Public belonging on social media: psychometric validation study of the Turkish desire to belong publicly scale (DTBP)
Authors: Mehmet Kavaklı
Published: 2026

ABSTRACT
AbstractBackgroundThe sense of belonging is among the most fundamental psychological needs of an individual. Today, in addition to face-to-face interactions, social media platforms also fulfill this need and make it publicly visible. Social media posts of an individual, in particular, can be interpreted as a reflection of their tendency to express a sense of belonging. The current study aimed to examine the validity and reliability of the Turkish version of the Desire to Belong Publicly (DTBP) scale, which aims to explain individual tendencies to display belonging on social media.MethodsThis research, comprised of three separate studies (N = 1046), collected data exclusively from Instagram users. Exploratory factor analysis was used in the first study, and confirmatory factor analysis was used in the second and third studies. Additionally, internal consistency, four-week test–retest reliability, convergent and discriminant validity were analyzed. The scale's relationships with social media usage habits, personality traits, social comparison orientation, and perceived ostracism were examined.ResultsThe findings indicate that the Turkish form of the eight-item DTBP scale has a single-factor structure. The scale has high internal consistency (α = 0.93, ω = 0.93) and high test–retest reliability (r = .80, p < .001) measured at a four-week interval. The scale is related to, but conceptually distinct from, the general belongingness (GB). The CFA conducted in Study 3 indicated that the single-factor structure of the scale was appropriate. DTBP was also positively correlated with social comparison orientation, excessive Instagram usage, and perceived ostracism, and negatively correlated with conscientiousness.ConclusionThis study provides evidence for a distinct individual-difference construct related to the public display of belonging on social media. The findings suggest that DTBP is associated with several psychosocial variables, including excessive Instagram use, personality traits, perceived ostracism, and social comparison orientation. This scale may contribute to future theoretical and applied studies on understanding digital self-presentation and visible belonging behaviors among Instagram users and within image-based social media contexts.Keywords: Desire to belong publicly, Scale adaptation, Belonging, Instagram, Social media, Psychometric validation

Introduction

Social media has become an essential part of life and is used for promoting interpersonal relationships, self-expression, and the fulfillment of basic psychological needs [1]. Social media usage meets a fundamental psychological need for belonging, which can have a profound impact on human motivation and behavior [2–4]. Humans are evolutionarily motivated to develop and maintain meaningful relationships [5]. Social media promotes the establishment and maintenance of such relationships while also providing a unique platform for individuals to demonstrate their present relationships with others. Of note, individuals tend to make their social belongings "visible" in their offline lives as well (e.g., symbolisms that indicate that they belong to a group/relationship, shared activities, etc.). Social media disseminates these visible signs of belonging rapidly to a wider audience in the virtual world. Furthermore, social media enables quantifiable social feedback (e.g., likes, comments). In line with this, studies have shown that being excluded from such visible online interactions (e.g., not being tagged in an Instagram post) can be perceived as socially painful and can threaten fundamental human needs, such as the need to belong [6].

Social media not only meets the satisfaction of the need for "belonging," but also makes it possible to present one’s sense of belonging to the social environment in a visible/public way [7, 8]. Therefore, being on social media not only satisfies this internal need, but can become a socially displayed and validated phenomenon, which addresses the keenness of individuals to openly display this sense of belonging on such platforms. For example, an individual may feel that they belong to a group [9], but may also be particularly motivated to present that belonging in a visible and public way online. Despite the availability of a large body of evidence on the relationship between social media usage and factors such as mental health [10], self-presentation tactics, depression, and anxiety [11, 12] there is still a lack of understanding of the motivation for the public display of belonging on social media.

A better understanding of this motivation is important because “belonging” and “visible or public belonging” do not entail the same motivational processes. For example, individuals may have a need to belong and may try to satisfy their psychological needs on social media [13]. However, some individuals are additionally motivated to make their belongingness visible and public online. Therefore, being able to measure the need for this visibility can provide a unique understanding of social media behavior. Thus, the focus of the current study was not "how much an individual feels a sense of belonging," but rather "the desire to make their sense of belonging visible online." This distinction can offer a unique contribution towards understanding visible belonging behaviors among Instagram users (e.g., frequency of posts, desire to be tagged, sharing photos, videos, and stories with different groups).

Büttner et al. [7] established the concept of Desire to Belong Publicly (DTBP), which is defined as individual differences in the willingness to openly share one's sense of belonging on social media, rather than their actual experience of belonging [7]. The DTBP scale was designed to evaluate this notion. The purpose of the current study was to adapt and assess the validity and reliability of the DTBP scale reported by Büttner et al. [7] in the Turkish context. The primary characteristic of DTBP that makes it different is that unlike scales that measure general belongingness (GB) [14, 15], DTBP measures not belonging itself but the desire for the "visible expression/display" of belonging through social media. In this respect, DTBP offers a relatively more comprehensive conceptual tool to better understand patterns of sharing and engagement, especially on image-based platforms. This distinction becomes particularly relevant on platforms such as Instagram where visibility and feedback are built into the system. A combination of the motivation of individuals with the visibility and feedback features offered by social media platforms may be associated with stronger and more frequent manifestations of public display of belongingness.

The desire to belong publicly and its psychological foundations

Social media has emerged as a platform that individuals utilize extensively for numerous purposes. Many studies in the literature indicate that social media usage correlates with various motivational and psychological needs [16–18]. Users can share several types of content on social media platforms, including posts, photographs, selfies, videos, stories, tags [19], and emotions [20]. The high use of social media has led to numerous studies that have explored of the origins and effects of these activities [21–23]. Nevertheless, research examining actual social media posts is notably limited [7]. The available studies indicate that individuals are especially motivated to share their pictures with friends [24] and that images with human faces receive more likes and comments [25, 26]. These findings indicate that interpersonal content in social media messages can elicit greater engagement.

DTBP, in particular, is much more easily reinforced by visible social content (e.g., group photos, tags, and group activities) and through social feedback (likes and comments) [27, 28]. This reinforcement cycle can motivate some individuals to increase their tendency to make their sense of belonging visible. Social feedback may serve as a validation of social connectedness, beyond mere popularity cues. In this way, the public display of belonging can become a frequently repeated behavioral pattern.

An image-based social media platform such as Instagram provides an environment in which individuals create and distribute content for various psychosocial purposes, including self-expression, social interaction, archiving, and escaping the stress of daily life [29–32]. Instagram offers a special context for DTBP as the former encourages visual content creation, generate visibly measurable social feedback (likes and comments) [33], and has features such as tagging that allow for direct display of who one is associating with. These features can make the visible belonging motivation measured by DTBP more understandable and observable. In fact, Instagram is regarded as the most appropriate social media platform for individuals to exhibit sociability, proximity, and compassion, as per user perceptions [34]. In the same vein as Instagram, a study has demonstrated that subjective well-being was positively correlated with the number of friends and positive self-presentation on Facebook [35]. In addition, studies suggest that sharing photographs on Instagram can provide satisfaction, social interaction, entertainment, and expression [36]. Another study reported that the frequency of photo sharing on Instagram may play a significant role in the relationship between an individual's sense of social connection and well-being, and this effect may vary, depending on the type of loneliness that the user faces [37]. Posts and photos that depict an individual’s engagement in social activities on social media platforms may serve more specific and distinct psychological functions compared to text-only content that collates similar information. To the best of our knowledge, no research has systematically investigated the reasons why individuals display their belongingness (i.e., photographs of themselves with others) on social media, as stated by Büttner et al. [7].

