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Journal of Economic Psychology 20 (1999) 571±591
www.elsevier.com/locate/joep

Mood and children: Proposition of a measurement scale q
C. Derbaix *, C. Pecheux
LABACC (Consumer Behavior Analysis Laboratory), FUCAM, Catholic University of Mons,
151 Chauss
ee de Binche, 7000 Mons, Belgium
Received 13 October 1997; accepted 12 June 1999

Abstract
After having presented the mood construct, a brief overview of the literature on mood and
consumer behavior and the interest of studying mood and children, the authors detail the
building of a mood scale especially suited to children from 8 to 12. Special attention is devoted
to particular problems encountered in assessing the validity and most of all the reliability of
such a scale. Ó 1999 Elsevier Science B.V. All rights reserved.
PsycINFO classi®cation: 2360
JEL classi®cation: M31
Keywords: Mood; Children; Validity; Reliability

1. Introduction

People may sometimes experience an emotion but are always in some kind
of mood (Nowlis, 1970). Although it could take the extreme forms of elation

q
*

A longer version of this article is available on request from the authors.
Corresponding author. Tel.: +32-65-323-325; fax: +32-65-323-426; e-mail: derbaix@fucam.ac.be

0167-4870/99/$ ± see front matter Ó 1999 Elsevier Science B.V. All rights reserved.
PII: S 0 1 6 7 - 4 8 7 0 ( 9 9 ) 0 0 0 2 5 - 2

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or depression, mood is generally depicted as a mild, generalized, di€use and
transient a€ective state. Capitalizing on the works of Isen (1984); Clark and
Isen (1982); Gardner (1985); Schwarz and Clore (1983, 1988); Pieters and van
Raaij (1988); Derbaix and Pham (1991), the following characteristics of

mood seem essential to stress: one may or may not be aware of one's mood;
moods may result from a lot of small mildly pleasant or unpleasant events or
may emerge as the residual of a speci®c emotion once the emotion's intensity
decreases and its cause is no longer in the focus of attention (Bollnow, 1956);
moods do not always have an identi®able cause 1; moods are of an undifferentiated and unfocused nature or have a di€use and unfocused quality
(i.e., with no or less speci®c target and not induced by a particular stimulus 2;
this undi€erentiated and unfocused nature of mood states makes them potentially informative for a wide variety of judgments); come very often
gradually; tend to last longer than emotions; as other a€ective states are
dicult to verbalize. In psychology, it has been shown that mood impacts on
Encoding/Learning (e.g., Bower, 1981; Leight & Ellis, 1981), Memory/Recall
(e.g., Teasdale & Fogarty, 1979; Clark, Milberg & Ross, 1983); Time perception and orientation (e.g., Hornik, 1982, 1993), Evaluative judgments
(e.g., Isen, Shalker, Clark & Karp, 1978; Isen & Simmonds, 1978; Isen &
Shalker, 1982), Expectations (e.g., Sj
oberg & Magneberg, 1987), Opinions (as
guide to an evaluation, i.e., the ``How-do-I-feel about it'' heuristic, Schwarz
& Clore, 1983, 1988). In marketing an extensive amount of empirical research
has focused on the e€ects of mood states on a variety of dependent variables:
product and brand evaluations (Axelrod, 1963; Miniard, Bhatla & Sirdeshmukh, 1992; Gorn, Goldberg & Basu, 1993), behavioral intentions
(Donovan & Rossiter, 1982; Swinyard, 1993), shopping behavior (Sherman,
Belk & Smith, 1986), ad evaluation (Goldberg & Gorn, 1987), variety seeking

(Kahn & Isen, 1993). Most of these studies have been achieved with adults
as consumers, within an experimental paradigm using different inducing
strategies, the success of which being sometimes checked by the use of
measurement scales. Moreover let us stress that all this literature was dif®cult to structure, with some fragile phenomena (i.e., mood congruent recall,
see Blaney (1986); Bower & Mayer (1985)), with an asymmetry between
positive and negative (especially sadness) moods in effect on memory,
1
Let us stress the way we talk about mood with respect to emotion: we are afraid of something or of
someone but we are in a happy mood.
2
This undi€erentiated and unfocused nature of mood states makes them potentially informative for a
wide variety of judgements.

