index.qmd

---
title: "Summaries of initial survey responses"
subtitle: "Equity, diversity, and inclusion in the PsychoPy community"
author: 
  name: "Patrick Bolger, PhD | Community Development Champion"
  affiliation: "School of Psychology at the University of Nottingham"
date: now
date-format: "D MMM YYYY, h:mm a"
bibliography: bibs/grateful-refs-sumandvis.bib
csl: bibs/apa.csl
---

```{r}
#| label: turnWarningsOff 

options(warn=-1)

```


```{r}
#| label: getAndAttachPackages 
#| output: false
#| warning: false
#| message: false

# list the required packages

packagesRequired <-
  c(
    "colorblindcheck",
    "dplyr",
    "DT",
    "flextable",
    "forcats",
    "gdata",
    "ggplot2",
    "ggtext",
    "grateful",
    "gtsummary",
    "knitr",
    "magrittr",
    "purrr",
    "readr",
    "rmarkdown",
    "showtext",
    "sjlabelled",
    "sjmisc",
    "sjPlot",
    "stringr",
    "sysfonts",
    "systemfonts",
    "summarytools",
    "tibble",
    "tidyr",
    "tidyselect",
    "xfun"
    )


# Un-comment the code below to install any packages you're missing from the 
# list in packagesRequired

# packagesInstalled <- installed.packages()[,"Package"]
# packagesMissing <- packagesRequired[!(packagesRequired %in% packagesInstalled)]
# if(length(packagesMissing)) install.packages(packagesMissing, repos = getCRANmirrors()[1,"URL"])

# attach the packages
invisible(lapply(packagesRequired, require, character.only=T))

```

```{r}
#| label: getFontRaleway 
#| output: false
## use *raleway* font throughout
## an active internet connection is required for this step

font_add_google("Raleway", "raleway")
showtext_auto()

```


```{r}
#| label: readTidiedData 
#| output: false

# source of data
# The data imported here was pre-processed in another *R* script.

# Read in the data that was saved as .rds output in tidyingAndFormatting.qmd
visMain <- readRDS("data/tidyLabeledSurveyData.rds")
              
```


```{r}
#| label: importCustomFunctions

# This attaches custom themes and functions to reduce clutter and increase efficiency

source("themesAndFunctions.R")

```


# introduction

This report summarises the findings of a survey sent out to the *PsychoPy* community between 28 November 2022 and 16 March 2023. The topic was equity, diversity, and inclusion (EDI) in the *PsychoPy* community. 


::: {.callout-note title="Funding"}
The development of the survey was funded by a grant from the [Essential Open Source Software for Science](https://chanzuckerberg.com/eoss/) program at the [Chan Zuckerberg Inititiative](https://chanzuckerberg.com/). Here is the [project page at CZI](https://chanzuckerberg.com/eoss/proposals/raising-diversity-and-internationalization-in-psychopy/).
:::

It was the first, baseline version, of two identical surveys to be sent out. The second will be sent out in 2024.

It was sent out as an *announcement* to the [PsychoPy User Forum](https://discourse.psychopy.org/) on the [Discourse platform](https://discourse.org/). It was also sent out by email to a list of authors generated through a cited-reference search on the [Web of Science](https://clarivate.com/products/scientific-and-academic-research/research-discovery-and-workflow-solutions/webofscience-platform/). Specifically, these authors published multiple research studies citing one or more papers authored (or co-authored) by Jonathan Peirce over the past two decades about *PsychoPy*.

The survey contained between 25-75 questions, depending on how participants responded. 

Responses were all anonymous. That is, nowhere do we have any record of who, exactly, replied to the survey.

There were three main parts to the survey:

- participant background\
- EDI experience\      
- guidance

*Participant background* asked participants about their career status, the degree to which they were engaged in the PsychoPy community, how they contributed to the project, and if there was anything that deterred them from contributing more than they already do.

Below are the full survey categories in more detail, roughly in order of the original presentation.

- Professional & *PsychoPy* background\
  - career status\
  - type of engagement with *PsychoPy*<sup>&reg;</sup>\
  - ways of contributing\
  - deterrents to contributing\
- EDI experience\
  - gender\
  - sexual orientation\
  - race and/or culture\
  - disability and/or neurodivergence\
  - language dominance\
- *PsychoPy* Guidance\
  - awareness of *Code of Conduct*\
  - findability, searchability, & accessibility of documentation\
  - trust in enforcement of *Code of Conduct*

## general

## original order of presentation

The original presentation of the survey begins with *professional and PsychoPy background* questions. It then proceeds to issues of equity, diversity, and inclusion (*EDI*) for respondents who indicated that they not only are part of a particular identity of interest, but also feel they have been affected somehow by having that identity in the *PsychoPy* community. The survey finished with a few questions about the *Code of Conduct* and *documentation*, which we will simply call *PsychoPy guidance*. Thus:

- *Professional and PsychoPy background*\
- *EDI experience*\
- *PsychoPy guidance*

Each participant saw the all of the *professional and PsychoPy background* items on the survey, as well as the *PsychoPy guidance* items. In the section on *EDI experience*, each respondent saw at least one of the questions, with the exception of *gender*, in which case everyone saw at least two. 

The one EDI questions that everyone saw had to do with whether they identified with, or was typically associated with, one of the EDI groups. In the case of *gender*, they simply indicated what their gender was, or if it was not listed.

If they answered *yes* to any particular EDI question (or any response for *gender*), two more questions appeared. The first invited them to supply more specific information about that particular aspect of their identity, but only if they wanted to. The second had to do with whether they felt that this particular aspect of their identity had affected their interactions in the *PsychoPy*<sup>&reg;</sup> community.

Importantly, this latter question determined whether participants saw a further eight questions regarding that particular identity. If they answered *yes*, they saw those questions a little bit later in the survey. If they answered *no*, they did not. 

This has an important implication. Namely, although one may identify or be associated with a particular identity, that does not necessarily mean that one feels that it had affected one's interactions in the *PsychoPy*<sup>&reg;</sup> community. Indeed, there were many participants throughout the survey who felt that although they are associated with a particular identity, it had not affected their interactions.

Recall that for the dimension of *gender*, everyone saw the question concerning whether they felt that their interactions had suffered as a result of gender. This is because everyone has a gender identity, so there was no logical way of excluding anyone from seeing the subsequent community-interaction question.

## order of data summaries

Each of the headings in the list above above is depicted below with a visualization, followed by a table of the data, and in the cases of identity, a table of labels that some participants optionally supplied to describe themselves on that particular EDI variable.

Ultimately however, it makes more sense to present the data summaries in a different order. Specifically, it would be informative to see how the background variables and related issues interact with the EDI variables. Therefore, the background and guidance variables are presented *after* the EDI variables, giving us a data-summary order as follows:

- *EDI experience*\
- *Professional & PsychoPy background*\
- *PsychoPy Guidance*

Each background and guidance variable is presented in isolation first, but then followed by two-way interactions with the EDI variables of *gender*, *sexual orientation*, *race/culture*, *disability/neurodivergence*, and *written-English language dominance*. In some cases, the interactions with the latter four EDI variables are presented in a single figure.

To the extent possible, each summary is available as a link in the sidebar. However, some interactions were grouped together and don't have links, *per se*. Most commonly, interactions with *gender* are linked, followed by interactions with *other EDI variables*.

Note that none of the questions required responses. This means that there will be plenty of non-responses in the summaries below. These are indicated as either *NA* or *missing*.

---

# data summaries

## participant EDI experience

The second group of items on the survey (again, presented first here) collected information about selected dimensions of equity, diversity, and inclusion, namely *gender*, *sexual orientation*, *race* and/or *culture*, *disability* and/or *neurodivergence*, and *language dominance*.

For each dimension, participants were asked if they identified with the dimension, or whether they thought that others would associate them with it, along with the optional opportunity to supply more information about their own specific identity along this dimension.

Crucially, they were also asked whether they felt that that identity or association had affected their interactions in the *PsychoPy*<sup>&reg;</sup> community. If they answered in the affirmative, they saw eight more questions related to this identity shortly thereafter in the survey.

Thus, the reader will notice that the sample sizes uniformly differ greatly between those who answered the background questions, and those who answered the eight further questions.

These eight further questions fell into three categories in the manner shown below:

- ***Treatment by others***\
  - *negative perception*\
  - *need to hide identity*\
  - *dismissiveness towards contributions*\
  - *target of derisive comments*\
  - *target of microaggressions*\
- ***Self-regard***\
  - *self-doubt*\
  - *stereotype threat*\
- ***Isolation***\
  - *a desire to interact with others more like themselves*
  
Participants could agree or disagree with each of these statements using a `1`-`7` Likert scale, where `1` indicated *Strongly disagree* and a `7` indicated *Strongly agree*.

::: {.callout-note}
Note that on the `1`-`7` scale for each of the statements, the number `4` is directly in the middle of the scale, which can be interpreted as neither agreeing nor disagreeing. You will see that we set responses of `4` to the side of the respective stacked frequency barplots, in yellow.

Also, the barplots are sorted within each category (*treatment*, *self-regard*, and *isolation*) along descending frequency of agreement. That is, the topmost barplot within each category is the one with highest number of agreements, whereas the bottom-most barplot within each category is the one with the highest number of disagreements.
:::
  
Summaries of the responses to these statements are provided below after the respective questions concerning their identity.


### gender

The first EDI category is *gender*. We present the responses to the issue of identity, followed by a table of descriptions (supplied by some of the participants). This is followed by whether the participant felt affected in the *PsychoPy*<sup>&reg;</sup> community by that identity. Finally, we summarise the participants responses to items listed under *treatment* (by others), *self-regard*, and *isolation*. 


#### identity

The sections directly below summarise, both visually and verbally, the answer to the following question:

>`r get_label(visMain$gender)`

##### figure

```{r}
#| label: gender-plot
#| fig-alt: "Barplot of responses to the following statement: 'Which gender do you identify most with?'"

visMain |> 
  select(gender) |> 
  mutate(gender = forcats::fct_na_value_to_level(gender, level = "(missing)")) |>
  freqPlot(
    ostColour = ostBlue,
    sorting = "none"
  )
gdata::mv("p", "GnWh") # p is sent to the global env. from the function
suppressWarnings(print(GnWh))

```

##### table

```{r}
#| label: gender-count-table
#| tbl-cap: "Summary of responses to gender."
#| output: asis

visMain |>
  select(gender) |>
  mutate(gender = forcats::fct_na_value_to_level(gender, level = "(missing)")) |>
  tbl_summary() |>
  modify_header(label = "**Question**") |>
  as_flex_table() |>
  flextable::flextable_to_rmd()

```

##### descriptions

If participants chose ***not listed*** as an answer above, they were given the opportunity to describe their gender in their own words, though doing so was optional. For those who did, the table below lists the descriptions they provided. The "NA" in the table refers to those who either did not see the question or chose not to supply a description. 

