When Interaction Becomes Addiction: The Psychological Consequences of Instagram Dependency

Abstract

The purpose of the present research is to analyse the negative outcomes associated with the excessive Instagram dependency of those users that access the application through their smartphones. An empirical study was conducted through online interviews using structured questionnaires, resulting in 342 valid responses, with the target population being young users over 18 years old who access Instagram daily. Research shows that dependency on Instagram is primarily driven by individuals’ need for orientation and understanding, with entertainment being a secondary motivation. The results indicate that dependency on the social network is positively associated with excessive use, addiction, and Instastress. Furthermore, excessive use contributes to personal and social problems and increases both stress levels and mindfulness related to the platform. In turn, this excessive use intensifies addiction, which functions as a mediating variable between overuse and Instastress, mindfulness, and emotional exhaustion. This study offers valuable insights for academics, mental health professionals, and marketers by emphasizing the importance of fostering healthier digital habits and developing targeted interventions.

1. Introduction

In today’s digital society, constant connectivity has made the intensive use of social media platforms a common activity [1]. The increased time spent on platforms intensifies social interactions and strengthens consumer–brand relationships, ultimately influencing purchase intentions [2,3]. Nevertheless, despite these advantages, concerns have been raised regarding the potential adverse effects of social media usage [4], since these platforms are intentionally designed to maximise engagement and thus may foster addictive behaviours.

Excessive social media use can harm mental health, leading to anxiety, depression, and psychological distress. This effect has been particularly evidenced among younger users, who may experience social isolation, emotional detachment, and lower academic or professional performance [4,5,6]. These concerns underscore the need to understand the psychological and behavioural effects of social media dependency [7]. As digital platforms compete for user attention and evolve to increase engagement, it is essential to assess their broader impact on well-being and behaviour.

Instagram has become a leading platform among younger users, who are attracted by its visual and interactive design, personalised notifications and algorithm-driven content, which all together deepen user immersion [8,9]. Therefore, Instagram’s appeal lies in its ability to satisfy users’ psychological and social needs through a continuous loop of gratification. Users often turn to the platform to fulfil their need for play, seeking entertainment, enjoyment, and occasionally escapism. At the same time, they pursue orientation, using Instagram to stay informed, socially connected, and aware of current trends, products and brands. The understanding component reflects their desire for information, inspiration, and content that helps them make sense of themselves. These gratification dimensions contribute to Instagram’s attractiveness and explain the emergence of user dependency. The platform’s ease of use, coupled with its ability to satisfy such fundamental needs, thereby increases the risk of compulsive use and, ultimately, Instagram addiction [10]. Recent studies have recognised the marketing implications of user dependency on social media [11,12,13]. Increased dependency often leads users to engage more actively with branded content and create their own content, which, in turn, reduces marketing costs and increases brand visibility. For companies, understanding these dynamics is essential to developing competitive strategies rooted in co-creation and consumer interaction.

To this end, it is vital for organisations to comprehend the behavioural mechanisms behind social media dependency, as these patterns influence not only media consumption but also platform preferences [13]. Media System Dependency (MSD) Theory offers a useful framework for analysing how individuals turn to media to meet needs related to decision-making, information access, and social connection. Understanding these dependencies sheds light on how digital experiences are reshaping individual habits, brand interactions, and broader market structures. Consequently, social media data provide valuable insights into user motivations, needs, and behaviour—offering brands an opportunity to design more targeted and responsive strategies [2].

This study contributes to the academic literature by focusing on the negative consequences of users’ dependency on Instagram—an issue that has received less attention compared with the extensive body of research on the positive aspects and gratifications associated with social media use [10,14]. While numerous studies have examined the benefits perceived by users, few have explored how such dependency can trigger adverse psychological and behavioural outcomes [15,16]. In particular, there is a notable lack of research that analyses Instagram dependency from the perspective of its negative effects [6,17], which underscores the relevance and originality of this work.

This study identifies three interconnected constructs that emerge from Instagram dependency: excessive use, addiction, and Instastress. These variables help explain how users’ social and psychological characteristics influence both platform dynamics and brand performance. The study also explores the relationship between dependency and time spent on the platform, which increases exposure to branded content and strengthens consumer–brand relationships. Moreover, the study offers a theoretical contribution by linking dependency with Instagram addiction—a relationship that has been scarcely explored in the existing literature [2,18,19,20]. Additionally, the concept of Instastress is introduced as a contextualised adaptation of technostress, allowing for a more precise understanding of the platform’s psychological impact.

From a conceptual standpoint, the analysis is grounded in Individual Media Dependency Theory and is integrated with a socio-digital perspective to offer a more holistic view of the psychological, social, and behavioural implications of digital engagement. In doing so, the study not only deepens the understanding of the “dark side” of social media but also expands existing theoretical frameworks, providing a solid foundation for future research in the fields of digital marketing, consumer psychology, and mental health.

To address the research objectives, the paper is structured in two main sections. The first presents the theoretical foundations, including the literature review, hypothesis development, and methodological approach. The second offers an empirical examination of Instagram dependency and its negative effects based on a study involving 342 daily users of the platform aged 18 and above.