The quantification of the visible display of belonging in the context of a social media platform such as Instagram and how this might relate to individual differences offers an important area of ​​research for understanding the psychological underpinnings of social media behavior. DTBP describes an individual's desire to communicate the sense of belonging they feel in real life to others through the use of social media [7]. Such a wish can be expressed in a variety of ways, including inclusion in the content of others, being tagged in posts, or posting photos or stories [7]. In this context, one of the fundamental questions is why individuals would want to display their real-life experiences of belonging through a social media platform. A significant portion of social media platforms prepare the ground for or assist individuals in psychological processes such as self-presentation, impression management, and seeking social acceptance [12, 38]. Büttner et al. [7] asserted that individuals with higher DTBP scores can use their social media posts as strategic signals to exhibit their sense of belonging. The same authors [7] proposed that this signal may function in two distinct and important ways. Initially, the individual has the option to communicate their appreciation for their current social network and relationships by posting on social media. Symbolic indicators like emojis, likes, or tags can effectively communicate this message. Secondly, individuals who exhibit their connections may be perceived by other users as a reliable and positive social interaction partner. Through sharing, an individual can convey the message "I value my existing relationships." But at the same time, they can also signal to a wider social circle that "I socially belong to a person/group and am a positive partner or group member." Thus, DTBP may provide a framework for understanding how belonging is not only experienced internally but may also be publicly expressed and interpreted as a form of social signaling within image-based social media contexts.

These explanations can be grounded more strongly in two important theoretical approaches. From the perspective of the social identity theory, individuals may seek social acceptance and approval by making their social identities and group memberships visible [39–42]. In collectivistic societies where relationships are more tightly knit into groups, displaying belonging to the social environment through social media can convey the message that the person is "valuable" and "worth relating to." Thus, the visible display of belonging in collectivistic cultures may not be merely an individual choice. It can also become a more normative form of behavior intertwined with processes such as social approval, acceptance, and avoidance of exclusion. From this perspective, DTBP can also be explained via the signaling theory. The social media posts of an individual can function as a strategic indicator, a sign through which they "signal" their social resources and relational connections to their environment [43, 44]. However, this interpretation does not imply that DTBP reflects belongingness itself or a broad tendency toward social approval seeking. Rather, DTBP may represent a belongingness-related self-presentational tendency involving the public signaling of social connectedness and the visible expression of social relationships in online contexts. Although DTBP may partially overlap with conceptually related constructs such as impression management, social approval seeking, and social validation processes, the present framework conceptualizes DTBP as a narrower tendency focused specifically on making social connectedness publicly visible rather than managing broader social impressions.

DTBP may emerge at various levels among individuals and influence their sharing preferences, views on appropriateness, and decisions about the audience for their content. This suggests that measurement of DTBP may be significant for both theoretical and practical reasons. The visible display of social relations, particularly in collectivist cultures, may be linked to social acceptance and group approval, as previously mentioned. For this reason, adapting the DTBP into the Turkish is important for understanding how the motivation for visible belonging is structured within a specific cultural context.

Present study

The current study aims to provide a practical tool for measuring the motivation for public belongingness in Türkiye and to initiate research that examines the psychological processes of visible belonging behaviors among Instagram users in a culture-related context. The first aim of the current research was to evaluate the validity and reliability of the Turkish version of the DTBP scale, which was developed by Büttner et al. [7]. Second, we analyzed a Turkish sample to ascertain the conceptual distinction between DTBP and general belongingness. Third, we assessed the relationships between DTBP, social media usage habits (daily usage time), and excessive Instagram usage. Fourth, the relationship between DTBP and five-factor personality traits, perceived ostracism, and social comparison orientation were examined.

Although this research is primarily a scale adaptation study, it also lays the groundwork for integrating DTBP into a broader conceptual framework of visible belonging in digital environments. DTBP was expected to be positively correlated with excessive Instagram usage, perceived ostracism, and an orientation for social comparison. Individuals with higher DTBP levels were hypothesized to engage more frequently with Instagram and to report greater visible social media engagement behaviors. Rather than suggesting direct causal mechanisms, the present findings may offer an initial perspective for future research exploring how social feedback indicators (e.g., likes and comments), social comparison processes, and perceived ostracism are associated with visible belonging behaviors in online environments. In this respect, the current framework provides a theoretically grounded basis for future studies examining DTBP and digital self-presentation.

The current research incorporated three separate studies with 1046 individuals and was limited to Instagram users only. The objective was to enhance our comprehension and provide psychometric evidence of the tendency of individuals to publicly disclose their belongingness with the use of image-based social media platforms. The original study [7] was the foundation for the adaptation procedure of the scale and all subsequent studies. The results obtained indicated that the psychometric properties of the Turkish version of the DTBP scale were suitable and that a positive correlation existed between DTBP and excessive Instagram usage, as expected. Similar to the original study, we determined that DTBP was associated with general belongingness (GB), yet was conceptually distinct. The scale's test–retest reliability was supported by measurements obtained at four-week intervals. The results of the current study demonstrate that the Turkish version of the DTBP scale is a reliable and valid measurement instrument that can be employed to ascertain the motivations of an individual for revealing their sense of belonging on image-based social media platforms like Instagram. This tool can be used for future studies that aim to evaluate the “visible/public belonging” motivation within Instagram and other image-based social media contexts and investigate the relationship between it and usage habits.

Study 1

The aim of Study 1 was to conduct the initial evaluation of the Turkish version of the DTBP scale. For this, the relationship between DTBP and general belongingness and excessive Instagram usage was tested. The hypothesis of this study was that, as reported by the authors who developed the original scale, DTBP is related to general belongingness but is a different construct and that individuals with high DTBP level use social media more excessively. An image-based social media site such as Instagram was chosen for the current study since the same site was used in the original study [7], additionally, Instagram usage rate is quite high in Türkiye.

Method

Participants

The current research was carried out on university students who are active Instagram users and were studying at a state university in Türkiye. A total of 364 participants aged 18–50 years were included (Mage = 22.40, SD = 4.93). Sixty-eight males (18.7%) and 296 females (81.3%) were included, and the participants were selected using the convenience sampling method. Sample sizes were determined pragmatically, aiming to satisfy widely used recommendations for factor-analytic studies (e.g., absolute minimum sample sizes and participant-to-variable ratios) and to ensure stable EFA/CFA estimation across independent samples [45–47]. All participants were provided with an informed consent form that outlined the specifics of the investigation. The study sample consisted of participants who willingly volunteered for the study, completed the approval form, and provided their agreement to participate.

Measures

Personal information form

A questionnaire including the following questions was developed: How long have you been using Instagram? Is your Instagram profile set to public visibility? What is the duration of your daily usage of Instagram? What is the number of followers you have on Instagram? In addition, variables such as age and gender were queried.

Desire to belong publicly (DTBP) scale

The DTBP scale was developed by Büttner et al. [7] to measure the DTBP levels of individuals. The scale is a 7-point Likert scale ranging from not at all (1) to very much (7). The scale consists of 8 items (e.g., It is important to me that people who look at my [social media] profile see that I have many friends) and two-factors, namely, quantity and quality. The scale additionally yields an overall DTBP score.

General belongingness scale

The General Belongingness Scale was developed by Malone et al. [14]. and was adapted to the Turkish by Duru [15]. The scale is a 7-point Likert scale ranging from strongly disagree (1) to strongly agree (7). The scale consists of 12 items (e.g., When I am with other people, I feel included) and two-factors, namely, acceptance and rejection. The general belongingness score is computed by reversing the rejection items. The scale showed strong reliability coefficients in the current study (Cronbach’s α = 0.81, McDonald’s ω = 0.85, M = 5.40, SD = 1.02; Cronbach’s α = 0.85, McDonald’s ω = 0.85, Macceptance = 5.30, SD = 1.14; Cronbach’s α = 0.86, McDonald’s ω = 0.86, Mrejection = 2.51, SD = 1.18).

Instagram addiction scale

The Instagram Addiction Scale was developed by D’Souza et al. [48] and was adapted to the Turkish by Kavaklı and İnan [49]. The scale is a 5-point Likert scale ranging from never (1) to all the time (5). The scale consists of 21 items (e.g., I often upload photos or videos on Instagram) and five-factors, namely, lack of control, escapism, disengagement, obsession, and health and interpersonal problems. The scale also calculates a total score. This scale also showed strong reliability coefficients in the current study (Cronbach’s α = 0.93, McDonald’s ω = 0.93, M = 2.38, SD = 0.77).