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573

with some results probably due to the particular product (stimulus) used
(Gardner & Scott, 1990), and ®nally with an unbalance between the number
of studies dealing with positive moods with respect to the ones focused on

negative moods whose effects are typically less reliable (Isen, 1984). Thus this
stream of research generated inconclusive results except the robust congruency bias that consumers' moods exert on the evaluation of (marketing)
stimuli.
Mood e€ects are important to the understanding of children's consumer
behavior as well. A child in a good mood will behave di€erently, during a
shopping trip with his (her) mother, with respect to a child in a bad mood.
The former might disturb less his/her mother and therefore the time spent by
his/her mother for her shopping could be more important. Moreover, the
retail environment (``atmospherics'' in the terms of Kotler, 1974) may impact
on the child's mood. The child's mood could also in¯uence his/her attitude
toward commercials or toward advertised brands. It is also interesting to
study the impact of the editorial climate (eliciting some particular mood) on
the way children rate ads and in order to pretest ads, it is important to work
with as many children in a bad mood than in a good mood to the extent that
the latter might be too positive in evaluating these ads. What seems also
particularly important for those studying mood and children is that mood
might be an input in decisions about consumption for such respondents. The
``How do I feel about it'' heuristic is a shortcut particularly suited to these
respondents for whom the task at hand appears very often complex and for
whom the use of a variety of attributes in a decision process has a very low

probability to occur. Rather than basing their evaluations on a piecemeal
analysis of the available information, children ± as ``cognitive misers''
(Taylor, 1981) ± consult their mood as a salient source of relevant information. Mood e€ects might indeed be more pronounced (Schwarz & Clore,
1988): the more complex the judgmental task, the less cognitively developed
the subjects, the less accessible other information, the higher the time pressure, and the more burdensome the judgment. Thus ± especially for children ±
mood states might serve informative functions through simplifying complex
tasks. In fact for children, evaluative criteria are very often ill-de®ned and
therefore mood can act as a guide to an evaluation. Last but not least children's intention to dissimulate (deception) their mood may be less strong
than adults due to fewer or even no display rules. To the best of our
knowledge none of the research reported in the extant literature (essentially
in Psychology) on mood and children (e.g., Mischel, Coates & Rasko€, 1968;
Moore, Underwood & Rosenhan, 1973; Isen, Horn & Rosenhan, 1973;

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Underwood, Moore & Rosenhan, 1973; Seeman & Schwarz, 1974; Fry, 1975;
Moore, Clyburn & Underwood, 1976; Cialdini & Kenrick, 1976; Masters &
Furman, 1976; Bartlett & Santrock, 1979), assesses mood through a valid and

reliable scale.
The lack of such a scale is perhaps the reason for so little basic research on
children and mood e€ects. However, if we accept the challenge of grappling
with the a€ective side of children's consumer behavior, our methodological
devices must keep pace. Therefore in order to test the evoked hypotheses
within this stream of research measurement tools are needed. To the best of
our knowledge previous research did not address the problem of building a
mood scale especially suited to children from 8 to 12. Children's affect has
nevertheless been assessed in different forms. For instance the most prevalent
means of measuring children's attitudes appears to be an affective measure
either in terms of preference (e.g., Roedder-John & Lakshmi-Ratan, 1992) or
liking (e.g., Hoy, Young & Mowen, 1986; Roedder, Sternthal & Calder,
1983). Macklin (1988) tried two approaches to measure Aad (attitude toward
the ad) using preschoolers. In her ®rst study, Aad was determined by asking
each child how much she or he likes the ad. In her second study, this author
included ®ve additional items that depicted faces showing emotions in relation to the commercial. Nevertheless, the absence of validated constructs
related to children's affect, a lack of coherence in the number of points of the
scales used and undependable methods of data collection can cast doubt on
the results of previous research (as underlined by Bree, 1991; Macklin &
Machleit, 1990; Mangleburg & Tech, 1990).

The building of a valid and reliable mood scale especially suited to children
is thus the purpose of this research. We detail in the next pages a step-by-step
approach clearly modeled on Churchill's (Churchill, 1979) paradigm and
leading to the building of this scale. When studying consumer children, our
primary focus is here on the 8±12 year old range. This age range refers to
children able to answer a questionnaire in writing, who are both prescriptors
and actual buyers (Kapferer, 1985; Mac Neal, 1987; Bree, 1993), who mainly
correspond to a cognitive developmental stage characterized by the ability to
perform complex tasks on concrete objects (Piaget, 1972), who are in primary
school (as opposed to high-school) and ®nally who are not yet entering the
teenagers' segment. According to Mac Neal (1992), ``As a primary market,
children 3 have around $9 billion in income from their families, their

3

In fact American children from 4 to 12 years old.

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575

household responsibilities and work and they spend a major portion of it on
a wide variety of items that please themselves. As a market of in¯uencers,
they give direction to at least $130 billion of parental purchases . . . No other
consumer group has a larger proportion of their income earmarked as discretionary. This means they can spend it for whatever they want, whenever
they want to, wherever they want to''.

