Mood and children: Proposition of a measurement scale
qC. Derbaix*, C. Pecheux
LABACC (Consumer Behavior Analysis Laboratory), FUCAM, Catholic University of Mons, 151 Chaussee 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 www.elsevier.com/locate/joep
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: [email protected]
or depression, mood is generally depicted as a mild, generalized, diuse and transient aective 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 cause1; moods are of an undif-ferentiated and unfocused nature or have a diuse and unfocused quality (i.e., with no or less speci®c target and not induced by a particular stimulus2; this undierentiated and unfocused nature of mood states makes them po-tentially informative for a wide variety of judgments); come very often gradually; tend to last longer than emotions; as other aective states are dicult 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 per-ception 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., Sjoberg & 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 eects of moodstateson a variety of dependent variables: product and brand evaluations (Axelrod, 1963; Miniard, Bhatla & Sir-deshmukh, 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,
1Let us stress the way we talk about mood with respect to emotion: we are afraidofsomething orof
someone but we areina happy mood.
2This undierentiated and unfocused nature of mood states makes them potentially informative for a
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 congru-ency bias that consumers' moods exert on the evaluation of (marketing) stimuli.
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 eects. However, if we accept the challenge of grappling with the aective 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 ofbuilding 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 rela-tion 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, children3 have around $9 billion in income from their families, their
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 dis-cretionary. 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 Sjoberg, 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 in-terrogative 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
Mood: Speci®c conceptual and methodological problems in the building of a measurement scale
Speci®c problems re-larly acute due to the instability of a lot of their conducts
To use the measurement scaleexactly at the timeyou want to study mood and its impact
Predictive validity In order to assess the predictive validity of some constructs one measures, in some circumstanc-es, the predictor (here mood) and the predicted variables at 2 separated moments. But mood may be quite dierent at times 1 and 2
It seems thatconcurrent validity(i.e. measuring the different variables at the same moment, see De Vellis (1991)) is more appropriate to the mood construct
Social desirability There is a tendency, particularly for adults (see Derbaix, 1995) to dissimulate one's mood espe-cially if negative
Children are generally more spon-taneous than adults. Therefore the usual display rules may not be used by young respondents
Multi-situational The mood scale to be developed has to be applicable to numer-ous contexts
To avoid too situational items
Test±retest reliability 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
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. Bipolarity of the
un-derlying dimensions of the construct
Mood is often depicted as a bipolar concept. But there is no assurance that the items illus-trating the underlying dimen-sions are really bipolar
Principal component analysis
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.
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 aective, 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 ex-perienced by children from 8 to 12, i.e., their vocabulary, the a priori un-derlying dimensions, the salient associations. All this was classically achieved using open-ended questions and in an unstructured manner looking for an-tecedents 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 children5 participated to the ®rst data collection. Each child had to answer to 216items followed by a NO±YES scale (the expertsÕadvice was to disregard the classical 4-point Likert type scale anchored by De®nitely dis-agree(1) and De®nitely agree (4), ill-suited to most of our items concerning mood):
4Essentially scholars working (in France and in Belgium) in the domain of aect and/or in the domain
of marketing and children. They took into account redundancy, ambiguity, understanding,. . .
A classic factor analysis was conducted (amount of variance61% with 5 factors) and then an oblique rotation was asked for to achieve a simpler, theoretically more meaningful factor pattern7. 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 hier-archical clustering approach8 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 re-vealing three or four signi®cant clusters. The ®ve items eliminated in our factor analyses were spread in dierent 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 dierent 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) children9participated 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 variance65.3% 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 theconstruct, involvement was selected in order to as-sess discriminant validity (a reliable and valid scale to measure enduring involvement within such a population has been recently built, Derbaix and
7The option we worked with is OBLIMIN provided by SPSS. 8Provided by SPSS.
Pecheux (1997)10). As far as thesecond formatof 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 formats11both for mood and for involvement12. 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 scale13.
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
55.616, df41, p0.063; RMSEA0.0499, p0.474; CFI0.973;
TLI0.963 for the NO±YES response format and v248.289, df37,
p0.101; RMSEA0.0462,p0.541; CFI0.985; TLI0.977 forSmiling
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 for-mat. Therefore we decided to drop the Smiling Faces response format ill-suited 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 dierential 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).
13The results displayed are the ones ofpatternmatrix (the amount of variance was 52% for the ®rst
format and 57.4% for the second one).
14See our tentative translation in Table 2. The item was of course a proposition with justoneword (i.e.,
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 Dierential with 4 points separating the bipolar items) and doing it twice (for the test: ®fth data collection and for the retest: sixth data collec-tion). 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 Table 2
Results of the third data collection
Items Factor 1 Factor 2
(1) Format (NO no yes YES)
Moan/grumble 0.876
Angry/cross 0.774
Sad 0.738
To sulk 0.721
Unhappy 0.710
Grouse 0.644
To be bored 0.507
Joyful 0.763
To feel like pleasing ... 0.744
Happy 0.740
To have great fun 0.658
To laugh 0.646
To be a good boy/girl 0.569
a 0.828 0.779
(2) Smiling faces
Moan/grumble 0.884
Angry/cross 0.860
Grouse 0.841
Unhappy 0.816
To sulk 0.803
Sad 0.745
To be bored 0.587
To have great fun 0.782
To be a good boy/girl 0.712
To feel like pleasing ... 0.705
Happy 0.676
To laugh 0.666
Joyful 0.542
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: v250.647, df38, p0.082; RMSEA0.0502,
p0.468; CFI0.966; TLI0.951 and for theSemantic Differentialformat:
v252.546, df40, p0.088; RMSEA0.0487, p0.495; CFI0.967; TLI0.955. 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 coecients) between two (dierent) 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 be-tween good and bad mood),
2. factor correlations were signi®cantly dierent from unity (based on the con®dence interval around the estimated factor correlation, i.e., the PHI). Finally, nine items emerged from these data collections16 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)
15See Campbell and Fiske (1959), for the way ®gures of, for instance, the convergent validity diagonal
have to be compared to ®gures of the monomethod triangles and of the heterotrait-heteromethod triangles (dotted lines).