Procedure

Permission was first obtained by email from Büttner et al. [7] who developed the DTBP scale, for the Turkish adaptation of the scale. The Social and Human Sciences Ethics Committee of Necmettin Erbakan University, Türkiye provided ethical approval for all three studies after the permission was provided (Approval date: 10.03.2023, Approval number: 2023/105). The translation of the scale items into the Turkish was initiated after the receipt of ethical approval. A clinical psychologist and a social psychologist independently translated the items. The final version was determined through a collaborative effort. The final version of the scale was subsequently submitted to two independent social and clinical psychologists, and their feedback was obtained. The Turkish version of the scale was finalized in accordance with expert views. The final version of the scale was then translated back to the English by using back translation and the items were found to be consistent with the original English version of the scale. Data collection was started after the completion of the back translation stage. An informed consent form stating the details of the research was provided to all participants prior to the start of the study. The data were collected through an online platform in March 2023 (Google Forms) in which the questions were presented in random in order to prevent any order effect. The participants were asked whether they used Instagram or not, and participants who did not use the social media platform were excluded. Next, all participants were asked to complete the scales. For descriptive purposes (Additional File 1), the participants were asked how long they had been using Instagram (M = 70.53 months, SD = 31.23, Range = 1–180), whether their Instagram profile was visible to everyone (6.6%) or set to private (93.4%), average daily Instagram usage time (M = 144.08 min, SD = 106.36, Range = 5–900), number of followers on Instagram (M = 306.71 followers, SD = 250.10, Range = 3–2406), and number of accounts they followed on Instagram (M = 336.84 followed, SD = 281.16, Range = 1–3408).

Results

Exploratory factor analysis

Statistical analyses were conducted using JASP, an open-access statistical program. Initially, the scale items were evaluated for any missing data, and it was determined that none were absent. The Kaiser–Meyer–Olkin (KMO) measure of sample adequacy and Bartlett's test of sphericity confirmed that the items were appropriate for factor analysis (KMO = 0.93, Bartlett’s χ2(28) = 1763.52, p < 0.001). An exploratory factor analysis (EFA) was conducted using the maximum likelihood estimation method and oblimin rotation. The factor number of the scale was obtained via parallel analysis. The results revealed the presence of a single-factor structure, unlike the original study (see also Fig. 1). A one-factor solution explained 58% of variance (model fit: χ2 = 60.48, df = 20, χ2/df = 3.02, p < 0.001, CFI = 0.98, TLI = 0.97, RMSEA = [90% CI] = 0.07 [0.05, 0.10], SRMR = 0.03). The reliability analysis of the one-factor structure was carried out with the Cronbach Alpha and McDonald Omega coefficients (Total DTBP score: α = 0.92, ω = 0.92; MDTBP = 2.91, SD = 1.44). The factor loadings and item-total correlations are presented in Table 1.

Parallel analysis plot for determining the number of factors in the DTBP (Study 1)

Table 1Factor loadingsItemsFactorItem Total Correlations1. It is important to me that people who look at my [social media] profile see that I have many friends.672.6472. I want my [social media] profile to reflect my popularity in real life.644.6283. I want my [social media] profile to show that many people like me.695.6764. It is important to me that other people see on my [social media] profile how good my social life is.797.7725. I want people who look at my [social media] profile to see that I have close friends.717.6876. I want people who look at my [social media] profile to see that I spend a lot of time with my friends.866.8147. On my [social media] profile, I want others to see that I have a lot of fun with my friends.852.7908. On my [social media] profile, I want others to see that I am part of a great group of friends.834.782

Factor loadings

In the figure representing Study 1, the solid line shows the observed eigenvalues ​​obtained from the correlation matrix of the DTBP items. The dashed line shows the eigenvalues ​​generated from simulated random data of the same sample size, carried out in a parallel analysis. Factors where the observed eigenvalues ​​were greater than the simulated eigenvalues ​​were retained. As shown in the figure, only the first observed eigenvalue was greater than the simulated eigenvalue. This finding supports the one-factor solution for the Turkish version of DTBP.

Convergent and discriminant validity

For the convergent and discriminant validity, the relationship between DTBP and general belongingness was examined. An EFA analysis was carried out using all items of the DTBP and general belongingness scale (maximum likelihood estimation method and oblimin rotation). Parallel analysis was carried out to determine the number of factors. The items were precisely grouped in accordance with their theoretical differentiation, with all eight DTBP items loading on the first factor, and the acceptance and rejection dimension items of general belongingness on the second and third factors (model fit: χ 2 (117) = 2.38, p < 0.001, CFI = 0.95, TLI = 0.93, RMSEA = [90% CI] = 0.06 [0.05, 0.07], SRMR = 0.03). This finding provides initial empirical evidence that the DTBP is distinct from the dimensions of general belongingness. DTBP was positively related with rejection dimension (r = 0.12, 95% CI [0.02, 0.22], p < 0.05), but was not associated with acceptance (r = 0.06, 95% CI [−0.04, 0.17], p = 0.223) or the general belongingness total score (r = −0.03, 95% CI [−0.14, 0.07], p = 0.515). Furthermore, we observed no significant correlation between the GB total score and acceptance, while a weak correlation was identified with the rejection dimension. This suggests that these constructs were conceptually related but not identical and provide exploratory support for the possibility that DTBP is a construct that is distinct from GB.

Concurrent validity

To analyze concurrent validity, a series of hierarchical regression analyses were conducted. For this, the potential connection between DTBP and Instagram usage was evaluated, independent of overall general belongingness.

Similar to the original study, a series of hierarchical regression analyses were conducted to determine the concurrent validity of the Turkish version of DTBP (see also Table 2). The first step of all analyses included DTBP in the model, while the second step included the GB total score. The dependent variables included the excessive Instagram usage total score, the number of followers, the number of accounts followed, and the daily duration of use of Instagram (in minutes). Since the number of followers, number of accounts followed, and daily use were not normally distributed, log transformation was applied prior to the analyses. Both DTBP and GB were significantly associated with excessive Instagram usage and the number of followers. However, DTBP was positively associated with excessive Instagram usage, whereas general belongingness was negatively associated with it. Both DTBP and general belongingness were positively associated with the number of followers. We next carried out a hierarchical regression analysis where the addition of GB to the regression model in the second step resulted in a significant increase in explaining excessive Instagram use (ΔR2 = 0.080, Fchange (2, 361) = 41.81, p < 0.001). The effect size of this increase was small-to-moderate according to Cohen's f2 measure (f2 = 0.116). The contribution of GB to the follower count was smaller (ΔR2 = 0.025, Fchange (2, 346) = 9.68, p = 0.002; f2 = 0.028). Only DTBP showed positive associations with the number of accounts followed and daily usage (in minutes). The additional contribution of GB towards the number of accounts followed (ΔR2 = 0.006, p = 0.127, f2 = 0.006) and daily usage time (ΔR2 = 0.010, p = 0.055, f2 = 0.011) was not statistically significant, and the effect sizes were minimal. Thus, a high DTBP scale score was associated with high to excessive Instagram usage and duration of daily use. A larger number of followers and accounts followed was also associated with a higher DTBP score (Table 2). We next took into account the risk of Type-I errors that may arise from multiple testing. For this, the p-values ​​for the GB variable were corrected using the Benjamini–Hochberg False Discovery Rate (FDR, q = 0.05) method in the second step of the hierarchical regression analysis [50]. The trend of the data remained robust following the FDR correction. The effects of excessive Instagram usage and number of followers remained statistically significant, whereas the contributions to the number of accounts followed and daily usage duration did not reach statistical significance.

