Import light glasses evaluation

Author

Johannes Zauner

Preface

This document imports the evaluation (of using light glasses) and shows descriptive statistics for the site.

Setup

library(tidyverse)
library(LightLogR)

Warning: package 'LightLogR' was built under R version 4.5.2

library(glue)
library(readxl)
library(gt)
library(gtsummary)

remote <- 
  "https://raw.githubusercontent.com/MeLiDosProject/Data_Metadata_Conventions/main/scripts/"

c("labeling",
  "radio_factors",
  "add_label",
  "prepare_codebook",
  "filefinder",
  "general_parameters",
  "coltype_checker",
  "tables"
) |> walk(\(x) source(paste0(remote, x, ".R")))

Preparation

#collect codebook
codebook <- 
  prepare_codebook("MeLiDosDischargeQuestionnaire_DataDictionary_2024-10-16.csv",
                   "light_glasses_evaluation")
#collect files
files <- filefinder("discharge",individual = FALSE)
#import files
data <- 
  read_csv2(files, show_col_types = FALSE) |> 
  mutate(record_id = paste0("MPI_S", record_id)) |> 
  filter(!redcap_survey_identifier %in% c(200, 217)) |> 
  mutate(glasses_use = as.logical(glasses_use))

ℹ Using "','" as decimal and "'.'" as grouping mark. Use `read_delim()` for more control.

  # drop_na(redcap_repeat_instance)
if("improvements_v3" %in% names(data)) {
  data <- data |> rename(change_behavior = improvements_v3)
}
if(!"change_behavior" %in% names(data)){
  data$change_behavior <- NA_character_
}
#check column types
coltype_check <- coltype_checker(codebook, data)
coltype_check$details |> gt()

col	expected	present	actual	type_ok	issue	expected_example
glasses_use	logical	TRUE	logical	TRUE	ok	as.logical(...)
general_feeling	character	TRUE	character	TRUE	ok	as.character(...)
challenges	character	TRUE	character	TRUE	ok	as.character(...)
act_impact	character	TRUE	character	TRUE	ok	as.character(...)
beh_adapt	character	TRUE	character	TRUE	ok	as.character(...)
social	character	TRUE	character	TRUE	ok	as.character(...)
improvements	character	TRUE	character	TRUE	ok	as.character(...)
change_behavior	character	TRUE	character	TRUE	ok	as.character(...)

#collect relevant columns
relevant_columns <- 
  coltype_check$details |> 
  pull(col) |> 
  c("record_id")
#select relevant columns
data <- data |> select(any_of(relevant_columns))
#label
data <-
data |> 
  add_radio_factors(codebook, 
                    var_col = `Variable / Field Name`, 
                    type_col = `Field Type`,
                    levels_col = `Choices, Calculations, OR Slider Labels`
                    ) |> 
  add_col_labels(codebook, var_col = `Variable / Field Name`, label_col = `Field Label`)

#reorder variables
data <- 
  data |> 
  relocate(record_id, any_of(codebook$`Variable / Field Name`))
data$record_id <- add_label(data$record_id, "Record ID")

Translate comments

Native language is translated into English with AI and later checked by a site researcher.

# library(ellmer)
# 
# chat <- chat_openai(paste0("Copy content and make translations according to specific instructions. They represent answers to questionnaires in a scientific field study."))
# 
# #Providing the input
# data_red <-
#   data |>
#   pmap(~ paste(paste(names(data), c(...), sep = ": "), collapse = ", "))
# 
# #creating an output structure
# type_data <- type_object(
#   record_id = type_string("Copy the original 'record_id' column here"),
#   general_feeling_english = type_string("Translate (or if in english already, copy) the 'general_feeling' column here. Question: How did you feel about wearing the light glasses throughout the experiment?", required = FALSE),
#   challenges_english = type_string("Translate (or if in english already, copy) the 'challenges' column here. Question: Can you describe any challenges or discomfort you experienced while wearing the light glasses? How did you cope with them?", required = FALSE),
#   act_impact_english = type_string("Translate (or if in english already, copy) the 'act_impact' column here. Question: In what situations did you notice the light glasses having the most impact on your daily activities or behavior?", required = FALSE),
#   beh_adapt_english = type_string("Translate (or if in english already, copy) the 'beh_adapt' column here. Question: How did you adapt your behaviour, if at all, because of the light glasses? Please provide some examples.", required = FALSE),
#   social_english = type_string("Translate (or if in english already, copy) the 'social' column here. Question: Were there any social situations or interactions where the presence of the light glasses caused curiosity, feedback and/or other reactions?", required = FALSE),
#   improvements_english = type_string("Translate (or if in english already, copy) the 'social' column here. Question: Can you share any suggestions or improvements for the design or functionality of the light glasses (comprising the sensor and the glasses) for future experiments?", required = FALSE),
#   change_behavior_english = type_string("Translate (or if in english already, copy) the 'social' column here. Question: At the end of the measurement week, do you think that completing the questionnaires has changed your behavior with regard to light exposure, sleep, or other factors? If so, in what way?", required = FALSE)
# )
# 
# data_llm <-
# parallel_chat_structured(
#   chat,
#   data_red,
#   type = type_data,
#   rpm = 500,
#   max_active = 100
# )
# 
# #Ensure that no NA is caught as string
# data_llm <-
#   data_llm |>
#   mutate(across(everything(), \(x) case_when(x == "NA" ~ NA, .default = x)))
# 
# #check that input and output are identical
# stopifnot("Input must by identical to output check" =
#             all(data_llm$record_id == data$record_id, na.rm = TRUE))
# 
# data_llm <-
#   data_llm |> left_join(data, by = "record_id")
# 
# path <- "../data/AI_translations/"
# if(!dir.exists(path)) dir.create(path, recursive = TRUE)
# write_csv(data_llm, "../data/AI_translations/evaluation.csv")

data_llm <- 
  read_csv("../data/AI_translations/evaluation.csv") |> 
  select(record_id, ends_with("english"))

Rows: 26 Columns: 16
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (13): record_id, general_feeling_english, challenges_english, act_impact...
lgl  (3): change_behavior_english, glasses_use, change_behavior

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

#add output to original
data <- data |> left_join(data_llm, by = c("record_id"))
data <-
  data |> 
  mutate(across(ends_with("english"), \(x) add_label(x, "English translation")
                ))

Export

data <- data |> rename(Id = record_id)
evaluation <- data
path <- "../data/imported/"
if(!dir.exists(path)) dir.create(path, recursive = TRUE)
save(evaluation, file = "../data/imported/evaluation.RData")