Calculating Simple Linear Regression

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Simple linear regression is a procedure that provides an estimate of the value of a dependent variable (outcome) based on the value of an independent variable (predictor). Knowing that estimate with some degree of accuracy, we can use regression analysis to predict the value of one variable if we know the value of the other variable (Cohen & Cohen, 1983). The regression equation is a mathematical expression of the influence that a predictor has on a dependent variable, based on some theoretical framework. For example, in Exercise 14, Figure 14-1 illustrates the linear relationship between gestational age and birth weight. As shown in the scatterplot, there is a strong positive relationship between the two variables. Advanced gestational ages predict higher birth weights.

A regression equation can be generated with a data set containing subjects’ x and y values. Once this equation is generated, it can be used to predict future subjects’ y values, given only their x values. In simple or bivariate regression, predictions are made in cases with two variables. The score on variable y (dependent variable, or outcome) is predicted from the same subject’s known score on variable x (independent variable, or predictor).

Research Designs Appropriate for Simple Linear Regression
Research designs that may utilize simple linear regression include any associational design (Gliner et al., 2009). The variables involved in the design are attributional, meaning the variables are characteristics of the participant, such as health status, blood pressure, gender, diagnosis, or ethnicity. Regardless of the nature of variables, the dependent variable submitted to simple linear regression must be measured as continuous, at the interval or ratio level.

Statistical Formula and Assumptions
Use of simple linear regression involves the following assumptions (Zar, 2010):

  1. Normal distribution of the dependent (y) variable
  2. Linear relationship between x and y
  3. Independent observations
  4. No (or little) multicollinearity
  5. Homoscedasticity

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Data that are homoscedastic are evenly dispersed both above and below the regression line, which indicates a linear relationship on a scatterplot. Homoscedasticity reflects equal variance of both variables. In other words, for every value of x, the distribution of y values should have equal variability. If the data for the predictor and dependent variable are not homoscedastic, inferences made during significance testing could be invalid (Cohen & Cohen, 1983; Zar, 2010). Visual examples of homoscedasticity and heteroscedasticity are presented in Exercise 30.

In simple linear regression, the dependent variable is continuous, and the predictor can be any scale of measurement; however, if the predictor is nominal, it must be correctly coded. Once the data are ready, the parameters a and b are computed to obtain a regression equation. To understand the mathematical process, recall the algebraic equation for a straight line:

y=bx+a

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where

y=the dependent variable(outcome)

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x=the independent variable(predictor)

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b=the slope of the line

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a=y-intercept(the point where the regression line intersects the y-axis)

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No single regression line can be used to predict with complete accuracy every y value from every x value. In fact, you could draw an infinite number of lines through the scattered paired values (Zar, 2010). However, the purpose of the regression equa­tion is to develop the line to allow the highest degree of prediction possible—the line of best fit. The procedure for developing the line of best fit is the method of least squares. The formulas for the beta (β) and slope (α) of the regression equation are computed as follows. Note that once the β is calculated, that value is inserted into the formula for α.

β=n∑xy−∑x∑yn∑x 2 −(∑x) 2

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α=∑y−b∑xn

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Hand Calculations
This example uses data collected from a study of students enrolled in a registered nurse to bachelor of science in nursing (RN to BSN) program (Mancini, Ashwill, & Cipher, 2014). The predictor in this example is number of academic degrees obtained by the student prior to enrollment, and the dependent variable was number of months it took for the student to complete the RN to BSN program. The null hypothesis is “Number of degrees does not predict the number of months until completion of an RN to BSN program.”

The data are presented in Table 29-1. A simulated subset of 20 students was selected for this example so that the computations would be small and manageable. In actuality, studies involving linear regression need to be adequately powered (Aberson, 2010; Cohen, 1988). Observe that the data in Table 29-1 are arranged in columns that correspond to 321the elements of the formula. The summed values in the last row of Table 29-1 are inserted into the appropriate place in the formula for b.

TABLE 29-1

ENROLLMENT GPA AND MONTHS TO COMPLETION IN AN RN TO BSN PROGRAM

Student ID x y x2 xy
(Number of Degrees) (Months to Completion)
1 1 17 1 17
2 2 9 4 18
3 0 17 0 0
4 1 9 1 9
5 0 16 0 0
6 1 11 1 11
7 0 15 0 0
8 0 12 0 0
9 1 15 1 15
10 1 12 1 12
11 1 14 1 14
12 1 10 1 10
13 1 17 1 17
14 0 20 0 0
15 2 9 4 18
16 2 12 4 24
17 1 14 1 14
18 2 10 4 20
19 1 17 1 17
20 2 11 4 22
sum Σ 20 267 30 238
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The computations for the b and α are as follows:

Step 1: Calculate b.
From the values in Table 29-1, we know that n = 20, Σx = 20, Σy = 267, Σx2 = 30, and Σxy = 238. These values are inserted into the formula for b, as follows:

b=20(238)−(20)(267)20(30)−20 2

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b=−2.9

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Step 2: Calculate α.
From Step 1, we now know that b = −2.9, and we plug this value into the formula for α.

α=267−(−2.9)(20)20

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α=16.25

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Step 3: Write the new regression equation:

y=−2.9x+16.25

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Step 4: Calculate R.
The multiple R is defined as the correlation between the actual y values and the predicted y values using the new regression equation. The predicted y value using the new equation is represented by the symbol ŷ to differentiate from y, which represents the actual y values in the data set. We can use our new regression equation from Step 3 to compute predicted program completion time in months for each student, using their number of academic degrees prior to enrollment in the RN to BSN Program. For example, Student #1 had earned 1 academic degree prior to enrollment, and the predicted months to completion for Student 1 is calculated as:

y ̂ =−2.9(1)+16.25

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y ̂ =13.35

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Thus, the predicted ŷ is 13.35 months. This procedure would be continued for the rest of the students, and the Pearson correlation between the actual months to completion (y) and the predicted months to completion (ŷ) would yield the multiple R value. In this example, the R = 0.638. The higher the R, the more likely that the new regression equation accurately predicts y, because the higher the correlation, the closer the actual y values are to the predicted ŷ values. Figure 29-1 displays the regression line where the x axis represents possible numbers of degrees, and the y axis represents the predicted months to program completion (ŷ values).

