394 Iv. COGNITI vE AND M OTIvATIONAL P ROCESSES
Achievement, predicted research partici -
pants’ likelihood of adjusting their ratings 
of artworks and persons. Conversely, high 
n Achievement, but not high san  Achieve -
ment, predicted episodic memory and per -
formance on a scrambled-  word test. Consis -
tent with these early observations, Biernat 
(1989) found that n Achievement predicted 
good performance on an arithmetic task, 
but not volunteering for a task group leader -
ship position, whereas san  Achievement did 
not predict arithmetic task performance but 
instead predicted participants’ inclination to 
be a task group leader. Similarly, Brunstein 
and Hoyer (2002; see also Brunstein & 
Maier, 2005) reported that n Achievement 
predicted performance on an attention task, 
but not participants’ choice of whether to 
continue with the task or do something else, 
whereas san Achievement positively predict -
ed the choice to continue, but not the actual 
performance on the task.
Differences between implicit and explic -
it measures of motivation have also been 
reported for other motives (e.g., Craig, 
Koestner, & Zuroff, 1994; Koestner, Wein -
berger, & McClelland, 1991; Schult  heiss & 
Brunstein, 1999). For instance, Hagemeyer, 
Dufner, and Denissen (2016) videotaped 
participants, whose n and san  Affiliation 
they had assessed, in a standardized social 
interaction situation with the experimenter. 
Videotapes were coded for verbal and non -
verbal affiliative behaviors, such as self- 
disclosure and smiling, respectively. Hage -
meyer and colleagues found n Affiliation to 
predict nonverbal but not verbal affiliative 
behaviors, and san  affiliation to predict ver -
bal but not nonverbal affiliative behaviors.
Taken together, these studies suggest a 
double dissociation between implicit and 
explicit motives and their behavioral cor -
relates, such that implicit motives are more 
likely to predict nonverbal performance in -
dicators, and explicit motives are more like -
ly to predict choices, judgments, and verbal 
declarations. This characterization of the 
differences in predictive validity between 
implicit and explicit motives is probably too 
coarse to apply across the board (for ex -
amples of implicit and explicit achievement 
motives additively or interactively influenc -
ing the same performance measures, see, 
e.g., Brunstein & Maier, 2005; Brunstein & Schmitt, 2010). However, it is broadly con -
sistent with meta-  analytic findings (Span -
gler, 1992) and can serve as a useful heuris -
tic for predicting which type of measure will 
perform well for which outcome type.
Implicit and  Explicit Motives Respond 
to Different Types of Cues
Implicit motives are more aroused by non -
verbal than verbal cues. Klinger (1967) ob -
served that individuals showed increases in 
PSE affiliation and achievement imagery 
after watching an affiliation-  oriented or 
achievement-  oriented experimenter, even 
when they could not hear his verbal in -
structions. Similarly, Shantz and Latham 
(2009) found nonverbal achievement prim -
ing to increase n Achievement. Schult  heiss 
and Brunstein (1999, 2002) demonstrated 
that experimenters who verbally assigned 
a power-  related goal failed to arouse their 
participants’ n Power. Only after partici -
pants had had an opportunity to translate 
the assigned goal into an experiential format 
through a goal imagery exercise did their 
implicit power motive predict goal commit -
ment and task performance.
In recent years, incentive effects of non -
verbal cues for implicit motives have been 
studied extensively through the lens of mo -
tivational field theory (MFT; Stanton, Hall, 
& Schult  heiss, 2010). Building on earlier 
interpersonal theory work (e.g., Wiggins & 
Trobst, 1999), MFT holds that nonverbal 
signals of emotion can be classified along the 
orthogonal axes of dominance and affilia -
tion. According to MFT, dominant emotion -
al signals, such as anger, represent disincen -
tives for perceivers, particularly if their own 
n Power is high, and, conversely, submissive 
signals, such as surprise or fear, represent 
incentives for such perceivers. Affiliative 
emotional signals, such as social smiles, rep -
resent incentives for perceivers, particularly 
if their own n Affiliation is high, whereas 
hostile signals, such as disgust, represent 
disincentives for affiliation-  motivated per -
ceivers. Research focusing on facial expres -
sions of emotion provides support for these 
predictions. Compared to others, individu -
als high in n Power are particularly sensi -
tive to signals of dominance (e.g., anger) and 
submission (e.g., surprise) in studies on per -