2. Literature Review and Hypotheses

2.1. Direct Negative Outcomes of Instagram Dependency

The present study is grounded in Individual Media Dependency Theory, which seeks to explain the relationship between media content and audience behaviour. According to this theory, individuals rely on communication media to satisfy various needs. Media dependency emerges when the content provided by the media contributes to fulfilling objectives related to understanding, orientation, and play—both at a personal and social level—thus addressing users’ needs and desires [8,10].

In the context of this research, which focuses on the online social network Instagram, social understanding refers to keeping oneself informed about the activities of other individuals or brands. Self-understanding involves interpreting the information in a way that justifies one’s own actions. Interaction orientation encompasses the ways individuals seek to connect and communicate with other users or brands, while action orientation involves obtaining inspiration regarding products or services to purchase, as well as places or events to attend. Finally, social play relates to shared entertainment through interactions such as commenting or sharing pictures and videos, whereas solitary play reflects the use of Instagram for personal relaxation and stress relief [21,22,23].

Building on these conceptualizations, the immersive and highly interactive nature of platforms such as Instagram enables users to simultaneously fulfil objectives related to play, orientation, and understanding while also engaging with branded content. These digital environments facilitate the integration of marketing messages—often through influencers or peer-generated content—via tagging, storytelling, and visual formats that seamlessly blend with users’ everyday interactions [9]. As users navigate the platform in search of relaxation, inspiration, or social interpretation, they encounter brand messages that align with their motivational needs, thus fostering the early development of consumer–brand relationships [24].

The participatory architecture of social networks encourages individuals to transcend passive browsing, engaging instead in practices that contribute to brand value co-creation. Marketing strategies on platforms like Instagram increasingly leverage these behavioural patterns, aligning content with users’ needs for contextual guidance, exploratory engagement, and self-relevant insights. This user-centric approach allows brands to organically embed themselves into users’ digital routines, enhancing emotional proximity and reinforcing the perceived relevance of branded content. This dynamic makes Instagram an especially potent platform for media dependency to emerge, as it allows users to derive cognitive, behavioural, and emotional gratifications simultaneously [25,26].

Such dynamics are particularly effective when gratifications linked to play, orientation, and understanding are consistently met. Under these conditions, users are more likely to interact with content, revisit the platform, and develop stable affective ties with brands. As prior research indicates [9,25], this sustained engagement not only shapes platform perception but also drives behavioural responses such as content consumption, sharing, and advocacy. Ultimately, when these gratifications are continually reinforced, users may experience heightened reliance on the platform, setting the stage for the development of deeper media dependency. This study, therefore, reconceptualises Instagram dependency through the three-dimensional lens of understanding, orientation, and play, adapting Media System Dependency Theory [27] to contemporary digital contexts. This approach captures the multifaceted nature of user-platform reliance in contemporary interactive environments.

The degree of dependency on a given medium can significantly influence individuals’ attitudes and behaviours. Prior studies have documented cognitive, affective, and conative changes in individuals who are frequently exposed to such media environments [5,14,27,28]. Indeed, research has found that a higher dependency on social networks is positively associated with, among other effects, more favourable attitudes [16,29] and increased loyalty toward the platform [5,30].

While media dependency, motivated by the pursuit of understanding, orientation, and play, can lead to significant gratifications and positive outcomes, it may also result in a diminished sense of volitional control. This loss of control can give rise to persistent engagement and excessive use [31,32].

From the lens of Individual Media System Dependency Theory, platforms such as Instagram function not merely as tools for interpersonal communication but as powerful socio-technological systems that shape users’ perceptions, emotions, and behaviours. The algorithmic infrastructure of Instagram fosters a high degree of psychological dependency by curating content tailored to users’ preferences and vulnerabilities, thereby sustaining engagement through mechanisms that tap into the human desire for social validation. As a result, users become increasingly reliant on the platform to derive meaning, uphold self-esteem, and navigate social relationships [13,19].

Within this dependency dynamic, Instagram exerts a strong influence on consumer culture and aspirational lifestyles. The constant exposure to curated images, influencer content, and brand messages introduces users to idealised portrayals of beauty and success, frequently prompting upward social comparisons [12,23]. Such comparisons can heighten materialistic values and affect users’ self-concept, especially as social metrics like likes, comments, and followers gain symbolic importance as markers of self-worth and social relevance. In this way, the platform intensifies dependency by making emotional regulation and identity construction increasingly reliant on algorithmically mediated social feedback [33,34].

This pattern of compulsive engagement has broader psychological consequences. In particular, young people’s dependency on social media and the endless consumption of content have been associated with anxiety, depression, social isolation, detachment from real-life relationships, and declining academic and professional performance [6,35].

Moreover, such dependency may trigger technostress in users [36,37]. Technostress refers to the adverse effects on thoughts, attitudes, and behaviours that stem—directly or indirectly—from the use of technology [38,39,40]. In this study, technostress is conceptualised in the context of Instagram usage as “Instastress”, understood as the negative impact Instagram may exert on users’ psychological states and behavioural patterns. High levels of dependency often lead to spending excessive time online and staying constantly alert for the latest content. This, in turn, generates ongoing stress, largely due to information overload. When individuals are constantly “bombarded” with news about the life of their friends or preferred brands, it is easier for them to get stressed, especially when the news is negative. Additionally, the pressure to stay updated and to adopt the latest features may lead to perceptions of complexity and uncertainty, especially among users facing cognitive limitations or slower adaptation to change [4,41].

