Exact(4)
The first area of interest contained the health text (coping vs. high risk) and the second area of interest contained the photo.
Smokers (n = 23); Non-Smokers (n = 41) Means (SD) of self-report measures for message acceptance, novelty, relevance and threat for each health text (coping vs. high risk) in combination with a high threat photo or a low threat photo.
Mixed analysis of variances (ANOVA) were conducted to test the effects of within-subjects factors health text (coping vs. high risk) and photo (low threat vs. high threat) and the between-subjects factor smoking status (smokers vs. non-smokers) on the number of fixations and dwell time.
Smokers (n = 23); Non-Smokers (n = 41) Means (SD) of fixations and dwell Time (in milliseconds) for the AOIs text and photo for each health text (coping vs. high risk) in combination with a high threat photo or a low threat photo.
Similar(56)
The finding that coping text information received more attention than high risk text information in smokers does not seem to be the result of the novelty of the presented textual information.
For creating the sixteen cigarette packages for the main experiment each low threat and high threat photo was paired to one risk or coping text with the result that each of the sixteen images used to represent a cigarette package contained a unique combination of photo and health text (risk or coping text).
Eight coping texts and eight high risk texts were selected.
Five items that measured clarity, credibility, interest, usefulness and acceptability of each of the presented risk and coping texts were combined to measure message acceptance of the health texts (α's > .88; 1 = not at all, 7 = very much).
The primary purpose of the present study was to examine the amount of attention allocation to risk information and coping texts on cigarette packages.
The experiment varied the content of the health text (high risk vs. coping) and photo (high threat vs. low threat) as within-subjects factors and smoking status (smoker vs. non-smoker) as between-subjects factor.
In the text, how to cope with more than two species is described.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com