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Running head: MOOD, ATTENTION, AND THE AHA! MOMENT 1

Mood, Attention, and the Aha! Moment

Eureka C. Y. Foong, Kay Livesay

Linfield College

MOOD, ATTENTION AND THE AHA! MOMENT 2

Abstract

Although past research has generally found that positive affect broadens attentional scope

and enhances creativity, recent evidence suggests that the relationship between mood and

attentional scope depends on the present dominant attentional focus. The current research seeks

to extend these new findings to the ability to solve insight problems. Undergraduates were

primed with a global or local focus of attention using a computerized modified Navon letter task

and induced with a positive, negative, or neutral mood state using short video clips. They then

worked on three insight problems that required restructuring to arrive at the solutions. Contrary

to past research, the study found a significant main effect of attentional focus on insight problem

solving performance. Specifically, participants primed with a local, as opposed to global, focus

of attention solved significantly more insight problems. There was no significant interaction

between mood and attentional focus on insight problem solving ability. Together, these results

suggest that convergent thinking may play as substantial a role as divergent thinking in insight

problem solving. Moreover, at least in the realm of insight, mood does not act as a signal that

determines if a dominant attentional focus is acted upon or not. The paper concludes with

suggestions for future research, including a closer examination of the relationship between

motivational intensity, attentional scope, and insight.

Keywords: insight, problem solving, creativity, attention, mood


Mood, Attention, and the Aha! Moment

Life is full of ill-defined problems and our success in life largely depends on the ability to

recognize, restructure, and solve these problems. An ill-defined problem is a problem that

requires restructuring in order to arrive at its solution (DeYoung, Flanders, & Peterson, 2008).

Unlike well-defined problems, the path to solving an ill-defined problem is not clear from the

outset. Ill-defined problems can be as simple as deciding what a close relative would like for

Christmas (Hayes, 1989) or as complex as deciding where to construct a new building. In the

laboratory, researchers have used a variety of riddle-like problems to simulate the ill-defined

problems of real life. For instance, Maier’s (1931) two-string problem asks participants how they

would tie two strings hanging from the ceiling if the two strings were too far apart from one

another. The solution is to make a pendulum by attaching a heavy object to one string and

swinging it until it is close enough to be tied to the other. Ill-defined problems are often solved

by insight, a sudden “Aha!” moment that reveals the solution to the problem.

Insight has persisted as “one of the central questions of [the] psychology of thinking” in

this past century (Humphrey, 1963). Nevertheless, researchers have shown great variance on

how they define the concept. Some view insight as a thinking process (Mayer, 1992), as three

processes (Davidson, 1986; Davidson & Sternberg, 1986), as a knowledge state (Dominowski &

Dallob, 1995), as a moment of illumination (Westcott, 1961), or as the final phase in the problem

solving process (Bowers, Farvolden, & Mermigis, 1995). Some researchers even deny that

insight be considered a special construct in problem solving, arguing that it is merely part of

normative processes involved in perception and learning (Perkins, 1981; Weisberg, 1986;

Langley & Jones, 1988).


Among researchers who view insight as special, insight occurs when a problem is solved

through mental restructuring (Weisberg, 1995) by either redefining the goal or the givens of a

problem (Duncker, 1945). Additionally, it has been described as a “sudden realization” (Kaplan

& Simon, 1988; Kohler, 1956, 1969; Worthy, 1975) and an inexplicable “Aha!” or “Eureka”

moment (Metcalfe, 1986). Some researchers have also argued that insight occurs when we

overcome past experiences and knowledge that hinder our ability to solve a specific problem

(Duncker, 1945). Insight problem solving seems to be objectively different from algorithmic

problem solving. EEG recordings of individuals solving or preparing to solve problems show

heightened neural activity in the right anterior superior temporal gyrus (Bowden, Jung-Beeman,

Fleck, & Kounios, 2005) and the medial frontal areas of the brain (Kounios et al., 2006) prior to

solving insight but not non-insight problems.

Insight is closely linked to creativity. Like creative ideas, insightful solutions must be

novel and appropriate to a given problem (Dominowski, 1995). Dominowski (1995) argued that

insightful solutions are statistically less frequent than more dominant solutions. For instance,

insightful solutions often involve unusual uses of objects or a less dominant meaning of a word.