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FIGURE 29-1 REGRESSION LINE REPRESENTED BY NEW REGRESSION EQUATION.
Step 5: Determine whether the predictor significantly predicts y.

t=Rn−21−R 2 ‾ ‾ ‾ ‾ √

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To know whether the predictor significantly predicts y, the beta must be tested against zero. In simple regression, this is most easily accomplished by using the R value from Step 4:

t=.638200−21−.407 ‾ ‾ ‾ ‾ ‾ √

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t=3.52

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The t value is then compared to the t probability distribution table (see Appendix A). The df for this t statistic is n − 2. The critical t value at alpha (α) = 0.05, df = 18 is 2.10 for a two-tailed test. Our obtained t was 3.52, which exceeds the critical value in the table, thereby indicating a significant association between the predictor (x) and outcome (y).

Step 6: Calculate R2.
After establishing the statistical significance of the R value, it must subsequently be examined for clinical importance. This is accomplished by obtaining the coefficient of determination for regression—which simply involves squaring the R value. The R2 represents the percentage of variance explained in y by the predictor. Cohen describes R2 values of 0.02 as small, 0.15 as moderate, and 0.26 or higher as large effect sizes (Cohen, 1988). In our example, the R was 0.638, and, therefore, the R2 was 0.407. Multiplying 0.407 × 100% indicates that 40.7% of the variance in months to program completion can be explained by knowing the student’s number of earned academic degrees at admission (Cohen & Cohen, 1983).
The R2 can be very helpful in testing more than one predictor in a regression model. Unlike R, the R2 for one regression model can be compared with another regression model that contains additional predictors (Cohen & Cohen, 1983). The R2 is discussed further in Exercise 30.
The standardized beta (β) is another statistic that represents the magnitude of the association between x and y. β has limits just like a Pearson r, meaning that the standardized β cannot be lower than −1.00 or higher than 1.00. This value can be calculated by hand but is best computed with statistical software. The standardized beta (β) is calculated by converting the x and y values to z scores and then correlating the x and y value using the Pearson r formula. The standardized beta (β) is often reported in literature instead of the unstandardized b, because b does not have lower or upper limits and therefore the magnitude of b cannot be judged. β, on the other hand, is interpreted as a Pearson r and the descriptions of the magnitude of β can be applied, as recommended by Cohen (1988). In this example, the standardized beta (β) is −0.638. Thus, the magnitude of the association between x and y in this example is considered a large predictive association (Cohen, 1988).

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SPSS Computations
This is how our data set looks in SPSS.

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Step 1: From the “Analyze” menu, choose “Regression” and “Linear.”

Step 2: Move the predictor, Number of Degrees, to the space labeled “Independent(s).” Move the dependent variable, Number of Months to Completion, to the space labeled “Dependent.” Click “OK.”

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Interpretation of SPSS Output
The following tables are generated from SPSS. The first table contains the multiple R and the R2 values. The multiple R is 0.638, indicating that the correlation between the actual y values and the predicted y values using the new regression equation is 0.638. The R2 is 0.407, indicating that 40.7% of the variance in months to program completion can be explained by knowing the student’s number of earned academic degrees at enrollment.

Regression
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The second table contains the ANOVA table. As presented in Exercises 18 and 33, the ANOVA is usually performed to test for differences between group means. However, ANOVA can also be performed for regression, where the null hypothesis is that “knowing the value of x explains no information about y”. This table indicates that knowing the value of x explains a significant amount of variance in y. The contents of the ANOVA table are rarely reported in published manuscripts, because the significance of each predictor is presented in the last SPSS table titled “Coefficients” (see below).

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The third table contains the b and a values, standardized beta (β), t, and exact p value. The a is listed in the first row, next to the label “Constant.” The β is listed in the second row, next to the name of the predictor. The remaining information that is important to extract when interpreting regression results can be found in the second row. The standardized beta (β) is −0.638. This value has limits just like a Pearson r, meaning that the standardized β cannot be lower than −1.00 or higher than 1.00. The t value is −3.516, and the exact p value is 0.002.

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Final Interpretation in American Psychological Association (APA) Format
The following interpretation is written as it might appear in a research article, formatted according to APA guidelines (APA, 2010). Simple linear regression was performed with number of earned academic degrees as the predictor and months to program completion as the dependent variable. The student’s number of degrees significantly predicted months to completion among students in an RN to BSN program, β = −0.638, p = 0.002, and R2 = 40.7%. Higher numbers of earned academic degrees significantly predicted shorter program completion time.

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Study Questions

  1. If you have access to SPSS, compute the Shapiro-Wilk test of normality for months to completion (as demonstrated in Exercise 26). If you do not have access to SPSS, plot the frequency distributions by hand. What do the results indicate?
  2. State the null hypothesis for the example where number of degrees was used to predict time to BSN program completion.
  3. In the formula y = bx + a, what does “b” represent?
  4. In the formula y = bx + a, what does “a” represent?
  5. Using the new regression equation, ŷ = −2.9x + 16.25, compute the predicted months to program completion if a student’s number of earned degrees is 0. Show your calculations.
  6. Using the new regression equation, ŷ = −2.9x + 16.25, compute the predicted months to program completion if a student’s number of earned degrees is 2. Show your calculations.

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  1. What was the correlation between the actual y values and the predicted y values using the new regression equation in the example?
  2. What was the exact likelihood of obtaining a t value at least as extreme as or as close to the one that was actually observed, assuming that the null hypothesis is true?
  3. How much variance in months to completion is explained by knowing the student’s number of earned degrees?
  4. How would you characterize the magnitude of the R2 in the example? Provide a rationale for your answer.

Computational Practice

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Using the example from Mancini and colleagues (2014), students enrolled in an RN to BSN program were assessed for demographics at enrollment. The predictor in this example is age at program enrollment, and the dependent variable was number of months it took for the student to complete the RN to BSN program. The null hypothesis is: “Student age at enrollment does not predict the number of months until completion of an RN to BSN program.” The data are presented in Table 29-2. A simulated subset of 20 students was randomly selected for this example so that the computations would be small and manageable.