2. Methodology
2.1. Scale development objective
In order to apply a mood scale to children, we had to build and validate
such a scale within such a population. We did not want to adapt or
``translate'' for children a scale developed for measuring adults' moods. In
fact these scales were: too long (e.g., the 140 adjectives of the scale of Green
and Nowlis (1957), the 71 items of the scale developed by Sj
oberg, Svensson
and Persson (1979), the 32 adjectives used by Lawson (1985) adapted from
Lubin (1965), the 18 items of Mehrabian and Russel (1974), the 24 adjectives
of Mano (1988), the 24 items of Izard (1977)); built on underlying dimensions
which are perhaps not the ones underlying children's moods (Goldberg &
Gorn, 1987; Allen & Janiszewski, 1989); not devoid of de®ciencies (Nowlis &

Nowlis, 1965; Catell, 1973). So, the objective was to build a measurement
scale particularly suited to children, i.e., being short and easy to ful®ll,
multisituational, using children's vocabulary and with an appropriate format
as far as the number of points of the scale was concerned.
Taking into account the advice of Rossiter (1977), Mac Neal (1987), and
Bree (1991) and our experience with interviewing children from 8 to 12, the
goal was ± at the technical level ± to: use a verbal scale from the Likert type;
propose 4 points on that scale (2 to agree and 2 to disagree); avoid the interrogative negative format ill-suited to children and rotate the items when
using more than 5. Building a mood scale is crucial for the exploration of the
role of moods in children consuming behaviors. But working with mood
generates some speci®c problems summarized in Table 1.
2.2. Issues in scale development
Table 1 summarizes the speci®c issues encountered when building a mood
scale especially suited to our young population.

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Table 1

Mood: Speci®c conceptual and methodological problems in the building of a measurement scale
Speci®c problems related to the study of
mood

Description

Solutions

Mood ˆ a transient
phenomenon

Mood is a short-lived phenomenon. Therefore its measurement, compared for instance to
enduring or ego-involvement, is
time-speci®c. With children,
this problem may be particularly acute due to the instability
of a lot of their conducts
In order to assess the predictive
validity of some constructs one
measures, in some circumstances, the predictor (here mood)
and the predicted variables at 2

separated moments. But mood
may be quite di€erent at times 1
and 2
There is a tendency, particularly
for adults (see Derbaix, 1995) to
dissimulate one's mood especially if negative
The mood scale to be developed
has to be applicable to numerous contexts
To assess test-retest reliability,
one has to measure mood of the
same children at time 1 (test)
and later (at time 2, retest). But
mood may change between the
test and the retest

To use the measurement scale exactly
at the time you want to study mood
and its impact

Predictive validity

Social desirability

Multi-situational

Test±retest reliability

Bipolarity of the underlying dimensions
of the construct

Mood is often depicted as a
bipolar concept. But there is no
assurance that the items illustrating the underlying dimensions are really bipolar

It seems that concurrent validity (i.e.
measuring the different variables at the
same moment, see De Vellis (1991)) is
more appropriate to the mood
construct

Children are generally more spontaneous than adults. Therefore the usual
display rules may not be used by young
respondents
To avoid too situational items

In order to focus on the stability of
the scale and to rule out changes coming
from mood alteration, we may screen our
young respondents on the basis of 3
procedures:
(1) to assess their mood through a
(simple) one item smiling face mood scale
at the test and at the retest;
(2) to compute their mood score
(by summing up their responses to all
our items designed to measure mood) on
both occasions;
(3) to ask the teacher, on both
occasions, their pupils' mood.
Principal component analysis
and oblique factorial analysis will help in
``solving'' that problem

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577

In order to get a valid and reliable scale we worked within a framework
borrowed from Churchill's paradigm. The various steps of our work are
described in Fig. 1.

Fig. 1. Our detailed framework.

