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The Influence of Cognitive Structure and Task Structure on Creativity in a Military Context.


Like many organisations today, military forces face an ever-evolving stream of new challenges, and as a result, require their personnel to be adaptive and innovative. In fact, a recent former Australian Chief of Air Force, highlighted the need for the Royal Australian Air Force (RAAF) to "develop an innovative and empowered workforce" (Brown, 2015). Innovation is the exploitation of creative ideas (D. H. Cropley, 2009), and it is important to understand that innovation cannot exist without creativity. Problematically, however, the military requires rules, boundaries and norm-compliance, which are seen to be incompatible with the norm-breaking required for creativity. As a result, there are some who believe that this dependence on structure holds the military back from fostering creativity in its personnel, and hence, from being a truly innovative organization (Price, 2013; Vego, 2013). However, before accepting this conclusion, it is important to understand the type of people who work in military forces, and whether or not boundaries and structure influence their creativity.

A number of studies have explored specific factors believed to influence creativity in a military sample. These include time pressure (Kayaalp, 2014), divergent thinking (Vincent, Decker, & Mumford, 2002), service priming in cadets (i.e., imagining a career in a specific service) (Chiu & Tu, 2014), and loyalty to rules (Kirkhaug, 2011). Furthermore, previous studies have also found evidence to suggest that there may be creativity differences between military personnel and civilian populations. For example, a study conducted by Clark (2008) found that officers attending the Joint and Combined Warfighter School in Norfolk, VA, had slightly below average figural (i.e., drawing) creativity based on normative data, but above average verbal creativity. Johnson (2003) also found that military leaders had more adaptive cognitive styles than civilian leaders, suggesting that when it comes to creative problem solving, military leaders prefer to "do things better", compared to civilian leaders who prefer to "do things differently" (see Kirton, 1976, p. 622 for a summary of behvaiour descriptions of adaptors and innovators). It is important to note, however, that this study measured creativity style rather than level. Both of these studies suggest that there may be something specific in the way that military personnel think that influences their creativity.

One possibility is that those in the military have a different Personal Need for Structure (PNS). PNS can be thought of as a cognitive style (Kemmelmeier, 2010), which is viewed as the overlap between personality and cognition, implying a disposition (based on personality) to process information in a particular way (Martinsen, Kaufmann, & Furnham, 2011). Importantly, cognitive styles reflect the how to of cognition, rather than the how well that is associated with cognitive ability.

The PNS scale has been shown to be relevant in a military sample, and has been used to examine soldiers' perceptions of situations (Parmak, Mylle, & Euwema, 2013), the influence of death-threat (the awareness of the risk of death associated with their duties) on thoughts (van den Berg & Soeters, 2009) and behavior before and after operational deployment (Parmak, Euwema, & Mylle, 2012). Individuals high in PNS are likely to organize information in simple ways, have a high preference for routine and possess an intolerance of ambiguity (Neuberg & Newsom, 1993). They can be characterized as "decisive and confident" (Thompson, Naccarato, Parker, & Moskowitz, 2001, p. 20), and are more likely to show a preference for authoritarianism (Jugert, Cohrs, & Duckitt, 2009). There is speculation that military organizations are attractive to people of this nature (Jackson, Thoemmes, Jonkmann, Ludtke, & Trautwein, 2012; Parmak et al., 2013), however, to date no studies have explored whether or not a high PNS is more generally related to military service. Furthermore, the PNS scale is considered to be an undervalued tool of personality assessment in this context (Parmak et al., 2013).

Importantly, PNS has been shown to influence creativity (Rietzschel, Slijkhuis, & Van Yperen, 2014; Slijkhuis, Rietzschel, & Van Yperen, 2013). Given that creativity requires novelty, it is intuitive to assume that creativity might not be produced by a mindset that requires structure and clarity. In fact, openness to experience is one personality facet that has been found consistently to be positively correlated with creativity (Batey & Furnham, 2006; Furnham, Batey, Booth, Patel, & Lozinskaya, 2011; McCrae, 1987) but negatively correlated with PNS (Landau et al., 2004; Neuberg & Newsom, 1993). Additionally, researchers have long suggested that a tolerance of ambiguity is a trait associated with creative individuals (A. J. Cropley, 2001; Dacey, 1989), but not with individuals high in PNS (Neuberg & Newsom, 1993). However, the internally imposed structure of an individual (i.e., their cognitive style) is just one facet of the creativity problem. It is also important to understand how structure and boundaries (i.e., externally imposed structure) impact creativity.

