Study title

Digital Gaming, Work and Health Survey 2021

Dataset ID Number

FSD3689

Persistent identifiers

https://urn.fi/urn:nbn:fi:fsd:T-FSD3689
https://doi.org/10.60686/t-fsd3689

Data Type

Quantitative

Authors

• Karhulahti, Veli-Matti (University of Jyväskylä)
• Vahlo, Jukka (University of Jyväskylä)
• Munukka, Matti (University of Jyväskylä)
• Koskimaa, Raine (University of Jyväskylä)
• von Bonsdorff, Mikaela (University of Jyväskylä)

Abstract

The survey charted the wellbeing of Finnish employees, their work and digital gaming. The same respondents were invited to volunteer for a similar survey one year later: FSD3673 Digital Gaming, Work and Health Survey 2022. Respondents to both surveys can be matched using a randomized identification variable in the data.

In the survey, the respondents were first asked about their perceived health and quality of life, before moving on to digital gaming. They were asked about the amount of time and money spent on gaming-related things per week. Respondents were also asked how much they liked or disliked various aspects of games. Non-gamers were asked why they do not play digital games and how much they have played various non-digital games.

The survey then moved on to the negative phenomena associated with digital gaming. For example, respondents were asked how often in the last six months they had thought about gaming during the day. They were also asked about gambling. This was followed by questions on anxiety, depression, loneliness, fear of the future and feelings of self-worth. Finally, respondents were asked about their recovery from work and their current capacity to work.

The survey includes the following additional measurement indicators: Gaming addiction scale (GAS7), Internet Gaming Disorder Test (IGDT10), Gaming disorder test (GDT), Problem gaming test (THL1), PROMIS General Mental Health (GMH-2), PROMIS General Physical Health (GPH-2), Work ability index (WAI), Work recovery question (WR), Perceived loneliness (PL), Pathological gambling (BBDS), General anxiety disorder scale 2 (GAD-2) and Beck Depression Inventory (BDI).

Background variables included the respondent's mother tongue, gender, year of birth, age, level of education, party affiliation and NUTS3 region of residence.

Keywords

addiction; attitudes; digital games; employees; exercise (physical activity); gambling; health status; labour and employment; money; psychological well-being; time budgets

Topic Classification

• Social sciences (Fields of Science Classification)
• General health and well-being (CESSDA Topic Classification)
• Occupational health (CESSDA Topic Classification)
• Information society (CESSDA Topic Classification)
• Leisure, tourism and sport (CESSDA Topic Classification)

Series

Individual datasets

Distributor

Finnish Social Science Data Archive

Access

The dataset is (B) available for research, teaching and study.

Data Collector

• Karhulahti, Veli-Matti (University of Jyväskylä)
• Vahlo, Jukka (University of Jyväskylä)
• Koskimaa, Raine (University of Jyväskylä)
• Munukka, Matti (University of Jyväskylä)
• Bilendi

Funders

• Finnish Work Environment Fund (200349)
• Academy of Finland (312397)

Time Period Covered

2021

Collection Dates

2021-05-20 – 2021-05-31

Nation

Finland

Geographical Coverage

Finland

Analysis/Observation Unit Type

Individual

Universe

Finnish working population aged 18-65

Time Method

Cross-section

Sampling Procedure

Probability: Cluster: Stratified random

Bilendi has collected the data in sections based on age, gender and region of residence to be nationally representative of the Finnish working population.

Collection Mode

Self-administered questionnaire: Web-based (CAWI)

Research Instrument

Structured questionnaire

Data File Language

Downloaded data package may contain different language versions of the same files.

The data files of this dataset are available in the following languages: Finnish.

FSD translates quantitative data into English on request, free of charge. More information on ordering data translation.

Data Version

1.0

Related Datasets

FSD3673 Digital Gaming, Work and Health Survey 2022

FSD3678 Health and Digital Gaming: Gamer Interviews 2021

FSD3685 Health and Digital Gaming: Expert Interviews 2021

FSD3798 Health and Digital Gaming: Follow-up Gamer Interviews 2022

Completeness of Data and Restrictions

To prevent identification of respondents, the researcher has removed the industry variable from the data and created a coarser area variable (region) from the original postcode variable.

In the FSD, the original id variable has been removed and a randomized identifier variable (respid) has been created to link respondents to the dataset FSD3673 Digital Gaming, Work and Health Survey 2022.

Weighting

The data includes a weight variable that allows the data to be weighted to represent the Finnish working population aged 18-65 by gender, age and region (provinces).

Citation Requirement

The data and its creators shall be cited in all publications and presentations for which the data have been used. The bibliographic citation may be in the form suggested by the archive or in the form required by the publication.

Bibliographical Citation

Karhulahti, Veli-Matti (University of Jyväskylä) & Vahlo, Jukka (University of Jyväskylä) & Munukka, Matti (University of Jyväskylä) & Koskimaa, Raine (University of Jyväskylä) & von Bonsdorff, Mikaela (University of Jyväskylä): Digital Gaming, Work and Health Survey 2021 [dataset]. Data version 1.0 (2023-08-16). Finnish Social Science Data Archive [distributor]. DOI: https://doi.org/10.60686/t-fsd3689; URN: https://urn.fi/urn:nbn:fi:fsd:T-FSD3689

Deposit Requirement

Notify FSD of all publications where you have used the data by sending the citation information to user-services.fsd@tuni.fi.

Disclaimer

The original data creators and the archive bear no responsibility for any results or interpretations arising from the reuse of the data.

Related Publications

Karhulahti, V., Vahlo, J., Martoncik, M., Munukka, M., Koskimaa, R., & von Bonsdorff, M. (2022). Ontological Diversity in Gaming Disorder Measurement: A Nationally Representative Registered Report. https://doi.org/10.31234/osf.io/qytrs

Charlotte Pennington (2022) Different ontologies, different constructs? Instruments for gaming-related health problems identify different groups of people and measure different problems. Peer Community in Registered Reports. https://rr.peercommunityin.org/articles/rec?id=209

Billieux, J., & Fournier, L. (2023). Commentary on Karhulahti et al.(2022): addressing ontological diversity in gaming disorder measurement from an item-based psychometric perspective. Addiction Research & Theory, 31(3), 170-173. https://doi.org/10.1080/16066359.2022.2125508

Karhulahti, V. M., Adamkovic, M., Vahlo, J., Martoncik, M., Munukka, M., Koskimaa, R., & von Bonsdorff, M. (2023). Reply to Billieux and Fournier (2022): collaborative shortcut to ontological diversity. Addiction Research & Theory, 31(3), 174-177. https://doi.org/10.1080/16066359.2022.2160448

Amendola, S. (2023). Commentary on Karhulahti et al.(2022): Exploring gaming disorder from the harmful dysfunction analysis perspective. Addiction Research & Theory, 31(3), 168-169. https://doi.org/10.1080/16066359.2023.2173743