34

Medical Ethics

and scientific communities and the right to information about epidemics or outbreaks of disease; persecution of health profession- als for their independent medical or human rights activities; attacks on health facilities and personnel; medical evidence of torture and sexual violence and their severe physi- cal and psychological impacts; reproduc- tive rights and health; collusion of health professionals in human rights violations, including torture and executions; overt ob-

struction of the right to health; discrimina- tion within health systems; and much more. PHR has submitted documentation to this process on human rights violations in Bah- rain, Myanmar, the United States and Zim- babwe, among other countries.

Dozens of organizations worldwide regu- larly send representatives to speak at Hu- man Rights Council meetings on a range of issues. But the credible and influential voice

of the medical community in these halls of power is singularly underrepresented. PHR has been opening a door to these opportu- nities and welcomes company to develop a more robust presence in Geneva as threats against the independence of medical pro- fessionals and the silencing of civil soci- ety become ever more pervasive across the globe.

Susannah Sirkin, Director of Policy, Physicians for Human Rights

Ewan C Goligher Maria Cigolini Alana Cormier Sinéad Donnelly Catherine Ferrier Vladimir A. Gorsh- kov-Cantacuzène

Sheila Rutledge Harding

Mark Komrad Edmond Kyrillos Timothy Lau Rene Leiva Renata Leong Sephora Tang John Quinlan

Euthanasia and Physician-Assisted Suicide are Unethical Acts

The World Medical Association (WMA), the voice of the international community of physicians, has always firmly opposed euthanasia and physician-assisted suicide (E&PAS) and considered them unethi- cal practices and contrary to the goals of health care and the role of the physi- cian [1]. In response to suggested changes to WMA policy on this issue, an exten- sive discussion took place among WMA Associate Members. We, representing a voice of many of those involved in this

discussion, contend that the WMA was right to hold this position in the past and must continue to maintain that E&PAS are unethical.

The Central Issue Under Debate is the Ethics of E&PAS The question is whether it is ethical for a doctor to intentionally cause a patient’s death, even at his or her considered re-

quest. The fact that E&PAS has been legalized in some jurisdictions and that some member societies support these practices has no bearing on the ethical question. What is legal is not necessarily ethical. The WMA already recognizes this distinction, for example, by condemning the participation of physicians in capital punishment even in jurisdictions where it is legal. The WMA should be consis- tent in this principle also with respect to E&PAS.

35

Medical Ethics

E&PAS Fundamentally Devalues the Patient This devaluation is built into the very logic of E&PAS. To claim that E&PAS is compassionate is to suggest that a pa- tient’s life is not worth living, that her existence is no longer of any value. Since the physician’s most basic tasks and con- siderations are to ‘always bear in mind the obligation to respect human life’ and ‘the health and well-being of the patient’ [2, 3], E&PAS must be opposed. E&PAS distorts the notion of respect for the pa- tient. On the one hand it claims to help suffering persons, while on the other hand it eliminates them. This is a profound in- ternal contradiction; the ethical priority is to respect the fundamental intrinsic worth of the person as a whole.

E&PAS Puts Patients at Risk Patients are autonomous agents but are not invulnerable to their need for affirma- tion from others, including their physi- cian. Amidst the overwhelming fears of those who suffer (4, 5), a free autono- mous decision to die is an illusion. Par- ticular concern exists for those who may feel their life has become a burden due to changing perceptions of the dignity and value of human life in all its differ- ent stages and conditions, and an explicit or implicit offer of E&PAS by a physi- cian profoundly influences the patient’s own thinking. The troubles of human relationships within families, the pres- ence of depression, and problems of abuse and physician error in an already stressed medical system, make muddy waters even more turbulent [6]. Evidence shows that societies cannot always defend the most vulnerable from abuse if physicians be- come life-takers instead of healers [1, 6]. The power of the therapeutic relationship cannot be underestimated in the creation of patient perceptions and choices.

E&PAS Totally Lacks Evidence as ‘Medical Treatment’

The consequences of E&PAS are unknown as both physicians and patients have no knowledge of what it is like to be dead. Ad- vocates of E&PAS place blind faith in their own assumptions about the nature of death and whether or not there is an afterlife when arguing that euthanasia is beneficial. E&PAS is therefore a philosophical and quasi-religious intervention, not a medical intervention informed by science. Doctors should not offer therapy when they have no idea of its effects—to offer E&PAS is to offer an experimental therapy without any plans for follow-up assessment. Therefore, key elements in any medical intervention such as informed consent are simply not possible without knowing what stands on the other side of death. Rather than a stan- dard medical discussion of alternatives based on scientific data or clinical experience, the discussion must leave the clinical domain and enter the domain of speculation. This is not an exercise in informed-consent. This is not the accepted medical ethics of medi- cal practice. All this is, in part, why E&PAS cannot be a medical procedure.

These Weighty Moral Considerations are Supported by the Ethical Intuition of the Global Medical Community

Only a small minority of physicians sup- port E&PAS. The vast majority of doctors around the world wish only to foster the will to live and to cope with illness and suf- fering, not to facilitate acts of suicide or to create ambiguity around what constitutes a medical treatment. We must remember that the four regional WMA symposia demon- strated that most doctors would never be willing to participate in euthanasia. Even the insistence of E&PAS proponents on (a)

using ambiguous language such as ‘Medical Assistance in Dying’ to describe their prac- tice and (b) avoiding mention of E&PAS on death certificates suggests that they share to some degree this fundamental ethi- cal intuition about killing patients.

Acceptance of E&PAS Undermines Boundaries Between End-Of-Life Care Practices That do not Intend Death (palliative care, withholding/withdrawing life- sustaining therapy) and Those that do Intend Death (E&PAS)

Confusion is created at a societal level about what constitutes “medical treatment,” espe- cially when language such as “medical assis- tance in dying” or “voluntary assisted dying” is used. This renders the reality of such acts and their application unclear. As many pa- tients share our conviction that deliberately causing death is wrong, a misunderstanding of the distinction between E&PAS and pal- liative care may lead to rejection of palliative care or insistence on futile life-sustaining therapies. The availability of E&PAS also distracts from the priority of providing so- cial services and palliative care to those who are sick and dying [7].

The WMA’s Code of Ethics Strongly Influences Standards for the Practice of Medicine Around the World and Neutrality on E&PAS by the WMA Would be Interpreted Globally as Tacit Approval

A change in the WMA statement would imply a tacit endorsement of E&PAS and render the WMA complicit with such prac- tices [8, 9]. Neutrality by professional medi-

36

cal organisations on E&PAS is perceived by society, governments and the international pro-euthanasia lobby as that organisation’s acceptance of them as medical practice, rather than as a response to a societal/po- litical agenda. Those who seek international approval to justify these practices will cre- ate a silencing of the majority of the com- munity, which has real medical, societal and ethical concerns around E&PAS and their effects on society internationally.

WMA policy on E&PAS reflects that which is in place in hundreds of jurisdic- tions with widely divergent legal and politi- cal traditions. While it may be tempting to placate some member societies so as to avoid dissension, we must not destabilize medical ethics around the world. We must continue to characterize E&PAS as unethical even if it conflicts with the demands of the state or influential groups backed by the law. We must not let imperfect law trump good medical ethics. Undoubtedly many doctors who perform E&PAS believe themselves to be acting nobly; but it does not follow that they should expect others to affirm their views or not to oppose them; nor are they wronged by existing WMA policy. Any society that insists on transforming suicide from a freedom to a right, should stand up a different profession with the duty to fulfil that new right, as killing does not belong in the House of Medicine.

Neutrality on E&PAS has Serious Consequences for Physicians who Refuse to Participate

In jurisdictions where E&PAS is legalized, physicians who adhere to the long-standing Hippocratic ethical tradition are suddenly regarded as outliers, as conscientious objec- tors to be tolerated and ultimately excluded from the profession [10]. A neutral stance by the WMA would compromise the po- sition of the many medical practitioners

around the world who believe these prac- tices to be unethical and not part of health care. In some jurisdictions it is illegal not to refer for these practices, creating a dystopic situation where the doctor who practises quality end-of-life care needs to conscien- tiously object in order to do so, and may be coerced to refer for E&PAS. Neutrality from the WMA would promote the con- travention of the rights and ethical practice of these doctors, undermining their ethical medical position at the behest of a societal demand that can fluctuate with time.

In sum, the changes currently being de- bated, arising from political, social, and economic factors, have been rejected time and again and most recently by the over- whelming consensus of WMA regions. The present debate represents a crucially im- portant moment for the WMA that must not be squandered. Given the influence of the WMA and the profound moral issues at stake, neutrality should not be an option. The WMA policy must continue to stand as a beacon of clarity to the world, bringing comfort to patients and support to physi- cians around the globe. The WMA should not be coerced into promoting euthanasia and assisted suicide by making its stance neutral.

References 1. Leiva R, Friessen G, Lau T. Why Euthana-

sia is Unethical and Why We Should Name it as Such. WMJ. 2018 Dec; 64 (4) pages 33-37. [Cited 2019 Feb 05]. https://www.wma.net/wp- content/uploads/2019/01/wmj_4_2018_WEB. pdf

2. WMA INTERNATIONAL CODE OF MEDICAL ETHICS. WMA [Internet] [cited 2019 Feb 05]. https://www.wma.net/policies- post/wma-international-code-of-medical- ethics

3. WMA DECLARATION OF GENEVA. WMA [Internet] [cited 2019 Feb 05]. https:// www.wma.net/policies-post/wma-declaration- of-geneva

4. Zaorsky NG et al. Suicide among cancer pa- tients. Nat Commun. 2019 Jan 14;10 (1):207. [cited 2019 Feb 05]. https://www.nature.com/ articles/s41467-018-08170-1

5. Rodríguez-Prat A et al. Understanding pa- tients’ experiences of the wish to hasten death: an updated and expanded systematic review and meta-ethnography. BMJ Open. 2017 Sep 29;7(9):e016659. [Cited 2019 Feb 05].https://bmjopen.bmj.com/content/7/9/ e016659.long

6. Miller DG, Kim SYH. Euthanasia and physi- cian-assisted suicide not meeting due care cri- teria in the Netherlands: a qualitative review of review committee judgements. BMJ Open. 2017 Oct 25;7(10):e017628. [cited 2019 Feb 05].htt- ps://bmjopen.bmj.com/content/7/10/e017628. long

7. The Canadian Society of Palliative Care Physi- cians -KEY MESSAGES RE HASTENED DEATH [Internet] [cited 2019 Feb 05]. https:// www.cspcp.ca/wp-content/uploads/2015/10/ CSPCP-Key-Messages-FINAL.pdf

8. Sulmasy DP, Finlay I, Fitzgerald F, et al. Phy- sician-assisted suicide: why neutrality by organ- ized medicine is neither neutral nor appropriate. J Gen Intern Med 2018; 33: 1394-1399.

9. Canadian Medical Association softens stand on assisted suicide. Globe and Mail. AUGUST 19, 2014 [Internet] [cited 2019 Feb 05]. https:// www.theglobeandmail.com/news/national/ca- nadian-medical-association-softens-stance-on- assisted-suicide/article20129000/

10. Euthanasia in Canada: A Cautionary Tale. WMJ 2018 Oct; 64 (3), p 17-23. [cited 2019 Feb 05].https://www.wma.net/wp-content/up- loads/2018/10/WMJ_3_2018-1.pdf

(Institutional affiliations are provided for identification purposes only and do not im- ply endorsement by the institutions.)

Ewan C Goligher MD PhD Assistant Professor

Interdepartmental Division of Critical Care Medicine

University of Toronto E-mail: [email protected]

Dr Maria Cigolini MBBS(Syd) FRACGP FAChPM

Grad.DiPallMed(Melb) Clinical Director Palliative Medicine,

Royal Prince Alfred Hospital Senior Clinical Lecturer,

University of Sydney New South Wales, Australia

E-mail: [email protected]

Medical Ethics

37

Alana Cormier MD CCFP Family Physician, Twin Oaks

Memorial Hospital Assistant Professor, Department of Family Medicine, Faculty of Medicine, Dalhousie

University, Nova Scotia, Canada E-mail: [email protected]

Sinéad Donnelly MD, FRCPI, FRACP, FAChPM

Consultant physician Internal Medicine and Palliative Medicine,

Module convenor and Clinical lecturer Palliative Medicine, University Otago,

Wellington, Aotearoa New Zealand E-mail: [email protected]

Catherine Ferrier, MD, CCFP (COE), FCFP

Division of Geriatric Medicine, McGill University Health Centre

Assistant Professor of Family Medicine, McGill University

E-mail: [email protected]

Vladimir A. Gorshkov-Cantacuzène, BChE, MNeuroSci, MD,

DSc(med), TD, JCD

Director, Department of Clinical Cardioneurology, American Institute

of Clinical Psychotherapists E-mail: [email protected]

Sheila Rutledge Harding, MD, MA, FRCPC Hematologist, Saskatchewan Health Authority

Professor, College of Medicine, University of Saskatchewan

Saskatoon SK Canada E-mail: [email protected]

Mark Komrad MD Faculty of Psychiatry Johns Hopkins,

University of Maryland, Tulane Ethics Committee, American

College of Psychiatrists E-mail: [email protected]

Edmond Kyrillos, MD, CCFP, B. Eng. (Mechanical), Lecturer, Department

of Family Medicine, Faculty of Medicine, University of Ottawa

E-mail: [email protected]

Timothy Lau, MD, FRCPC Distinguished Teacher, Associate

Professor, Faculty of Medicine,

Department of Psychiatry, Geriatrics, Royal Ottawa Hospital.

E-mail: [email protected]

Rene Leiva, MD CM, CCFP (Care of the Elderly/ Palliative Care); FCFP

Assistant Professor Department of Family Medicine

Faculty of Medicine University of Ottawa

E-mail: [email protected]

Renata Leong MDcM, MHSc, CCFP, FCFP

Assistant Professor, DFCM, University of Toronto

E-mail: [email protected]

Sephora Tang, MD, FRCPC Staff Psychiatrist, The Ottawa Hospital

Lecturer, Faculty of Medicine, Department of Psychiatry

University of Ottawa E-mail: [email protected]

John Quinlan MB.BS(Syd) FAFRM MA(ethics)

E-mail: [email protected]

Defensive medical practice represents an increasing concern in all over the world. The practice of defensive medicine is main- ly associated to the rising number of medi- cal malpractice lawsuits. It negatively affect the quality of care and waste the limited resources in health sector. The economic burden of defensive medicine on health care systems should provide an essential stimulus for a prompt review of this situ- ation. Defensive medicine in simple words is departing from normal medical practice as a safeguard from litigation. The most

frequent daily practice of defensive medi- cine is performing more unnecessary tests and referring more patients to consultants and hospitalization. Such behavior is an ethically wrong and disagrees with deon- tological duties of the doctor. Investigating the prevalence of defensive medicine in a number of international healthcare set- tings, defensive medicine has been found to be highly prevalent in many countries. Majority of physicians across various spe- cialties tends to adopt a defensive profes- sional culture. Daiva Brogiene

Regional Medical Affairs

The Defensive Medicine isn’t the Best Way to Avoid Mistakes

LITHUANIA

Copyright of World Medical Journal is the property of World Medical Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.

