The following two graphs are to be contextualized in my final assignment called “Final Assignment Battisti Sofia 2025”. Indeed, thye represent and visualize data regarding the Italian population and collected in the European Social Survey (ESS11, 2023).

The following graph illustrates the rate at which italian respondent to the ESS11 survey feel happy, ejoyed life, depressed and sad, lonely, sleep deprived, feel everything is an effort and could not get going in thier lives. 

plot(likert_table, main = "Likert Plot for CES-D8 Scale", xlab = "Percentage")

However, it might be interesting to quantify such answers and further analyse the mean and counts of the survey’s responses to create a numeric, quantifiable overview of such responses.

The following lollipop graph represents indeed the average frequency of each depressive symptom in the Italian sample, based on a 0–3 scale.
Positive feelings like “Enjoyed life” and “Felt happy” have higher mean scores, indicating they occurred more often. In contrast, symptoms like “Felt depressed” and “Felt lonely” have lower averages, suggesting they were less frequently experienced.
However, as will be explained later on the aforementioned paper, such less frequently experienced feelings still have significant implications for mental health.

kable(likert_table$results, caption = "Distribution of CES-D8 Scale Responses (Italy)", digits = 2) %>% kable_styling(full_width = F)
Distribution of CES-D8 Scale Responses (Italy)
Item None or almost none of the time Some of the time Most of the time All or almost all of the time Mean Count
Felt depressed 71.1 24.0 4.1 0.8 1.3 2840
Felt everything was an effort 52.6 37.4 7.3 2.7 1.6 2838
Sleep was restless 53.7 38.1 6.0 2.2 1.6 2850
Felt happy 14.8 43.3 34.2 7.7 2.3 2817
Felt lonely 61.8 29.6 5.9 2.7 1.5 2837
Enjoyed life 9.8 29.7 45.7 14.7 2.7 2803
Felt sad 48.3 45.3 4.5 1.9 1.6 2832
Could not get going 57.2 35.4 5.7 1.7 1.5 2825 
ggplot(likert_table$results, aes(x = reorder(Item, Mean), y = Mean)) +
  geom_segment(aes(xend = Item, yend = 0), color = "firebrick") +
  geom_point(size = 4, color = "steelblue") +
  coord_flip() +
  labs(title = "Mean CES-D8 Score per Item",
       x = "Item",
       y = "Mean Score (0–3)") +
  theme_minimal()


Considering that the average number of individuals reporting happiness is higher than those reporting sadness, it is worthwhile to investigate whether there are gender-based differences in the frequency of negative emotional experiences. Specifically, the aim is to examine whether a higher proportion of women report feeling sad, lonely, and depressed compared to men.

To do so, items “fltdpr” (felt depressed), “fltlnl” (felt lonely), and “fltsd” (felt sad), will be isolated to focus exclusively on the response categories “Most of the time” and “All or almost all of the time.” This allows to capture individuals who experience these negative emotions with greater frequency.

depression_filtered %>%
  kable(
    caption = "High Levels of Depressive Symptoms by Gender (Italy)",
    col.names = c("Symptom", "Gender", "Number of Respondents"),
    align = c("l", "c", "c"),
    format = "markdown",
    digits = 0
  ) %>%
  kable_styling(
    full_width = FALSE,
    bootstrap_options = c("striped", "hover", "condensed", "responsive"),
    font_size = 14
  )
High Levels of Depressive Symptoms by Gender (Italy)
Symptom Gender Number of Respondents
Felt depressed Female 85
Felt depressed Male 55
Felt lonely Female 161
Felt lonely Male 85
Felt sad Female 116
Felt sad Male 65 
ggplot(depression_filtered, aes(x = Item, y = Count, fill = gndr)) +
  geom_bar(stat = "identity", position = "dodge") +
  scale_fill_manual(values = c("Male" = "steelblue", "Female" = "firebrick")) +
  labs(title = "Reported High Levels of Depressive Symptoms by Gender",
       subtitle = '"Most" or "All or almost all of the time" responses only',
       x = "Depressive Symptom",
       y = "Number of Respondents",
       fill = "Gender") +
  theme_minimal()


As confirmed by the table and clearly illustrated in the accompanying graph, in Italy, individuals identifying as female tend to experience emotions commonly classified as negative more frequently than their male counterparts. Beyond the potential explanations for this phenomenon, this finding opens up the possibility for future research to explore whether this reported difference corresponds to a genuinely higher prevalence of depressive symptoms among women.