SOCIAL EXCLUSION AND MENTAL HEALTH: INSIGHTS FROM SIMULATION AND THEORY

Liviu Poenaru, Oct. 12, 2025

ABSTRACT

Context and Problematic
Social exclusion—both as objective isolation and as the subjective feeling of being left out—has emerged as a key determinant of psychological well-being. Extensive empirical research demonstrates that chronic social disconnection increases risks for depression, anxiety, cognitive decline, and even premature mortality. Yet, distinguishing the independent effects of objective and perceived exclusion remains difficult in observational data, as both often co-occur. Moreover, digital environments now magnify perceived exclusion through constant exposure to curated lives, generating social comparison and “fear of missing out” (FoMO). These modern forms of digital isolation highlight the need for theoretical integration and simulation-based approaches to understand how exclusion dynamics influence mental health over time.

Goal
This study aimed to clarify how real and perceived exclusion each contribute to psychological well-being and physiological stress. By combining computational simulation and theoretical synthesis, it sought to examine the dynamic evolution of mental health and allostatic load under varying degrees of social isolation and loneliness, offering insights consistent with epidemiological and neuropsychological findings.

Method
A simplified simulation of 200 virtual agents was developed, modeling two independent predictors—objective isolation (actual exclusion, AE) and perceived isolation (perceived exclusion, PE)—and one continuous outcome: mental health. Higher MHI (Mental Health Index) values indicated better well-being. The model tested both cross-sectional differences among four isolation–loneliness groups and longitudinal changes over 365 simulated days. Cumulative AE and PE contributions to allostatic load were analyzed to approximate physiological stress accumulation.

Results
Average mental health was high across all groups, though systematically lower under conditions of isolation or loneliness. Agents who were both isolated and lonely had the lowest mean MHI (≈97.5), compared to 99.9 among non-isolated, non-lonely peers. Over time, mean MHI dropped sharply during the first 30 days (~87) and then stabilized near 98.9, suggesting early vulnerability followed by adaptive recovery. Both AE and PE showed additive effects on cumulative allostatic load, with PE exerting a slightly stronger impact, indicating that perceived exclusion may weigh more heavily on stress physiology than objective isolation.

Interpretation
Despite modest numerical differences, the simulation reproduces well-documented human patterns: perceived loneliness and objective isolation independently and cumulatively reduce mental well-being and heighten physiological strain. These findings reinforce the need to address both real and perceived social disconnection—offline and online—to improve mental health and societal resilience.

Introduction

Human beings are inherently social, and a wealth of evidence indicates that social belonging is a fundamental human need (Baumeister & Leary, 1995). When this need is thwarted through social exclusion or isolation, the consequences can be severe. Classic and contemporary studies have linked lack of interpersonal attachments to wide-ranging negative outcomes in health and well-being. Even brief episodes of ostracism—such as being ignored in a group—can elicit strong feelings of pain and threat (Williams, 2007). Neurobiologically, social exclusion triggers brain regions involved in physical pain. For example, Eisenberger and Lieberman (2004) found that the anterior cingulate cortex (ACC), a region central to physical pain perception, becomes more active during experiences of social exclusion and this activity correlates with the individual’s distress. Such findings have given rise to the concept of “social pain,” highlighting that social rejection is processed in the brain much like physical pain. This neural overlap underscores the deep evolutionary importance of social connection: being cast out of the group was historically a threat to survival, and so our brains treat it as inherently alarming.

Beyond immediate pain, chronic social disconnection poses serious risks for mental and physical health. Prolonged social isolation and loneliness have been associated with elevated rates of depression and anxiety, cognitive decline, and even mortality (Cacioppo & Hawkley, 2009). Epidemiological research by Holt-Lunstad et al. (2015) showed that individuals who are socially isolated or who feel lonely face about a 26–32% higher likelihood of early mortality compared to socially connected peers. Remarkably, the impact of chronic social disconnection on mortality risk is comparable to well-established medical risk factors. Importantly, this includes both objective social isolation (such as having few or no social contacts) and subjective isolation (feeling alone even when others are around). Meta-analytic evidence indicates that actual and perceived social isolation are similarly detrimental; both aspects independently contribute to worse health outcomes. In other words, it is not only the absence of others that matters, but also one’s internal sense of exclusion or not belonging.