TABLE 29-2

AGE AT ENROLLMENT AND MONTHS TO COMPLETION IN AN RN TO BSN PROGRAM

Student ID x y x2 xy
(Student Age) (Months to Completion)
1 23 17 529 391
2 24 9 576 216
3 24 17 576 408
4 26 9 676 234
5 31 16 961 496
6 31 11 961 341
7 32 15 1,024 480
8 33 12 1,089 396
9 33 15 1,089 495
10 34 12 1,156 408
11 34 14 1,156 476
12 35 10 1,225 350
13 35 17 1,225 595
14 39 20 1,521 780
15 40 9 1,600 360
16 42 12 1,764 504
17 42 14 1,764 588
18 44 10 1,936 440
19 51 17 2,601 867
20 24 11 576 264
sum Σ 677 267 24,005 9,089
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Name: ___________________________________________ Class: _________

Date: _______________________________________________________________________

Follow your instructor’s directions to submit your answers to the following questions for grading. Your instructor may ask you to write your answers below and submit them as a hard copy for grading. Alternatively, your instructor may ask you to use the space below for notes and submit your answers.

  1. If you have access to SPSS, compute the Shapiro-Wilk test of normality for the variable age (as demonstrated in Exercise 26). If you do not have access to SPSS, plot the frequency distributions by hand. What do the results indicate?
  2. State the null hypothesis where age at enrollment is used to predict the time for completion of an RN to BSN program.
  3. What is b as computed by hand (or using SPSS)?
  4. What is a as computed by hand (or using SPSS)?

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  1. Write the new regression equation.
  2. How would you characterize the magnitude of the obtained R2 value? Provide a rationale for your answer.
  3. How much variance in months to RN to BSN program completion is explained by knowing the student’s enrollment age?
  4. What was the correlation between the actual y values and the predicted y values using the new regression equation in the example?
  5. Write your interpretation of the results as you would in an APA-formatted journal.
  6. Given the results of your analyses, would you use the calculated regression equation to predict future students’ program completion time by using enrollment age as x? Provide

(Grove 319-332)

Grove, Susan K., Daisha Cipher. Statistics for Nursing Research: A Workbook for Evidence-Based Practice, 2nd Edition. Saunders, 022016. VitalBook file.

The citation provided is a guideline. Please check each citation for accuracy before use.

Assignment: Assessing, Diagnosing, And Treating Adults With Mood Disorders/NRNP 6665

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Assignment: Assessing, Diagnosing, And Treating Adults With Mood Disorders/NRNP 6665

Assignment: Assessing, Diagnosing, and Treating Adults With Mood Disorders

Photo Credit: Monkey Business / Adobe Stock
It is important for the PMHNP to have a comprehensive understanding of mood disorders in order to assess and accurately formulate a diagnosis and treatment plan for patients presenting with these disorders. Mood disorders may be diagnosed when a patient’s emotional state meets the diagnostic criteria for severity, functional impact, and length of time. Those with a mood disorder may find that their emotions interfere with work, relationships, or other parts of their lives that impact daily functioning. Mood disorders may also lead to substance abuse or suicidal thoughts or behaviors, and although they are not likely to go away on their own, they can be managed with an effective treatment plan and understanding of how to manage symptoms.
In this Assignment you will assess, diagnose, and devise a treatment plan for a patient in a case study who is presenting with a mood disorder. Assignment: Assessing, Diagnosing, And Treating Adults With Mood Disorders/NRNP 6665
To Prepare
• Review this week’s Learning Resources. Consider the insights they provide about assessing, diagnosing, and treating mood disorders.
• Review the Focused SOAP Note template, which you will use to complete this Assignment. There is also a Focused SOAP Note Exemplar provided as a guide for Assignment expectations.
• Review the video, Case Study: Petunia Park. You will use this case as the basis of this Assignment. In this video, a Walden faculty member is assessing a mock patient. The patient will be represented onscreen as an avatar.
• Consider what history would be necessary to collect from this patient.
• Consider what interview questions you would need to ask this patient. Assignment: Assessing, Diagnosing, And Treating Adults With Mood Disorders/NRNP 6665
• Consider patient diagnostics missing from the video:
• Provider Review outside of interview:
• Temp 98.2 Pulse 90 Respiration 18 B/P 138/88
• Laboratory Data Available: Urine drug and alcohol screen negative. CBC within normal ranges, CMP within normal ranges. Lipid panel within normal ranges. Prolactin Level 8; TSH 6.3 (H)
The Assignment
Develop a Focused SOAP Note, including your differential diagnosis and critical-thinking process to formulate a primary diagnosis. Incorporate the following into your responses in the template:
• Subjective: What details did the patient provide regarding their chief complaint and symptomatology to derive your differential diagnosis? What is the duration and severity of their symptoms? How are their symptoms impacting their functioning in life?
• Objective: What observations did you make during the psychiatric assessment?
• Assessment: Discuss the patient’s mental status examination results. What were your differential diagnoses? Provide a minimum of three possible diagnoses with supporting evidence, listed in order from highest to lowest priority. Compare the DSM-5 diagnostic criteria for each differential diagnosis and explain what DSM-5 criteria rules out the differential diagnosis to find an accurate diagnosis. Explain the critical-thinking process that led you to the primary diagnosis you selected. Include pertinent positives and pertinent negatives for the specific patient case.
• Plan: What is your plan for psychotherapy? What is your plan for treatment and management, including alternative therapies? Include pharmacologic and nonpharmacologic treatments, alternative therapies, and follow-up parameters as well as a rationale for this treatment and management plan. Also incorporate one health promotion activity and one patient education strategy. Assignment: Assessing, Diagnosing, And Treating Adults With Mood Disorders/NRNP 6665

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• Reflection notes: What would you do differently with this client if you could conduct the session again? Discuss what your next intervention would be if you were able to follow up with this patient. Also include in your reflection a discussion related to legal/ethical considerations (demonstrate critical thinking beyond confidentiality and consent for treatment!), health promotion, and disease prevention that takes into consideration patient factors (such as age, ethnic group, etc.), PMH, and other risk factors (e.g., socioeconomic, cultural background, etc.).
By Day 7 of Week 4

INSTRUCTIONS ON HOW TO USE EXEMPLAR AND TEMPLATE—READ CAREFULLY

If you are struggling with the format or remembering what to include, follow the Focused SOAP Note Evaluation Template AND the Rubric as your guide.  It is also helpful to review the rubric in detail in order not to lose points unnecessarily because you missed something required.  After reviewing full details of the rubric, you can use it as a guide.

In the Subjective section, provide:

  • Chief complaint
  • History of present illness (HPI)
  • Past psychiatric history
  • Medication trials and current medications
  • Psychotherapy or previous psychiatric diagnosis
  • Pertinent substance use, family psychiatric/substance use, social, and medical history
  • Allergies
  • ROS

Read rating descriptions to see the grading standards! 