The question was as follows:

>`r get_label(visMain$genderDesc)`

```{r}
#| label: gender-desc-table
#| tbl-cap: Descriptions of gender identities volunteered by participants

visMain |> 
  count(genderDesc) |>
  arrange(desc(n)) |>
  datatable(
    class = 'cell-border stripe',
    colnames = c(
      "Feel free to describe your gender here (or not)",
      "count"
      ),
    options = list(
      columnDefs = list(
        list(
          targets = 1,
          render = JS(
            "function(data, type, row, meta) {",
            "return data === null ? 'NA' : data;",
            "}"
            )
          )
        )
      )
    )


```


---

#### felt affected

The sections directly below summarise, both visually and verbally, the answer to the following question:

>`r get_label(visMain$genderAffected)`

##### figure

```{r}
#| label: gender-affected-plot
#| fig-alt: "Barplot of responses to: 'Do you feel that your gender status has affected your interactions with the PsychoPy community or software ecosystem?'"

visMain |> 
  select(genderAffected) |> 
  mutate(genderAffected = forcats::fct_na_value_to_level(genderAffected, level = "(missing)")) |>
  freqPlot(
    ostColour = ostOrange,
    sorting = "none"
  )
gdata::mv("p", "GnFa") # p is sent to the global env. from the function
suppressWarnings(print(GnFa))

```

##### table

```{r}
#| label: gender-felt-affected-count-table
#| tbl-cap: "Summary of responses to whether participants felt affected by their gender identity."
#| output: asis

visMain |>
  select(genderAffected) |>
  mutate(genderAffected = forcats::fct_na_value_to_level(genderAffected, level = "(missing)")) |>
  tbl_summary() |>
  modify_header(label = "**Question**") |>
  as_flex_table() |>
  flextable::flextable_to_rmd()

```

::: {.callout-important}
Important: The question directly above regarding gender determined whether or not the participant saw the respective items directly below regarding *treatment (by others)*, *self-regard*, and *isolation*.
:::

---

#### treatment, self-regard, isolation

The following statements were seen only by the subset of participants noted above. Specifically, they were restricted to the **`r numbers_to_words(length(which(visMain$genderAffected=="Yes")))`** who replied ***yes*** to the question asking them whether they had felt that their gender identity has affected their interactions with the *PsychoPy*<sup>&reg;</sup> community. Of those, **`r numbers_to_words(length(which(!is.na(visMain$genderNegPerc))))`** provided responses, seen below.

The exact questions are listed in the verbal summary after the visualization.

##### figure

```{r}
#| label: gender-likert-plot
#| warning: false
#| fig-alt: "Stacked frequency barplots of responses to several statements on gender, categorised into the following: treatment by others, self-regard, and isolation." 

visMain |> 
  select(genderNegPerc:genderOthersLikeMe) |> 
  stackedLikertGroups(likertTitle = "Gender")
gdata::mv("p", "GnLk") # p is sent to the global env. from the function
suppressWarnings(print(GnLk))

```

##### table

```{r}
#| label: gender-stats-table
#| tbl-cap: "Statistics for responses to statements regarding gender"
#| output: asis

visMain |>
  select(genderNegPerc:genderOthersLikeMe) |>
  likertTable(
    lowerBound = "1 = Strongly disagree",
    upperBound = "7 = Strongly agree",
    byVar = NULL,
    spanVar <- NULL
  )

```


<!-- {{< include notes/_gender.md >}} -->

---


### sexual orientation

The second EDI category is *sexual orientation*. As above, we present the responses to the issue of identity, followed by a table of descriptions (supplied by some of the participants). This is followed by whether the participant felt affected in the *PsychoPy*<sup>&reg;</sup> community by that identity. Finally, we summarise the participants responses to items listed under *treatment* (by others), *self-regard*, and *isolation*. 


#### identity

##### figure

```{r}
#| label: nonhetero-plot
#| fig-alt: "Barplot of responses to the following: 'Do you, or might others who know you well, consider you somehow NOT to be part of the heterosexual community?'"

visMain |> 
  select(nonHeteroCommunity) |> 
  mutate(nonHeteroCommunity = forcats::fct_na_value_to_level(nonHeteroCommunity, level = "(missing)")) |>
  freqPlot(
    ostColour = ostYellow,
    sorting = "none"
  )
gdata::mv("p", "NhId") # p is sent to the global env. from the function
suppressWarnings(print(NhId))

```

##### table

```{r}
#| label: sexuality-count-table
#| tbl-cap: "Summary of responses to sexual orientation"
#| output: asis

visMain |>
  select(nonHeteroCommunity) |>
  mutate(nonHeteroCommunity = forcats::fct_na_value_to_level(nonHeteroCommunity, level = "(missing)")) |>
  tbl_summary() |>
  modify_header(label = "**Question**") |>
  as_flex_table() |>
  flextable::flextable_to_rmd()

```

---

##### descriptions

If participants chose ***yes*** as an answer above, they were given the opportunity to describe their sexual identity, though doing so was optional. For those who did, the table below lists the descriptions they provided. The "NA" in the table refers to those who either did not see the question or chose not to supply a description.

The question was as follows:

>`r get_label(visMain$nonHeteroDesc)`

```{r}
#| label: nonhetero-desc-table
#| tbl-cap: "Descriptions of sexual orientation volunteered by participants"

visMain |> 
  count(nonHeteroDesc) |>
  arrange(desc(n)) |>
  datatable(
    class = 'cell-border stripe',
    colnames = c(
      "Feel free to describe your sexual orientation here (or not)",
      "count"
      ),
    options = list(
      columnDefs = list(
        list(
          targets = 1,
          render = JS(
            "function(data, type, row, meta) {",
            "return data === null ? 'NA' : data;",
            "}"
            )
          )
        )
      )
    )

```

---

#### felt affected

The sections directly below summarise, both visually and verbally, the answer to the following question:

>`r get_label(visMain$nonHeteroAffected)`

##### figure

```{r}
#| label: nonhetero-affected-plot
#| fig-alt: "Barplot of responses to the following: 'Do you feel that your sexual orientation has affected your interactions with the PsychoPy community...?'"

visMain |> 
  select(nonHeteroAffected) |> 
  mutate(nonHeteroAffected = forcats::fct_na_value_to_level(nonHeteroAffected, level = "(missing)")) |>
  freqPlot(
    ostColour = ostBlue,
    sorting = "none"
  )
gdata::mv("p", "NhFa") # p is sent to the global env. from the function
suppressWarnings(print(NhFa))

```

##### table

```{r}
#| label: sexuality-felt-affected-count-table
#| tbl-cap: "Summary of responses to whether participants felt affected by their sexual orientation"
#| output: asis

visMain |>
  select(nonHeteroAffected) |>
  mutate(nonHeteroAffected = forcats::fct_na_value_to_level(nonHeteroAffected, level = "(missing)")) |>
  tbl_summary() |>
  modify_header(label = "**Question**") |>
  as_flex_table() |>
  flextable::flextable_to_rmd()

```

::: {.callout-important}
Important: The question directly above regarding sexual orientation determined whether or not the participant saw the respective items directly below regarding *treatment (by others)*, *self-regard*, and *isolation*.
:::

---

#### treatment, self-regard, isolation

The following statements were seen only by the subset of participants noted above. Specifically, they were restricted to the **`r numbers_to_words(length(which(visMain$nonHeteroAffected=="Yes")))`** who replied ***yes*** to the question asking them whether they had felt that their sexual orientation has affected their interactions with the *PsychoPy*<sup>&reg;</sup> community. Of those, **`r numbers_to_words(length(which(!is.na(visMain$nonHeteroNegPerc))))`** provided responses, seen below.

The exact questions are listed in the verbal summary after the visualization.

##### figure

```{r}
#| label: nonhetero-likert-plot
#| warning: false
#| fig-alt: "Stacked frequency barplots of responses to several statements on sexuality, categorised into the following: treatment by others, self-regard, and isolation." 

visMain |>
  select(nonHeteroNegPerc:nonHeteroOthersLikeMe) |> 
  stackedLikertGroups(likertTitle = "Non-heterosexuality")
gdata::mv("p", "NhLk") # p is sent to the global env. from the function
suppressWarnings(print(NhLk))

```

##### table

```{r}
#| label: nonhetero-stats-table
#| tbl-cap: "Statistics for responses to statements regarding sexual orientation"
#| output: asis

visMain |>
  select(nonHeteroNegPerc:nonHeteroOthersLikeMe) |>
  likertTable(
    lowerBound = "1 = Strongly disagree",
    upperBound = "7 = Strongly agree",
    byVar = NULL,
    spanVar <- NULL
  )
  
```


<!-- {{< include notes/_nonhetero.md >}} -->

---

### race / culture

The third EDI category is *race* and/or *culture*. As before, we present the responses to the issue of identity, followed by a table of descriptions (supplied by some of the participants). This is followed by whether the participant felt affected in the *PsychoPy*<sup>&reg;</sup> community by that identity. Finally, we summarise the participants responses to items listed under *treatment* (by others), *self-regard*, and *isolation*. 



#### identity

##### figure

```{r}
#| label: raceculture-plot
#| fig-alt: "Barplot of responses to: 'Do you, or might others who know you well, consider you part of a race/culture that is potentially discriminated against?'"

visMain |> 
  select(raceCulture) |> 
  mutate(raceCulture = forcats::fct_na_value_to_level(raceCulture, level = "(missing)")) |>
  freqPlot(
    ostColour = ostOrange,
    sorting = "none"
  )
gdata::mv("p", "RcId") # p is sent to the global env. from the function
suppressWarnings(print(RcId))

```

##### table

```{r}
#| label: race-count-table
#| tbl-cap: "Summary of responses to race and/or culture"
#| output: asis

visMain |>
  select(raceCulture) |>
  mutate(raceCulture = forcats::fct_na_value_to_level(raceCulture, level = "(missing)")) |>
  tbl_summary() |>
  modify_header(label = "**Question**") |>
  as_flex_table() |>
  flextable::flextable_to_rmd()

```

---

##### descriptions

If participants chose ***yes*** as an answer above, they were given the opportunity to describe their race(s) and/or culture(s), though doing so was optional. For those who did, the table below lists the descriptions they provided. The "NA" in the table refers to those who either did not see the question or chose not to supply a description.