Modern society presents new contexts in which perceived social exclusion can arise. In the age of social media and digital platforms, people are constantly exposed to images of others’ lives, successes, and gatherings. This ubiquitous connectivity paradoxically can foster feelings of being left out. The pressure to maintain high standards of visibility and performance online—amassing “likes,” followers, and picture-perfect posts—means that many individuals worry they are not measuring up socially. Psychologists have dubbed this the “fear of missing out” (FoMO), defined as a pervasive apprehension that others might be having rewarding experiences from which one is absent. FoMO is essentially the fear of social exclusion in a digital guise. Through social media, people have continuous awareness of what fun or interesting things others are doing, which can create distorted perceptions of the edited lives of others (Gupta & Sharma, 2021). Seeing peers’ highlight reels can lead to upward social comparisons that make one feel inferior or left behind. Thus, even someone with an active online network might perceive themselves as excluded or not keeping up, which can adversely impact self-esteem and mood. Recent studies confirm that heavy use of social networking sites is, paradoxically, associated with heightened feelings of loneliness and social anxiety among young people, as noted by Gupta and Sharma. In a national survey of U.S. young adults, those in the highest quartile of social media use had significantly higher odds of feeling socially isolated than those in the lowest quartile (Primack et al., 2017). Such findings raise pressing questions about how both real-world and virtual-world exclusion contribute to mental health.

In sum, existing literature suggests that social exclusion—both in reality and as a subjective experience—plays a critical role in mental well-being. However, these two facets (objective vs. perceived exclusion) are often intertwined, making their independent effects difficult to disentangle using observational data alone. Additionally, the emerging influence of digital social contexts necessitates new theoretical integration. This exploration addresses these gaps by using an empirical simulation to illustrate the distinct and combined impacts of actual and perceived social exclusion on mental health outcomes. We then interpret the simulation in light of psychological, sociological, and neurobiological theories, extending the discussion to the context of social media-driven exclusion. By merging empirical modeling with theory, our goal is to provide a nuanced understanding of how feeling excluded—or actually being excluded—affects mental health, and to explore the implications for individuals and society.

Method

Simulation Design

We constructed a simplified simulation model to examine how objective social exclusion and perceived exclusion each affect mental health. The simulation was programmed to represent a sample of 200 “individuals” with two key attributes: (1) Objective social connectedness, an index reflecting actual social inclusion or isolation (e.g., number of social ties or frequency of social contact), and (2) Subjective social inclusion, an index reflecting the individual’s perceived belonging or loneliness. For conceptual clarity, higher values on the objective index indicate greater social isolation (fewer connections), and higher values on the subjective index indicate stronger feelings of loneliness or exclusion. In real life, these two aspects are related but not perfectly synonymous; for example, a person with many friends might still feel lonely, and someone with few contacts might still feel content. To mirror this, our simulation treated the objective and subjective exclusion factors as correlated but distinguishable variables. We initialized the data such that objective and perceived isolation had a moderate positive correlation (approximately r = 0.6), consistent with empirical studies showing that actual and perceived isolation often co-occur (Holt-Lunstad et al. 2015) yet can diverge in individual cases. Each individual was also assigned a mental health score representing psychological well-being (with higher values indicating better mental health).

Procedure

The simulation specified a simple linear model whereby each individual’s mental health score was affected by their level of objective isolation and perceived isolation. In essence, we assumed that being more socially isolated in reality, and feeling more excluded or lonely, would each independently contribute to worse mental health outcomes. These effects were modeled as additive and roughly equal in magnitude. Mathematically, we generated mental health as a continuous outcome:

Mental Health=b0+b1(Objective Isolation)+b2(Perceived Isolation)+error

b₀ = the intercept (baseline value of mental health when all predictors are 0)
b₁ = the regression coefficient for Objective Isolation
b₂ = the regression coefficient for Perceived Isolation

Random noise was added to represent individual differences and other unmodeled influences on mental health. We then conducted analyses to evaluate the impact of each factor. Specifically, we examined the simulation output via multiple regression to test whether objective and perceived exclusion each showed a significant unique effect on mental health. We also compared the mental health outcomes of four illustrative groups: (a) individuals low in both actual and perceived isolation (well-connected and feeling included), (b) those high in actual isolation but low in perceived isolation (socially isolated yet not feeling lonely, perhaps due to coping or personality), (c) those low in actual isolation but high in perceived isolation (socially active yet feeling lonely), and (d) those high in both actual and perceived isolation (socially isolated and feeling lonely).