Another major negative consequence of media dependency is addiction [3,32,42]. Although such behaviours often begin under the influence of positive reinforcement (i.e., pleasure-seeking), over time, they may shift toward negative reinforcement mechanisms aimed at relieving emotional discomfort such as boredom, loneliness, or nervousness [2,39,43,44].

In this regard, mobile social networks represent potentially addictive services that fill socio-psychological voids in users’ lives [39,45]. Consequently, mobile social network site addiction is characterised as a problematic dependency on mobile-based platforms [32,46,47].

Simultaneously, users are persistently exposed to idealised lifestyles, narratives of success, and aspirational consumption—frequently disseminated by influencers and brands—that promote conformity through consumption [48]. Thus, Instagram not only offers instant gratification driven by dopamine responses but also plays a crucial role in shaping cultural and social aspirations linked to consumption. The platform fosters continuous comparison with mediated representations of reality. For instance, viral campaigns such as the well-known Lidl sneakers phenomenon exemplify how even mundane or aesthetically unremarkable products can acquire symbolic value when amplified by trends and influencer discourse, thereby encouraging consumption and reinforcing identity through material possessions. Furthermore, brands actively contribute to this dynamic by crafting “authentic” content strategies and partnering with influencers to promote their products in ways that resonate socially and emotionally. Numerous studies [34,49] have highlighted influencer marketing as a pivotal force in shaping perceptions of beauty, success, and consumer behaviour within the Instagram ecosystem. Growing academic interest has turned toward understanding the evolving relationships between social media users and influential online figures within these digital environments. Among these figures, social media influencers (SMIs) have emerged as pivotal actors in brand communication strategies. Unlike traditional celebrity endorsements, SMIs create a sense of intimacy and authenticity by sharing content that feels personal and approachable such as tutorials, product reviews, and aesthetically curated imagery integrated into users’ daily feeds [9]. Through these practices, influencers not only shape consumer attitudes and purchasing decisions but also actively contribute to the co-creation of brand meaning and value in contemporary interactive marketing ecosystems [3].

Nowadays, social network addiction is a matter of growing concern due to its serious consequences for users who find themselves unable to disconnect. This addiction manifests through constant thoughts about social media and an irresistible urge to engage—whether by posting, updating statuses, sharing content, or browsing profiles of others [23,28,47]. Therefore, Instagram dependency should not be viewed merely as an excessive behavioural pattern but rather as a complex psychological condition that affects users’ mental and emotional well-being. The above discussion motivates the following hypotheses:

H1. 

Instagram dependency is positively related to excessive Instagram use.

H2. 

Instagram dependency is positively related to Instastress.

H3. 

Instagram dependency is positively related to Instagram addiction.

2.2. Indirect Negative Outcomes of Instagram Dependency

As discussed earlier, one of the possible negative outcomes of technology and media dependency is its excessive use, which, in turn, may lead to a wide range of adverse psychological, social, and behavioural consequences. Excessive use is often the result of an increasingly blurred boundary between online and offline life, particularly in highly immersive environments like social media.

In this regard, excessive usage may not only reduce users’ ability to regulate the time they remain connected but also foster compulsive checking and scrolling behaviours. These patterns often lead to constant exposure to an uninterrupted flow of digital stimuli, which can easily distract users and impair their capacity to remain attentive to the tasks or activities they are supposed to be performing [4,5]. This diminished attentional control has frequently been associated with lower levels of general mindfulness, understood as the ability to pay full and conscious attention to present-moment experiences in a non-judgmental and accepting way [50].

In our research, we introduce the concept of Instagram mindfulness to describe a specific attentional shift observed in users addicted to or dependent on social media. More specifically, these users’ cognitive focus becomes excessively oriented toward the Instagram environment (its content, interactions, and notifications) while their awareness of offline life diminishes. This form of attentional narrowing does not reflect an adaptive or self-regulated form of mindfulness but rather a compulsive engagement with the platform’s stimuli. Therefore, we propose an inverted perspective on the traditional concept of mindfulness by defining Instagram mindfulness as a state in which presence is maintained within the digital environment at the cost of reduced attention to physical, real-world surroundings. This interpretation contributes to a deeper understanding of how social media addiction impacts users’ cognitive functioning and overall psychological well-being.

Moreover, extensive media engagement can generate serious personal and social problems, such as reduced involvement in offline relationships, diminished participation in social activities, and increased social withdrawal [42]. High levels of stress are also commonly reported among individuals who spend excessive time online, often due to the overwhelming volume of information and the pressure to stay constantly updated [2,36]. In some cases, these stressors may evolve into psychological fatigue or burnout-like symptoms [17].

Crucially, prior research has consistently established that excessive engagement with technology and media platforms can lead to media addiction [2]. This transition from excessive use to addiction is often gradual, fuelled by reinforcement mechanisms and a perceived need to maintain social connection or emotional stability.

