Final Project: [Investigating the Relationship Between Sleep Quality, Stress, and Reaction Time]
[Skyler Wetklow]
23 May, 2025
Introduction
Provide a brief introduction to your research question. Summarize the empirical articles you reviewed.
This psychological research analysis will be focusing on the interaction between sleep quality per night and reaction time. Further analysis will be conducted to incorporate how stress corresponds, or changes, this relationship. To provide greater depth and clarity, additional information from “The University of Split School of Medicine” and “The Journal of Sleep Medicine” is integrated to reinforce this analysis.
Literature Review
Article 1 Summary
Summarize the empirical article you selected. Discuss the key findings.
The University of Split School of Medicine conducted a study on how different aspects of sleep quality affects reaction time and thinking speed. 164 medical students completed the Pittsburgh Sleep Quality Index (PSQI) questionnaire and then completed a series of Complex Reactionmeter Drenovac (CRD) computer tests. Sleep quality didn’t show a clear link to performance. That being said, taking too long to fall asleep, sleeping less, and using sleep medications were all connected to slower reaction times. There was a strong negative relationship between worse sleep quality and an increase in occasional delays, moments of slowness, or long pauses (lapses) during the CRD testing. This supports the idea that lapses in focus and poor sleep quality are linked to slower reaction times. Even subtle sleep disturbances (such as those caused by stress) can negatively affect performance.
Article 2 Summary
Summarize the empirical article you selected. Discuss the key findings.
The Journal of Clinical Sleep Medicine looked at how sleep quality affects reaction time in women with PTSD and found out how much sleep participants thought they got (based on daily sleep diaries) predicted their reaction time and attention better than objective sleep data from devices or general sleep quality scores. Women who reported sleeping less had slower reaction times and more attention lapses. PTSD symptoms themselves did not directly predict reaction time, but the stress and exhaustion from PTSD likely made participants feel like they slept worse. This is a negative relationship. As sleep quality decreases, reaction time gets worse. So sleep quality per night, especially how it is experienced subjectively, does affect reaction time, and stress can change this relationship by intensifying the effects of perceived sleep loss.
Hypothesis
State your directional hypothesis. Specify the expected relationship between your variables. This section should be clear and concise. You need one hypothesis for IV1, one hypothesis for IV2, and one hypothesis for a predicted interaction. If you are running a logistic regression, you do not need a hypothesis for an interaction.
It is hypothesized that lower sleep quality per night will be associated with slower reaction times, as measured by the PVT. Higher self-reported stress levels are also expected to be associated with slower reaction times. Additionally, the relationship between sleep quality and reaction time is expected to be stronger among individuals reporting higher levels of stress.
Method
Sample
The Dataset selected is “Sleep Deprivation & Cognitive Performance”. It includes a population of measures taken by Stroop Task, N-Back Test, and Psychomotor Vigilance Task (PVT) related to sleep research and cognitive functions. These include, but are not limited to, sleep hours, sleep quality, emotional regulation, and reaction times. It includes demographic variables such as age, gender, BMI, and lifestyle variables like caffeine intake, physical activity levels and stress levels.
Variables and Operationalization
List your independent and dependent variables. Explain how each variable was operationalized, including the range for continuous variables and levels for categorical variables.
Loading Required Libraries
# Load your dataset in this chunk
library(readr)
sleep_deprivation_dataset_detailed <- read_csv("sleep_deprivation_dataset_detailed.csv")
View(sleep_deprivation_dataset_detailed)## Error in check_for_XQuartz(file.path(R.home("modules"), "R_de.so")): X11 library is missing: install XQuartz from www.xquartz.orgDescriptive Statistics
Present the descriptive statistics for your variables. Include appropriate measures of central tendency (mean, median), variability (standard deviation, range), and frequency distributions where applicable. Use R code chunks to generate and display your results.
# Example R code for descriptive statistics
library(psych)
describe(sleep_deprivation_dataset_detailed)## vars n mean sd median trimmed mad min
## Participant_ID* 1 60 30.50 17.46 30.50 30.50 22.24 1.00
## Sleep_Hours 2 60 5.81 1.83 5.69 5.76 2.35 3.12
## Sleep_Quality_Score 3 60 8.32 5.64 8.00 8.15 6.67 0.00
## Daytime_Sleepiness 4 60 12.00 7.58 11.50 11.98 9.64 0.00
## Stroop_Task_Reaction_Time 5 60 3.24 0.83 3.26 3.27 1.04 1.60
## N_Back_Accuracy 6 60 75.01 13.67 74.27 74.64 15.09 50.90
## Emotion_Regulation_Score 7 60 38.15 17.13 37.00 37.90 19.27 10.00
## PVT_Reaction_Time 8 60 332.54 87.80 327.21 328.96 106.94 201.56
## Age 9 60 29.52 8.17 28.50 29.27 11.12 18.00
## Gender* 10 60 1.62 0.49 2.00 1.65 0.00 1.00
## BMI 11 60 27.33 4.54 27.37 27.39 5.51 18.74
## Caffeine_Intake 12 60 2.38 1.69 2.50 2.35 2.22 0.00
## Physical_Activity_Level 13 60 4.12 3.11 4.00 3.94 3.71 0.00
## Stress_Level 14 60 17.87 11.02 17.50 17.62 13.34 0.00
## max range skew kurtosis se
## Participant_ID* 60.00 59.00 0.00 -1.26 2.25
## Sleep_Hours 8.82 5.70 0.21 -1.32 0.24
## Sleep_Quality_Score 20.00 20.00 0.20 -1.07 0.73
## Daytime_Sleepiness 24.00 24.00 0.02 -1.27 0.98
## Stroop_Task_Reaction_Time 4.49 2.89 -0.21 -1.19 0.11
## N_Back_Accuracy 99.73 48.83 0.25 -1.02 1.76
## Emotion_Regulation_Score 67.00 57.00 0.14 -1.14 2.21
## PVT_Reaction_Time 494.55 292.99 0.26 -1.17 11.33
## Age 43.00 25.00 0.20 -1.33 1.05
## Gender* 2.00 1.00 -0.47 -1.81 0.06
## BMI 34.93 16.19 -0.08 -1.23 0.59
## Caffeine_Intake 5.00 5.00 0.00 -1.34 0.22
## Physical_Activity_Level 10.00 10.00 0.36 -1.00 0.40
## Stress_Level 40.00 40.00 0.08 -1.15 1.42Statistical Analysis
Analysis
Perform your chosen analysis. Make sure your output shows.