Studies are revealing that the way a problem or task is presented influences the creativity of the solution, and that externally imposed structure can actually enhance creativity. Research conducted by Goldenberg, Mazursky, and Solmon (1999) found that when participants were asked to think about existing products in a structured or compartmentalized way (e.g., in terms of features and functions), their suggested improvements for those products were rated as more original and valuable. Sagiv, Arieli, Goldenberg, and Goldschmidt (2010) also found evidence suggesting that a higher-structure task enhanced creativity. In that study, participants were presented with either a form-first (often referred to as function follows form) task or a function-first (often referred to as form follows function) task. The form-first task represents a scenario in which the solution is given (e.g., a brick) and a problem appropriate to that solution must be found (e.g., something you could build a house with; a way to stop papers blowing away; a way to tenderize meat, etc.). Conversely the function-first task presents a problem (e.g., something you could use to build a house) to which a solution must be found (e.g., bricks, compacted ice, seashells, etc.).

The form-first task is deemed to be more structured because, in this condition, the emphasis is on the form (i.e., the brick), which can only be the solution to a finite number of problems. That is, because the possible functions of the form are intrinsically linked to the form itself, there are fewer potential problems the form could solve, and the task is more structured because of its restrictive nature. Conversely, in the function-first task, the emphasis is on the function (i.e., providing shelter), which is not intrinsically linked to any specific form and, therefore, could be fulfilled by an almost infinite number of forms. It is deemed less structured because there is more freedom for selecting solutions. Somewhat counter-intuitively, Sagiv et al. (2010) found that, overall, participants performed more creatively on the high-structure, form-first problem. This was particularly true for those who analyzed information in a systematic way.

Supporting this, it has been found that when high PNS participants are given what they demand cognitively (i.e., a higher-structure task), they perform more creatively than when they are given are lower-structure task. Rietzschel et al. (2014) found that high PNS participants who were given an alien drawing task produced more creative sketches, judged on originality, when they were also given a step-by-step plan. However, for participants low in PNS, there were no differences in creativity between those who received instructions and those who did not. Comparably, Slijkhuis et al. (2013) found that when participants were told that they were expected to perform creatively on a task (i.e., the instructions were disambiguating and somewhat controlling), those low in PNS performed less creatively than the control group who were merely given informational (advisory rather than commanding) instructions. However, those high in PNS performed equally creatively in both conditions and the researchers concluded that this was because high PNS individuals simply prefer the disambiguating effect of receiving clear information, even when it is interpreted as controlling. Relatedly, individuals high in PNS prefer task-orientated leaders, who provide high but realistic goals (Ehrhart & Klein, 2001). While it might be concluded that the military is attractive to people of this nature, there is also some evidence to suggest that military service might be playing a causal role in personality development.

Although there has been little longitudinal research of personalities in military organizations, one recent study (Jackson et al., 2012) compared German adult males who undertook either a compulsory nine-month service in the military or a community service program. It was found that those who undertook military service showed significantly lower scores on agreeableness compared to their civilian counterparts, even five years after their completion of service. Jackson et al. (2012) concluded this might be because lower levels of agreeableness are beneficial in military setting, showing an adaptability of personality traits. These changes are in line with the maturity principle, which asserts that personality changes occur in young adulthood as part of maturation (Ludtke, Trautwein, & Husemann, 2009; Vaidya, Gray, Haig, Mroczek, & Watson, 2008). However, what is significant about these findings is that the maturation of personality was found to be different between military and civilian samples. Given that PNS is a thinking-style based on personality, it is possible that there might also be changes in this construct for those who are exposed to an environment that demands structure and order, such as the military, for a longer period of time.

The present study aimed to investigate the relationship between military service and cognitive style, how task structure influences creativity in the military, and if this relationship is impacted by length of time served. It also aimed to investigate the relationship between individual creative potential and product creativity, and if this is influenced by cognitive style. Therefore, it was hypothesized that PNS would be positively related to time served (hypothesis 1). It was also hypothesized that military personnel would perform more creatively on higher-structure tasks than lower-structure tasks (hypothesis 2), and that a higher-structure task would result in higher product creativity for those who have served longer (hypothesis 3). Individual creative potential was hypothesized to relate positively to product creativity (hypothesis 4), however, it was expected that PNS would moderate this relationship (hypothesis 5).



Volunteers were recruited from personnel within a single RAAF base. The population in question consists of approximately 850 uniformed personnel with various occupations including technical, clerical, logistical, engineering and systems operators. A total of 77 RAAF personnel volunteered to participated in the research (20 females). The minimum amount of time served by participants was one year and the maximum was 33 years ([M.sub.time_served] = 12.6 years, SD = 7.6). This includes any discontinuous service (i.e., leaving and re-joining), or any previous service with other non-Australian militaries. In the current study, all personnel were aged between 18 and 60. There were 38 and 39 participants in the higher- and lower-structure conditions respectively.


This study used a quasi-experimental, correlational design. Participants were randomly assigned to either a higher- or lower-structure task condition to determine the effect of task structure (independent variable) on product creativity (dependent variable). Three further independent variables were also measured: individual creative potential, time served and PNS.


