Reeling in Stories: An Investigation of Creative Behaviors and Creativity-Support on Instagram
ABSTRACT
Creative behaviors are increasingly impacted by digital technologies, but little is known about the way digital technologies support everyday creativity and what factors predict their creative use. We investigated to what extent individual differences in person-specific (creativity, personality) and platform-specific (e.g., perceived creativity support) characteristics relate to the creative use of Instagram. The results from a sample of 191 Instagram users revealed that more frequent creative use of Instagram was related to greater engagement in everyday creative behaviors, creative self-beliefs, the openness facet of creative imagination, extraversion, a more positive attitude toward Instagram, greater platform-related self-efficacy, and greater perceived creativity-support. Regression analysis further revealed a unique contribution of everyday creativity, creative personal identity, extraversion, attitude toward Instagram, Instagram self-efficacy, and perceived creativity-support for creative use of Instagram. Although creativity was not the most central motive for using Instagram, the results from the present study indicated considerable levels of creative use, suggesting that common online spheres are important for everyday creative behavior. Together, this study identified relevant person- and platform-specific factors predicting creative behavior at Instagram, while also highlighting the relevance of creativity in the digital world even outside of devoted digital creativity tools.
When people open Instagram on their phones, they do it for various reasons. Some want to get an update from their favorite celebrity (Huang & Su, 2018) and escape from reality (Lee, Lee, Moon, & Sung, 2015), whereas others want to present themselves and increase their popularity (Sheldon & Bryant, 2016). Above all, the platform is used to socialize and keep in touch with family and friends (Kocak, Nasir, & Turker, 2020), which is a particularly strong predictor of continuous use (Hwang & Cho, 2018). Yet, Instagram also attracts those who are driven by creative motives (Kocak et al., 2020; Sheldon & Bryant, 2016) and the platform is associated with various creative domains, particularly visual arts (Ceh & Benedek, 2021). However, little is known about those who use Instagram for creative purposes, and the extent to which Instagram supports their creativity. The present research explores what person- and platform-specific factors are related to the creative use of Instagram, which will contribute to a better understanding of creative behaviors in the age of the digital transformation.
CREATIVITY AND THE INTERNET
Creativity is a complex phenomenon involving the creative potential (ability, personality, and expertise) to engage in creative behavior and obtain creative achievements in a given sociocultural environment (Benedek, 2024). Especially over recent years, this context has increasingly shifted toward digital environments and activities (Ceh, Rafner, & Benedek, 2024). The term digital creativity specifies creativity that is “manifested in all forms that are driven by digital technologies” (Lee & Chen, 2015). Online creativity specifically relates to the use of the Internet as a context and as a medium for creativity: Online spheres have been theorized to impact the creation, distribution, interpretation, and appropriation of creativity, influencing all stages of the creative lifecycle (Literat, 2019) and the representation of creativity as a concept (Ceh, Christensen, Lebuda, & Benedek, 2023). What is more, the Internet influences creative behavior on a social, material, and temporal level (Literat & Glăveanu, 2018), making it an increasingly distributed phenomenon. Native forms of digital creativity, but also digital effigies of offline everyday creative behaviors are often distributed online, typically in pursuit of self-expression and prosocial motives (Ceh & Benedek, 2021). This also holds true for Instagram—one of the world's leading Social Media platforms. It combines features that enable the generation and elaboration of content with a web-interface involving a huge community and massive content availability. Users can draw from these resources, edit and share (audio-)visual content, and interact with other users through messaging, commenting and/or liking published content. Ceh and Benedek (2021) found that, among a pre-selected list of 29 online platforms, Instagram was used most actively for creativity, that is, it was the platform with the highest rate of users that actively use the platform for posting creative content online. Another study found that while Instagram was positively related to the quality of creative accomplishments, other platforms were more strongly used for creativity (Acar, Neumayer, & Burnett, 2021). Research investigating motives for Instagram use further revealed aims such as escapism, representation, socialization, archiving, and—crucially—curiosity and creativity (Kocak et al., 2020; Sheldon & Bryant, 2016). While there is an apparent motivation for the use of this online sphere for creativity, little is known about the person and platform-specific factors that relate to interindividual differences in the extent of creative behavior on Instagram.
PERSON-RELATED VARIABLES AND CREATIVE USE OF INSTAGRAM
Research has identified a range of robust predictors of real-life creativity, such as divergent thinking ability (Jauk, Benedek, & Neubauer, 2014), creative self-beliefs (Karwowski, Lebuda, & Beghetto, 2019), and openness to experience (McCrae, 1987). Openness has further been associated with greater social media use (e.g., Correa, Hinsley, & de Zúñiga, 2010), and Instagram users pursuing creative motives were also more open (Kocak et al., 2020). Still, little is known about whether creativity-related variables and user personality bear importance for online creative behaviors all the same. Looking at the small corpus of empirical studies that investigated how creativity and use of online environments are related, most are unspecific regarding the type of use (i.e., general rather than creative usage) and environment (i.e., social media in general rather than specific environments). One study found that active use of social media was related to greater creative accomplishments, but lower creative thinking performance, while the frequency of passive use was unrelated to both (Upshaw, Davis, & Zabelina, 2022). In Acar et al. (2021), greater social media use was generally related to higher scores in creativity measures (e.g., greater tendency to engage in ideational behaviors, greater quality of creative work), particularly for active use. Drawing from this research, it seems important to consider active versus passive forms of creative use. Arguably, some creative behaviors, such as generating creative content through Instagram, or posting digital effigies of offline creations are considerably more active than merely consuming creative content generated by others, although the latter also reflects (passive) creative use.