In the Objective section, provide:

  • Physical exam documentation of systems pertinent to the chief complaint, HPI, and history
  • Diagnostic results, including any labs, imaging, or other assessments needed to develop the differential diagnoses. Assignment: Assessing, Diagnosing, And Treating Adults With Mood Disorders/NRNP 6665

Read rating descriptions to see the grading standards!

In the Assessment section, provide:

  • Results of the mental status examination, presented in paragraph form.
  • At least three differentials with supporting evidence. List them from top priority to least priority. Compare the DSM-5 diagnostic criteria for each differential diagnosis and explain what DSM-5 criteria rules out the differential diagnosis to find an accurate diagnosis. Explain the critical-thinking process that led you to the primary diagnosis you selected. Include pertinent positives and pertinent negatives for the specific patient case.
  • Read rating descriptions to see the grading standards! Assignment: Assessing, Diagnosing, And Treating Adults With Mood Disorders/NRNP 6665

Reflect on this case. Include: Discuss what you learned and what you might do differently. Also include in your reflection a discussion related to legal/ethical considerations (demonstrate critical thinking beyond confidentiality and consent for treatment!), health promotion and disease prevention taking into consideration patient factors (such as age, ethnic group, etc.), PMH, and other risk factors (e.g., socioeconomic, cultural background, etc.).

(The FOCUSED SOAP psychiatric evaluation is typically the follow-up visit patient note. You will practice writing this type of note in this course. You will be focusing more on the symptoms from your differential diagnosis from the comprehensive psychiatric evaluation narrowing to your diagnostic impression. You will write up what symptoms are present and what symptoms are not present from illnesses to demonstrate you have indeed assessed for illnesses which could be impacting your patient. For example, anxiety symptoms, depressive symptoms, bipolar symptoms, psychosis symptoms, substance use, etc.)

EXEMPLAR BEGINS HERE

Subjective:

CC (chief complaint): A brief statement identifying why the patient is here. This statement is verbatim of the patient’s own words about why presenting for assessment. For a patient with dementia or other cognitive deficits, this statement can be obtained from a family member.

HPI: Begin this section with patient’s initials, age, race, gender, purpose of evaluation, current medication and referral reason. For example:

N.M. is a 34-year-old Asian male presents for medication management follow up for anxiety. He was initiated sertraline last appt which he finds was effective for two weeks then symptoms began to return.

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Or

P.H., a 16-year-old Hispanic female, presents for follow up to discuss previous psychiatric evaluation for concentration difficulty. She is not currently prescribed psychotropic medications as we deferred until further testing and screening was conducted.

Then, this section continues with the symptom analysis for your note. Thorough documentation in this section is essential for patient care, coding, and billing analysis.

Paint a picture of what is wrong with the patient. First what is bringing the patient to your follow up evaluation? Document symptom onset, duration, frequency, severity, and impact. What has worsened or improved since last appointment? What stressors are they facing? Your description here will guide your differential diagnoses into your diagnostic impression. You are seeking symptoms that may align with many DSM-5 diagnoses, narrowing to what aligns with diagnostic criteria for mental health and substance use disorders.

Substance Use History: This section contains any history or current use of caffeine, nicotine, illicit substance (including marijuana), and alcohol. Include the daily amount of use and last known use. Include type of use such as inhales, snorts, IV, etc. Include any histories of withdrawal complications from tremors, Delirium Tremens, or seizures.

Current Medications: Include dosage, frequency, length of time used, and reason for use. Also include OTC or homeopathic products. Assignment: Assessing, Diagnosing, And Treating Adults With Mood Disorders/NRNP 6665

Allergies: Include medication, food, and environmental allergies separately. Provide a description of what the allergy is (e.g., angioedema, anaphylaxis). This will help determine a true reaction vs. intolerance.

Reproductive Hx: Menstrual history (date of LMP), Pregnant (yes or no), Nursing/lactating (yes or no), contraceptive use (method used), types of intercourse:  oral, anal, vaginal, other, any sexual concerns

ROS: Cover all body systems that may help you include or rule out a differential diagnosis.  Please note: THIS IS DIFFERENT from a physical examination!

You should list each system as follows: General: Head: EENT: etc. You should list these in bullet format and document the systems in order from head to toe.

Example of Complete ROS:

GENERAL: No weight loss, fever, chills, weakness, or fatigue.

HEENT: Eyes: No visual loss, blurred vision, double vision, or yellow sclerae. Ears, Nose, Throat: No hearing loss, sneezing, congestion, runny nose, or sore throat.

SKIN: No rash or itching.

CARDIOVASCULAR: No chest pain, chest pressure, or chest discomfort. No palpitations or edema.

RESPIRATORY: No shortness of breath, cough, or sputum.

GASTROINTESTINAL: No anorexia, nausea, vomiting, or diarrhea. No abdominal pain or blood.

GENITOURINARY: Burning on urination, urgency, hesitancy, odor, odd color

NEUROLOGICAL: No headache, dizziness, syncope, paralysis, ataxia, numbness, or tingling in the extremities. No change in bowel or bladder control.

MUSCULOSKELETAL: No muscle, back pain, joint pain, or stiffness.

HEMATOLOGIC: No anemia, bleeding, or bruising.

LYMPHATICS: No enlarged nodes. No history of splenectomy.

ENDOCRINOLOGIC: No reports of sweating, cold, or heat intolerance. No polyuria or polydipsia.

Objective:

Diagnostic results: Include any labs, X-rays, or other diagnostics that are needed to develop the differential diagnoses (support with evidenced and guidelines). Assignment: Assessing, Diagnosing, And Treating Adults With Mood Disorders/NRNP 6665

Assessment:

Mental Status Examination: For the purposes of your courses, this section must be presented in paragraph form and not use of a checklist! This section you will describe the patient’s appearance, attitude, behavior, mood and affect, speech, thought processes, thought content, perceptions (hallucinations, pseudohallucinations, illusions, etc.)., cognition, insight, judgment, and SI/HI. See an example below. You will modify to include the specifics for your patient on the above elements—DO NOT just copy the example. You may use a preceptor’s way of organizing the information if the MSE is in paragraph form.