Individual Creative Potential. Creative potential was measured using the Test for Creative Thinking--Drawing Production (TCT-DP) as this measure is seen to be a more holistic assessment of creativity. Rather than assessing only divergent thinking, which is common in many creativity tests, the TCT-DP also assesses mental risk-taking, unconventionality, and humour, and as a result, the test is suited to identifying creative potential in both children and adults (Urban, 2005).

Participants are asked to finish an incomplete drawing in any way they choose, based on six figural fragments: a large square or "frame", a smaller square outside of the frame, and four fragments within the frame. Creativity is then measured on 14 factors, including continuation or completion of fragments, drawing new elements, connecting figures or fragments, using a theme, boundary breaking (drawing outside of the frame), using perspective, and expressing humour, emotion or unconventionality. Inter-rater reliability for scores often measure above r = .87 (Urban, 2005). For the current study, the Intraclass Correlation Coefficient (ICC; two-way random, consistency) was .97 for the two independent raters, which reflects substantial agreement.

Personal need for structure (PNS). PNS was measured using the 12-item questionnaire developed by Neuberg and Newsom (1993). This scale measures respondents' preference for simple structure, clarity and routine, and is comprised of two factors: Desire For Structure (DFS; questions 3, 4, 6 and 10) and Response to a Lack of Structure (RLS). Due to known social desirability effects, item-5 was dropped from the final analysis as per Neuberg and Newsom's suggestion (Neuberg & Newsom, 1993). Participants rated their agreement with items such as "I don't like situations that are uncertain" and "I enjoy having a clear and structured mode of life" on a 6-point, Likert-type scale (1 = strongly disagree; 6 = strongly agree). Higher scores indicate a greater PNS. This scale has been found to have an internal reliability estimate between .76 and .86 (Neuberg & Newsom, 1993), and in the current study a = .80.

Big Five Inventory--10 item (BFI-10). Personality was assessed across five dimensions (openness, conscientiousness, extraversion, agreeableness and neuroticism) using the Big Five Inventory--10 item (BFI-10) (Rammstedt & John, 2007) and allowed for verification of previously found relationships between personality, creativity, and PNS. Each dimension is assessed with two questions, and participants rate their agreement with statements such as "I see myself as someone who is reserved" on 5-point, Likerttype scale (1 = disagree strongly, 5 = agree strongly). A higher score on each dimension indicates a stronger expression of that trait. The BFI-10 has a mean, partwhole correlation with the 44-item test (BFI-44) of r = .83, and has the added benefit of a short administration time.

Product Creativity. Product creativity was assessed based on the performance on one of two types of tasks: higher-structure (form-first) or lower-structure (function-first). Each participant was assigned randomly to one of these conditions and was given three problems for which they were asked to provide creative solutions. The higher- and lower-structure problems were reciprocals of each other such that the forms presented in the high-structure could fulfil the functions presented in the lower-structure condition, and vice-versa. For example, one lower-structure task asked participants to solve the problem of military personnel slipping on ships, while the higher-structure equivalent asked participants to find a possible function for high-grip boots (see Appendix A).

Three experienced military supervisors were asked to rate independently the solutions to each of the three problems according to three criteria: (1) the effectiveness of the solutions; (2) the unusualness of the solutions; and (3) the overall creativity of the solutions - each scored on a scale of 0 to 4 (0 = not at all; 4 = very). It should be noted that, at a minimum, product creativity is defined as something that is both novel and effective (Sternberg & Lubart, 1999), thus, the criterion of creativity should encompass the other two criteria (correlation analyses confirmed this relationship). The raters were trained together and were provided with a brief explanation of effectiveness (e.g., "will the solution work?") and unusualness (e.g., "how surprising is the solution?"), however, they were asked to assess overall creativity according to their own criteria. This method of utilising independent domain experts to judge creative products is known as the Consensual Assessment Technique (CAT) (Amabile, 1982) and is used widely in creativity research because of its high degree of ecological validity (for a summary see Hennessey, Amabile, & Mueller, 2011).

Consequently, each judge provided nine scores for each participant: a single score each for effectiveness, unusualness, and creativity, for problems A, B, and C. The intraclass correlation coefficient (ICC; two-way random, consistency) was used to measure agreement between judges across the three problems. The coefficients for creativity scores were .71, .78 and .67 for problems A, B, and C respectively, reflecting good agreement between judges, however, for both the effectiveness and unusualness scores, agreement was only marginally acceptable (as low as .55) (Cicchetti, 1994). Therefore, it was deemed appropriate to use only the creativity scores for the final analyses. Creativity scores were then averaged across the three judges such that each participant received three creativity scores (one for each problem A, B, and C) that were used in the final analyses.