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3. Scale development and testing
3.1. Preliminary scale development and puri®cation
This research was achieved in Europe, in a French-speaking country.
Therefore, the starting de®nition was in French and due to Thines and
Lempereur (1984). Its tentative translation is ``Mood is a transient a€ective,
emotional and instinctive state giving a pleasant or unpleasant tone to oneÕs
frame of mind''. A pilot study consisting of 16 focused group interviews (64
children) was undertaken in order to grasp the way this construct was experienced by children from 8 to 12, i.e., their vocabulary, the a priori underlying dimensions, the salient associations. All this was classically achieved
using open-ended questions and in an unstructured manner looking for antecedents and consequences of mood. From this pilot study and from the
overview of the literature, 47 items emerged (dealing with the following a
priori dimensions: pleasure, happiness, arousal, to be friendly with others, to
be in good/bad shape, boredom, loneliness, sadness, . . .). These propositions
were submitted to nine experts 4 to evaluate their ``goodness of ®t'' to
measure the moods of children from 8 to 12. On the basis of the expertsÕ
evaluation, 22 items were selected for the ®rst data collection bearing in mind
the cognitive capacities of our target population.
167 children 5 participated to the ®rst data collection. Each child had to
answer to 21 6 items followed by a NO±YES scale (the expertsÕ advice was to
disregard the classical 4-point Likert type scale anchored by De®nitely disagree (1) and De®nitely agree (4), ill-suited to most of our items concerning
mood):

4
Essentially scholars working (in France and in Belgium) in the domain of a€ect and/or in the domain
of marketing and children. They took into account redundancy, ambiguity, understanding, . . .
5
Due to incomplete questionnaires, only the answers of 148 children were usable to analyse the data.
6
A pre-test achieved with 48 children led us to rule out one item misunderstood by children.

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579

A classic factor analysis was conducted (amount of variance ˆ 61% with 5
factors) and then an oblique rotation was asked for to achieve a simpler,
theoretically more meaningful factor pattern 7. Items loading greater than 0.5
on a factor after the oblique rotation were retained. 16 items emerged from
this ®rst data analysis with good CronbachÕs a for the ®rst three factors
(respectively 0.84, 0.79 and 0.79). In order to show that we did not leave out
any potential constructs a clustering method was also run. In clear, a hierarchical clustering approach 8 using two types of clustering (``complete
linkage or furthest neighbor'' and ``single linkage or nearest neighbor'') was
implemented. These two types of clustering led to very similar results revealing three or four signi®cant clusters. The ®ve items eliminated in our
factor analyses were spread in di€erent clusters. This means that they didn't
merge in an homogenous and separated cluster (illustration of an actual
construct). Moreover, three out of these ®ve items were in the ``biggest'' and
less homogenous cluster composed of 11 items, their contribution to the
meaning of this cluster being rather limited. Concerning the two other items,
they belonged to two di€erent clusters, which they integrated during the last
steps of the clustering procedure, being thus to some extent ``outliers''. In
conclusion this complementary analysis supported the results of our factor
analysis.
149 (other) children 9 participated to the second data collection which led
to the selection of 13 items loading highly (>0.5) on one of the factors after
oblique rotation (amount of variance ˆ 65.3% with ®ve factors).
3.2. Final scale development and testing
3.2.1. Third and fourth data collections
The ®rst two data collections were achieved in order to purify the measure.
New data were necessary to build a Multitrait±Multimethod Matrix
(MTMM) in order to assess construct validity and test±retest reliability. Such
a matrix requires the use of an alternative construct and an alternative
method. Concerning the construct, involvement was selected in order to assess discriminant validity (a reliable and valid scale to measure enduring
involvement within such a population has been recently built, Derbaix and

7
8
9

The option we worked with is OBLIMIN provided by SPSS.
Provided by SPSS.
137 questionnaires were completely ful®lled and formed the data base of our second analysis.

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C. Derbaix, C. Pecheux / Journal of Economic Psychology 20 (1999) 571±591

Pecheux (1997) 10). As far as the second format of response is concerned, we
decided to select a 4-point smiling face scale (with no verbal support). For
each item, the child had to choose one of the four faces (ranging from a
smiling face to a sad face) which best illustrated what he was currently
feeling. Thus during the third data collection (undertaken with 150 children)
and the fourth data collection (achieved two weeks later with 130 children
out of 150), the same child had to respond to the items in two formats 11 both
for mood and for involvement 12. As one can see, in Table 2, the results of the
factor analysis with oblique rotation are similar for both response formats
for the mood scale 13.
So, for the ®rst time, we had got a clear 2-factor solution: the ®rst factor
with items illustrating bad mood and the second factor with items about
good mood. 14 With LISREL 8, a con®rmatory factor analysis (CFA) was
run on these two factors and a good solution for eleven items was obtained
(six for bad mood (``to be bored'' disappeared); ®ve for happy mood (``to be a
good boy/girl'' disappeared)) with the following goodness of ®t indices
(v2 ˆ 55.616, df ˆ 41, p ˆ 0.063; RMSEA ˆ 0.0499, p ˆ 0.474; CFI ˆ 0.973;
TLI ˆ 0.963 for the NO±YES response format and v2 ˆ 48.289, df ˆ 37,
p ˆ 0.101; RMSEA ˆ 0.0462, p ˆ 0.541; CFI ˆ 0.985; TLI ˆ 0.977 for Smiling
Faces). (The matrices of covariance between items used for running LISREL
8 are displayed in the Appendix.)
At that stage we built a ®rst MTMM matrix. Unfortunately, this matrix
revealed some problems especially for the convergent validity of the ``bad
mood'' dimension of our scale. Looking at each questionnaire we found
problems with bad mood items when using the Smiling Faces response format. Therefore we decided to drop the Smiling Faces response format illsuited to measure bad mood (see Section 4) and to undertake two new data
collections (®fth and sixth) with a new response method. Two new formats
were pretested (43 children) and the semantic di€erential was selected.