The question was as follows:

>`r get_label(visMain$raceCultureDesc)`

```{r}
#| label: raceculture-desc-table
#| tbl-cap: Descriptions of race and/or culture volunteered by participants

visMain |> 
  count(raceCultureDesc) |>
  arrange(desc(n)) |>
  datatable(
    class = 'cell-border stripe',
    colnames = c(
      "Feel free to describe your race and/or culture here (or not)",
      "count"
      ),
    
    options = list(
      columnDefs = list(
        list(
          targets = 1,
          render = JS(
            "function(data, type, row, meta) {",
            "return data === null ? 'NA' : data;",
            "}"
            )
          )
        )
      )
    )

```

---

#### felt affected

The sections directly below summarise, both visually and verbally, the answer to the following question:

>`r get_label(visMain$raceCultureAffected)`

##### figure

```{r}
#| label: raceculture-affected-plot
#| fig-alt: "Frequency barplot of responses to the following statement: 'Do you feel that your race and/or culture has affected your interactions with the PsychoPy community or software ecosystem?' If participants chose to respond, they could respond with either 'yes' or 'no.'"


visMain |> 
  select(raceCultureAffected) |> 
  mutate(raceCultureAffected = forcats::fct_na_value_to_level(raceCultureAffected, level = "(missing)")) |>
  freqPlot(
    ostColour = ostYellow,
    sorting = "none"
  )
gdata::mv("p", "RcFa") # p is sent to the global env. from the function
suppressWarnings(print(RcFa))

```

##### table

```{r}
#| label: race-felt-affected-count-table
#| tbl-cap: "Summary of responses to whether participants felt affected by their race and/or culture"
#| output: asis

visMain |>
  select(raceCultureAffected) |>
  mutate(raceCultureAffected = forcats::fct_na_value_to_level(raceCultureAffected, level = "(missing)")) |>
  tbl_summary() |>
  modify_header(label = "**Question**") |>
  as_flex_table() |>
  flextable::flextable_to_rmd()

```

::: {.callout-important}
Important: The question directly above regarding race and/our culture determined whether or not the participant saw the respective items directly below regarding *treatment (by others)*, *self-regard*, and *isolation*.
:::

---

#### treatment, self-regard, isolation

The following statements were seen only by the subset of participants noted above. Specifically, they were restricted to the **`r numbers_to_words(length(which(visMain$raceCultureAffected=="Yes")))`** who replied ***yes*** to the question asking them whether they had felt that their racial and/or cultural identity has affected their interactions with the *PsychoPy*<sup>&reg;</sup> community. Of those, **`r numbers_to_words(length(which(!is.na(visMain$raceCultureNegPerc))))`** provided responses, seen below.

The exact questions are listed in the verbal summary after the visualization.

##### figure

```{r}
#| label: raceculture-likert-plot
#| warning: false
#| fig-alt: "Stacked frequency barplots of responses to statements on race/culture, categorised into the following: treatment by others, self-regard, and isolation." 

visMain |>
  select(raceCultureNegPerc:raceCultureOthersLikeMe) |> 
  stackedLikertGroups(
    likertTitle = "Race(s) and/or Culture(s)"
    )
gdata::mv("p", "RcLk") # p is sent to the global env. from the function
suppressWarnings(print(RcLk))

```

##### table

```{r}
#| label: raceculture-stats-table
#| tbl-cap: "Statistics for responses to statements regarding race and/or culture"
#| output: asis

visMain |>
  select(raceCultureNegPerc:raceCultureOthersLikeMe) |> 
  likertTable(
    lowerBound = "1 = Strongly disagree",
    upperBound = "7 = Strongly agree",
    byVar = NULL,
    spanVar <- NULL
  )

```


<!-- {{< include notes/_raceculture.md >}} -->

---

### disability / neurodivergence

The fourth EDI category is *disability* and/or *neurodivergence*. As above, we present the responses to the issue of identity, followed by a table of descriptions (supplied by some of the participants). This is followed by whether the participant felt affected in the *PsychoPy*<sup>&reg;</sup> community by that identity. Finally, we summarise the participants responses to items listed under *treatment* (by others), *self-regard*, and *isolation*.



#### identity

##### figure

```{r}
#| label: disability-plot
#| fig-alt: "Frequency barplot of responses to the following question: 'Do you, or might others who know you well, consider you disabled and/or neurodivergent (i.e., visible or invisible; e.g., blind, paralysed, cerebral palsy, ASD, ADHD)?' If participants chose to respond, they could respond with either 'yes' or 'no.'"

visMain |> 
  select(disability) |> 
  mutate(disability = forcats::fct_na_value_to_level(disability, level = "(missing)")) |>
  freqPlot(
    ostColour = ostBlue,
    sorting = "none"
  )
gdata::mv("p", "DnId") # p is sent to the global env. from the function
suppressWarnings(print(DnId))

```

##### table

```{r}
#| label: disability-count-table
#| tbl-cap: "Summary of responses to disability and/or neurodivergence"
#| output: asis

visMain |>
  select(disability) |>
  mutate(disability = forcats::fct_na_value_to_level(disability, level = "(missing)")) |>
  tbl_summary() |>
  modify_header(label = "**Question**") |>
  as_flex_table() |>
  flextable::flextable_to_rmd()

```

---

##### descriptions

If participants chose ***yes*** as an answer above, they were given the opportunity to describe their disability(-ies) and/or neurodivergence, though doing so was optional. For those who did, the table below lists the descriptions they provided. The "NA" in the table refers to those who either did not see the question or chose not to supply a description.

The question was as follows:

>`r get_label(visMain$disabilityDesc)`


```{r}
#| label: disability-desc-table
#| tbl-cap: Descriptions of disability volunteered by participants

visMain |> 
  count(disabilityDesc) |>
  arrange(desc(n)) |>
  datatable(
    class = 'cell-border stripe',
    colnames = c(
      "Feel free to describe your disabled and/or neurodivergent status (or not)",
      "count"
      ),
    
    options = list(
      columnDefs = list(
        list(
          targets = 1,
          render = JS(
            "function(data, type, row, meta) {",
            "return data === null ? 'NA' : data;",
            "}"
            )
          )
        )
      )
    )

```

---

#### felt affected

The sections directly below summarise, both visually and verbally, the answer to the following question:

>`r get_label(visMain$disabilityAffected)`

##### figure

```{r}
#| label: disability-affected-plot
#| fig-alt: "Frequency barplot of responses to the following statement: 'Do you feel that your disabled and/or neurodivergent status has affected your interactions with the PsychoPy community or software ecosystem?' If participants chose to respond, they could respond with either 'yes' or 'no.'"

visMain |> 
  select(disabilityAffected) |> 
  mutate(disabilityAffected = forcats::fct_na_value_to_level(disabilityAffected, level = "(missing)")) |>
  freqPlot(
    ostColour = ostOrange,
    sorting = "none"
  )
gdata::mv("p", "DnFa") # p is sent to the global env. from the function
suppressWarnings(print(DnFa))

```

##### table

```{r}
#| label: disability-felt-affected-count-table
#| tbl-cap: "Summary of responses to whether participants felt affected by their disability and/or neurodivergence"
#| output: asis

visMain |>
  select(disabilityAffected) |>
  mutate(disabilityAffected = forcats::fct_na_value_to_level(disabilityAffected, level = "(missing)")) |>
  tbl_summary() |>
  modify_header(label = "**Question**") |>
  as_flex_table() |>
  flextable::flextable_to_rmd()

```

::: {.callout-important}
Important: The question directly above regarding disability and/or neurodivergence determined whether or not the participant saw the respective items directly below regarding *treatment (by others)*, *self-regard*, and *isolation*.
:::

---

#### treatment, self-regard, isolation

The following statements were seen only by the subset of participants noted above. Specifically, they were restricted to the **`r numbers_to_words(length(which(visMain$disabilityAffected=="Yes")))`** who replied ***yes*** to the question asking them whether they had felt that their disability and/or neurodivergence has affected their interactions with the *PsychoPy*<sup>&reg;</sup> community. Of those, **`r numbers_to_words(length(which(!is.na(visMain$disabilityNegPerc))))`** provided responses, seen below.

The exact questions are listed in the verbal summary after the visualization.

##### figure

```{r}
#| label: disability-likert-plot
#| warning: false
#| fig-alt: "Stacked frequency barplots of responses to disability/neurodivergence, categorised into the following: treatment by others, self-regard, and isolation." 

visMain |>
  select(disabilityNegPerc:disabilityOthersLikeMe) |> 
  stackedLikertGroups(likertTitle = "Disability and/or neurodivergence")
gdata::mv("p", "DnLk") # p is sent to the global env. from the function
suppressWarnings(print(DnLk))

```


##### table

```{r}
#| label: disability-stats-table
#| tbl-cap: "Statistics for responses to statements regarding disability"
#| output: asis

visMain |>
  select(disabilityNegPerc:disabilityOthersLikeMe) |> 
  likertTable(
    lowerBound = "1 = Strongly disagree",
    upperBound = "7 = Strongly agree",
    byVar = NULL,
    spanVar <- NULL
  )

```


<!-- {{< include notes/_disability.md >}} -->

---



### written-English language dominance

The fifth EDI category is *written-English language dominance*. As before, we present the responses to the issue of identity, followed by a table of descriptions (supplied by some of the participants). This is followed by whether the participant felt affected in the *PsychoPy*<sup>&reg;</sup> community by that identity. Finally, we summarise the participants responses to items listed under *treatment* (by others), *self-regard*, and *isolation*.



#### identity

##### figure

```{r}
#| label: dominant-language-plot
#| fig-alt: "Frequency barplot of responses to the following question: 'Is your dominant (preferred) written language English?' If participants chose to respond, they could respond with either 'yes' or 'no.'"

visMain |> 
  select(domLangEnglish) |> 
  mutate(domLangEnglish = forcats::fct_na_value_to_level(domLangEnglish, level = "(missing)")) |>
  freqPlot(
    ostColour = ostYellow,
    sorting = "none"
  )
gdata::mv("p", "DlWe") # p is sent to the global env. from the function
suppressWarnings(print(DlWe))


```

##### table

```{r}
#| label: domlang-count-table
#| tbl-cap: "Summary of responses to written-English language dominance"
#| output: asis

visMain |>
  select(domLangEnglish) |>
  mutate(domLangEnglish = forcats::fct_na_value_to_level(domLangEnglish, level = "(missing)")) |>
  tbl_summary() |>
  modify_header(label = "**Question**") |>
  as_flex_table() |>
  flextable::flextable_to_rmd()

```

---

##### descriptions

If participants chose ***no*** as an answer above, they were given the opportunity to describe their dominant language, though doing so was optional. For those who did, the table below lists the descriptions they provided. The "NA" in the table refers to those who either did not see the question or chose not to supply a description.

The question was as follows:

>`r get_label(visMain$domLangDesc)`

```{r}
#| label: domlang-desc-table
#| tbl-cap: Non-dominant languages volunteered by participants

visMain |> 
  count(domLangDesc) |>
  arrange(desc(n)) |>
  datatable(
    class = 'cell-border stripe',
    colnames = c(
      "Feel free to type in your dominant language (or not)",
      "count"
      ),
    
    options = list(
      columnDefs = list(
        list(
          targets = 1,
          render = JS(
            "function(data, type, row, meta) {",
            "return data === null ? 'NA' : data;",
            "}"
            )
          )
        )
      )
    )

```

---

#### felt affected

The sections directly below summarise, both visually and verbally, the answer to the following question:

>`r get_label(visMain$domLangAffected)`

##### figure

```{r}
#| label: dominant-language-affected-plot
#| fig-alt: "Frequency barplot of responses to the following statement: 'Do you feel that your dominant language has affected your interactions with the PsychoPy community or software ecosystem?' If participants chose to respond, they could respond with either 'yes' or 'no.'"

visMain |> 
  select(domLangAffected) |> 
  mutate(domLangAffected = forcats::fct_na_value_to_level(domLangAffected, level = "(missing)")) |>
  freqPlot(
    ostColour = ostBlue,
    sorting = "none"
  )
gdata::mv("p", "DlFa") # p is sent to the global env. from the function
suppressWarnings(print(DlFa))

```

##### table

```{r}
#| label: domlangEng-felt-affected-count-table
#| tbl-cap: "Summary of responses to whether participants felt affected by their non-English written-language dominance"
#| output: asis

visMain |>
  select(domLangAffected) |>
  mutate(domLangAffected = forcats::fct_na_value_to_level(domLangAffected, level = "(missing)")) |>
  tbl_summary() |>
  modify_header(label = "**Question**") |>
  as_flex_table() |>
  flextable::flextable_to_rmd()

```

::: {.callout-important}
Important: The question directly above regarding language dominance in written English determined whether or not the participant saw the respective items directly below regarding *treatment (by others)*, *self-regard*, and *isolation*.
:::

---

#### treatment, self-regard, isolation

The following statements were seen only by the subset of participants noted above. Specifically, they were restricted to the **`r numbers_to_words(length(which(visMain$domLangAffected=="Yes")))`** who replied ***yes*** to the question asking them whether they had felt that their language dominance has affected their interactions with the *PsychoPy*<sup>&reg;</sup> community. Of those, **`r numbers_to_words(length(which(!is.na(visMain$domLangNegPerc))))`** provided responses, seen below.