Publishing creative content on Instagram means exposing it to the opinions and feedback of a potentially large audience, unknowing how it will be received. Doing so likely reflects the willingness to take social risks, which is essential for pushing the boundaries of personal creativity, as reflected in positive correlations between social risk-taking and creative self-beliefs (Bonetto, Pichot, Pavani, & Adam-Troïan, 2021a). Furthermore, engaging with social media inevitably involves social comparison, as users evaluate themselves in relation to others, which could also play a role for creative behaviors. For example, it has been argued in educational contexts that engaging in social comparison may be detrimental to one's creativity (Beghetto, 2005). In contrast, when believing that creativity can grow (i.e., holding a growth creative mindset; Karwowski, 2013), the exposure to creative content and/or evaluation of creative work might be taken as a source of inspiration rather than discouragement, informing greater creative participation. Taken together, there is a need to explore the role of established characteristics of the offline creative person in socially focused online contexts like Instagram.
PLATFORM-RELATED VARIABLES AND CREATIVE USE OF INSTAGRAM
Besides individual creativity, also how one perceives and interacts with the platform may influence creative behavior. One aspect that might be important for active and passive use of Instagram is the self-efficacy toward it, that is, the conviction that one is able to swiftly navigate through the platform/app, interact with other users and content, effectively use its tools and understand their capabilities (Davis, Winnemöller, Dontcheva, & Yi-Luen Do, 2013). Likewise, the general stance toward Instagram likely has implications for all types of its use. To better understand the adoption of specific technology for specific tasks, the technology acceptance model (Davis, 1985, 1989) and similar user acceptance models (cf. Venkatesh, Morris, Davis, & Davis, 2003) consider variables like the perceived usefulness for a given task, the perceived ease of use, and having a generally positive attitude toward it (Al-Qaysi, Mohamad-Nordin, & Al-Emran, 2020; Lee & Lehto, 2013; Marangunić & Granić, 2015). If the task is to be creative, the degree of usefulness relates to the extent to which an online platform like Instagram can be a handy tool for creativity.
So far, research on the creativity support of tools mainly focused on devoted tools but hardly considered the creative potential of social media. For example, the Creativity Support Index (CSI; Carroll & Latulipe, 2009; Cherry & Latulipe, 2014) measures perceived creativity support across six dimensions (i.e., collaboration, enjoyment, exploration, expressiveness, immersion and results worth effort) with two items each (e.g., I enjoyed using the system or tool). The conceptualization is based on flow research and work on creative play and exploration (Boden, 2004; Cherry & Latulipe, 2014; Csikszentmihalyi, 1997). Applying this measure to an online social network like Instagram would, however, just tell a fragment of the story. Although enjoyment is a motive for creative use of online platforms (Ceh & Benedek, 2021), and general Instagram use (e.g., Sheldon & Bryant, 2016), the social character of the platform might support creativity in additional ways, such as by facilitating interaction with other creatives on the platform, finding creative content from others, discussing creative ideas, and obtaining feedback and support by others.
To assess the creativity-support of Instagram in a differentiated and process-specific way, we devised a measure that considers the levels of Inspiration, Generation, Elaboration, Presentation, Collaboration, and Motivation. Inspiration relates to an early stage of the creative process, where new ideas get sparked, which could be supported on Instagram by confronting users with a wealth of original content (e.g., “collect” in Shneiderman, 2002). Generation refers to the potential of the available tools for creating new content from scratch, while Elaboration refers to platform tools for embellishing and fine-tuning content, together resembling the creation of artifacts (e.g., “process” and “products” in Rhodes, 1961). Presentation refers to the showcasing and distribution of creative content (e.g., “donate” in Shneiderman, 2002). Additionally, collaboration addresses the relevance of the platform community, measuring how one can work with others, or get valuable input on creative work (e.g., Cherry & Latulipe, 2014). Finally, motivation tries to capture how Instagram itself drives creative agency (Karwowski & Beghetto, 2018). These aspects aim to account for both the digital tool, and the social environment provided by Instagram. Importantly, Instagram could support different stages in the creative process (e.g., Ceh et al., 2024; Lubart, 2010; Shneiderman, 2002; Wagner & Jiang, 2012; Wang & Nickerson, 2017) such as sparking inspiration through the available content, offering features for creating and editing creative content such as images and videos, and for the presentation of creative content through creating posts, stories, or reels. In consequence, merely measuring the global extent of enjoyment or immersion might obscure the specific ways of how Instagram supports creativity.
AIMS OF THE STUDY
The main objective of this study is to explore platform- and person-specific factors that relate to the creative use of Instagram. This platform is widely used for creativity, yet only tangentially studied in the context of creativity (Ceh & Benedek, 2021; Kocak et al., 2020; Sheldon & Bryant, 2016). Drawing from the literature about technology-acceptance and creativity-support (e.g., Cherry & Latulipe, 2014; Davis, 1989; Davis et al., 2013; Lee & Lehto, 2013; Shneiderman, 2002), we devised a nuanced measure of creativity-support as well as platform-related self-efficacy and attitude. Extending the focus to person-specific characteristics, this study also integrates established indicators of creativity—creative potential, creative self-beliefs and mindsets, and openness—and explores personality factors like social risk-taking and social comparison orientation, to capture correlates of creative behaviors on Instagram. Incorporating both platform- and person-specific variables offers a comprehensive framework to understand not just how Instagram may serve as a creativity support tool, but also how individual predispositions contribute to creative activities in this digital context. We believe that this exploratory study constitutes an important step in achieving a better understanding of creative behaviors in the Internet age.