Data collection occurred in two locations, across multiple sessions, with varying numbers of participants in each session (usually between three and ten). Participants were briefed on the purpose of the study, and what would be required of them. After giving their consent, the instructions for both the TCT-DP and the questionnaire booklet were then read aloud, and participants were asked to complete the TCT-DP first. Participants were also directed to cover each test booklet with the instruction sheet provided, in order to maintain complete anonymity when returning the tests. Given that there was no deception in the testing, participants were welcome to leave once they had completed the testing, however, all participants were invited to provide an email address in order to enter a draw for one of three $100 gift vouchers, and to receive a summary of results.


Participant scores were entered into SPSS v20, and were screened for missing data, outliers and normality. A single score was missing for one PNS question, and one conscientiousness question, which were each replaced with the variable mean. Removing these cases from the analysis would have reduced an already small sample size, and it was deemed that this method would not distort the results, particularly given that the PNS item is one of several others in the test used to determine the overall PNS score. All independent variables were normally distributed and without outliers, however, the creativity scores for problems A, B, and C were positively skewed and kurtosed. Transformations were unable to achieve normality, and therefore, all analyses were performed using the bootstrap method in SPSS (based on 1000 bootstrap samples). This method was deemed appropriate because the bootstrap procedure is distribution independent, and is achieved by estimating the sampling distribution based on the inferred population, taken from hundreds of samples within the sample data (see Ader, Ader, & Mellenbergh, 2008). This method can also account for distortions that might be caused by a small sample size. Table 1 shows Pearson correlations and descriptive statistics for key variables used in the study.

Turning to the hypotheses, an analysis of the correlation between Time Served and PNS (see Table 1) revealed no significant relationship between these two variables. However, a small but significant negative relationship was found between Time Served and the DFS subscale of PNS, r = -.19, p = .05 (one-tailed). It was predicted that the relationship between Time Served and PNS would be positive, and therefore, hypothesis 1 was not supported.

In order to test the hypotheses that military personnel would perform more creatively on the higher-structure task than on the lower-structure task (hypothesis 2), and that those who had served longer would perform better on the higher-structure task than on the lower-structure task (hypothesis 3), a regression analysis was run on creativity scores for each of the three problems. The predictor variables--task structure (coded lower-structure = -1 and higher-structure = 1), time served (centred; [+ or -] 1 SD), and the interaction between these--yielded non-significant main and interaction effects across all three problems (see Table 2). Therefore, both hypotheses 2 and 3 were not supported.

To test hypotheses 4 and 5 the data set was split into two conditions. This meant that the relationship between individual creative potential and product creativity, and the hypothesized moderation effect of PNS, could be determined for the higher- and lower-structure conditions independently. The lower-structure condition consisted of creativity scores for participants who had completed the lower-structure task (n = 39) and the higher-structure condition consisted of creativity scores for participants who had completed the higher-structure task (n = 38). To test the hypothesis that individual creative potential is positively related to product creativity, correlations between TCT-DP scores and the three product creativity scores were analysed (see Table 3). In the higher-structure condition, creative potential showed a significant and moderate, positive correlation to product creativity, only on Problem A, r = .31, p = .03 (one-tailed). However, in the lower-structure condition, a significant and moderate, positive correlation between creative potential and product creativity was found for Problem B, r = .31, p = .03 (one-tailed), and a similar relationship was also close to significance for Problem A, r = .24, p = .07 (one-tailed). Thus, partial support was found for hypothesis 4 -that individual creative potential is positively related to product creativity--however, this relationship appeared to be more prevalent in the lower-structure condition (i.e., it occurred in more than one problem). It should be noted that Problem C in the lower-structure condition was not significantly correlated with any other creativity measure, suggesting the influence of other factors on these scores, and hence, cannot be interpreted in the same way as the other two problems.

To test the prediction that the relationship between individual creative potential and product creativity would be moderated by PNS (hypothesis 5), a linear regression was performed on product creativity scores across each of the three problems, for both the higher- and lower-structure tasks. PNS (centred; [+ or -] 1 SD), TCT-DP (centred; [+ or -] 1 SD), and their interaction were entered as predictor variables. For Problem A, in the lower-structure condition, there was a significant interaction effect between creative potential (TCT-DP) and PNS (B = .04, SE = .12, t = 3.79, p = .03). A similar effect was also found for Problem B (B = .04, SE = .02, t = 2.72, p = .01; see Figure 1). The models explained 33.2% and 26.1% of the variance in product creativity scores, for problems A and B respectively, in the lower-structure condition. The regression analysis on Problem C revealed no significant main or interaction effects for the lower-structure condition.

