Dataset DOI: 10.5061/dryad.hx3ffbgvs

Description of the data and file structure

Subjective Perceptions of Gaming Motivation Among College Students at High Risk of Gaming Disorder Employing Q-Methodology

The following data files are provided to complete each step of the analysis using KenQ Analysis.

This dataset contains Q-methodology data collected to examine subjective patterns of gaming motivation among college students at risk of gaming disorder. Using purposive sampling, 25 college students from the Seoul metropolitan area who were identified through screening as being at high risk of gaming disorder completed a Q-sort of 34 statements. The dataset includes the Q-set statements and participants’ Q-sort data.

The dataset consists of files exported from KenQ Analysis, an online Q-methodology software platform, as well as one additional factor-analysis results file. The files provide the results of the five-factor analysis, the forced-distribution pattern used for the Q-sort task, the Q-set statements, the raw Q-sort data collected from the 25 participants, and auxiliary metadata generated by KenQ Analysis, included for completeness and reproducibility.

Q_Statements.csv — Contains the results of the by-person factor analysis of the Q-sort data (5-factor solution), including the factor arrays (idealized Q-sorts) for each extracted factor.

• Item: statement number and full text, matching Ken_Q_GD_P_samples_statements.csv.
• Columns labeled 1–5 (each appearing twice): the five factors extracted from the data.
• Z: standardized factor z-score for the statement on that factor.
• Q: rounded, weighted factor score (Q-sort value, –4 to +4) for the statement on that factor.
• An asterisk (*) following a Q value indicates a distinguishing statement for that factor, meaning that the score on that factor differs significantly from its scores on the other factors, according to KenQ Analysis output conventions.

Ken_Q_GD_P_samples_pattern.csv — Contains the forced (quasi-normal) distribution grid used for the Q-sort task.

• Row 1: possible score values on the Q-sort grid, from –4 (least characteristic/most disagree) to +4 (most characteristic/most agree). The software automatically generates columns from –6 to 13, but only the –4 to +4 range was used in this study; all other columns contain 0.
• Row 2: the number of statements participants were required to place at each score value (2, 3, 4, 5, 6, 5, 4, 3, 2 for scores –4 through +4, respectively), summing to 34.

Ken_Q_GD_P_samples_name.csv — Contains the project name assigned within KenQ Analysis ("Gaming disorder"). This file is an auxiliary metadata file automatically generated by the software; it is not analytic or substantive data but is included for completeness and reproducibility of the original project file.

Ken_Q_GD_P_samples_sorts.csv — Contains the raw Q-sort data for all participants (no header row).

• Column 1: participant ID (p1–p25), corresponding to the 25 study participants.
• Columns 2–35: the score (–4 to +4) assigned by each participant to statements 1 through 34, in the order defined in Ken_Q_GD_P_samples_statements.csv.
• Each row represents one participant's complete Q-sort, following the forced distribution defined in Ken_Q_GD_P_samples_pattern.csv.

Ken_Q_GD_P_samples_statements.csv — Contains the 34 Q-set statements used in the study.

• Number: sequential ID (1–34) identifying each statement. This ID is used to match the statements across the other files.
• Statements: full text (English) of each statement presented to participants.

Ken_Q_GD_P_samples_version.csv — Contains the internal software/file-format version code used by KenQ Analysis (value: 2), along with software-generated warning text instructing users not to change the version number or delete the sheet. This file is an auxiliary metadata file automatically generated by the software; it is not analytic or substantive data but is included for completeness and reproducibility of the original project file.

Ken_Q_GD_P_samples_type.csv — Contains the internal project-type code used by KenQ Analysis (value: 2), along with software-generated warning text instructing users not to change the type number or delete the sheet. This file is an auxiliary metadata file automatically generated by the software; it is not analytic or substantive data but is included for completeness and reproducibility of the original project file.

Missing data

There are no missing values in this dataset; all 25 participants completed the full 34-statement Q-sort as required by the forced distribution.

Code/software

The files can be opened and read using the latest versions of Microsoft Word and Microsoft Excel, as appropriate.