analytic eXtract.

 

Examples of nonresearch-oriented secondary data sources include:

  • Public documents and official records, such as government agency proceedings, court records, state laws, city ordinances, directories, almanacs, and indexes such as the New York Times Article Archive and The Reader’s Guide to Periodical Literature
  • Official statistics, such as vital statistics from birth, death, marriage, and divorce certificates, and census data
  • Private documents and records, such as diaries, letters, notes, personnel and sales records, inventories, tax records, and patient records
  • Media, such as the Internet, television, newspapers, radio, periodicals, and movies
  • Physical nonverbal materials, such as works of art (paintings and pictures), artifacts, and collections

 

Responses identifying other secondary data sources are also acceptable.

 

  1. What are the strengths and weaknesses of secondary analysis as a scientific inquiry?

The principal strength of secondary analysis is economy, achieved through money, time, and personnel saved in data collection and management. The development of computer-based analyses has also made it relatively easy for health services researchers to share their data with one another. The multiple sources of secondary data enable researchers to conduct inquiries into many areas of interest. Because of the economy and availability of secondary data, secondary analysis is fast becoming one of the most popular methods of health services research.

 

In addition to savings on time, cost, and personnel, the use of available data may afford the opportunity to generate significantly larger samples than primary research, such as surveys and experiments. Secondary data may also be viewed as more objective and, therefore, more credible because the purpose of data collection is not research oriented, and personal biases are less likely to be introduced. Secondary analysis affords the opportunity to study trends and changes over a long period of time, and is also the preferred method for carrying out area-based research, particularly international comparative studies. Using secondary data can also strengthen primary research, as secondary data are helpful in designing subsequent primary research studies and can serve as a baseline for comparison with primary data collection results.

 

The principal weakness of secondary analysis is the extent of compatibility between the available data and the research question. Secondary data must be found rather than created to the researcher’s specifications, and searching for relevant data sources isn’t easy. Once identified, the value of available data will depend on the degree of match between the research questions to be addressed and the data that happen to be available. Often, available data are not well suited to the researcher’s intended purposes. Because of potential compatibility problems, the design of secondary studies may have to be started from back to front. One key disadvantage is that the scope and content of the studies are constrained by the nature of the data available. Even if relevant secondary data exist, they may not offer the information required to address the research question, including the definitions and classifications that the researcher wishes to use. Access to data may also pose a challenge. It may need to be negotiated, there may be constraints for confidentiality and ethical concerns, and laws may sometimes prohibit the release of certain government data.

 

Another limitation of secondary data, particularly administrative records that were not collected for research purposes, is that records are frequently incomplete or inaccurate. The process of examining secondary data can be time-consuming, and there are several ethical issues to consider regarding secondary data analysis. The researcher must obtain informed consent, and authorship and acknowledgment issues must be worked out between the researcher and the owner of the data. The researcher must also make clear his or her intentions for the use of the data at the start of the project, and must maintain the subjects’ confidentiality in the data throughout the project.

 

  1. Do the following exercise as a way to learn the process of conducting secondary analysis. Choose an available data set, either from published sources or other researchers, and study the measurements carefully. Based on the measurements available, try to conceptualize a research topic of interest to you. Describe, in detail, what measures you will use to study your topic. Describe any limitations you might encounter (e.g., missing variables or inaccurate approximates).

 

Answers will vary, but should identify a research topic and include a detailed description of the measures the student will use to study the topic, and any limitations the student is likely to encounter.

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