User Guide
The Scale
The Basic Needs in Games (BANGS) is an open-access, free to use scale. You can use it to understand how players experience a game or gaming in general. However, to ensure good measurement and fair comparisons, it is important to use the scale as devised.
Below, we provide a few tips. This is not meant to be guide on how to conduct surveys or how to perform statistical analysis of results. For more general information on conducting survey studies, I point you in the direction of a few useful resources at the bottom of this page.
If you are comfortable with player experience measurement, quick-start templates can be found here Excel file.
How to use
What order should the items be in?
We strongly recommend randomizing the order in which items appear. This allows you to better use multiple items to measure the same underlying thing (i.e., the three autonomy satisfaction items) without it being overly obvious or tedious for participants who would have to otherwise fill out several similar items in a row.
What are the response options?
BANGS was designed using a 7-pt Likert scale with the following format:
1 - Strongly disagree |
2 | 3 | 4 - Neither agree nor disagree |
5 | 6 | 7 - Strongly agree |
In one study, we tested an alternative format where the numeric values were changed to range from -3 to +3, instead of 1 to 7. We did not find any evidence that this affected the validity of the measure, so if you feel this better represents your goals with measuring basic needs, this is an alternative option. However, because the majority of our research used a 1 to 7 scale, the -3 to +3 variant should be used with some caution.
How do you fill in the blanks?
BANGS was tested for three kinds of usage:
- Experiences of a particular game session
- Experiences of a particular game over time
- Experiences of gaming in general over time
It’s important to be explicit about which of these you are interested in, and measure appropriately. For each, you will need to update the stem text and the placeholder [X]s in each item to suit the context. The table below summarizes the changes you’ll need to make. Fully-updated variants are available in the Excel file.
Variant | Stem Text | Replacement for placeholder [X] |
---|---|---|
Particular game session | Throughout my session of the game… | “the game” |
Particular game | Throughout my experiences playing [name of game]… | [name of game] |
Gaming in general | Throughout my experiences playing games in the last [time period]... | “the games I played” OR remove [X]s entirely (untested) |
Scoring
If possible, we recommend calculating factor scores based on players’ responses to each item, or using a measurement model—this allows you to account for the fact that each item gives a different amount of information about the underlying construct. Research shows that these scores typically differ somewhat from simply taking the mean of each subscale, and that this can have an appreciable impact on your results.
If this is not feasible or convenient, we recommend simply using the mean of all items in each subscale (e.g., the mean of items 1, 2, and 3 for autonomy satisfaction; items 4, 5, and 6 for autonomy frustration, and so on).
Depending on your research interests, it may be appropriate to calculate the mean of all the need satisfaction items (i.e., satisfaction of autonomy, competence, and relatedness) and the mean of all need frustration items (i.e., frustration of autonomy, competence, and relatedness) as holistic indications of people’s overall need satisfaction and frustration. Note, however, that this will result in the loss of information about which needs are more satisfied or frustrated.
We do not recommend calculating a score of all 18 items together (e.g., subtracting the mean of all need frustration items from the mean of all need satisfaction items)—need satisfaction and frustration are separate constructs with different consequences, and are therefore best handled separately.
General Resources for Conducting Survey Studies
Kelley, K., Clark, B., Brown, V., & Sitzia, J. (2003). Good practice in the conduct and reporting of survey research. International Journal for Quality in Health Care, 15(3), 261–266. https://doi.org/10.1093/intqhc/mzg031
Flake, J. K., & Fried, E. I. (2020). Measurement Schmeasurement: Questionable Measurement Practices and How to Avoid Them. Advances in Methods and Practices in Psychological Science, 3(4), 456–465. https://doi.org/10.1177/2515245920952393