339
Journal of Sport & Exercise Psychology, 2013, 35, 339-357
© 2013 Human Kinetics, Inc.
Sylvain Laborde is with UFR STAPS, EA 4260, University of
Caen, France, and with the Institute of Psychology, German
Sport University, Cologne, Germany. Markus Raab is with the
Institute of Psychology, German Sport University, Cologne,
Germany, and with the Department of Applied Sciences,
London South Bank University, London, UK.
The Tale of Hearts and Reason:
The Influence of Mood on Decision Making
Sylvain Laborde
1,2
and Markus Raab
2,3
1
University of Caen;
2
German Sport University;
3
London South Bank University
In decision-making research, one important aspect of real-life decisions has so far been neglected: the mood
of the decision maker when generating options. The authors tested the use of the take-the-irst (TTF) heuristic
and extended the TTF model to understand how mood inluences the option-generation process of individuals
in two studies, the irst using a between-subjects design (30 nonexperts, 30 near-experts, and 30 experts) and
the second conceptually replicating the irst using a within-subject design (30 nonexperts). Participants took
part in an experimental option-generation task, with 31 three-dimensional videos of choices in team handball.
Three moods were elicited: positive, neutral, and negative. The indings (a) replicate previous results concern-
ing TTF and (b) show that the option-generation process was associated with the physiological component of
mood, supporting the neurovisceral integration model. The extension of TTF to processing emotional factors
is an important step forward in explaining fast choices in real-life situations.
Keywords: emotion, option generation, heart rate variability, creativity, sport, choice
Decision-making research in sports has often
conceived of the athlete as a “cold” decision maker,
unmoved by “hot” affective processes (e.g., Johnson &
Raab, 2003; for an exception, see Laborde, Dosseville,
& Raab, 2013). Yet athletes experience affective states in
training and sports competition (e.g., Martinent, Campo,
& Ferrand, 2012), making them a crucial component of
performance, at both the psychological and the physical
level (Woodman et al., 2009). We sought to test the effects
of affective states on the decision process. Affective states
is a broad term that encompasses several types of affec-
tive phenomena, such as mood and emotions (Scherer,
2005). Here we are concerned only with mood. We tested
decisions made in different mood states that relect the
overall affective state of the individual decision maker
(Scherer, 2005).
Individual decision making is often described in
terms of a inal choice and analyzed by presenting a
ixed set of options, ignoring how options are generated
in the environment or retrieved from memory (Raab,
de Oliveira, & Heinen, 2009). Yet in real life, options
often need to be dynamically encountered or generated
(Johnson & Raab, 2003). Option-generation processes
have been studied in sports to understand better how
an athlete decides (e.g., Johnson & Raab, 2003). Such
decisions and the option generation that precedes them
have been modeled in recent decades (Johnson & Raab,
2003; Ward, Suss, Eccles, Williams, & Harris, 2011).
Some option-generation approaches assume that a high
number of generated options is not detrimental to perfor-
mance (e.g., Ward et al., 2011); the take-the-irst (TTF)
heuristic (Johnson & Raab, 2003), in contrast, assumes
a less-is-more effect: Fewer options generated results in
better choices, at least for experts.
Experts make decisions by relying on their mental
capacities and the characteristics of the speciic decision
environment (Todd & Gigerenzer, 2012). For instance,
when time pressure is not a main characteristic of the task,
as in chess, experts have been found to prefer deliberative
strategies, searching for and relying on a large amount of
information (Bilali´ c, McLeod, & Gobet, 2009; Campitelli
& Gobet, 2004; Moxley, Anders Ericsson, Charness, &
Krampe, 2012). In contrast, when time pressure becomes
a dominant characteristic of the task, as in sports, experts
use mainly relevant information and rely on heuristics
(Raab, 2012). They tend to use simpler rules, such as
TTF, that relect intuitive choices (Raab & Laborde,
2011). Experts have a higher quality of irst and overall
options compared with near-experts or novices (Raab
& Johnson, 2007). Dynamic inconsistency, the number
of trials in which the irst and the best choice are not
identical, has been found to be lower in experts (Raab
& Johnson, 2007), as have decision time (i.e., the time
taken to generate the initial option) and generation time
of all options (Raab & Johnson, 2007). Experts’ gaze
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