Additionally, insight problems require taking a new perspective to a problem and overcoming

convention, properties that are key to creativity.

An incredible amount of research has been dedicated to studying creativity, which has

been positively associated with extraversion (Cropley, 1999), moderate levels of evaluative

stress (Byron, Khazanchi, & Nazarian, 2010), mindfulness training (Ostafin & Kassman, 2012),

dim lighting conditions (Steidle & Werth, 2013), and mind wandering (Mooneyham & Schooler,

2013). Research linking mood to creativity has been especially abundant. Much of this research

supports the idea that positive affect enhances creativity relative to neutral and negative moods


(Baas, De Dreu, & Nijstad, 2008; Ashby, Isen, & Turken, 1999; Kaufmann, 2003; Davis, 2009).

For instance, individuals who viewed a comedy film were significantly more likely to solve an

insight problem and include atypical exemplars as part of a category compared to individuals

who viewed a neutral or negatively toned film (Isen, Daubman, & Nowicki, 1987). Moreover,

positive mood has been shown to facilitate idea generation (Isen, Labroo, & Durlach, 2004;

Murray, Sujan, Hirt, & Sujan, 1990) and the ability to make unusual word associations

(Sacharin, 2010). With regard to the impact of negative moods on creativity, findings have been

significantly less consistent. In a meta-analysis of 66 papers, Baas et al. (2008) found that, in

some studies, negative affect had a positive influence on creativity, while in others it had

negative or no effect.

In response to the strong link between positive moods and creativity, researchers have

offered several explanations. Fiedler (1990, 1991) suggests that positive and negative affect are

conducive to different thinking styles. Specifically, positive moods facilitate productive, top-

down thinking, while negative moods encourage an externally focused thinking style (Fiedler,

2000). Other researchers rely on the Affect-as-Information Model (Schwarz & Clore, 1983;

2007) to explain the benefits of positive mood on creativity. According to this model, moods

provide us with information about whether a situation is benign or problematic. Positive moods

signal that a situation is safe and encourage broad information processing, while negative moods

signal a problematic environment and facilitate more analytic processing (Frijda, 1988). The

Mood Behavior Model (Gendolla, 2000) provides a motivational explanation for the mood-

creativity link. In a positive mood state, we become motivated to maintain our pleasant affect by

relying on simple, heuristic processing strategies conducive to creativity. While in a negative


mood state, we increase our processing efforts in hopes of removing the aversive mood state

(Clark & Isen, 1982).

One of the more prominent explanations is that broadened attentional scope mediates the

creative benefits of positive affect. Attentional scope refers to “the number and range of stimuli

that a subject attends to at any one time” (Memmert, 2007, p. 281). In order to combine two or

more concepts in memory and create an innovative idea, these concepts must be within the focus

of attention (Martindale, 1995). Rowe, Hirsh, and Anderson (2007) found that positive mood

states reduce inhibitory control and increase the breadth of visual and conceptual attention. In

their study, listening to happy, as opposed to sad, music impaired participants’ ability to ignore

distractor letters, but enhanced access to remote associates of words from memory. Furthermore,

defocused attention has been shown to be a stable trait in creative people (Eysenck, 1995; Kasof,

1997; Mendelsohn, 1976). Attentional broadening training also seems to improve children’s

ability to employ original and creative strategies in team sports (Memmert, 2007).

Another view that has gained popularity in recent creativity research is that the

relationship between mood and creativity is not definite but is dependent on situational and

motivational factors. Davis (2009) provided support for this contextual view of mood-creativity

relations. In his review of 72 studies, the creative benefits of positive affect were greatest when

compared to neutral but not negative affect and when participants were unaware of the source of

their mood. Sacharin (2010) alludes to a similar point, suggesting that negative affect may

increase cognitive breadth under certain environmental conditions. Likewise, Baas et al. (2008)

argue that we cannot explain the relationship between mood and creativity as a function of

hedonic tone alone. In their meta-analysis, the researchers found that only activating positive


moods (i.e., happy), but not deactivating positive moods (i.e., relaxed), were associated with

higher levels of originality.

