Healthcare Research and Statistics
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Free Healthcare Research and Statistics Questions
A new blood pressure–lowering medication is tested on a group of patients. The average systolic blood pressure of patients who did not receive the medication is 138 mm Hg, and the average systolic blood pressure of patients who did receive the medication is 126 mm Hg. A t-test was used to compare the two outcomes. The 95% confidence interval was 10.23 to 13.77, and the 99% confidence interval was 9.68 to 14.3. The null hypothesis states that there is no difference between the groups.
What is the correct interpretation of this study’s results?
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Using the 95% confidence interval, one fails to reject the null hypothesis.
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Using the 99% confidence interval, one fails to accept the null hypothesis.
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Increasing the confidence interval from 95% to 99% decreases the probability of accepting the null hypothesis.
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Increasing the confidence interval from 95% to 99% decreases the probability of rejecting the null hypothesis.
Explanation
Correct Answer:
D. Increasing the confidence interval from 95% to 99% decreases the probability of rejecting the null hypothesis.
Explanation:
Both confidence intervals exclude zero, meaning there is a statistically significant difference between the two groups. When the confidence level increases from 95% to 99%, the interval widens, making it less likely to reject the null hypothesis because it allows for greater uncertainty. Therefore, raising the confidence level decreases the probability of rejecting the null hypothesis.
A researcher concludes that there is no relationship between nurse staffing levels and patient satisfaction scores.
Which hypothesis is supported by this finding?
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Null hypothesis
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Directional hypothesis
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Alternative hypothesis
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Non-directional hypothesis
Explanation
Correct Answer:
Null hypothesis
Explanation:
The null hypothesis states that there is no relationship or difference between variables. Because the study found no significant relationship, the null hypothesis is supported, meaning the staffing levels and satisfaction scores are statistically unrelated.
A hospital administrator wants to understand staff satisfaction levels. She randomly selects 50 nurses from each hospital department. What type of sampling method is this?
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Stratified random sampling
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Simple random sampling
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Convenience sampling
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Systematic sampling
Explanation
Correct Answer:
Stratified random sampling
Explanation:
Stratified random sampling divides the population into subgroups (in this case, departments) and then selects random samples from each subgroup to ensure proportional representation.
A nurse researcher studying the relationship between sleep duration and stress among hospital staff finds a correlation coefficient (r) of -0.78.
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There is a strong inverse relationship between sleep and stress levels.
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There is a weak positive relationship between sleep and stress levels.
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There is no correlation between sleep and stress levels.
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The relationship between sleep and stress is random.
Explanation
Correct Answer:
There is a strong inverse relationship between sleep and stress levels.
Explanation:
A correlation coefficient of -0.78 indicates a strong negative correlation—meaning as sleep duration increases, stress levels decrease. The closer the correlation coefficient is to -1 or 1, the stronger the relationship.
A doctor needs to develop clinical guidelines for a rare psychiatric disorder.
Which evidence is appropriate for this situation?
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Case reports
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Systematic review
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Cross-sectional survey
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Randomized controlled trials
Explanation
Correct Answer:
A. Case reports.
Explanation:
For rare psychiatric disorders, case reports are the most appropriate form of evidence. These reports document individual or small groups of patients, providing valuable clinical observations where large-scale studies are not feasible due to the limited number of cases. Case reports often serve as the foundation for developing clinical guidelines in rare conditions by offering insight into symptoms, treatment responses, and outcomes observed in actual patients.
A study comparing pain relief between two medications used a t-test and found p = 0.45.
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There is no statistically significant difference between the medications.
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There is a statistically significant difference between the medications.
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The null hypothesis should be rejected.
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The new medication is more effective.
Explanation
Correct Answer:
There is no statistically significant difference between the medications.
Explanation:
A p-value of 0.45 is greater than 0.05, which means there is no statistically significant difference between the two medications. The null hypothesis (no difference) cannot be rejected.
A clinical researcher tests a new weight-loss medication in a randomized controlled trial. The treatment group loses an average of 8.4 kg (SD = 2.1), and the control group loses 4.2 kg (SD = 2.3). The p-value is 0.001, and the 95% confidence interval for the mean difference is 3.1–5.2 kg.
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The treatment produces a statistically significant and clinically meaningful reduction in weight.
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The treatment effect is statistically significant but not clinically meaningful.
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The results show no statistically significant difference between groups.
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The wide confidence interval indicates an unreliable result.
Explanation
Correct Answer:
The treatment produces a statistically significant and clinically meaningful reduction in weight.
Explanation:
Because the p-value (0.001) is well below 0.05 and the confidence interval (3.1–5.2) does not include zero, the result is statistically significant. The mean weight loss difference (about 4–5 kg) is also large enough to be clinically meaningful.
A screening study is performed to determine the prevalence of colon cancer in 10,000 subjects in a rural community. Researchers are examining the efficacy between a fecal occult blood (stool) sampling and a colonoscopy. The two-tailed test with a p-value of 0.025 and a 95% confidence interval indicates that the colonoscopy screening provides a higher rate of early detection. Researchers found that allowing the participant to select the screening test did not affect the findings compared to previous results.
Which limitation of this study reduces the credibility of the report?
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Confounders are difficult to control in this study.
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Data collection on a large sample size is difficult.
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The respondent bias affects this cross-sectional study.
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Causality is determined by the screening method in this study.
Explanation
Correct Answer:
The respondent bias affects this cross-sectional study.
Explanation:
A major limitation that reduces the credibility of this report is that respondent bias affects this cross-sectional study. Because participants were allowed to choose their screening method, their preferences, health awareness, or previous experiences could influence outcomes. This introduces selection or respondent bias, compromising the objectivity of the findings and weakening causal interpretation. Cross-sectional studies can show associations but not definitive cause-and-effect relationships.
A healthcare organization analyzes three independent predictors — patient age, medication compliance, and number of chronic conditions — to forecast hospital readmission.
Which statistical technique best fits this scenario?
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Logistic regression
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Chi-square test
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Independent t-test
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ANOVA
Explanation
Correct Answer:
Logistic regression
Explanation:
When predicting a categorical outcome (e.g., readmitted vs. not readmitted) based on multiple independent predictors, logistic regression is the appropriate statistical technique.
A researcher collected data on the number of cases for several infectious diseases, including TB (respiratory), TB (non-respiratory), septicemia, hepatitis, and other viral or bacterial infections. The goal is to present the proportion of each disease category as part of the total cases in a published report.
Which graphic should be used to visually represent these data for publication?
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Box plot
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Pie chart
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Line graph
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Scatter plot
Explanation
Correct Answer:
B. Pie chart.
Explanation:
A pie chart is the most appropriate choice because it effectively shows the relative proportions of categorical data, such as the number of cases per disease type. Each slice of the pie represents a category’s percentage of the total, making it easy for readers to visualize which diseases occur more frequently compared to others. It is ideal for summarizing categorical frequency data in publication format.
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