Social research methods and applications

Social Research - Quality of Life in the Elderly Community

If I were interested in studying the quality of life among the elderly, I would study a number of quantitative and qualitative factors to assess the quality of their lives. The qualitative factors that I would look at would be the activities of daily living ADLs). The activities of daily living would yield information as to the individual senior's pursuit for quality in life. I would look for:

The individual's network of contacts with friends and relatives

The individual's activities in private

The individual's activities in public

Exercise routine

Social routines

Ability to prepare meals

Ability to do housework

Hygiene

Tasks demonstrating mental acuity, like paying bills, reading, writing, and hobbies.

Each of these ADLs contribute a value to an individual's quality of life, and assigning them a value score based on medical literature and recommendations would serve to quantify them in a way that would put the information into research perspective.

The basis for which the notion of ecological fallacy, simply put, emerges is that an individual, or animal, adapts to their environment and evolves in conformity with that environment. Selection acts result in producing learning abilities which are conducive to adapting to the environment around you. Once you have made the minimal selections that force the adaptation to the environment, then other developmental responses to the environment will likewise follow, and in a more natural way. It is important to understand that the term ecological fallacy, brings about some confusion in understanding its meaning. The process of reasoning from aggregate to individual level processes is neither ecological nor a fallacy. Quantitative information about people can be done at aggregate levels of analysis, and many methods of unbiased ecological inference have been developed.

A model of research representing an ecological fallacy would be one, as described in response to Question 1, where the observations would be assigned quantitative values without quantifying the value of the ADL to the individual's own life. The way to correct this would to be to quantify the ADL in the life of the individual, as opposed to the life of a group of individuals, and to use that information accordingly as to the quantitative value of the ADL in the life of the person who is being observed.

The proposed research and model to be developed is on work related stress disorders. The study will limit its scope to those disorders of the upper extremities; the neck, shoulders, arms and hands. The data for examining WRSD will be for a 10-year period, 1996 to 2006, using data compiled from workman compensation claims to establish a number in the increase of WRSD claims for conditions of the specified upper body extremities. The process will seek to evaluate and extrapolate the number of increased claims in 2-year increments for a set of five data elements. The study will further examine and extrapolate quantitative information based on the increase in surgical procedures over that same period of time to determine if there was an increase in the procedures performed arising out of WRSD.

A model can be built by reviewing the theories of job stress disorders involving the upper extremities. Two mechanisms will be presented for the relationship between job related stress disorders and job stress: 1) psychological precipitator 2) response to precipitator by way of stress reaction. The model will include a component for examining work or organization type, stress, and WRSDs related to those occupational types.

As sometimes happens, if a researcher finds that information on 10 to 35 cases out of 2000 are missing for each variable that she intends to use in her composite measure. The first option is to go back and redo the missing 10 to 35 cases, which might not be an option depending upon the process involved in collecting the data. The other option would be to compensate for the data loss by including the missing data as a margin of error; or reducing the 2000 cases in proportion to the missing data.

Creating scales, indexes, or any measurement/assessment instrument that might be called a test is part of the research process that is concerned with calibration. In many ways, calibration is a quick and easy way to achieve precision and accuracy, which are, of course, important goals of measurement. One can just as easily get by without creating a scale or index, but at some point, at least in estimating the reliability and validity of your study, you're going to have to look at item and response patterns. Do the items (questions) you're asking fit together in the most productive way, or do they overlap redundantly? Do the response patterns (answers) hint at ways you can improve your measuring instrument? There's a big difference between scaling and scoring a test, and since most readers are familiar with the typical multiple choice tests found in education, that's where we'll start. it's not uncommon for social sciences to draw upon the field of Education Statistics.

A scale is a cluster of items (questions) that taps into a unitary dimension or single domain of behavior, attitudes, or feelings. They are sometimes called composites, subtests, schedules, or inventories. Aptitude, attitude, interest, performance, and personality tests are all measuring instruments based on scales. A scale is always unidimensional, which means it has construct and content validity. A scale is always at the ordinal or interval level, but it's conventional for researchers to treat them as interval or higher. Scales are predictive of outcomes (like behavior, attitudes, or feelings) because they measure underlying traits (like introversion, patience, or verbal ability).

The Gallup data helps us understand the voter perspectives as regards the integrity of the voting system and processes. However, it should be noted that the information is based upon a small sampling of the nation as a whole, and that the area where the poll would be conducted would have an impact on the data yield. For instance, voters on the east coast might have different political leanings based on their geographical concerns, careers, environmental, social and other life factors that voters feel should be impacted or addressed by the government. The poll as given in this example tells us that the information should be regarded with caution.

The aftermath of Hurricane Katrina, which left the city of New Orleans devastated in way that it has yet to recover, is the a perfect case for a study of health related issues arising out of that devastation. Public facilities like sewer and water were compromised in such a way that event that the impact of the health related conditions are as of yet unrealized. Studies should be set up to conduct quantitative and qualitative research on health related conditions such as breathing ailments, conditions related to fungus and other allergens that are residual factors of such a massive natural disaster. Perhaps the most significant study would be one related to physical and psychological impact of the disaster on the population that remained in the city vs. The population that were evacuated from the city. It would be interesting to note as to whether or not the stress related conditions would produce similar or different stress conditions in those two groups of individuals.