model <- lm(PVT_Reaction_Time ~ Sleep_Quality_Score + Stress_Level, data = sleep_deprivation_dataset_detailed)
summary(model)##
## Call:
## lm(formula = PVT_Reaction_Time ~ Sleep_Quality_Score + Stress_Level,
## data = sleep_deprivation_dataset_detailed)
##
## Residuals:
## Min 1Q Median 3Q Max
## -137.35 -68.17 -7.79 65.51 178.00
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 360.9308 25.7319 14.027 <2e-16 ***
## Sleep_Quality_Score -1.7650 2.0734 -0.851 0.398
## Stress_Level -0.7675 1.0611 -0.723 0.472
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 88.15 on 57 degrees of freedom
## Multiple R-squared: 0.02626, Adjusted R-squared: -0.007909
## F-statistic: 0.7685 on 2 and 57 DF, p-value: 0.4684Post-hoc Power Analysis
Run a post-hoc power analysis with the pwr package. Use
the pwr.f2.test function for multiple regression power
analysis.
##
## Multiple regression power calculation
##
## u = 2
## v = 57
## f2 = 0.02696818
## sig.level = 0.05
## power = 0.1816535Results Interpretation
Results are interpreted clearly using APA style; connection to hypothesis is made; statistical significance and practical implications are addressed; power level is addressed.
The regression analysis found that sleep quality and stress did not signififcantly predict reaction time, F(2,57) = 0.77, p = .47, R2 = 0.03. A post-hoc power analysis showed low power (0.18), meaning the study may not have been able to detect small effects. This means the hypothesis needs more research.
Graph and Table
Include at least one table and one graph that effectively summarize your analysis and findings. Use R code chunks to generate these visualizations.
ggplot(sleep_deprivation_dataset_detailed, aes(x = Sleep_Quality_Score, y = PVT_Reaction_Time)) +
geom_point() +
geom_smooth(method = "lm", se = TRUE) +
theme_apa() +
labs(title = "Relationship Between Sleep Quality and Reaction Time", x = "Sleep Quality Score",
y = "PVT Reaction Time (ms)") 
#Example R code for creating a graph
# You will be performing a median split
# Median split for Experience to visualize the linear x linear interaction
# Plot the interaction using the median split
sleep_deprivation_dataset_detailed <- sleep_deprivation_dataset_detailed %>%
mutate(Stress_Group = ifelse(Stress_Level > median(Stress_Level, na.rm = TRUE), "High Stress", "Low Stress"))summary_table <- sleep_deprivation_dataset_detailed %>%
group_by(Stress_Group) %>%
summarise(
Mean_Reaction = mean(PVT_Reaction_Time, na.rm = TRUE),
SD_Reaction = sd(PVT_Reaction_Time, na.rm = TRUE),
Mean_Sleep = mean(Sleep_Quality_Score, na.rm = TRUE),
SD_Sleep = sd(Sleep_Quality_Score, na.rm = TRUE)
)# Display the table using knitr::kable()
kable(summary_table, caption = "Descriptive Statistics for Stress Group")| Stress_Group | Mean_Reaction | SD_Reaction | Mean_Sleep | SD_Sleep |
|---|---|---|---|---|
| High Stress | 325.617 | 82.83886 | 8.600000 | 5.739158 |
| Low Stress | 339.461 | 93.39269 | 8.033333 | 5.616990 |
Discussion
Discuss the implications of your results for psychological theory or practice. Address the following points:
Implications: Although sleep quality and stress level did not significantly predict reaction time, the observed trends and low statistical power suggest that there may still be a relationship. These findings support the idea that both sleep and stress could play a role in reaction time and cognitive performance.
Limitations: The study had a small sample size, which limited statistical power and may have prevented detection of smaller effects. Also, stress was measured on a continuous scale without considering other factors like coping mechanisms or duration of stress. These factors may have influenced the results.
Future Directions: Future studies should use more people to get stronger results. It would also help to look at different types of stress and see how they can affect reaction time. Testing sleep and stress in a controlled experiement could show cause and effect better.
References
List the articles you reviewed in APA format. Do not worry about the indentations.
Article One: “Lapses of reaction times during cognitive and psychomotor testing are the most delicate indicator of poor sleep assessed with Pittsburgh Sleep Quality Index in medical students”
Dodig, I. P., Dogas, Z., & Dogas, V . (2022). Lapses of reaction times during cognitive and psychomotor testing are the most delicate indicator of poor sleep assessed with Pittsburgh Sleep Quality Index in medical students. Sleep Medicine, 100, S34-. https://doi.org/10.1016/j.sleep.2022.05.104
Article Two: “Effect of Quality of Sleep on Choice Reaction Time, Coordination and Fatigue Level in Football Players”
. D., Sabharwal, R., & Sahana, A. (2024). Effect of Quality of Sleep on Choice Reaction Time, Coordination and Fatigue Level in Football Players. Journal of Clinical and Diagnostic Research. https://doi.org/10.7860/JCDR/2024/75486.19998