Recently, Huntsinger (2013) proposed an idea that follows the lead of the Affect-as-

Information Model and combines the concept of attentional focus with the contextual view of

mood-creativity relations. He challenges the existence of a fundamental difference between the

attentional consequences of positive and negative mood states. Instead, Huntsinger (2013)

proposes that affect acts as a “stop” or “go” signal that encourages us to either act upon on or run

counter of dominant attentional cues in the environment. According to Huntsinger, research has

generally found that positive affect enhances creativity because the default focus of attention is

global. Furthermore, this tendency to focus broadly is strengthened in experimental

environments (Clore & Huntsinger, 2007).

In a study by Huntsinger, Clore and Bar-Anan (2010), participants were primed with a

global focus of attention through a modified Navon (1977) letter task. Following this, they were

induced with either a happy or sad mood by writing about a personal life event or by listening to

music. Later, attentional scope was measured using a Kimchi task, in which participants were

asked to look at a target figure and choose, from two other figures, which looked most similar to

the target. When primed with a global focus of attention, people in happy moods chose more

globally similar figures and had a broader attentional scope compared to those in negative

moods. Conversely, when primed with a local focus of attention, people in happy moods chose

more locally similar figures and had a narrower attentional scope than those in sad moods.

Hence, the study showed that people in happy moods tended to adopt whichever scope of

attention was dominant, whereas those in sad moods tended to counter it.


Considering the everyday importance of creativity and insightful problem solving, the

purpose of the current study was to extend Huntsinger’s (2013) hypothesis to the ability to solve

insight problems. Participants in this study were first primed with either a global or local focus of

attention using a modified version of the Navon letter task. Following this, they were induced

with either a positive (i.e., happy) or negative (i.e., sad) mood state by watching a short video

clip. Participants in the neutral mood control group did not watch any video clips. Then,

participants were prompted to answer three insight problems and were compared on the ability to

answer these problems correctly.

Through this study, I hoped to determine if the flexible relationship between affect and

attentional focus would influence an individual’s ability to think creatively. In addition, this

study addressed a limitation of Huntsinger’s (2012) research by including a neutral mood control

to establish if global-local priming influences insight problem solving independent of an induced

mood. Three hypotheses emerged from this research

Hypothesis 1: Participants in a positive mood and primed with a global focus of attention

will solve more insight problems than participants in a positive mood who are primed

with a local focus of attention. This is because positive affect will enhance the use of

dominant global attentional cues in the environment, broaden the conceptual scope of

attention, and lead to greater creative thinking.

Hypothesis 2: Participants in a negative mood and primed with a global focus of

attention will solve fewer insight problems than participants in a negative mood who are

primed with a local focus of attention. This is because negative affect will inhibit the use

of dominant global attentional cues in the environment, narrow the scope of conceptual

attention, and lead to less creative thinking.


Hypothesis 3: Assuming that participants are in neither a positive nor negative mood, a

dominant global focus of attention will enhance the ability to solve insight problems,

compared to a dominant local focus of attention.

Method

Participants

Participants in this study were 68 undergraduate students (48 female, 20 male) at Linfield

College in McMinnville, Oregon. In return for participating, participants were entered in a raffle

to win a $15 gift card, as well as a separate raffle in the Psychology Department to win either

$100, $75, or $50 at the end of the year. Additionally, some participants received academic

credit. All participants indicated that they were above 18 years of age and had normal or

corrected-to-normal vision.

Design and Procedure

Participants were assigned to one of six experimental groups by block randomization.

Half of the groups was primed with a local focus of attention, while the other half was primed

with a global focus of attention during the experiment. The groups were further split into three

mood conditions that would either induce them with a positive affect, negative affect, or no

affect at all. After signing an informed consent form, participants sat down in front of a computer

monitor and keyboard. They were first asked to respond to two demographic questions about

their gender and age. Then, participants’ baseline positive and negative mood levels were

assessed using a modified version of Watson and Clark’s (1994) expanded Positive and Negative

Affect Schedule (PANAS-X), which is described below. Next, participants completed a variant

of the Navon (1977) letter task. Half of the participants was exposed to a version of the task that

primed them with a broad, global focus of attention, while the other half was exposed to a


version that primed them with a narrow, local focus of attention. In the next stage of the

experiment, participants in the positive and negative affect conditions were shown 2-min-45-

second video clips to induce amusement and sadness respectively. Participants in the neutral

affect condition proceeded immediately to the next task. For this next task, participants were

asked to complete three insight problems shown consecutively on the computer screen.