A power analysis is a statistical procedure needed to determine an effective sample size to make a reasonable conclusion.

Power Analyses (Ali & Bhaskar, 206; Polit & Beck, 2017)

Helps to decide how large a sample is needed to make sure judgments about statistical findings are accurate and reliable.

Prevent the recruitment of too many or too few numbers of subjects.

Must be used to determine sample size before the study begins

Chi-Square is powerful for what it is intended to do – determine if variables are associated in any way.

Chi-Square Analysis (Ali & Bhaskar, 206; Polit & Beck, 2017)

Is a type of inferential statistic.

Evaluates if two categorical variables (e.g., gender, educational level, race, etc.) are related (correlated) in any way.

Appropriate for discrete variables (nominal, ordinal).

Does not work with continuous variables (interval, ratio).

The null hypothesis states that there is no relationship between variables. As such, if the null is accepted, you are agreeing that there is no relationship between variables.

Null Hypothesis Testing (Polit & Beck, 2017)

The beginning point for statistical significance testing.

A formal approach to deciding between two interpretations of a statistical relationship in a sample.

Null Hypothesis – suggests there is no relationship between variables, populations, etc. meaning there was an error in sampling.

Alternative Hypothesis – suggests there is a relationship between variables, populations, etc.

Rejecting the Null Hypothesis – suggests being in support of the Alternative Hypothesis.

I want to pick up on your comments specific to type I and type II error and add some thoughts because it is very important to understand these concepts.

First, I can share that sometimes as a researcher, making sense of a type I and type II error can be really challenging! It is important to understand what each is as well as the strategies researchers use to prevent these errors.

In statistics, a null hypothesis is a statement that one seeks to nullify (that is, to conclude is incorrect) with evidence to the contrary. Most commonly, it is presented as a statement that the phenomenon being studied produces no effect or makes no difference. An example of such a null hypothesis might be the statement, "A diet low in carbohydrates has no effect on people's weight." A researcher usually frames a null hypothesis with the intent of rejecting it: that is, intending to run an experiment which produces data that shows that the phenomenon under study does indeed make a difference (in this case, that a diet low in carbohydrates over some specific time frame does, in fact, tend to lower the bodyweight of people who adhere to it)

A type I error(or error of the first kind) is the incorrect rejection of a true null hypothesis. Usually, a type I error leads one to conclude that a supposed effect or relationship exists when in fact it doesn't. Examples of type I errors include a test that shows a patient to have a disease when in fact the patient does not have the disease, a fire alarm going on indicating a fire when in fact there is no fire, or an experiment indicating that medical treatment should cure a disease when in fact it does not. The type I error rate or significance level is the probability of rejecting the null hypothesis given that it is true. It is denoted by the Greek letter α (alpha) and is also called the alpha level. Often, the significance level is set to 0.05 (5%), implying that it is acceptable to have a 5% probability of incorrectly rejecting the null hypothesis.

Type I error is rejecting the null hypothesis when it is true. This is also known as a false positive finding or conclusion.

A type II error(or error of the second kind) is the failure to reject a false null hypothesis. Examples of type II errors would be a blood test failing to detect the disease it was designed to detect, in a patient who really has the disease; a fire breaking out and the fire alarm does not ring, or a clinical trial of a medical treatment failing to show that the treatment works when really it does. The rate of the type II error is denoted by the Greek letter β (beta) and related to the power of a test (which equals 1−β).

A type II error is the failure of rejecting a false null hypothesis. This is also known as a false negative finding or conclusion.

Much of statistical theory revolves around the minimization of one or both of these errors, though the complete elimination of either is treated as a statistical impossibility.

sampling.

One of the things that are significant to consider is the use of a sample and sampling error. We all generally understand that a sample, be it randomized or a convenience method, is intended to represent a certain population. Inferences about sample statistics (such as a mean and standard deviation) are used to approximate population parameters. Martin and Bridgmon (2012) posit it is highly unlikely that sample statistics will be exactly the same as population parameters and the difference that emerges is what is referred to as sampling error.

It is important to remember as you move forward in your doctoral program, that the use of random sampling is thought to be the best way to reduce sampling error (Martin & Bridgmon, 2012; Tappen, 2016: Treiman, 2009). However, Shadish et al. (2002) have previously discussed that an alternative selection method to random selection used by experimental researchers is known as purposive sampling. This is an intentional process by a researcher to identify population characteristics, including participants, treatments, outcomes, and settings, and then select a sample that most closely embodies the desired population characteristics. However, I encourage you to carefully consider that random error can occasionally include fluctuations in the characteristics of individuals, such as the motivation level of novice nurses changing rapidly from one intervention to the next. So the timing, or rather, the length of study involving the participants, must always be key part of the methodology design.

Thank you for your post this week that includes an important dialogue about the null hypothesis. As pointed out by MacKenzie et al. (2018), hypothesis testing leads to a dichotomous decision; one either rejects the null hypothesis or not. They also argue the decision by the researcher (to reject or not) can be either right or wrong with respect to the truth. However, it is important to gently remember that a hypothesis can never be “proven” to be correct. I have heard my previous doctoral students describe their findings in this way and this description is inaccurate. We should always be mindful that no amount of experimental testing or evidence can truly prove anything in science (McLaughlin, 2006). Rather, it is important to note that if a research scientist’s results match his/her prediction, then the hypothesis is supported.

The language we use to describe possible problems with a hypothesis is also key. The nomenclature for the errors that can occur, such as Type 1 or Type 2, depend upon the decision of whether to reject the null hypothesis. Other considerations involve the p value and its role in determining to accept or reject the null hypothesis. There are some key factors to remember from the lesson this week on the p value (Taylor, 2019). These include:

With most analyses, an alpha of 0.05 is used as the cutoff for statistical significance;

If the p-value is less than 0.05, we reject the null hypothesis that there is no difference between the means and conclude that a significant difference does exist;

If the p-value is larger than 0.05, we cannot conclude that a significant difference exists;

The p-value is also known as the calculated probability; and

The p-value is commonly referred to as the alpha.

If the null hypothesis is not true, then the effect size will be greater than zero;

The larger the effect size, the greater the degree to which the phenomenon (e.g., the outcome of an intervention study) will be manifested; and

The larger the effect size is, the greater the power will be, so a smaller sample will be needed to detect the phenomenon and reject the null hypothesis (Cohen, 1988) [as cited by Tappen, 2016, p. 128].

I also took particular note of your comments about whether you would utilize the research study with regard to the suggested error. You explained that there are still too many gray areas to feel a comfortable in considering this particular research. I can see certainly see your point about this but want to offer that one of the potential opportunities is for the study to be repeated by other researchers, making note of the contributing factors which contributed to the original sample error. One of the challenges with the case study this week is that the generalizability of the results cannot be considered until the sample error is resolved. Thank you and take care.

the Chi-square test of independence (also known as the Pearson Chi-square test, or simply the Chi square) is one of the most useful statistics for testing hypotheses when the variables are nominal, as often happens in clinical research (McHugh, 2013). Chi Square is used to examine the difference between what you actually find in your study (or DNP Project) and what you are expecting to find. So, there are key questions which should be asked to determine if this test is appropriate for your upcoming DNP Project which include:

Are you trying to see if there is a difference between what you have found and what would be found in a random pattern?

Is the data gathered organized into a set of categories?

In each category, is the data displayed as frequencies (not percentages)?

Does the total amount of data collected (observed data) add up to more than 20?

Does the expected data for each category exceed four?

If any of the answers are no to these questions, then is not the correct test to use. Thanks Angela, and I hope this information is helpful. Take care.

Kindly,

Dr. Kyzar

Reference

McHugh, M.L. (2013). The chi-square test of independence. Biochemia Medica, 23(2), 143-149. http://dx.doi.org/10.11613/bm.2013.018 (Links to an external site.)

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Collapse SubdiscussionKate Blue

Kate Blue

WednesdayJan 27 at 4:56pm

Dr. Kyzar and class,

What statistical procedure is needed to determine an effective sample size to make a reasonable conclusion? Explain your rationale.

When determining the appropriate sample size, the general rule of the have the largest sample size possible is best. This allows for the best representation of the population. Utilizing the power analysis tool helps prevent type II errors or false negatives. In conducting this test, the validity of the conclusion is stronger (Polit, 2016).

Reading through the study, you observe that the researcher used a chi-square analysis to analyze nominal and ordinal data. Is this the appropriate level of statistical analysis to answer the research question? Explain your rationale.

Chi-square analysis determines the differences in variables and is used to test the hypothesis. It can be utilized in both nominal and ordinal data (Chamberlain College of Nursing, 2020). The observed frequencies of outcome following intervention are compared to the expected frequencies of outcome following not intervention. Through calculations, a 0.05 significance is determined. Then the Chi-square value and significance value are compared leading to the p-value, which determines statistical significance. In most nursing research, a value of 0.05 or less is considered to be statistically significant (Polit, 2016).

Reading further, the researcher reports that the p-level led her to conclude that the null hypothesis was rejected. In your critique of the study, you determine that the null hypothesis is true. Do these findings impact your decision about whether to use this evidence to inform practice change? Why or why not?

When the p level is greater than 0.05 it is determined to be not statistically significant. It means more than five out of one hundred times of completing a similar size study the results would show probability of the control versus intervention groups being different by likelihood. If the DNP scholar found a p level less than 0.05 it would be considered statistically significant and support the null hypothesis (Polit, 2016).

When a researcher rejects a null hypothesis that is true a type 1 error occurs. When the criteria for type 1 is very tight there is a higher chance for type 2 errors. To avoid type 2 errors the researcher wants to have a larger sample size. This would change the DNP scholar’s choice to utilize in practicum. When there is an error it may be related to inadequate sample size, poor statistical processes, inaccurate measures, or errors in the study method (Polit, 2016). Therefore, the level of evidence would be poor leading to a non-acceptable study for implementing practice change.

References

Chamberlain College of Nursing. (2020). NR 714 Week 4: Data Analysis [Online lesson]. Adtalem Global Education.

Polit, D. F. (2016). Nursing research: Generating and assessing evidence for nursing practice (10th ed.). Wolters Kluwer Health.

Excellent comments to this week’s post! You have provided a highly competent discussion of the Week 4 questions and I took particular note of your points about the Chi Square Analysis. Since this is one of the main focuses of our study this week, I want to summarize some very important key points about this important test. Below are a list of advantages and disadvantages that students should remember.

Advantages

Noted for its robustness with respect to distribution of the data and ease of computation;

The detail of information which can be derived from the test;

It use in studies when certain parametric assumptions cannot be met;

Its flexibility in handling data from both two groups and multiple group studies;

Can be used to test the difference between an actual sample (actual data) or observed, and hypothetical expectations (expected outcome/values from a hypothesis);

Can test association between variables;

Used to test the difference between what you expect to find from an experiment, and what you actually find from an experiment; and

Examines the differences in data between categories.

Disadvantages

Can be used on raw data that is counted (BUT cannot be used for measurements, proportions, or percentages);

Data must be numerical;

Categories of two are not good to compare;

The number of observations must be 20+;

The test becomes invalid if any of the expected values are below 5; and

A type of nonparametric statistics and is not as powerful as other types of statistical methods.

Thanks so much and I hope this information greatly adds to your knowledge this week about this important test.

Kindly,

. Additionally an estimate of a sample size is used to avoid a type 2 error which happens when the null hypothesis is accepted when it should be rejected (Polit & Beck, 2017, p 402).

These comments are at the heart of a power analysis, which is a method of estimating that the sample is large enough to assume that your statistical analysis is meaningful and large enough to detect errors. An underpowered quantitative study typically has too few subjects or an insensitive measure of change (or both), leading to an increased risk of type 2 errors. The effect size is another important estimate of power and is the estimated magnitude of the phenomenon under study (Tappen, 2016, p. 127). Consider then, that if the null hypothesis is true, the effect size will be zero; however, most researchers anticipate a real effect in most of their studies. Thus, it is important for the researcher to actually conduct a real calculation of the sample population which will be needed.

I can share that there are some very useful software packages that can calculate power for you (many are free on the internet), but some of these may be limited by the number of designs that can be inputted into the calculation in question (Creswell & Creswell, 2017). Ultimately, the best advice for doctoral students and novice researchers is to use as large of a sample as possible to maximize the possibility that the means, percentages, and other statistics are the true estimates of the population (Wood & Ross-Kerr, 2011, p. 129

Please click on the link below and read the brief discussion. Knowing the content this week may be a bit challenging, does the illustration help solidify your understanding of rejecting the null hypothesis (meaning a difference exists) or failing to reject the null (meaning no difference was found)?

Best Regards,

Dr. Kyzar

https://www.statisticssolutions.com/to-err-is-human-what-are-type-i-and-ii-errors/ (Links to an external site.)

Rejecting the Null Hypothesis--Week 4.jpg

ReplyReply to Comment

Collapse SubdiscussionCarlos Legra Elias

Carlos Legra Elias

SaturdayJan 30 at 12:55pm

Hi Dr Kyzar

Excellent to know how rejecting and failing to reject null hypothesis The illustration explains the concept of Type I and Type II error that can result from rejecting and failing to reject the null hypothesis (Davis, 2020). Type I error occurs when a true null hypothesis is rejected. Type II error on the side occurs when we fail to reject a false hypothesis. The rejection region as illustrated depends on the significant level provided. A significant level of α = 0.05 is commonly used in many research studies. However, other significant levels such as α = 0.01 and α = 0.10 can also be used depending on the requirement and type of the study. Using one of the significant levels affects the decisions made on the null hypothesis. A calculated p-value can be statistically significant when α = 0.10 but fails to be significant when the significant level is changed to α = 0.05.

