As a young working adult, I am constantly reminded that mental health is important. People like me are constantly faced with stress which comes from work, school, family, peers, and even from our own thoughts. Growing up, there was never a book about what it is like to be an adult and all the hardships that comes with it. We are expected to provide and take care of ourselves. But with all of this in mind, how can we take of ourselves if we don’t even have the proper resources to reach out to and get help? The system is flawed in so many ways that people are having troubles seeking what they truly need. In this research, it will explore and study the ways why the system is like this and why we need better resources to achieve a better mental health care system.
In the article, “What Young People Want from Mental Health Services: A Youth Informed Approach for the Digital Age”, it highlights that most young people face some of the highest rates of mental health struggles, yet they don’t like to seek professional support. The article made a point that we are living in the digital age, and it is essential to understand young adult’s expectation and needs from mental health services. The book drew from 400 young people asking and researching about their perspective, valuable insights, and experience living in the digital age along with their mental health problems. The article also revealed how young people manage and access their mental health service providers if they are even present and accessible.
In the article, “Overcoming Mental Health Challlenges in Higher Education”, it examines the factors contributing to mental health challenges, particularly among vulnerable student groups such as women, people of color, international students, and those from low-income households. Students in higher education tend to face a lot of stressors that negatively impact their mental well-being. These include intense academic demands, financial burdens, feelings of social isolation, experiences of trauma, and systemic exclusion related to race, gender, or cultural background. Also, the prolonged effects of the COVID-19 pandemic have intensified existing mental health challenges by increasing uncertainty, disrupting social connections, and limiting access to in-person support. Efforts to seek mental health care are often hindered by structural and institutional barriers as well, such as under-resourced counseling centers, inconsistent support services, and complex steps to achieve care. The article shows that mental health stigma and a widespread lack of confidence in mental health professionals discourage many students from reaching out for help, leading to anxiety and depression.
Independent Variable Hypothesis: Young adults with greater access to essential resources experience significantly lower levels of anxiety and depression compared to those with limited access.
Student Depression Data Set
Age, Gender, Sleep Patterns, and Profession
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.
## vars n mean sd median trimmed mad min max range skew
## Sepal.Length 1 150 5.84 0.83 5.80 5.81 1.04 4.3 7.9 3.6 0.31
## Sepal.Width 2 150 3.06 0.44 3.00 3.04 0.44 2.0 4.4 2.4 0.31
## Petal.Length 3 150 3.76 1.77 4.35 3.76 1.85 1.0 6.9 5.9 -0.27
## Petal.Width 4 150 1.20 0.76 1.30 1.18 1.04 0.1 2.5 2.4 -0.10
## Species* 5 150 2.00 0.82 2.00 2.00 1.48 1.0 3.0 2.0 0.00
## kurtosis se
## Sepal.Length -0.61 0.07
## Sepal.Width 0.14 0.04
## Petal.Length -1.42 0.14
## Petal.Width -1.36 0.06
## Species* -1.52 0.07
Perform your chosen analysis. Make sure your output shows.
Run a post-hoc power analysis with the pwr
package. Use
the pwr.f2.test
function for multiple regression power
analysis.
Results are interpreted clearly using APA style; connection to hypothesis is made; statistical significance and practical implications are addressed; power level is addressed.
Include at least one table and one graph that effectively summarize your analysis and findings. Use R code chunks to generate these visualizations.
#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
iris <- iris %>%
mutate(Sepal_Length_Split = ifelse(Sepal.Length > median(Sepal.Length), "Long Sepals", "Short Sepals"))
# Plot the interaction using the median split
ggplot(iris, aes(x = Sepal.Width, y = Petal.Length, color = Sepal_Length_Split)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE) +
labs(title = "Effect of Sepal Width on Petal Length by Sepal Length (Median Split)",
x = "Sepal Width", y = "Petal Length") +
scale_color_manual(values = c("Long Sepals" = "green", "Short Sepals" = "orange")) +
theme_apa()
# Example R code for creating a table
# Create a summary table by Species
summary_table <- iris %>%
group_by(Sepal_Length_Split) %>%
dplyr::summarise(
Petal.Length.Mean = mean(Petal.Length),
Petal.Length.SD = sd(Petal.Length),
Petal.Length.Min = min(Petal.Length),
Petal.Length.Max = max(Petal.Length)
)
# Display the table using knitr::kable()
kable(summary_table, caption = "Descriptive Statistics for Iris Sepal Length")
Sepal_Length_Split | Petal.Length.Mean | Petal.Length.SD | Petal.Length.Min | Petal.Length.Max |
---|---|---|---|---|
Long Sepals | 5.238571 | 0.6876325 | 4 | 6.9 |
Short Sepals | 2.462500 | 1.3500469 | 1 | 5.1 |
Discuss the implications of your results for psychological theory or practice. Address the following points:
List the articles you reviewed in APA format. Do not worry about the indentations.