816 vIII. EMERGING  ISSuES AND  NEW  DIRECTIONS
To protect their own privacy and the privacy 
of people around them, participants had full 
discretion to take the life logger off as de -
sired and, at the end of the study, they had 
the opportunity to review their pictures and 
delete any they did not want to go into the 
study. The streams of pictures of everyday 
situations were then segmented into mean -
ingful units and rated on situational features 
and dimensions.
Finally, with the launch of Google’s Glass 
in 2013, the technology market saw a first 
foray into commercial smart glasses. Only 
a few years later, companies are now rou -
tinely developing smart glasses and includ -
ing them into their product lineups. Smart 
glasses have the scientific appeal that they 
are minimally obtrusive, obviate the need 
for a separate wearable camera, and reveal 
as closely as possible how a person sees the 
world. Over the next years, wearable cam -
eras, as clip-on cameras or smart glasses, are 
bound to become increasingly mainstream, 
which would facilitate image-based research 
on everyday situations.
In a pioneering series of studies in Swit -
zerland, Wettstein and his colleagues used 
camera-  glasses to investigate how situations 
elicit aggressive behavior among adolescents 
(Wettstein & Jakob, 2010; Wettstein & 
Scherzinger, 2015). The studies showed that 
the physical (e.g., in the school yard, at the 
gym) and social (e.g., alone, in group) envi -
ronment of adolescents can be studied using 
camera-  glasses with limited reactivity. Fur -
thermore, they showed that the method can 
provide insights into context under which 
direct and indirect forms of aggression arise. 
The manual coding of image content limited 
the feasible sample size. However, in the fu -
ture, automatic image-based object and per -
son recognition (i.e., posture, gesture, and 
facial expression) might be able to assist in 
this task (Schmid Mast et al., 2015).
Subjective Assessment of  Situation 
Experiences and  Perceptions
Most experience sampling studies (e.g., on 
emotions or interpersonal perceptions and 
interactions) also assess subjective percep -
tions of momentary situations (for technical 
and design issues, see “Ecological Assess -
ment of Daily Experiences”). For example, studies examining emotional responses to 
stressful situations showed that the subjec -
tive content, importance, predictability, 
and controllability of stressors moderate 
emotional responses (Dickerson & Kemeny, 
2004; Lazarus, 1999). In addition, stud -
ies often statistically control for situational 
characteristics that potentially affect emo -
tional experiences, such as time of day or 
location.
Most previous studies used study-  specific 
lists of perceived situation characteristics— 
often focusing on present persons, location, 
activity, and valence (for review see Rauth -
mann, 2015; Saucier, Bel-Bahar, & Fernan -
dez, 2007; Ten Berge & De Raad, 1999). 
Approaches to systematize situational in -
formation generally distinguish between ob -
jectively available cues (see “Observational 
Assessment of Objective Situation Cues”) 
and subjectively perceived characteristics 
and classes of situations (Magnusson, 1981; 
 Rauthmann et al., 2015; Rauthmann, Sher -
man, Nave, & Funder, 2015; Wagerman 
& Funder, 2009). While there is not yet an 
agreed-  upon taxonomy of situation classes 
in personality psychology, there are appli -
cable approaches regarding the assessment 
of situation characteristics, including the 
Riverside Situation Q -Sort (RSQ; Funder, 
2016; Wagerman & Funder, 2009), the re -
lated eight-  dimensional DIAMONDS model 
(Rauthman et al., 2014; Rauthman & Sher -
man, 2016), and a seven-  dimensional model 
based on identified situational dimensions 
based on Kenrick, Griskevicius, Neuberg, 
and Schaller’s (2010) fundamental motives 
theory (Morse, Neel, Todd, & Funder, 2014).
Serfass and Sherman (2015) coded the 
eight DIAMONDS dimensions (Duty, In -
tellect, Adversity, Mating, pOsitivity, Neg -
ativity, Deception, and Sociality) in over 
20 million Tweets using computerized, 
word-count-based algorithms and provided 
evidence for the validity of their approach 
through theory-  consistent temporal pat -
terns and gender differences. For example, 
on weekdays Duty  peaked midmorning and 
declined steadily thereafter, whereas Socia -
bility  increased after typical wake-up time, 
remained high over the day, and peaked in 
the evening (Serfass & Sherman, 2015).
In summary, great progress has been made 
in theorizing and assessing daily situations. 