This study helps in illustration of hypotheses testing during data analysis. This is one of the most vital part that can lead to decision making using the provided data. It is clear from the given illustration that decisions made have a great impact and the type of error committed can be costly depending on the study at hand. This explains the importance of keenness when handling hypotheses.

Therefore, the article solidifies the understanding of rejecting the null hypothesis and failing to reject the null hypothesis. It helps in understanding how irrelevant a decision can be when either of the errors is made.

Reference

Davis, I. (2020, March 4). To Err is Human: What are Type I and II Errors? Retrieved January 30, 2021, from https://www.statisticssolutions.com/to-err-is-human-what-are-type-i-and-ii-errors/ (Links to an external site.)

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Collapse SubdiscussionJannet Patton

Jannet Patton

SaturdayJan 30 at 8:34pm

Greetings, Dr. Kyzar and Class,

Thank you for providing the additional resources and questions this week to further our understanding of Type I and Type II errors. I especially appreciated the article from Statistics Solutions and the illustration about holding versus looking at puppies to demonstrate the difference between a Type I and Type II error. For example, if a researcher rejects a true null hypothesis, this would be a Type I error-also known as a false-positive. If the researcher fails to reject a false null hypothesis, this would be considered a false-negative result (McLeod, 2019). Type I errors can cause unnecessary problems when making healthcare changes, and Type II errors can prevent needed interventions (McLeod, 2019). I have attached a visual chart that demonstrates the conclusion from statistical analysis, based on whether the results yielded a Type I error or Type II error (McLeod, 2019).

Jan

Reference

McLeod, S. A. (2019). What are type I and type II errors? Simple Psychology. https://www.simplypsychology.org/type_I_and_type_II_errors.html (Links to an external site.)

McLeod_Chart.docx

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Collapse SubdiscussionRacheal Aneke

Racheal Aneke

WednesdayJan 27 at 9:19pm

NR 714 week 4 discussion

What statistical procedure is needed to determine an effective sample size to make a reasonable conclusion? Explain your rationale.

To determine if the sample size is adequate to make a reasonable decision depends on the descriptive statistics applied in the study like mode, median, and mean. Mode occurs with the most significant mathematical values frequency and measures the nominal data in a central tendency. The median score is at the 50th percentile or center of the frequency or distribution. It is the correct measurement of the ordinal data. Mean is the sum of the total score divided; it measures the interval and ratio. Another statistical method to decide a sample size includes the range, variance, and standard deviation. Chi-test is also a statistical procedure that is needed to determine sample size (Chamberlain College of Nursing. (2021). Facts remain that there might be enough participants in a research study and statistical methods to select the sample size. The sample size in quantitative research studies is sometimes invariable, numerical at the beginning of the study, or the end as a narrative (Gray & Grove, 2021). One numerical technique does not decide a sample size in a study.

Reading through the study, you observe that the researcher used chi-square analysis to analyze nominal and ordinal data. Is this the appropriate level of statistical analysis to answer the research question? Explain your rationale.

The Chi-square test is the statistical procedure that describes the different variables in a research study, such as if they are dependent or independent variables. It determines the descriptive measurements and can use nominal or ordinal data, but not for causalities. Since this is the case, the Chi-square analysis is acceptable to use to answer the research question. Chi-square results are not significant if there is no difference in the outcome, but the researcher using chi-square implement numerous samples (Chamberlain College of Nursing, 2021). But if the product is positive, it is applied. My research question can be answered with chi-square because it assesses the mentally ill in a crowded environment.

Reading further, the researcher reports that the p-level led her to conclude that the null hypothesis was rejected. In your critique of the study, you determine that the null hypothesis is true. Do these findings impact your decision about whether to use this evidence to inform practice change? Why or why not?

Type II error regarding null hypotheses occurs because of mistakes in the research methods, but they are false positives. Type II error risk is decided using power analysis. Power analysis includes the level of significance, sample size, power, and effect size as parameters (Polit & Beck, 2017). As long as the minimum power level is obtained for the study, the validity is more robust, and the study is less questionable. Based on the fact that if a research null hypothesis is rejected, the power level analysis is reported to question the study's outcome validity, I would not change my decision to use it as evidence to inform practice change.

References

Chamberlain College of Nursing. (2021). NR-714 week 3: Summaries of multiple Research studies Address the Systematic Review.[Online lesson]. Adtalem Global Education.

Gray, J., & Grove, S. K. (2021). Burns and Grove's the practice of nursing research: appraisal, synthesis, and generation of evidence. Elsevier.

Polit, D. F., & Beck, C. T. (Eds.). (2017). Nursing research: Generating and assessing

evidence for nursing practice (10th ed.). Wolters Kluwer. 

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Collapse SubdiscussionTheresa Kyzar

Theresa Kyzar

FridayJan 29 at 6:17pm

Hi Racheal:

Thank you for your practical commentary to the Week 4 discussion. I noted the macro-level perspective you provided as part of a general overview of statistical methods and the chi square test. However, I want you to take a deeper dive with me because it is important to really grasp the concepts associated with parametric and non-parametric testing. Remember that you will likely be required during your defense presentation of your DNP project to discuss your data analysis to demonstrate mastery of the statistical tests you utilized to measure the outcomes of your change project. It will be exciting, I promise!

So, let’s talk about this more at the doctoral level now so you will be able to explain it during your final DNP Project presentation. As you have learned from your assigned chapter readings this week, the Chi-square test is a non-parametric statistic, also called a distribution free test (Polit & Beck, 2017). From this important information, you (and your fellow student peers) have learned that non-parametric tests should be used when any one of the following conditions pertains to the data:

The level of measurement of all the variables is nominal or ordinal.

The sample sizes of the study groups are unequal; for the χ2 the groups may be of equal size or unequal size whereas some parametric tests require groups of equal or approximately equal size.

The original data were measured at an interval or ratio level, but violate one of the following assumptions of a parametric test:

The distribution of the data was seriously skewed or kurtotic (parametric tests assume approximately normal distribution of the dependent variable), and thus the researcher must use a distribution free statistic rather than a parametric statistic.

The data violate the assumptions of equal variance or homoscedasticity.

For any of a number of reasons, the continuous data were collapsed into a small number of categories, and thus the data are no longer interval or ratio (McHugh, 2013).

Sometimes the term, homoscedasticity, scares students, but really it shouldn’t. It just means “having the same scatter”. As an example, we want our data results from the participant responses to a questionnaire used as part of a DNP project or research study to be scattered evenly on a plot graph. This is very important if I am trying to compare the responses between two groups who participated (such as physician responses vs nurse responses). However, both groups need to be the same sample size or interpretation of the data, especially for comparison, could be compromised. Does that make sense? Look at the example below:

Homoscedasticity Example.jpg

What about Groups B & C? Is it the same, meaning, evenly scattered? The answer is no, likely because the two groups in the project were not the same sample size (say as an example, 10 nurse and 6 physician participants). So, I cannot say determine an association in the data (among participant responses) and that is a problem. This is where the important use of non-parametric testing comes into play and I will likely need to use a chi square test analysis. The exciting aspect of this particular test is its flexibility in handling data from both two groups and multiple group studies and I can then delve into a possible association between the two sample groups.

Does this information help to better explain how nonparametric testing, including a chi square test can support your upcoming DNP project data analysis? Let me know your thoughts. Thanks!

Kindly,

Dr. Kyzar

References

McHugh, M.L. (2013). The chi-square test of independence. Biochemia Medica, 23(2), 143-149. http://dx.doi.org/10.11613/bm.2013.018 (Links to an external site.)

Ogee, A., Ellis, M., Scibilia, B., & Pammer, C. (2021). Homoscedasticity? Don't be a victim of statistical hippopotomonstrosesquipedaliophobia. https://blog.minitab.com/blog/statistics-and-quality-data-analysis/dont-be-a-victim-of-statistical-hippopotomonstrosesquipedaliophobia (Links to an external site.)

Polit, D. F., & Beck, C. T. (2017). Nursing research: Generating and assessing evidence for nursing practice (10th ed.). Wolters Kluwer.

, R. (2016). Advanced nursing research: From theory to practice (2nd ed). Jones & Bartlett.

Edited by Theresa Kyzar on Jan 29 at 6:21pm

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Collapse SubdiscussionRacheal Aneke

Racheal Aneke

SundayJan 31 at 8:36am

Dr. Kyzar,

Thank you so much for those in-depth explanations on how to solve homoscedasticity problems with non-parametric testing like chi-square.

Yes, it was and will be more helpful on this DNP Journey.

I appreciate your support,

Racheal Aneke

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Collapse SubdiscussionKimberly Austin

Kimberly Austin

ThursdayJan 28 at 5:36pm

As a practice scholar, you are searching for evidence to translate into practice. In your review of evidence, you locate a quantitative descriptive research study as possible evidence to support a practice change. You notice the sample of this study includes 200 participants and is not normally distributed. Reflect upon this scenario to address the following.

What statistical procedure is needed to determine an effective sample size to make a reasonable conclusion? Explain your rationale.

Research typically relies on samples for their data. Because of the importance of the accuracy of data collected, researchers must carefully choose their samples. Samples should allow the researchers to draw conclusions with good validity and pertain beyond the sample used (Polit & Beck, 2017).

A sampling plan identifies how subjects are selected and how many subjects should be used for the research. In the first step, researchers should clearly identify the criteria that defines who is in the population, and if it represents all types of individuals and diversity for similarly occurring circumstances. This eligible criteria composes the inclusion or exclusion criteria needed for the study. Additional considerations should include costs, constraints, individual ability to participate, and design considerations (Polit & Beck, 2017).

The statistical procedure needed to determine an effective sample size is power analysis. Power analysis is best used with larger sample groups to decrease the likelihood of achieving a deviant sample (Polit & Beck, 2017). In the scenario above, the study includes 200 participants therefore power analysis would be best for this quantitative study as this sample will have an increased likelihood of being representative, however the large sample does not guarantee this (Polit & Beck, 2017).

Reading through the study, you observe that the researcher used a chi-square analysis to analyze nominal and ordinal data. Is this the appropriate level of statistical analysis to answer the research question? Explain your rationale.

The Chi-Square Test determines if two variables are independent or related. This case is typically used with nominal or ordinal data, and results used when the analysis shows a difference (Chamberlain, 2020).

According to McHugh (2013) the Chi-square test is a non-parametric statistic, or distribution free, test, therefore is appropriate for use in the study reviewed above.

Reading further, the researcher reports that the p-level led her to conclude that the null hypothesis was rejected. In your critique of the study, you determine that the null hypothesis is true. Do these findings impact your decision about whether to use this evidence to inform practice change? Why or why not?

Polit and Beck (2017) explain that hypothesis testing is based on negative inference. When differences occur from random factors, it is known as the null hypothesis. When this occurs, care must be taken to not jump to quickly on how to use these results. When deciding to accept or reject a null hypothesis, researchers, must determine how probable that chance was the factor causing the results. Rejecting a true hypothesis, or accepting a false hypothesis are two types of statistical errors researchers can make, known as Type I and Type II errors (Polit & Beck, 2017).

In the scenario above, the researcher concluded the null hypothesis was rejected, however upon my further review, the null hypothesis is true, therefore the researcher made a Type I error; and I would use these findings to support the practice change.

References

Chamberlain College of Nursing. (2020). NR 714 Week 4: Data Analysis [Online lesson]. Adtalem Global Education.

McHugh M. L. (2013). The chi-square test of independence. Biochemia medica, 23(2), 143–149. https://doi.org/10.11613/bm.2013.018

Polit, D. F., & Beck, C. T. (2017). Nursing research: Generating and assessing evidence for nursing practice (10th ed.). Wolters Kluwer Health.

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Collapse SubdiscussionKayla Jones

Kayla Jones

SundayJan 31 at 12:10pm

Hi Kimberly,

Thank you for further explanation in simplest terms for this week’s discussion! Dreaded by statistics, it has been insightful to review the readings in detail along with reading everyone’s posts! While many of us may not communicate the statistical terminology in talking to others, it is used in our everyday life. Hypotheses are basically our guesses of why and how events are occurring. In many instances, our guesses are inspired by our beliefs and experiences (Kaur, 2017). However, in research the hypothesis is the relationship between the independent and dependent variable. The independent variable is the cause with the dependent variable being the effect. Hypotheses play a different role in qualitative and quantitative research. Quantitative research stimulates critical thinking, engaging the researcher to interpret the data. Qualitative research usually does not include the hypothesis in the early stages because observation and detailed interviews/inquiries are the driving forces to justify the hypothesis (Kaur, 2017). Concluding the research, a significance level is established to test the hypothesis in which can further determine the reliability. In agreement with you, it is my belief that it would be safe to implement the change.

Reference

Kaur, S. P. (2017). Writing the hypothesis in research. International Journal of Nursing Education, 9(3), 122-125. https://doi:10.5958/0974-9357.2017.00081.2Links to an external site.

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Collapse SubdiscussionTheresa Kyzar

Theresa Kyzar

SundayJan 31 at 6:26pm

Hi Kim,

Thank you for your contribution to the week 4 discussion!

A key point to remember from this discussion relates to power analysis. Please allow me to build on your post.

A power analysis is a statistical procedure needed to determine an effective sample size to make a reasonable conclusion. Researchers conduct a power analysis before recruiting human subjects into their quantitative research study. In each published quantitative study, the research team will state a power analysis as well as report what it was a priori.

Power Analyses (Ali & Bhaskar, 2016; Polit & Beck, 2021)

Help decide how large a sample is needed to make sure judgments about statistical findings are accurate and reliable.

Prevent the recruitment of too many or too few numbers of subjects.

The cut-off for a power analysis is 0.80.

Must be used to determine sample size beforethe study begins

Thank you and take care.

Kindly,

Dr. Kyzar

References

Ali, Z., & Bhaskar, S. B. (2016). Basic statistical tools in research and data analysis. Indian Journal of Anesthesia, 60(9), 662–669. doi:10.4103/0019- 5049.190623. Retrieved https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5037948/ (Links to an external site.).

Polit, D.F. & Beck, C. T. (2021). Nursing research: Generating and assessing evidence for nursing practice (11th ed). Wolters Kluwer.

