The Great Generational Divide in ‘Childish’ Perceptions

Difference between 65+ and 18-34 age groups reveals surprising patterns: while older Britons typically view more activities as childish, Star Wars and Disney Films show the opposite trend

MakeoverMonday
Data Visualization
R Programming
2025
Analysis of YouGov survey data revealing how British attitudes toward ‘kidult’ activities vary dramatically by age. While older adults typically view more hobbies as childish, entertainment franchises like Star Wars and Disney Films show surprising reversals, suggesting cultural legitimization over time.
Published

September 16, 2025

Original

The original visualization Do younger Britons see ‘kidult’ hobbies as less childish?Do younger Britons see ‘kidult’ hobbies as less childish? comes from Which ‘kidult’ hobbies and practices do Britons think are really for children?

Original visualization

Makeover

Figure 1: Diverging bar chart showing generational differences in viewing activities as childish. Comic Books have the largest gap at +28 percentage points, with older adults more likely to see it as childish. Most activities follow this pattern, but Star Wars (-3 pts) and Disney Films (-6 pts) diverge in the opposite direction, with younger people more likely to view them as childish than older adults.

Steps to Create this Graphic

1. Load Packages & Setup

Show code 
```{r}
#| label: load
#| warning: false
#| message: false
#| results: "hide"

## 1. LOAD PACKAGES & SETUP ----
suppressPackageStartupMessages({
  if (!require("pacman")) install.packages("pacman")
  pacman::p_load(
  tidyverse,  # Easily Install and Load the 'Tidyverse'
  ggtext,     # Improved Text Rendering Support for 'ggplot2'
  showtext,   # Using Fonts More Easily in R Graphs
  scales,     # Scale Functions for Visualization
  glue        # Interpreted String Literals
  )
})

### |- figure size ----
camcorder::gg_record(
    dir    = here::here("temp_plots"),
    device = "png",
    width  = 10,
    height = 8,
    units  = "in",
    dpi    = 320
)

# Source utility functions
suppressMessages(source(here::here("R/utils/fonts.R")))
source(here::here("R/utils/social_icons.R"))
source(here::here("R/utils/image_utils.R"))
source(here::here("R/themes/base_theme.R"))
```

2. Read in the Data

Show code 
```{r}
#| label: read
#| include: true
#| eval: true
#| warning: false
#|
kidult_hobbies_raw <- readxl::read_excel(
  here::here('data/MakeoverMonday/2025/pct saying kidult hobbies are entirely or mostly for children.xlsx')) |> 
  janitor::clean_names()
```

3. Examine the Data

Show code 
```{r}
#| label: examine
#| include: true
#| eval: true
#| results: 'hide'
#| warning: false

glimpse(kidult_hobbies_raw)
skimr::skim_without_charts(kidult_hobbies_raw)
```

4. Tidy Data

Show code 
```{r}
#| label: tidy
#| warning: false

kidult_hobbies_long <- kidult_hobbies_raw |>
  pivot_longer(
    cols = -age_group,
    names_to = "hobby",
    values_to = "percentage"
  ) |>
  mutate(
    hobby_clean = str_replace_all(hobby, "_", " ") |>
      str_to_title() |>
      str_replace("D D", "(D&D)") |>
      str_replace("Dungeons And Dragons", "Dungeons & Dragons"),
    age_group = factor(age_group, levels = c("18-34", "35-49", "50-64", "65+"))
  )

# plot data
plot_data <- kidult_hobbies_long |>
  filter(age_group %in% c("18-34", "65+")) |>
  pivot_wider(names_from = age_group, values_from = percentage, names_prefix = "age_") |>
  mutate(
    age_gap = `age_65+` - `age_18-34`,
    gap_direction = ifelse(age_gap > 0, "Older view as more childish", "Younger view as more childish"),
    abs_gap = abs(age_gap),
    # Add category for story-telling
    activity_type = case_when(
      hobby_clean %in% c("Comic Books", "Receiving Birthday Presents", "Advent Calendars") ~ "Traditional Childhood",
      hobby_clean %in% c("Star Wars", "Disney Films") ~ "Entertainment Reversal",
      hobby_clean %in% c("Stuffed Animals", "Dressing Up In Costumes") ~ "Physical Play",
      TRUE ~ "Other"
    )
  ) |>
  arrange(desc(age_gap))
```