Participants were given up to 4 min to complete each question, after which they heard a low beep

sound and viewed the next question. Participants who arrived at a solution in less than 4 min

could choose to proceed to the next question by pressing on the keyboard. They recorded their

solutions in pen on blank sheets of paper that were provided to them at the beginning of the

experiment.

After seeing all three insight problems, participants responded once again to items on the

modified PANAS-X. In this mood assessment, participants were instructed to think about how

they felt during the experiment. This assessment served mainly as a manipulation check to

ensure that participants in the positive and negative affect conditions were induced with those

affective states. Finally, participants were thanked, debriefed about the experiment, and asked if

they had previously encountered any of the insight problems shown. Each participant received

solutions to the insight problems the following day via email.

Materials

Mood measurement. Participants’ levels of positive and negative affect before and after

the experiment were assessed using an abridged version of the PANAS-X (Watson & Clark,

1994). The PANAS-X is a 60-item questionnaire that measures self-reported affect on two

general dimension scales (i.e., positive and negative affect) and 11 specific affect scales. Watson

and Clark (1994) suggest that researchers facing time constraints select and assess only those


scales which are relevant to their research. Hence, I decided to assess only the basic negative

emotion scales (i.e., fear, hostility, guilt, sadness) and the basic positive emotion scales (i.e.,

joviality, self-assurance, attentiveness) as determined by the researchers. This modified version

of the PANAS-X contained 41 items total – 23 negative emotions and 18 positive emotions.

Participants were asked to rate on a scale of 1 (very slightly or not at all) to 5 (extremely) the

extent to which they were currently feeling each of the listed emotions. Participants’ negative

and positive mood levels were scored by summing the responses to the items in the basic

negative and basic positive emotion scales respectively.

Global-local focus priming. Participants in this study completed a variant of the Navon

letter task on the computer to prime them with either a global or local focus of attention. This

task was based on the version used in Huntsinger et al. (2010). On each trial, a figure was shown

on the screen. This figure was a composite letter – a large letter (5 cm x 5 cm) made up of

smaller black letters (1 cm x 1 cm) on a white background (see Figure 1 for examples of these

stimuli). Participants were instructed to press the “L” key if an “L” appeared in the figure or the

“H” key if an “H” appeared in the figure. A correct response was followed by the next stimulus

after a 250-ms delay, whereas an incorrect response was followed by a sharp beep and a 1250-ms

delay. Participants in the global priming condition encountered 120 trials with global-letter

targets and 30 trials with local-letter targets. Inversely, participants in the local priming condition

encountered 120 trials with local-letter targets and 30 trials with global-letter targets. Participants

were given 16 practice trials with even numbers of global-letter and local-letter targets prior to

beginning the experimental trials so that they could familiarize themselves with the task.

Mood induction. Video clips were used to induce participants with positive and negative

mood states. Participants in the positive affect condition watched a 2-min-45-s video clip from


the comedy improvisation show, Whose Line is It Anyway?. In this video clip, two of the show’s

actors act out a scene about a heavily pregnant woman who gives birth on a roller coaster. In the

negative affect condition, participants watched a video clip of the same length from the movie,

The Champ. This scene shows a young boy coming to terms with his father’s death and has been

cited as the most effective film clip for evoking sadness in a sample of 250 films and film clips

(Gross & Levenson, 1995).

Insight problems. The three insight problems that were shown to participants were

classified as pure insight problems by Weisberg (1995). Unlike hybrid insight problems,

Weisberg argued that pure insight problems can only be solved through restructuring. For

example, one of the problems asks participants how it is possible for a man to legally marry 20

women in one town without being polygamous. In order to solve this problem, participants must

restructure the problem and realize that it is possible for the man to preside over the marriage

ceremony of 20 women, hence “marrying” all of them. The exact problems used in this study and

their solutions are listed in the Appendix. To provide variety, I chose to present insight problems

from different categories. The first problem was a brainteaser, while the remaining problems

were related to geometry and mathematics.