METHODS
PARTICIPANTS AND PROCEDURE
A total of 196 Instagram users took part in this online study. They were recruited by students as part of a course on research methods. Participants followed an online link, where they received information about the study and provided informed consent. Then, demographic data was collected, followed by measures for creativity, Instagram, and personality. The experiment lasted 52 minutes on average and was approved by the local ethics committee. We excluded three participants who spent an excessive amount of time (>3 SD) on the survey and two participants reporting diverse gender identity, as this group was too small for robust analyses of gender differences. The final sample consisted of 191 participants (71% female). The mean age was 25.18 years (SD = 7.85, range: 18–58). Anonymized data and additional materials, including three measures that were not considered for the present study, are available on the OSF (http://doi.org/10.17605/OSF.IO/Q9RZU).
MATERIALS AND MEASURES
The central-dependent variable, Creative use of Instagram, was measured with 13 items asking to report the frequency of active and passive creative behaviors on Instagram over the last 12 months using a five-point Likert scale (0—never to 4—very often; M = 1.52, SD = 0.71). The items (e.g., “I have posted self-made things.”, “I viewed creative content.”) and descriptive statistics are listed in Table S1. An exploratory factor analysis (KMO: MSA = 0.87, Bartlett's Test of sphericity: χ2 = 815.22, df = 78, p < .001; maximum-likelihood estimation; oblimin rotation) indicated a two-factor structure with an active (8 items; eigen value = 4.13; loadings .46 to .76; ωh = .86 [.82; .89]; omega hierarchical with bootstrapped 95% confidence intervals based on 1000 samples; Kelley & Pornprasertmanit, 2016) and a passive (5 items; eigenvalue = 1.12; loadings .36 to .76; ωh = .74 [.67; .80]) creative use factor (42% variance explained; ωh = .85 [.80; .88]). Noteworthy, two items initially considered as passive creative use items (i.e., “archiving my own creative work” and “viewing feedback on my own creative postings”) strongly loaded on the active use factor. Albeit not related to generating something new or publicly sharing it, the former item does indeed involve active engagement. The latter case indicates that the dichotomy between active and passive creative use likely misses out on the middle ground that is perhaps best described as engaged consumption. Finally, the two factors were substantially correlated (r = .47, p < .001).
Participants self-reported properties of their current Instagram account. Specifically, we obtained follower count (Mdn = 287, SD = 445.92) and followed by count (Mdn = 318, SD = 263.57), an estimated average like count over the last 12 months (Mdn = 90, SD = 94.78), the average daily time spent using Instagram (in minutes; Mdn = 40, SD = 46.67), the account type (78.53% private, 18.32% public, 3.14% professional), the main type of access (94.76% App, 4.71% Browser, 0.52% other), and a self-estimated active-passive use ratio (M = 0.24, SD = 0.24; 0 = passive, 1 = active).
To measure the general attitude toward Instagram, participants reflected on six self-devised statements about Instagram using a five-point Likert scale (0–4; e.g., “Instagram is fun.” or “Instagram dehumanizes our society.”; see Table S2). One item (“Instagram makes it difficult to keep your private life private.”) was removed to increase internal consistency (ωh = .59 [.49; .71]). Average approval was medium (M = 1.93, SD = 0.62). An exploratory factor analysis (KMO: MSA = 0.63, Bartlett's Test of sphericity: χ2 = 107.06, df = 10, p < .001; maximum-likelihood estimation; oblimin rotation) indicated a one-factor solution (eigenvalue = 1.16, 23% variance explained) with loadings ranging from .38 to .56.
Instagram-related self-efficacy was measured with 10 self-devised items describing whether users know their way around various features of Instagram (e.g., “I know how to change privacy settings.” or “I could use some help with some of Instagram's features.”; see Table S3). On average, participants reported high self-efficacy on a Likert scale ranging from zero to four (M = 3.33, SD = 0.69; ωh = .86 [.82; .90]). An exploratory factor analysis (KMO: MSA = 0.88, Bartlett's Test of sphericity: χ2 = 1037.76, df = 45 p < .001; maximum-likelihood estimation; oblimin rotation) indicated a one-factor solution (eigenvalue = 4.91, 49% variance explained) with loadings ranging from .36 to .88.
We measured the perceived creativity-support of Instagram along six facets (Inspiration, Generation, Elaboration, Presentation, Community, and Motivation). Participants responded to 20 statements using a Likert scale from zero (do not agree) to four (agree). Two items were omitted to increase internal consistency, resulting in a total of 18 items (see Table S4). An exploratory factor analysis (KMO: MSA = 0.89, Bartlett's Test of sphericity: χ2 = 1041.68, df = 153 p < .001; maximum-likelihood estimation; oblimin rotation) indicated a one-factor solution (eigenvalue = 5.41, 30% variance explained) with loadings ranging from .32 to .65. Internal consistency was high (ωh = .88 [.85; .90]).
Finally, we were interested in the general motives for using Instagram. We administered a measure of common motives for Instagram use (Kocak et al., 2020), consisting of the six facets Creativity, Expression, Prying, Recording, Recreation, and Socialization that had been compiled from previous studies (Lee et al., 2015; Sheldon & Bryant, 2016). Participants reported how frequently they use Instagram to pursue these motives on a Likert scale from 0 (never) to 4 (very often). Internal consistency indices were ranging from ωh = .68 to .81 for the six facets.
