HLT-362V Exercise 19: Understanding Pearson Chi-Square

NEED TO ANSWER THE QUESTIONS TO BE GRADED. SAMPLE STUDY QUESTION ANSWER GIVEN ANSWER SHOULD BE ACCORDING TO THEM. 100% PLAGIARISM FREE. BOOK NAME- Grove, Susan K., Daisha Cipher. Statistics for Nursing Research: A Workbook for Evidence-Based Practice, 2nd Edition. Saunders, 022016. VitalBook file.
Exercise 19
Understanding Pearson Chi-Square
Statistical Technique in Review
The Pearson Chi-square (χ2 ) is an inferential statistical test calculated to examine differences among groups with variables measured at the nominal level. There are different types of χ2 tests and the Pearson chi-square is commonly reported in nursing studies. The Pearson χ2 test compares the frequencies that are observed with the frequencies that were expected. The assumptions for the χ2 test are as follows:
1. The data are nominal-level or frequency data.
2. The sample size is adequate.
3. The measures are independent of each other or that a subject's data only fit into one category (Plichta & Kelvin, 2013).
The χ2 values calculated are compared with the critical values in the χ2 table (see Appendix D Critical Values of the χ2 Distribution at the back of this text). If the result is greater than or equal to the value in the table, significant differences exist. If the values are statistically significant, the null hypothesis is rejected (Grove, Burns, & Gray, 2013). These results indicate that the differences are probably an actual reflection of reality and not just due to random sampling error or chance.
In addition to the χ2 value, researchers often report the degrees of freedom (df). This mathematically complex statistical concept is important for calculating and determining levels of significance. The standard formula for df is sample size (N) minus 1, or df = N − 1; however, this formula is adjusted based on the analysis technique performed (Plichta & Kelvin, 2013). The df formula for the χ2 test varies based on the number of categories examined in the analysis. The formula for df for the two-way χ2 test is df = (R − 1) (C − 1), where R is number of rows and C is the number of columns in a χ2 table. For example, in a 2 × 2 χ2 table, df = (2 − 1) (2 − 1) = 1. Therefore, the df is equal to 1. Table 19-1 includes a 2 × 2 chi-square contingency table based on the findings of An et al. (2014) study. In Table 19-1, the rows represent the two nominal categories of alcohol 192use and alcohol nonuse and the two columns represent the two nominal categories of smokers and nonsmokers. The df = (2 − 1) (2 − 1) = (1) (1) = 1, and the study results were as follows: χ2 (1, N = 799) = 63.1; p < 0.0001. It is important to note that the df can also be reported without the sample size, as in χ2(1) = 63.1, p < 0.0001.
TABLE 19-1
CONTINGENCY TABLE BASED ON THE RESULTS OF AN ET AL. (2014) STUDY
Nonsmokers n = 742 Smokers n = 57*
No alcohol use 551 14
Alcohol use†
191 43
* Smokers defined as “smoking at least 1 cigarette daily during the past month.”
† Alcohol use “defined as at least 1 alcoholic beverage per month during the past year.”
An, F. R., Xiang, Y. T., Yu., L., Ding, Y. M., Ungvari, G. S., Chan, S. W. C., et al. (2014). Prevalence of nurses' smoking habits in psychiatric and general hospitals in China. Archives of Psychiatric Nursing, 28(2), 120.
If more than two groups are being examined, χ2 does not determine where the differences lie; it only determines that a statistically significant difference exists. A post hoc analysis will determine the location of the difference. χ2 is one of the weaker statistical tests used, and results are usually only reported if statistically significant values are found. The step-by-step process for calculating the Pearson chi-square test is presented in Exercise 35.
Research Article
Source
Darling-Fisher, C. S., Salerno, J., Dahlem, C. H. Y., & Martyn, K. K. (2014). The Rapid Assessment for Adolescent Preventive Services (RAAPS): Providers' assessment of its usefulness in their clinical practice settings. Journal of Pediatric Health Care, 28(3), 217–226.
Introduction
Darling-Fisher and colleagues (2014, p. 219) conducted a mixed-methods descriptive study to evaluate the clinical usefulness of the Rapid Assessment for Adolescent Preventative Services (RAAPS) screening tool “by surveying healthcare providers from a wide variety of clinical settings and geographic locations.” The study participants were recruited from the RAAPS website to complete an online survey. The RAAPS risk-screening tool “was developed to identify the risk behaviors contributing most to adolescent morbidity, mortality, and social problems, and to provide a more streamlined assessment to help providers address key adolescent risk behaviors in a time-efficient and user-friendly format” (Darling-Fisher et al., 2014, p. 218). The RAAPS is an established 21-item questionnaire with evidence of reliability and validity that can be completed by adolescents in 5–7 minutes.