He is an 8-year-old African American male who looks his stated age. He is cooperative with examiner. He is neatly groomed and clean, dressed appropriately. There is no evidence of any abnormal motor activity. His speech is clear, coherent, normal in volume and tone. His thought process is goal directed and logical. There is no evidence of looseness of association or flight of ideas. His mood is euthymic, and his affect appropriate to his mood. He was smiling at times in an appropriate manner. He denies any auditory or visual hallucinations. There is no evidence of any delusional thinking.   He denies any current suicidal or homicidal ideation. Cognitively, he is alert and oriented. His recent and remote memory is intact. His concentration is good. His insight is good.

Diagnostic Impression: You must begin to narrow your differential diagnosis to your diagnostic impression.  You must explain how and why (your rationale) you ruled out any of your differential diagnoses. You must explain how and why (your rationale) you concluded to your diagnostic impression.  You will use supporting evidence from the literature to support your rationale. Include pertinent positives and pertinent negatives for the specific patient case.

Also included in this section is the reflection. Reflect on this case and discuss whether or not you agree with your preceptor’s assessment and diagnostic impression of the patient and why or why not. What did you learn from this case? What would you do differently?

Also include in your reflection a discussion related to legal/ethical considerations (demonstrating critical thinking beyond confidentiality and consent for treatment!), health promotion and disease prevention taking into consideration patient factors (such as age, ethnic group, etc.), PMH, and other risk factors (e.g., socioeconomic, cultural background, etc.).

Case Formulation and Treatment Plan

Includes documentation of diagnostic studies that will be obtained, referrals to other health care providers, therapeutic interventions including psychotherapy and/or psychopharmacology, education, disposition of the patient, and any planned follow-up visits. Each diagnosis or condition documented in the assessment should be addressed in the plan. The details of the plan should follow an orderly manner.  *See an example below. You will modify to your practice so there may be information excluded/included. If you are completing this for a practicum, what does your preceptor document?

Risks and benefits of medications are discussed including non- treatment. Potential side effects of medications discussed (be detailed in what side effects discussed). Informed client not to stop medication abruptly without discussing with providers. Instructed to call and report any adverse reactions. Discussed risk of medication with pregnancy/fetus, encouraged birth control, discussed if does become pregnant to inform provider as soon as possible. Discussed how some medications might decreased birth control pill, would need back up method (exclude for males).

 

Discussed risks of mixing medications with OTC drugs, herbal, alcohol/illegal drugs. Instructed to avoid this practice. Encouraged abstinence. Discussed how drugs/alcohol affect mental health, physical health, sleep architecture.

 

Initiation of (list out any medication and why prescribed, any therapy services or referrals to specialist): Assignment: Assessing, Diagnosing, And Treating Adults With Mood Disorders/NRNP 6665

 

Client was encouraged to continue with case management and/or therapy services (if not provided by you)

 

Client has emergency numbers:  Emergency Services 911, the  Client’s Crisis Line 1-800-_______. Client instructed to go to nearest ER or call 911 if they become actively suicidal and/or homicidal. (only if you or preceptor provided them)

 

Reviewed hospital records/therapist records for collaborative information; Reviewed PMP report (only if actually completed)

 

Time allowed for questions and answers provided. Provided supportive listening. Client appeared to understand discussion. Client is amenable with this plan and agrees to follow treatment regimen as discussed. (this relates to informed consent; you will need to assess their understanding and agreement) Assignment: Assessing, Diagnosing, And Treating Adults With Mood Disorders/NRNP 6665

 

Follow up with PCP as needed and/or for:

 

Labs ordered and/or reviewed (write out what diagnostic test ordered, rationale for ordering, and if discussed fasting/non fasting or other patient education)

 

Return to clinic:

Continued treatment is medically necessary to address chronic symptoms, improve functioning, and prevent the need for a higher level of care.

 

References (move to begin on next page)

You are required to include at least three evidence-based, peer-reviewed journal articles or evidenced-based guidelines which relate to this case to support your diagnostics and differentials diagnoses. Be sure to use correct APA 7th edition formatting. Assignment: Assessing, Diagnosing, And Treating Adults With Mood Disorders/NRNP 6665

 

 

 

Calculating Pearson Chi-Square

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The Pearson chi-square test (χ2) compares differences between groups on variables measured at the nominal level. The χ2 compares the frequencies that are observed with the frequencies that are expected. When a study requires that researchers compare proportions (percentages) in one category versus another category, the χ2 is a statistic that will reveal if the difference in proportion is statistically improbable.

A one-way χ2 is a statistic that compares different levels of one variable only. For example, a researcher may collect information on gender and compare the proportions of males to females. If the one-way χ2 is statistically significant, it would indicate that proportions of one gender are significantly higher than proportions of the other gender than what would be expected by chance (Daniel, 2000). If more than two groups are being examined, the χ2 does not determine where the differences lie; it only determines that a significant difference exists. Further testing on pairs of groups with the χ2 would then be warranted to identify the significant differences.

A two-way χ2 is a statistic that tests whether proportions in levels of one nominal variable are significantly different from proportions of the second nominal variable. For example, the presence of advanced colon polyps was studied in three groups of patients: those having a normal body mass index (BMI), those who were overweight, and those who were obese (Siddiqui, Mahgoub, Pandove, Cipher, & Spechler, 2009). The research question tested was: “Is there a difference between the three groups (normal weight, overweight, and obese) on the presence of advanced colon polyps?” The results of the χ2 test indicated that a larger proportion of obese patients fell into the category of having advanced colon polyps compared to normal weight and overweight patients, suggesting that obesity may be a risk factor for developing advanced colon polyps. Further examples of two-way χ2 tests are reviewed in Exercise 19.

Research Designs Appropriate for the Pearson χ2
Research designs that may utilize the Pearson χ2 include the randomized experimental, quasi-experimental, and comparative designs (Gliner, Morgan, & Leech, 2009). The variables may be active, attributional, or a combination of both. An active variable refers to an intervention, treatment, or program. An attributional variable refers to a characteristic of the participant, such as gender, diagnosis, or ethnicity. Regardless of the whether the variables are active or attributional, all variables submitted to χ2 calculations must be measured at the nominal level.

