Academic challenge on Bol et al. (2016)

 Academic challenge on Bol et al. (2016)

This exploratory paper has enquired about the way people pay attention to online health illustrations and texts, and under what circumstances this attention leads to accurate recall of the information presented in the stimulus (Bol et al., 2016). Although the study has used a satisfactory sample size (n = 129) for three conditions – allowing for at least 30 participants in each condition –, applied eye-tracking for data-collection in the most useful way for enquiring about people’s attention to stimulus, and followed all recommendations of eye-tracking reporting by King et al. (2019): The sample size and related decisions (e.g., mixed recruitment strategies for heterogeneity) (Bol et al., 2016, p. 389), the experimental between-subject design (Bol et al., 2016, pp. 388-389), the two areas of interests (Bol et al., 2016, p. 391), the study-setting (Bol et al., 2016, p. 389), stimulus-presentation (Bol et al., 2016, pp. 389-390), eye-tracking unit (SMI RED 120 SensoMotoric), its calibration details and metrics (Bol et al., 2016, p. 389-391), were all clearly indicated. Yet, several implications remain around the methods.

Age

First, gathering participants from an association’s database, called the Dutch Senior Citizens’ Association, as well as dividing age into ‘young’ and ‘old’ groups by the age of 65 – whereby anybody from the age of 18 was able to participate – (Bol et al., 2016, pp. 388-389), both lead to a bias in the sample towards elderly citizens. It is particularly problematic because age has been a key variable in the study. Defining everyone under 65 collectively as ‘young’ is worrying, because this brings together the digital generation (those growing up and consequently, becoming experts of the online world) (Buckingham, 2013), with those elderly who, for various reasons, are still not very confident with the Internet and its websites – particularly women (Millward, 2003; Ramón-Jerónimo et al., 2013). Although, it has been tried to be compensated by the pre-screening of Internet-experience levels, self-reporting Internet-experience does not guarantee the unified perception of what ‘being experienced’ means to someone in their 20s and others in their early 60s, or a man compared to a woman (Chu, 2010; Durndell & Haag, 2002). Besides Internet-experience levels, difference in recall rates under picture-plus-words conditions have been found to be higher among youngsters (mean age 20.7), than the elderly (mean age 68.3) (Maisto & Queen, 1992). This, again, confirms the need for more age-groups for this study, where attention has been a key variable.

In addition, among ‘younger adults’ there was a variance of 43 years (21-64), whereas among ‘older adults’ it was only 23 (65-88) (Bol et al., 2016, p. 389). Again, instead of only two age-groups, more could have been defined – although, that would have required a larger sample size, too. It would be interesting to form a third group of those between 30 and 65 (Zickuhr & Madden, 2012). Presumably, the results would have shown more significant differences, as those falling outside the digital generation would not count towards the results of those from the digital generation. This is because the group of ‘young adults’ might have significant differences within the group – young adults 20-30 and adults 30-64 – in attention paid to the illustrations – both, cognitive or affective –, which could have been potentially revealed instead of the lack of difference among the two vague age-groups (Bol et al., 2016). This age-grouping has therefore, potentially hidden a significant difference, that is right to assume, based on the findings of Maisto and Queen (1992).

Stimulus

Third, I found the difference among cognitive- and affective illustrations stimulus-materials rather worrying. Although, the website and its textual content remained the same, the images of the two illustrative conditions not only differ in their emotive versus informative nature, but also vary in style. Both cognitive graphics, for example, contain further text and alt-text, while also, they are both drawn/animated, compared to the real-life photographs of the affective condition, without any textual content on or below the images. In addition, since the text remains the same, it is natural that some texts require cognitive-, while others affective illustrations (Mayer & Tormala, 2010), leading to a mismatch between the text and the image in one of the illustration-conditions, while not in the other.

Fourth, the problem arises from the application of two images, on both instances. By this, it cannot be determined, which one of the two images triggered the participant’s mind, that has eventually led to increasing recall rates. In the cognitive illustration condition, for example, was it the image about hair or the image about lungs and heart, that caught the mind of participants to remember the content of the stimulus? In the affective condition, was it the female or male healthcare worker, who made participants remember? Besides the low levels of visual attention to the images in both conditions, these are still relevant factors, that have not been controlled for. All the above-mentioned issues of the stimulus might have contributed to the results that participants of both illustration-conditions and both age-groups paid significantly higher levels of attention to cognitive illustrations, than affective illustrations. Although, the significant difference among stimulus materials – drawn versus real-life picture, inner-body versus ‘outer body’ humans – contributes to the strength of the finding that participants have barely looked at the images in any condition. Since the images differ greatly, it is surer that any illustration leads to the same result, that is, people do pay more attention to the text than to the illustration, whether it is cognitive or affective (Bol et al., 2016). Yet, improvements could have been made to both, defining age-groups and the stimulus material.

References

Bol, N., van Weert, J. C. M., Loos, E. F., Romano Bergstrom, J. C., Bolle, S., & Smets, E. M. A. (2016). How are online health messages processed? Using eye tracking to predict recall of information in younger and older adults. Journal of Health Communication, 21, 387-396. https://doi.org/10.1080/10810730.2015.1080327

Buckingham, D. (2013). Is there a digital generation? (pp. 13-26). Routledge.

Chu, R. J. C. (2010). How family support and Internet self-efficacy influence the effects of e-learning among higher aged adults–Analyses of gender and age differences. Computers & Education, 55(1), 255-264. https://doi.org/10.1016/j.compedu.2010.01.011

Durndell, A., & Haag, Z. (2002). Computer self efficacy, computer anxiety, attitudes towards the Internet and reported experience with the Internet, by gender, in an East European sample. Computers in human behavior, 18(5), 521-535. https://doi.org/10.1016/S0747-5632(02)00006-7

King, A. J., Bol, N., Cummins, R. G., & John, K. K. (2019). Improving visual behavior research in communication science: An overview, review, and reporting recommendations for using eye-tracking methods. Communication Methods and Measures, 13(3), 149-177. https://doi.org/10.1080/19312458.2018.1558194

Maisto, A. A., & Queen, D. E. (1992). Memory for pictorial information and the picture superiority effect. Educational Gerontology: An International Quarterly, 18(2), 213-223. https://doi.org/10.1080/0360127920180207

Mayer, N. D., & Tormala, Z. L. (2010). “Think” Versus “Feel” Framing Effects in Persuasion. Personality and Social Psychology Bulletin, 36(4), 443–454. https://doi.org/10.1177/0146167210362981

Millward, P. (2003). The'grey digital divide': Perception, exclusion and barriers of access to the Internet for older people. First monday. https://doi.org/10.5210/fm.v8i7.1066

Ramón-Jerónimo, M. A., Peral-Peral, B., & Arenas-Gaitán, J. (2013). Elderly persons and Internet use. Social Science Computer Review, 31(4), 389-403. https://doi.org/10.1177%2F0894439312473421

Zickuhr, K., & Madden, M. (2012). Older adults and internet use. Pew Internet & American Life Project, 6, 1-23.https://www.sainetz.at/dokumente/studien/ Older_adults_and_internet_use_2012.pdf