When focusing specifically on social media platforms, the literature highlights a growing number of studies linking excessive use to negative psychological and interpersonal consequences [4,5,35]. These include decreased social self-esteem [43], impaired interpersonal communication skills, and weakened social bonds with family and friends [51]. In addition, excessive social media use has been associated with behavioural disorders such as addiction [6,39] and symptoms resembling compulsive behaviour [52]. Given these observations, the present study proposes the following hypotheses to examine the consequences of excessive Instagram use:

H4. 

Excessive Instagram use is positively related to Instagram mindfulness.

H5. 

Excessive Instagram use is positively related to negative outcomes (personal and social problems).

H6. 

Excessive Instagram use is positively related to Instastress.

H7. 

Excessive Instagram use is positively related to addiction.

Previous studies have documented a strong negative correlation between social media addiction and mindfulness [53,54,55]. However, the association between the two variables may be bidirectional. On the one hand, lower levels of mindfulness may lead to higher levels of social media addiction. On the other, individuals who are addicted to social networks may have a reduced capacity for mindfulness. Increasing empirical evidence suggests that addiction negatively affects mindfulness, as users who are unable to control their impulses and behaviour toward social media tend to struggle to focus or pay attention to their work or other activities, with their attention being absorbed by the online environment [56,57].

Although the existing literature has revealed that higher social media addiction is associated with lower general mindfulness (i.e., reduced awareness of the physical and personal environment), no previous study has explored whether such addiction may be linked to increased attention specifically focused on the platform itself. Therefore, we hypothesise that, in contexts of addictive use, a decreased awareness of the offline environment may be accompanied by a compensatory increase in attentional absorption within the digital environment, giving rise to what we define in this study as Instagram mindfulness.

Social media addiction may also induce emotional exhaustion, i.e., emotional depletion and fatigue [12,58]. Though the concept has been mainly used in job performance research [59,60], it can also be applied to the context of the present study. On one hand, users that are constantly connected to online social media may feel a lack of energy and a greater mental exhaustion than those who have spent less time online. On the other hand, young users addicted to these platforms tend to spend prolonged periods of time immersed in them, increasing their exposure to persuasive messages and the appealing display of desirable brands and products. As a result, they become more susceptible to purchasing or consuming the products showcased in these social media platforms [2,34,61].

Moreover, social media addiction can also provoke stress [17]. Past research found a series of emotional factors that are related to media addiction, with depression, anxiety and stress among them [62,63]. Thus, it has been established that social media addiction has a considerable direct and positive impact on stress [44]. These considerations lead to the following hypotheses:

H8. 

Instagram addiction is positively related to Instagram mindfulness.

H9. 

Instagram addiction is positively related to emotional exhaustion.

H10. 

Instagram addiction is positively related to Instastress.

The hypothesised relationships to be tested in this study are depicted in Figure 1.

3. Methodology

3.1. Sample Description

To fulfil the aims of the investigation and test the hypothesised relationships, an empirical study was conducted through online interviews with structured questionnaires. A pretest of the questionnaire was conducted through personal interviews so as to detect problems and reduce ambiguity in the questions. As a result, some of the items in the scales were further adapted to the present context and their wording was made clearer. The study population comprised young people aged over 18 who accessed Instagram on a daily basis. The choice of this study population was motivated by (1) the fact that they are more susceptible to develop problematic behaviours associated with excessive technology use [22,28,46]; (2) their greater use of smartphones as the primary medium to access social media networks is reflected in recent data, which indicate that users aged between 18 and 34 spend approximately 3 h per day on social media platforms, a figure significantly higher than that of users over the age of 34 [1]; and (3) their greater addiction to social media sites due to the benefits it gives them [2,61].

Nowadays, smartphones represent the vast majority of mobile devices, with usage patterns highlighting their central role in digital life. On average, individuals spend approximately 3.5 h per day on their smartphones, underscoring a high degree of connectivity. A significant portion of this time is dedicated to social media, with 91% of social media users in the region accessing these platforms via mobile devices. Around 59% of individuals across the European Union engage in social networking activities, such as maintaining a profile or interacting on platforms like Facebook, Instagram, X, Snapchat, or TikTok [1,64].

Among these, Facebook and Instagram stand out as the leading platforms in the region. Facebook remains the most widely used social network in Europe, with an estimated user base exceeding 459 million. Instagram, currently the second most popular platform, is experiencing steady growth, with over 311 million users across the continent and projections suggesting an increase to more than 325 million by 2028. This upward trend contrasts with Facebook’s slowing engagement levels in certain demographics, particularly among younger users, who are increasingly gravitating toward more visually dynamic and mobile-native platforms such as Instagram and TikTok [1,65].

The adopted sampling technique was non-probabilistic (convenience sampling). The field research was conducted by a market research company. Data were collected via an online survey which received 360 questionnaires, 342 of which were valid after discarding those with missing values. Of the final sample, 29.5% were men and 70.5% were women. The largest part of the sample was composed of students (85.7%), whose average age was 22 years. We found that 100% of the interviewees access Instagram daily, with both the average number of times per day they access the app (32 times on average) and the average amount of time they are connected (2–3 h and a half approximately) being high.