In the higher-structure condition, an interaction effect for individual creative potential and PNS was observed only for Problem B (B = .04, SE = .02, t = 2.64, p = .01; see Table 4 and Figure 2). In problems A and C, main effects for PNS approached, but did not reach, significance (B = -.35, SE = .23, t = -1.61, p = .11; B = -.23, SE = .16, t = -1.30, p = .10 respectively). Additionally, the regression model did not approach significance for Problem C suggesting that other factors were influencing product creativity on this problem. Therefore, partial support was found for hypothesis 5 however, as with hypothesis 4, this effect was more stable in the low-structure condition than the high-structure condition.


The first hypothesis predicted that PNS would be positively related to length of time served in the military, however, a negative relationship was found between the desire for structure (DFS) subscale of PNS and time served. This finding suggests that the longer military personnel serve, the less they desire order and routine. While this is counter-intuitive, it does not contradict the current literature. Given that military service entails order, structure and discipline, there is speculation that it is appealing to people with traits congruent with this (Jackson et al., 2012; Parmak et al., 2013), however, military service also requires adaptability. Personnel are often required to work irregular shifts, move locations, update skill sets, and perform effectively in environments that might be unpredictable. Thus, it is possible that as military personnel become more adaptable throughout their careers, their desire for structure decreases. This is partially supported by research conducted by Parmak et al. (2012) who found that military personnel who scored at the extreme ends of the PNS scale before a 6-month operational deployment to Afghanistan, scored towards a moderate level on PNS one week after their return. Although the researchers concluded that this was likely to be a state (rather than a trait) effect, it does suggest that certain military experiences impact this cognitive style. Additionally, there is little evidence to suggest that this cognitive style is related to age. In a study specifically looking for age-related influences on PNS, Hess (2001) concluded that there was no evidence of normative age differences in PNS. This provides further support for the assertion that DFS decreases with length of service, rather than the close correlate of age.

Relatedly, an analysis of the third hypothesis revealed that time served was not found to impact product creativity, however, a positive relationship between time served and creative potential approached significance (r = .18, p = .07, one-tailed). This is of interest given that there are no documented normative age differences for adults on the TCT-DP (Urban & Jellen, 2010). However, if adaptability is increasing in individual military personnel over the period of their service (as reflected in the negative correlation between DFS and Time Served), then this would be congruent with the current literature which asserts that traits of flexibility and adaptability are conducive to creativity (Davis, 2011; Feist & Barron, 2003), and hence, we may also expect an improvement in creative potential in military personnel with time served.

The current study found that there were no differences between creativity scores on higher- and lower-structure tasks, leaving the second hypothesis without support. This is contrary to findings made by Sagiv et al. (2010), who found that creativity scores were higher when participants were presented with a higher-structure (form-first) task than when presented with a lower-structure (function-first) task. Given that the tasks in the present study were adaptations of those by Sagiv et al. (2010), modified to create military-centric tasks, it is possible that these adaptations influenced the results. More specifically, it is likely that the higher-structure task was overly constrained, and therefore both tasks produced the same level of creativity.

This constraint could be explained by examining the associative theory of creativity. This theory posits that creativity is enhanced when unusual and/or appropriate combinations between uncommon responses to stimuli are formed, while uncreative responses are those that are stereotypical, or conventional (Mednick, 1962). Creative individuals are said respond to stimuli in equally stereotypical ways compared to less creative individuals, but will then move on to suggests more unusual responses because they have a flatter hierarchy of associations e.g., when presented with the word "table", they will think of "chair" but then also "leg" and "food" (for a summary see Fairweather, 2011). An important part of this theory highlights that the final solution to a problem is selected because it achieves the closest fit with the problem requirements (Mednick, 1962). In other words, when creative people are presented with a problem, they initially think of stereotypical responses, but will then think of more unusual responses, and select their final answer based on how well it meets the criteria of the problem. However, it is conceivable that if the task is highly constrained, the problem solver may find it difficult to move away from stereotypical responses in order to meet the requirements of the problem. For example, in the current study, one problem asked participants to come up with a creative military use for electrifying mesh that produces a safe shock. Given that the requirement was for the solution to be useful in the military, it is perhaps unsurprising that most responses focused on security deterrents, and few participants responded with more active, or offensive functions, such as using the mesh as a net for catching fish during field exercises. Importantly, this effect is more likely to occur in the higher-structure (form-first) task because the solution (or form) is provided first, and it is easier to make conventional associations about what a particular form normally does. Conversely, the associations between a function (e.g., holding water) and the potential forms that could fulfill that function (e.g., a glass, a tin can, a plastic bag) are less strong. As a result, the higher-structure task in this study did not enhance creativity above the lower-structure task, because the constraint was twofold: constraint imposed by the task and constraint imposed by the context.