The exact questions are listed in the verbal summary after the visualization.

##### figure

```{r}
#| label: domlang-likert-plot
#| warning: false
#| fig-alt: "Stacked frequency barplots of responses to language dominance, categorised by the following: treatment by others, self-regard, and isolation." 

visMain |>
  select(domLangNegPerc:domLangOthersLikeMe) |> 
  stackedLikertGroups(likertTitle = "Dominant Language")
gdata::mv("p", "DlLk") # p is sent to the global env. from the function
suppressWarnings(print(DlLk))

```

##### table

```{r}
#| label: domlang-stats-table
#| tbl-cap: "Statistics for responses to statements regarding dominant language"
#| output: asis

visMain |>
  select(domLangNegPerc:domLangOthersLikeMe) |> 
  likertTable(
    lowerBound = "1 = Strongly disagree",
    upperBound = "7 = Strongly agree",
    byVar = NULL,
    spanVar <- NULL
  )

```


<!-- {{< include notes/_domlang.md >}} -->

---


## participant background

The first few items on the survey collected information about  general background demographics, including participants' career status, the role they typically play in their usage of *PsychoPy*<sup>&reg;</sup>. 

Unlike the items above that directly address dimensions of equity, diversity, and inclusion, everyone was able to answer the questions below. However, we can still view each item with respect to whether responses varied according to the various groups that respondents identified with.

These are covered in the subsections below.

```{r}
#| label: importLongFiles
# These are for some of the interactions between EDI variables
# and background variables

longerDataSimple <- readRDS("data/longerDataSimple.rds")
longerDataContributions <- readRDS("data/longerDataContributions.rds")
longerDataDeterrents <- readRDS("data/longerDataDeterrents.rds")

```


### career status

This section summarises, both visually and verbally, the answer to the following question:

>`r get_label(visMain$careerStatus)`

Participants had to choose from one of the following:

- *Researcher - early career (e.g. PhD, postdoc)*\
- *Researcher - mid career (e.g. Assistant/Associate Professor)*\
- *Researcher - senior (e.g. Full Professor)*\
- *Technical - junior*\
- *Technical - senior*

#### everyone 

The visualization below presents responses in descending order of frequency.

##### figure

```{r}
#| label: career-status-plot
#| fig-alt: "Descending frequency barplot of the responses to the following question: 'Roughly speaking, what is your career status?'"

visMain |>
  select(careerStatus) |>
  mutate(careerStatus = forcats::fct_na_value_to_level(careerStatus, level = "(missing)")) |>
  freqPlot(
    ostColour = ostBlue, 
    sorting = "desc"
    )
gdata::mv("p", "CsWh") # p is sent to the global env. from the function
suppressWarnings(print(CsWh))

```

##### table

```{r}
#| label: career-status-count-table
#| tbl-cap: "Summary of responses to career status"
#| output: asis

visMain |>
  select(careerStatus) |>
  mutate(careerStatus = forcats::fct_na_value_to_level(careerStatus, level = "(missing)")) |>
  tbl_summary() |>
  modify_header(label = "**Question**") |>
  as_flex_table() |>
  flextable::flextable_to_rmd()

```


<!-- {{< include notes/_careerStatus.md >}} -->

---

#### interactions

##### gender

###### figure

```{r}
#| label: career-status-by-gender-plot
#| fig-alt: "Descending frequency barplot of the responses by gender to the following question: 'Roughly speaking, what is your career status?'"

contingencyPlot(
  df = visMain,
  contingX = "careerStatus",
  contingGrp = "gender",
  colours = ostColours4na
  )
gdata::mv("p", "Cs_Gn") # p is sent to the global env. from the function
suppressWarnings(print(Cs_Gn))

```

###### table

```{r}
#| label: careerstatus-by-gender-stats-table
#| tbl-cap: "Summary of responses to career status by gender."
#| output: asis

visMain |>
  contingencyTable(
    contingX = "careerStatus", 
    contingGrp = "gender"
    )

```

##### other EDI dimensions

{{< include interactionNotes.qmd >}}

###### figure

```{r}
#| label: career-status-by-other-edis-plot
#| fig-alt: "Wrapped, stacked frequency barplots of the responses by EDI variables other than gender to the following question: 'Roughly speaking, what is your career status?'"

careerStatusLabel <- get_label(longerDataSimple$careerStatus)

longerDataSimple |>
  #drop_na(response) |>
  #drop_na(careerStatus) |>
  wrappedStackedFreqPlot(
    xVar = careerStatus,
    fillVar = response,
    fillLabel = "Member of\nrespective\nEDI group",
    wrapVar = ediVar,
    ostColours = ostColours2rev,
    figCaption = NULL,
    figTitle = careerStatusLabel,
    titleAdjust = -202
  )
gdata::mv("p", "Cs_Id") # p is sent to the global env. from the function
suppressWarnings(print(Cs_Id))

```

###### tables


```{r}
#| label: careerstatus-by-sexuality-stats-table
#| tbl-cap: "Summary of responses to career status by sexual orientation"
#| output: asis

visMain |>
  contingencyTable(
    contingX = "careerStatus", 
    contingGrp = "nonHeteroCommunity"
    )

```

---

```{r}
#| label: careerstatus-by-race-stats-table
#| tbl-cap: "Summary of responses to career status by race and/or culture"
#| output: asis

visMain |>
  contingencyTable(
    contingX = "careerStatus", 
    contingGrp = "raceCulture"
    )

```

---

```{r}
#| label: careerstatus-by-disability-stats-table
#| tbl-cap: "Summary of responses to career status by disability and/or neurodivergence"
#| output: asis

visMain |>
  contingencyTable(
    contingX = "careerStatus", 
    contingGrp = "disability"
    )

```

---

```{r}
#| label: careerstatus-by-domlang-stats-table
#| tbl-cap: "Summary of responses to career status by dominant written language"
#| output: asis

visMain |>
  contingencyTable(
    contingX = "careerStatus", 
    contingGrp = "domLangEnglish"
    )

```

<!-- {{< include notes/_careerStatusInteractions.md >}} -->

---

### type of engagement with *PsychoPy*<sup>&reg;</sup>

This section summarises, both visually and verbally, the responses to the following prompt:

>`r get_label(visMain$engagement)`

Participants had to choose from one of the following:

- *Occasional user*\
- *Frequent user*\
- *Occasional contributor*\
- *Frequent contributor*\
- *Senior developer*

#### everyone

The visualization below presents responses in descending order of frequency.

##### figure

```{r}
#| label: engagement-type-plot-everyone
#| fig-alt: "Descending frequency barplot of everyone's responses to the following question: 'What best describes your role/usage of PsychoPy?'"

visMain |>
  select(engagement) |>
  mutate(engagement = forcats::fct_na_value_to_level(engagement, level = "(missing)")) |>
  freqPlot(
    ostColour = ostOrange, 
    sorting = "desc"
    )
gdata::mv("p", "EnTp") # p is sent to the global env. from the function
suppressWarnings(print(EnTp))

```

##### table

```{r}
#| label: engagement-count-table
#| tbl-cap: "Summary of responses to engagement level"
#| output: asis

visMain |>
  select(engagement) |>
  mutate(engagement = forcats::fct_na_value_to_level(engagement, level = "(missing)")) |>
  tbl_summary() |>
  modify_header(label = "**Question**") |>
  as_flex_table() |>
  flextable::flextable_to_rmd()

```


<!-- {{< include notes/_engagement.md >}} -->

#### interactions

##### gender

###### figure

```{r}
#| label: engagement-type-plot-gender
#| fig-alt: "Descending frequency barplot of responses by gender to the following question: 'What best describes your role/usage of PsychoPy?'"

contingencyPlot(
  df = visMain,
  contingX = "engagement",
  contingGrp = "gender",
  colours = ostColours4na
  )
gdata::mv("p", "En_Gn") # p is sent to the global env. from the function
suppressWarnings(print(En_Gn))

```

###### table

```{r}
#| label: engagement-by-gender-stats-table
#| tbl-cap: "Summary of responses by gender to type of engagement"
#| output: asis

visMain |>
  contingencyTable(
    contingX = "engagement", 
    contingGrp = "gender"
    )

```

---

##### other EDI variables

{{< include interactionNotes.qmd >}}

###### figure

```{r}
#| label: figEngagementByOtherVars

engagementLabel <- paste0("What best describes your role/usage of PsychoPy?")

longerDataSimple |>
  #drop_na(response) |>
  #drop_na(engagement) |>
  wrappedStackedFreqPlot(
    xVar = engagement,
    fillVar = response,
    fillLabel = "Member of\nrespective\nEDI group",
    wrapVar = ediVar,
    ostColours = ostColours2rev,
    figCaption = NULL,
    figTitle = engagementLabel,
    titleAdjust = -202
  )
gdata::mv("p", "En_Id") # p is sent to the global env. from the function
suppressWarnings(print(En_Id))

```


###### tables

---

```{r}
#| label: engagement-by-sexuality-stats-table
#| tbl-cap: "Summary of responses by sexual orientation to type of engagement"
#| output: asis

visMain |>
  contingencyTable(
    contingX = "engagement", 
    contingGrp = "nonHeteroCommunity"
    )

```

---

```{r}
#| label: engagement-by-race-stats-table
#| tbl-cap: "Summary of responses by race and/or culture to type of engagement"
#| output: asis

visMain |>
  contingencyTable(
    contingX = "engagement", 
    contingGrp = "raceCulture"
    )

```

---

```{r}
#| label: engagement-by-disability-stats-table
#| tbl-cap: "Summary of responses by disability and/or neurodivergence to type of engagement"
#| output: asis

visMain |>
  contingencyTable(
    contingX = "engagement", 
    contingGrp = "disability"
    )

```

---

```{r}
#| label: engagement-by-dominant-language-stats-table
#| tbl-cap: "Summary of responses by dominant language to type of engagement"
#| output: asis

visMain |>
  contingencyTable(
    contingX = "engagement", 
    contingGrp = "domLangEnglish"
    )

```


<!-- {{< include notes/_engagementInteractions.md >}} -->

---

### ways of contributing

This was a select-all-that-apply question, worded as follows:

>In which way do you contribute most? (select all that apply)

Each participant could select more than one option when describing how they contribute most. For ease of visual and verbal summary, the responses were converted into new variables, one per response. It is important to note here that multiple responses from the same person were possible here (and certainly did occur).