3.2. Measurement

Items from previously validated measurement scales were selected and adapted to operationalise the constructs in the research model. This process was supported by a qualitative pretest involving personal interviews with individuals from the target population, thus ensuring contextual relevance and clarity. All constructs were subsequently assessed for reliability, as well as convergent and discriminant validity (see

Table 1. Measurement model.

Construct/ Dimension/ Indicator	VIF	Weight	Loading	t-Value	Cronbach Alpha	Composite Reliability	AVE
Dependency (second-order factor)						n.a	n.a
Understanding	1.361	0.450			0.751	0.836	0.513
SOU1			0.816	40.048
SOU2			0.796	32.733
SOU3			0.601	12.307
SEU2			0.645	15.234
SEU3			0.773	23.353
Orientation	1.491	0.712			0.758	0.838	0.503
AO1			0.666	10.832
AO2			0.786	16.468
AO3			0.675	10.228
IO1			0.712	14.906
IO2			0.719	12.024
IO3			0.655	11.256
Play	1.161	0.157			0.801	0.861	0.529
SP1			0.692	4.065
SP2			0.680	3.509
SP3			0.725	3.862
STP1			0.746	4.907
STP2			0.789	5.435
STP3			0.702	3.962
Addiction (formative)						n.a	n.a
ADD1	1.539	0.311
ADD2	1.371	0.246
ADD3	1.284	0.008
ADD4	1.513	0.107
ADD5	1.423	0.357
ADD6	1.401	0.110
ADD7	1.220	0.428
ADD8	1.484	0.034
Excessive use (reflective)					0.745	0.855	0.663
EUSE1			0.777	26.754
EUSE2			0.802	31.366
EUSE3			0.861	58.986
Instastress (reflective)					0.701	0.867	0.765
IST1			0.874	38.995
IST2			0.875	46.866
Negative Outcome (reflective)					0.745	0.851	0.656
NEGO1			0.833	18.737
NEGO2			0.781	13.610
NEGO3			0.814	19.539
Instagram Mindfulness (reflective)					0.753	0.830	0.523
INM1			0.601	6.544
INM2			0.753	7.556
INM3			0.815	34.405
INM4			0.829	29.659
INM5			0.762	10.506
Emotional exhaustion (reflective)					0.767	0.855	0.603
EE1			0.603	12.546
EE2			0.882	52.576
EE3			0.903	70.932
EE4			0.674	14.822

Note: n.a = non-applicable.

and

Table 2. Discriminant validity.

	Addiction	Mindfulness	Dependency	Emotional Exhaustion	Instastress	Negative Outcomes	Excessive Use
Addiction	n.a	-	-	-	-	-	-
Mindfulness	0.653	0.723	-	0.713	0.242	0.530	0.625
Dependency	0.574	0.434	n.a	-	-	-	-
Emotional exhaustion	0.700	0.556	0.499	0.776	0.354	0.529	0.744
Instastress	0.323	0.158	0.465	0.254	0.785	0,426	0.259
Negative outcomes	0.549	0.439	0.389	0.410	0.303	0.810	0.330
Excessive use	0.684	0.447	0.407	0.573	0.197	0.268	0.814

Note: Values below the diagonal are the correlation estimates, diagonal elements are squared AVE values, and values above the diagonal show the results of the HTMT criterion. n.a = non-applicable.

), following methodological guidelines [66]. The dependency construct was operationalised as a composite of three dimensions: understanding, orientation, and play [27]. Each dimension of the scale includes six items, thus amounting to eighteen indicators for the whole construct. The scale has been successfully applied in current digital contexts [17]. Instagram addiction was measured with eight items [67]. The items of excessive use and negative outcome constructs were drawn by adapting the subscales of the Problematic and Risky Internet Use Screening Scale (PRIUSS) [68], each of which was measured with three items. Mindfulness was assessed with five items based on the State Mindfulness Scale (SMS) [69]. Emotional exhaustion was measured with four items using the Emotional Exhaustion Scale (ECE) [70]. To measure Instastress, two of the items of the techno-invasion scale [71] were adapted to the context of the study. Some of the items of the previously published measures of mindfulness, emotional exhaustion, and Instastress were eliminated as they were incompatible with the study context. Appendix A provides the full list of items used to measure the different constructs.

3.3. Structural Model Assessment

To test the measurement instrument and the proposed structural model, PLS (Partial Least Squares) modelling was used. The choice of PLS was mainly motivated by the fact that it allows estimating models to include both formative and reflective constructs. In this paper, the Instagram dependency and addiction constructs are conceived as formative ones, with the dependency factor designated as a second-order construct, as determined by three first-order reflective dimensions [66]. The software tool used to test the proposed theoretical model was Smart-PLS 4.1.0.9 [72], where a bootstrapping procedure with 5000 subsamples was used for parameter significance testing.

4. Results

4.1. Measurement Model

As for the measurement model, first, the reliability of the individual items and the loadings of the reflective constructs were assessed. The results showed that all loadings were above the accepted threshold of 0.6 [73], except for item SEU1, whose value was 0.457 and which was eliminated. The significance of the loadings was confirmed by using the bootstrap procedure (5000 subsamples). In addition, all constructs and dimensions showed convergent validity as their average variance extracted (AVE) values exceeded the 0.5 benchmark [74] (Table 1).