5. Visualization Parameters

Show code 
```{r}
#| label: params
#| include: true
#| warning: false

### |-  plot aesthetics ----
# Get base colors with custom palette
colors <- get_theme_colors(palette = c(
  "#2c3e50", "#e17055"
))   

### |-  titles and caption ----
title_text <- str_glue("The Great Generational Divide in 'Childish' Perceptions")

subtitle_text <-str_glue(
  "Difference between 65+ and 18-34 age groups reveals surprising patterns: while older Britons\n",
  "typically view more activities as childish, Star Wars and Disney Films show the opposite trend"
)

# Create caption
caption_text <- create_mm_caption(
  mm_year = current_year,
  mm_week = current_week,
  source_text = paste0("YouGov")
)

### |-  fonts ----
setup_fonts()
fonts <- get_font_families()

### |-  plot theme ----

# Start with base theme
base_theme <- create_base_theme(colors)

# Add weekly-specific theme elements
weekly_theme <- extend_weekly_theme(
  base_theme,
  theme(
    # Legend formatting
    legend.position = "plot",
    legend.justification = "top",
    legend.margin = margin(l = 12, b = 5),
    legend.key.size = unit(0.8, "cm"),
    legend.box.margin = margin(b = 10),
    legend.title = element_text(face = "bold"),

    # Axis formatting
    axis.ticks.y = element_blank(),
    axis.ticks.x = element_line(color = "gray", linewidth = 0.5),
    # axis.ticks.length = unit(0.2, "cm"),
    axis.title.x = element_text(
      face = "bold", size = rel(0.85),
      margin = margin(t = 10)
    ),
    axis.title.y = element_text(
      face = "bold", size = rel(0.85),
      margin = margin(r = 10)
    ),
    axis.text.x = element_text(
      size = rel(0.85), family = fonts$subtitle,
      color = colors$text
    ),
    axis.text.y = element_text(
      size = rel(0.85), family = fonts$subtitle,
      color = colors$text
    ),

    # Grid lines
    panel.grid.minor = element_line(color = "#ecf0f1", linewidth = 0.2),
    panel.grid.major = element_line(color = "#ecf0f1", linewidth = 0.4),

    # Margin
    plot.margin = margin(20, 20, 20, 20)
  )
)

# Set theme
theme_set(weekly_theme)
```

6. Plot

Show code 
```{r}
#| label: plot
#| warning: false

### |- final plot ----
p <- ggplot(plot_data, aes(x = age_gap, y = reorder(hobby_clean, age_gap))) +

  # Annotate
  annotate("rect",
    xmin = -15, xmax = 0, ymin = -Inf, ymax = Inf,
    fill = colors$palette[2], alpha = 0.08
  ) +
  annotate("text",
    x = -7.5, y = 8.5, label = "Younger see as\nMORE childish",
    size = 3.5, color = colors$palette[2], fontface = "bold",
    family = fonts$text,
    hjust = 0.5, vjust = 0.5, alpha = 0.7
  ) +
  annotate("text",
    x = 15, y = 8.5, label = "Older see as\nMORE childish",
    family = fonts$text,
    size = 3.5, color = colors$palette[1], fontface = "bold",
    hjust = 0.5, vjust = 0.5, alpha = 0.7
  ) +

  # Geoms
  geom_col(aes(fill = gap_direction), alpha = 0.85, width = 0.75) +
  geom_text(
    aes(
      label = ifelse(abs(age_gap) >= 3,
        paste0(ifelse(age_gap > 0, "+", ""), round(age_gap, 0)), ""
      ),
      x = age_gap + ifelse(age_gap > 0, 1.2, -1.2)
    ),
    size = 3.2, fontface = "bold", color = colors$text,
    hjust = ifelse(plot_data$age_gap > 0, 0, 1)
  ) +
  geom_vline(xintercept = 0, color = "gray20", linewidth = 1, alpha = 0.8) +

  # Scales
  scale_fill_manual(
    values = c(
      "Older view as more childish" = colors$palette[1],
      "Younger view as more childish" = colors$palette[2]
    ),
    name = "Generation Gap Direction"
  ) +
  scale_x_continuous(
    labels = function(x) paste0(ifelse(x > 0, "+", ""), x, " pts"),
    breaks = seq(-15, 30, 5),
    limits = c(-15, 33),
    expand = expansion(mult = c(0.02, 0.02)),
    position = "top"
  ) +
  scale_y_discrete() +

  # Labs
  labs(
    title = title_text,
    subtitle = subtitle_text,
    caption = caption_text,
    x = "Percentage Point Difference (65+ minus 18-34)",
    y = NULL,
  ) +

  # Theme
  theme(
    # Grid
    panel.grid.major.x = element_line(color = "gray80", linewidth = 0.15),
    panel.grid.minor = element_blank(),
    panel.grid.major.y = element_blank(),

    # Legend
    legend.position = "none",
    axis.title.x.top = element_text(
      face = "bold", size = rel(0.85),
      margin = margin(t = 10, b = 10)
    ),
    plot.title = element_text(
      size = rel(1.85),
      family = fonts$title,
      face = "bold",
      color = colors$title,
      lineheight = 1.1,
      margin = margin(t = 5, b = 5)
    ),
    plot.subtitle = element_text(
      size = rel(0.90),
      family = fonts$subtitle,
      color = alpha(colors$subtitle, 0.9),
      lineheight = 1.2,
      margin = margin(t = 5, b = 10)
    ),
    plot.caption = element_markdown(
      size = rel(0.6),
      family = fonts$caption,
      color = colors$caption,
      hjust = 0.5,
      margin = margin(t = 15)
    )
  )
```