Similarly, as predicted in hypothesis 4, it would be expected that individual creative potential would predict product creativity, however, this was found to be the case only in the lower-structure condition and only for a single problem (i.e., Problem A) in the higher-structure condition. This provides further support for the assertion that the higher-structure tasks were overly constraining and resulted in stereotypical thinking, even for creative individuals. However, given that Problem A in the higher-structure condition was related to creative potential, this suggests that there is something different about this specific task. This problem asks participants to think of a creative way to use the surrounding vegetation on a field exercise, and is a scenario that military personnel are highly familiar with, given their training. It is possible that because of familiarity, participants were able to overcome their stereotypical responses. This fits with the assertion of associative theory that respondents with more information about the stimulus will give more creative responses (see Fairweather, 2011; Mednick, 1962). Therefore, it might be concluded that individual creative potential was related to product creativity when the task was not overly constraining, or when participants had deeper knowledge of the subject matter and could overcome this constraint.

PNS was found also to moderate the relationship between individual creative potential and product creativity, as predicted in hypothesis 5. In the lower-structure condition it was found that, regardless of creative potential, those with low PNS displayed similar levels of product creativity. However, for those high in PNS, creative potential was a strong predictor of product creativity such that those with high creative potential had much higher levels of product creativity than those with low creative potential. This suggests a perceived similarity between these two tasks for those high in PNS. It is quite possible, considering that the TCT-DP is an unconstrained task (participants are told to draw whatever they wish) and the lower-structure task also is somewhat unconstrained, that those high in PNS interpreted both tasks as unstructured. In fact, it has been found that those high in PNS are more likely than those with a low PNS to interpret unclear situations (lacking instructions and predictability) as unstructured (Parmak et al., 2013). This may explain why, for those high in PNS, the relationship between the two tasks was strong but for those low in PNS, creative potential did not relate to product creativity.

In the higher-structure condition, generally speaking, those with high PNS displayed lower levels of product creativity than those with low PNS, although this effect was only significant for Problem B (Problems A and C approached significance for this main effect). This is contrary to the current literature, which asserts that high PNS participants should perform as well as low PNS participants on structured tasks (Rietzschel et al., 2014; see also Sagiv et al., 2010), however, this might be due to the over constraint in the higher-structure condition. It has been shown that high PNS individuals are more likely than low PNS individuals to think in stereotypical ways (Neuberg & Newsom, 1993; Schaller, Boyd, Yohannes, & O'Brien, 1995), and thus, if the higher-structure task encourages stereotypical thought because of over constraint, those with a high PNS would be more likely to produce conventional and less creative responses. This suggests that not all types of constraint will lead to greater creativity.

One of the implications from the findings surrounding task constraint, particularly in an organizational context, is that care should be taken not to present problems to employees in such a way that encourages stereotypical thinking, and this is especially true for those high in PNS, who are predisposed to this type of thinking. Problem presentation should avoid directing the solver's thought to a particular solution or, in other words, should be "solution-neutral" (Dieter & Schmidt, 2012, p. 225), allowing for abstract thinking and enhancing the possibility of creative solutions. However, future research should verify the delineation between a higher-structure task that is conducive to creativity and one that is too constraining.

Another important implication of the current research is that if a longer military career is associated with improved mental flexibility, then it might be beneficial for organizational innovation that those who have served longer hold positions where creative thinking is required (e.g., logistics, instructing, etc.). In fact, evidence suggests that this might be part of natural career progression given that it has been observed that as personnel move into more senior positions, they score higher on creative problem solving skills (Mumford, Marks, Connelly, Zaccaro, & Reiter-Palmon, 2000). However, it should be noted that a longer career may not necessarily cause more mental adaptability in personnel, and it could be the case that those with a high desire for routine and order simply leave the military because the mental adaptability and flexibility required for military service does not suit their cognitive style. Future research should explore personality and cognitive style differences between military and civilian samples, and the mechanisms that may facilitate potential changes due to military service, as suggested by Jackson et al. (2012). This should also be explored in the context of creativity.

An important consideration when interpreting the results from the current study is that Sagiv et al. (2010) (the study from which the form-first/function-first tasks were adapted) conceptualized cognitive styles - in relation to creativity and task structure--in a slightly different manner. Instead of having participants rate their PNS, the researchers asked participants to rate themselves on the Thinking and Working Style Scale (see Sagiv et al., 2010) as either systematic or intuitive. In the context of creativity, a systematic individual will suggest conventional solutions because they follow regular methods and processes, which is similar to an individual high in PNS. Conversely, an intuitive individual might be seen as similar to someone with a low PNS because they are able to link various areas of thought due to a flatter hierarchy of associations. Therefore, although individuals high or low in PNS could be thought of as systematic or intuitive in the context of creativity, these constructs likely differ, and this may explain the incongruent results between their findings and that of the current study.