Table 2Hierarchical linear regressions assessing the effect of DTBP and general belongingness on excessive Instagram usage and Instagram usage habits (Study 1)Excessive Instagram UsageβtpR2R2 changeFchangepStep 1 Intercept-20.36 <.001.228.228106.70 <.001 DTBP.47710.33 <.001Step 2 Intercept-14.26 <.001.308.08041.81 <.001 DTBP.46710.67 <.001 GB-.283−6.47 <.001Number of followersStep 1 Intercept49.12 <.001.092.09235.09 <.001 DTBP.3035.92 <.001Step 2 Intercept-16.82 <.001.117.0259.68.002 DTBP.3056.03 <.001 GB.1573.11.002Number of accounts followedStep 1 Intercept-55.04 <.001.046.04617.30 <.001 DTBP.2144.16 <.001Step 2 Intercept-19.97 <.001.052.0062.34.127 DTBP.2164.21 <.001 GB.0791.53.127Daily use (minute)Step 1 Intercept-49.15 <.001.062.06223.66 <.001 DTBP.2504.86 <.001Step 2 Intercept-20.86 <.001.072.0103.70.055 DTBP.2464.82 <.001 GB-.098−1.92.055DTBP Desire to belong publicly scale, GB general belongingness

Hierarchical linear regressions assessing the effect of DTBP and general belongingness on excessive Instagram usage and Instagram usage habits (Study 1)

DTBP Desire to belong publicly scale, GB general belongingness

Study 2

Study 1 examined the psychometric properties of the Turkish version of the DTBP. The aim of Study 2 was to replicate the results obtained in Study 1. For this purpose, a confirmatory factor analysis was carried out for DTBP. In addition, the results obtained in Study 1 regarding the convergent-discriminant and concurrent validity of the scale were replicated. Study 2 used the same procedure and measurement tools as Study 1.

Method

Participants

The study was carried out with active Instagram users who were university students studying at a state university in Türkiye. A total of 272 participants aged 18–46 years were included in this study (Mage = 21.91, SD = 3.09). Thirty-nine male (14.3%) and 233 female (85.7%) participants were included, who were selected using the convenience sampling method. Sample sizes were determined pragmatically, aiming to satisfy widely used recommendations for factor-analytic studies (e.g., absolute minimum sample sizes and participant-to-variable ratios) and to ensure stable EFA/CFA estimation across independent samples [45–47]. All participants were provided with an informed consent form that outlined the specifics of the research. The study sample consisted of participants who willingly volunteered, completed the approval form, and provided their agreement to participate in the study.

Measures

Personal information form

The same personal information form as in Study 1 was used.

The DTBP Scale

The DTBP scale was developed by Büttner et al. [7] to measure the desire to belong publicly levels of individuals. Study 1 revealed that the Turkish version of the scale displayed a single factor structure. Both Cronbach Alpha and McDonald Omega reliability coefficients of the scale were calculated as 0.93 (MDTBP = 2.65, SD = 1.40).

General belongingness scale

In Study 2, the general belongingness scale used in Study 1 was used. The scale's reliability coefficients in Study 2 were found to be strong (Cronbach’s α = 0.92, McDonald’s ω = 0.93, M = 5.36, SD = 1.10; Cronbach’s α = 0.90, McDonald’s ω = 0.90, Macceptance = 5.32, SD = 1.12; Cronbach’s α = 0.90, McDonald’s ω = 0.91, Mrejection = 2.61, SD = 1.31).

Instagram addiction scale

The Instagram addiction scale used in Study 1 was also used in study 2. The scale's reliability coefficients in study 2 were identified to be strong (Cronbach’s α = 0.93, McDonald’s ω = 0.94, M = 2.39, SD = 0.77).

Procedure

Prior to the start of the study, an informed consent form stating the details of the research was provided to all participants. The data were collected through an online platform in April 2023 (Google Forms) in which the questions were presented in random order to prevent any order effect. The participants were asked whether they used Instagram or not, and participants who did not use it were excluded. Next, all participants were asked to complete the scales. For descriptive purposes, we also asked how long they had been using Instagram (M = 67.41 months, SD = 29.58, Range = 1–132), whether their Instagram profile was visible to everyone (6.6%) or set to private (93.4%), the average daily duration of the use of Instagram (M = 136.19 min, SD = 89.64, Range = 10–600), number of followers on Instagram (M = 306.07 followers, SD = 253.47, Range = 0–2300), and number of accounts they followed on Instagram (M = 354.84 followed, SD = 338.81, Range = 7–3637).

Results

Confirmatory factor analysis

A confirmatory factor analysis was conducted to test the single-factor structure obtained in Study 1. In Study 2, a confirmatory factor analysis (CFA) was conducted to examine the single-factor DTBP model. Although some fit indices were at an acceptable level (CFI = 0.94, SRMR = 0.05), the high RMSEA (RMSEA = 0.14) indicated that the model could not be adequately reproduced in this sample [51]. Therefore, the CFA results in Study 2 are reported for informational purposes only and were not used as the basis for fundamental inferences regarding the factor structure. Structural validity assessments were based on the EFA in Study 1 and on the CFA, model comparisons, and bifactor analyses in Study 3.

The reliability analyses of the one-factor structure were assessed with the Cronbach Alpha and McDonald Omega coefficients (Total DTBP score: α = 0.93, ω = 0.93; MDTBP = 2.65, SD = 1.40).

Convergent and discriminant validity

To re-examine the convergent and discriminant validity findings obtained in Study 1, exploratory factor analysis was conducted by considering all items of the DTBP and the general belongingness scale together (maximum likelihood estimation method and oblimin rotation). A parallel analysis was carried out to determine the number of factors. Similar to Study 1, the items were precisely grouped in accordance with their theoretical differentiation, with all eight DTBP items loading on the first factor, and acceptance and rejection dimension items in GB loading on the second and third factors (model fit: χ 2 (133) = 3.24, p < 0.001, CFI = 0.92, TLI = 0.89, RMSEA = [90% CI] = 0.09 [0.08, 0.10], SRMR = 0.04). This pattern shows that the discriminant structure obtained in Study 1 is repeated in Study 2. DTBP was not related with rejection dimension (r = 0.12, 95% CI [−0.01, 0.23], p > 0.05), but was negatively associated with acceptance (r = −0.14, 95% CI [−0.25, −0.02], p < 0.05) and GB total score (r = −0.14, 95% CI [−0.25, −0.02], p < 0.05). We observed that DTBP did not show a significant relationship with the rejection dimension but exhibited a weak and negative correlation with the acceptance dimension and the total GB score. This suggests that these structures are conceptually related but not identical and provide exploratory but replicable evidence that DTBP may be a divergent structure from GB.

Concurrent validity

To replicate concurrent validity, a series of hierarchical regression analyses were conducted. The purpose of these analyses was to examine the potential relationship between DTBP and Instagram usage, independent of overall GB.

In Study 2, a series of hierarchical regression analyses were conducted to replicate the concurrent validity of the Turkish version of DTBP examined (see also Table 3). The first step of all analyses included DTBP in the model, while the second step included the GB total score. The dependent variables included the excessive Instagram usage total score, the number of followers, the number of accounts followed, and the daily use of Instagram (in minutes). Since the number of followers, number of accounts followed, and daily use were not normally distributed, log transformation was applied before the analyses as in Study 1. Both DTBP and GB were significantly associated with excessive Instagram usage, the number of followers, and number of accounts followed. However, DTBP was positively associated with excessive Instagram usage, whereas general belongingness was negatively associated with it. Both DTBP and GB were positively associated with the number of followers, and number of accounts followed whereas only DTBP showed a positive association with the daily usage (in minutes). The addition of GB at Step 2 significantly increased the explained variance for excessive Instagram usage (ΔR2 = 0.036, Fchange (2, 269) = 12.32, p < 0.001, f2 = 0.046) and the number of followers (ΔR2 = 0.042, Fchange (2, 265) = 12.43, p < 0.001, f2 = 0.047). The Step 2 increment was smaller but significant for the number of accounts followed (ΔR2 = 0.021, Fchange (2, 266) = 5.95, p = 0.015, f2 = 0.022). In contrast, the increment in the duration of daily use was not significant (ΔR2 = 0.006, Fchange (2, 266) = 1.66, p = 0.199, f2 = 0.006). Furthermore, the multiplicity across the four Step 2 tests was addressed with the Benjamini–Hochberg FDR correction (q = 0.05), and the pattern of significance remained unchanged. Overall, a high DTBP scale score was related to more excessive Instagram usage and the duration of daily use. A larger number of followers and accounts followed were also associated with a higher DTBP score as presented in Table 3. Thus, this study replicated the concurrent validity tested in Study 1.

