Saint Petersburg College Module 5 Health & Human Services Discussion Paper Module 5 Discussion

Do you know the Difference?

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Saint Petersburg College Module 5 Health & Human Services Discussion Paper Module 5 Discussion
Do you know the Difference?
Students new to research often

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Students new to research often find some of the terms and concepts confusing as some of the terms may be used interchangeably in different areas of research, such as data and statistics. However, when reviewing scholarly research, it is important to understand the differences between some key terms.

For this discussion, I want you to take on the role of the instructor and explain the difference between the following terms: data, statistics, descriptive statistic, inferential statistic, statistical methods, and describe/identify an example of each that you find in a single research article from the SPC article databases

Post a working link and/or URL to your article (do not forget citations and references). Check out this Permalinks Tutorial to help you find a “Permalink” or “Persistent link” for your article so that you can post a direct link to the article. I recommend that you keep the tutorial for future reference (note, these links are what you should use for retrieval information in your APA formatted Reference entry when there is not a doi present).

You may wish go back and visit one of the early topics in the book, Empirical Research, as well as this weeks required reading. Outside reading is also recommended. I want to hear that you have a good understanding of these terms and the differences between them as you prepare to complete the next part of your Article Analysis

Module 6 Discussion

Applying Research Findings

You have been analyzing research studies for the past 6 weeks. Using the research article that you chose to analyze in Analysis 1 and Analysis 2, please address each of the following questions in your POSTING:

Effects of large financial incentives for long-term smoking cessation. A Randomized Trial, by Jean-François Etter and Felicia Schmid. This article is published in the Journal of the American College of Cardiology, Volume 68, Number 8, 2016.doi: https://doi.org/10.1016/j.jacc.2016.04.066

What experiment was taking place in your study

What did your research study mean to YOU?

What do you think the “take home message” is?

Will what you learned from this study alter YOUR practice behaviors?

Has this study influenced your professional THOUGHT? How?

Identify and RESPOND to one of your colleague’s postings

In that post, tell us something you learned from your colleague’s posting.

How might you APPLY this information to YOUR professional setting?

Module 7 Discussion

Protection of Human Subjects

As an overview for this forum, start by reading the content page titled : Unethical Research at Home, four specific atrocities are introduced briefly.

Please search the Internet to find an electronic report on ONE of these research atrocities/human experimentation examples listed below.

Tuskegee Terre Haute Prison Experiment

Willowbrook Belleview Electro Shock Experiments

Jewish Chronic Disease Hospital Study Eugenics laws for forced sterilizations

Human Radiation Experiment The Milgram Experiment

Stanford Prison Experiment Little Albert Study

The Monster Study Emma Eckstein Study

Pellagra Incident The Monkey Drug Trials

1940 Chicago Malaria Study The Bobo Doll Experiment

Chemical Warfare Services studies completed by the U.S. Army (many – find a specific one)

The Landis Facial Expressions Experiment

CIA studies related to mind control and LSD (find a specific one as there are several, i.e., Project MK-ULTRA) Harry Harlow The Pit of Despair Experiment

U.S. Army germ/biological warfare studies (find a specific one, there are many!) John Darley and Bibb Latane The Bystander Effect

U.S. Army Mustard gas and lewisite experiments Racism among Elementary School Students Jane Elliott

U.S. Military Yellow Fever studies UCLA Schizophrenia Experiments

Pennsylvania Prison studies related to Dioxin Loftus Lost in the Mall Study

SV40 Virus contamination of the Polio Vaccine Dr. William Beaumont The Hole in the Stomach study

Guatemala Syphilis Experiment

For this forum:

Provide a working link and/or URL to your electronic report OR attach a copy of your report to the Discussion forum.

Provide the title of the Experiment or Research

Provide the date(s) of when it took place

In a 250-300 word post please share with all of us: Give an overview of the content of your report – in your own words (Do not cut and paste – you will not receive points if you do).

Describe your reaction to what you read.

