Week 1 DQ 1 1. Voluntary consent of the participant is absolutely essential. The subject must be capable of giving consent without coercion, and full responsibility for obtaining consent rests with the principal investigator. 2. The experiment must be designed to bring forth results that will benefit society and that cannot be obtained in any other manner. 3. Human experimentation should be based on animal research results as well as knowledge of the natural course of events, disease, or problems. 4.
All unnecessary mental or physical harm should be avoided. 5. When there is reason to believe that death or disabling injury may occur, no experiment should be conducted except, perhaps, when the experimenting physicians also serve as subjects. 6. The degree of risk should never exceed the humanitarian importance of the problem to be solved. 7. All precaution should be taken to protect subjects from even remote possibilities of injury or death. 8. Only qualified personnel should be allowed to conduct experiments.
The principal investigator must be ready to terminate the experiment at any stage if it appears that injury or death will result. Research Techniques for the Health Sciences, Fourth Edition Chapter 4: Considering Ethics in Research Explain two basic principles for humane treatment of human subjects in research. Drawing on the course readings or a current news item, provide an example of a study in which ethical principles were not followed. How might study design have been improved in that case?
The two basic principles for human treatment of human subjects in research most significant to me are, making sure all precaution is taken to protect subjects from even remote possibilities of injury or death, and allowing the subject to withdraw from the experiment at any time if a point is reached that may bring about physical or mental harm. It is important that we do not use humans in research as crash dummies, as if they are simply replaceable after harm and injury.
It is only right to take all precautions and allow the human subject to change their mind about participating in the research. Ethical principles were not followed in the Tuskegee Syphilis Study found in our text. The human subjects were not fully aware of the study, and the purpose of the research was more so the subjects could die and they could perform an autopsy. Week 1 DQ 2 What are the advantages of using a mixed method approach to research? What are the challenges? Provide an example of how you have used (or, in the future, could use) this approach in your professional role.
The strength of the research; 2) Use of multiple methods in a research helps to research a process or a problem from all sides; 3) Usage of different approaches helps to focus on a single process and confirms the data accuracy. A mixed research complements a result from one type of research with another one. This research does not miss any available data. The aim of a mixed method design is to summarize positive aspects of two approaches and produce a highly accurate data.
When you use several methods in your research process, then you can use the strength of every type of information collection and minimize the weak points of every of both approaches. A mixed method approach of gathering and evaluation can increase the validity and accuracy of the information. The advantages of using a mixed method approach to research are having several different outcomes in the process of your research. What this does is allows the researcher to use the strengths from the information collected and minimize the weaknesses from the information collected.
Using a mixed method approach can ultimately increase the accuracy and validity of the information. The challenges of using a mixed method approach will be that the time of researching will be extended. Extending the time of research could definitely be a challenge if there is a time frame to find results in. Depending on the purpose of the research, using a mixed method approach can be a waist of time. An example of using the mixed method approach was when I wanted to explore (qualitative objective) why people shop on-line.
I conducted open-ended interviews (qualitative data collection) asking people why they shop on-line, and then I quantified the results by counting the number of times each type of response occurred (quantitative data analysis). Week 2 DQ 1 What is the difference between reliability and validity? Imagine that you are going to develop a new instrument for research in your field, using course readings, provide specific examples of how you might go about establishing its reliability and validity. (Make sure to cover at least one approach for determining reliability and one for determining validity. Reliability is, roughly, whether you could replicate an experiment and get comparable results – either because an individual’s responses are consistent (for example, their reaction times in a test are consistent when the test is carried out again), or the general overall results are consistent (for example, the average score on a test is the same or similar when carried out again on a comparable group) Validity is whether the construct you are using really measures what you are using it to measure.
For example, if you devised a test to measure people’s self-esteem, does it really measure self-esteem, or something similar such as extraversion? Reliability refers to the ability to perform the same experiment and get the same results. Validity refers to the accuracy of those results. You could perform the same experiment many times and get the same results, but they may not be correct (if the experiment is flawed for example). This would be reliable, but not valid. Conversely, you could perform an experiment that yields accurate results once, but not when it is repeated.
This would be accurate (one time anyway), but not reliable. Reliability is the consistency of the degree to which an instrument measures the same way each time it is used under the same condition with the same subjects; in short, it is replicating an experiment and getting comparable results. For example, a second test measuring reaction time showing the same reaction times as the first test. Reliability is all about the ability to perform the same experiment and get the same results. Validity is whether the construct you are using really measures what you are using it to measure.
It is essentially the strength of our conclusions, inferences or propositions. For example, a test measuring people’s confidence, does it really measure confidence, or something similar such as faith in something? Week 2 DQ 2 What are some of the advantages and disadvantages of survey research? Provide an example of survey research findings that were recently published in the news. First, briefly summarize the study design and findings. Second, based on what we have read about survey research, provide critical feedback on this study’s design or explain what additional information you would need to make a critical assessment of this study.
Strengths: 9. Surveys are relatively inexpensive (especially self-administered surveys). 10. Surveys are useful in describing the characteristics of a large population. No other method of observation can provide this general capability. 11. They can be administered from remote locations using mail, email or telephone. 12. Consequently, very large samples are feasible, making the results statistically significant even when analyzing multiple variables. 13. Many questions can be asked about a given topic giving considerable flexibility to the analysis. 14.