7. Save

Show code 
```{r}
#| label: save
#| warning: false

### |-  plot image ----  
save_plot(
  plot = p, 
  type = "makeovermonday", 
  year = current_year,
  week = current_week,
  width = 10, 
  height = 8
  )
```

8. Session Info

R version 4.4.1 (2024-06-14 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 22631)

Matrix products: default


locale:
[1] LC_COLLATE=English_United States.utf8 
[2] LC_CTYPE=English_United States.utf8   
[3] LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.utf8    

time zone: America/New_York
tzcode source: internal

attached base packages:
[1] stats     graphics  grDevices datasets  utils     methods   base     

other attached packages:
 [1] here_1.0.1      glue_1.8.0      scales_1.3.0    showtext_0.9-7 
 [5] showtextdb_3.0  sysfonts_0.8.9  ggtext_0.1.2    lubridate_1.9.3
 [9] forcats_1.0.0   stringr_1.5.1   dplyr_1.1.4     purrr_1.0.2    
[13] readr_2.1.5     tidyr_1.3.1     tibble_3.2.1    ggplot2_3.5.1  
[17] tidyverse_2.0.0 pacman_0.5.1   

loaded via a namespace (and not attached):
 [1] gtable_0.3.6      xfun_0.49         htmlwidgets_1.6.4 tzdb_0.5.0       
 [5] vctrs_0.6.5       tools_4.4.0       generics_0.1.3    curl_6.0.0       
 [9] gifski_1.32.0-1   fansi_1.0.6       pkgconfig_2.0.3   skimr_2.1.5      
[13] readxl_1.4.3      lifecycle_1.0.4   farver_2.1.2      compiler_4.4.0   
[17] textshaping_0.4.0 munsell_0.5.1     repr_1.1.7        janitor_2.2.0    
[21] codetools_0.2-20  snakecase_0.11.1  htmltools_0.5.8.1 yaml_2.3.10      
[25] pillar_1.9.0      camcorder_0.1.0   magick_2.8.5      commonmark_1.9.2 
[29] tidyselect_1.2.1  digest_0.6.37     stringi_1.8.4     rsvg_2.6.1       
[33] rprojroot_2.0.4   fastmap_1.2.0     grid_4.4.0        colorspace_2.1-1 
[37] cli_3.6.4         magrittr_2.0.3    base64enc_0.1-3   utf8_1.2.4       
[41] withr_3.0.2       timechange_0.3.0  rmarkdown_2.29    cellranger_1.1.0 
[45] ragg_1.3.3        hms_1.1.3         evaluate_1.0.1    knitr_1.49       
[49] markdown_1.13     rlang_1.1.6       gridtext_0.1.5    Rcpp_1.0.13-1    
[53] xml2_1.3.6        renv_1.0.3        svglite_2.1.3     rstudioapi_0.17.1
[57] jsonlite_1.8.9    R6_2.5.1          systemfonts_1.1.0

9. GitHub Repository

The complete code for this analysis is available in mm_2025_38.qmd.

For the full repository, click here.

10. References

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