Just now, I am angry (En ce moment, je suis f^ache)
Just now, I am grumbling (En ce moment, je rouspete)
Just now, I am in a joyful mood (En ce moment, je suis joyeux)
Just now, I have great fun (En ce moment, je rigole beaucoup)
Just now, I feel like laughing (En ce moment, jÕai envie de rire)
Just now, I am happy (En ce moment, je suis heureux)
3.2.3. Criterion validity
A ®nal data collection focused oncriterion validitywas 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 ahappy 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
commercials.17Finally 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 dierent: 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 de-scribed): 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 chil-dren 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
17Selected as being as neutral as possible in order to minimize the possible impact of these commercials
and bad mood. In clear, the dierent 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 load-ings 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 dicult to use a Smiling Faces response format with children when working in the domain of aect, especially when proposed items were about bad mood. It seemed that a child did not understand the dierence between reporting what he was currently feeling and selecting a smiling face corre-sponding to the item. Therefore our conclusion was to recommend not using this response format when working with negative aect.
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 Sjoberg 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
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 situ-ations 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 measure-ment can lead to the assignmeasure-ment 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 dier.
Appendix A. Covariance matrices (LISREL 8)
Third data collection ± Yes±No scale
Grouse Sulk Moan Angry Unhap. Sad G. Fun Joyful Happy Laugh Pleasing Grouse 1.00
Sulk 0.44 1.00
Third data collection ± Smiling Faces scale
Fifth data collection ± Yes±No scale
Grouse Sulk Moan Angry Unhap. Sad G. Fun Joyful Happy Laugh Pleasing Grouse 1.00
Sulk 0.60 1.00
Moan 0.74 0.66 1.00
Angry 0.76 0.60 0.74 1.00
Unhap. 0.59 0.66 0.57 0.66 1.00
Sad 0.55 0.47 0.51 0.56 0.64 1.00
G. Fun ÿ0.11 0.02 0.01 ÿ0.07 0.02 ÿ0.03 1.00
Joyful ÿ0.15 ÿ0.33 ÿ0.27 ÿ0.20 ÿ0.28 ÿ0.28 0.29 1.00
Happy ÿ0.29 ÿ0.19 ÿ0.23 ÿ0.30 ÿ0.31 ÿ0.28 0.44 0.38 1.00
Laugh ÿ0.26 ÿ0.17 ÿ0.17 ÿ0.17 ÿ0.21 ÿ0.15 0.50 0.33 0.42 1.00
Pleasing ÿ0.19 ÿ0.15 ÿ0.11 ÿ0.28 ÿ0.22 ÿ0.18 0.36 0.36 0.43 0.27 1.00
Grouse Sulk Moan Angry Unhap. Sad G. Fun Joyful Happy Laugh Pleasing Grouse 1.00
Sulk 0.18 1.00
Moan 0.49 0.36 1.00
Angry 0.56 0.33 0.49 1.00
Unhap. 0.33 0.31 0.17 0.42 1.00
Sad 0.47 0.31 0.37 0.56 0.61 1.00
G. Fun 0.04 0.10 ÿ0.02 0.11 ÿ0.07 0.02 1.00
Joyful ÿ0.13 ÿ0.22 ÿ0.15 ÿ0.15 ÿ0.22 ÿ0.14 0.27 1.00
Happy ÿ0.32 ÿ0.03 ÿ0.20 ÿ0.12 ÿ0.24 ÿ0.23 0.33 0.47 1.00
Laugh ÿ0.07 0.04 0.02 ÿ0.09 ÿ0.09 ÿ0.01 0.50 0.35 0.32 1.00
Pleasing ÿ0.05 0.06 0.08 0.01 ÿ0.03 0.01 0.36 0.23 0.29 0.21 1.00
Text Table (continued)
Grouse Sulk Moan Angry Unhap. Sad G. Fun Joyful Happy Laugh Pleasing
Angry 0.42 0.53 0.67 1.00
Unhap. 0.43 0.34 0.49 0.39 1.00
Sad 0.35 0.47 0.59 0.64 0.49 1.00
G. Fun ÿ0.17 ÿ0.11 ÿ0.03 ÿ0.17 ÿ0.14 ÿ0.16 1.00
Joyful ÿ0.19 ÿ0.35 ÿ0.19 ÿ0.30 ÿ0.16 ÿ0.35 0.43 1.00
Happy ÿ0.12 ÿ0.22 ÿ0.23 ÿ0.34 ÿ0.08 ÿ0.29 0.35 0.64 1.00
Laugh ÿ0.07 ÿ0.14 ÿ0.07 ÿ0.16 ÿ0.03 ÿ0.09 0.36 0.40 0.38 1.00
Fifth data collection ± Semantic Dierential scale
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