Table 3Hierarchical linear regressions assessing the effect of DTBP and general belongingness on excessive Instagram usage and Instagram usage habits (Study 2 and Study 3)Outcome VariableStudyStepPredictorβtpR2R2 changeFchangepExcessive Instagram Usage21Intercept-19.44 <.001.184-60.83 <.001DTBP.4297.80 <.0012Intercept-10.80 <.001.220.03612.32 <.001DTBP.4027.39 <.001GB-.191−3.51 <.00131Intercept-25.37 <.001.161-78.14 <.001DTBP.4018.84 <.0012Intercept-13.82 <.001.214.05327.49 <.001DTBP.3698.31 <.001GB-.233−5.24 <.001Number of Followers21Intercept-44.24 <.001.068-19.28 <.001DTBP.2604.39 <.0012Intercept-14.08 <.001.109.04212.43 <.001DTBP.2884.93 <.001GB.2073.53 <.00131Intercept-50.24 <.001.058-24.58 <.001DTBP.2414.96 <.0012Intercept-13.61 <.001.093.03515.14 <.001DTBP.2675.54 <.001GB.1883.89 <.001Number of Accounts Followed21Intercept-53.97 <.001.035-9.60.002DTBP.1873.10.0022Intercept-18.61 <.001.056.0215.95.015DTBP.2073.43 <.001GB.1472.44.01531Intercept-61.77 <.001.022-8.95.003DTBP.1472.99.0032Intercept-17.90 <.001.055.03314.22 <.001DTBP.1733.53 <.001GB.1843.77 <.001Daily Use (Minutes)21Intercept-46.32 <.001.021-5.67.018DTBP.1442.38.0182Intercept-18.84 <.001.027.0061.66.199DTBP.1332.18.030GB-.079−1.29.20031Intercept-61.13 <.001.041-17.59 <.001DTBP.2044.19 <.0012Intercept-22.34 <.001.047.0062.53.113DTBP.1933.94 <.001GB-.078−1.59.113DTBP Desire to belong publicly scale, GB general belongingness

Hierarchical linear regressions assessing the effect of DTBP and general belongingness on excessive Instagram usage and Instagram usage habits (Study 2 and Study 3)

DTBP Desire to belong publicly scale, GB general belongingness

Study 3

Studies 1 and 2 demonstrated that the DTBP scale is a valid and reliable measurement instrument within the Turkish context. Study 3 aimed to assess the test–retest reliability of the DTBP scale, conducted across a 4-week interval. Secondly, since certain confirmatory factor analysis fit indices of the DTBP scale were outside the acceptable range in Study 2, an additional the goal was to replicate the confirmatory factor analysis. This study also explored the relationships between personality traits, social comparison orientation, and perceived ostracism, which may be associated with DTBP.

Method

Participants

The study was carried out with active Instagram users who were university students studying at a state university in Türkiye. In this study, 410 participants aged 18–46 years were included (Mage = 23.84, SD = 5.05). Eighty-four males (20.5%) and 326 females (79.5%) participated, and the participants were selected using the convenience sampling method. Sample sizes were determined pragmatically, aiming to satisfy widely used recommendations for factor-analytic studies (e.g., absolute minimum sample sizes and participant-to-variable ratios) and to ensure stable EFA/CFA estimation across independent samples [45–47]. All participants were provided with an informed consent form that outlined the specifics of the research. The study sample consisted of participants who willingly volunteered, completed the approval form, and provided their agreement to participate.

Measures

Personal information form

The same personal information form as in Study 1 and Study 2 was used.

Desire to belong publicly (DTBP) scale

DTBP was developed by Büttner et al. [7] to measure desire to belong publicly levels of individuals. Study 1 and Study 2 revealed that the Turkish version of the scale displayed a single factor structure. Both Cronbach Alpha and McDonald Omega reliability coefficients of the scale were calculated as 0.93.

The big five inventory

The Big Five Inventory was developed by Benet-Martinez and John [52] and adapted to the Turkish by Sümer and Sümer [53]. The scale is a 5-point Likert scale ranging from strongly disagree (1) to strongly agree (5). The scale consists of 44 items (e.g., tends to be quiet, tends to be lazy, worries a lot) and five-factors, namely, extraversion, agreeableness, conscientiousness, neuroticism, and openness. The Cronbach's Alpha and McDonald's ω reliabilities of the five-factor personality dimensions in this study are shown in Table 4.

Table 4Fit indices for competing measurement models (Study 3)Modelχ2dfCFITLIRMSEA [90% CI]BICAICOne-Factor (Proposed)62.6820.982.975.072 [.05,.09]11,04210,946Two-Factor50.1719.987.981.063 [.04,.09]11,03610,935Bifactor Model33.3812.990.976.067 [.04,.09]11,06110,933

Fit indices for competing measurement models (Study 3)

The Iowa-Netherlands comparison orientation measure

The Iowa-Netherlands Comparison Orientation Measure was developed by Gibbons and Buunk [54], and adapted to the Turkish by Teközel [55]. The scale aims to assess social comparison orientation and is a 5-point Likert type ranging from strongly disagree (1) to strongly agree (5). The scale consists of 11 items (e.g., I often compare myself with others with respect to what I have accomplished in life) and two-factors, namely, ability comparisons, opinion comparisons. The total social comparison orientation score was used in the current study. The Cronbach's Alpha and McDonald's ω reliability of the social comparison orientation in this study are shown in Table 4.

General belongingness scale

The General Belongingness Scale used in Studies 1 and 2 was also used in Study 3. The scale showed strong reliability coefficients in the current study as well (Cronbach’s α = 0.81, McDonald’s ω = 0.85, M = 5.40, SD = 1.02; Cronbach’s α = 0.85, McDonald’s ω = 0.85, Macceptance = 5.30, SD = 1.14; Cronbach’s α = 0.86, McDonald’s ω = 0.86, Mrejection = 2.51, SD = 1.18).

Instagram addiction scale

The same Instagram Addiction Scale was used as in Studies 1 and 2. The scale showed strong reliability coefficients in Study 3 as well (Cronbach’s α = 0.93, McDonald’s ω = 0.93, M = 2.38, SD = 0.77).

Ostracism experience scale

The Ostracism Experience Scale was developed by Gilman et al. [56], and adapted to the Turkish by Sertelin-Mercan [57]. The scale is a 5-point Likert type ranging from never (1) to always (5) and consists of 11 items (e.g., In general, others treat me as if I am invisible) and two-factors, namely, ignored, exclusion. The Cronbach's Alpha and McDonald's ω reliabilities of the dimensions determined in the current study are shown in Table 4.

Procedure

Prior to the start of the study, an informed consent form stating the details of the research was provided to all participants. The data were collected through an online platform in May 2023 (Google Forms) in which the questions were presented in random order to prevent any order effect. The participants were asked whether they used Instagram or not, and participants who did not use the social media platform were excluded. Next, all participants completed the scales. For descriptive purposes, we also asked how long the participant had been using Instagram (M = 68.92 months, SD = 30.16, Range = 1–144), whether their Instagram profile was visible to everyone (10%) or set to private (90%), average daily Instagram usage time (M = 132.00 min, SD = 90.27, Range = 1–900), number of followers on Instagram (M = 422.33 followers, SD = 1181.69, Range = 3–16,010), and number of accounts they follow on Instagram (M = 385.51 followed, SD = 333.08, Range = 2–3771).

Results

Common method bias

Since all variables were measured from the same self-report source, the risk of common method bias was assessed using the Harman one-factor test. In each study, all items were included in a one-factor exploratory factor analysis without rotation. The variance explained by the first factor was 26.0% in Study 1, 26.1% in Study 2, and 13.9% in Study 3, well below the recommended 50% threshold [58]. These findings indicate that there is no significant common method bias in the measurements.

Confirmatory factor analysis and model comparison

A confirmatory factor analysis was conducted to test and replicate the single-factor structure obtained in Study 1 and Study 2. The confirmatory factor analysis fit indices for the DTBP were as follows: χ2 = 62.68, df = 20, χ2/df = 3.13, p < 0.001, CFI = 0.98, NFI = 0.97, TLI = 0.97, IFI = 0.98, RMSEA = 0.07, SRMR = 0.02. Excellent fit indices were obtained by the model. The reliability analyses of the one-factor structure were assessed with the Cronbach Alpha and McDonald Omega coefficients (Total DTBP score: α = 0.93, ω = 0.93; MDTBP = 2.72, SD = 1.49).