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Collapse SubdiscussionCarlene Yearwood

Carlene Yearwood

ThursdayJan 28 at 8:49pm

Dr. Kyzar and class,

With regards to the sample size of 200 participants and not normally distributed, the statistical procedure needed to determine an effective sample size for a reasonable conclusion is the P value or alpha level, power analysis, effect and alternative hypothesis. Sample size is a critical step in the design of a well - planned research protocol (Polit & Beck, 2017). P values states whether an observation is as a result of a change made or random occurrences. In order to accept the result there must be a low - p value. Studies must have an adequate sample size, relative to the goals and variabilities of the study (Suresh, et, al. 2012).

Chi- square analysis is used to analyze nominal and ordinal data. The chi- square test analysis is one of the most useful statistics for testing hypotheses when the variables are nominal in clinical research (Mc Hugh, 2013). This is the appropriate level of statistical analysis to answer the research question since chi- square can provide information not only on the significance of any observed differences, but also provides detailed information on exactly which categories account for any differences found. The amount and detail of information this statistical analysis can provide makes it one of the most useful tools available to researchers for analysis ( Mc Hugh, 2013).

Depending on the p - value, a low p - value means the sample result would be unlikely if the hypothesis were true and leads to the rejection of the null hypothesis. In null hypothesis testing the criterion is called a (alpha) and is almost set to .05. If there is enough evidence to conclude that the null hypothesis is true, I will use the evidence to inform practice change. Researchers can only conclude that hypotheses are probably true or false and there is always a risk for error ( Polit & Beck, 2017). Researchers can make a Type 1 error by rejecting a null hypothesis that is true.

References

Mc Hugh, M., L. ( 2013). The Chi - square test of independence. Biochemia Medica, 23 ( 2), 143 - 149.

Polit, D.F. & Beck, C. T. (2017). Nursing research: Generating and assessing evidence for nursing practice (10th ed.). Wolters Kluwer.

Suresh, K. P. & Chandrashekara, S. (2012). Sample size estimation and power analysis for clinical research studies. Journal of Human Reproductive Sciences, 5 ( 1), 7 - 13.

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Collapse SubdiscussionEjiro Ohonbamu

Ejiro Ohonbamu

SundayJan 31 at 7:25pm

Carlene thanks for your post. In other to get a better understanding, of the p-value. You stated that the researchers can make a Type 1 error by rejecting a null hypothesis which is true. The null hypothesis in many types of research is typically not voiced, but in this case, it is. Now to determine the obvious that the null was actually true. The null hypothesis is truthfully based on statistical errors that precede further investigation. Prior to any conclusion, do you not think that what led to the initial rejection must be investigated? Will you be using the evidence for the rejection to inform the practice change? I am thinking that the evidence that led to the rejection, is the same evidence that has led to the truth. The higher the level of significance, the more extreme, nature of the risk of a Type I error diminishes (Polit & Beck, 2017). Thanks for your post.

References

Polit, D. F., & Beck, C. T. (Eds.). (2017). Nursing research: Generating and assessing

evidence for nursing practice (10th ed.). Wolters Kluwer. 

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Collapse SubdiscussionTheresa Kyzar

Theresa Kyzar

ThursdayJan 28 at 10:01pm

Week 4 Class Question

Students:

What is a normal distribution and what does it look like? Why is the normal distribution important in statistics?

I look forward to your responses. Thank you!

Dr. Kyzar

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Collapse SubdiscussionAngela Wilson

Angela Wilson

FridayJan 29 at 2:30pm

Dr. Kyzar and class,

A normal distribution looks like a bell curve. The normal distribution is used in statistics to describe how the variables are distributed in the research study. This is especially significant in evaluating whether the values from the variables are reliable and significant to the research question. Understanding the normal distribution can assist with the evaluation of whether the study is worth translating into practice. The bell curve can show the normal, medium, and mean of the statistical data gathered from the study. Averages can be calculated as well. The bell curve also shows a relationship between the results of the interventions in a study. For example, the tails of the distribution should be equal to the peak in the distribution to determine that both variables are just as likely as the next. This is extremely useful in deciding if the results from the study meet the specifics of the practice setting seeking evidence based practice improvements.

Angie

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Collapse SubdiscussionKimberly Austin

Kimberly Austin

SundayJan 31 at 12:30pm

Angie,

In your post, you mention "the bell curve also shows a relationship between results of the interventions in a study". As I picture this, what comes to mind is something very different than what I used to picture when interpreting data. Since the last time I took a statistics class, our world has changed; and looking at a "curve" or the phrase, "flattening the curve" has become much more well-known since the beginning of the Covid-19 pandemic. Identifying the relationship between results of the interventions has taken on great importance to more than just scientists and scholars as the world tries to understand what is happening with the spread of the Covid-19 virus. In an interesting twist, seeing normal distribution exampled in relationship to Covid-19 has helped me better understand a concept I have struggled with in the past. I appreciate your post in further clarifying the usefulness in determining how results can be applied to practice improvements.

Kim

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Collapse SubdiscussionKate Blue

Kate Blue

SaturdayJan 30 at 11:22am

Dr. Kyzar and class,

What is a normal distribution and what does it look like? Why is the normal distribution important in statistics?

Normal distribution is also called bell-shaped curve distribution. The sampling distribution presents a wave curve that is symmetrical. When sample sizes are large the data tends to result in a normal distribution. When normal distribution of the study sample is achieved, it will always be equal to the general population. Looking at the standard deviations of the data helps tell the accuracy of the sample. With a normal distribution pattern, sixty-eight percent of the data is included within one standard deviation to the left and right. Therefore, the accuracy of data in a normal distribution is high (Polit, 2016). A DNP scholar would put a higher preference on a study's data that resulted in normal distribution due to the accuracy of sampling reflecting the normal population.

Reference

Polit, D. F. (2016). Nursing research: Generating and assessing evidence for nursing practice (10th ed.). Wolters Kluwer Health.

Kate Blue

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Collapse SubdiscussionCarlos Legra Elias

Carlos Legra Elias

SaturdayJan 30 at 12:48pm

Hello Dr Kyzar and Class

Normal distribution can also be referred as a Gaussian distribution which is a distribution of possibility that happens to be symmetric in relation to the mean, which is an indication that any data found close to the mean tend have an occurrence that is more frequent in comparison to data that is not close to the mean. When it is illustrated in a graph, it assumes the shape of a bell. The distribution that is normal has various properties that are interesting which include; has equal median as well as mean, has a bell shape in addition to having a 68% of its data falling within the deviation of 1 standard (Jabbari Nooghabi, 2020).

The deviation that is standard is the one in that is in control of the distribution's spread. A standard deviation that is smaller is an indication that the data is clustered closely around the given mean, while normal distribution will end up being taller. Standard deviation that is taller shows that the spreading of the data is sparse near the mean hence the normal distribution tends to be wider and flatter. Has at the center is basically symmetric, 50% of the values tend to be at the left side of the center and 50% of the values are situated at the right. The general region under the cover basically is one and a normal model standard.

The importance of the normal distribution within statistics is mainly because of its capability of being in a position to fit many phenomena that are natural. For example, measurement error, heights, scores related to IQ in addition to blood pressure are done as per the distribution that is natural (Kim, et.al, 2020).

References

Jabbari Nooghabi, M. (2020). Process capability indices in normal distribution with the presence of outliers. Journal of Applied Statistics, 47(13-15), 2443-2478.

Kim, C., Cho, S., Sunwoo, M., Resende, P., Bradaï, B., & Jo, K. (2020). A Geodetic Normal Distribution Map for Long-term LiDAR Localization on Earth. IEEE Access.

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Collapse SubdiscussionCarlene Yearwood

Carlene Yearwood

SaturdayJan 30 at 4:31pm

Dr. Kyzar and class,

A normal distribution is a continuous probability distribution that is symmetrical on both sides of the mean, so the right side of the center is a mirror image of the left. The area under the normal distribution curve represents probability and the total area under the curve sums to one. Most of the continuous data values in a normal distribution tend to cluster around the mean, and the further a value is from the mean, the less likely it is to occur. For a perfect normal distribution the mean, median and mode are measures of central distribution of numerical values important for any research findings. The normal distribution is often called the bell curve because the graph of its probability density looks like a bell.

The normal distribution is the most important probability distribution in statistics because many continuous data in nature and psychology displays this bell - shaped curve when compiled and graphed for evidence. A normal distribution frequency curve can be used to measure continuous variables, such as IQ, height, weight and blood pressure. As a DNP scholar a normal distribution is an important factor to consider towards the contribution of accurate results for a practice change.

Reference

McLeod, S. A. (2019). Introduction to the normal distribution ( bell curve). Simply psychology: https://www.simplypsychology.org/normal-distribution.html

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Collapse SubdiscussionYosvani Garcia Boss

Yosvani Garcia Boss

SaturdayJan 30 at 9pm

Hello Dr. Kyzar,

Normal distribution which is also referred to as Gaussian distribution, is basically a distribution of probability considered to be symmetric in relation to the mean, which indicates that the data that is close to the mean tend to be more frequent within their occurrence as compared to the data that happens to be far as from the mean. When in a graph form, the normal distribution appears to be in the form of a bell curve. The distribution is said to be an appropriate term in relation to a bell curve of probability. Within a distribution that is normal, mean happens to be zero while the standard deviation ends up being one. This means its skew is zero while the kurtosis is three. These types of distributions happen to be symmetrical though it is not possible to say that every distribution that is symmetrical is normal (Martínez-Flórez, et.al, 2020).

Distributions considered to be normal tend to have a regular appearance in relation to statistics, in addition, they are known to have some properties that are interesting which include having the shape of a bell, has a median as well as a means that are equivalent in addition to a data falls of 68% within a standard deviation of 1. However, in reality, most distributions for pricing can not be said to be normal perfectly. The model of this distribution tends to be motivated by the theorem of Central limit. It is a thesis stating that the calculated averages from the variables that are independent as well as identically distributed randomly tend to have distributions that are approximately normal, despite of the form of distribution where the variables get to be sampled from as long as it has a variance that is finite (Mirfarah, et.al, 2021).

A times the normal distribution tends to be confused with the distribution that is symmetrical. The symmetrical distribution involves having the dividing line producing two images mirroring each other, however, the real data might be in form of humps that are two or a sequence of hills as well as the bell curve indicating a distribution that is normal.

The main reason as to why normal distribution is of great significance within statistics is due to the fact that it fits into many phenomena that are natural. For instance, blood pressure, heights, scores of IQ in addition to measurement error adhere to the distribution that is normal. The distribution that is normal is a function of probability used in describing the manner in which a variable value gets to be distributed. It is known as a distribution that is symmetric whereby most of the given observation tends to cluster all over the peak that is central in addition to the possibilities for values that are at a far distance from the taper off of the mean equally within the two directions. Values that are extreme within the two distribution tails tend to be similarly not likely (Lee and McLachlan, 2020)

The statistical tests that are most powerful by the name parametric which tend to be utilized by the psychologists need the data to be distributed normally. In case the data is not in resemblance with a curve in the bell shape, researchers might be forced into using a type that is considered to be less powerful in relation to the statistical test, which is referred to as statistics that are non-parametric.

References

Lee, S. X., & McLachlan, G. J. (2020). On mean and/or variance mixtures of normal distributions. arXiv preprint arXiv:2005.06883. Retrieved from https://arxiv.org/abs/2005.06883 (Links to an external site.)

Martínez-Flórez, G., Leiva, V., Gómez-Déniz, E., & Marchant, C. (2020). A family of skew-normal distributions for modeling proportions and rates with zeros/ones excess. Symmetry, 12(9), 1439. Retrieved from https://www.mdpi.com/2073-8994/12/9/1439 (Links to an external site.)

Mirfarah, E., Naderi, M., & Chen, D. G. (2021). Mixture of linear experts model for censored data: A novel approach with scale-mixture of normal distributions. Computational Statistics & Data Analysis, 107182. Retrieved from https://www.sciencedirect.com/science/article/pii/S0167947321000165 (Links to an external site.)

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Collapse SubdiscussionTheresa Kyzar

Theresa Kyzar

SundayJan 31 at 6:25pm

Hi Yosvani:

Thank you for your thoughtful response. Excellent! I really appreciated the insight you provided about the main reasons that the normal distribution is very significant in statistics and I strongly agree with these points.

Please allow me to add to your comments.

With a normal distribution, you should expect to observe approximately 68% of values within one standard deviation; about 95% of the values within two standard deviations; and about 99.7% are within three standard deviations. This is referred to as the 68 95 99.7 rule or Empirical Rule (Statistics How To, 2019). Exactly half the data is to the left as well as the right side of the mean. To visualize this, with x being the horizontal plane of the graph showing the data value scale and y being the vertical plane showing the frequency scale (Vetter, 2017). An example could be a group of individuals who are participating in a weight loss program. The x would be the weights with the distribution ranging from 150 lbs. to 350 lbs. The frequency would be how often each weight was recorded. In a normal distribution, 250 lbs. would be the mean and median with a bell shape. I think sometimes that students who are still novices with these kind of experiences struggle with how to set up their equations to properly understand the significance of the process involved with normal distribution. Your own thoughts about the importance of this and how non-parametric testing comes into play add meaning to this discussion.

Thank you and take care.

Kindly,

Dr. Kyzar

References

Statistics How To. (2019). What is the 68 95 99.7 rule? Retrieved from https://www.statisticshowto.datasciencecentral.com/68-95-99-7-rule/ (Links to an external site.)

Vetter, T. R. (2017). Fundamentals of research data variables: The devil is in the details. Anesthesia & Analgesia, 125(4), 1375-1380. http://dx.doi.org/10.1213/ANE0000000000002370 (Links to an external site.)

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Collapse SubdiscussionKimberly Austin

Kimberly Austin

SundayJan 31 at 12:19pm

What is a normal distribution and what does it look like? Why is the normal distribution important in statistics?

Normal distribution, which is also known as Gaussian distribution, or bell-shaped curve, is a symmetric, unimodal distribution, and not too peaked probability distribution (Polit & Beck, 2017).

Normal distribution is important in statistics as it is an essential tool used for analysis and interpretation of data (Kumar & Anila, 2017). Normal distribution fits many natural phenomena, such as height, weight, blood pressures, etc. This probability theory calculates corresponding values (Sokouti et al., 2017). As data is plotted, important findings are revealed which identify, standard deviation, mean, and mode.

References

Kumar, C. S., & Anila, G. V. (2017). On Some Aspects of a Generalized Asymmetric Normal Distribution. Statistica, 77(3), 161-79.

http://dx.doi.org.chamberlainuniversity.idm.oclc.org/10.6092/issn.1973-2201/7134 (Links to an external site.)