Another limitation was that this study did not analyze job roles. This may be relevant to the discussion of creativity and task structure given that a recent study found that cognitive fixation (i.e., an inability to break away from spontaneously activated ideas) was more likely to occur and constrain creative problem solving in engineers than in industrial designers (Agogue, Le Masson, Dalmasso, Houde, & Cassotti, 2015). Thus, we might also expect that the influence of task constraint may differ between those with different types of training or, perhaps even differ between branches of the military (i.e., Army, Navy and Air Force) given the variations in training and culture between these three services. Therefore, because the current sample consisted of Air Force personnel only, a further limitation is that the results may not be generalizable to other branches of military organizations.

Although a strength of this study was that the sample was drawn from the population of interest, military personnel have little experience participating in psychological research, and may have interpreted the process as ambiguous. Given that tolerance of ambiguity has been known to influence creativity (Zenasni, Besancon, & Lubart, 2008), it is possible that the ambiguity of the process influenced the participants' creativity and may also explain why these results differ somewhat from the current literature. Therefore, future research should aim to study creativity in serving military personnel in a more naturalistic setting. A further strength was that the judges used to assess solutions were experienced supervisors in the RAAF and, as domain experts, possess substantial knowledge of the subject area. However, this can also be a limitation as their judgments might be bound by the conventions of the field and less open to truly novel ideas.


The current study found that time served in the military was negatively correlated with DFS, suggesting that a longer career in the military might be associated with an increase in mental adaptability. This finding is likely to be relevant to the organizational structure of the military, where it might be appropriate to place longer serving and more mentally adaptable personnel in positions where creative thinking is required. The current study also found that a higher-structure task did not increase creativity over a lower-structure task in military personnel. Finally, it was found that an overly constrained task may lead to stereotypical thinking and thus reduce creativity. This is particularly true for those individuals with more rigid cognitive styles. Thus, for managers, care should be taken to present problems to employees in a way that it solution-neutral, rather than adding too much constraint, and future research should investigate the delineation between a structured task that is conducive to creativity and one that is not.


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Instructions (structure modes were not included in the participant version). Below are descriptions of several problems. Read each description and try to suggest a creative solution for the problem it presents.

Problem A - Low-Structure (function-first)

Your unit is on a field exercise, and has run out of sandbags. You still require several meters of protective barrier. Can you think of creative solution to this problem?

Problem A - High-Structure (form-first)

Your unit is on a field exercise, and you have been ordered to clear a small patch of vegetation. Can you think of a creative use for the vegetation that will help you during the exercise after you have clearer the area?

Problem B - Low-Structure (function-first)

You are the Executive Office of a Naval vessel, and you are concerned that a small number of sailors that participate in boarding parties slip and injure themselves when they are on board other vessels. Can you think of a creative way to reduce the number of accidents?

Problem B - High-Structure (form-first)

You are the officer in charge of a logistics section, and have been sent a box of prototype boots with high grip soles. Can you think of a creative use for these new boots?

Problem C - Low-Structure (function-first)

You are a military instructor and are concerned by the number of trainees that are being injured on your obstacle course. There is a section that employs barbed wire, which snags on the trainees clothing to indicate that they are not low enough when leopard crawling, however, this is also causing injuries. Can you think of a creative way to reduce the injuries in this section of the course without sacrificing the training objectives?

Problem C - High-Structure (form-first)

You work in the development department for military technologies, and have been told that someone has invented electrifying mesh with a small current that causes no injury (only an unpleasant feeling). Can you think of a creative use for the new mesh that can assist the military?

Adapted from Sagiv et al. (2010)

Bree L. Sandwith, David H. Cropley and Lisa J. Chantler

University of South Australia, Australia

Correspondence concerning this article should be addressed to David H. Cropley, School of Engineering, Mawson Lakes Campus, University of South Australia, Mawson Lakes, SA 5095 AUSTRALIA. E-mail: David.Cropley
Table 1
Summary of Pearson Correlations, Mmeans, and Standard Deviations for
Scores on Key Variables (n = 77).

Measure             1          2          3         4          5

1. PNS              -
2. RLS               .92 (**)  -
3. DFS               .73 (**)   .41 (**)  -
4. TCT-DP           -.31 (**)  -.33 (**)  -.15      -
5. Time Served      -.13       -.06       -.19 (*)    .18      -
6. Pr A Creativity  -.19 (*)   -.18       -.15        .27 (*)    .05
7. Pr B Creativity  -.28 (**)  -.25 (*)   -.23 (*)    .20 (*)   -.01
8. Pr C Creativity  -.03        .02       -.11        .01        .01
M                   3.53       3.33       3.90      31.00      12.61
SD                   .70        .83        .82      11.86       7.64

Measure             6          7         8

1. PNS
2. RLS
3. DFS
5. Time Served
6. Pr A Creativity  -
7. Pr B Creativity   .52 (**)  -
8. Pr C Creativity   .20 (*)    .22 (*)  -
M                   2.44       2.28      2.60
SD                   .71        .88       .64

Note: PNS = Personal Need for Structure, RLS = Response to Lack of
Structure, DFS = Desire for Structure, TCT-DP = Test for Creative
Thinking--Drawing Production, Time Served Measured in Years, Pr =

(*) p < .05, (**) p < .01 (one-tailed)

Regression Analyses between Time Served and Task Structure on
Creativity, for Problems A, B, and C.