410
Statistical Formula and Assumptions
Use of the Pearson χ2 involves the following assumptions (Daniel, 2000):

  1. Only one datum entry is made for each subject in the sample. Therefore, if repeated measures from the same subject are being used for analysis, such as pretests and posttests, χ2 is not an appropriate test.
  2. The variables must be categorical (nominal), either inherently or transformed to categorical from quantitative values.
  3. For each variable, the categories are mutually exclusive and exhaustive. No cells may have an expected frequency of zero. In the actual data, the observed cell frequency may be zero. However, the Pearson χ2 test is sensitive to small sample sizes, and other tests, such as the Fisher’s exact test, are more appropriate when testing very small samples (Daniel, 2000; Yates, 1934).

The test is distribution-free, or nonparametric, which means that no assumption has been made for a normal distribution of values in the population from which the sample was taken (Daniel, 2000).

The formula for a two-way χ2 is:

χ 2 =n[(A)(D)−(B)(C)] 2 (A+B)(C+D)(A+C)(B+D)

image
The contingency table is labeled as follows. A contingency table is a table that displays the relationship between two or more categorical variables (Daniel, 2000):

A B
C D
With any χ2 analysis, the degrees of freedom (df) must be calculated to determine the significance of the value of the statistic. The following formula is used for this calculation:

df=(R−1)(C−1)

image
where

R=Number of rows

image
C=Number of columns

image
Hand Calculations
A retrospective comparative study examined whether longer antibiotic treatment courses were associated with increased antimicrobial resistance in patients with spinal cord injury (Lee et al., 2014). Using urine cultures from a sample of spinal cord–injured veterans, two groups were created: those with evidence of antibiotic resistance and those with no evidence of antibiotic resistance. Each veteran was also divided into two groups based on having had a history of recent (in the past 6 months) antibiotic use for more than 2 weeks or no history of recent antibiotic use.

411
The data are presented in Table 35-1. The null hypothesis is: “There is no difference between antibiotic users and non-users on the presence of antibiotic resistance.”

TABLE 35-1

ANTIBIOTIC RESISTANCE BY ANTIBIOTIC USE

 Antibiotic Use  No Recent Use

Resistant 8 7
Not resistant 6 21
The computations for the Pearson χ2 test are as follows:

Step 1: Create a contingency table of the two nominal variables:

 Used Antibiotics    No Recent Use   Totals

Resistant 8 7 15
Not resistant 6 21 27
Totals 14 28 42 ←Total n
image

Step 2: Fit the cells into the formula:

χ 2 =n[(A)(D)−(B)(C)] 2 (A+B)(C+D)(A+C)(B+D)

image

χ 2 =42[(8)(21)−(7)(6)] 2 (8+7)(6+21)(8+6)(7+21)

image

χ 2 =666,792158,760

image

χ 2 =4.20

image

Step 3: Compute the degrees of freedom:

df=(2−1)(2−1)=1

image

Step 4: Locate the critical χ2 value in the χ2 distribution table (Appendix D) and compare it to the obtained χ2 value.

The obtained χ2 value is compared with the tabled χ2 values in Appendix D. The table includes the critical values of χ2 for specific degrees of freedom at selected levels of significance. If the value of the statistic is equal to or greater than the value identified in the χ2 table, the difference between the two variables is statistically significant. The critical χ2 for df = 1 is 3.84, and our obtained χ2 is 4.20, thereby exceeding the critical value and indicating a significant difference between antibiotic users and non-users on the presence of antibiotic resistance.

Furthermore, we can compute the rates of antibiotic resistance among antibiotic users and non-users by using the numbers in the contingency table from Step 1. The antibiotic resistance rate among the antibiotic users can be calculated as 8 ÷ 14 = 0.571 × 100% = 57.1%. The antibiotic resistance rate among the non-antibiotic users can be calculated as 7 ÷ 28 = 0.25 × 100% = 25%.

412
SPSS Computations
The following screenshot is a replica of what your SPSS window will look like. The data for subjects 24 through 42 are viewable by scrolling down in the SPSS screen.

image

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Step 1: From the “Analyze” menu, choose “Descriptive Statistics” and “Crosstabs.” Move the two variables to the right, where either variable can be in the “Row” or “Column” space.

image

Step 2: Click “Statistics” and check the box next to “Chi-square.” Click “Continue” and “OK.”

image

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Interpretation of SPSS Output
The following tables are generated from SPSS. The first table contains the contingency table, similar to Table 35-1 above. The second table contains the χ2 results.

Crosstabs
image

image

The last table contains the χ2 value in addition to other statistics that test associations between nominal variables. The Pearson χ2 test is located in the first row of the table, which contains the χ2 value, df, and p value.

Final Interpretation in American Psychological Association (APA) Format
The following interpretation is written as it might appear in a research article, formatted according to APA guidelines (APA, 2010). A Pearson χ2 analysis indicated that antibiotic users had significantly higher rates of antibiotic resistance than those who did not use antibiotics, χ2(1) = 4.20, p = 0.04 (57.1% versus 25%, respectively). This finding suggests that extended antibiotic use may be a risk factor for developing resistance, and further research is needed to investigate resistance as a direct effect of antibiotics.

415
Study Questions

  1. Do the example data meet the assumptions for the Pearson χ2 test? Provide a rationale for your answer.
  2. What is the null hypothesis in the example?
  3. What was the exact likelihood of obtaining a χ2 value at least as extreme or as close to the one that was actually observed, assuming that the null hypothesis is true?
  4. Using the numbers in the contingency table, calculate the percentage of antibiotic users who were resistant.
  5. Using the numbers in the contingency table, calculate the percentage of non-antibiotic users who were resistant.
  6. Using the numbers in the contingency table, calculate the percentage of resistant veterans who used antibiotics for more than 2 weeks.

416

  1. Using the numbers in the contingency table, calculate the percentage of resistant veterans who had no history of antibiotic use.
  2. What kind of design was used in the example?
  3. What result would have been obtained if the variables in the SPSS Crosstabs window had been switched, with Antibiotic Use being placed in the “Row” and Resistance being placed in the “Column”?
  4. Was the sample size adequate to detect differences between the two groups in this example? Provide a rationale for your answer.

Computational Practice

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A retrospective comparative study examining the presence of candiduria (presence of Candida species in the urine) among 97 adults with a spinal cord injury is presented as an additional example. The differences in the use of antibiotics were investigated with the Pearson χ2 test (Goetz, Howard, Cipher, & Revankar, 2010). These data are presented in Table 35-2 as a contingency table.

