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In their article, Seder and Oishi (2012) ask a novel question based on previous research conducted by Harker and Keltner (2001) which had demonstrated that there was a relationship, namely a positive correlation, between the smile intensities (as a measure of expressed positive emotionality) of women in their yearbook photographs and their self-reported well-being decades later. Seder and Oishi (2012) had 2 main questions. For their first question, they examined whether positive emotional expression in informally posed photographs, such as Facebook profile pictures, are also related to future life satisfaction and whether they could replicate the previous findings of Harker and Keltner (2001). Secondly, Seder and Oishi (2012) asked how and why could such a relationship between expression of positive affect and future well-being exist, and what other variables might mediate this relationship. Also, after having successfully replicated the main findings of Harker and Keltner (2001), Seder and Oishi (2012) noted that their sample consisted of early adapters to Facebook and this might suggest that the sample may not be representative of different Facebook users, so they decided to replicate the findings, again, in another sample. They also wanted to check the relationship between other variables and extraversion again as well, so they eventually conducted a second study.
The authors had multiple hypotheses. First, they argued that the intensity of Facebook users’ smiling would predict their future life satisfaction. Secondly, they proposed that extraversion is a third variable that mediates the relationship in the first hypothesis. Thirdly, they hypothesized that a more intense smile may predict better social relationships, which, in turn, could predict a higher future life satisfaction.
The researchers employed a longitudinal study design. Since the researchers aimed to investigate the predictive power of smiling intensity specifically on -future- life satisfaction, I think that the use of a longitudinal research design can be said to be the most appropriate method possible. However, the longitudinal research design brings with itself a major disadvantage: the possibility of sample attrition. In fact, almost 48% of the sample dropped out in study 1, and almost 27% of the sample dropped out in study 2 between the start and the end of the research processes. It is likely that the researchers knew that this could create a systematic bias in the sample if participants with a certain characteristic were more likely to drop out or stay in the research. Therefore, they analyzed the descriptive statistics of the groups who dropped out and those who completed the follow-ups and found that there were no significant differences in the variables that the research aimed to investigate between the groups to deal with this caveat of longitudinal research.
The main variables of interest in the study were smile intensity, life satisfaction, extraversion, and social relationships satisfaction. First, the researchers collected self-reported extraversion data through an extraversion assessment at the beginning of the participants’ first semester at college. Extraversion ranged from 1 to 5. At the end of the first semester, self-reported life satisfaction, operationalized as the scores on the Satisfaction with Life Scale ranging from 5 to 35 (Diener, Emmons, Larsen, & Griffin, 1985), and self-reported social relationship satisfaction scores ranging from 1 to 7. After this data collection, smile intensity data, which was operationalized as the intensity of action in specific facial muscle units in the participant’s most recent codable Facebook profile picture ranging from 2 to 10, was collected.
The participants were University of Virginia freshmen who used Facebook and had a suitable profile picture in Facebook at the time of the experiment. The researchers used a (non-probability) purposive sampling to only select students who were freshmen at the university and had a codable Facebook profile picture. Since the researchers wanted to use Facebook pictures to assess the hypothesized relationship, I think that the sampling technique was appropriate. However, a non-probability sample that consists solely of college students is likely to be biased and non-representative of the general population. So, if the researchers had more resources, probability sampling would have obviously been a better choice since it is likely that it would make the sample more representative.
The researchers conducted a t-test to examine the difference between men and women’s smiling intensities. In line with previous research, women’s smiling was more intense. The researchers also used correlation and linear regression analyses to investigate the relationships and predictive strengths of smile intensity on life satisfaction and the other variables– extraversion and social relationship satisfaction. The main results showed that there was a statistically significant relationship between smile intensity and future life satisfaction even after controlling for extraversion. Also, smile intensity did predict social relationship satisfaction at the end of the first semester, and relationship satisfaction itself was significantly related to future life satisfaction in both studies. Although there was not a significant statistical support for extraversion being a mediating factor for the relationship between smile intensity and future life satisfaction in the first study, the results of the second study did show a significant effect.
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