Variable                    B        SE   t      p     [R.sup.2]

Problem A
  Intercept                   2.44   .08  29.51  .001  .01
  Time Served (centred)        .003  .01    .28  .79
  TStructure                  -.03   .01   -.38  .67
  Time Served x TStructure     .01   .01    .76  .49
Problem B
  Intercept                   2.28   .10  22.46  .001  .02
  Time Served (centred)       -.003  .01   -.20  .85
  TStructure                  -.10   .10  -1.00  .33
  Time Served x TStructure     .01   .02    .78  .47
Problem C
  Intercept                   2.60   .07  34.80  .001  .001
  Time Served (centred)     < -.001  .01   -.01  .996
  TStructure                   .01   .07    .10  .91
  Time Served x TStructure    -.002  .01   -.25  .82

Variable                    Model F  p

Problem A
  Intercept                 .30       .83
  Time Served (centred)
  Time Served x TStructure
Problem B
  Intercept                 .53       .66
  Time Served (centred)
  Time Served x TStructure
Problem C
  Intercept                 .03      .995
  Time Served (centred)
  Time Served x TStructure

Note: TStructure = Task Structure

Table 3
Summary of Pearson Correlations between Creative Potential (TCT-DP) and
Product Creativity for Problems A, B and C, as a Function of Task
Structure (i.e., High or Low).

Measure             1         2         3         4

1. TCT-DP           -         .31 (*)   .07         .14
2. Pr A Creativity   .24      -         .52 (**)  40 (**)
3. Pr B Creativity   .31 (*)  .53 (**)  -         44 (**)
4. Pr C Creativity  -.10      .02       .05       -

Note: Correlations for the High-structure Condition (n = 38) are
Represented Above the Diagonal Line and Correlations for the
Low-structure Condition (n = 39) are Represented Below the Diagonal
Line. Pr = Problem.

(*) p < .05, (**) p < .01 (one-tailed)

Table 4
Regression Analyses between Creative Potential (TCT-DP) and PNS on
Creativity, for Problems A, B, and C.

                    Low Structure Task (n =39)
Variable             B      SE    t      p

Problem A
  Intercept          2.60   .09   26.06  .001
  TCT-DP (centred)    .02   .01    2.46  .09
  PNS (centred)      -.06   .12    -.50  .62
  TCT-DP x PNS        .04   .02    3.80  .03
  [R.sup.2]           .33
  Model F            5.80
  p                   .003
Problem B
  Intercept          2.50   .14   18.11  .001
  TCT-DP (centred)    .03   .01    2.46  .014
  PNS (centred)      -.14   .17    -.82  .40
  TCT-DP x PNS        .04   .02    2.73  .01
  [R.sup.2]           .261
  Model F            4.11
  p                   .013
Problem C
  Intercept          2.61   .12   21.54  .001
  TCT-DP (centred)   -.003  .01    -.31  .73
  PNS (centred)       .06   .13     .40  .65
  TCT-DP x PNS        .01   .01     .48  .62
  [R.sup.2]           .02
  Model F             .27
  p                   .849

                    HighStructure Task (n =38)
Variable             B      SE   t      p

Problem A
  Intercept          2.41   .12  20.05  .001
  TCT-DP (centred)    .01   .01   1.32  .30
  PNS (centred)      -.35   .23  -1.61  .11
  TCT-DP x PNS       -.002  .02   -.16  .87
  [R.sup.2]           .16
  Model F            2.17
  p                   .109
Problem B
  Intercept          2.27   .12  18.72  .001
  TCT-DP (centred)   -.001  .01   -.11  .932
  PNS (centred)      -.66   .21  -3.02  .002
  TCT-DP x PNS        .04   .02   2.64  .01
  [R.sup.2]           .342
  Model F            5.89
  p                   .002
Problem C
  Intercept          2.62   .10  26.14  .001
  TCT-DP (centred)    .004  .01    .41  .73
  PNS (centred)      -.23   .16  -1.30  .10
  TCT-DP x PNS        .01   .01    .42  .48
  [R.sup.2]           .07
  Model F             .88
  p                   .462

Note: TCT-DP = Test for Creative Thinking - Drawing Production, PNS =
Personal need for structure
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Author:Sandwith, Bree L.; Cropley, David H.; Chantler, Lisa J.
Publication:The International Journal of Creativity and Problem Solving
Article Type:Report
Date:Oct 1, 2017
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