The possible selections were as follows:

- *Improving documentation*\
- *Supporting other users (e.g., on the forum)*\
- *Fixing bugs*\
- *Adding new features*\
- *Providing translations to other languages*\
- *Other (describe)*

It is important to keep in mind that participants may be counted as *yes* or *no* independently in any of the possible responses, which were converted to individual Boolean variables below. If they selected the response, we assigned the value *selected*; if they did not, we assigned the value *not selected*. 

```{r importContributionsLong}

longerDataContributions <- readRDS("data/longerDataContributions.rds")
contributeLabel <- get_label(longerDataContributions$contributionType)
contributeCaption <- "Notes:\n1. Respondents could select more than one contribution type.\n2. 'Unselected' is equivalent to 'NA'"

```


#### everyone

##### figure

```{r}
#| label: contribEveryone-plot
#| fig-alt: "Frequency barplot of the selections made in response to the following question: 'In which way do you contribute most?'"

longerDataContributions |>
  #drop_na(selected) |>
  wrappedFreqPlot(
    xVar = choices,
    fillVar = choices,
    wrapVar = contributionType,
    ostColours = ostColours2rev
  )
gdata::mv("p", "CtWy") # p is sent to the global env. from the function
suppressWarnings(print(CtWy))

```

##### table

```{r}
#| label: contributions-stats-table
#| tbl-cap: "Summary of responses to contribution type"
#| output: asis

longerDataContributions |>
  contingencyTable(
    contingX = "contributionType", 
    contingGrp = "choices"
    )

```

##### descriptions

The participants were given the option to describe those other contributions. These descriptions are listed in the table below.

```{r}
#| label: other-contributions-table
#| tbl-cap: "Descriptions of other contributions to PsychoPy/JS that some participants provided"

visMain |> 
  select(contribOtherDesc) |>
  drop_na() |>
  datatable(
    class = 'cell-border stripe',
    colnames = "[I] contribute in these other ways"
  )

```


<!-- {{< include notes/_otherContributions.md >}} -->

---

#### interactions

{{< include interactionNotes.qmd >}}

##### gender

###### figure

```{r}
#| label: contrib-by-gender-plot
#| fig-alt: "Frequency barplot of the choices made by gender in response to the following question: 'In which way do you contribute most?'"

legendLabel = "Gender"
longerDataContributions |>
  #drop_na(gender) |>
  wrappedStackedFreqPlot(
    xVar = choices,
    fillVar = gender,
    fillLabel = legendLabel,
    wrapVar = contributionType,
    ostColours = ostColours3,
    figTitle = contributeLabel,
    figCaption = contributeCaption,
    titleAdjust = NULL
  )
gdata::mv("p", "Ct_Gn") # p is sent to the global env. from the function
suppressWarnings(print(Ct_Gn))

```

###### table

```{r}
#| label: ways-of-contributing-by-gender-stats-table
#| tbl-cap: "Summary of responses by gender to ways of contributing"
#| output: asis

longerDataContributions |>
  select(gender, contributionType, choices) |>
  stratifiedContingencyTable(
    strataVar = "gender",
    byVar = "choices"
    )

```


---

##### sexual orientation

###### figure

```{r}
#| label: contrib-by-sexuality-plot
#| fig-alt: "Frequency barplot of the selections made by sexual orientation in response to the following question: 'In which way do you contribute most?'"

legendLabel = "non-heterosexual\ncommunity"
longerDataContributions |>
  drop_na(nonHeteroCommunity) |>
  wrappedStackedFreqPlot(
    xVar = choices,
    fillVar = nonHeteroCommunity,
    wrapVar = contributionType,
    ostColours = ostColours2rev,
    titleAdjust = NULL,
    fillLabel = legendLabel,
    figTitle = contributeLabel,
    figCaption = contributeCaption
  )
gdata::mv("p", "Ct_Nh") # p is sent to the global env. from the function
suppressWarnings(print(Ct_Nh))

```

###### table

```{r}
#| label: ways-of-contributing-by-sexuality-stats-table
#| tbl-cap: "Summary of responses by sexual orientation to ways of contributing"
#| output: asis

longerDataContributions |>
  select(nonHeteroCommunity, contributionType, choices) |>
  stratifiedContingencyTable(
    strataVar = "nonHeteroCommunity",
    byVar = "choices"
    )

```


---

##### race and/or culture

###### figure

```{r}
#| label: contrib-by-race-plot
#| fig-alt: "Frequency barplot of the selections made by race and/or culture in response to the following question: 'In which way do you contribute most?'"

legendLabel = "Race and/or\nculture"
longerDataContributions |>
  drop_na(raceCulture) |>
  wrappedStackedFreqPlot(
    xVar = choices,
    fillVar = raceCulture,
    wrapVar = contributionType,
    ostColours = ostColours2rev,
    titleAdjust = NULL,
    fillLabel = legendLabel,
    figTitle = contributeLabel,
    figCaption = contributeCaption
  )
gdata::mv("p", "Ct_Rc") # p is sent to the global env. from the function
suppressWarnings(print(Ct_Rc))

```

###### table

```{r}
#| label: ways-of-contributing-by-race-stats-table
#| tbl-cap: "Summary of responses by race and/or culture to ways of contributing"
#| output: asis

longerDataContributions |>
  select(raceCulture, contributionType, choices) |>
  stratifiedContingencyTable(
    strataVar = "raceCulture",
    byVar = "choices"
    )

```


---

##### disability and/or neurodivergence

###### figure

```{r}
#| label: contrib-by-disability-plot
#| fig-alt: "Frequency barplot of the selections made by disability and/or neurodivergence in response to the following question: 'In which way do you contribute most?'"

legendLabel = "Disability and/or\nneurodivergence"
longerDataContributions |>
  drop_na(disability) |>
  wrappedStackedFreqPlot(
    xVar = choices,
    fillVar = disability,
    wrapVar = contributionType,
    ostColours = ostColours2rev,
    titleAdjust = NULL,
    fillLabel = legendLabel,
    figTitle = contributeLabel,
    figCaption = contributeCaption
  )
gdata::mv("p", "Ct_Dn") # p is sent to the global env. from the function
suppressWarnings(print(Ct_Dn))

```

###### table

```{r}
#| label: ways-of-contributing-by-disability-stats-table
#| tbl-cap: "Summary of responses by disability and/or neurodivergence to ways of contributing"
#| output: asis

longerDataContributions |>
  select(disability, contributionType, choices) |>
  stratifiedContingencyTable(
    strataVar = "disability",
    byVar = "choices"
    )

```


---

##### English as dominant language

###### figure

```{r}
#| label: contrib-by-dominant-language-plot
#| fig-alt: "Frequency barplot of the selections made by whether one is dominant in written English in response to the following question: 'In which way do you contribute most?'"

legendLabel = "English as a\ndominant language"
longerDataContributions |>
  drop_na(domLangEnglish) |>
  wrappedStackedFreqPlot(
    xVar = choices,
    fillVar = domLangEnglish,
    wrapVar = contributionType,
    ostColours = ostColours2rev,
    titleAdjust = NULL,
    fillLabel = legendLabel,
    figTitle = contributeLabel,
    figCaption = contributeCaption
  )
gdata::mv("p", "Ct_Dl") # p is sent to the global env. from the function
suppressWarnings(print(Ct_Dl))

```

###### table

```{r}
#| label: ways-of-contributing-by-language_dominance-stats-table
#| tbl-cap: "Summary of responses by written-English dominance to ways of contributing"
#| output: asis

longerDataContributions |>
  select(domLangEnglish, contributionType, choices) |>
  stratifiedContingencyTable(
    strataVar = "domLangEnglish",
    byVar = "choices"
    )

```


---


### deterrents to contributing

Participants were asked the following:

>To what extent do each of the following limit the amount you feel able to contribute to the PsychoPy project?

Below the question was a list of the following potential causes:

- *Lack of interest*\
- *Lack of time*\
- *Lack of knowledge on how to get started*\
- *Lack of coding skills*\
- *Not confident I would be welcomed by the community*\
- *Not aware contributing was possible*

Participants could rank each of these on a `1`-`5` Likert scale, where `1` indicated *not at all* and a `5` indicated *very much*.

This section summarises, both visually and verbally, the rankings that participants provided for each potential cause.

::: {.callout-note}
Note that on this `1`-`5` scale, the number `3` is directly in the middle of the scale, which can be interpreted as neither agreeing nor disagreeing. We set responses of `3` to the side of the stacked frequency barplots below, in yellow.

Also, the barplots are sorted along descending frequency of agreement. That is, the topmost barplot is the one with highest number of agreements, whereas the bottom-most barplot is the one with the highest number of disagreements.
:::

#### everyone

##### figure

```{r}
#| label: deterrents-plot
#| fig-alt: "Stacked frequency barplots of the responses to: 'To what extent do each of the following limit the amount you feel able to contribute to the PsychoPy project?'"

visMain |>
  dplyr::select(starts_with("deterrents")) |>
  stackedFrequencies(
    colours = ostColours5,
    figTitle = "Deterrents to contributing for everyone"
    )
gdata::mv("p", "DtCt") # p is sent to the global env. from the function
suppressWarnings(print(DtCt))

```


##### table

```{r}
#| label: deterrents-stats-table
#| tbl-cap: "Statistical summaries of responses to statements regarding deterrents to contributing."
#| output: asis

visMain |>
  select(starts_with("deterrents"))  |>
  likertTable(
    lowerBound = "1 = not at all",
    upperBound = "5 = very much",
    byVar = NULL,
    spanVar <- NULL
  )

```


<!-- {{< include notes/_deterrents.md >}} -->

#### interactions

```{r}
#| label: createDeterrentsLabel

deterrentsLabel <- get_label(longerDataDeterrents$deterrent)
deterrentsCaption <- "Notes: \n1. A response of 1 indicates 'not at all' \n2. A response of 5 indicates 'very much'\n3. The mean is represented by the diamond"

```


##### gender

###### figure

```{r}
#| label: deterrents-likert-plot-by-gender
#| fig-alt: "Boxplots of responses by gender to the the following question: 'To what extent do each of the following limit the amount you feel able to contribute to the PsychoPy project?.'" 


legendLabel <- "Gender"
longerDataDeterrents |>
  select(gender, deterrent, response) |>
  #drop_na(gender) |>
  #drop_na(deterrent) |>
  #drop_na(response) |>
  interactionBoxplot(
    xVar = response,
    yVar = gender,
    wrapVar = deterrent,
    lowerBound = 1,
    upperBound = 5,
    ostColours = ostColours3,
    xLabel = NULL, #deterrentsLabel,
    fillLabel = legendLabel,
    figCaption = "1 = Strongly disagree; 5 = Strongly agree" #deterrentsCaption
    )
gdata::mv("p", "Dt_Gn") # p is sent to the global env. from the function
suppressWarnings(print(Dt_Gn))

```

###### table

```{r}
#| label: deterrents-by-gender-stats-table
#| tbl-cap: "Statistical summaries by gender of responses to statements regarding deterrents to contributing."
#| output: asis

textForSpan <- get_label(visMain$gender)

visMain |>
  select(starts_with("deterrents"), gender) |>
  mutate(gender = as.character(gender)) |>
  mutate(gender = forcats::fct_na_value_to_level(gender, level = "NA")) |>
  likertTable(
    lowerBound = "1 = not at all",
    upperBound = "5 = very much",
    byVar = "gender",
    spanVar = textForSpan
  )