Results

Each participant’s insight problem solving score was obtained by summing the number of

correct responses to the three insight problems. To calculate baseline positive and negative mood

levels, participant’s responses to the basic positive and negative emotion scales of the first

PANAS-X were summed. Similarly, participants’ final positive and negative mood levels were

calculated by summing their responses on the basic positive and negative emotion scales on the

second administration of the PANAS-X. Thus, each participant had four mood scores – baseline


positive mood, baseline negative mood, final positive mood, and final negative mood (see Table

1). A total of 17 participants were excluded from the analyses. Of these excluded participants,

four identified less than 80% of the target letters correctly on the Navon letter task and may not

have been successfully primed with a focus of attention. Another 13 participants were excluded

because they reported previously seeing one or more of the insight problems. Hence, a total of 51

participants (N = 51) were included in these analyses.

On average, participants were 96.93% accurate at identifying target letters in the Navon

letter task, suggesting that participants across all conditions were effectively primed with a

global or local focus of attention. However, an independent T-test showed that participants in the

local focus group were significantly more accurate at the Navon letter task (M = 97.87)

compared to participants in the global focus group (M = 95.95), F (1, 49) = 4.13, p = .024. In

terms of performance on each of the insight problems, 39% of the participants answered the first

problem correctly (i.e., brainteaser – “Marrying Man”), while only 6% of participants found the

solution to the second problem (i.e. geometrical problem – “Matchsticks”). On the other hand,

57% of participants solved the last problem (i.e. mathematical problem – “Horse Trading”; see

Appendix for complete problems and their solutions).

A one-way analysis of variance (ANOVA) was used to determine if participants differed

significantly in mood states across the different mood manipulation groups at the beginning of

the experiment. The analysis showed no significant differences in the baseline positive mood

scores, F(2, 48) = .53, p = .594, nor in the baseline negative mood scores, F(2, 48) = .20, p =

.820, across groups. However, the same ANOVA revealed that participants across the mood

manipulation groups also did not differ significantly in final positive mood scores, F(2, 48) =

2.20, p = .122, or final negative mood scores, F(2, 48) = 1.05, p = .36. Based on these results, it


seems that the mood induction methods were ineffective at producing a noticeable effect on

participants’ basic positive and negative moods.

These results prompted a closer examination of participants’ responses to specific

subscales in the PANAS-X. As noted earlier, the version of the PANAS-X that participants

completed in this experiment contained the basic positive and basic negative emotion scales,

which each contained a number of specific emotion subscales. Specifically, I looked at the

subscales for sadness and joviality, as these were the emotions that were the most relevant to the

mood manipulation and research goals. The sadness subscale contained five items (i.e., sad, blue,

downhearted, alone, lonely), while the joviality subscale contained eight items (i.e., cheerful,

happy, joyful, delighted, enthusiastic, excited, lively, energetic). After totaling participants’

responses to the sadness and joviality subscales (see Table 2), I used a one-way ANOVA to

determine if the mood groups differed on these subscales. It was found that the mood

manipulation groups differed significantly on their final sadness subscale scores, F(2, 48) = 3.54,

p = .037, but did not differ significantly on any of the other subscales. A post-hoc Scheffe test

revealed that participants in the negative mood condition had significantly higher final sadness

subscale scores (M = 8.88) compared to participants in the positive mood condition (M = 6.31), p

= .041. However, participants in the positive and negative mood conditions did not differ

significantly on the sadness subscale relative to the neutral mood controls (M = 7.22).

Additionally, joviality ratings were not significantly different across groups, neither at the

beginning nor at the end of the experiment. These findings suggest that the sad video clip in the

negative mood manipulation group may have been more effective at inducing a sad mood than

the funny video clip was at inducing a happy mood state.


