_02-09_adhd_adult.qmd

## ADHD/Executive Functioning {#sec-adhd}

```{r}
#| label: setup-adhd
#| include: false

# Suppress warnings from being converted to errors
options(warn = 1) # Set warn to 1 to make warnings not halt execution

# domain
domains <- c("ADHD")

# target phenotype
pheno <- "adhd"
```

```{r}
#| label: export-adhd
#| include: false
#| eval: true

# Read the CSV file into a data frame
adhd <- vroom::vroom("neurobehav.csv")

# Filter the data frame based on certain conditions
# Keep only the rows where 'domain' equals 'domains' and 'z_mean_domain' is not NA
adhd <- adhd |>
  dplyr::filter(domain %in% domains)

# Select specific columns from the data frame
adhd <- adhd |>
  dplyr::select(
    test,
    test_name,
    scale,
    raw_score,
    score,
    ci_95,
    percentile,
    range,
    domain,
    subdomain,
    narrow,
    pass,
    verbal,
    timed,
    description,
    result,
    z,
    z_mean_domain,
    z_sd_domain,
    z_mean_subdomain,
    z_sd_subdomain,
    z_mean_narrow,
    z_sd_narrow
  )

# Write the 'adhd' data frame to a CSV file
# The file name is derived from the 'pheno' variable
readr::write_excel_csv(adhd, paste0(pheno, ".csv"), na = "", col_names = TRUE, append = FALSE)
```

```{r}
#| label: data-adhd
#| include: false

scales <- c(
  "Activation",
  "Focus",
  "Effort",
  "Emotion",
  "Memory",
  "Action",
  "Total Composite",
  "Inattention/Memory Problems",
  "Hyperactivity/Restlessness",
  "Impulsivity/Emotional Lability",
  "Problems with Self-Concept",
  "DSM-5 Inattentive Symptoms",
  "DSM-5 Hyperactive-Impulsive Symptoms",
  "DSM-5 ADHD Symptoms Total",
  "ADHD Index",
  # CEFI
  "Full Scale",
  "Attention",
  "Emotion Regulation",
  "Flexibility",
  "Inhibitory Control",
  "Initiation",
  "Organization",
  "Planning",
  "Self-Monitoring",
  "Working Memory",
  "Inattention/Executive Dysfunction",
  "Hyperactivity",
  "Impulsivity",
  "Emotional Dysregulation",
  "Negative Self-Concept",
  "ADHD Inattentive Symptoms",
  "ADHD Hyperactive/Impulsive Symptoms",
  "Total ADHD Symptoms",
  "ADHD Index",
  "CAARS-OR Inattention/Memory Problems",
  "CAARS-OR Hyperactivity/Restlessness",
  "CAARS-OR Impulsivity/Emotional Lability",
  "CAARS-OR Problems with Self-Concept",
  "CAARS-OR DSM-5 Inattentive Symptoms",
  "CAARS-OR DSM-5 Hyperactive-Impulsive Symptoms",
  "CAARS-OR DSM-5 ADHD Symptoms Total",
  "CAARS-OR ADHD Index",
  "CAARS-SR Inattention/Memory Problems",
  "CAARS-SR Hyperactivity/Restlessness",
  "CAARS-SR Impulsivity/Emotional Lability",
  "CAARS-SR Problems with Self-Concept",
  "CAARS-SR DSM-5 Inattentive Symptoms",
  "CAARS-SR DSM-5 Hyperactive-Impulsive Symptoms",
  "CAARS-SR DSM-5 ADHD Symptoms Total",
  "CAARS-SR ADHD Index",
  "CEFI-OR Full Scale",
  "CEFI-OR Attention",
  "CEFI-OR Emotion Regulation",
  "CEFI-OR Flexibility",
  "CEFI-OR Inhibitory Control",
  "CEFI-OR Initiation",
  "CEFI-OR Organization",
  "CEFI-OR Planning",
  "CEFI-OR Self-Monitoring",
  "CEFI-OR Working Memory",
  "CEFI-SR Full Scale",
  "CEFI-SR Attention",
  "CEFI-SR Emotion Regulation",
  "CEFI-SR Flexibility",
  "CEFI-SR Inhibitory Control",
  "CEFI-SR Initiation",
  "CEFI-SR Organization",
  "CEFI-SR Planning",
  "CEFI-SR Self-Monitoring",
  "CEFI-SR Working Memory",
  "Inattention (INATTN) Index"
)

# Filter the data using the filter_data function from the bwu library
data_adhd <- bwu::filter_data(data = adhd, domain = domains, scale = scales)
```

```{r}
#| label: text-adhd-self
#| cache: true
#| eval: true
#| include: false

# Self-report
data_adhd_self <-
  data_adhd |>
  dplyr::filter(test == "caars_sr" | test == "cefi_sr" | test == "caars2_sr" | test == "brown_efa_self" | test == "pai") |>
  dplyr::arrange(dplyr::desc(percentile)) |>
  dplyr::distinct(.keep_all = FALSE)

# Flatten the text
bwu::cat_neuropsych_results(data = data_adhd_self, file = "_02-09_adhd_adult_text_self.qmd")
```


```{r}
#| label: qtbl-adhd-self
#| dev: tikz
#| fig-process: pdf2png
#| eval: true
#| include: false

# Set the default engine for tikz to "xetex"
options(tikzDefaultEngine = "xetex")

# table arguments
pheno <- "adhd_self"
table_name <- "table_adhd_self"
vertical_padding <- 0
multiline <- TRUE

# variables
data_adhd_self <-
  dplyr::mutate(data_adhd_self, scale = stringr::str_remove_all(scale, "CAARS-SR |CEFI-SR |CAARS2 Self |Brown EF/A |PAI "))

# footnotes
# fn_standard_score <- gt::md("Standard score: Mean = 100 [50th‰], SD ± 15
# [16th‰, 84th‰].

# Lower scores reflect reduced functioning.")

fn_t_score <- gt::md("T-score: Mean = 50 [50th‰], SD ± 10 [16th‰, 84th‰].

Higher scores reflect reduced functioning.")

# fn_t_score <- gt::md("Brown EF/A T-score: Mean = 50 [50th‰], SD ± 10 [16th‰, 84th‰].

# Higher scores reflect reduced functioning.")

source_note <- gt::md("T-score: Mean = 50 [50th‰], SD ± 10 [16th‰, 84th‰].

Higher scores reflect reduced functioning.")

# source_note <- gt::md("CEFI Standard score: Mean = 100 [50th‰], SD ± 15 [16th‰, 84th‰].

# Lower scores reflect reduced functioning in the given area.")

# groupings
grp_adhd <- list(
  standard_score = c("CEFI Self-Report", "CEFI Observer-Report", "CEFI Self", "CEFI Observer"),
  t_score = c("CAARS Self-Report", "CAARS Observer-Report", "CAARS-2 Self-Report", "CAARS-2 Observer-Report", "CAARS2 Self", "CAARS2 Observer", "CAARS Self", "Brown EF/A Self-Report", "PAI")
)

grp_caars <- list(
  t_score = c("CAARS Self-Report", "CAARS Observer-Report", "CAARS-2 Self-Report", "CAARS-2 Observer-Report", "CAARS2 Self", "CAARS2 Observer", "CAARS Self")
)

grp_cefi <- list(
  standard_score = c("CEFI Self-Report", "CEFI Observer-Report", "CEFI Self", "CEFI Observer")
)

grp_self <- list(
  standard_score = c("CEFI Self-Report", "CEFI Self"),
  t_score = c("CAARS Self-Report", "CAARS-2 Self-Report", "CAARS2 Self", "CAARS Self", "Brown EF/A Self-Report", "PAI")
)

# make `gt` table
bwu::tbl_gt(
  data = data_adhd_self,
  pheno = pheno,
  table_name = table_name,
  vertical_padding = vertical_padding,
  source_note = source_note,
  # fn_standard_score = fn_standard_score,
  # fn_t_score = fn_t_score,
  # grp_standard_score = grp_self[["standard_score"]],
  # grp_t_score = grp_self[["t_score"]],
  dynamic_grp = grp_self,
  multiline = multiline
)
```


```{r}
#| label: fig-adhd-self
#| include: false
#| fig-hight: 5
#| out-height: 100%
#| fig-cap: "Attention and executive functions are multidimensional concepts that contain several related processes. Both concepts require self-regulatory skills and have some common subprocesses; therefore, it is common to treat them together, or even to refer to both processes when talking about one or the other."

# dotplot variables to plot (x, y)
x <- data_adhd_self$z
y <- data_adhd_self$scale

# dotplot arguments
filename <- "fig_adhd_self.svg"
colors <- NULL
return_plot <- TRUE

# Suppress warnings from being converted to errors
options(warn = 1) # Set warn to 1 to make warnings not halt execution

bwu::dotplot(
  data = data_adhd_self,
  x = x,
  y = y,
  colors = colors,
  return_plot = return_plot,
  filename = filename,
  na.rm = TRUE
)

# Reset warning options to default if needed
options(warn = 0) # Reset to default behavior
```