Creativity
We assessed everyday creative activity through the Biographical Inventory of Creative Behaviors (BICB; Batey, 2007). It is a binary checklist consisting of 34 items (i.e., creative activities) and participants self-report whether they have done these activities (e.g., “written a short story”) during the last year. A recent study showed that the measure has high psychometric quality, but additionally suggested that four specific items (items 8, 17, 19, and 23) may be omitted or replaced by more contemporary creative activities (Silvia et al., 2021). We replaced these items 8, 17, 19, and 23 accordingly (see Table S5). On average, participants agreed with 9.02 statements (SD = 4.64). The internal consistency (omega categorical with bootstrapped 95% confidence intervals based on 1000 samples; Kelley & Pornprasertmanit, 2016) of the scale was ωc = .82 [.55; .89]. A confirmatory factor analysis using robust weighted least squares indicated that the slightly adapted scale conforms to a unidimensional structure (RMSEA = .055 [.047; .062], baseline-RMSEA = .130, = .916, using scaled χ2 = .950) although not all indices suggested good fit (SRMR = .150, CFI = .833, TLI = .823; e.g., Hu & Bentler, 1999). Note that using CFI and TLI is discouraged for cases when null model RMSEA <.158 (cf. Kenny, 2020).
Creative achievements were assessed by asking participants to report their top three lifetime creative achievements (cf. Diedrich et al., 2018). Four independent raters rated the responses on a scale ranging from zero (not creative at all) to five (very creative; ICC2k = .70 [.63; .76]). 160 participants provided valid responses. The average rating for the highest rated achievement was selected as an indicator for creative achievement (M = 2.12, SD = 0.53).
We were also interested in the participants' general motivation for everyday creative behavior and had them self-report their motives for creativity (MoCS; Benedek, Bruckdorfer, & Jauk, 2020). This scale asks participants to reflect on their motivations behind engaging in creative activities, consisting of nine motivational facets (e.g., prosocial), that capture intrinsic (i.e., Enjoyment, Expression, Challenge, Coping) and extrinsic (i.e., Prosocial, Social, Recognition, Material, Duty) motivation factors. Internal consistency indices were high for the nine facets consisting of two items, each (ωh = .71 to .92), but less satisfactory for the two factors (intrinsic motivation: ωh = .74 [.62; .83], extrinsic motivation: ωh = .52 [.40; .74]) that were replicated through exploratory factor analysis.
To obtain a measure of creative cognitive potential, we used the Alternate Uses Task (AUT), an established divergent thinking task (Guilford, 1967). Participants were instructed to produce alternative uses for the objects brick and newspaper for 2 min, each. The instruction was to be creative (cf. Nusbaum, Silvia, & Beaty, 2014). Due to problems with the online timing of the survey (e.g., loading times), not all participants had exactly 120 s for each of the AUTs. We excluded AUT data for participants with <120 s or >125 s time on task (23.5%). We assessed both DT fluency (i.e., the average number of responses across both tasks; Mbrick = 5.67, SDbrick = 2.40; Mnews = 6.83; SDnews = 2.79) and the max-3 score for DT creativity (i.e., the three most creative responses by means of rating for each task, which were then averaged; Mbrick = 1.41, SDbrick = 0.41; Mnews = 1.42; SDnews = 0.35). Max-scoring is used to address the confound between originality and fluency (Benedek, Mühlmann, Jauk, & Neubauer, 2013; Silvia et al., 2008). Six independent raters rated all responses on a scale ranging from zero (not creative at all) to three (very creative). Interrater reliability estimates (ICC2k) were high for both items (brick: ICC = .91; newspaper: ICC = .85). Internal consistency was ωh .67 [.58; .74] for DT originality and ωh = .77 [.66; .85] for DT fluency.
We additionally assessed convergent thinking through a set of 10 Remote Associates problems. The Remote Associates Task (RAT; Mednick, 1962) requires participants to find a fourth word that produces a meaning when combined with each of three stimulus words (e.g., home, bed, sea: sick). We used 10 items from a German item set with increasing item difficulties (Landmann et al., 2014), of which participants solved 2.68 on average (SD = 1.54; range = 0–6; ωc = .51 [.11; .65]).
We further measured creative self-beliefs with (a) the Short Scale of Creative Self (SSCS; Karwowski, Lebuda, & Wiśniewska, 2018). The SSCS consists of 11 items on a five-point Likert scale (0–4), with the two subscales of Creative Personal Identity (CPI; M = 2.94, SD = 0.99) and Creative Self-Efficacy (CSE; M = 2.61, SD = 0.75), and has good psychometric properties (Zielińska, Lebuda, & Karwowski, 2022). The internal consistency (CPI: ωh = .92 [.90; .93]; CSE: ωh = .84 [.79; .84]) was high. In addition, we administered (b) the Creative Mindset Scale (Karwowski, 2013), which consists of 10 items (i.e., growth creative mindset, ωh = .70 [.62; .76]; and fixed creative mindset; ωh = .84 [.79; .87]), using a four-point Likert scale (0–4; Mgrowth = 3.03, SDgrowth = 0.64; Mfixed = 1.49; SDfixed = 0.84).
Personality
We assessed personality structure using the German version of the Big Five Inventory 2 (BFI-2-S and BFI-2-XS; Rammstedt, Danner, Soto, & John, 2018; Soto & John, 2017). Participants reported to what extent these statements apply to them using a five-point Likert scale. For the factor Openness to Experience we used the short scale (S) consisting of 12 items (M = 3.62, SD = 0.64, ωh = .77 [.69; .83]) reflecting three sub-facets (aesthetic sensitivity: M = 3.75, SD = 0.94, ωh = .82 [.76; .86]; intellectual curiosity: M = 3.70, SD = 0.75, ωh = .69 [.60; .76]; creative imagination: M = 3.40, SD = 0.78, ωh = .77 [.69; .82]); for the remaining factors, we used the very short scale (XS) with three items per factor to keep the survey to a reasonable length (conscientiousness: M = 3.34, SD = 0.83, ωh = .67 [.53; 1.00]; extraversion: M = 3.07, SD = 0.83, ωh = .61 [.45; .69]; agreeableness: M = 3.82, SD = 0.74, ωh = .56 [.42; .67]; neuroticism: M = 3.06, SD = 0.87, ωh = .65 [.55; .71]).