To test this study’s hypotheses, a 2 x 3 (Attentional Focus [global, local] x Mood

[positive, neutral, negative]) univariate ANOVA was conducted. This ANOVA revealed only a

significant main effect of attentional scope on insight problem solving performance, F(1, 45) =

7.58, p = .008 (see Figure 2). Across mood conditions, participants who were primed with a local

focus of attention came up with significantly more solutions to the insight problems (M = 1.24)

compared to those who were primed with a global focus of attention (M = .76) (see Figure 3).

This finding seems to contradict past research, which suggests that a global attentional focus is

analogously related to broadened conceptual scope and enhanced creativity (e.g., Martindale,

1995; Kasof, 1997; Friedman, Fishbach, Förster, & Werth, 2003). Although there was no

significant main effect of mood on insight problem solving ability, F(2, 45) = 1.96, p = .152, post

hoc comparisons using the LSD test indicated that on average, participants in the neutral control

group solved significantly more insight problems (M = 1.18) than participants induced with a

negative mood (M = .77). Participants induced with a positive mood did not differ significantly

in performance compared to both of these groups (M = 1.06). There was no significant

interaction between attentional focus and mood, F(2, 45) = 1.27, p = .290, contrary to predictions

made based on the Mood-as-Information model.

One possible explanation why participants in the narrowed attention condition performed

better on the insight problems compared to participants in the broadened attention condition is

that the global-focus Navon letter task unintentionally made participants more frustrated. It is

possible that the global-target stimuli were more challenging for participants to respond to

because they were less straightforward than the local-target stimuli, which were composed of the

target letter. To investigate this possibility, I compared participants on their responses to items on

the hostility subscale of the PANAS-X’s basic negative emotions scale (see Table 2 for mean


final scores on the hostility subscale). A one-way ANOVA found that participants in all groups

did not differ significantly in initial, F(2, 48) = .34, p = .714, and final hostility levels, F(2, 48) =

.05, p = .953. Accuracy on the Navon letter task also did not affect the overall results of this

study. A univariate ANOVA controlling for accuracy on the Navon letter task showed only a

significant main effect of attentional scope on insight, F(1, 44) = 8.56, p = .005; participants

primed with a narrow scope of attention still solved significantly more insight problems (M =

1.28) than participants primed with a broad scope of attention (M = .74). Thus, these results

suggest that although participants in the global focus condition were less accurate at the Navon

letter task than those in the local focus condition, this had no impact on their insight problem

solving nor on their level of frustration.

Discussion

In this study, I hypothesized that there would be an interaction between mood state and

attentional focus on insight problem solving performance, consistent with Huntsinger’s (2013)

finding that moods influence whether or not a dominant attentional focus is acted upon.

Furthermore, I hypothesized that there would be no main effect of mood on insight as the impact

of mood on creative problem solving ability would be moderated by attentional focus.

Specifically, I predicted that participants induced with a positive mood would solve more insight

problems than participants induced with a negative mood or no mood, only if a global focus of

attention was primed. Inversely, participants in a negative mood would solve more insight

problems than participants in the other conditions if a local focus of attention was primed.

Although this study did not find a main effect for mood on insight problem solving ability, there

was no significant interaction between the mood and attention variables. Hence, these findings

do not seem to support the contention that moods act as “stop” or “go” signals, at least in the


realm of insight problem solving. A positive or negative mood neither inhibited nor facilitated

the use of dominant attentional cues and subsequently creative problem solving ability.

Instead, there was a significant main effect of attentional focus on overall insight problem

solving performance. On average, participants primed with a local focus of attention solved

significantly more insight problems than those primed with a global focus of attention regardless

of the mood condition they were in. Additionally, participants showed high accuracy on the

Navon letter task, providing support that they were effectively primed with a global or local

scope of attention. This finding contradicts past research, which has found that broadened, as

opposed to narrow, perceptual focus analogously leads to a broadened conceptual focus and

enhanced creativity.

There are several ways that these findings could be explained. First, it could be that

insight problem solving is not as closely related to creative or divergent thinking as previously

thought and may instead also require convergent and linear thinking abilities. Several researchers

have already raised this issue. DeYoung et al. (2008) found that abilities related to convergent

thinking, divergent thinking, and breaking frame (i.e., the ability to switch between categories)

contribute differentially to insight problem solving performance. They suggest that all forms of

problem solving rely on convergent thinking and logical operation, but that insight problems in

particular additionally require divergent thinking and the ability to switch between categories in

order for restructuring to occur. Future studies might include measures of divergent and

convergent thinking to clarify the relationship the mood, attentional scope, and these modes of

thinking.