10
After having interviewed more or less 2000 children from 8 to 12, two dimensions underlying the
involvement construct clearly appeared: Appeal (seven items) and Opinion (three items).
11
In order to avoid ``spurious'' convergence between ``methods'', once the ®rst part of the questionnaire
was ful®lled (so after the ®rst response format), this questionnaire was taken in.
12
Questions about involvement were asked with respect to three products (ice creams, comics and
yogurt).
13
The results displayed are the ones of pattern matrix (the amount of variance was 52% for the ®rst
format and 57.4% for the second one).
14
See our tentative translation in Table 2. The item was of course a proposition with just one word (i.e.,
``f^
ache'') in French and not two as in our tentative translation (angry or cross) in English.

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581

Table 2
Results of the third data collection
Items
(1) Format (NO no yes YES)
Moan/grumble
Angry/cross
Sad
To sulk
Unhappy
Grouse
To be bored
Joyful
To feel like pleasing ...
Happy
To have great fun
To laugh
To be a good boy/girl
a
(2) Smiling faces
Moan/grumble
Angry/cross
Grouse
Unhappy
To sulk
Sad
To be bored
To have great fun
To be a good boy/girl
To feel like pleasing ...
Happy
To laugh
Joyful
a

Factor 1

Factor 2

0.876
0.774
0.738
0.721
0.710
0.644
0.507
0.763
0.744
0.740
0.658
0.646
0.569
0.828

0.779

0.884
0.860
0.841
0.816
0.803
0.745
0.587
0.782
0.712
0.705
0.676
0.666
0.542
0.902

0.776

3.2.2. Fifth and sixth data collections
133 children participated to the ®fth collection. Out of these children 88
children were retested (sixth collection). As it was the case for the third and
the fourth data collections, each child had to answer both to the mood (11
items) and involvement (10) items using two response formats (YES±NO and
Semantic Di€erential with 4 points separating the bipolar items) and doing it
twice (for the test: ®fth data collection and for the retest: sixth data collection). In order to focus on the stability of our scale and to rule out changes
coming from mood alteration, we screened our respondents on the basis of
the three procedures described in Table 1 (point 5). On these bases, 68

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children were selected to compute the test±retest reliability diagonal of the
MTMM matrix. The data coming from the ®fth collection were submitted to
2 CFA (LISREL 8), one for each response format. The results were for the
YES±NO format: v2 ˆ 50.647, df ˆ 38, p ˆ 0.082; RMSEA ˆ 0.0502,
p ˆ 0.468; CFI ˆ 0.966; TLI ˆ 0.951 and for the Semantic Differential format:
v2 ˆ 52.546, df ˆ 40, p ˆ 0.088; RMSEA ˆ 0.0487, p ˆ 0.495; CFI ˆ 0.967;
TLI ˆ 0.955. Two items (``Just now, I had like to please the other people''
and ``Just now, I have the sulks'') did not exhibit good reliability. The results
concerning the involvement construct con®rmed perfectly the 2-factor
structure previously obtained for this variable (see Derbaix & Pecheux, 1997).
The test±retest reliability diagonal was computed by correlating the scores
of each child on both occasions for bad mood, good mood and the two
underlying dimensions of involvement (Appeal and Opinion). All the other
values of the MTMM matrix were obtained similarly on the basis of our 133
children having participated to the ®fth collection. The MTMM matrix is
displayed (see Fig. 2). Far from being perfect, this MTMM is nevertheless
acceptable. The test±retest reliability diagonal contains good ®gures and the
problem of low convergent validity for the bad mood factor (due to the
Smiling Faces response format previously used) is now solved. All the ®gures
in this matrix are as they should be with respect to the others 15.
An additional test of discriminant validity was provided by LISREL 8. For
each correlation (obtained by Lisrel, i.e., the PHI coecients) between two
(di€erent) factors of the MTMM, we found that:
1. the average variance extracted (for each of the two factors) was greater
than the squared correlation between the two factors (Fornell & Larcker,
1981) (for 22 out of 24 cases, the two exceptions being two correlations between good and bad mood),
2. factor correlations were signi®cantly di€erent from unity (based on the
con®dence interval around the estimated factor correlation, i.e., the PHI).
Finally, nine items emerged from these data collections 16 and analyses.
Our ®nal scale (which is in French between brackets) is:
Just now, I am feeling sad (En ce moment, jÕai du chagrin)
Just now, I am feeling unhappy (En ce moment, je suis malheureux)
Just now, I am grousing (En ce moment, je r^ale)
15
See Campbell and Fiske (1959), for the way ®gures of, for instance, the convergent validity diagonal
have to be compared to ®gures of the heterotrait-monomethod triangles and of the heterotraitheteromethod triangles (dotted lines).
16
Undertaken with a total of 800 di€erent children from 8 to 12 years old.

