topic 3 DQ 2

Please i would need this questions to be answered by Thursday. words between 150-200. with references as well.

What factors need to be considered when determining whether or not identified actions are within the domain of nursing practice? Be sure to cite current literature in your response.

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Topic 3 DQ 2

Please write a paragraph with your opinion based on the text bellow. Please include citations and references in case you need to used for the question:

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There are a variety of environmental factors that are strongly correlated to increased rates of teen pregnancy. There is a strong correlation between teen pregnancy and the neighborhood in which the teens live. Teens who live in neighborhoods with high levels of poverty, low levels of education and high residential turnover are at higher risk for teen pregnancy (Bishop, 2007). Family is also a strong indicator of the possibility of teen pregnancy. Typically, teens that come from poor, less educated, single-parent families are at a greater risk for pregnancy (Bishop, 2007). Teens whose mother or sister gave birth as a teen are also more likely to become pregnant during their teenage years. Females whose families provide less support and supervision are more likely to become pregnant as teenagers. Several individual risk factors may affect whether a teen becomes pregnant. Apparent risk factors include poor performance in school, aggressive behavior, engaging in other risky behavior (including using drugs and alcohol), dating at a young age, dating older partners, and not being well-liked by peers (Bishop, 2007). Teens who experience puberty at an early age, males with high levels of testosterone and adolescents who have experienced sexual abuse or pressure are also at greater risk of early childbearing. Females who have permissive attitudes toward premarital sex, have negative attitudes toward using contraceptives, and either want to have a child or are ambivalent about having a child during adolescence are more likely to become pregnant as teenagers. An adolescent female may be ambivalent about becoming pregnant if she has a low expectation for her future, feels unable to control her life or
feels isolated.

One resource that is available in my state of WI is called The Wisconsin Second Chance Home Project. This program addresses numerous prejudices and ensures that all homeless pregnant and parenting youth in WI will have a safe alternative to the street. This project also addresses the need of these young people and their children for a safe living environment by creating a system of second chance homes (Wisconsin Association for Homeless and Runaway Services, 2010). Another national resource that is available is Planned Parenthood. Planned Parenthood “delivers vital reproductive health care, sex education, and information to millions of women, men, and young people worldwide” (Planned Parenthood, 2012).

According to the Wisconsin Department of Health Services (2012), Wisconsin had 6,849 births to teen parents, ages 15-19 in 2001 and 5,147 births in 2010. In my small hometown in Washington County, we had 76 teen births in 2001, and 48 teen births in 2010 (Wisconsin Department of Health Services, 2012). I think this decrease rate is due to the increase in sex education classes in schools and the community as well as the increase use of contraceptive use in teens.

References

Bishop, D. (2007). Teenage pregnancy: An adolescent health issue in Australia. Nuritinga, (8), 1-9. Retrieved from http://library.gcu.edu:2048/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=rzh&AN=2009934760&site=ehost-live&scope=site

Planned Parenthood. 2012. Who we are. Retrieved from http://www.plannedparenthood.org/about-us/who-we-are-4648.htm

Wisconsin Association for Homeless and Runaway Services. 2010. Second chance homes. Retrieved from http://www.wahrs.org/secondChanceHomes.html

Wisconsin Department of Health Services. 2012. Births to teens in Wisconsin. Retrieved from http://www.dhs.wisconsin.gov/publications/P4/P4536…

Topic 3 DQ 2

Please Respond to the following post with a paragraph, add citations and references.

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Each alpha level is dependent on the circumstances that surround a particular study. In statistical hypothesis testing, a type I error is the rejection of a true null hypothesis (also known as a “false positive” finding), while a type II error is failing to reject a false null hypothesis (also known as a “false negative” finding). More simply stated, a type I error is to falsely infer the existence of something that is not there, while a type II error is to falsely infer the absence of something that is (“Type I and type II errors,” 2018). For example, if doing a test for cancer and that test would determine if a cancerous organ should be removed, then you want to set the alpha level very stringent at 0.01. You do not want to remove an organ if it is cancer free. On the other hand, if you set the alpha level too stringent and you determine that the organ does not have cancer, when in fact it does then the patient may die prematurely because you made a type II error, failure to detect a difference when one in fact does exist. This can make for a delicate balance.

Situations where you might raise the alpha to 0.1 can vary greatly. The obvious one is when the results of the study are not that critical. For example, when trying to see if a mood therapy has an effect, you might raise the alpha to find the effect even though this increases the chance of making a type I error. Certain studies may appear to have biased results because they could have raised their alpha to 0.25 to say their product is better, and the statistics will support that claim, however the chance of making a type I error is 25%! This is why it is important to know statistics to make decisions that are important to you.

Generally, the only reason to raise a type I error rate is if a limited sample size or if no money to conduct the study at the 0.05 level. Choosing between a type I error or a type II error is a tradeoff, the more stringent the type I error the greater the change for a type II error. The question then becomes which is the lesser of two evils. Is it better to say there is an effect when there wasn’t (type I error) or is it better to say there was no effect when there was (type II error)? There can be other factors involved, but basically that is what it comes down to.

References

Type I and type II errors. (2018). In Wikipedia. Retrieved October 8, 2018, from https://en.wikipedia.org/wiki/Type_I_and_type_II_e…

Topic 3 DQ 2

Please Respond to the following post with a paragraph, add citations and references.

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When researchers are testing their hypotheses, the Alpha level should show significant results of your experiment. The researcher’s experiment should have enough evidence to support their proposed theory. When planning their experiment, they can set their Alpha level to what they want, and usual value is 5%, or 5 in 100 probability that the result is achieved by accident.

There are specific instances where it is more reliable to use a lower alpha level compared to a higher alpha. Your findings will have more significance and rate of accuracy, the lower the alpha. Alpha levels are set low to help decrease the possibility of obtaining Type 1 error. For example, if there’s a possibility of serious injury or death, we want to make the level smaller. When you have a high alpha level, the chance of having an error is raised. There are much stricter alpha levels when pharmaceutical companies are conducting research on new medications.

If the alpha levels are poorly designed, the results will not be accurate and have little importance in the research. A larger value of alpha, even one greater than 0.10 may be appropriate when a smaller value of alpha results in a less desirable outcome. Type 1 errors can occur when concluding your results. An example of when a higher level is acceptable is when the research has no significance on death or injury and can prove the theory that is being conducted.

References

The Minitab Blog, (2012). Alphas, P-Values, and Confidence Intervals, Oh My! Retrieved from http://blog.minitab.com/blog/alphas-p-values-confi… October 9, 2018

Grove, S.K. & Cipher, D. (2017). Statistics for Nursing Research: A workbook for evidenced based practice. https://pageburstls.elsevier.com/#/books/978032335… October 9, 2018