Besides that, participants may not have been effectively induced with a mood state. Even

though the differences in final positive and negative mood between the mood conditions were in


the general expected direction, these differences did not reach significance. Upon closer

examination, participants in the negative mood condition scored significantly higher on the

sadness subscale of the PANAS-X at the end of the experiment compared to participants in the

positive mood condition. Participants did not differ on the sadness subscale at the beginning of

the experiment. This suggests that the negative mood manipulation was, at the very least,

effective at inducing feelings of sadness but not a general negative mood state. Nonetheless,

participants did not differ significantly on the joviality subscale of the PANAS-X neither at the

beginning nor at the end of the experiment, suggesting that the positive mood manipulation was

less effective at inducing a happy mood state.

Another potential explanation that was explored is that participants in the global focus

condition were more frustrated with the Navon letter task than the local focus participants and

this frustration may have reduced the effectiveness of the mood manipulation. The analyses

found that participants in the global focus condition were indeed significantly less accurate at the

Navon letter task than participants in the local focus condition. Nevertheless, there was no

significant difference between participants on the hostility subscale of the PANAS-X at the end

of the experiment. Furthermore, the overall results of the study remained unchanged even after

controlling for accuracy on the Navon letter task. Thus, although those in the global focus group

were less accurate at the Navon letter task than those in the local focus group, this did not seem

to make them any more frustrated or less insightful than the other participants.

Aside from that, these results might suggest that a mechanism besides emotional valence

determines the relationship between attentional scope and insight problem solving ability. In

other words, it may be that the positivity or negativity of an emotion does not directly influence

whether or not a dominant attentional scope is adopted. As mentioned earlier, Baas et al. (2008)


found that only activating, as opposed to deactivating, positive moods were associated with

higher levels of originality. Another group of researchers also proposed that visual and

conceptual attentional breadth is influenced not only by affective valence but also by

motivational intensity. Gable and Harmon-Jones (2011) found that, relative to neutral moods,

high approach-motivated positive moods narrowed attentional scope, whereas low approach-

motivated positive moods broadened it. Approach motivation was manipulated by varying the

possibility of earning a reward on a modified flanker task. The researchers then measured

attentional scope by using a modified Navon letter task. Overall, the study showed that high

approach-motivated positive states enhanced performance on local-target trials, while low

approach-motivated positive states enhanced performance on global-target trials. Because

sadness and happiness are states of low approach motivation (Gable & Harmon-Jones, 2010),

there may not have been differences between participants in the present study because they were

functionally equivalent on motivational intensity. Future research should be focused on exploring

this potential interaction between motivational intensity and attentional focus on creative

problem solving.

One of the limitations of this study was the mood manipulation. Past research has shown

that the mood-creativity relationship is strongest when participants are given a cover story along

with the mood induction (Davis, 2009). According to Davis (2009), the absence of a cover story

makes participants more aware of the source of their mood and less likely to use their mood state

as information to guide subsequent behaviors. The induced mood states also may not have

persisted throughout the experiment. In addition, the nature of the PANAS-X may have given

participants some clue of the purpose of the study and affected their responses. There was also a

floor effect for the second insight problem – only 6 % of participants in this study managed to


solve this problem within the time limit. I also express doubts about the use of the mathematical

problem as an insight problem (see “Horse Trading” in the Appendix). Most participants solved

this question correctly but this may have been because they were given too much time to work

on the problem. Furthermore, they had access to a pen and paper and could easily perform these

calculations on paper. I am doubtful that that this problem can only be solved through insight and

restructuring as it seems that there is a clear progression of steps to the solution. Apart from that,

this study also used only three insight problems, leaving little variability in insight problem

solving performance between participants.

