_02-12_daily_living.qmd

## Daily Living {#sec-daily-living}

{{< include _02-12_daily_living_text.qmd >}}

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

# domain
domains <- c("Daily Living")

# phenotype
pheno <- "daily_living"
```

```{r}
#| label: export-daily_living
#| include: false

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

# Filter the data frame to keep only rows where 'domain' equals 'domains'
daily_living <- daily_living |> dplyr::filter(domain %in% domains)

daily_living <- daily_living |>
  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,
    z_mean_pass,
    z_sd_pass,
    z_mean_verbal,
    z_sd_verbal,
    z_mean_timed,
    z_sd_timed
  )

# Write the resulting data frame to a new CSV file
# If the file already exists, it is overwritten (not appended)
readr::write_excel_csv(daily_living, paste0(pheno, ".csv"), na = "", col_names = TRUE, append = FALSE)
```

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

scales <- c(
  "Bill Payment",
  "Daily Living Memory Delayed Recall",
  "Daily Living Memory Delayed Recognition",
  "Daily Living Memory Immediate Recall",
  "Daily Living Memory Recall vs. Recognition",
  "Daily Living Memory Retention",
  "Driving Scenes",
  "Judgment",
  "Map Reading",
  "Medication Instructions Delayed Recall",
  "Medication Instructions Delayed Recognition",
  "Medication Instructions Immediate Recall",
  "Name/Address/Phone Delayed Recall",
  "Name/Address/Phone Delayed Recognition",
  "Name/Address/Phone Immediate Recall"
)


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

```{r}
#| label: text-daily_living
#| cache: true
#| include: false

# export text
bwu::cat_neuropsych_results(
  data = data_daily_living,
  file = "_02-12_daily_living_text.qmd"
)
```

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

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

data_daily_living_tbl <- dplyr::filter(data_daily_living, !is.na(percentile))

ordering_list <- c(
  "Driving Scenes",
  "Bill Payment",
  "Daily Living Memory Immediate Recall",
  "Daily Living Memory Delayed Recall",
  "Daily Living Memory Retention",
  "Daily Living Memory Delayed Recognition",
  # "Daily Living Memory Recall vs. Recognition",
  "Medication Instructions Immediate Recall",
  "Medication Instructions Delayed Recall",
  "Medication Instructions Delayed Recognition",
  "Name/Address/Phone Immediate Recall",
  "Name/Address/Phone Delayed Recall",
  "Name/Address/Phone Delayed Recognition",
  "Map Reading",
  "Judgment"
)

# Process the data
data_daily_living_tbl <- data_daily_living |>
  dplyr::filter(scale %in% ordering_list) |>
  dplyr::mutate(scale = factor(scale, levels = ordering_list)) |>
  dplyr::arrange(scale)

# args
table_name <- "table_daily_living"
vertical_padding <- 0
multiline <- TRUE

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

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

# Define the groups for the table
grp_daily_living <- list(
  t_score = c("NAB Daily Living", "NAB", "NAB-S", "NIH EXAMINER", "NAB Language")
)

# make `gt` table
bwu::tbl_gt(
  data = data_daily_living_tbl,
  pheno = pheno,
  table_name = table_name,
  source_note = source_note,
  # fn_t_score = fn_t_score,
  # grp_t_score = grp_daily_living[["t_score"]],
  dynamic_grp = grp_daily_living,
  vertical_padding = vertical_padding,
  multiline = multiline
)
```

```{r}
#| label: fig-daily-living-subdomain
#| include: false
#| fig-cap: "Daily Living tests evaluate functional abilities required for independent living through ecologically-valid tasks, including bill payment processing, remembering appointments and medication instructions, map navigation, driving awareness, and everyday judgment. These tasks assess how cognitive abilities translate to real-world performance, providing insight into the patient's daily functioning and independence."

# Arguments
colors <- NULL
return_plot <- TRUE
filename <- "fig_daily_living_subdomain.svg"

# variables to plot
x <- data_daily_living$z_mean_subdomain
y <- data_daily_living$subdomain

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

# Make dotplot
bwu::dotplot(
  data = data_daily_living,
  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
```



```{=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, [
            _Daily Living_ tests evaluate functional abilities required for independent living through ecologically-valid tasks, including bill payment processing, remembering appointments and medication instructions, map navigation, driving awareness, and everyday judgment. These tasks assess how cognitive abilities translate to real-world performance, providing insight into the patient's daily functioning and independence. 
            ]),
          placement: none,
          kind: "image",
          supplement: [*Figure*],
          gap: 0.5em,
          ),
        )
    }
```

```{=typst}
#let title = "Daily Living"
#let file_qtbl = "table_daily_living.png"
#let file_fig = "fig_daily_living_subdomain.svg"
#domain(
  title: [#title Scores],
  file_qtbl,
  file_fig
)
```