In addition, we administered the social-risk-taking subscale of the revised domain-specific risk-taking scale (DOSPERT; Blais & Weber, 2006), consisting of six items that were translated to German (ωh = .66 [.53; .74]). Participants indicated their willingness to engage in socially risky behaviors (e.g., “Disagreeing with an authority figure on a major issue.”) on a Likert scale from zero (certainly not) to four (certainly; M = 2.64, SD = 0.68).
Finally, participants reported their social comparison orientation using the German version the Iowa-Netherlands Comparison Orientation Measure (INCOM; Gibbons & Buunk, 1999), consisting of 11 items with good psychometric qualities (Schneider & Schupp, 2011) that assess the tendency to engage in social comparison regarding abilities and opinions on a five-point Likert scale ranging from zero (strongly disagree) to four (strongly agree; e.g., “I always like to know what others in a similar situation would do.”; M = 2.46, SD = 0.67; ωh = .84 [.79; .87]).
RESULTS
MOTIVES
The most prevalent motive for using Instagram was prying (M = 2.43, SD = 0.84), followed by socialization (M = 1.94, SD = 0.91). As such, the main rationale behind using the Social Media platform Instagram is indeed a social one (cf. Kocak et al., 2020), manifested in observing and interacting with peers and other users. The remaining motives were less frequently endorsed, with creativity being the lowest-ranking motive for using Instagram (M = 1.02, SD = 0.87). Looking next at the motives for creativity (Benedek et al., 2020), participants reported personal enjoyment, to challenge oneself, and self-expression as the main drivers for creative engagement. Prosocial and social motives were less frequently endorsed, but also play a substantial role for leisurely creativity in the present sample, unlike material aims and the feeling of duty (see Table S6). The distribution of motives largely conforms to the results of previous studies investigating reasons for everyday creative behaviors in offline (Benedek et al., 2020) and online contexts (Ceh & Benedek, 2021) and Instagram user motives (Kocak et al., 2020; Lee et al., 2015; Sheldon & Bryant, 2016).
DESCRIPTIVE STATISTICS
Table 1 shows the descriptive statistics and intercorrelations of all relevant measures. As indicated by Shapiro–Wilk tests of normality, skewness and kurtosis, and visual inspection of the distributions, not all measures were normally distributed (see Table S7). The biggest deviation occurred for age, which was right-skewed and leptokurtic.
| M (SD) | (1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | (10) | (11) | (12) | (13) | (14) | (15) | (16) | (17) | (18) | (19) | (20) | (21) | (22) | (23) | (24) | (25) | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| USE | (1) | 1.64 (0.70) | — | ||||||||||||||||||||||||
| USE_A | (2) | 1.20 (0.83) | .864 | — | |||||||||||||||||||||||
| USE_P | (3) | 2.07 (0.80) | .852 | .472 | — | ||||||||||||||||||||||
| Age | (4) | 25.18 (7.85) | −.135 | −.172 | −.058 | — | |||||||||||||||||||||
| Sex | (5) | 0.29 (0.46) | −.117 | −.012 | −.191 | .090 | — | ||||||||||||||||||||
| DT FLU | (6) | 6.25 (2.32) | .082 | .025 | .115 | −.008 | −.014 | — | |||||||||||||||||||
| DT CREA | (7) | 1.42 (0.32) | .089 | .029 | .123 | .094 | −.009 | .528 | — | ||||||||||||||||||
| C_ACH | (8) | 2.12 (0.53) | .098 | .085 | .081 | .090 | .030 | −.038 | .084 | — | |||||||||||||||||
| RAT | (9) | 2.68 (1.54) | −.060 | −.144 | .044 | .027 | .031 | −.071 | −.013 | .035 | — | ||||||||||||||||
| BICB | (10) | 9.17 (4.35) | .386 | .303 | .361 | .004 | −.005 | .210 | .250 | .176 | .053 | — | |||||||||||||||
| CMS_g | (11) | 3.03 (0.64) | .051 | .008 | .080 | −.113 | −.131 | .057 | .137 | .065 | −.090 | .160 | — | ||||||||||||||
| CMS_f | (12) | 1.49 (0.84) | −.137 | −.042 | −.197 | .174 | .182 | −.217 | −.261 | −.200 | .031 | −.179 | −.393 | — | |||||||||||||
| CPI | (13) | 2.49 (0.99) | .325 | .239 | .309 | .096 | −.024 | .191 | .268 | .118 | −.105 | .375 | .131 | −.111 | — | ||||||||||||
| CSE | (14) | 2.61 (0.75) | .211 | .152 | .211 | .272 | .116 | .224 | .198 | .029 | −.078 | .316 | .138 | .082 | .606 | — | |||||||||||
| O_AS | (15) | 3.75 (0.94) | .117 | −.006 | .211 | .143 | −.106 | .156 | .149 | .198 | .041 | .223 | .185 | −.399 | .409 | .179 | — | ||||||||||
| O_IC | (16) | 3.70 (0.75) | .142 | .053 | .194 | −.010 | .083 | .123 | .134 | .120 | .091 | .228 | .186 | −.271 | .384 | .338 | .441 | — | |||||||||
| O_CI | (17) | 3.40 (0.78) | .268 | .196 | .265 | .123 | .059 | .182 | .125 | .146 | −.049 | .410 | .210 | −.229 | .641 | .637 | .369 | .422 | — | ||||||||
| C | (18) | 3.34 (0.83) | .021 | .016 | .020 | .108 | −.095 | .014 | .059 | −.030 | −.027 | .050 | −.007 | .030 | .014 | .149 | −.156 | −.118 | .054 | — | |||||||
| E | (19) | 3.07 (0.83) | .228 | .164 | .228 | .041 | −.044 | .177 | .021 | .009 | −.025 | .231 | .071 | −.117 | .158 | .269 | .117 | .221 | .272 | .275 | — | ||||||