```

---

##### sexual orientation

###### figure

```{r}
#| label: deterrents-likert-plot-by-sexuality
#| fig-alt: "Boxplots of responses by sexual orientation to the the following question: 'To what extent do each of the following limit the amount you feel able to contribute to the PsychoPy project?.'" 

legendLabel <- "Non-heterosexual\ncommunity"
longerDataDeterrents |>
  select(nonHeteroCommunity, deterrent, response) |>
  #drop_na(nonHeteroCommunity) |>
  # drop_na(deterrent) |>
  # drop_na(response) |>
  interactionBoxplot(
    xVar = response,
    yVar = nonHeteroCommunity,
    wrapVar = deterrent,
    lowerBound = 1,
    upperBound = 5,
    ostColours = ostColours2rev,
    xLabel = NULL, #deterrentsLabel,
    fillLabel = legendLabel,
    figCaption = "1 = Strongly disagree; 5 = Strongly agree" #deterrentsCaption
)
gdata::mv("p", "Dt_Nh") # p is sent to the global env. from the function
suppressWarnings(print(Dt_Nh))

```

###### table

```{r}
#| label: deterrents-by-sexuality-stats-table
#| tbl-cap: "Statistical summaries by sexual orientation of responses to statements regarding deterrents to contributing."
#| output: asis

textForSpan <- get_label(visMain$nonHeteroCommunity)

visMain |>
  select(starts_with("deterrents"), nonHeteroCommunity)  |>
  mutate(nonHeteroCommunity = as.character(nonHeteroCommunity)) |>
  mutate(nonHeteroCommunity = forcats::fct_na_value_to_level(nonHeteroCommunity, level = "NA")) |>
  likertTable(
    lowerBound = "1 = not at all",
    upperBound = "5 = very much",
    byVar = "nonHeteroCommunity",
    spanVar = textForSpan
  )


```

---

##### race and/or culture

###### figure

```{r}
#| label: deterrents-likert-plot-by-race
#| fig-alt: "Boxplots of responses by race and/or culture to the the following question: 'To what extent do each of the following limit the amount you feel able to contribute to the PsychoPy project?.'" 

legendLabel <- "Race and/or culture\nthat is potentially\ndiscriminated against"
longerDataDeterrents |>
  select(raceCulture, deterrent, response) |>
  # drop_na(raceCulture) |>
  # drop_na(deterrent) |>
  # drop_na(response) |>
  interactionBoxplot(
    xVar = response,
    yVar = raceCulture,
    wrapVar = deterrent,
    lowerBound = 1,
    upperBound = 5,
    ostColours = ostColours2rev,
    xLabel = deterrentsLabel,
    fillLabel = legendLabel,
    figCaption = deterrentsCaption
)
gdata::mv("p", "Dt_Rc") # p is sent to the global env. from the function
suppressWarnings(print(Dt_Rc))

```

###### table

```{r}
#| label: deterrents-by-race-stats-table
#| tbl-cap: "Statistical summaries by race and/or culture of responses to statements regarding deterrents to contributing."
#| output: asis

textForSpan <- get_label(visMain$raceCulture)
visMain |>
  select(starts_with("deterrents"), raceCulture)  |>
  mutate(raceCulture = as.character(raceCulture)) |>
  mutate(raceCulture = forcats::fct_na_value_to_level(raceCulture, level = "NA")) |>
  likertTable(
    lowerBound = "1 = not at all",
    upperBound = "5 = very much",
    byVar = "raceCulture",
    spanVar = textForSpan
  )

```

---

##### disability and/or neurodivergence

###### figure

```{r}
#| label: deterrents-likert-plot-by-disability
#| fig-alt: "Boxplots of responses by disability and/or neurodivergence to the the following question: 'To what extent do each of the following limit the amount you feel able to contribute to the PsychoPy project?.'" 

legendLabel <- "Disabled and/or\n neurodivergent"
longerDataDeterrents |>
  select(disability, deterrent, response) |>
  # drop_na(disability) |>
  # drop_na(deterrent) |>
  # drop_na(response) |>
  interactionBoxplot(
    xVar = response,
    yVar = disability,
    wrapVar = deterrent,
    lowerBound = 1,
    upperBound = 5,
    ostColours = ostColours2rev,
    xLabel = deterrentsLabel,
    fillLabel = legendLabel,
    figCaption = deterrentsCaption
)
gdata::mv("p", "Dt_Dn") # p is sent to the global env. from the function
suppressWarnings(print(Dt_Dn))

```

###### table

```{r}
#| label: deterrents-by-disability-stats-table
#| tbl-cap: "Statistical summaries by disability and/or neurodivergence of responses to statements regarding deterrents to contributing."
#| output: asis

textForSpan <- get_label(visMain$disability)

visMain |>
  select(starts_with("deterrents"), disability)  |>
  mutate(disability = as.character(disability)) |>
  mutate(disability = forcats::fct_na_value_to_level(disability, level = "NA")) |>
  likertTable(
    lowerBound = "1 = not at all",
    upperBound = "5 = very much",
    byVar = "disability",
    spanVar = textForSpan
  )

```


---

##### English as dominant language

###### figure

```{r}
#| label: deterrents-likert-plot-by-domlang
#| fig-alt: "Boxplots of responses by whether English is the respondent's dominant written language to the the following question: 'To what extent do each of the following limit the amount you feel able to contribute to the PsychoPy project?.'" 
legendLabel <- "English is dominant\nwritten language"
longerDataDeterrents |>
  select(domLangEnglish, deterrent, response) |>
  # drop_na(domLangEnglish) |>
  # drop_na(deterrent) |>
  # drop_na(response) |>
  interactionBoxplot(
    xVar = response,
    yVar = domLangEnglish,
    wrapVar = deterrent,
    lowerBound = 1,
    upperBound = 5,
    ostColours = ostColours2rev,
    xLabel = deterrentsLabel,
    fillLabel = legendLabel,
    figCaption = deterrentsCaption
)
gdata::mv("p", "Dt_Dl") # p is sent to the global env. from the function
suppressWarnings(print(Dt_Dl))

```

###### table

```{r}
#| label: deterrents-by-domlang-stats-table
#| tbl-cap: "Statistical summaries by whether the respondents' dominant written language is English of responses to statements regarding deterrents to contributing."
#| output: asis

textForSpan <- get_label(visMain$domLangEnglish)

visMain |>
  select(starts_with("deterrents"), domLangEnglish)  |>
  mutate(domLangEnglish = as.character(domLangEnglish)) |>
  mutate(domLangEnglish = forcats::fct_na_value_to_level(domLangEnglish, level = "NA")) |>
  likertTable(
    lowerBound = "1 = not at all",
    upperBound = "5 = very much",
    byVar = "domLangEnglish",
    spanVar = textForSpan
  )

```


---

### workshops on contributing

This section summarises, both visually and verbally, the answer to the following question:

>`r get_label(visMain$workshopsOnContributing)`

Participants provided answers on a `1`-`5` Likert scale, where `1` indicated *Strongly disagree* and a `5` indicated *Strongly agree*.

#### everyone

##### figure

```{r}
#| label: workshopLabels

workshopLabel <- get_label(longerDataSimple$workshopsOnContributing)
likertValues <- get_labels(longerDataSimple$workshopsOnContributing)

```


```{r}
#| label: contrib-workshops-plot
#| fig-alt: "Barplot of responses to the following statement: 'My engagement with the community would be helped if workshops were provided on how to contribute'"

longerDataSimple |> 
  select(workshopsOnContributing) |> 
  freqPlot(
    ostColour = ostYellow,
    sorting = "none"
  )
gdata::mv("p", "CtWk") # p is sent to the global env. from the function
suppressWarnings(print(CtWk))

```


##### table

```{r}
#| label: workshops-stats-table
#| tbl-cap: "Statistical summaries of responses to statement regarding the potential helpfulness of contributor workshops."
#| output: asis

visMain |>
  select(workshopsOnContributing)  |>
  likertTable(
    lowerBound = "1 = Strongly disagree",
    upperBound = "5 = Strongly agree",
    byVar = NULL,
    spanVar = NULL
  )

```

<!-- {{< include notes/_workshops.md >}} -->

#### interactions

##### gender

###### figure

```{r}
#| label: workshop-likert-plot-by-gender
#| fig-alt: "Boxplots of responses by gender to the question regarding whether the participant felt their engagement would increase with contributor workshops." 

figCaptionText <- paste0(
  "Notes: \n1. A response of 1 indicates 'Strongly disagree' \n2. A response of 5 indicates 'Strongly agree'\n3. The mean is represented by the diamond."
)
legendLabel <- "Gender"
visMain |>
  select(gender, workshopsOnContributing) |>
  drop_na(gender) |>
  drop_na(workshopsOnContributing) |>
  interactionBoxplot(
    xVar = workshopsOnContributing,
    yVar = gender,
    lowerBound = 1,
    upperBound = 5,
    ostColours = ostColours3,
    xLabel = workshopLabel,
    fillLabel = legendLabel,
    tickLabels = likertValues,
    pointFill = "darkgrey",
    wrapVar = NULL,
    figCaption = figCaptionText
    )
gdata::mv("p", "Wk_Gn") # p is sent to the global env. from the function
suppressWarnings(print(Wk_Gn))

```

###### table

```{r}
#| label: workshops-by-gender-stats-table
#| tbl-cap: "Summary of responses to desire for workshops by gender."
#| output: asis

textForSpan <- get_label(visMain$gender)
visMain |>
  select(workshopsOnContributing, gender)  |>
  mutate(gender = forcats::fct_na_value_to_level(gender, level = "NA")) |>
  likertTable(
    lowerBound = "1 = Strongly disagree",
    upperBound = "5 = Strongly agree",
    byVar = "gender",
    spanVar = textForSpan
  )

```

---

##### other EDI dimensions

{{< include interactionNotes.qmd >}}

###### figure

```{r}
#| label: workshop-likert-plot-by-other-edis
#| fig-alt: "Boxplots of responses by EDI variables other than gender to the question regarding whether the participant felt their engagement would increase with contributor workshops." 

legendLabel <- "Member of\nrespective\nEDI group"
longerDataSimple |>
  drop_na(workshopsOnContributing) |>
  drop_na(response) |>
  interactionBoxplot(
    xVar = workshopsOnContributing,
    yVar = response,
    lowerBound = 1,
    upperBound = 5,
    ostColours = ostColours2rev,
    xLabel = workshopLabel,
    fillLabel = legendLabel,
    tickLabels = likertValues,
    pointFill = "#F7F11C",
    wrapVar = ediVar,
    figCaption = "Notes:\n1. A response of 1 indicates 'Strongly disagree'\n2. A response of 5 indicates 'Strongly agree'\n3. The mean is represented by the diamond"
  )
gdata::mv("p", "Wk_Id") # p is sent to the global env. from the function
suppressWarnings(print(Wk_Id))