TABLE 35-2

CANDIDURIA AND ANTIBIOTIC USE IN ADULTS WITH SPINAL CORD INJURIES

 Candiduria  No Candiduria   Totals

Antibiotic use 15 43 58
No antibiotic use 0 39 39
Totals 15 82 97
image

Name: ___________________________________________ Class: _________

Date: _______________________________________________________________________

Follow your instructor’s directions to submit your answers to the following questions for grading. Your instructor may ask you to write your answers below and submit them as a hard copy for grading. Alternatively, your instructor may ask you to use the space below for notes and submit your answers.

  1. Do the example data in Table 35-2 meet the assumptions for the Pearson χ2 test? Provide a rationale for your answer.
  2. Compute the χ2 test. What is the χ2 value?
  3. Is the χ2 significant at α = 0.05? Specify how you arrived at your answer.
  4. If using SPSS, what is the exact likelihood of obtaining the χ2 value at least as extreme as or as close to the one that was actually observed, assuming that the null hypothesis is true?

420

  1. Using the numbers in the contingency table, calculate the percentage of antibiotic users who tested positive for candiduria.
  2. Using the numbers in the contingency table, calculate the percentage of non-antibiotic users who tested positive for candiduria.
  3. Using the numbers in the contingency table, calculate the percentage of veterans with candiduria who had a history of antibiotic use.
  4. Using the numbers in the contingency table, calculate the percentage of veterans with candiduria who had no history of antibiotic use.
  5. Write your interpretation of the results as you would in an APA-formatted journal.
  6. Was the sample size adequate to detect differences between the two groups in this example? Provide a rationale for your answer.

(Grove 409-420)

Grove, Susan K., Daisha Cipher. Statistics for Nursing Research: A Workbook for Evidence-Based Practice, 2nd Edition. Saunders, 022016. VitalBook file.

The citation provided is a guideline. Please check each citation for accuracy before use.

Need answers of questions to be graded at the end of each exercise.

Transformational Leadership Style

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using formal APA writing convention, using the 7th Edition APA

Transformational Leadership Style

A good leadership style plays an important role in nursing and the retention of nurses because it helps in shaping the healthcare practice environment to produce quality outcomes for staff nurses and patients. The type of leadership that one chooses to use in a leadership role or position determines the outcome and accomplishment of the mission set before an organization. The leadership style that I prefer and that is productive is transformational leadership. Adopting the qualities of a transformational leader will allow nurse managers to feel more comfortable and confident when engaging in the development of healthcare policies, the ever-changing components of healthcare technology, and the mentorship of new graduate nurses” (Smith, 2011).

Transformational leadership style has been identified as the most effective approach to building up a business organization. Leaders that use the transformational style of leadership showcase integrity, high emotional intelligence, and they motivate people with a shared vision of the future and communicate well to their team or organization. As a nurse, I prefer this leadership style because it embraces self-awareness, authenticity, and humility which is among the list of styles that is missing in today’s management. A nurse leader who uses a transformational leadership style will promote a healthy atmosphere for her nurses to work in and promote job satisfaction for everyone. A good nurse leader brings out the best in their nurses by promoting a good leader for their nurse to climb on career-wise and promote a thriving environment for everyone in the team. Transformational leaders create a safe and soft influence and provide a high job satisfaction by supporting followers’act of making individual choices (Long et; al 2014) Transformational Leadership Style

ORDER   A PLAGIARISM FREE PAPER   NOW

 In nursing today, we find more autocratic leadership that doesn’t care about anyone else but themselves and what they stand to achieve. Such leaders don’t last very long in an organization, and this is the leadership style that I have seen, and it doesn’t work.  According to Smith, Transformational leadership qualities promote a healthy environment for employees and staff, which will produce improved staff satisfaction, retention, and patient satisfaction (Smith, 2011). I have been opportune to work with good nurse leaders and a few of them I have admired and am still in close contact with them.  I worked with a good manager as a delegating nurse, and she showed me what a good leader is supposed to be. She was someone that I admired so much because she was a team leader, she has positive energy, easy to talk to, and is very humble. Her attributes made me see a leadership position as an asset instead of deplorable. She made the atmosphere very conducive and welcoming for everyone who worked on her team even as a new hire. Transformational Leadership Style

 

 

References

Choi Sang Long, Wan Mardhia M. Yusof, Tan Owee Kowang and Low Hock Heng 1 The Impact of Transformational Leadership Style on Job Satisfaction retrieved from https://www.researchgate.net/profile/Choi-Sang   Long/publication/289580477_The_impact_of_transformational_leadership_style_on_job_satisfaction/links/59e6ad544585151e545ce679/The-impact-of-transformational-leadership-style-on-job-satisfaction.pdf

Smith, Mary Atkinson FNP-BC Are you a transformational leader?, Nursing Management (Springhouse): September 2011 – Volume 42 – Issue 9 – p 44-50 doi: 10.1097/01.NUMA.0000403279.04379.6a

 

 

Practicum – Assessing Client Progress

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To prepare:

· Reflect on the client you selected for the Week 3 Practicum Assignment.

· Review the Cameron and Turtle-Song (2002) article in this week’s Learning

Resources for guidance on writing case notes using the SOAP format.

The Assignment

Part 1: Progress Note

Using the client from your Week 3 Assignment, address the following in a progress note (without violating HIPAA regulations):………THE WEEK 3 ASSIGNMENT IS ATTACHED

· Treatment modality used and efficacy of approach

· Progress and/or lack of progress toward the mutually agreed-upon client goals

(reference the Treatment plan—progress toward goals)

· Modification(s) of the treatment plan that were made based on progress/lack of

progress

· Clinical impressions regarding diagnosis and/or symptoms

· Relevant psychosocial information or changes from original assessment (i.e.,

marriage, separation/divorce, new relationships, move to a new

house/apartment, change of job, etc.)

· Safety issues

· Clinical emergencies/actions taken

· Medications used by the patient (even if the nurse psychotherapist was not the

one prescribing them)

· Treatment compliance/lack of compliance

· Clinical consultations

· Collaboration with other professionals (i.e., phone consultations with physicians,

psychiatrists, marriage/family therapists, etc.)

· Therapist’s recommendations, including whether the client agreed to the

recommendations

· Referrals made/reasons for making referrals

· Termination/issues that are relevant to the termination process (i.e., client

informed of loss of insurance or refusal of insurance company to pay for

continued sessions)

· Issues related to consent and/or informed consent for treatment

· Information concerning child abuse, and/or elder or dependent adult abuse,

including documentation as to where the abuse was reported

· Information reflecting the therapist’s exercise of clinical judgment

                                                 Learning Resources

Required Readings

Wheeler, K. (Ed.). (2014). Psychotherapy for the advanced practice psychiatric nurse: A how-to guide for evidence-based practice (2nd ed.). New York, NY: Springer Publishing Company.