Name and describe ( using the section number or titles) 1 specific standard that is now in place through the IRB: Title 45 Protection of Human Subjects that may help protect subjects from the uneithical action that you discovered in your readings. Select one from the Guidebook OR the Health and Human Services link: Title 45 Protection of Human Subjects. For example, in the HHS link I might NAME: 46.116 General Regulations for Informed consent and then DESCRIBE, in my own words the specifics of this section. Descriptive Statistics

A statistic is a numeric characteristic of a sample

A parameter is a numeric characteristic of a population

Descriptive Statistics are used to:

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organize, condense and summarize data with numbers and pictures

pictures: frequency distributions and graphs (histogram, polygon)

numbers:

o measures of central tendency: mean, median, mode

o measures of variation: range, standard deviation

Measures to Condense Data

Frequency Tables

Example:

DATA SET: ages of 12 randomly selected members of our HSA 3702 Research Class

(sample size is n=12)

22

33

25

40

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25

30

41

50

34

63

25

39

20-29=4

30-39=4

40-49=2

50-59=1

60-69=1

Measures of Central Tendency

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mean: arithmetic average; add all ages divide by “n.”

median: arrange data set in ascending or descending order and select the middle

value. If there is an even # in the data set

calculate a mean of the middle two numbers.

mode: variable that occurs the most.

Now you try: use our data set above to calculate

Mean age of our research class_______________

Median age of our research class_____________

Mode of our research class____________________

How did you do?

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mean of our data set: 35.6 years

median of our data set: 33.5

mode of our data set 25

These are ALL measures of central tendency aka “averages” and look how much they

vary.

Does your assignment research article use an “average?”

Do the authors alert the reader to which “average” they used: mean? median? mode?

Measures of variability

range: difference between highest and lowest value in your collected data.

According to our data set, what is the range of ages in our class? _______

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Answer: 41 years

Standard deviation of a data set is the average deviation of each of our ages from the

mean. Just remember the concept. We will be using it later on in the module.

Inferential Statistics

Inferential statistics, are those statistics that use sample data to make decisions or

‘inferences’ about a population. Populations are the groups of interest when inferential

statistics are used even though the data are analyzed from samples.

There are two broad purposes of inferential statistics:

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estimating population parameters using sample data

testing hypotheses

Population parameters

To estimate population parameters from sample data, an understanding of sampling

error and sampling distribution are necessary.

Sampling errors occur when a sample does NOT accurately reflect the population.

Whenever we use a sample to make inferences about a “population”…..no matter how

careful we are to select a representative sample….there is a chance for sampling error.

For example, suppose 25 of our BASHSA students were randomly selected to represent

all of our BAS students at SPC on a standardized test administered by the college. The

sample’s mean score on the test was 70 and the standard deviation was 10.

Would we have obtained the exact same mean score on the standardized test if we had

used every person in the BAS programs at SPC in our calculation of the mean and

standard deviation? Most likely, not. As Patten (2014) indicates: random sampling

produces random errors. At first, this situation might seem rather hopeless but,

fortunately, the effects of random sampling errors are fairly predictable.

Here is how:

A widely reported inferential statistic is the margin of error. It is a type of standard

deviation. The margin of error expresses the amount of random sampling error in a

research study’s results. This statistic helps us, the readers of the research study, to

interpret the study’s results in light of sampling error. To calculate this inferential statistic

we need to divide the standard deviation by the square root of the sample size. We

have all the data we need.

Our standard deviation is 10 and our sample size is 25. Now plug it into the formula:

The square root of 25 is 5 so the square root of our sample size is 5.

When we divide our standard deviation of 10 by 5 we have a margin of error of 2.

Margin of Error = 2

Sampling distribution

Now that we know that the margin of error we are able to make some interesting

predictions with varying degrees of confidence.

In order to make these predictions we need to think back on the concept of the central

limit theorem that perhaps you might remember from earlier science classes? It states

that a sampling distribution of means forms a normal curve. The readings in Topic 53

and Appendix D reiterate this concept.

When there are a number of sample values that are arranged in a frequency

distribution, those values will be normally distributed.

IN FACT, 68% of those values will fall within 1 standard deviation above and below the

mean; 95% of those values will fall within 2 standard deviations above and below the

mean and 99% will fall within 3 standard deviations above and below the mean!

With these facts in mind, consider a practical use of the margin of error: Confidence

Intervals.

Confidence intervals

Specifically, the margin of error can be used to build 68%, 95% and 99% confidence

intervals (CI) for constructing a population mean from a sample mean.

A confidence interval (CI) is a range of values that, with a specified degree of

probability, is thought to contain the population value.

In everyday terms we could say that while we found that the mean standardized test

score of our sample was 70, the value might have been influenced by sampling errors.

To account for these errors a more reliable estimate of the true population mean is that

the mean score would fall between 68 and 72. We could report this interval with 68%

confidence.

How did we come up with this interval? By adding and subtracting the Margin of Error

(2) from our sample mean.