The single-factor structure obtained in Study 1 was tested with CFA in Study 3. In Study 3 we, compared the single-factor structure proposed for the Turkish sample with the original two-factor structure and the bifactor model (see also Table 4). Although the two-factor model showed good fit (χ2 = 50.17, CFI = 0.987), the correlation between the factors was found to be quite high (r = 0.96). This indicates weak discriminant validity. Moreover, a comparison of the one-factor model (χ2 (20) = 62.68, CFI = 0.982) with the two-factor model (χ2 (19) = 50.17, CFI = 0.987) suggested a significantly better fit (Δ χ2 (1) = 12.51, p < 0.001) with the two-factor structure. However, the very small increase in CFI (ΔCFI = 0.005) indicates that the difference between the two models was not significant in practical terms. Thus, the two-factor structure did not provide any significant psychometric advantage over the one-factor model. Furthermore, to examine whether the quantity-quality distinction in the original scale was empirically discernible in the Turkish context, a bifactor CFA was conducted in Study 3. In this model, a general DTBP factor, loaded by all items, and two group factors representing the quantity and quality dimensions were defined. The findings showed that all items loaded strongly onto the general factor (standardized loadings ranged from 0.62 to 0.88). In contrast, the loadings for the group factors were quite low. While loadings on the quantity dimension ranged from 0.00 to 0.17, only one item loaded moderately (0.45) on the quality dimension, with the others falling below 0.20. This suggests that when the general DTBP factor was controlled for, any additional variance that could be explained by the quantity and quality dimensions was negligible. The remarkably high correlation (r = 0.96) between quantity and quality factors in the two-factor CFA indicates that the DTBP operates as an essentially one-dimensional structure in the Turkish sample (χ2 = 62.68, CFI = 0.982, RMSEA = 0.072), reflecting an integrated expression of public belonging, rather than two separate dimensions.

We next assessed whether the DTBP scale measured the same construct between female and male participants. For this, the measurement invariance was tested using multigroup CFA. First, a configurational model demonstrating construct equivalence was estimated, followed by a metric model testing the equality of factor loadings, and finally a scalar model testing the equality of cutoff points. The findings showed that the differences in CFI between the configurational model (CFI = 0.978), the metric model (CFI = 0.979), and the scalar model (CFI = 0.979) were less than 0.01 (ΔCFI ≤ 0.001) [59]. This indicates that the DTBP items were answered with the same psychological meaning by both females and males and that the scale maintained measurement invariance between the genders.

Convergent and discriminant validity

We next tested whether DTBP was related to, but distinct from, GB. For this, a three-factor CFA was carried out including DTBP, and the acceptance and rejection dimensions of GB. Due to the ordinal nature of the items, the WLSMV (DWLS) estimator was initially attempted, but due to numerical convergence issues, the analyses were completed using ML-robust estimation, and the results remained unchanged in estimator sensitivity checks. The model showed a satisfactory fit (CFI = 0.964, TLI = 0.959, RMSEA = 0.048, SRMR = 0.046).

The Average Variance Extracted (AVE) for DTBP was found to be 0.626, which is above the recommended threshold of 0.50. According to the Fornell-Larcker criterion, √AVE (~ 0.79) for DTBP was significantly larger than the latent correlations with the acceptance (r = −0.13) and rejection (r = 0.20) dimensions. Furthermore, the Heterotrait-Monotrait (HTMT) ratios were 0.104 for DTBP-acceptance and 0.110 for DTBP-rejection, both were well below the limit of 0.85. This suggests that DTBP was conceptually related to GB but empirically distinct from it [60, 61].

Similar to the original study [7], the relationship between DTBP and certain variables such as personality, social comparison orientation and additionally perceived ostracism were examined for better understanding (see also Table 5). In the original DTBP study, the authors computed partial correlations, controlling for the four remaining personality traits when testing the correlation with the fifth one, most likely because different personality traits might share some common variance. A similar procedure was also followed in the current study. A positive, statistically significant relationship was found between DTBP and extraversion (r = 0.10, 95% CI [0.01, 0.20], p < 0.05). A negative significant relationship was found between consciousness and DTBP (r = −0.13, 95% CI [−0.23, −0.04], p < 0.01). However, no significant relationship was found between DTBP and other personality traits (agreeableness: r = −0.03, 95% CI [−0.17, 0.02], p = 0.139, openness: r = 0.04, 95% CI [−0.03, 0.16], p = 0.198, neuroticism: r = 0.06, 95% CI [−0.03, 0.16], p = 0.188). DTBP was positively related with social comparison orientation (r = 0.20, 95% CI [0.11, 0.29], p < 0.001). This finding suggests that individuals with high DTBP scores may also have a high tendency for social comparison. Moreover, we investigated the relationship between the ostracism scale and DTBP. DTBP was positively related with the ignored dimension (r = 0.10, 95% CI [0.01, 0.20], p < 0.05) (perceived ostracism), but was not related to the exclusion dimension (r = −0.04, 95% CI [−0.13, 0.06], p = 0.441) (perceived social exclusion). This may ultimately indicate that individuals who are ignored or perceive ostracism may have a desire to display their belongingness on social media as presented in Table 5.

Table 5Correlations between variables and descriptive statistics (Study 3)123456789101112131415161DTBP-2Acceptance-.11*-3Rejection.13**-.52***-4GB-.14**.87***-.87***-5Extraversion.10*.24***-.26***.29***-6Consciousness-.13**.22***-.29***.29***.25***-7Agreeableness-.07.17***-.27***.25***.16***.37***-8Openness.06.17***-.12*.16***.49***.22***.10*-9Neuroticism.06-.21***.23***-.25***-.24***-.24***-.19***-.15***-10SCO.20***-.06.20***-.15**-.02-.18***-.16***.01.18***-11Ignored.10*-.47***.60***-.61***-.20***-.27***-.20***-.14**.14***.12*-12Exclusion-.04-.41***.39***-.46***-.33***-.18***-.14***-.23***.13***.07.43***-13EIU.40***-.18***.31***-.28***-.12*-.34***-.16***-.09.22***.33***.30***.13**-14Instagram followers.24***.10*-.16***.15**.22***.05.14**.16***-.08-.02-.15**-.26***.11*-15Instagram accounts followed.15**.14**-.14**.16***.17***.07.08.08-.05.07-.11*-.20***.14**.67***-16Daily use (min).20***-.09.10-.10*.01-.14**-.11*-.04.12*.09-.02-.05.45***.22***.28***-M2.725.432.465.493.253.533.123.672.963.081.582.542.28422.33385.51132SD1.491.151.161.010.500.460.370.630.440.540.670.750.731181.7333.0890.27α.93.85.84.88.81.74.70.82.76.82.87.81.92---ω.93.85.85.88.81.73.69.83.76.82.88.82.92---DTBP Desire to belong publicly, GB general belongingness, SCO Social comparison orientation, EIU Excessive Instagram usage, M mean, SD standard deviation, α = Cronbach Alpha, ω = McDonald Omega

Correlations between variables and descriptive statistics (Study 3)

DTBP Desire to belong publicly, GB general belongingness, SCO Social comparison orientation, EIU Excessive Instagram usage, M mean, SD standard deviation, α = Cronbach Alpha, ω = McDonald Omega

Concurrent validity

To replicate the concurrent validity observed in Study 1 and 2, a series of hierarchical regression analyses were carried out to examine the potential connection between DTBP and Instagram usage, independent of overall GB (see also Table 3).