Construct reliability was measured with Cronbach’s alpha [75] and composite reliability (ρc) [76]. The constructs excessive use, Instastress, mindfulness, negative outcome and emotional exhaustion proved reliable as their Cronbach’s alpha and composite reliabilities (ρc) were greater than 0.7 [77] (Table 1).

Regarding the formative measures (Instagram Dependency and addiction), weights provide information about the contribution of each formative indicator to a construct [78]. Formative models are based on multiple regression analysis. As a result, high collinearity among dimensions would produce an unstable estimation. This instability would make it difficult to assess the separate effect of each construct dimension [79]. Considering this, a variance inflation factor (VIF) test for collinearity was performed. According to [80], a VIF value higher than five can be troublesome, but the results of the test were far below this cut-off threshold (Table 1), which indicates no multicollinearity between dimensions.

To test discriminant validity, two criteria were used. On the one hand, the square roots of the AVE values were compared with the correlations between constructs. On average, the constructs related to their own measures more strongly than they did to other measures (Table 2). On the other hand, the heterotrait–monotrait (HTMT) ratio of the correlations was assessed [81], confirming that the monotrait–heteromethod values exceeded the heterotrait–heteromethod values (Table 2).

4.2. Structural Equation Model

Table 3. Structural model. Tested hypotheses.

Hypothesis	(β)	Weights (Loading)	t-Value (Bootstrap)	Contrast
Dependency → addiction	0.355 ***		6.123	Accepted
Dependency → excessive use	0.407 ***		8.320	Accepted
Dependency → Instastress	0.419 ***		8.338	Accepted
Addiction → exhaustion emotion	0.700 ***		23.249	Accepted
Addiction → mindfulness	0.653 ***		11.634	Accepted
Addiction → Instastress	0.120 *		2.122	Accepted
Excessive use → negative outcomes	0.268 ***		4.775	Accepted
Excessive use → mindfulness	0.025		0.005	Rejected
Excessive use → Instastress	0.056		0.962	Rejected
Excessive use → addiction	0.540 ***		8.944	Accepted
Formative measures
Addiction 1 → Addiction		0.311 ***	5.416
Addiction 2 → Addiction		0.246 ***	5.186
Addiction 3 → Addiction		0.008	0.221
Addiction 4 → Addiction		0.107 *	2.034
Addiction 5 → Addiction		0.357 ***	6.809
Addiction 6 → Addiction		0.110 *	2.103
Addiction 7 → Addiction		0.428 ***	9.350
Addiction 8 → Addiction		0.034	0.541
Understanding → dependency		0.450 ***	5.357
Orientation → dependency		0.712 ***	9.540
Play → dependency		0.157 ***	3.543

* p < 0.05; *** p < 0.001; R² (addiction) = 0.571; R² (mindfulness) = 0.423; R² (emotional exhaustion) = 0.489; R² (Instastress) = 0.223; R² (negative outcomes) = 0.215; R² (excessive use) = 0.325; Q² (addiction) = 0.155; Q² (mindfulness) = 0.187; Q² (emotional exhaustion) = 0.268; Q² (Instastress) = 0.158; Q² (negative outcomes) = 0.110; Q² (excessive use) = 0.132.

shows the results of the structural model assessment. Bootstrapping (5000 re-samples) was used to generate standard errors and t-statistic values [66]. In addition, R² values surpassed the minimum level of 0.10 [82], and cross-validated redundancy measures showed that the theoretical model had predictive relevance (Q² > 0).

The results of the estimated model indicate that excessive use (β = 0.407; p < 0.01; H1 accepted), addiction (β = 0.355; p < 0.01; H3 accepted) and Instastress (β = 0.419; p < 0.01; H2 accepted) are negative outcomes of users’ dependency toward Instagram. Instagram addiction, in turn, was found to be a strong predictor of Instastress (β = 0.120; p < 0.01; H10 accepted), mindfulness (β = 0.653; p < 0.01; H8 accepted), and emotional exhaustion (β = 0.700; p < 0.01; H9 accepted), thus emerging as a key variable in the proposed model. According to the data, addiction is strengthened by the positive direct effect of excessive use (β = 0.540; p < 0.01; H7 accepted), which, in turn, is positively related to personal and social problems (β = 0.268; p < 0.01; H5 accepted). However, contrary to the stated hypotheses, excessive Instagram use did not exert a significant effect on either Instastress (β = 0.056; p < 0.01; H6 rejected) or Instagram mindfulness (β = 0.025; p < 0.01; H4 rejected). Thus, the relationship between them seems to be mediated by Instagram addiction.

Also, regarding the formative measures of Instagram dependency and addiction, the individual weight of each of their indicators/dimensions could be assessed so as to reveal which of them had the greatest contribution to the construct. As for Instagram dependency, the results showed that addicted Instagrammers go beyond using it to satisfy an entertainment (or play) need (π = 0.157; p < 0.01), as the dimensions of orientation (i.e., using it to communicate with others) (π = 0.712; p < 0.01) and social understanding (i.e., keeping up with what’s happening with others/celebrities/brands) (π = 0.450; p < 0.01) contributed in a greater extent to this construct. With regard to the addiction construct, the results revealed that it was pushed mainly by (1) spending more time on Instagram than initially intended, (2) unsuccessfully trying to cut down on the use of Instagram, (3) the feeling users’ have to use it more and more in order to get the same pleasure from it, and (4) thinking about Instagram even when not being online.