It is much more common for researchers to report 95% and 99% confidence intervals

instead of the 68%.

Using our concept of the normal curve, we would subtract & add 2 margin of error units

(4) for a 95% Confidence Interval AND 3 margin of error units (6) for a 99% Confidence

Interval

OK, now you give it a try:

Using a random sample of BASHSA students with a standardized test score of 70 and a

margin of error of 2, we could be 95% confident that the mean test score of all BAS

students at SPC lies between ____________and ______________. We could have

99% confidence that the mean test score of ALL BAS students at SPC lies between

___________and___________.

How did you do?

We could have 95% confidence that the mean test score of all BAS students lies

between 66 and 74.

We could have 99% confidence that the mean test score of all BAS students lies

between 64 and 76.

Levels of measurement

Before determining the appropriate data analysis procedures that will be used to test a

hypothesis, a researcher must understand the level of measurement being collected by

the study’s data collection tool aka measurement instrument.

The level of measurement dictates which statistical procedures can be used. For

example, if a researcher has collected nominal level data, a mean cannot be calculated

on the data.

There are four levels of measurement.

Nominal level

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categories: Republicans, Democrats, males, females, yes, no

no rank order. You cannot say that Republicans are higher on a scale than

Democrats

counting is the only mathematical operation you can do with nominal level data:

10 Republicans/4 Democrats; 16 yes/11 no.

mode is the only measure of central tendency that can be done on nominal data

Ordinal level

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numbers specify the orde,r but there is no certainty that the intervals between

ranked categories are equal

example: a rubric might have a rank-order of 0-6 for content. Each of the

numbers stand for specific criteria. Where 5 is excellent, several sentences follow

to describe what “excellent” means. Only as a result of the sentence descriptions

do we know that excellent is better than good.

a researcher is able to rank-order the respondents or their responses to

questions because one category is ranked higher or lower, better or worse than

another.

many health care scales use ordinal level data

median and mode are measures of central tendency with ordinal data

Reports of nominal data might state: most (mode) of the students in the research

class scored “good” or better on their article analysis content.

Or, the median content score was “good.”

Interval level

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intervals between the numbers are meaningful and can be compared, but there is

no absolute zero

example: the average temperature in St. Petersburg was 60 degrees

Fahrenheit in January 2013 and could be meaningfully compared to the average

temperature of 55 degrees in January 2012.

mean, median and mode can be calculated using interval data.

Ratio level

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possesses a true zero

a 20 pound turkey is twice as heavy as a 10 pound turkey

weight measurement, length, cell counts, oxygen saturation

mean, median, mode can be calculated using ratio level data

Think about this…..

If you think back to your problem statement in Module 1 and the data that you would

need to collect in order to answer your research problem statement, what level of

measurement would you use?

Would you be able to calculate a mean? median? mode?

Ethical Considerations

Tuskegee

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1932, US Public Health Service initiated a study of syphilis in African-American

men

Study continued for 40 years, finally discovered and stopped in 1972

Purpose was to study the natural course of disease in African-American men

Lacked informed consent

Withheld available treatment from subjects

Tuskegee apology, human experimentation

Willowbrook Study (New York)

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Mid 1950 s to early 1970 s research was conducted by Dr. Saul Krugman at the

Willowbrook Institution for the Mentally Retarded

Mentally retarded children deliberately injected with hepatitis

Parents were forced to give consent for their children to be in the study in order

to obtain placement at the facility. Willowbrook was overcrowded and only the

research wing would admit new patients.

Persons conducting the study defended it by saying that the children would have

gotten hepatitis anyway by being exposed to everyday conditions at a mental

institution and that because of the study funding the children benefited from a

clean environment, better supervision and higher nurse patient ratio

Jewish Chronic Disease Hospital Study (New York)

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Occurred in 1960 s

Patients injected with cancer cells to determine the body’s ability to reject cancer

Patients were not informed regarding research or injection of live cancer cells

Physicians caring for patients were unaware of research

Human Radiation Experiments

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On April 10, 1945, medical staff of the U.S. Manhattan Engineer District in Oak

Ridge, TN, injected plutonium into the victim of a car accident

American scientists had only recently begun producing plutonium and thousands

of workers were laboring to produce the quantities required for the first atomic

bombs.

While aware that plutonium was hazardous, project officials were uncertain how

much exposure would cause harm.

Desire for information about human metabolism and retention of plutonium led to

this first injection in Oak Ridge.

Over the next 2 years, 17 other people also received plutonium injections.

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