Additionally, a series of hierarchical regression analyses were carried out to replicate the concurrent validity of the Turkish version of the DTBP scale examined in Studies 1 and 2. The first step of all analyses included DTBP in the model, while the second step included the GB total score. The dependent variables included the excessive Instagram usage total score, the number of followers, the number of accounts followed, and the daily use of Instagram (in minutes). Since the number of followers, number of accounts followed, and daily use were not normally distributed, log transformation was applied prior to the analyses as in Studies 1 and 2. Both DTBP and GB were significantly associated with excessive Instagram usage, the number of followers, and number of accounts followed. However, DTBP was positively associated with excessive Instagram usage, whereas GB was negatively associated with it. Both DTBP and GB were positively associated with the number of followers, and the number of accounts followed. Nevertheless, only DTBP showed a positive association with daily Instagram usage (in minutes). The adding of GB at Step 2 produced significant increments for excessive Instagram usage (ΔR2 = 0.053, Fchange (2, 407) = 27.49, p < 0.001; f2 = 0.067), number of followers (ΔR2 = 0.035, Fchange (2, 398) = 15.14, p < 0.001; f2 = 0.039), and number of accounts followed (ΔR2 = 0.033, Fchange (2, 403) = 14.22, p < 0.001; f2 = 0.035). The increment for daily use duration was not significant (ΔR2 = 0.006, Fchange (2, 406) = 2.53, p = 0.113; f2 = 0.006). The Benjamini–Hochberg FDR correction (q = 0.05) was also applied across the four Step 2 tests in Study 3, and results remained unchanged. Overall, a high DTBP scale score was associated with excessive Instagram usage and a high duration of daily use. A larger number of followers and accounts followed were also associated with a higher DTBP scale score. Therefore, Study 3 could also replicate the concurrent validity tested in Studies 1 and 2.

Test–retest reliability after four weeks

To assess the test–retest reliability of the DTBP, a group of individuals (N = 85) from Study 2 was re-evaluated with the DTBP scale four weeks later as a part of Study 3. The findings indicated a significant positive correlation between the two DTBP scale measurements (r = 0.80, 95% CI [0.71, 0.87], p < 0.001).

Discussion

A total of three different studies were conducted in the current research to adapt the DTBP scale to the Turkish and evaluate its psychometric properties and were found to be appropriate. The Turkish version of the DTBP scale was found to have a single-factor structure, in contrast to the original study [7]. One possible interpretation is that the desire for public belonging may be experienced more holistically within the Turkish cultural context. In relatively collectivist cultural contexts like Türkiye, motivations for social acceptance/approval, maintenance of relationships, avoidance of exclusion, and being positively perceived within a group are often intertwined rather than experienced independently. Therefore, the tendency of individuals to demonstrate their belonging on social media may have been perceived as a single integrated motivation. From this perspective, this cultural interconnectedness may help explain the emergence of a single-factor structure in the Turkish form of the scale. It also suggests that the sub-dimensions of the DTBP scale may be integrated into a single factor rather than be separated, depending on the cultural context. However, this interpretation should be approached cautiously. Although collectivistic cultural integration may offer one possible explanation for the observed one-factor structure, alternative explanations should also be considered, including translation-related influences, adaptation-specific effects, sample characteristics, and platform-specific patterns of Instagram usage. Importantly, the present data cannot distinguish among these explanations. Therefore, these interpretations should be considered provisional, and future cross-cultural validation studies are needed to evaluate these possibilities more directly. The elevated RMSEA observed in Study 2 may likewise reflect sample specific characteristics rather than a fundamental problem with the proposed structure. One possible explanation is that CFA fit indices may vary across independent samples, particularly when relatively brief scales are evaluated and small differences in response patterns influence global fit statistics such as RMSEA. It is also possible that minor adaptation or translation-related nuances contributed to differences in how the model reproduced across studies. Additionally, because the samples consisted of relatively homogeneous groups of university students and Instagram users, contextual characteristics specific to Study 2 may have influenced model fit. Nevertheless, these possibilities remain speculative and cannot be directly evaluated with the current data. Therefore, the Study 2 findings were interpreted cautiously and were not used as the primary basis for structural validity conclusions. Instead, greater emphasis was placed on the converging evidence obtained from the EFA in Study 1 and the CFA, model comparison, and bifactor analyses in Study 3, which consistently supported the proposed one-factor structure. Furthermore, the test–retest reliability was found to be quite high when conducted after a four-week interval. These results suggest that the Turkish version of the DTBP scale is also a valid and reliable measurement instrument for assessing individual differences in the tendency to make one's sense of belonging visible on social media.

Summary of results

Similar to the original study for convergent and discriminant validity, DTBP was found to be associated with GB. Nonetheless, it was found to be a distinct concept in all three studies. This distinction can be attributed to the fact that DTBP emphasizes the external visibility of belonging on image-based social media platforms, whereas GB is a more internal and experiential process. Consequently, the results suggest that DTBP may represent a conceptually distinct tendency related to the public expression of belonging on image-based social media platforms rather than a wholly novel motivational construct.

The current study identified significant positive relationships between DTBP and excessive Instagram use, as well as Instagram usage habits. Our findings are overall consistent with similar research conducted in Türkiye. For example, negative emotional states such as loneliness and psychological distress were shown to be associated with problematic social media use in a Turkish sample. From this perspective, DTBP may be interpreted as a belongingness-related self-presentational tendency in which the visible expression of social connectedness may also be associated with perceived social acceptance [13]. Our data also suggest that DTBP may be associated with behaviors and habits related to Instagram usage. Positive correlations between DTBP and factors such as excessive Instagram use, follower count, number of followed accounts, and daily duration of Instagram usage suggest that DTBP may represent an important framework for understanding visible belonging behaviors among Instagram users and within image-based social media contexts. The relationship between DTBP and social media usage habits indicates that this framework can serve as a useful tool for a better comprehension of visible belonging behaviors on image-based social media platforms. A comparable outcome was observed in the original study of the scale for both Facebook and Instagram [7].

The results of Study 3 indicated a positive correlation between DTBP and perceived ostracism. However, no association was found with the dimension referred to as perceived social exclusion [62, 63]. A positive correlation between DTBP and perceived ostracism, which is manifested as being ignored, is expected [64, 65]. Individuals experiencing high levels of perceived ostracism may seek to demonstrate their social relationships through social media as a means of mitigating the adverse effects associated with ostracism [66–68]. Büttner et al. [7] asserted that showcasing an individual’s belonging on social media can facilitate the formation of new relationships or group memberships by communicating the message, “I am someone worth having a relationship with,” to others. This view also appears to be consistent with both social identity theory and signaling theory [39, 40, 43, 44]. The current study found a significant positive relationship between DTBP and social comparison orientation, which aligns with the original study of the scale. Büttner et al. [7] indicated the presence of a significant positive relationship between the propensity for social comparison and DTBP. Interactions including tagging, liking, and sharing of photos, videos and stories on social media, can enhance an individual's perception of social acceptance. Burrow and Rainone [69] reported a positive correlation between the number of likes an individual receives and their level of self-esteem. Individuals with increased DTBP levels may prioritize external feedback and engage in social comparisons.

The relationship between personality traits and DTBP (Study 3) was also examined in the current study. We observed that DTBP was positively correlated with extraversion and negatively correlated with conscientiousness. Additionally, DTBP was not significantly correlated with openness to experience, neuroticism, or agreeableness. The current study identified a negative, statistically significant correlation between DTBP and consciousness, in contrast to the original study. These findings indicate that DTBP may be relatively high in individuals who are extroverted but have lower levels of self-discipline and organization. Seidman [4] reported that individuals exhibiting high extrovert traits utilized Facebook more frequently for interpersonal communication. The same study asserted that self-presentational actions and motivations were correlated with lower levels of conscientiousness. These findings support the association between DTBP and personality, as determined in Study 3.

Overall, the current study shows that the Turkish version of DTBP is a functional and original concept for understanding an individual’s desires and motivations to present themselves and express their sense of belonging on Instagram within the Turkish context. The DTBP scale provides a potentially useful measurement tool for understanding individual differences in the tendency to make belonging publicly visible among Instagram users.

Theoretical contributions and conceptual framework

DTBP behavior might be explained with social identity and signaling theory as mentioned before. On the other hand, the role of DTBP in understanding behaviors on image-based social media platforms may be directly related to three different theoretical frameworks. These are: self-presentation theory [70], need to belong theory [5], and impression management [71]. According to the self-presentation theory, individuals can use various “staging” strategies to create and manage certain impressions in social life. Social media has now transferred this stage to the within Instagram context, where individuals can make their belongings visible through methods such as photos, stories, and tagging. The DTBP is a strategic concept that emphasizes the importance of belonging when presenting oneself in the Instagram.