It should be noted that two of the indicators of the addiction construct presented non-significant weights (ADD3 and ADD8), but as their associated loadings were significant (β = 0.301; t = 5.189 and β = 0.485; t = 10.017, respectively), they were maintained in the measurement instrument [66]. Removing non-significant weights can compromise the content validity of formative constructs since they represent part of the scope covered by the concept. Those indicators referred to discussions with family and friends, as well as problems at work or university resulting from Instagram use. A possible explanation for this might be that the respondents may not be willing to admit that they are not as productive in their jobs or studies as they should be due to Instagram or that their families and friends are reproaching them the excessive Instagram use.

5. Discussion and Conclusions

Social media is part of today’s society’s daily routine. Its use could be considered positive if it does not prevent individuals’ from performing basic everyday life activities (such as working, studying, and meeting friends and family), as its abuse can produce a strong negative impacts on users’ behaviour.

The findings of this study contribute to the growing literature on the negative psychological and behavioural consequences of social media use by focusing specifically on Instagram dependency. While previous research has primarily emphasised the gratifications derived from social media engagement, such as entertainment, information, and social connectedness [10,14], relatively few studies have examined how dependency on platforms like Instagram may lead to maladaptive outcomes, including stress, emotional exhaustion, and impaired functioning [6,16]. This research thus shifts the analytical lens toward the darker dimensions of digital interaction, aligning with recent calls to address the psychological costs of constant connectivity [4,83].

A significant theoretical contribution of this work lies in the integration of Individual Media Dependency Theory with a socio-digital framework, enabling a deeper understanding of how user dependency extends beyond mere gratification-seeking. The study reveals that Instagram dependency is not only positively associated with excessive use, stress and addiction but also indirectly related to adverse psychological states such as emotional exhaustion, Instagram mindfulness or social and personal problems. Importantly, addiction was found to function as a mediating construct, amplifying the effects of excessive use on well-being, an insight that helps clarify the internal dynamics of compulsive digital behaviour and supports findings from prior studies on mediated reinforcement cycles in social media usage [2,63].

Moreover, the introduction of the construct Instastress, conceptualizing a platform-specific manifestation of technostress, constitutes a novel contribution. Whereas general technostress has been associated with information overload, continuous connectivity, and user fatigue [36,71], Instastress captures the emotional toll exerted by Instagram’s algorithmic content curation, constant social comparison, and pressures for digital self-presentation [19,44]. This platform-specific adaptation provides a more fine-grained understanding of user distress, adding precision to the study of digital well-being.

Although the previous literature has linked excessive social media use to increased stress and mindfulness toward social networks, our findings suggest that these effects are not directly attributable to excessive use alone but are rather mediated through addiction.

A possible explanation is that the mere frequency or amount of usage does not necessarily trigger stress or mindful attention to a social network unless it is accompanied by compulsive or dependency-driven behaviours. In our model, addiction emerges as a psychological mechanism that channels the effects of excessive consumption into emotional and cognitive consequences such as stress and mindfulness. This suggests that problematic outcomes do not arise from high usage per se but from the user’s inability to regulate the compulsive need to be on Instagram [84]. From a theoretical standpoint, this reinforces the mediating role of addiction and highlights its key role in the dependency–outcome pathway.

These contributions are particularly relevant in the current context of increasing digital engagement among young adults, for whom mobile access to social media platforms is near-ubiquitous [1]. The structural model tested in this study offers robust empirical support for the relationships between Instagram dependency, excessive use, addiction, and their negative psychological outcomes, providing a foundation for further research and practical interventions aimed at reducing problematic usage patterns and fostering healthier digital behaviours.

Moreover, dependence on Instagram is closely linked to addictive behaviours and increased exposure to branded content, which may lead to higher purchase intentions. Based on Media System Dependency Theory [85], emotional and cognitive attachments to the platform emerge as users rely on it for social connection, entertainment, and consumption cues. These dependency processes are especially relevant in interactive marketing contexts, where user engagement shapes responsiveness to brand messages embedded within personalised and influencer-driven content ecosystems.

A noteworthy observation is that the dependency on Instagram was mainly caused by individuals’ needs of orientation and understanding, with entertainment being a secondary motivation. This finding is contrary to previous studies that have typically pointed out entertainment as the main driver of SNS use [83,86]. A possible explanation for this might be that social media is so integrated in users’ daily life that they are not solely used for passing time but also to satisfy social and informational needs. The latter is in line with recent Instagram investigations, which identified knowledge about others [87] and social interaction [88] as primary motives for Instagram use.

5.1. Theoretical and Managerial Implications

The findings of this study have relevant implications for multiple stakeholders, particularly in terms of digital behaviour management, marketing strategy, and public health. For social media users, especially young adults, the results underscore the psychological risks of excessive and compulsive Instagram use. Understanding the difference between high engagement and addiction is essential to fostering healthier digital habits. Awareness campaigns and educational interventions should be designed to promote digital literacy, self-regulation, and critical reflection on personal usage patterns.