| A | (20) | 3.82 (0.74) | .092 | .004 | .156 | .073 | −.158 | .089 | .020 | −.118 | .028 | .019 | .126 | −.080 | .247 | .256 | .219 | .287 | .246 | .109 | .144 | — | |||||
| N | (21) | 3.06 (0.87) | −.039 | −.029 | −.038 | −.238 | −.123 | −.066 | .041 | .043 | −.080 | −.011 | .136 | −.086 | −.143 | −.314 | −.100 | −.165 | −.201 | −.261 | −.241 | −.268 | — | ||||
| DOS | (22) | 2.64 (0.68) | .033 | −.005 | .063 | −.019 | .126 | −.045 | −.045 | .073 | .177 | .213 | .193 | −.122 | .195 | .273 | .218 | .373 | .246 | −.203 | .228 | .070 | −.121 | — | |||
| INC | (23) | 2.46 (0.67) | .122 | .045 | .166 | −.364 | −.106 | .049 | .093 | −.019 | −.033 | .026 | .084 | −.060 | −.009 | −.184 | −.005 | −.028 | .030 | −.166 | .025 | −.017 | .412 | −.014 | — | ||
| I_ATT | (24) | 1.93 (0.62) | .315 | .225 | .317 | .169 | −.134 | −.113 | .070 | .073 | −.025 | .258 | .077 | −.004 | .098 | .191 | −.079 | −.021 | .123 | .136 | −.020 | .019 | −.052 | −.031 | −.080 | — | |
| I_SE | (25) | 3.33 (0.69) | .298 | .210 | .303 | −.275 | −.118 | −.001 | −.045 | .038 | −.093 | .041 | .287 | −.190 | .027 | .032 | .047 | .148 | .073 | −.042 | .051 | .135 | .095 | .208 | .184 | .155 | — |
| I_CS | (26) | 2.61 (0.55) | .338 | .199 | .384 | .032 | −.228 | −.029 | −.016 | −.056 | −.072 | .130 | .238 | −.049 | .106 | .218 | .054 | .131 | .184 | .226 | .173 | .277 | −.012 | .006 | .043 | .507 | .289 |
- Note. N = 191, n (C-ACH) = 160, n (DT CREA) = 146. |r| > .141: p < .05, |r| > .184: p < .01, |r| > .232: p < .001 for N = 191. USE_A/P = Instagram creative use active/passive, Sex (0 = female, 1 = male), DT FLU = fluency, DT CREA = originality for top 3 responses, C_ACH = achievement score for top response, RAT = remote associates task, BICB = everyday creativity, CMS_g = growth mindset, CMS_f = fixed mindset, CPI = creative personal identity, CSE = creative self-efficacy, O = openness, AS = aesthetic sensitivity, IC = intellectual curiosity, CI = creative imagination, C = conscientiousness, E = extraversion, A = agreeableness, N = neuroticism, DOS = social risk-taking, INC = social comparison orientation, I_ATT = attitude toward Instagram, I_SE = Instagram self-efficacy, I_CS = perceived creativity-support through Instagram.
PREDICTING CREATIVE USE OF INSTAGRAM
Creative Use of Instagram showed positive correlations with indicators of creativity (everyday creativity, creative personal identity, creative self-efficacy), personality (extraversion, openness: creative imagination), and Instagram-related measures (attitude, self-efficacy, creativity-support). The correlation patterns were similar for active and passive creative use (the former generally exhibiting slightly weaker correlations than the latter), which is unsurprising considering that the two factors were substantially correlated (r = .47). Thus, we decided to proceed with the global estimate of (i.e., mean of active and passive) creative use. We performed a bootstrapped multiple linear regression analysis with 2000 samples, predicting creative use of Instagram by all measures showing significant zero-order correlations with the criterion. Model assumptions were met (e.g., linearity, independence and normality of residuals, homoscedasticity, no multicollinearity; see Figures S1 and S2; max VIF = 2.18, min TOL = .45; D-W test = 1.97, p = .830). The model was statistically significant (F8,182 = 11.54, p < .001, R2 = .34, 95% CI [.25, .49]; see Table 2), revealing that the creative use of Instagram was independently predicted by everyday creative activity (ß = .24), creative personal identity (ß = .26), extraversion (ß = .11), attitude toward Instagram (ß = .16), Instagram-related self-efficacy (ß = .21), and perceiving Instagram as creativity-supporting (ß = .15).
| Predictor | ß [95% CI] | p | sr2 [95% CI] | r (p) | R2 [95% CI] |
|---|---|---|---|---|---|
| .34 [.19, .42] | |||||
| BICB | .24 [.09, .38] | <.001 | .04 [.01, .10] | .39 (<.001) | |
| CPI | .26 [.11, .40] | .003 | .03 [.01, .08] | .32 (<.001) | |
| CSE | −.11 [−.29, .07] | .205 | .01 [.00, .04] | .21 (.003) | |
| O_CI | −.02 [−.19, .14] | .790 | .00 [.00, .02] | .27 (<.001) | |
| E | .13 [−.00, .26] | .042 | .02 [.00, .05] | .23 (.002) | |
| I_ATT | .15 [.01, .28] | .049 | .01 [.00, .05] | .31 (<.001) | |
| I_SE | .21 [.04, .36] | <.001 | .04 [.00, .11] | .30 (<.001) | |
| I_CS | .15 [−.01, .31] | .047 | .01 [.00, .06] | .34 (<.001) |
- Note. CI = 95% percentile confidence interval based on 2000 bootstrapping samples; r = zero-order correlation; sr2 = squared semi-partial correlation; ß = standardized regression weight. BICB = everyday creativity, CPI = creative personal identity, CSE = creative self-efficacy, O_CI = openness: creative imagination, E = extraversion, I_ATT = attitude toward Instagram, I_SE = Instagram self-efficacy, I_CS = perceived creativity-support through Instagram.