The need to belong theory states that one of the basic needs of an individual is their desire to establish meaningful and lasting relationships with other people [5]. DTBP, however, is associated not just with the need for belonging, but also with the wish to show it publicly. Indeed, the current research asserts that while DTBP shares similarities with GB, it represents a distinct concept. Overall, DTBP may serve as a framework for understanding visible belonging by emphasizing the public expression of belonging rather than the experience of belonging itself. Conceptually, however, DTBP should not be considered identical to general belongingness, impression management, or social validation seeking. Rather, DTBP may be conceptualized as a belongingness-related self-presentational tendency involving the public signaling of social connectedness. Future research should further examine the conceptual boundaries of DTBP and evaluate whether it demonstrates incremental validity relative to related constructs such as need for popularity, contingent self-worth, impression management, self-monitoring, and broader social validation tendencies.

Finally, when viewed from the perspective of impression management theory, social media platforms such as Instagram, Facebook, X may provide individuals with more visible and controllable opportunities to shape how they are perceived by others online. Individuals with high levels of DTBP may be on Instagram not only to start new relationships, make friends, and join groups, but also to show that they are socially accepted and valuable individuals. From this perspective, DTBP may also contribute to understanding how individuals manage and display their social identities in online environments. Considering the three theoretical frameworks together enhances our understanding of the position of DTBP. People may shape their social media behaviors and attitudes to organize their self-presentation, display their belonging, and create a positive impression in digital environments. In this respect, the DTBP framework may provide a useful conceptual structure for understanding motivations related to the public display of belonging on Instagram.

Strengths and implications

The current study examined the effectiveness of the DTBP scale among the users of the image-based platform Instagram [30, 31]. One of the most important reasons for this effort is that Türkiye (where the current study was conducted) ranks fifth in the world in Instagram usage [72]. In addition, Instagram is the most popular social media platform among young individuals. However, the relevance of DTBP extends beyond Instagram to other social media platforms such as Facebook [7]. We can assert that DTBP serves as a valid measurement tool for text-based social media platforms such as X. While it is possible to visually demonstrate belonging with photos and videos, it is also possible to express the same sentiment in writing. Specifically, expression of belonging to a specific group can serve as an alternative method of demonstrating belongingness. However, future studies are needed to substantiate this. DTBP can be considered as an important variable for coping with excessive social media use and for digital self-presentation and is therefore important for a better understanding of the behavior and attitudes of individuals on social media. From a practical perspective, the concept of DTBP provides a functional framework, especially for mental health professionals engaged with adolescents and young adults. Counselors and psychologists can establish the likelihood of tendencies for social comparison and the associated emotional challenges (e.g., ostracism, social exclusion, peer rejection, problematic social media use) in individuals exhibiting elevated DTBP levels. Teachers can include topics like digital self-presentation and visible belonging in their programs and activities when teaching digital literacy. These activities can help younger people to evaluate their reasons for using social media in a healthier way. In a broader sense, social media sites can provide users more control over how visible their posts are, which may make users with high DTBP levels less likely to want to show belongingness publicly. However, when evaluating the theoretical and applied implications of this research, we should consider the strength of the findings in the context of the study sample, which was predominantly composed of young adult female university students who were using Instagram. Thus, DTBP may not show similar patterns in other age groups or on different social media platforms (e.g., TikTok or X). Future studies with a more balanced sample profile and in different platform contexts will clarify the generalizability and cross-platform validity of DTBP.

Limitations

The current study has some limitations in addition to its contributions. First, the fact that the samples of all three studies consisted of university students and only active Instagram users limits the generalizability of the findings. In addition, the samples were predominantly female, which may further limit the generalizability of the findings across different demographic groups. Although measurement invariance analyses supported construct equivalence across gender, the unequal subgroup sizes should still be considered when interpreting these findings. Future studies with more balanced and diverse samples, including older adults, male-dominant groups, and clinical or community-based populations, as well as different platform contexts, will help establish the generalizability and cross-platform validity of DTBP. Moreover, all data in these three studies were based on self-report measures, which may limit the accuracy of the results due to factors such as social desirability bias and common method bias. In addition, because the study was cross-sectional, causal relationships between variables could not be inferred. Future research should explore different age groups and social media platforms (e.g., image-based and text-based environments, including TikTok and X) and should evaluate DTBP not only with self-report scales but also with behavioral indicators. For instance, researchers can discern the relationship between DTBP and Instagram-related or platform-specific visible belonging behaviors more objectively by using data such as the actual number of posts, the frequency of receiving likes and comments, follower and following counts, daily screen time, and tagging behavior [73]. Second, the current study did not include content-based indicators that directly reflect visible belonging behaviors on Instagram (e.g., relationship/family/group emphasis in posts, frequency of tagging, or belonging-related themes in shared content). Therefore, it is not possible to identify which types of content are more strongly associated with DTBP. In this regard, combining self-report data with digital trace data or content analysis may increase the explanatory power of DTBP in predicting visible belonging behaviors on Instagram. Finally, DTBP was assessed at a single measurement time point, providing limited information about its long-term stability. Experimental and longitudinal research designs may be designed in the future to examine the behavioral and emotional outcomes associated with DTBP in greater detail and test whether DTBP can prospectively predict maladaptive social media use and related psychosocial outcomes over time. Furthermore, experimental studies can shed light on the causal mechanisms of the concept by examining the behavioral consequences of DTBP under manipulations such as ostracism (e.g., being ignored), social approval (e.g., receiving likes), or visibility settings.

Conclusion

The current study contributes to the relevant existing literature in three main ways. Theoretically, the DTBP concept attempts to explain individuals' motivations for displaying their sense of belonging through image-based social media platforms such as Instagram. The DTBP scale serves as a novel conceptual framework in both theoretical and applied domains and describes an individual’s desires to make their sense of belonging visible and to demonstrate it via the Instagram. DTBP serves as a significant theoretical framework for analyzing digital self-presentation of an individual in the context of Instagram, describing how they express their need for belonging along with the fundamental motivations that drive their social media engagement. Psychometrically, three different studies conducted in the capacity of the current research could effectively adapt the DTBP scale in the Turkish context, establishing that the Turkish version of the scale was a valid and reliable measurement instrument. Moreover, DTBP can also be used as a functional measurement tool in clinical and educational applications to better understand problematic social media use, social comparison, and digital self-presentation behaviors.

Acknowledgements

Not applicable.

Abbreviations

Akaike Information Criterion

Average Variance Extracted

Bayesian Information Criterion

Confirmatory factor analysis

Comparative Fit Index

Confidence interval

Degree of freedom

Diagonally Weighted Least Squares

Desire to belong publicly

Explanatory factor analysis

False Discovery Rate

General belongingness

Heterotrait-Monotrait

Kaiser-Meyer-Olkin

Mean

Maximum Likelihood

Root Mean Square Error of Approximation

Standard deviation

Standardized Root Mean Square Residual

Tucker-Lewis Index

Weighted Least Squares Mean and Variance Adjusted

Authors’ contributions

The author is the sole contributor to the conception, design, data collection, analysis, interpretation, and writing of this manuscript. The author read and approved the final manuscript.

Funding

The author did not receive support from any organization for the submitted work.

Data availability

The datas (Study 1, 2, and 3) supporting the findings of this research are publicly available at the Open Science Framework (OSF) repository: [https://osf.io/jhdtx/]

Declarations

Ethics approval and consent to participate

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the Ethical Committee of the Necmettin Erbakan University (Approval Date: 10.03.2023, Approval Number: 2023/105). Prior to data collections, informed consent was obtained from all participants using an informed consent form, and only volunteers were included in the studies.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

Associated Data

Data Availability Statement

The datas (Study 1, 2, and 3) supporting the findings of this research are publicly available at the Open Science Framework (OSF) repository: [https://osf.io/jhdtx/]