### SELF-REPORT

{{< include _02-09_adhd_adult_text_self.qmd >}}

```{=typst}
#let domain(title: none, file_qtbl, file_fig) = {
  let font = (font: "Roboto Slab", size: 0.7em)
  set text(..font)
  pad(top: 0.5em)[]
  grid(
    columns: (50%, 50%),
    gutter: 8pt,
    figure(
      [#image(file_qtbl)],
      caption: figure.caption(position: top, [#title]),
      kind: "qtbl",
      supplement: [*Table*],
    ),
    figure(
      [#image(file_fig)],
      caption: figure.caption(
        position: bottom,
        [Attention and executive functions are multidimensional concepts that contain several related processes. Both concepts require self-regulatory skills and have some common subprocesses; therefore, it is common to treat them together, or even to refer to both processes when talking about one or the other.],
      ),
      placement: none,
      kind: "image",
      supplement: [*Figure*],
      gap: 0.5em,
    ),
  )
}
```

```{=typst}
#let title = "ADHD/Executive Function Self Ratings"
#let file_qtbl = "table_adhd_self.png"
#let file_fig = "fig_adhd_self.svg"
#domain(
  title: [#title],
  file_qtbl,
  file_fig
  )
```

<!-- ### OBSERVER RATINGS -->

<!-- {{< include _02-09_adhd_adult_text_observer.qmd >}} -->

<!-- ```{=typst}
#let domain(title: none, file_qtbl, file_fig) = {
  let font = (font: "Roboto Slab", size: 0.7em)
  set text(..font)
  pad(top: 0.5em)[]
  grid(
    columns: (50%, 50%),
    gutter: 8pt,
    figure(
      [#image(file_qtbl)],
      caption: figure.caption(position: top, [#title]),
      kind: "qtbl",
      supplement: [Table],
    ),
    figure(
      [#image(file_fig)],
      caption: figure.caption(
        position: bottom,
        [
          Observer-report of the patient's ADHD symptoms and executive functioning in daily life.
        ],
      ),
      placement: none,
      kind: "image",
      supplement: [Figure],
      gap: 0.5em,
    ),
  )
}
``` -->


<!-- ```{=typst}
#let title = "ADHD Observer Ratings"
#let file_qtbl = "table_adhd_observer.png"
#let file_fig = "fig_adhd_observer.svg"
#domain(title: [#title], file_qtbl, file_fig)
``` -->