There is flexibilty at the creation phase in deciding how the questions will be administered: as face-to-face interviews, by telephone, as group administered written or oral survey, or by electonic means. 15. Standardized questions make measurement more precise by enforcing uniform definitions upon the participants. 16. Standardization ensures that similar data can be collected from groups then interpreted comparatively (between-group study). 17. Usually, high reliability is easy to obtain–by presenting all subjects with a standardized stimulus, observer subjectivity is greatly eliminated.
Weaknesses: * A methodology relying on standardization forces the researcher to develop questions general enough to be minimally appropriate for all respondents, possibly missing what is most appropriate to many respondents. * Surveys are inflexible in that they require the initial study design (the tool and administration of the tool) to remain unchanged throughout the data collection. * The researcher must ensure that a large number of the selected sample will reply. * It may be hard for participants to recall information or to tell the truth about a controversial question. As opposed to direct observation, survey research (excluding some interview approaches) can seldom deal with “context. ” Advantages of survey research could be cost efficiency since surveys are relatively inexpensive. Surveys are useful in describing the characteristics of a large population and not a lot of other methods of observation can provide this general capability. They can be administered from distant locations. Many questions can be asked about a given topic giving flexibility to the analysis. Disadvantages of survey research could be researchers being forced to develop general questions.
Surveys are inflexible because they remain unchanged throughout the data collection. Also, with surveys the researcher must ensure that a large number of the selected sample will reply, otherwise the survey would not be sufficient. In the news there was a survey about homelessness in Santa Cruz County. A count and survey conducted by the United Way of Santa Cruz County and the nonprofit research firm Applied Survey Research, and it showed that the homeless population in Santa Cruz County has jumped 22 percent in two years. The survey design was cross-sectional. It asked several questions at one oint in time. The survey collected age, gender, race, and reason for being homeless. http://www. santacruzsentinel. com/opinion/ci_18565125 http://www. phc-santacruz. org/_pdfs/2011%20Santa%20Cruz%20Homeless%20Report%20-%20FINAL. pdf Week 3 DQ 1 How can you avoid bias when selecting samples for human services research? Imagine that you are going to design a survey that will be administered to consumers/clients in your field (e. g. , nursing home residents, youth mentors, single mothers); how would you go about sampling from this population in order to generate meaningful data?
What might be some of the challenges in ending up with a representative sample? To avoid bias when selecting samples for human services research a diverse set of individuals should be chosen within the same community. Different ethnicities, different genders, equals different beliefs, backgrounds, and futures. Selecting individuals in this manner should avoid bias. Hypothetically I work for an organization that offers services to young and troubled girls, especially those who have been to juvenile hall. Schools and juvenile halls if permitted would be great places to begin my sampling.
Schools and juvenile halls both have a diverse population where bias could be avoided. The barriers I could see myself running into would be getting the permission to survey the minors in the first place. The biggest barrier would be knowing what girls are considered troubled or not and who they are specifically to get only their feedback and not girls who are not considered troubled. Week 3 DQ 2 List different measures of variability discussed in the readings and, using your professional field, provide an example to illustrate the concept.
If you were a manager looking at these measures of variability around some aspect of employee productivity, what may they tell you about an individual’s or team’s performance? The range is the most obvious measure of dispersion and is the difference between the lowest and highest values in a dataset. The range is based solely on the two most extreme values within the dataset. The range is simple to compute and is useful when you wish to evaluate the whole of a dataset. The standard deviation indicates how tightly the values in the dataset are bunched around the mean value.
The standard deviation is the most vigorous measure of variability because it’s measuring how every value in the dataset varies from the mean. You must be careful when calculating the standard deviation to consider whether the entire population or a sample is being examined and to use the appropriate formula. If I were a manager looking at these measures of variability around some aspect of employee productivity, the range would point out the highs and the lows of the team performance.
This would allow me to know my team’s strength and weakness, and then I would be able to work on ways to minimum the weaknesses in performance. Week 4 DQ 1 Based on the textbook readings, describe the “third variable problem” as it relates to correlation and provide an example of how you might see this played out in your own field. Week 4 DQ 2 How does hypothesis testing contribute to the scientific knowledge base? Based on the textbooks’ descriptions of hypothesis testing, provide an example of how you might implement this in your work. othesis is an edjucated guess an it is some time’s the closest we can get to the trueth of things we do not yet understand Scientists use a scientific method to investigate phenomena and acquire knowledge. They base the method on verifiable observation — i. e. , on empirical evidence rather than on pure logic or supposition — and on the principles of reasoning.   Scientists propose explanations — called hypotheses — for their observed phenomena, and perform experiments to determine whether the results accord with (support) the hypotheses or falsify them.
They also formulate theories that encompass whole domains of inquiry, and which bind supported hypotheses together into logically coherent wholes. They refer to theories sometimes as ‘models’, which usually have a mathematical or computational basis.   determining the focus and direction of the research, it forces researcher to state the purpose of the activity, determines what variable are being studied and or considered and also it allows to a required operational definition of the variable that are being studied.
Hypothesis testing is a must for any person to successfully test their studies and make sure there are no flaws. Hypothesis is an educated guess an it is some times the closest we can get to the truth on matters that we do not yet understand. Scientist base their method on verifiable observation rather than on logic. Hypothesis testing forces researchers to address the purpose of the activity while determining what variables need to be studied and also requires operational definition.
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