```

###### tables

---

```{r}
#| label: workshops-by-sexuality-stats-table
#| tbl-cap: "Summary of responses to desire for workshops by sexual orientation."
#| output: asis

textForSpan <- get_label(visMain$nonHeteroCommunity)
visMain |>
  select(workshopsOnContributing, nonHeteroCommunity)  |>
  mutate(nonHeteroCommunity = as.character(nonHeteroCommunity)) |>
  mutate(nonHeteroCommunity = forcats::fct_na_value_to_level(nonHeteroCommunity, level = "NA")) |>
  likertTable(
    lowerBound = "1 = Strongly disagree",
    upperBound = "5 = Strongly agree",
    byVar = "nonHeteroCommunity",
    spanVar = textForSpan
  )

```

---

```{r}
#| label: workshops-by-race-stats-table
#| tbl-cap: "Summary of responses to desire for workshops by race and/or culture."
#| output: asis

textForSpan <- get_label(visMain$raceCulture)
visMain |>
  select(workshopsOnContributing, raceCulture)  |>
  mutate(raceCulture = as.character(raceCulture)) |>
  mutate(raceCulture = forcats::fct_recode(raceCulture, "yes" = "1", "no" = "0")) |>
  mutate(raceCulture = forcats::fct_na_value_to_level(raceCulture, level = "NA")) |>
  likertTable(
    lowerBound = "1 = Strongly disagree",
    upperBound = "5 = Strongly agree",
    byVar = "raceCulture",
    spanVar = textForSpan
  )

```

---

```{r}
#| label: workshops-by-disability-stats-table
#| tbl-cap: "Summary of responses to desire for workshops by disability and/or neurodivergence."
#| output: asis

textForSpan <- get_label(visMain$disability)
visMain |>
  select(workshopsOnContributing, disability)  |>
  mutate(disability = as.character(disability)) |>
  mutate(disability = forcats::fct_recode(disability, "yes" = "1", "no" = "0")) |>
  mutate(disability = forcats::fct_na_value_to_level(disability, level = "NA")) |>
  likertTable(
    lowerBound = "1 = Strongly disagree",
    upperBound = "5 = Strongly agree",
    byVar = "disability",
    spanVar = textForSpan
  )

```

---

```{r}
#| label: workshops-by-domlangenglish-stats-table
#| tbl-cap: "Summary of responses to desire for workshops by written-English language dominance."
#| output: asis

textForSpan <- get_label(visMain$domLangEnglish)
visMain |>
  select(workshopsOnContributing, domLangEnglish)  |>
  mutate(domLangEnglish = as.character(domLangEnglish)) |>
  mutate(domLangEnglish = forcats::fct_recode(domLangEnglish, "yes" = "1", "no" = "0")) |>
  mutate(domLangEnglish = forcats::fct_na_value_to_level(domLangEnglish, level = "NA")) |>
  likertTable(
    lowerBound = "1 = Strongly disagree",
    upperBound = "5 = Strongly agree",
    byVar = "domLangEnglish",
    spanVar = textForSpan
  )

```

---

## guidance

The third group of items on the survey collected information about documentation and the participants' awareness of and experience with the [Code of Conduct](https://github.com/psychopy/psychopy/blob/dev/code-of-conduct.md).


There were three questions concerning each of the following:

- awareness of the *Code of Conduct*\
- how findable, searchable, and accessible *PsychoPy*'s<sup>&reg;</sup> documentation is\
- how much they trust the *Code of Conduct* will be enforced

The first was answered with a simple *yes* or *no*. The latter two were statements evaluated with a `1`-`7` Likert scale, where `1` represented *Strongly disagree*, and `7` represented *Strongly agree*.

### awareness of *Code of Conduct*

The sections directly below summarise, both visually and verbally, the answer to the following question:

>`r get_label(visMain$awareOfCodeOfConduct)`

#### everyone

##### figure

```{r}
#| label: codeofconduct-plot
#| fig-alt: "Frequency barplot of responses to the following question: 'I am aware of the community Code of Conduct' If participants chose to respond, they could respond with either 'yes' or 'no.'"

visMain |> 
  select(awareOfCodeOfConduct) |> 
  mutate(awareOfCodeOfConduct = forcats::fct_na_value_to_level(awareOfCodeOfConduct, level = "NA")) |>
  freqPlot(
    ostColour = ostOrange,
    sorting = "none"
  )
gdata::mv("p", "CcAw") # p is sent to the global env. from the function
suppressWarnings(print(CcAw))

```

##### table

```{r}
#| label: aware-code-of-conduct-count-table
#| tbl-cap: "Summary of responses to awareness of Code of Conduct"
#| output: asis

visMain |>
  select(awareOfCodeOfConduct) |>
  mutate(awareOfCodeOfConduct = forcats::fct_na_value_to_level(awareOfCodeOfConduct, level = "NA")) |>
  tbl_summary() |>
  modify_header(label = "**Question**") |>
  as_flex_table() |>
  flextable::flextable_to_rmd()

```

---

#### interactions

##### gender

###### figure

```{r}
#| label: codeofconduct-awareness-by-gender-plot
#| fig-alt: "Contingency barplot of responses by gender to the following question: 'I am aware of the community Code of Conduct' If participants chose to respond, they could respond with either 'yes' or 'no.'"

contingencyPlot(
  df = visMain,
  contingX = "awareOfCodeOfConduct",
  contingGrp = "gender",
  colours = ostColours4na
  )
gdata::mv("p", "Cc_Gn") # p is sent to the global env. from the function
suppressWarnings(print(Cc_Gn))

```

###### table

```{r}
#| label: code-of-conduct-by-gender-stats-table
#| tbl-cap: "Summary of responses by gender to awareness of the Code of Conduct"
#| output: asis

visMain |>
  contingencyTable(
    contingX = "awareOfCodeOfConduct", 
    contingGrp = "gender"
    )

```

##### other EDI dimensions

{{< include interactionNotes.qmd >}}

###### figure

```{r}
#| label: codeofconduct-awareness-by-edivars-plot
#| fig-alt: "Contingency barplot of responses by EDI variable (except gender) to the following question: 'I am aware of the community Code of Conduct' If participants chose to respond, they could respond with either 'yes' or 'no.'"

codeOfConductLabel <- get_label(longerDataSimple$awareOfCodeOfConduct)

longerDataSimple |>
  drop_na(response) |>
  drop_na(awareOfCodeOfConduct) |>
  wrappedStackedFreqPlot(
    xVar = awareOfCodeOfConduct,
    fillVar = response,
    fillLabel = "Member of\nrespective\nEDI group",
    wrapVar = ediVar,
    ostColours = ostColours2rev,
    figCaption = NULL,
    figTitle = codeOfConductLabel,
    titleAdjust = NULL
  )
gdata::mv("p", "Cc_Id") # p is sent to the global env. from the function
suppressWarnings(print(Cc_Id))

```

###### tables


```{r}
#| label: code-of-conduct-by-sexuality-stats-table
#| tbl-cap: "Summary of responses by sexual orientation to awareness of the Code of Conduct"
#| output: asis

visMain |>
  contingencyTable(
    contingX = "awareOfCodeOfConduct", 
    contingGrp = "nonHeteroCommunity"
    )

```

---

```{r}
#| label: code-of-conduct-by-race-stats-table
#| tbl-cap: "Summary of responses by race and/or culture to awareness of the Code of Conduct"
#| output: asis

visMain |>
  contingencyTable(
    contingX = "awareOfCodeOfConduct", 
    contingGrp = "raceCulture"
    )

```

---

```{r}
#| label: code-of-conduct-by-disability-stats-table
#| tbl-cap: "Summary of responses by disability and/or neurodivergence to awareness of the Code of Conduct"
#| output: asis

visMain |>
  contingencyTable(
    contingX = "awareOfCodeOfConduct", 
    contingGrp = "disability"
    )

```

---

```{r}
#| label: code-of-conduct-by-domlang-stats-table
#| tbl-cap: "Summary of responses by written-English language dominance to awareness of the Code of Conduct"
#| output: asis

visMain |>
  contingencyTable(
    contingX = "awareOfCodeOfConduct", 
    contingGrp = "domLangEnglish"
    )

```


### findability, searchability, & accessibility

The sections directly below summarise, both visually and verbally, the answer to the following question:

>`r get_label(visMain$psychopyDocumentationEasy)`

#### everyone

##### figure

```{r}
#| label: find-doceasy-plot
#| warning: false
#| fig-alt: "Barplot of agreement responses to the statement regarding findability, searchability, and accessibility of documentation."

visMain |>
  select(psychopyDocumentationEasy) |>
  freqPlot(
    ostColour = ostOrange,
    sorting = "none"
  )
gdata::mv("p", "DcEs") # p is sent to the global env. from the function
suppressWarnings(print(DcEs))

```


##### table

```{r}
#| label: doceasy-stats-table
#| tbl-cap: "Statistics for responses to statements regarding whether the documentation is findable, searchable, and accessible."
#| output: asis

visMain |>
  select("psychopyDocumentationEasy") |> 
  likertTable(
    lowerBound = "1 = Strongly disagree",
    upperBound = "7 = Strongly agree",
    byVar = NULL,
    spanVar = NULL
  )

```
  

---
  
#### interactions

```{r}
#| label: findabilityLabels

docEasyLabel <- get_label(visMain$psychopyDocumentationEasy)

```


##### gender

###### figure

```{r}
#| label: doceasy-likert-plot-by-gender
#| fig-alt: "Boxplots of responses by EDI variables by gender to the question regarding whether the participants felt the documentation for PsychoPy was easily findable, searchable, and accessible." 

legendLabel <- "Gender"
visMain |>
  drop_na(gender) |>
  drop_na(psychopyDocumentationEasy) |>
  interactionBoxplot(
    xVar = psychopyDocumentationEasy,
    yVar = gender,
    lowerBound = 1,
    upperBound = 7,
    ostColours = ostColours3,
    xLabel = docEasyLabel,
    fillLabel = legendLabel,
    tickLabels = likertValues,
    pointFill = "#F7F11C",
    wrapVar = NULL,
    figCaption = "Notes:\n1. A response of 1 indicates 'Strongly disagree'\n2. A response of 7 indicates 'Strongly agree'\n3. The mean is represented by the diamond"
  )
gdata::mv("p", "Dc_Gn") # p is sent to the global env. from the function
suppressWarnings(print(Dc_Gn))

```

###### table

```{r}
#| label: doceasy-by-gender-stats-table
#| tbl-cap: "Summary of responses by gender to finding the documentation easily findable, searchable, and accessible"
#| output: asis

textForSpan <- get_label(visMain$gender)
visMain |>
  select(psychopyDocumentationEasy, gender)  |>
  mutate(gender = forcats::fct_na_value_to_level(gender, level = "NA")) |>
  likertTable(
    lowerBound = "1 = Strongly disagree",
    upperBound = "7 = Strongly agree",
    byVar = "gender",
    spanVar = textForSpan
  )