Polit, D. F., & Beck, C. T. (2017). Nursing research: Generating and assessing evidence for nursing practice (10th ed.). Wolters Kluwer Health.

Sokouti, M., Sadehhi, R., Pashazedeh, S., Eslami, S., Abgadi, H., Ghojazadeh, M., & Sokouti, B. (2017). Most accurate non-linear approximation of standard normal distribution integral based on artificial neural networks, Suranaree Journal of Science & Technology, 24(3), 263-280.

https://chamberlainuniversity.idm.oclc.org/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=a9h&AN=127020973&site=eds-live&scope=site

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Collapse SubdiscussionTheresa Kyzar

Theresa Kyzar

SundayJan 31 at 6:17pm

Hi Angela, Kim, Carlos, Carlene, & Kate,

Thank you for your posts and for participating in this conversation. You have all provided excellent responses which expand upon the normal distribution!

Adding to your comments, I thought we could summarize the features of a normal distribution which include:

symmetric bell shape is noted;

the mean and median are equal; both located at the center of the distribution;

approximately equals, 68% of the data falls within one standard deviation of the mean;

approximately equals, 95%of the data fall s within two standard deviations of the mean; and

approximately equals, 99.7% of the data falls within three standard deviations of the mean.

normal distribution.svg

Take care,

Dr. Kyzar

References

Khan Academy. (2010, January 8). Normal distribution problems: Empirical rule [Video]. YouTube.

https://youtu.be/OhRr26AfFBU (Links to an external site.)

Khan, S. (2020). Normal distribution problems: Empirical rule. Retrieved from https://www.khanacademy.org/math/ap-statistics/density-curves-normal-distribution-ap/stats-normal-distributions/v/ck12-org-normal-distribution-problems-empirical-rule (Links to an external site.)

Edited by Theresa Kyzar on Jan 31 at 6:18pm

ReplyReply to Comment

Collapse SubdiscussionRacheal Aneke

Racheal Aneke

SundayJan 31 at 9:24pm

What is a normal distribution?

The most important probability distribution in statistics (Links to an external site.) is normal distribution because it fits many natural occurrences and curves for a real-world random variable. It describes how the values of variables are distributed evenly. The normal distribution also functions for independent randomly generated variables. The readings are assembled at the top, and the probability values from the mean (Links to an external site.) are narrow or equal on both sides. Heights, weight, blood pressure, and IQ scores are examples of normal distribution (Gray. J., & Grove. S. K., 2021). Normal distribution is also called bell curve or the Gaussian distribution. The common thing about normal distribution is that mean, median (Links to an external site.), and mode (Links to an external site.) are all equal. The Empirical Rule or the 95% rule allows you to determine the proportion of values that fall within certain distances from the mean.

What does it look like?

Week 4 picture.png

This is a normal distribution with some interesting properties such as the bell shape or curve, the mean and median are equal, and 68% of the data are within a standard deviation (Gray. J., & Grove. S. K., 2021).

Why is the normal distribution important in statistics?

A hypothesis test assumes that figures follow a regular circulation in a normal distribution since the mean, median, and mode are equal. A normal distribution is essential in statistics because its probability distribution does not fit all populations to create variety. Linear and nonlinear degeneration (Links to an external site.) both assume that the residuals (Links to an external site.) also follow a normal distribution (Gray. J., & Grove. S. K., 2021). The central limit theorem (Links to an external site.) in a probability theory established that, in some situations, if independent variables are added, the sum normalizes the curve even if the original variables were not distributed normally.

Reference:

(Gray. J., & Grove. S. K., 2021) Burns and Grove's the practice of nursing research: appraisal, synthesis, and generation of evidence. Elsevier.

ReplyReply to Comment

Collapse SubdiscussionEjiro Ohonbamu

Ejiro Ohonbamu

SaturdayJan 30 at 6:18pm

Good evening Dr. Kyzar and classmates.

Appraising Descriptive Statistics

What statistical procedure is needed to determine an effective sample size to make a reasonable conclusion? Explain your rationale.

Quantitative research studies use a power analysis to approximate an actual sample size needed for a practical deduction. However, large sample sizes are desirable to small samples. The reason for this is that the large samples boost statistical conclusion legitimacy, which tends to be more typical. The researchers performed a power analysis at the early stage of the study to estimate the sample size and to assist in the reduction of possible errors of Type II (Polit & Beck, 2018). Basically, sample size defines the number of participants needed in a study. If the research calls for a specific sample to determine a specific outcome, it is essential that that is followed. On that note, with every large or small sample, there is a probability of errors if the sampling technique is not followed. The standard deviation promotes caring for the certainty that the sample is not typically dispersed.

Reading through the study, you observe that the researcher used chi-square analysis to analyze nominal and ordinal data. Is this the appropriate level of statistical analysis to answer the research question? Explain your rationale.

The importance of the Chi-square value is noted by using the appropriate degree of freedom and significance (Turhan, 2020). Usually, the Chi-square determines the relationship between the two existing variables in a sample setting and the probability to show an actual relationship amongst the two variables in a given situation. It also assesses some uncompromising variables are connected with some populations, because variables tend to be a bit diverse from their populations (Turhan, 2020). In data analysis, it is mandatory to find degrees of freedom, expected occurrences, test statistics, and P-value connected to the test statistic (Turhan, 2020).

The researcher reports that the p-level led her to conclude that the null hypothesis was rejected. In your critique of the study, you determine that the null hypothesis is correct. Do these findings impact your decision about whether to use this evidence to inform practice change? Why or why not?

It is essential to note that the value P is the observation possibility of a sample statistic that is the highest test of statistics (Turhan, 2020). Now each hypothesis test uses the p-value to assess the depth of evidence. It shows that the null hypothesis untrue, which establishes that this could be a mistake. The null hypothesis is truthfully based on statistical errors and might institute further need added investigation. On that note, Type I error occurs when the null hypothesis is rejected when it is true. There is a greater risk of a Type I error with a 0.05 level of importance as compared to a 0.01 level of significance. The higher the level of significance, the more extreme, nature of the risk of a Type I error diminishes (Polit & Beck, 2017).

The null hypothesis is not obviously voiced in many research studies. In this case, it is, and it will impact my decision because an error has been determined by the researcher. In particular, scientists are challenged and not convinced with time‐to‐event results intensely understanding the null hypotheses based on hazard roles and their uses (Stensrud et al., 2019).

References

Polit, D. F., & Beck, C. T. (Eds.). (2017). Nursing research: Generating and assessing

evidence for nursing practice (10th ed.). Wolters Kluwer. 

Stensrud, M., J., Roysland, K., & Ryalen, P., C. (2019). On null hypotheses in survival analysis.

Biometrics. 75(4),1276-1287. http://doi:10.1111/biom.13102.

Turhan, S., N. (2020). Karl Pearson's Chi-Square Tests. Educational Research and Reviews,16

(9), 575-580. https://eric.ed.gov/contentdelivery/servlet/ERICServlet?accno=EJ1267545

ReplyReply to Comment

Collapse SubdiscussionTheresa Kyzar

Theresa Kyzar

SundayJan 31 at 6:28pm

Hi Ejiro:

Good response this week! You offered some very interesting perspectives, and I would like to take this brief opportunity to add to your discussion. My comments relate specifically to the use of the Chi Square Analysis. This type of test along with correlations, t-tests, and ANOVA, are foundational techniques, typically covered in introductory statistics textbooks and introductory statistics classes. Chi-square tests are by far the most popular of the non-parametric or distribution free tests and the default choice when applied psychological researchers analyze categorical data (Sharpe, 2015). It is important to note that it is an important, useful when both variables are nominal-level data, e.g., simple counts of people within a category such as gender or ethnic group membership). Tappen (2016) discusses that the Chi-square test compares the observed (actual) frequencies in each cell to the expected frequencies (p. 350). However, remember that a key objection is that when the total number of observations is under thirty or when one or more expected cell frequencies are under five for total numbers under fifty then Fisher's exact test should be used in place of the Chi-square test (Langley, 1970; Siegel, 1956; Zar, 1974)[as cited by Hoffman, 1975]. Failure to do so may lead to an erroneous probability of rejecting the null hypothesis.

Thank you and take care.

Kindly,

Dr. Kyzar

References

Hoffman, J.E. (1975). The incorrect use of Chi-square analysis for paired data. Clinical and Experimental Immunology, 24, 227-229.

Sharpe, D. (2015). Chi-square test is statistically significant: Now what? Practical Assessment, Research, and Evaluation, 20(8). doi: https://doi.org/10.7275/tbfa-x148 (Links to an external site.). Retrieved https://scholarworks.umass.edu/pare/vol20/iss1/8 (Links to an external site.).

Tappen, R. (2016). Advanced nursing research: From theory to practice (2nd ed). Jones & Bartlett.

ReplyReply to Comment

Collapse SubdiscussionTheresa Kyzar

Theresa Kyzar

SundayJan 31 at 6:12pm

Important PLEASE READ: Week 4 Content Summary

Hi Class:

As we approach the weekend, here are tips from Week 4 and Week 5. These tips will assist you as you prepare for the week 5 quiz!

Week 4 Descriptive Statistics Key Points & Questions Properties of Descriptive Statistics (Polit & Beck, 2017)

Key Points-Descriptive Statistics

Summarize or describe characteristics of a data set.

They are numerical and graphical summaries of data.

Consist of two basic categories of measures: measures of central tendency and measures of variability or spread.

Measures of central tendency describe the center of a data set.

Measures of variability or spread describe the dispersion of data within the set.

Power Analyses (Ali & Bhaskar, 2016; Polit & Beck, 2017)

Help decide how large of a sample is needed to make sure judgments about statistical findings are accurate and reliable.

Prevent the recruitment of too many or too few numbers of subjects.

Must be used to determine sample size before the study begins.

Chi-Square Analysis (Ali & Bhaskar, 2016; Connelly, 2019; Polit & Beck, 2017)

Is a type of inferential statistic.

o Evaluates if two categorical variables (e.g., gender, educational level, race, etc.) are related (correlated) in any way.

o Appropriate for discrete variables (nominal, ordinal).

o Does not work with continuous variables (interval, ratio)

Null Hypothesis Testing (Ali & Bhaskar, 2016; Polit & Beck, 2017)

o The beginning point for statistical significance testing.

o A formal approach to deciding between two interpretations of a statistical relationship in a sample

o Null Hypothesis – suggests there is no relationship between variables, populations, etc. meaning there was an error in sampling.

o Alternative Hypothesis – suggests there is a relationship between variables, populations, etc.

o Rejecting the Null Hypothesis – suggests being in support of the Alternative Hypothesis.

Inferential Statistics (Ali & Bhaskar, 2016)

Allow one to make inferences (conclusions, predictions, associations, correlations) from data.

Take data from samples and make generalizations about a population.

Example: Say you are interested in an intervention to improve care at life’s end in the inpatient setting. Using inferential statistics, you take the data from your sample and assess whether or not the data can be expected to demonstrate that the intervention will work at the population level.

P-value (Taylor, 2019)

With most analyses, an alpha of 0.05 is used as the cutoff for statistical significance.

o If the p-value is less than 0.05, we reject the null hypothesis that there's no difference between the means and conclude that a significant difference does exist

o If the p-value is larger than 0.05, we cannot conclude that a significant difference exists.

o The p-value is also known as the calculated probability.

o The p-value is commonly referred to as the alpha.

Questions for your review as you prepare for the Week 5 Quiz.

What are inferential statistics used for?

Inferential statistics are used to make inferences (conclusions, predictions, associations, correlations) from a sample to a larger population (Ali & Bhaskar, 2016).

What is it called when research findings and conclusions from a study conducted on a sample population are used with the population at large?

Generalizability is the term used to describe when research findings and conclusions from a study conducted on a sample population are used with the population at large (Ali & Bhaskar, 206; Polit & Beck, 2017).

What are some examples of nominal and ordinal variables?

Interval – weight, height

Ratio – Level of pain: 0 to 10

Nominal – gender, blood type, marital status, hair color

Ordinal – socioeconomic status (e.g., low, middle, high), course grades (e.g., A, B, C), high school class ranking (e.g., 1st, 9th, 45th...)

What is a normal distribution and what does it look like?

Represents the distribution of many random variables as a symmetrical bell-shaped graph.

With a normal distribution, you should expect to observe approximately 68% of values within one standard deviation; about 95% of the values within two standard deviations; and about 99.7% are within three standard deviations. This is referred to as the 68 95 99.7 rule or Empirical Rule (Statistics How To, 2019).

What are some of the properties of descriptive statistics?

Summarize or describe characteristics of a data set.

They are numerical and graphical summaries of data.

Consist of two basic categories of measures: measures of central tendency and measures of variability or spread.

Measures of central tendency describe the center of a data set.

Measures of variability or spread describe the dispersion of data within the set.

What is the most precise definition of a sample?

The sample is a subset of the larger population that a researcher aims to study.

What is the difference between the p-value and alpha?

When performing hypothesis testing in statistics, a p-value helps to decide the significance of results. A p-value is a number between 0 and 1.

A small p-value (typically ≤ 0.05) indicates strong evidence against the null hypothesis, so the null hypothesis is rejected (Taylor, 2019).

The alpha level is the probability of rejecting the null hypothesis when the null hypothesis is true or the probability of making a wrong decision (Taylor, 2019).

What is the name of the hypothesis that is accepted when significant differences exist?

Alternative hypothesis

What is random sampling and why is it important?

Random sampling is choosing small groups (subsets) of a population with each person having an equal chance of being chosen. Random sampling is important in that is supposed to be representative of the larger population (Polit & Beck, 2017).

Random sampling controls sampling bias also called sampling selection bias (Krautenbacher, Theis, & Fuchs, 2017).

Innovations in CLINICAL NEUROSCIENCE [ V O L U M E 1 3 , N U M B E R 1 1 – 1 2 , N O V E M B E R – D E C E M B E R 2 0 1 6 ]12

ABSTRACT Managing individuals with chronic

disorders of consciousness raises

ethical questions about the

appropriateness of maintaining life-

sustaining treatments and end-of-life

decisions for those who are unable to

make decisions for themselves. For

many years, the positions fostering

the “sanctity” of human life (i.e., life

is inviolable in any case) have led to

maintaining life-sustaining

treatments (including artificial

nutrition and hydration) in patients

with disorders of consciousness,

allowing them to live for as long as

possible. Seldom have positions that

foster “dignity” of human life (i.e.,

everyone has the right to a worthy

death) allowed for the interruption

of life-sustaining treatments in some

patients with disorders of

consciousness. Indeed, most ethical

analyses conclude that the decision

to interrupt life-sustaining therapies,

including artificial nutrition and

hydration, should be guided by

reliable information about how the

patient wants or wanted to be

treated and/or whether the patient

wants or wanted to live in such a

condition. This would be in keeping

with the principles of patient-

centered medicine, and would

conciliate the duty of respecting both

the dignity and sanctity of life and

the right to a worthy death. This

“right to die” has been recognized in

some countries, which have legalized

euthanasia and/or physician-assisted

suicide, but some groups fear that

legalizing end-of-life decisions for

some patients may result in the

inappropriate use of euthanasia, both

voluntary and nonvoluntary forms

(slippery slope argument) in other

patients.