“Quantitative and qualitative analyses indicated the RAAPS facilitated identification of risk behaviors and risk discussions and provided efficient and consistent assessments; 86% of providers believed that the RAAPS positively influenced their practice” (Darling-Fisher et al., 2014, p. 217). The researchers concluded the use of RAAPS by healthcare providers could improve the assessment and identification of adolescents at risk and lead to the delivery of more effective adolescent preventive services.
Relevant Study Results
In the Darling-Fisher et al. (2014, p. 220) mixed-methods study, the participants (N = 201) were “providers from 26 U.S. states and three foreign countries (Canada, Korea, and Ireland).” More than half of the participants (n = 111; 55%) reported they were using the RAAPS in their clinical practices. “When asked if they would recommend the RAAPS to other providers, 86 responded, and 98% (n = 84) stated they would recommend RAAPS. The two most common reasons cited for their recommendation were for screening (n = 76, 92%) and identification of risk behaviors (n = 75, 90%). Improved communication (n = 52, 63%) and improved documentation (n = 46, 55%) and increased patient understanding of their risk behaviors (n = 48, 58%) were also cited by respondents as reasons to recommend the RAAPS” (Darling-Fisher et al., 2014, p. 222).
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“Respondents who were not using the RAAPS (n = 90; 45%), had a variety of reasons for not using it. Most reasons were related to constraints of their health system or practice site; other reasons were satisfaction with their current method of assessment . . . and that they were interested in the RAAPS for academic or research purposes rather than clinical use” (Darling-Fisher et al., 2014, p. 220).
Chi-square analysis was calculated to determine if any statistically significant differences existed between the characteristics of the RAAPS users and nonusers. Darling-Fisher et al. (2014) did not provide a level of significance or α for their study, but the standard for nursing studies is α = 0.05. “Statistically significant differences were noted between RAAPS users and nonusers with respect to provider types, practice setting, percent of adolescent patients, years in practice, and practice region. No statistically significant demographic differences were found between RAAPS users and nonusers with respect to race, age” (Darling-Fisher et al., 2014, p. 221). The χ2 results are presented in Table 2.
DEMOGRAPHIC COMPARISONS BETWEEN RAPID ASSESSMENT FOR ADOLESCENT PREVENTIVE SERVICE USERS AND NONUSERS
Current user Yes (%) No (%) χ2 p
Provider type (n = 161) 12.7652, df = 2 < .00
Health care provider 64 (75.3) 55 (72.4)
Mental health provider 13 (15.3) 2 (2.6)
Other 8 (9.4) 19 (25.0)
Practice setting (n = 152) 12.7652, df = 1 < .00
Outpatient health clinic 20 (24.1) 36 (52.2)
School-based health clinic 63 (75.9) 33 (47.8)
% Adolescent patients (n = 154) 7.3780, df = 1 .01
≤50% 26 (30.6) 36 (52.2)
>50% 59 (69.4) 33 (47.8)
Years in practice (n = 157) 6.2597, df = 1 .01
≤5 years 44 (51.8) 23 (31.9)
>5 years 41 (48.2) 49 (68.1)
U.S. practice region (n = 151) 29.68, df = 3 < .00
Northeastern United States 13 (15.3) 15 (22.7)
Southern United States 11 (12.9) 22 (33.3)
Midwestern United States 57 (67.1) 16 (24.2)
Western United States 4 (4.7) 13 (19.7)
Race (n = 201) 1.2865, df = 2 .53
Black/African American 11 (9.9) 5 (5.6)
White/Caucasian 66 (59.5) 56 (62.2)
Other 34 (30.6) 29 (32.2)
Provider age in years (n = 145) 4.00, df = 2 .14
20–39 years 21 (25.6) 8 (12.7)
40–49 years 24 (29.3) 19 (30.2)
50+ years 37 (45.1) 36 (57.1)
χ2, Chi-square statistic.
df, degrees of freedom.
Darling-Fisher, C. S., Salerno, J., Dahlem, C. H. Y., & Martyn, K. K. (2014). The Rapid Assessment for Adolescent Preventive Services (RAAPS): Providers' assessment of its usefulness in their clinical practice settings. Journal of Pediatric Health Care, 28(3), p. 221.
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Study Questions
1. What is the sample size for the Darling-Fisher et al. (2014) study? How many study participants (percentage) are RAAPS users and how many are RAAPS nonusers?
2. What is the chi-square (χ2) value and degrees of freedom (df) for provider type?
3. What is the p value for provider type? Is the χ2 value for provider type statistically significant? Provide a rationale for your answer.
4. Does a statistically significant χ2 value provide evidence of causation between the variables? Provide a rationale for your answer.
5. What is the χ2 value for race? Is the χ2 value statistically significant? Provide a rationale for your answer.
6. Is there a statistically significant difference between RAAPS users and RAAPS nonusers with regard to percentage adolescent patients? In your own opinion is this an expected finding? Document your answer.
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7. What is the df for U.S. practice region? Complete the df formula for U.S. practice region to visualize how Darling-Fisher et al. (2014) determined the appropriate df for that region.