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583

Fig. 2. Multitrait±multimethod matrix.

Just
Just
Just
Just
Just
Just

now,
now,
now,
now,
now,
now,

I
I
I
I
I
I

am angry (En ce moment, je suis f^ache)
am grumbling (En ce moment, je rouspete)
am in a joyful mood (En ce moment, je suis joyeux)
have great fun (En ce moment, je rigole beaucoup)
feel like laughing (En ce moment, jÕai envie de rire)
am happy (En ce moment, je suis heureux)

3.2.3. Criterion validity
A ®nal data collection focused on criterion validity was conducted through
an experimental procedure whose goal was to show that children in a good
mood vs those in a bad mood exhibited different patterns with respect to
remembering and evaluating a string of three commercials. Printed material
consisting of a sad text (starvation and death of children in Soudan with a
dramatic picture of skinny children) and a happy text (comic strips) supposed
to induce quite different moods was used.
98 children from 8 to 12 participated (in class) to this ®nal experiment: the
®rst group (``Soudan'') was composed of 40 children and the second group of
58 children. Both groups were instructed to read silently and individually the
sad or the happy text and to underline the elements or expressions they
thought were the most important in the text (to ensure the text was read).
Then they ®lled out the mood scale and saw a string of three unknown

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commercials. 17 Finally they were interviewed about what they recalled from
the string and their evaluative judgment of this string.
Our mood induction procedures were really successful. The mood scores
were indeed quite di€erent: 15.67 (``Soudan'') vs 28.17 (Comic strips;
p < 0.001). We would expect that a scale designed to measure mood would
yield different average scores for those who carefully read a very sad text and
those who read a happy text. But this issue still related more to construct
than to predictive validity. In fact this known group method of validation
had frequently been used to validate and re®ne attitude scales. As far as
criterion validity was concerned, the scores of recall and evaluation having
been obtained within the same time frame as the scores on the instrument to
be validated, this form of criterion validity was of the concurrent validity
type.
35% of the children in the sad group vs 56.9 % in the happy group correctly
reported the exact number of ads (3) in the string (p < 0.04). Then the focus
was on measures differing on the richness of recall to contrast both groups.
Use was made of the number of times children correctly reported (or described): the brand + the product + the ad (measure 1); the brand and the
product (measure 2); the brand and the ad (measure 3); the ad and the
product (measure 4) and ®nally the brand (measure 5). Signi®cant statistical
differences ± in the expected direction ± were found for the two richest
measures of recall (measures 1 and 2) (p < 0.05 ; p < 0.02). Finally the child
had to evaluate the whole string of commercials along three 4-point scales
(liking, annoying and great). The difference was not statistically signi®cant,
perhaps due to a contrast effect in the sad group (i.e., children in this group
seemed happy to watch something more enjoyable than the text about children in Soudan). On the basis of this experiment the conclusion was that our
scale satis®ed construct and criterion validities.

4. Discussion
After six data collections, a valid and reliable scale measuring mood of
children from eight to twelve was obtained. This scale was composed of two
dimensions which were not as bipolar as one might a priori think: good mood

17
Selected as being as neutral as possible in order to minimize the possible impact of these commercials
on childrenÕs mood.