This review describes the current

opinions and ethical issues

concerning end-of-life decisions in

patients with disorders of

consciousness, with a focus on the

impact misdiagnoses of disorders of

consciousness may have on end-of-

life decisions, the concept of

“dignity” and “sanctity” of human life

in view of end-of-life decisions, and

the risk of the slippery slope

argument when dealing with

euthanasia and end-of-life decisions.

We argue that the patient’s diagnosis,

prognosis, and wishes should be

by ROCCO SALVATORE CALABRÒ, MD, PhD; ANTONINO NARO, MD, PhD; ROSARIA DE LUCA, MS, PhD; MARGHERITA RUSSO, MD, PhD; LORY CACCAMO, PhD; ALFREDO MANULI, MS; ALESSIA BRAMANTI; and PLACIDO BRAMANTI, MD

Drs. Calabró, Naro, de Luca, Russo, Manuli, A. Bramanti, and P. Bramanti are from the IRCCS

Centro Neurolesi “Bonino-Pulejo” in Messina, Italy; and Dr. Caccamo is from the Department

of Psychology, University of Padua, Padua, Italy.

Innov Clin Neurosci. 2016;13(11–12):12–24

FUNDING: No funding was received for the preparation of this article.

FINANCIAL DISCLOSURES: The authors have no conflicts of interest relevant to the content of this article.

ADDRESS CORRESPONDENCE TO: Rocco Salvatore Calabrò, MD, PhD; E-mail: [email protected]

KEY WORDS: Artificial nutrition and hydration; euthanasia; minimally conscious state; right to die; sanctity of life; vegetative state.

R E V I E W A N D C O M M E N T A R Y

The Right to Die in Chronic Disorders of Consciousness: Can We Avoid the Slippery Slope Argument?

Innovations in CLINICAL NEUROSCIENCE [ V O L U M E 1 3 , N U M B E R 1 1 – 1 2 , N O V E M B E R – D E C E M B E R 2 0 1 6 13

central to determining the most

appropriate therapeutic approach

and end-of-life decisions for that

individual. Each patient’s diagnosis,

prognosis, and wishes should also be

central to legislation that guarantees

the right to die and prevents the

slippery slope argument through the

establishment of evidence-based

criteria and protocol for managing

these patients with disorders of

consciousness.

INTRODUCTION

Consciousness is the condition of

normal wakefulness (opening and

closing eyes, preserved sleep-wake

cycle) and awareness (of the self and

environment) in which an individual

is fully responsive to thoughts and

perceptions, as suggested by his or

her behaviors and speech. 1,2

A

disorder of consciousness (DOC)

results when awareness and/or

wakefulness are compromised

because of severe brain damage. 3

In recent years, the advances in

diagnostic procedures and intensive

care have increased the number of

patients who survive severe brain

injury and enter a vegetative state

(VS) (also recently named

unresponsive wakefulness

syndrome)4,5 or a minimally

conscious state (MCS). These

entities represent the two main

forms of chronic DOCs. 6–9

In

particular, patients suffering from VS

are unaware of the self and the

environment and cannot show

voluntary, purposeful behaviors

because of severe cortico-thalamo-

cortical connectivity breakdown 10,11

that globally impairs sensory-motor

processing and cognition. On the

other hand, patients with MCS show

fluctuant but reproducible signs of

awareness and have a limited

repertoire of purposeful behaviors.

The best management of patients

in VS and MCS requires a correct

diagnosis, an evidence-based

prognosis, and the full consideration

of the medical, ethical, and legal

elements concerning DOC. 12

In

particular, patients with DOC need

artificial nutrition and hydration

(ANH) and, often, intensive

treatments. These issues evoke a

thorny ethical problem concerning

the therapeutic decision-making of

such patients (including the

continuation of life-sustaining

therapies) in view of the

uncertainties about their state of

consciousness, prognosis, and

personal wishes, with particular

regard to the end-of-life decisions

(ELD). 13

In fact, it is worth

remembering that the

implementation of any life-sustaining

treatment, including ANH, should

not be automatic when considering

that every individual should make his

or her own decisions regarding any

kind of therapy, according to the

ethical principles of autonomy and

the right of self-determination and

freedom. If an individual is unable to

make a decision, as in the case of

patients with DOC, a surrogate

should be empowered to ensure the

patient’s best interest and personal

wishes concerning ELDs. Therefore,

the right to lose health, become ill,

refuse treatment, live the end of life

according to one’s personal view of

life, and die should be guaranteed,

which is in keeping with human

dignity and the duty to protect

physical and mental health. 14

The right to die is further

supported by the following

arguments. 14–19

1. The right to (a worthy) life

implies the right to (a worthy)

death.

2. There is no reason to have a

“dedicated” right to die, given that

dying is a very natural

phenomenon, as is life.

3. Death is a private matter, and

other people have no right to

interfere if there is no harm to

others or the community (a

libertarian argument.

4. It is possible to regulate

euthanasia by proper laws, and

thus avoid the slippery slope

argument (SSA).

3. Euthanasia may avoid illegal acts,

given that euthanasia may happen

anyway (a utilitarian or

consequentialist argument) and

save the extreme despair of

suicide or homicide.

6. Death is not necessarily a bad

thing, owing to the naturalness of

the phenomenon, regardless of

whether it is induced.

7. Euthanasia may satisfy the

criterion that moral rules must be

universalizable, but

universalizability is a necessary

but not a sufficient condition for a

rule to be morally good.

8. Medical resources can be better

managed, and though this is not a

primary reason for the right to

die, it is a useful consequence.

On the other hand, an opposite

view states that life is a unique and

incorruptible gift that, in keeping

with the concept of the sanctity of

human life, must always be

preserved. Hence, each individual

has the moral duty to attend to all

the treatment necessary to preserve

life, with the exception of those

burdensome and/or disproportionate

to the hoped for or expected result

(i.e., life preservation), and to avoid

behaviors that can deliberately

hasten or cause death. 13,19–24

A possible middle ground is

represented by the concept that the

sanctity and the dignity of life are

somehow coincident; consequently,

there is no reason why accepting

euthanasia makes some individuals

worth less than others. Since it is

possible to regulate euthanasia by

proper laws, there is no risk of the

following: 13,19–24

1. Starting an SSA that leads to

involuntary euthanasia, thus

killing people who are thought

undesirable

2. Less than optimal care for

terminally ill patients (for

economic reasons)

3. Giving too much power to medical

staff in limiting the access to

palliative and optimal care for the

dying, pain relief, saving lives,

using euthanasia as a cost-

effective way to treat the

terminally ill, and limiting the

research for new cures and

treatments for the terminally ill

Innovations in CLINICAL NEUROSCIENCE [ V O L U M E 1 3 , N U M B E R 1 1 – 1 2 , N O V E M B E R – D E C E M B E R 2 0 1 6 ]14

3. Exposing vulnerable people to

pressure to end their lives (duty

to die) by selfish families or by

medical staff to free up medical

resources or when patients are

abandoned by their families.

At first glance, the problem of

ELDs in patients with DOC may

seem easy to solve. The supporters

of the dignity of human life claim

that since patients with DOC are

unconscious and therefore cannot

fully benefit from their rights, ELDs

should assumed by a third party

(e.g., those with whom the patient is

familiar, medical staff, ethics

committees, or courts).25 These

parties would make the ELDs, taking

into account the best interests of the

patient, his or her wishes, the right

to freedom, and the respect of

human dignity. On the contrary,

those who advocate the sanctity of

life deny any possibility to hasten (by

interrupting life-sustaining

treatments) or cause death (by using

euthanasia and physician-assisted

suicide) (PAS), because they believe

that life preservation is a social and

ethical duty. Moreover, patients with

DOC are in a very frail and

vulnerable condition in which they

cannot express their thoughts on

these issues.13,19–24

Judgements in the Schiavo and

Englaro cases highlight this

controversy. In the Schiavo case,26

the argument was over whether Terri

Schiavo was in a persistent VS,

which had already lasted 15 years. It

began with her collapse in 1990, due

to cardiac arrest, and then her

husband’s initial court attempt to

have her feeding tubes removed in

1998. That was followed by court

battles between the husband and

Schiavo’s parents, who opposed the

removal the feeding tube. Her

feeding tube was removed several

times and then reinserted after more

court orders. It was removed for the

last time in March 2005 after the last

successful court petition by the

husband. Schiavo died 13 days later.

Likewise, Eluana Englaro27

entered a persistent VS in 1992

following a car accident, and

subsequently became the focus of a

court battle between supporters and

opponents of euthanasia. Shortly

after her accident, medical staff

began feeding Englaro with a feeding

tube, but her father “fought to have

her feeding tube removed, saying it

would be a dignified end to his

daughter’s life.” According to

reports, Englaro’s father said that

before the car accident, his daughter

visited a friend who was in a coma

and afterward told him, “If something

like that ever happened to me, you

have to do something. If I can’t be

what I am now, I’d prefer to be left to

die. I don’t want to be resuscitated

and left in a condition like that.” The

authorities refused father’s request,

but the decision was finally reversed

in 2009, after she had spent 17 years

in a persistent VS.

Of note, the United States

Supreme Court has stated that the

irreversibility of a DOC condition and

the clearly defined patient’s wish to

not live under such conditions should

both be clearly demonstrated in

order to withdraw the sustaining

therapies, including ANH.28,29 These

decisions are fully in keeping with

the right of freedom and self-

determination and with the

supporters of the right to life.

However, these are fiercely criticized

and hindered by the sanctity of life

supporters.13,19–24

Therefore, we consider whether it

is more ethical to respect human

dignity than to protect the sanctity

of human life at all costs. A correct

approach to this thorny ethical

dilemma requires taking into account

that there is a tangible uncertainty of

DOC diagnosis and prognosis,

consequently making it more difficult

to respect a patient’s rights properly

when making ELDs. Moreover, it is

still debated whether ANH should be

considered a fundamental (i.e.,

always due) or an aggressive therapy

(i.e., useless and bearer of further

suffering).22,24,30–34 Finally, the

motivation sustaining the right to live

with dignity and in respect of human

life sanctity must be analyzed

carefully, given that the access to the

right to die is a SSA. In fact, both the

withdrawal and the maintenance of

ANH may lead to a chain of related

events that may culminate in some

significant and potentially negative

effects on patients with DOC (e.g.,

death or unnecessary and prolonged

suffering). Liberalizing euthanasia

may lead to unnecessary application

in some cases. The strength of each

argument in favor or against ELDs

depends on whether one can

demonstrate a process that leads to a

significant effect. SSAs can be used

as a form of fear mongering in an

attempt to scare the audience, thus

ignoring the possibility of a middle

ground between the dignity and the

sanctity of human life. In this article,

we will review the key concepts of

the positions supporting the dignity

and the sanctity of human life in an

attempt to find a conciliating view to

solve the SSA.

DOC DIAGNOSES AND

PROGNOSES

When family members are faced

with an irreversible and hopeless

case of unconsciousness, leaving

their loved one in such a condition

may be unbearable for both the

patient and his or her family

members. The relatives of patients

with DOC live a paradoxical reality.

In fact, they live with a family

member who is both present

(inasmuch as he or she is awake)

and absent (unaware) and alive

(inasmuch as he can open and close

his or her eyes, breathe

independently, and make some

movements) and dead (given that he

or she cannot interact with the

family members or the

environment).35–37 These issues can

foster denial or misunderstanding in

the family members of their current

situation. For example, they may

deny that their loved one is in a VS

because they interpret spastic or

reflexive movements as signs of

improvement,6 thus imagining

chances of recovery that are not

supported by evidence-based

medicine. Given that the family

Innovations in CLINICAL NEUROSCIENCE [ V O L U M E 1 3 , N U M B E R 1 1 – 1 2 , N O V E M B E R – D E C E M B E R 2 0 1 6 15

members may witness important

responses by the patient that have

not been observed by the clinicians,

the medical staff should attempt to

observe the patient with the family

members and involve them in the

patient evaluation. Assisting family

members in better understanding the

patient’s behaviors and level of

awareness is important and may

strengthen the family members’

relationship with the medical staff.38

Hence, the correct communication

of a proper diagnosis and a reliable

prognosis is essential for the best

management of a patient with DOC.

In fact, inaccurate diagnoses and

prognoses and disclosure of false

diagnostic information to families

may have serious ethical, medical,

and legal consequences regarding

the medical management of the

patient, the well-being of patient’s

family members, and ELDs.39,40 In

fact, an incorrect diagnosis and

prognosis may result in a false

expectancy for recovery by the

family members, the unnecessary

and potentially harmful life-support

prolongation of the patient, financial

and emotional resources being

withheld or withdrawn, resource

misuse and misallocation, and an

inappropriate rehabilitation or long-

term care facility enrollment.13

Nonetheless, identifying residual

awareness in unconscious patients

(thus differentiating VS from MCS)

and establishing a correct prognosis

are extremely challenging, owing to

the inadequate sensitivity of the

clinical and paraclinical approaches

currently available for DOC diagnosis

and prognosis.41–47 Even though the

rate of consciousness recovery varies

from eight percent to 72 percent

(but decreases to 20–30% in patients

persisting in comas longer than 24

hours),47 a severe brain injury may

result persistent unconsciousness for

many years. There have been cases

of emergence from DOC, even after

many years.48 Generally, recovery

from a metabolic or toxic coma is far

more likely than from an anoxic one

where the traumatic brain injury

(TBI) occupies an intermediate

prognostic position. A post-anoxic

coma is a state of unconsciousness

caused by global anoxia of the brain,

most commonly due to cardiac

arrest. The outcome after a post-

anoxic coma lasting more than

several hours is generally, but not

invariably, poor.47

About 40 percent of patients with

VS may be clinically misdiagnosed in

that they may be conscious but are

unable to manifest any signs of

consciousness.49–51 Such a condition

has been recently labeled functional

locked-in syndrome (FLIS),

whereby, using neurophysiological

and functional neuroimaging

approaches, clinicians are able to

record residual brain network

connectivity that is sustaining a

covert awareness.52 A patient with

FLIS is clinically similar to one with

VS, with the exception that the

former is aware of the self and the

environment but is unable to

demonstrate awareness or

communicate.6–9 This may due to the

deterioration of sensory-motor

processes, which support motor

function, rather than the breakdown

of cerebral connectivity.6–12,53,60

The low rate of correct diagnoses

and prognoses may depend on the

variations in scale application,

awareness fluctuation, and subjective

interpretation of clinical findings.