For mental health professionals and lecturers, the identification of Instastress and the mediating role of Instagram addiction offer practical tools to detect early signs of emotional exhaustion and cognitive overload in highly connected individuals. These insights can guide the development of preventive programs that address the psychological burden of platform dependency.

From a managerial and marketing perspective, this study reveals that dependency-driven engagement, while potentially beneficial for brand exposure, comes with ethical considerations. Digital addiction behaviours are often driven by underlying psychological mechanisms such as fear of missing out (FoMO) and compulsive smartphone engagement [89]. Our findings support this perspective, as Instagram dependency and overuse appear to be reinforced by users’ constant need to stay updated and connected. For managers and platform designers, acknowledging the existence of these drivers of social media addiction has important implications. Strategies aimed at reducing the perception of continuous urgency (such as promoting mindful usage, limiting push notifications, or introducing digital well-being tools) can help mitigate problematic behaviours without compromising user interaction. From a marketing standpoint, understanding FoMO-driven patterns can also inform the design of campaigns that foster authentic engagement rather than exploiting compulsive consumption, thereby balancing business goals with users’ psychological health. Therefore, responsible brand actions on social media should aim for authentic, mindful interactions that support user well-being rather than exploit psychological vulnerabilities.

At the same time, the compulsive nature of Instagram use presents strategic opportunities for brands seeking to enhance visibility and co-create value. Dependency often results in greater user engagement, increased content sharing, and a stronger response to social influence. These behaviours can amplify brand credibility and reduce communication costs, provided that they are leveraged within ethical and user-centred frameworks.

For platform designers and technology developers, the findings suggest the need to reconsider the mechanisms that fuel algorithmic addiction. Features that reinforce constant engagement, such as infinite scrolling, push notifications, or reward-based interactions, should be critically evaluated to balance commercial goals with users’ mental health and attentional integrity.

Therefore, addressing social media dependency requires a multidisciplinary approach combining psychological, technological, and managerial strategies. By integrating behavioural insights into communication design and platform governance, stakeholders can help foster healthier digital ecosystems that are both engaging and sustainable.

5.2. Limitations and Future Research

The present study has some limitations that should be acknowledged. First, the investigation was focused on a single SNS, i.e., Instagram, which might have conditioned the obtained results. Thus, it would be interesting for future studies to include other social networks in the analysis so as to compare the results and examine differences.

A second limitation of the present study refers to the measurement instrument of the addiction construct. As being addicted is not a well-accepted behaviour in today’s society, the responses to the questions regarding addiction might have been biased, as interviewees might have been embarrassed to admit it publicly. Thus, future investigations might consider finding more objective measures of addiction, combining the questionnaire approach with other instruments.

Moreover, the present research was limited to a sample of young adults, which makes the results of the study less generalizable to the entire population of SNS users. To overcome this limitation, future studies should replicate the survey with individuals from diverse age groups to guarantee more robust results.

Furthermore, the use of a non-probabilistic sampling method, combined with a predominantly female sample, may limit the generalizability of the findings. Past research has documented that gender significantly influences the development of addictive behaviours. Women are often found to exhibit higher levels of social media addiction and associated outcomes (e.g., anxiety and low self-esteem), while men may have different usage patterns or motivations [52,90]. Moreover, the cross-sectional design of the study should be acknowledged as another limitation. Future research should address this by employing longitudinal designs to explore the evolution of addictive social media interactions over time.

Lastly, the exclusive reliance on online interviews using structured questionnaires for data collection should be acknowledged as another limitation. This single-source approach may constrain the study’s external validity and limit the generalizability of the findings, as responses are subject to self-report biases and influenced by the context in which the survey is administered. As emphasised [3], incorporating multiple data sources is critical for producing more robust and credible evidence. Hence, future studies should consider complementing survey-based methods with experimental designs, longitudinal studies, or secondary data analysis, thereby enhancing the validity and empirical strength of the findings.

On the one hand, further research could explore the role of other variables in the proposed model, assessing both additional negative outcomes of Instagram abusive use (e.g., compulsive use, deficient self-regulation, and loneliness) and other antecedents that may lead to adverse effects (e.g., cognitive preoccupation and negative affect anticipation). On the other hand, future research could implement intervention-based research designs, which would allow researchers to evaluate the impact of users’ mindfulness levels or digital consumption limits. This would offer practical implications for managing social media overuse.

Another possible area of future research would be to investigate if users’ addictive behaviour varies across cultures, as other sociodemographic and behavioural variables might influence users’ behaviour. Hence, a fruitful area for further work will be to assess the moderating impact of variables such as the amount of time spent online, gender or age, education level, socioeconomic status, digital literacy, personality traits, online activity patterns, and social network size in order to provide deeper insights into the proposed structural relationships.

Finally, further research is needed to examine whether social media addiction may lead to brand addiction, as well as how advertising content on social media platforms could capitalise on this phenomenon. Gaining insight into addictive behaviours associated with social media—whether related to platform usage, brand attachment, or impulsive purchasing—is essential for safeguarding consumer well-being. It may be interesting to explore the interconnections between social media dependency, brand-related compulsions, impulsive buying tendencies, and psychological health within the digital environment.