HOW DOES INSTAGRAM SUPPORT CREATIVITY?
Given that perceived creativity-support had the highest zero-order correlation with, and predicted creative use of Instagram, we tried to gain a better understanding of the creative affordances of Instagram through the different aspects of perceived creativity-support (Table S8). All facets of creativity-support by Instagram were substantially positively related (.44 < r < .63, all ps < .001) and participants endorsed the supportive characteristics of Instagram across all aspects, most strongly for Presentation (M = 3.03, SD = 0.68), but also for Inspiration (M = 2.77, SD = 0.73), Elaboration (M = 2.65, SD = 0.70), Generation (M = 2.47, SD = 0.74), Motivation (M = 2.39, SD = 0.72), and Community (M = 2.34, SD = 0.67). As can be assumed from the intercorrelations of the facets (see Table S8), they were also similarly related to the other investigated variables. Notable exceptions include the positive relationship between engaging in everyday creative activities and perceiving Instagram as supportive for presenting content (r = .20), the negative relationship between holding a more fixed mindset and presentation-support (r = −.17), and positive relationship between creative personal identity and finding Instagram to support creative motivation (r = .15). Likewise, perceived creativity-support was also positively related to growth mindset beliefs, creative self-efficacy, creative imagination, conscientiousness, extraversion, and agreeableness at the global level (see Table 1). What is more, female users found Instagram to be more creativity-supporting (r = .23).
DISCUSSION
The present study investigated person- and platform-factors predicting the use of Instagram for creative purposes. Users who are more frequently engaged in everyday creative behaviors, who consider their creativity as an important part of their self, and who are more extraverted are using the platform more frequently for creative behavior. Moreover, higher creative use of Instagram was also predicted by greater platform-related self-efficacy, a more positive attitude toward Instagram, and greater perceived creativity-support through Instagram. In other words, the creative use of Instagram is informed by person-, and platform-related characteristics. We discuss these findings in detail below.
Instagram users who are more frequently engaged in everyday creative behaviors are also more frequent active and passive creative users of the platform, partially conforming to a previous finding showing a positive relationship between the frequency of creative activities and social media use (Acar et al., 2021). However, this does not extend to creative achievements, which was positively related to active social media use in previous studies (Acar et al., 2021; Upshaw et al., 2022). Similarly, the present study did not find any relation between active nor passive creative use of Instagram and divergent thinking, nor convergent thinking. In this context, it should be noted that creative achievements, ideational fluency, and originality were positively related to everyday creativity, which is in line with previous studies (e.g., Jauk et al., 2014).
Furthermore, our study shows that people who more strongly consider creativity as an inherent part of their self (i.e., creative personal identity and self-efficacy; Karwowski et al., 2019) are more frequently creative users of Instagram. Similarly, users who more strongly believe in the malleable characteristics of creativity (i.e., that creativity can be enhanced through practice and effort; Karwowski, 2013) also perceive Instagram as more creativity-supporting, which was significantly related to and predicted creative use. Accordingly, those who are convinced by their own creativity and believe that Instagram can support their creative growth may also use this digital sphere more often to engage in creative behavior.
Two of the investigated personality variables were related to general creative use: Openness to experience, specifically, the facet creative imagination, and extraversion—two robust predictors of the creative person (Puryear, Kettler, & Rinn, 2017). Investigating openness to experience at the facet level has allowed us to uncover that the relationship between openness and creative use of Instagram is not purely the result of (a) Instagram being a visual arts focused platform (Ceh et al., 2024; Ceh & Benedek, 2021) and (b) openness to experience including items related to aesthetic sensitivity (e.g., treasuring the arts). Although passive creative use and aesthetic sensitivity were positively related, creative imagination was even more relevant. Neither social risk-taking nor social comparison orientation were related to creative use of Instagram at the global level in the present sample. However, users with higher social comparison orientation were also more frequently passive creative users, which is in line with literature on general passive social media use (e.g., Burnell, George, Vollet, Ehrenreich, & Underwood, 2019). What is more, social risk-taking was positively related to self-reported measures of creativity (i.e., openness facets, creative growth mindset, and creative self-beliefs), including predictors of creative use. This finding emphasizes the perceived social risk involved in creative behaviors, which is in line with previous research (Bonetto et al., 2021a; Tyagi, Hanoch, Hall, Runco, & Denham, 2017). Given that risk-taking and social comparison are relevant for/related to the use of social media in various contexts (e.g., Vannucci, Simpson, Gagnon, & Ohannessian, 2020; Verduyn, Gugushvili, Massar, Täht, & Kross, 2020; Weber, Messingschlager, & Stein, 2021), future studies should thus further investigate potential mechanisms, as well as the extent and implications of risk-taking and social comparison in online creative behaviors, perhaps using experimental designs, investigating users and non-users (e.g., Ryan & Xenos, 2011), and including other/additional indicators (e.g., see Shou & Olney, 2020, for an in-depth discussion of the limitations of the DOSPERT scale for measuring risk-taking). In the context of online creativity, such investigations seem particularly promising given that users need to adhere to social norms imposed by the respective social media community and balance them with the often norm-violating character of creative behaviors (Bonetto, Pichot, Pavani, & Adam-Troïan, 2021b).