The use of paraclinical tests to

detect residual and covert signs of

awareness may help in better

managing patients with DOC and

consequently supporting their right

to ELDs. Nevertheless, different

paraclinical tests would be necessary

to confirm awareness since single

tests may suffer from the same

methodological bias that clinical

approaches do.39,40,54

ELDs AND THE DIGNITY OF

HUMAN LIFE

The thought of interrupting life-

sustaining treatments, including

ANH, may arise in family members

and caregivers when their loved one

suffers from a long-lasting and

potentially irreversible DOC

condition.34 The idea of hastening

one’s own death may occur when

one’s quality of life is poor or

unbearable (e.g., in the case of

physical pain and/or mental anguish)

and life is considered without dignity

(e.g., feeling there is no chance of

recovery, finding nothing that makes

life worth living, and perceiving life

as a burden to others).55–58 One might

consider that respecting the dignity

of life means respecting the dignity

of death and thus avoiding

unbearable and/or unnecessary

suffering or living in what one might

considered a handicapped and

hopeless condition. As stated by

Marc Augé,59 “To die without dignity

is to die alone, abandoned, in an

inhospitable and anonymous place, in

a non-place. To die without dignity

means to die, suffering needlessly or

to die tied up to a technical gadget

that becomes the sovereign of my

last days. To die without dignity also

means to die in isolation, surrounded

by insensitive people, soulless

specialists, and bureaucrats who

carry out their professional tasks

mechanically.”

Many authors22,24,30–34,60–62 criticize

using the interruption of ANH as a

way to hasten death because ANH

suspension inevitably leads to a

lengthy death with the potential for

suffering, and suffering would be

considered an unworthy way to die.

This reasoning suggests that ANH

should be continued in order to avoid

suffering by the patient, even when

that patient is unconscious.61,62

Others argue that ANH is a

standard part of treatment for

patients with DOC, and suggest that

the discontinuation of ANH along

with any other standard treatment

should be permitted when explicitly

requested and that this is in keeping

with the principles of beneficence

and non-maleficence and the

“patient’s best interests” rationale.63–65

However, the rights to freely live

(with obvious due respect for others)

and to make any decision concerning

one’s own personal health are well

established as respecting the

principles of free will and the

personal understanding of the quality

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of life and human dignity.66 This

suggests that a human being has an

innate right to be valued and

respected and to receive ethical

treatment. In 1964, the Declaration

of Helsinki56 stated, “It is the duty of

physicians who participate in medical

research to protect the life, health,

dignity, integrity, right to self-

determination, privacy, and

confidentiality of personal

information of research subjects.”

Such issue was further corroborated

by the Council of Europe in 1997 in

the Convention for the Protection

of Human Rights and Dignity of

the Human Being with regard to

the Application of Biology and

Medicine57 and by the United

Nations Educational, Scientific, and

Cultural Organization’s Declaration

on the Human Genome and

Human Rights58 in 1998. Both of

these councils stated that there is an

absolute need for respecting the

human being both as an individual

and as a member of the human

species, for recognizing the

importance of ensuring the dignity of

the human being, and for

safeguarding human dignity and the

fundamental rights and freedoms of

the individual with regard to the

application of biology and medicine.

In keeping with the duties and

rights set forth in the

aforementioned declarations, a

competent individual or an

individual’s surrogate should be free

to make ELDs. We might consider

that ANH contributes to the physical

well-being of the patient and permits

a continuation of life and, possibly,

improvement in the quality of life.

And in cases of long-lasting VS

where the chances of recovery are

slim at best, we might consider that

withholding ANH might cause

physical and/or emotional pain. One

might also consider, however, that

when the burden of life on the

patient outweighs the benefits (e.g.,

in the case of a patient with DOC

who has no chance of amelioration),

the administration of ANH might be

futile treatment. Even the most

conservative positions on life

maintenance, e.g., the Catholic

church, admit that treatments are

not obligatory when considered

harmful.67 Hence, a form of passive

euthanasia might be acceptable when

1) aggressive or unnecessary

therapies in cases of terminal or

hopeless illness only prolong a

painful and suffering life, 2) an

informed request is made by a

sentient patient or, conscientiously,

by that patient’s surrogate(s); and 3)

death is an unintended, although

foreseeable, consequence of therapy

interruption. In this regard, the

unique scope of therapy interruption

must be to avoid the suffering of the

patient and not to provide or hasten

death. Thus, the most conservative

positions will deny any form of

euthanasia but will provide palliative

care, even if this shortens the

patient’s life, thus producing the

unwanted and undesired side effect

of death (passive euthanasia).

ELDs IN VIEW OF THE SANCTITY

OF HUMAN LIFE

The right to die is strongly

criticized by those who claim the

sanctity of human life and argue that

the willingness to die should be

considered unacceptable for moral,

religious, logical, and philosophical

reasons.13,20–24 In fact, it might be

argued that euthanasia and PAS can

be similarly compared to suicide and

homicide, respectively, even when

performed at the explicit request of

the patient or surrogate, given that

they cause death with established

methods and times. As argued by the

most conservatory positions

(including the Catholic Church),13,20–24

this issue is considered by some as

unacceptable because life is an

inviolable gift (by God or nature)

that cannot be removed by self of by

others. The expression sanctity of

life refers to the idea that human life

is sacred and holy, given that A) all

human beings are to be valued,

irrespective of age, sex, race,

religion, social status, or their

potential for achievement; B) human

life is a basic good as opposed to an

instrumental good—a good in itself

rather than a means to an end; and

C) human life is sacred because it is

a gift from God. Therefore, the

deliberate taking of human life

should be prohibited except in self-

defense or the legitimate defense of

others.

In religion and ethics, the

inviolability or sanctity of life is a

principle of implied protection

regarding the aspects of sentient life,

which are said to be holy, sacred, or

otherwise of such a value that they

are not to be violated.13,20–24 Hence, by

merely existing, every human being

lives his or her own life with dignity,

which includes living correctly,

according to moral and ethical

principles. This suggests that one

must die in a natural way, given that

death is a natural phenomenon.

Death might be considered the ‘last

page’ of life, and life must be

experienced with dignity. One’s

death has been decided by the

superior Being, and thus one should

adopt options of preservation,

including the administration of

analgesics and the provision of

adequate human, psychological, and

spiritual support, which may relieve

the sense of solitude and allow

relatives to grieve and be given the

opportunity to humanize death. On

the other hand, the voluntary refusal

of treatment may lengthen the

patient’s period of suffering but will

still result in death as a result of the

disease itself, not by any action or

omission of life-sustaining therapy. In

such cases, death would be natural

and expected.

Some secular positions criticize

the right to euthanasia and PAS from

a logical point of view.28,29 They claim

that it is unreasonable for one person

to determine the death of another

person as there could be a

reasonable chance of healing,

survival, or alternative care. In

addition, they argue that such a

determination should not be made

due to the inherent uncertainty of

the chances for recovery and real

level of awareness in patients with

DOC (e.g., a patient may be in a

state of FLIS, thus unable to

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communicate with those around him

or her but is still aware). Hence,

using this line of thinking, we might

conclude that patients with DOC

should always have the right to live

and to die peacefully and naturally

later rather than have their lives

prematurely ended by removing a

feeding tube, which would lead to

forced starvation.

MAKING CHOICES

We might consider in what way

the worthiness of life is defined,

since “worthy” is the pivotal element

of the right to death argument. An

important component of ELDs is

each individual’s perception of what

makes life important, worthy, and

valuable. For example, one individual

might perceive that living with a

disability makes his or her life

unworthy, whereas another

individual with the same disability

may consider his or her life

important and worth living.

Therefore, one might argue that the

dignity of one’s life has to be

determined by oneself, as long as

such determination does not harm

others, including family members.

From this point of view, dignity and

sanctity of life are not conflicting,

and ELDs for patients with DOC

could be based on sufficient evidence

that their condition is irreversible

and hopeless and any ELDs are in

keeping with their wishes. It could be

argued that putting an end to

unnecessary suffering is not an

affront to but rather a strengthening

of the sanctity and dignity of life,

provided this end is freely and

consciously wanted by the either the

patient or his or her surrogate on

behalf of the patient.

A clear and conscious decision to

request the discontinuation of one’s

own life-sustaining therapy, including

ANH, may serve as sufficient legal

justification for such a decision in

most United States courts as long as

the patient is an adult who is capable

of making decisions. But what about

in cases of DOC, in which the

patients lack the capacity to make

decisions, and thus the burden of

decision falls on the patient’s

surrogate or guardian? In the United

States, the Quinlan and Cruzan

cases highlight two important

considerations regarding the ethical

admissibility of ELDs made by a

patient’s guardian or surrogate when

the irreversibility of unconsciousness

has been established: 1) making a

presumptive decision for the patient

in the absence of a living will and 2)

making a decision for the patient

with a living will.68–70 Based on the

principle of substituted judgment, in

some states in the United States, a

surrogate is allowed to refuse life-

sustaining treatment on behalf of the

patient, with or without a living will,

if the patient lacks the capacity to

decide for him- or herself and the

treatment is considered burdensome

and/or unnecessary (i.e., the patient

will never recover, even with

treatment). In these cases,

withholding or interrupting life-

sustaining therapy would be

considered to be in the best interest

of the patient. In other states,

however, a surrogate must provide

evidence of a living will that

satisfactorily communicates the

patient’s desire to have life support

discontinued in the event of

irreversible DOC—before the

surrogate can make such a

request.68–70

The ethical admissibility of ELDs

made by a patient’s guardian or

surrogate becomes thornier when

dealing with cases of MCS, because

these patients may have residual

decision-making capacity and

cognitive ability. There are several

cases in the United States where

ANH was withheld in patients with

MCS (e.g., Conroy, Edna, Martin,

and Wendland cases).71–73 Because

MCS individuals are partially

conscious and are not typically

terminally ill, their legal status is

complex. While consciousness itself

might be a good reason to continue

life-sustaining aids, it may not always

be in the patient’s best interest to

continue living a severely

handicapped life.74,75 Determining

when existence is no longer

subjectively valuable for an individual

with a severely limited capacity to

communicate is a vexing situation.

Assuming that all persons have the

same right to die, MCS surrogates

should remain empowered to act on

behalf of these vulnerable

individuals,76 but also should take

into account the potential that their

loved one with MCS might still have

some cognitive ability.

Altogether, the ethical issues

surrounding ELDs made by someone

other than the patient highlight the

importance of establishing living

wills, which are written, legal

instructions regarding a patient’s

preferences for medical care

(doctors and caregivers) if he or she

is unable to make decisions for him-

or herself because of a terminal

illness, severe brain injury, coma, the

late stages of dementia, or the near-

end of life. By careful planning,

unnecessary suffering of the patient

and burdening the caregiver with

difficult ELDs might be avoided

during times of crisis or grief.

Through the power of attorney, a

person (healthcare agent, proxy,

surrogate, representative, attorney-

in-fact, or patient advocate) is

empowered to make decisions for the

individual who is unable to do so.

Living wills are allowed or legalized

in the United States (e.g., California

Natural Death Act77 and United

States Patient Self Determination

Act78), Germany, France, Canada,

Australia, Denmark, and England,

whereas they are still debated in

Italy.79–81 However, a living will may

present some critical problems. For

example, a patient’s wishes may not

be respected due to the lack of clear

legislation concerning the warranty

of the patient’s right to die. The

medical staff’s rights and duties also

may not be clearly defined, causing

further push back on respecting an

individual’s living wills by raising the

concern about potential criminal

consequences of an omission or

fulfillment of patient’s will.82

Furthermore, the disproportionality

of therapies has not been clearly

defined.83 Some may argue that a

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dying patient has the right to refuse

burdensome medical treatments that

A) have no chance of curing or

improving the patient’s medical

condition(s) and/or B) are

disproportionately painful, intrusive,

risky, or costly when compared to

the expected therapeutic outcome. It

can be argued that every individual

should be free to decide whether to

live in such a condition. But

regarding the living wills of patients

with DOC, it is important to consider

not the value of the life of the person

but rather the value of the treatment

to that person.

To avoid potential problems

regarding the authenticity of living

wills, they should be officially

certified by means of a notary or an

audio-video testimony overseen by a

lawyer or a solicitor. Moreover, a

living will should be checked and

updated continuously to confirm the

desires of its author in terms of ELDs

in general and ELDs specific to DOC,

should this occur. And finally, the

possibility of revising the will of an

incapacitated patient regarding

withdrawal of ANH and other life-

supporting care may need to be

considered, with the help of family

members and friends. Living wills

prepared in such a way will reduce

the chances of misinterpretation of

the document by judges, ethics

committees, and public health

committees.

THE SLIPPERY SLOPE ARGUMENT (SSA) OF THE “RIGHT TO DIE”

After considering the ethical

dilemma of maintaining a patient’s

dignity while respecting his or her

sanctity of life, the issue of how to

regulate the right to a worthy death

remains. In fact, the lack of a clear

position by those governments that

have not established ad hoc laws on

ELDs has led to the growth of the

phenomenon of indirect euthanasia,

in which pain medication is

administered to the patient to reduce

pain, with the side effect of

quickening the dying process.84 One

might consider that the primary

intention of such treatment is not to

kill the patient but to make the

patient more comfortable, which

might be viewed as morally

acceptable. This type of indirect

euthanasia might be justified using

the “Doctrine of Double Effect,”

which states that if doing something

morally good has a morally bad side

effect, it is ethically correct only

when the bad side effect is not

intended, even if the bad effect was

foreseeable.85 That is to say the good

result must be achieved

independently of the bad one, the

action must be proportional to the

cause, and the patient must be in a

terminal condition.