C. Derbaix, C. Pecheux / Journal of Economic Psychology 20 (1999) 571±591

585

and bad mood. In clear, the di€erent items describing each of these two factors
had not a perfect counterpart as far as the items of the other factor were
concerned. Classic factor analysis as well as oblique rotation provided loadings whose importance and sign showed clearly that one needed both factors
and therefore both sets of items to measure mood to the extent that clear
bipolarity was not dominant in the ®nal results. The practical implication was
that one needed nine items to measure mood, instead of four or ®ve.
It was also demonstrated that these two underlying dimensions were not
contaminated by dimensions from another construct and thus that our mood
construct was unidimensional. At this level the choice of another construct
was quite restricted to the extent that Marketing scale Handbooks, re¯ecting
the state of the art, did not propose validated and reliable scales suited to
children. Therefore use was made of a scale recently built to measure what
could be considered as one of the most essential construct in Consumer
Behavior: involvement. The ®nal experiment con®rmed the validity of the
scale, even at the predictive level.
What also emerged from this research ± at a more technical level ± is that it
was really dicult to use a Smiling Faces response format with children when
working in the domain of a€ect, especially when proposed items were about
bad mood. It seemed that a child did not understand the di€erence between
reporting what he was currently feeling and selecting a smiling face corresponding to the item. Therefore our conclusion was to recommend not using
this response format when working with negative a€ect.
The ®nal scale was completely free of items dealing with relationships
between the respondent and other persons such as ``Just now, I am punished ''
or ``Just now, I feel like pleasing the others''. These items did not go through
the screening procedure. So, mood was really an intra-personal state well
depicted here by individual, ``psychological'' items. Except for good and bad
(moods) the ®nal scale could not be characterized along classic underlying
factors discovered in measuring adults' mood: pleasure, arousal and tension
(see for instance Sj
oberg et al., 1979; Mano, 1988) described in the work of
Wundt (1905) as early as in 1905.
The ®nal scale was not too long (9 items) and could thus be implemented in
numerous applications dealing with the impact of the ``editorial climate''
(generating some kind of mood to be measured by our scale) on recall and
evaluation of ads targeted at children, or dealing with the success or failure of
atmospherics by measuring the child's mood when entering and leaving a
supermarket, or by comparing amount of positive or negative affective reactions elicited by commercials while watching TV in a good or bad mood.

586

C. Derbaix, C. Pecheux / Journal of Economic Psychology 20 (1999) 571±591

At this stage let us, one more time, stress how we believe in the adequacy of
the ``How do I feel-about-it ?'' heuristic to children. Since Piaget and Inhelder
(1992), studies have demonstrated that children do not process information
systematically in numerous situations, that they have a greater tendency to be
in¯uenced by heuristic cues, that most of their reactions in marketing situations are more from an affective than from a cognitive type (Derbaix, 1982;
Derbaix & Bree, 1997). So now (after interviewing more than 900 different
children), we have a measurement tool enabling us to experimentally test if
children frequently use in their consumption experiences the shortcut, i.e., to
use their mood as a source of information and evaluation with respect to
stimuli they consider not easy to appreciate. Moreover, being in a positive
mood can induce subjects to make their decisions relatively quickly, to base
their decisions on little information and to prefer intuitive heuristic problem
solving strategies to more effortful, detailed procedures (Isen, 1987). Children
are perhaps the prototypical subjects of this kind of decision processes. We
are now able to test that.
Furthermore, mood can also be viewed as a moderator whose measurement can lead to the assignment of children in various categories and to the
detection of outliers (i.e., totally elated or depressed respondents) who have
to be separately analyzed especially when working with small samples. Of
course the generalizability of the scale is restricted to 8±12 year old children.
In this age range we have children whose cognitive capacities enable them to
understand and answer questions in writing and who are not yet entering the
teenagers' segment. Whether our scale is suitable to older children has to be
checked by future studies. Finally, little is known about the psychological
mechanism by which Mood operates for Children across cultures. So we have
to be extremely cautious, as always after the building of a scale, as far as its
robustness across cultures is concerned. If good mood and bad mood seem a
priori universal the items as well as their degree of bipolarity might of course
di€er.

Appendix A. Covariance matrices (LISREL 8)
Third data collection ± Yes±No scale
Grouse
Grouse
Sulk
Moan

1.00
0.44
0.41

Sulk

1.00
0.59

Moan

1.00

Angry

Unhap.

Sad

G. Fun

Joyful

Happy

Laugh

Pleasing

587

C. Derbaix, C. Pecheux / Journal of Economic Psychology 20 (1999) 571±591
Text Table (continued)

Angry
Unhap.
Sad
G. Fun
Joyful
Happy
Laugh
Pleasing

Grouse

Sulk

Moan

Angry

Unhap.