```

##### other EDI dimensions

{{< include interactionNotes.qmd >}}

###### figure

```{r}
#| label: doceasy-likert-plot-by-other-edis
#| fig-alt: "Boxplots of responses by EDI variables other than gender to the question regarding whether the participants felt the documentation for PsychoPy was easily findable, searchable, and accessible." 

legendLabel <- "Member of\nrespective\nEDI group"
longerDataSimple |>
  drop_na(psychopyDocumentationEasy) |>
  drop_na(response) |>
  interactionBoxplot(
    xVar = psychopyDocumentationEasy,
    yVar = response,
    lowerBound = 1,
    upperBound = 7,
    ostColours = ostColours2rev,
    xLabel = docEasyLabel,
    fillLabel = legendLabel,
    tickLabels = likertValues,
    pointFill = "#F7F11C",
    wrapVar = ediVar,
    figCaption = "Notes:\n1. A response of 1 indicates 'Strongly disagree'\n2. A response of 7 indicates 'Strongly agree'\n3. The mean is represented by the diamond"
  )
gdata::mv("p", "Dc_Id") # p is sent to the global env. from the function
suppressWarnings(print(Dc_Id))

```

###### tables

```{r}
#| label: doceasy-by-sexuality-stats-table
#| tbl-cap: "Summary of responses by sexual orientation to finding the documentation easily findable, searchable, and accessible"
#| output: asis

textForSpan <- get_label(visMain$nonHeteroCommunity)
visMain |>
  select(psychopyDocumentationEasy, nonHeteroCommunity)  |>
  mutate(nonHeteroCommunity = forcats::fct_na_value_to_level(nonHeteroCommunity, level = "NA")) |>
  likertTable(
    lowerBound = "1 = Strongly disagree",
    upperBound = "7 = Strongly agree",
    byVar = "nonHeteroCommunity",
    spanVar = textForSpan
  )

```

---

```{r}
#| label: doceasy-by-race-stats-table
#| tbl-cap: "Summary of responses by race and/or culture to finding the documentation easily findable, searchable, and accessible"
#| output: asis

textForSpan <- get_label(visMain$raceCulture)
visMain |>
  select(psychopyDocumentationEasy, raceCulture)  |>
  mutate(raceCulture = forcats::fct_na_value_to_level(raceCulture, level = "NA")) |>
  likertTable(
    lowerBound = "1 = Strongly disagree",
    upperBound = "7 = Strongly agree",
    byVar = "raceCulture",
    spanVar = textForSpan
  )

```

---

```{r}
#| label: doceasy-by-disability-stats-table
#| tbl-cap: "Summary of responses by disability and/or neurodivergence to finding the documentation easily findable, searchable, and accessible"
#| output: asis

textForSpan <- get_label(visMain$disability)
visMain |>
  select(psychopyDocumentationEasy, disability)  |>
  mutate(disability = forcats::fct_na_value_to_level(disability, level = "NA")) |>
  likertTable(
    lowerBound = "1 = Strongly disagree",
    upperBound = "7 = Strongly agree",
    byVar = "disability",
    spanVar = textForSpan
  )

```

---

```{r}
#| label: doceasy-by-language-dominance-stats-table
#| tbl-cap: "Summary of responses by English-language dominance to finding the documentation easily findable, searchable, and accessible"
#| output: asis

textForSpan <- get_label(visMain$domLangEnglish)
visMain |>
  select(psychopyDocumentationEasy, domLangEnglish)  |>
  mutate(domLangEnglish = forcats::fct_na_value_to_level(domLangEnglish, level = "NA")) |>
  likertTable(
    lowerBound = "1 = Strongly disagree",
    upperBound = "7 = Strongly agree",
    byVar = "domLangEnglish",
    spanVar = textForSpan
  )

```


### trust in enforcement

The sections directly below summarise, both visually and verbally, the answer to the following question:

>`r get_label(visMain$trustCodeWillBeEnforced)`

#### everyone

##### figure

```{r}
#| label: trust-enforcement-plot
#| warning: false
#| fig-alt: "Barplot of agreement responses to the statement regarding trust in enforcement of the Code of Conduct."

visMain |> 
  select(trustCodeWillBeEnforced) |> 
  freqPlot(
    ostColour = ostYellow,
    sorting = "none"
  )
gdata::mv("p", "TrEn") # p is sent to the global env. from the function
suppressWarnings(print(TrEn))

```

##### table

```{r}
#| label: codeofconduct-stats-table
#| tbl-cap: "Statistics for responses to statements regarding trust in enforcement of the Code of Conduct"
#| output: asis

visMain |>
  select(trustCodeWillBeEnforced) |> 
  likertTable(
    lowerBound = "1 = Strongly disagree",
    upperBound = "7 = Strongly agree",
    byVar = NULL,
    spanVar = NULL
  )

```

<!-- {{< include notes/_trustCodeWillBeEnforced.md >}} -->

#### interactions

```{r}
#| label: trustCodeLabels

trustCodeLabel <- get_label(visMain$trustCodeWillBeEnforced)

```


##### gender

###### figure

```{r}
#| label: enforcementtrust-likert-plot-by-gender
#| fig-alt: "Boxplots of responses by EDI dimensions by gender to trust that the Code of Conduct would be enforced." 

legendLabel <- "Gender"
visMain |>
  drop_na(gender) |>
  drop_na(trustCodeWillBeEnforced) |>
  interactionBoxplot(
    xVar = trustCodeWillBeEnforced,
    yVar = gender,
    lowerBound = 1,
    upperBound = 7,
    ostColours = ostColours3,
    xLabel = trustCodeLabel,
    fillLabel = legendLabel,
    tickLabels = likertValues,
    pointFill = "#F7F11C",
    wrapVar = NULL,
    figCaption = "Notes:\n1. A response of 1 indicates 'Strongly disagree'\n2. A response of 7 indicates 'Strongly agree'\n3. The mean is represented by the diamond"
  )
gdata::mv("p", "Tr_Gn") # p is sent to the global env. from the function
suppressWarnings(print(Tr_Gn))

```

###### table

```{r}
#| label: enforcementtrust-by-gender-stats-table
#| tbl-cap: "Summary of responses by gender to trust that the Code of Conduct would be enforced"
#| output: asis

textForSpan <- get_label(visMain$gender)
visMain |>
  select(trustCodeWillBeEnforced, gender)  |>
  mutate(gender = forcats::fct_na_value_to_level(gender, level = "NA")) |>
  likertTable(
    lowerBound = "1 = Strongly disagree",
    upperBound = "7 = Strongly agree",
    byVar = "gender",
    spanVar = textForSpan
  )

```


##### other EDI variables

{{< include interactionNotes.qmd >}}

###### figure

```{r}
#| label: enforcementtrust-likert-plot-by-other-edis
#| fig-alt: "Boxplots of responses by EDI dimensions other than gender to trust that the Code of Conduct would be enforced." 

legendLabel <- "Member of\nrespective\nEDI group"
longerDataSimple |>
  drop_na(trustCodeWillBeEnforced) |>
  drop_na(response) |>
  interactionBoxplot(
    xVar = trustCodeWillBeEnforced,
    yVar = response,
    lowerBound = 1,
    upperBound = 7,
    ostColours = ostColours2rev,
    xLabel = trustCodeLabel,
    fillLabel = legendLabel,
    tickLabels = likertValues,
    pointFill = "#F7F11C",
    wrapVar = ediVar,
    figCaption = "Notes:\n1. A response of 1 indicates 'Strongly disagree'\n2. A response of 7 indicates 'Strongly agree'\n3. The mean is represented by the diamond"
  )
gdata::mv("p", "Tr_Id") # p is sent to the global env. from the function
suppressWarnings(print(Tr_Id))

```

###### tables


```{r}
#| label: enforcementtrust-by-sexuality-stats-table
#| tbl-cap: "Summary of responses by sexual orientation to trust that the Code of Conduct would be enforced"
#| output: asis

textForSpan <- get_label(visMain$nonHeteroCommunity)
visMain |>
  select(trustCodeWillBeEnforced, nonHeteroCommunity)  |>
  mutate(nonHeteroCommunity = forcats::fct_na_value_to_level(nonHeteroCommunity, level = "NA")) |>
  likertTable(
    lowerBound = "1 = Strongly disagree",
    upperBound = "7 = Strongly agree",
    byVar = "nonHeteroCommunity",
    spanVar = textForSpan
  )

```

---

```{r}
#| label: enforcementtrust-by-race-stats-table
#| tbl-cap: "Summary of responses by race and/or culture to trust that the Code of Conduct would be enforced"
#| output: asis

textForSpan <- get_label(visMain$raceCulture)
visMain |>
  select(trustCodeWillBeEnforced, raceCulture)  |>
  mutate(raceCulture = forcats::fct_na_value_to_level(raceCulture, level = "NA")) |>
  likertTable(
    lowerBound = "1 = Strongly disagree",
    upperBound = "7 = Strongly agree",
    byVar = "raceCulture",
    spanVar = textForSpan
  )

```

---

```{r}
#| label: enforcementtrust-by-disability-stats-table
#| tbl-cap: "Summary of responses by disability and/or neurodivergence to trust that the Code of Conduct would be enforced"
#| output: asis

textForSpan <- get_label(visMain$disability)
visMain |>
  select(trustCodeWillBeEnforced, disability)  |>
  mutate(disability = forcats::fct_na_value_to_level(disability, level = "NA")) |>
  likertTable(
    lowerBound = "1 = Strongly disagree",
    upperBound = "7 = Strongly agree",
    byVar = "disability",
    spanVar = textForSpan
  )

```

---

```{r}
#| label: enforcementtrust-by-domlang-stats-table
#| tbl-cap: "Summary of responses by language dominance in written English to trust that the Code of Conduct would be enforced"
#| output: asis

textForSpan <- get_label(visMain$domLangEnglish)
visMain |>
  select(trustCodeWillBeEnforced, domLangEnglish)  |>
  mutate(domLangEnglish = forcats::fct_na_value_to_level(domLangEnglish, level = "NA")) |>
  likertTable(
    lowerBound = "1 = Strongly disagree",
    upperBound = "7 = Strongly agree",
    byVar = "domLangEnglish",
    spanVar = textForSpan
  )

```

<!-- {{< include notes/_finalRemarks.md >}} -->

---

# Main *R* Packages used

```{r}
#| label: citePackages
#| results: asis

    pkgs <- grateful::cite_packages(
      pkgs = packagesRequired,
      output = "table", 
      out.dir = getwd(),
      cite.tidyverse = F,
      bib.file = "bibs/grateful-refs-sumandvis.bib"
      )
    knitr::kable(pkgs)

```

---

# Appendix

## Colour-blindness check

The custom palettes used in this report (which are based on the colours used at [Open Science Tools, Ltd.](https://opensciencetools.org/) are simulated through various forms of colour blindness below to ensure that most people can distinguish the colours on the figures.

### two colours

```{r}
#| label: colourblindnessCheckOst2
#| warning: false

palette_bivariate_plot(ostColours2)
#palette_check(ostColours2)

```

### three colours

```{r}
#| label: colourblindnessCheckOst3
#| warning: false

palette_bivariate_plot(ostColours3)
#palette_check(ostColours3)

```

### five colours

```{r}
#| label: colourblindnessCheckOst5
#| warning: false

palette_bivariate_plot(ostColours5)

```

### six colours

```{r}
#| label: colourblindnessCheckOst6
#| warning: false

palette_bivariate_plot(ostColours6)
#palette_check(ostColours6)

```