In the future, thought should be given to using insight problems that do not require

calculations, using more insight problems to increase the variability in problem solving

performance, allowing participants less time to work on these problems, and using other

measures of creativity that can be administered in a shorter amount of time, such as Mednick’s

(1962) remote associates task (RAT). To potentially increase the effectiveness of the mood

manipulation, future research could integrate mood elicitation into the current task or use a

different method of inducing mood, such as listening to music throughout the problem solving

phase or writing an essay about a personal experience. Moreover, future studies should consider

assessing only the specific subscales of the PANAS-X that are most relevant to the mood

manipulations, as the basic positive and negative emotions scales may not be sensitive to

changes in specific mood states.

In conclusion, insight remains at the center of controversy as it has been since it was

introduced by Gestalt psychologists more than 75 years ago (Weisberg, 1975). Overall, this study

suggests that Huntsinger’s (2013) hypothesis may not extend to insight problem solving. As a

whole, this study contributes to our understanding of insight and may indicate that insight


problem solving depends equally on convergent and divergent thinking abilities. It also serves as

a starting point for future research into the impact of motivational intensity on conceptual scope

and creative problem solving. In short, psychologists should continue to study insight and how it

is different from and similar to general problem-solving abilities. By enhancing our

understanding of the elusive concept of insight, we will be closer to uncovering the processes

behind innovative thinking that are so integral to the development of technology and society

today.


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Table 1

Mean Baseline and Final Scores on the Basic Positive and Negative Emotions Scales of the

PANAS-X

Mood

Attentional

focus n

Basic positive emotion Basic negative emotion

Baseline Final Baseline Final

M SD M SD M SD M SD

Positive Global 8 60.38 8.80 59.00 10.98 32.75 6.36 28.25 4.68

Local 8 56.00 9.29 50.63 12.25 33.63 9.68 31.50 6.78

Neutral Global 8 57.25 13.68 45.13 9.05 31.25 4.27 30.13 6.62

Local 10 54.80 6.43 47.50 8.48 36.50 17.69 35.80 16.67

Negative Global 9 50.89 11.12 46.56 14.88 37.33 9.50 36.67 6.93

Local 8 58.63 11.67 50.29 11.91 34.29 10.26 32.63 9.55


Table 2

Mean Final Scores on the Sadness, Joviality, and Hostility Subscales of the PANAS-X

Mood

Attentional

focus n

Sadness Joviality

Hostility

M SD M SD

M SD

Positive Global 8 5.87 1.46 27.00 4.67

7.13 1.55

Local 8 6.75 1.67 20.88 5.06

8.00 1.69

Neutral Global 8 6.50 2.14 20.75 6.63

7.00 1.20

Local 10 7.80 4.34 19.80 5.14

7.60 3.37

Negative Global 9 9.33 3.12 19.44 8.71

8.22 2.64

Local 8 8.38 2.77 23.38 6.52

6.63 .92


Figure 1. Example stimuli used in the modified Navon letter task. The target letters, “L” and

“H”, make up the larger letter in the global-target figures and the smaller letters in the local-

target figures.

Local-target figures

Global-target figures


Figure 2. Estimated marginal means of insight problem solving scores as a function of mood and

attentional focus.

0.0

0.5

1.0

1.5

2.0

Neutral Positive Negative

Mood

Local

Global

Est

imate

d M

arg

inal

Mean

s of

Insi

gh

t S

core

s


Figure 3. Estimated marginal means of insight problem solving scores (±SE) across participants

primed with a global (n = 25) and local focus of attention (n = 26). p < .01.

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

Est

imate

d M

arg

inal

Mea

ns

of

Insi

gh

t S

core

s

Local Global

Attentional Focus


Appendix

The following pure insight problems were adapted from Weisberg (1995, p. 192-193) and used

in this study.

Marrying man: A man in a town married 20 women in the town. He and the women are still

alive, and he has had no divorces. He is not a bigamist and is not a Mormon and yet he broke

now law. How is that possible?

Solution: The man is a minister who married the women and their husbands.

Matchsticks: Using six matches, make four equilateral triangles, with one complete match

making up the side of each triangle.

Solution: Tetrahedron (a triangular-based pyramid).

Horse trading: A man bought a horse for $60 and sold it later for $70. Then he bought it back

for $80 and sold it for $90. How much did he make in the horse trading business?

Solution: Made $20 ($10 profit on each sale).

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