8. State the null hypothesis for the years in practice variable for RAAPS users and RAAPS nonusers.
9. Should the null hypothesis for years in practice developed for Question 8 be accepted or rejected? Provide a rationale for your answer.
10. How many null hypotheses were accepted by Darling-Fisher et al. (2014) in Table 2? Provide a rationale for your answer.
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Answers to Study Questions
1. The sample size is N = 201 with n = 111 (55%) RAAPS users and n = 90 (45%) RAAPS nonusers as indicated in the narrative results.
2. The χ2 = 12.7652 and df = 2 for provider type as presented in Table 2.
3. The p = < .00 for the provider type. Yes, the χ2 = 12.7652 for provider type is statistically significant as indicated by the p value presented in Table 2. The specific χ2 value obtained could be compared against the critical value in a χ2 table (see Appendix D Critical Values of the χ2 Distribution at the back of this text) to determine the significance for the specific degrees of freedom (df), but readers of research reports usually rely on the p value provided by the researcher(s) to determine significance. Most nurse researchers set the level of significance or alpha (α) = 0.05. Since the p value is less than alpha, the result is statistically significant. You need to note that p values never equal zero as they appear in this study. The p values would not be zero if carried out more decimal places.
4. No, a statistically significant χ2 value does not provide evidence of causation. A statistically significant χ2 value indicates a significant difference between groups exists but does not provide a causal link (Grove et al., 2013; Plichta & Kelvin, 2013).
5. The χ2 = 1.2865 for race. Since p = .53 for race, the χ2 value is not statistically significant. The level of significance is set at α = 0.05 and the p value is larger than alpha, so the result is nonsignificant.
6. Yes, there is a statistically significant difference between RAAPS users and RAAPS nonusers with regard to percent of adolescent patients. The chi-square value = 7.3780 with a p = .01.You might expect that nurses caring for more adolescents might have higher RAAPS use as indicated in Table 2. However, nurses need to be knowledgeable of assessment and care needs of populations and subpopulations in their practice even if not frequently encountered. Two valuable sources for adolescent care include the Centers for Disease Control and Prevention (CDC) Adolescent and School Health at http://www(dot)cdc(dot)gov/HealthyYouth/idex.htm and the World Health Organization (WHO) adolescent health at http://www(dot)who(dot)int/topics/adolescent_health/en/.
7. The df = 3 for U.S. practice region is provided in Table 2. The df formula, df = (R − 1) (C − 1) is used. There are four “R” rows, Northeastern United States, Southern United States, Midwestern United States, and Western United States. There are two “C” columns, RAAPS users and RAAPS nonusers. df = (4 − 1)(2 − 1) = (3)(1) = 3.
8. The null hypothesis: There is no difference between RAAPS users and RAAPS nonusers for providers with ≤5 years of practice and those with >5 years of practice.
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9. The null hypothesis for years in practice stated in Questions 8 should be rejected. The χ2 = 6.2597 for years in practice is statistically significant, p = .01. A statistically significant χ2 indicates a significant difference exists between the users and nonusers of RAAPS for years in practice; therefore, the null hypothesis should be rejected.
10. Two null hypotheses were accepted since two χ2 values (race and provider age) were not statistically significant (p > 0.05), as indicated in Table 2. Nonsignificant results indicate that the null hypotheses are supported or accepted as an accurate reflection of the results of the study.
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EXERCISE 19 Questions to Be Graded
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 online at http://evolve(dot)elsevier(dot)com/Grove/Statistics/ under “Questions to Be Graded.”
Name: _______________________________________________________ Class: _____________________
Date: ___________________________________________________________________________________
1. According to the relevant study results section of the Darling-Fisher et al. (2014) study, what categories are reported to be statistically significant?
2. What level of measurement is appropriate for calculating the χ2 statistic? Give two examples from Table 2 of demographic variables measured at the level appropriate for χ2.
3. What is the χ2 for U.S. practice region? Is the χ2 value statistically significant? Provide a rationale for your answer.
4. What is the df for provider type? Provide a rationale for why the df for provider type presented in Table 2 is correct.
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5. Is there a statistically significant difference for practice setting between the Rapid Assessment for Adolescent Preventive Services (RAAPS) users and nonusers? Provide a rationale for your answer.
6. State the null hypothesis for provider age in years for RAAPS users and RAAPS nonusers.
7. Should the null hypothesis for provider age in years developed for Question 6 be accepted or rejected? Provide a rationale for your answer.
8. Describe at least one clinical advantage and one clinical challenge of using RAAPS as described by Darling-Fisher et al. (2014)
9. How many null hypotheses are rejected in the Darling-Fisher et al. (2014) study for the results presented in Table 2? Provide a rationale for your answer.
10. A statistically significant difference is present between RAAPS users and RAAPS nonusers for U.S. practice region, χ2 = 29.68. Does the χ2 result provide the location of the difference? Provide a rationale for your answer.
(Grove 200)
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.
(Grove 193-200)
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.