Affect Grid

The objectives of UX methods are to assess and improve user satisfaction by optimizing the whole user experience, including a range of subjective qualities such as satisfaction, motivations, and expectations.

Below is an example of a user experience method in action:

Affect grid

Affect Grid

The affect grid is a scale designed to quickly assess a user's feelings about a product or system along two dimensions: pleasure-displeasure and arousal-sleepiness. The participant marks their current emotional state on a 9x9 grid where arousal forms the y-axis and pleasantness forms the x-axis. A mark closer to the right indicates more positive feelings, while a mark closer to the left indicates more negative feelings. Arousal refers to how “up/activated” versus how “down/sedated” a person is feeling. For example, they could be feeling really “up” and that could be in a positive direction, which would feel like excitement. Or, they could be feeling “up” but in a negative direction, which would feel more like anxiety or stress. An “X” mark directly in the center of the grid indicates that a person is feeling totally neutral. The affect grid could be used to compare a participant's emotional state prior to and after interacting with a system, feelings at critical points throughout a task, or to confirm if a product has the intended effect on its users.

Example

Research Question: How do Hulu commercials differentially influence emotional reactions from viewers?

In order to answer this question, I created a survey in which I asked participants to review commercials for the Hulu streaming service. This survey was administered anonymously online via the platform, Qualtrics. Participants were presented with 5 different Hulu commercials, uploaded a picture of their affect grid response, and listed 1-2 things that they liked and did not like about each video. These survey results allowed me to compare a sample of Hulu commercials to determine which had the highest and lowest scores along each dimension.

Results indicated that the commercial with the highest average level of pleasantness was commercial number 2. On average, participants also rated their arousal as neutral (M= 5) for this video, which indicates that participants were somewhere halfway between excited and relaxed by the commercial (i.e., arousal neither too high nor too low). These ratings resulted in the overall highest affect score for this commercial, and indicate that commercial number 2 was the most enjoyable out of the five presented. The lowest affect score was recorded for commercial number 3. Ratings indicated that this video was more unpleasant than pleasant, and slightly more arousing than sedating. Descriptors displayed in the grid indicate that this should be interpreted to mean that the commercial was slightly stressful, which seems logical based on its content (i.e., people flying through walls). Comments on video 2 (i.e., the “best” commercial) indicate that viewers like the rhythm and animation in this commercial. Comments on video 3 (i.e., the “worst” commercial) indicate that viewers felt the video lacked clarity at points, was boring/forgettable, and encourages bingeing tv over socialization.

Things to remember:

Affect ratings alone are usually not sufficient. Allowing viewers to provide specific comments may be useful for the interpretation of affect grid results.
Collecting a baseline affect measure may be useful to determine how the product/system changed the viewers emotional state. A user may be influenced by factors other than what they are interacting with in your study (e.g., having a bad day, illness/injury,), so it is important to control for this by measuring their affect prior to doing anything else.

Pros:

Easy to complete; faster than using separate Likert-type scales.

Cons:

Requires well written instructions to ensure participant understanding of the measure.
Only provides descriptive information on emotional valence and arousal. Does not specify what aspects of a product or system lead to the effect.
Mixed research findings on validity of the measure.

References:

Russell, J. A., Weiss, A., & Mendelsohn, G. A. (1989). Affect grid: A single-item scale of pleasure and arousal. Journal of Personality and Social Psychology, 57(3), 493–502. https://doi.org/10.1037/0022-3514.57.3.493
Colomo-Palacios, R., Casado-Lumbreras, C., Soto-Acosta, P., García-Crespo, A. (2011). Using the affect grid to measure emotions in software requirements engineering. Journal of Universal Computer Science, 17(9), 1281-1298. https://doi.org/10.3217/jucs-017-09-1281

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