Relationships Between Health and Logged Video Game Play Across Platforms

🟢️ The output from this repo can be viewed at https://digital-wellbeing.github.io/platform-study-rr/. 🟢️

This repo documents the data and analysis code for our project on the relationship between video game play and wellbeing. It has four main components:

• generating simulated data to illustrate our preregistered analyses
• documenting the data and creating a codebook
• preprocessing the data for analysis
• data analysis for three outputs, structured to match our programmatic registered report.

To reproduce the project in its entirety, run quarto render (for non-lab members). More details are provided below.

Data files are saved as .csv.gz for space efficiency. These can either be unzipped and opened in a spreadsheet program, or read directly into R using readr::read_csv() or Python using pandas.read_csv().

Scripts

The first script generates a series of 8 simulated data tables, overviewed in codebook.xlsx. Generating the simulated data is only possible by internal users, but the code is available in 0_generateSyntheticData.qmd. The remaining scripts can be run by external users.

These data tables are generated in the following scripts:

• In 0_generateSyntheticData.qmd, we simulate a total of 8 data tables that will mimic the structure of the eventual
• In 1_preprocess.qmd, we clean the data and calculate relevant derived variables (e.g., mean scores, play behavior metrics, and so on).

We then analyze these data in the following scripts:

• In 2_basicNeeds.qmd, we present the analysis code for Study 1: the relationship between basic needs and video game play.
• In 3_sleep.qmd, we present the analysis code for Study 2: the relationship between sleep and video game play.
• In 4_genres.qmd, we present the analysis code for Study 3: the relationship between video game genres and video game play.
• In 9_screenshots.qmd, we present work-in-progress optical character recognition code for extracting screen use data from iOS screenshots.

Hygiene files

• .Renviron defines the path to key internal data files and API credentials.
• index.qmd is the header file that stitches the other Quarto files together into book form.
• _quarto.yml defines the order in which files are run and project-level variables for internal use
• _quarto-external.yml defines the order in which files are run and project-level variables for external use (same as _quarto-internal.yml with the exception of not running 0_generateSyntheticData.qmd)

Running

• Run quarto render --profile external in the Rstudio terminal to render all of the quarto files except 0_generateSyntheticData.qmd, which requires internal credentials. This command uses the specifications in _quarto.yml to render the files in the correct order (indicated by their number), and output them to outputs/.

• For internal use, run quarto render in the Rstudio terminal to render all quarto files. This command uses the specifications in _quarto-internal.yml to render the files in the correct order (indicated by their number), and output them to docs/. The files in docs/ are hosted on GitHub pages here: https://digital-wellbeing.github.io/platform-study-rr/.