Sad

0.42
0.43
0.35
ÿ0.17
ÿ0.19
ÿ0.12
ÿ0.07
ÿ0.13

0.53
0.34
0.47
ÿ0.11
ÿ0.35
ÿ0.22
ÿ0.14
ÿ0.13

0.67
0.49
0.59
ÿ0.03
ÿ0.19
ÿ0.23
ÿ0.07
ÿ0.08

1.00
0.39
0.64
ÿ0.17
ÿ0.30
ÿ0.34
ÿ0.16
ÿ0.18

1.00
0.49
ÿ0.14
ÿ0.16
ÿ0.08
ÿ0.03
ÿ0.06

1.00
ÿ0.16
ÿ0.35
ÿ0.29
ÿ0.09
ÿ0.29

G. Fun

Joyful

Happy

Laugh

Pleasing

1.00
0.43
0.35
0.36
0.33

1.00
0.64
0.40
0.44

1.00
0.38
0.42

1.00
0.32

1.00

G. Fun

Joyful

Happy

Laugh

Pleasing

1.00
0.29
0.44
0.50
0.36

1.00
0.38
0.33
0.36

1.00
0.42
0.43

1.00
0.27

G. Fun

Joyful

Happy

Laugh

1.00
0.47
0.35
0.23

1.00
0.32
0.29

1.00
0.21

Third data collection ± Smiling Faces scale
Grouse
Sulk
Moan
Angry
Unhap.
Sad
G. Fun
Joyful
Happy
Laugh
Pleasing

Grouse

Sulk

Moan

Angry

Unhap.

Sad

1.00
0.60
0.74
0.76
0.59
0.55
ÿ0.11
ÿ0.15
ÿ0.29
ÿ0.26
ÿ0.19

1.00
0.66
0.60
0.66
0.47
0.02
ÿ0.33
ÿ0.19
ÿ0.17
ÿ0.15

1.00
0.74
0.57
0.51
0.01
ÿ0.27
ÿ0.23
ÿ0.17
ÿ0.11

1.00
0.66
0.56
ÿ0.07
ÿ0.20
ÿ0.30
ÿ0.17
ÿ0.28

1.00
0.64
0.02
ÿ0.28
ÿ0.31
ÿ0.21
ÿ0.22

1.00
ÿ0.03
ÿ0.28
ÿ0.28
ÿ0.15
ÿ0.18

1.00

Fifth data collection ± Yes±No scale
Grouse
Sulk
Moan
Angry
Unhap.
Sad
G. Fun
Joyful
Happy
Laugh
Pleasing

Grouse

Sulk

Moan

Angry

Unhap.

Sad

1.00
0.18
0.49
0.56
0.33
0.47
0.04
ÿ0.13
ÿ0.32
ÿ0.07
ÿ0.05

1.00
0.36
0.33
0.31
0.31
0.10
ÿ0.22
ÿ0.03
0.04
0.06

1.00
0.49
0.17
0.37
ÿ0.02
ÿ0.15
ÿ0.20
0.02
0.08

1.00
0.42
0.56
0.11
ÿ0.15
ÿ0.12
ÿ0.09
0.01

1.00
0.61
ÿ0.07
ÿ0.22
ÿ0.24
ÿ0.09
ÿ0.03

1.00
0.02
ÿ0.14
ÿ0.23
ÿ0.01
0.01

1.00
0.27
0.33
0.50
0.36

Pleasing

1.00

588

C. Derbaix, C. Pecheux / Journal of Economic Psychology 20 (1999) 571±591

Fifth data collection ± Semantic Di€erential scale
Grouse
Sulk
Moan
Angry
Unhap.
Sad
G. Fun
Joyful
Happy
Laugh
Pleasing

Grouse

Sulk

Moan

Angry

Unhap.

Sad

1.00
0.44
0.42
0.32
0.29
0.34
ÿ0.10
ÿ0.20
ÿ0.24
ÿ0.18
ÿ0.05

1.00
0.42
0.41
0.41
0.56
0.07
ÿ0.37
ÿ0.33
ÿ0.12
ÿ0.16

1.00
0.44
0.25
0.24
ÿ0.01
ÿ0.29
ÿ0.23
ÿ0.14
ÿ0.26

1.00
0.41
0.35
ÿ0.05
ÿ0.32
ÿ0.33
ÿ0.14
ÿ0.29

1.00
0.49
ÿ0.24
ÿ0.31
ÿ0.44
ÿ0.21
ÿ0.31

1.00
ÿ0.14
ÿ0.42
ÿ0.37
ÿ0.16
ÿ0.18

G. Fun

1.00
0.29
0.26
0.47
0.07

Joyful

Happy

Laugh

1.00
0.59
0.42
0.31

1.00
0.42
0.29

1.00
0.21

Pleasing

1.00

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