At the level of the platform, higher Instagram self-efficacy was related to greater creative use of Instagram. Importantly, the two employed self-efficacy measures were unrelated in the present sample, suggesting that they differentiate between creative and platform-specific self-efficacy. As such, the present study adds to the literature showing how creative self-efficacy informs the agentic decision to engage in creative behaviors (Tierney & Farmer, 2011) and how task-specific self-efficacy is a central component related to digital tool usage (e.g., Al-Qaysi et al., 2020; Yi & Hwang, 2003). In addition, a more positive attitude toward Instagram, and greater perceived creativity-support through Instagram predicted higher creative use of the platform. These findings point to the role of the environment for creative behaviors, emphasizing that this aspect needs to put more strongly in focus in the context of the digitalization (Ceh & Benedek, 2021; Literat & Glăveanu, 2016, 2018; Rhodes, 1961). What is more, the present study shows that an online environment with a specific feature-set tailored to the visual domain is perceived as a creativity-supporting tool across all stages of the creative process and at a meta-level, pertaining to creative collaboration and motivation within a sample of predominantly non-professional creators. This is an important finding given that research in the field of human-computer interaction has often considered creativity-support tools at expert levels, paying lesser attention to the relevance of common digital tools and online spheres such as social media for everyday creative behaviors (Ceh et al., 2024; Frich, Macdonald Vermeulen, Remy, Biskjaer, & Dalsgaard, 2019).
The investigation of motives for Instagram use replicated the predominant social and somewhat lower creative role of the platform, as is indicated by other studies (Acar et al., 2021; Kocak et al., 2020; Lee et al., 2015; Sheldon & Bryant, 2016). Yet, while creativity was not the primary motive for using Instagram, the platform was generally viewed as creativity-supportive and was at least partly used for creative purposes by the majority of the sample, which is also in line with a previous finding (Ceh & Benedek, 2021). Possible reasons for why creativity was less endorsed as a general motive for using Instagram may lie in the nature of assessment. Specifically, the creative motive was estimated using three items (cf. Sheldon & Bryant, 2016), two of which reflect domain-specific, active behaviors (making art and showcasing photography skills), which generally had low prevalence compared to passive creative use. In addition, the third item (to find users with shared interests) does not explicitly relate to creativity in the first place. Certainly, differentiating between creativity-unrelated behaviors, active creative engagement (e.g., generating, editing, or publishing artifacts), ephemeral creative interactions (e.g., humorous comments), and different kinds of creative exposure reflecting varying degrees of intentionality or autonomy (e.g., a user browses through creative content versus makes a serendipitous creative encounter through platform suggestion) is not straightforward from both a researcher and user perspective, which might explain differences in user motives and behavioral outcomes. What is more, it is not unlikely that some creative behaviors are merely the byproduct of other intentions, such as when a meme (i.e., a mundane creative artifact) is generated and shared for socialization purposes. In sum, people may not always recognize the creative nature of their activities on Instagram, which is why they may underestimate creativity as motive for using it, even though they would still endorse specific creative activities such as those assessed by our creative Instagram use measure.
LIMITATIONS
This exploratory study presents an empirical investigation of the creative use of Instagram in conjunction with creativity, personality, and platform variables. There are, however, a few limitations that need to be noted. First, this study has recruited only a rather small sample of Instagram users, which limits the robustness and generalizability of the study findings. Still, the observed pattern of creativity and personality measures speaks to the representativeness of the sample with regards to the variables of interest. Second, the correlational nature of this study does not allow for causal interpretations. As an example, it would be interesting to see to what extent the creative use of Instagram and the evoked feedback shapes creative confidence beliefs over the course of time. Third, some of the measures used in this study suffer from low internal consistency and could be improved. This is perhaps most relevant for the general attitude toward Instagram, a predictor of creative use, which we intended as a broad measure of user perception. Internal consistency analysis may underestimate the reliability of such a broad construct (Osburn, 2000), so future research should also consider retest reliability. We hope that the measures we devised could serve as a starting point for future studies and share the full materials in the supplement to this end. In this context, we recommend that future studies could also refine the assessment of creative use. We devised this measure with an active and passive use scale. While such a two-factor structure was generally supported, item-level inspections indicated that the active/passive use dichotomy is not always that clear-cut, which resulted in correlated factors but also reflects ongoing discussions about how passive media use can be (e.g., Valkenburg, Beyens, Loes Pouwels, Van Driel, & Keijsers, 2021). As an alternative to self-reports, one could study the use of Instagram for creativity via data donations, or through an official API.
SUMMARY AND CONCLUSION
This exploratory study helped to identify factors contributing to the creative use of Instagram. People who are more open and extraverted, who are frequently engaging in creative behaviors and who have greater creative confidence use Instagram more frequently for creative purposes—a prevalent behavioral phenomenon, albeit not the most prominent motive for platform use. Platform-characteristics, such as a positive attitude toward the platform, and greater perceived platform-related self-efficacy further play a role for the creative use, even within a user-sample. In addition, perceived creativity support, spanning across levels of inspiration, generation, elaboration, presentation, community, and motivation, predicted creative use of Instagram. In particular, the aspect of presentation is valued at this specific online sphere. These findings underline the importance of personal and platform characteristics for creativity in the context of the digital transformation, motivating future research about the use and support of digital technology for creativity.
FUNDING INFORMATION
This study was not supported by any external sources.
CONFLICT OF INTEREST STATEMENT
The authors declare no conflict of interest.
ETHICS APPROVAL STATEMENT
This study was approved by the local ethics committee.
Open Research
DATA AVAILABILITY STATEMENT
Data, analysis scripts, and study materials are provided on the OSF (http://doi.org/10.17605/OSF.IO/Q9RZU). The data is original and was not used in any prior studies.