Without clear euthanasia

legislation, arbitrary nonvoluntary

and even involuntary euthanasia

could potentially occur.85 Euthanasia

must be voluntary to be ethical, but it

is nonvoluntary when it is used in

unconscious individuals or in persons

who are unable to make a meaningful

choice between living and dying and

an appropriate person (a surrogate or

a legal guardian) makes the decision

on their behalf. On the other hand,

nonvoluntary euthanasia can also be

when the person who dies had

chosen life but instead underwent

euthanasia at the request of someone

else (i.e., murder). A conservative

view is that this SSA could lead to an

out of control acceptance of

euthanasia or PAS, even if it is

deemed unacceptable.13,20–24 From a

logical point of view, if the

acceptance of an initial act logically

entails the acceptance of another

(but undesirable) act, it might be

argued that there is no relevant

conceptual difference between the

two acts. And on the other hand, if

the acceptance of an initial act will

lead to a series of similar acts that

are all acceptable, the eventual last

(and unacceptable) event is not

relevant. From an empirical or

psychological point of view, one

could argue that there is instead no

need for a logical connection between

two events; the acceptance of an

event will, in time and through a

process of moral change, lead to the

acceptance of another one.

To avoid an out of control

application of ELD, and to both grant

and regulate the right to die,

governments in the United Kingdom,

Canada, and some states in the

United States have outlined different

protocols for ELDs and euthanasia. A

clear law that limits ambiguity

regarding the representation of

patients with DOCs is still missing in

many countries, including Italy. The

media has brought attention to some

cases that have forced the courts to

decide whether to suspend ANH, but

no clear, consistent legislation with

documented protocol has been

established when considering

euthanasia for patients with

DOC.27,69,86–91

Active euthanasia, in which a

person (physician or not) directly

and deliberately causes the patient’s

death following that patient’s explicit

request (or that of the patient’s

surrogate) through the use of drugs

is legal in a few countries. As of June

2016, euthanasia of this nature is

legal in the Netherlands, Belgium,

Colombia, and Luxembourg.92 PAS

(which refers to cases wherein the

person, who is terminally ill, needs

and asks for the help of medical

professionals in ending his or her

life) is legal in Switzerland, Germany,

Japan, and Canada; it is also legal in

the states of Washington, Oregon,

Vermont, Montana, New Mexico, and

California in the United States.92

The Netherlands has legalized

both euthanasia and PAS but only

after the patient had received every

available type of palliative care. In

2004, the Groningen Protocol93 was

developed establishing the required

criteria each case must meet before

legal child euthanasia may be carried

out, which protects the liability of

the physician. It is worthy to note

that Belgium also allows child

euthanasia when the young patient is

conscious of his or her decision,

understands the meaning of

euthanasia, and suffers from a

terminal illness that causes an

intractable and unbearable pain; the

child’s parents and the medical team

must approve the request.94

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Luxembourg and Uruguay legalized

euthanasia for terminally ill patients,

who have received the approval of

two doctors and a panel of

experts.94,95

Switzerland allows PAS for both

adult citizens and foreigners,

whereas PAS is legal in Canada only

for all adult Canadian citizens with a

terminal illness that has progressed

to the point where natural death is

“reasonably foreseeable” (the

Assisted Dying for the Terminally Ill

Bill).96–100 Likewise, Colombia

approved euthanasia for terminally ill

patients with cancer, acquired

immunodeficiency syndrome (AIDS),

kidney or liver failure, and

degenerative diseases (including

Alzheimer’s, Parkinson’s, and

amyotrophic lateral sclerosis) that

cause extreme suffering.101 In

Germany, PAS is legal as long as the

lethal drug is taken without any help,

meaning there is no one guiding or

supporting the patient’s hand.102

Active euthanasia is illegal

throughout most of the United

States, whereas the passive form

(i.e., refusing medical treatment

even if this choice may hasten death)

is legal, with PAS being legal in five

states (Oregon, Washington,

Vermont, California, Montana, and

one county in New Mexico). The

legislation passed in Oregon,

Washington, and California was

based on Oregon’s “Death with

Dignity” Act,103–107 which states that a

“competent adult resident who has

been diagnosed by a physician with a

terminal illness, which will kill the

patient within six months, may

request in writing, from his or her

physician, a prescription for a lethal

dose of medication for the purpose of

ending the patient’s life. The

exercise of the option, under this

law, is voluntary, and the patient

must initiate the request. Any

physician, pharmacist, or healthcare

provider who has moral objections

may refuse to participate.” Two

witnesses, one of whom is not

related to the patient in any way,

must confirm the request. After the

request is made, another physician

must examine the patient’s medical

records and confirm the diagnosis.

The patient must be determined to

be free of a mental condition that

impairs his or her judgment. If the

request is authorized, the patient

must wait at least 15 days and make

a second oral request before the

prescription may be written. The

patient has a right to rescind the

request at any time. The patient

must be referred for a psychological

evaluation if the physician has

concerns about the patient’s ability

to make an informed decision or if he

or she suspects the patient’s request

may be motivated by depression or

coercion.103–107

Oregon’s Death with Dignity Act

protects doctors from liability

provided the adult patient is

competent and is in compliance with

the statute’s restrictions; at the same

time, this Act also guarantees and

regulates the access to the right to

die. Participation by physicians,

pharmacists, and healthcare

providers is voluntary. The law also

specifies that a patient’s decision to

end his or her life shall not “have an

effect upon a life, health, or accident

insurance or annuity policy.”

According to the Oregon Death with

Dignity Act: Data Summary 2015

Report,106 about 64 percent of the

people in Oregon who filled

prescriptions for lethal medications

died. There were no significant

differences concerning age, gender,

or levels of instruction. The primary

end of life concerns were the loss of

autonomy, the inability to make life

enjoyable, and loss of dignity.

Notably, there was no evidence of

heightened risk for euthanasia in the

elderly, women, the uninsured,

people with low educational status,

the poor, the physically and mentally

disabled, the chronically ill or

unconscious, minors, people with

psychiatric illnesses including

depression, or racial or ethnic

minorities compared with

background populations.108

In Oregon, futile or

disproportionately burdensome

treatments, including ANH, may be

withheld or interrupted under

specified circumstances and only

with the informed consent of the

patient or, as in the case of VS, with

the informed consent of the legal

surrogate.The United States Patient

Self Determination Act does not

address quality of life issues and

does not make a clear distinction

between active and passive

euthanasia when there is clear and

convincing evidence that the

informed consent to euthanasia,

passive or active, has been obtained

from a competent patient or the legal

surrogate of an incompetent patient.

Active euthanasia is explicitly

illegal in Australia, Austria, China,

Denmark, Finland, France, Ireland,

Italy, Latvia, Lithuania, New Zealand,

Norway, the Philippines, Russia,

Spain, Turkey, and the United

Kingdom, though some will allow

access to advanced care directive

options and offer reduced penalties

for those who assist patients in

dying. In Denmark and France, a sort

of “Right to Die with Dignity” act is

under debate.92

Passive euthanasia, as described

earlier, is legal in India, Sweden, and

Ireland. Moreover, passive euthanasia

is tolerated in the United States,

Mexico, Canada, Israel, Argentina,

Hungary, Finland, Thailand (even for

foreign individuals), Portugal (with

the exception of ANH interruption,

which is not allowed), and Germany.

In Japan, there is a law plan for

active euthanasia and PAS. The plan

includes clauses related to an

unbearable and untreatable suffering

(for which the physician must have

ineffectively exhausted all other

measures of pain relief), inevitable

and approaching death, and a written

consent (living wills and family

consent will not suffice).

Interestingly, Japan’s government

instituted “bioethics SWAT teams,”

which are made available to the

families of terminally ill patients in

order to help them, along with the

doctors, come to an informed

decision based on the personal facts

of the case. In Mexico, terminally ill

patients or, if they are unconscious,

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their closest relatives are permitted

to refuse medication or further

medical treatment to extend life in

Mexico City, the central state of

Aguascalientes, and the Western

state of Michoacán.92,108–110

In Italy, active euthanasia is under

the penal law (as being equated to

intentional homicide), as is assisted

suicide. Nevertheless, the extensive

use of pain-relieving drugs, which

could cause premature death (i.e.,

indirect euthanasia), is not

considered a form of euthanasia;

neither is the abstention from

aggressive treatments (i.e., those

therapies that can only prolong a

state without chances of

amelioration). The Italian

government is still in the

developmental stage in regard to

right to die policy, but theirs is

mainly directed at limiting an

individual’s personal autonomy and

the possibility of writing a personal

living will. Indeed, advanced care

directives, which are not yet broadly

recognized in Italy, probably

represent the best way to safeguard

the principle of autonomy.

AUTHORS’ POINT OF VIEW AND

FUTURE PERSPECTIVES

We believe that all patients with

DOC (i.e., their surrogates) should

be put in the position to freely

choose their own way to end their

lives, in full respect of the personal

and inviolable principles of the

dignity and sanctity of human life. In

our opinion, all patients should be

free to manage their own deaths, or

to empower someone to do it if they

are incapacitated, when they

perceive their quality of life as

severely impaired by physical or

psychological suffering (e.g.,

incontinence, nausea and vomiting,

breathlessness, paralysis, difficulty in

swallowing, depression, fearing a loss

of control or dignity, feeling like a

burden, having a dislike for being

dependent) and when there is no

chance of improvement.

It is urgent that governments

establish safeguards, criteria, and

protocol that protect the right to a

worthy death (in keeping the

patient’s lucid and conscious will and

the personal concepts of dignity and

the sanctity of life), ensure societal

oversight, and prevent euthanasia

and PAS from being abused or

misused (i.e., moving from being a

measure of ‘last resort to one of early

intervention).111 In fact, euthanasia is

progressively moving from terminally

ill people to those who are

chronically ill, and from physical

illness to mental illness or

psychological distress or suffering

(even “tired of living”), and from

conscious to unconscious patients.

This means that the actual laws may

fail to detect and prevent situations

in which people could be subjected

to undue pressure to access or

provide euthanasia and could

circumvent the safeguards that are in

place.

A balanced law should guarantee

and regulate the access to

euthanasia/PAS. Such laws should

require that all patients and their

surrogates are properly educated

regarding the law and their rights

and are capable of making ELDs.

Hence, ELDs must be voluntary, well

considered, informed, and, above all,

persistent over time. The requesting

person must have provided explicit,

written consent and must be

competent at the time the request

was made. In this regard, some states

require that the voluntariness of the

request has to be confirmed by at

least two witnesses.

A law would avoid non-voluntary

euthanasia in patients with DOC by

confirming the lack of chances of

recovery based on an accurate

clinical assessment corroborated by

advanced paraclinical approaches

and by demonstrating the will of the

patient to not live in such a

condition. In cases with no living will

in place, the best interest of the

patient should be pursued according

to evidence-based medicine and the

opinion of the patient’s surrogate.

The role of the physician is

imperative when making informed

ELDs. Indeed, the so-called

“therapeutic alliance” between the

patient and doctor should be

fundamental in ELD (as well as in

life) and only when this alliance

enforces the patient’s autonomy.

Physicians have a great responsibility

to use their knowledge and skill in

the primary interest of their patients,

and should not only aim to relieve

the burden of sorrow but also strive

to educate and enable patients and

their loved ones to understand,

evaluate, and make their own choices

concerning ELD. Only trained

healthcare clinicians can make

evidence-based diagnoses and

prognoses of DOC conditions, thus

the determination made by the

physician on whether a DOC patient

has any chance to improve is

evidence-based and carefully

considered. The pivotal role the

medical staff plays in ELDs has been

highlighted and regulated in

countries where euthanasia and/or

PAS are legal. Switzerland, however,

allows non-physicians to assist in

suicide. In the Netherlands and

Belgium, a second doctor must see

the patient to confirm the request to

die is valid and the suffering

unbearable, and a network of doctors

is trained to undertake these

consultations. In the United States,

in all five of the states that allow

PAS, it is required that a second

doctor must examine the patient to

confirm the terminal illness before

the request is approved. In Oregon,

Washington, and Vermont, the

patient must also see a mental health

professional when either the

attending or consulting doctor

suspects that the patient may be

suffering from a psychological

disorder (such as depression) that is

impairing his or her judgement. In

addition, ad hoc committees (even if

this is delayed) are used to revise

cases with potential mistakes in the

euthanasia or PAS procedures.

Unfortunately, these committees are

largely underutilized.

Governments and magistrates

must work to establish and

communicate the proper protocol for

ELDs to their citizens in order to

guarantee the rights of patients to a

Innovations in CLINICAL NEUROSCIENCE [ V O L U M E 1 3 , N U M B E R 1 1 – 1 2 , N O V E M B E R – D E C E M B E R 2 0 1 6 21

peaceful and worthy death and to

limit SSA. Indeed, no additional

requirement relating to the patient’s

experience of the disease or any

minimum level of suffering would

easily extend the application of

euthanasia. On the other hand,

narrowing euthanasia to unbearable

suffering would limit the accessibility

of the right to die for all the other

patients. Likewise, limiting the right

to die from a terminal illness (as in

the United States) could result in the

courts excluding patients with VS

from this right, given that they are

not terminally ill and their prognosis

can only be established with

sufficient confidence using advanced,

non-standard neurophysiological or

neuroimaging approaches. In

addition, the acceptance of solely

passive or indirect euthanasia for

patients in VS would limit their

accessibility to their right to die. In

fact, these patients deserve the same

accessibility to the right to die as

other people and do not deserve a

“worse” euthanasia than the others

(i.e., a slow and agonizing death

because of starvation and

dehydration).

Finally, the people who have the

duty of informing and educating the

public seek to help people cope with

the finiteness of the human

condition, the intrinsic limits of

medicine, and the responsibility to

explore the values surrounding

ELDs.

Hence, there is no reason why any

single moral view of physicians,

magistrates, politicians, or educators

should prevail. A conciliation of the

different currents of thought on

euthanasia may be reached by

placing, at the center, the patient’s

rights to freely manage his or her life

and death while keeping the

principles of dignity and sanctity of

human life intact. ELDs should be

guaranteed in patients with DOCs

when negative prognoses have been

well defined, possibly through the

use of advanced neurophysiological

and functional neuroimaging

techniques, and the desires of the

patients to not live in such

conditions have been clearly

expressed by living wills or by

surrogates. Finally, ad hoc

committees to oversee the proper

access and application of euthanasia

should be instituted and potentiated.

ACKNOWLEDGMENT

The authors would like to thank

Prof. Anthony Pettignano for his

editing services.

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