Disclaimer
This project is a simulated clinical study conducted solely for learning and exploration purposes. The methods, analysis, and results were developed to mimic real-world clinical research but are not intended for professional, medical, or therapeutic use. The findings should not be interpreted as clinically validated or used to guide decision-making in professional healthcare settings.
Objective
The objective of this study is to evaluate the effectiveness of a mindfulness meditation program in reducing stress levels among participants. Specifically, the study aims to compare the post-treatment stress levels of participants in a treatment group (who practice meditation) to those in a control group (who do not participate in any intervention), and to determine whether the treatment group experiences a statistically significant greater reduction in stress compared to the control group.
Background and Rationale
Stress is a common issue affecting mental and physical health, and mindfulness meditation is widely considered a potential solution for managing stress. This simulation models a clinical study to test whether mindfulness meditation can effectively reduce stress. While real clinical trials involve human participants, this simulated trial allows us to test the potential effects of meditation on stress levels by comparing a treatment group (meditation) and a control group (no intervention).
Although this is a personal trial in a simulated setting, the approach mimics a randomized controlled trial (RCT), the gold standard in clinical studies. This helps demonstrate how interventions like meditation could be evaluated for their effectiveness in real-world clinical settings.
Study Design
Sample:
Total number of participants: 100
Randomly divided into two groups:
- Treatment group: Participants practice mindfulness meditation.
- Control group: Participants do not practice meditation.
Baseline Stress Levels:
Before the intervention, we assume that all participants have similar levels of stress, on average. These stress levels are randomly generated from a normal distribution with:- Mean = 7: Most participants have moderate to high stress levels.
- Standard Deviation (SD) = 1.5: Represents variability in stress across participants.
Post-Intervention Stress Levels:
After the intervention:- Treatment group: Participants in this group are hypothesized to show a significant reduction in stress levels, with an average reduction of 2 points.
- Control group: Participants in this group may also experience a small reduction in stress (e.g., due to natural recovery or placebo effects), averaging a 0.5-point reduction.
Why Are These Means Chosen?
- Treatment group (2-point reduction): Mindfulness meditation is believed to have a meaningful effect on stress reduction, so a larger reduction is assumed.
- Control group (0.5-point reduction): Even without
an active intervention, participants in control groups often show slight
improvement due to:
- The placebo effect.
- Natural recovery over time.
- Small changes in lifestyle during the study.
How Is Stress Reduction Simulated?
We generate stress levels for each participant before and after the intervention:
- Baseline Stress Levels: Randomly assigned from a normal distribution (mean = 7, SD = 1.5).
- Post-Intervention Stress Levels:
- For the treatment group: Subtract ~2 points from the baseline, with some variability (SD = 1).
- For the control group: Subtract ~0.5 points from the baseline, with similar variability.
This variability ensures that the simulated data resemble real-world outcomes, where individual responses to interventions differ.
R Code for Simulation
Step 1: Simulate the Data
# Setting seed for reproducibility
set.seed(123)
# Defining study parameters
sample_size <- 100
group_assignment <- sample(c("Treatment", "Control"), sample_size, replace = TRUE)
# Simulating baseline stress levels
baseline_stress <- rnorm(sample_size, mean = 7, sd = 1.5)
# Simulating post-treatment stress levels
post_stress <- ifelse(group_assignment == "Treatment",
baseline_stress - rnorm(sample_size, mean = 2, sd = 1),
baseline_stress - rnorm(sample_size, mean = 0.5, sd = 1))
# Ensuring stress levels are within valid range (1 to 10)
post_stress <- pmin(pmax(post_stress, 1), 10)
# Combining into a data frame
study_data <- data.frame(
Participant_ID = 1:sample_size,
Group = group_assignment,
Baseline_Stress = baseline_stress,
Post_Stress = post_stress
)
# Preview of Data
head(study_data)## Participant_ID Group Baseline_Stress Post_Stress
## 1 1 Treatment 7.379978 4.592239
## 2 2 Treatment 6.957180 4.188138
## 3 3 Treatment 6.935694 4.603492
## 4 4 Control 9.052903 8.462407
## 5 5 Treatment 6.661344 4.780796
## 6 6 Control 9.274706 8.863271Data Analysis
Step 2: Descriptive Statistics
Calculating the average baseline and post-treatment stress levels for both groups:
# Summarizing by group
summary_by_group <- aggregate(cbind(Baseline_Stress, Post_Stress) ~ Group,
data = study_data,FUN = mean)
print(summary_by_group)## Group Baseline_Stress Post_Stress
## 1 Control 6.918940 6.221717
## 2 Treatment 6.919714 4.836112Step 3: Two Sample T-Test
Performing a t-test to compare the post-intervention stress levels between the two groups:
# Separating data by group
treatment_group <- subset(study_data, Group == "Treatment")$Post_Stress
control_group <- subset(study_data, Group == "Control")$Post_Stress
# Performing t-test
t_test_result <- t.test(treatment_group, control_group, var.equal = TRUE)
print(t_test_result)##
## Two Sample t-test
##
## data: treatment_group and control_group
## t = -3.8692, df = 98, p-value = 0.0001967
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -2.0962601 -0.6749503
## sample estimates:
## mean of x mean of y
## 4.836112 6.221717Step 4: Visualization
The boxplot visually compares stress levels between the treatment and control groups, showing a noticeable difference.
## Warning: package 'ggplot2' was built under R version 4.3.3# Boxplot to visualize post-treatment stress levels
ggplot(study_data, aes(x = Group, y = Post_Stress, fill = Group)) +
geom_boxplot() +
labs(title = "Post-Treatment Stress Levels by Group", x = "Group",
y = "Stress Level") +
theme(
plot.title = element_text(hjust = 0.5) # Center the title
)
Results
Descriptive Statistics
- Treatment Group: Mean post-treatment stress = 4.836.
- Control Group: Mean post-treatment stress = 6.222.
T-Test Results
- t-value: -3.87 (indicates the magnitude and direction of the difference).
- p-value: 0.0001967 (statistically significant at p < 0.05).
- 95% Confidence Interval: The true difference in means is between -2.10 and -0.67, suggesting the treatment group consistently shows lower stress levels.
Conclusion
The simulation demonstrates that the mindfulness meditation program significantly reduces stress levels compared to the control group. The results are statistically significant and align with the hypothesis.
References
Wheeler J, Dudas K, Brooks G. Anxiety and a Mindfulness Exercise in Healthcare Simulation Prebriefing. Clinical Simulation in Nursing. 2021;59:61-66. doi:10.1016/j.ecns.2021.05.008
Torné-Ruiz A, Reguant M, Roca J. Mindfulness for stress and anxiety management in nursing students in a clinical simulation: A quasi-experimental study. Nurse Educ Pract. 2023 Jan;66:103533. doi: 10.1016/j.nepr.2022.103533. Epub 2022 Dec 6. PMID: 36516640.