Chapter 5, “Supportive and Psychodynamic Psychotherapy” (pp. 238–242)

Chapter 9, “Interpersonal Psychotherapy” (pp. 347–368)

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Washington, DC: Author.

Abeles, N., & Koocher, G. P. (2011). Ethics in psychotherapy. In J. C. Norcross, G. R. VandenBos, D. K. Freedheim, J. C. Norcross, G. R. VandenBos, & D. K. Freedheim (Eds.), History of psychotherapy: Continuity and change (pp. 723–740). Washington, DC: American Psychological Association. doi:10.1037/12353-048

Cameron, S., & Turtle-Song, I. (2002). Learning to write case notes using the SOAP format. Journal of Counseling and Development, 80(3), 286–292. Retrieved from the Academic Search Complete database. (Accession No. 7164780)

Nicholson, R. (2002). The dilemma of psychotherapy notes and HIPAA. Journal of AHIMA, 73(2), 38–39. Retrieved from http://library.ahima.org/doc?oid=58162#.V5J0__krLZ4http://library.ahima.org/doc?oid=58162#.V5J0__krLZ4

U.S. Department of Health & Human Services. (n.d.). HIPAA privacy rule and sharing information related to mental health. Retrieved from http://www.hhs.gov/hipaa/for-professionals/special-topics/mental-health/

Required Media

Sommers-Flanagan, J., & Sommers-Flanagan, R. (2013). Counseling and psychotherapy theories in context and practice [Video file]. Mill Valley, CA: Psychotherapy.net.

Stuart, S. (2010). Interpersonal psychotherapy: A case of postpartum depression [Video file]. Mill Valley, CA: Psychotherapy.net.

Business Writer

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Details:

As the country focuses on the restructuring of the U.S. health care delivery system, nurses will continue to play an important role. It is expected that more and more nursing jobs will become available out in the community, and fewer will be available in acute care hospitals.

Write an informal presentation (500-700 words) to educate nurses about how the practice of nursing is expected to grow and change. Include the concepts of continuity or continuum of care, accountable care organizations (ACO), medical homes, and nurse-managed health clinics.

Share your presentation with nurse colleagues on your unit or department and ask them to offer their impressions of the anticipated changes to health care delivery and the new role of nurses in hospital settings, communities, clinics, and medical homes.

In 800-1,000 words summarize the feedback shared by three nurse colleagues and discuss whether their impressions are consistent with what you have researched about health reform.

A minimum of three scholarly references are required for this assignment.

While APA format is not required for the body of this assignment, solid academic writing is expected and in-text citations and references should be presented using APA documentation guidelines, which can be found in the APA Style Guide, located in the Student Success Center.

This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.

You are required to submit this assignment to Turnitin. Please refer to the directions in the Student Success Center.

Practicum Journal: Checkpoint for Certification Plan

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Psychiatric/mental health nurse practitioners currently have only one choice for certification, which is through the American Nurses Credentialing Center (ANCC). The ANCC offers the “psychiatric/mental-health nurse practitioner (across the lifespan)” board certification (PMHNP-BC). In many states, board certification is needed as a prerequisite to being granted an NP license. Even if board certification is not a requirement for state licensure, it may be a requirement to receive privileges in various hospitals and other health care facilities. It may also be required by malpractice insurance providers prior to issuing coverage to NPs.

                                  Learning Objectives

Students will:

Evaluate progress on certification plans

Report your progress on the Certification Plan you completed in Week 4 (SEE ATTACHED WEEK 4 CERTIFICATION PLAN DONE)

                            Assignment 


        Write a 2- to 3-page paper in which you do the following:

1) What have you done to prepare for your certification?

2) Have you completed the scheduled tasks assigned on your timeline as you

NB: for this Assignment (Journal Entries)

· Include references immediately following the content.

· Use APA style for your journal entry and references less than 5 years old.

. PLEASE INCLUDE INTRODUCTION, CONCLUSION AND REFERENCES LESS

THAN 5 YEARS OLD

                                         Learning Resources

Required Readings

Barton Associates. (2017). Nurse practitioner scope of practice laws.

American Psychiatric Association. (2016). Practice guidelines for the psychiatric evaluation of adults.

Case Study

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In a short essay (500-750 words), answer the Question at the end of Case Study 1. Cite references to support your positions.

Prepare this assignment according to the APA guidelines found in the APA Style Guide, located in the Student Success Center. An abstract is not required.

This assignment uses a grading rubric. Instructors will be using the rubric to grade the assignment; therefore, students should review the rubric prior to beginning the assignment to become familiar with the assignment criteria and expectations for successful completion of the assignment.

Max Points: 20.0

This is the case study 1 :

The case scenario provided will be used to answer the discussion questions that follow.

Case Scenario

Ms. G., a 23-year-old diabetic, is admitted to the hospital with a cellulitis of her left lower leg. She has been applying heating pads to the leg for the last 48 hours, but the leg has become more painful and she has developed chilling.

Subjective Data

Complains of pain and heaviness in her leg.

States she cannot bear weight on her leg and has been in bed for 3 days.

Lives alone and has not had anyone to help her with meals.

Objective Data

Round, yellow-red, 2 cm diameter, 1 cm deep, open wound above medial malleolus with moderate amount of thick yellow drainage

Left leg red from knee to ankle

Calf measurement on left 3 in > than right

Temperature: 38.9 degrees C

Height: 160 cm; Weight: 83.7 kg

Laboratory Results

WBC 18.3 x 10¹² / L; 80% neutrophils, 12% bands

Wound culture: Staphylococcus aureus

Critical Thinking Questions

What clinical manifestations are present in Ms. G and what recommendations would you make for continued treatment? Provide rationale for your recommendations.

Identify the muscle groups likely to be affected by Ms. G’s condition by referring to “ARC: Anatomy Resource Center.”

What is the significance of the subjective and objective data provided with regard to follow-up diagnostic/laboratory testing, education, and future preventative care? Provide rationale for your answer.

What factors are present in this situation that could delay wound healing, and what precautions are required to prevent delayed wound healing? Explain.