Assumptions and scope

This simulation is a simplified representation and does not capture every nuance of real social networks or psychological processes. It treats “mental health” as a single continuous outcome for illustrative purposes, acknowledging that in reality social exclusion can affect many facets (mood, self-esteem, stress levels, etc.). Furthermore, the model assumes a linear additive effect of the two forms of exclusion without interaction; we explore the possibility of interaction (the combination being especially harmful) through group comparisons rather than in the primary regression. Despite its simplicity, this approach allows us to isolate the core question: How do real and perceived social disconnection each relate to mental health in principle? The simulation’s strength is in providing a controlled thought experiment grounded in plausible effect sizes derived from literature (e.g., comparable impacts of subjective and objective isolation - Holt-Lunstad, 2015). The results from this simulated data are used as a heuristic complement to empirical findings, not as a definitive empirical study. All analyses were conducted in Python, and the code can be made available for reproducibility.

Results

The simulation results indicate that average mental health remains high across all social groups, with only slight variations by isolation and loneliness status (Figure 1: Mean MHI by Social Isolation and Loneliness Group). In particular, agents who were neither isolated nor lonely achieved the highest mean Mental Health Index (MHI ≈ 99.86), closely followed by those who were not isolated yet felt lonely (MHI ≈ 99.77).

Objective social isolation was associated with marginally lower scores: isolated but not lonely individuals had a mean MHI of about 98.62, and those who were both isolated and lonely showed the lowest mean MHI at approximately 97.49. Although these numerical differences are small (on the order of only 2–3 points between the extremes), they are systematic in direction. Any experience of social exclusion—whether objective or subjective—is linked to a slight reduction in average mental health, and the combination of both forms corresponds to the greatest (albeit still modest) decrease. This consistent ranking suggests that even in a generally resilient population (with MHI near its ceiling), the presence of social isolation and feelings of loneliness can cumulatively chip away at mental well-being in a measurable way.

Beyond these cross-sectional group differences, the model reveals a clear temporal dynamic in mental health adaptation over the one-year simulation (Figure 2: Trajectory of Mean MHI over 365 Days). Initially, mean mental health declines sharply: immediately after agents begin experiencing social exclusion stressors, the population’s mean MHI falls from a near-perfect baseline (~99–100) to a nadir of roughly 87 within the first few weeks (approximately by day 21).

Subsequently, a recovery trend emerges. After this initial drop, the mean MHI rises steadily over time, eventually stabilizing at about 98.9 toward the end of the 365-day period. By the final quarter of the simulation, the average mental health levels off, remaining close to this high plateau through day 365. This trajectory suggests an adaptation dynamic: there is an early adverse impact of social exclusion on mental health followed by a gradual rebound as agents adjust to or cope with their social environment. In other words, the population as a whole recovers much of its mental health over time, indicating that adaptive processes (whether behavioral or physiological) help mitigate the initial negative effects of exclusion.

To further elucidate the stress mechanisms underlying these outcomes, we examined the accumulation of allostatic load (AL) in relation to actual and perceived social exclusion (Figure 3: Cumulative Allostatic Load from Actual vs. Perceived Exclusion). The analysis shows that both objective isolation – denoted as Actual Exclusion (AE) – and subjective loneliness – denoted as Perceived Exclusion (PE) – independently contribute to heightened allostatic load, and their effects are roughly additive.

In practical terms, individuals experiencing both high AE and high PE accumulated the greatest allostatic burden, reflecting a cumulative impact of both forms of exclusion on physiological stress. Notably, the relationship between perceived exclusion and allostatic load is somewhat steeper than that for actualexclusion. A given increase in loneliness (PE) produces a slightly larger rise in AL than an equivalent increase in objective isolation. Thus, while being socially isolated elevates stress, feeling socially isolated appears to impose an even greater physiological strain. In sum, both the objective lack of social contact and the subjective sense of exclusion incrementally drive up allostatic load, with subjective perceptions of exclusion having a marginally stronger effect.

These findings underscore that the combined presence of actual and perceived exclusion exacts the highest toll on the body’s stress system, aligning with the mental health patterns observed above. The small but systematic differences in MHI across groups, together with the adaptation over time and the additive stress effects of AE and PE, paint a coherent picture in which subjective loneliness and objective social isolation each play a significant role in shaping mental health outcomes and stress physiology in the simulated population.

Discussion

The present simulation, while simplified and warranting further empirical validation, aligns closely with evidence from human research and deepens our understanding of how social exclusion influences mental health. The result that both objective and perceived social exclusion independently worsen mental health dovetails with extensive empirical literature. Holt-Lunstad et al. (2015) reported that both living in social isolation (objective state) and feeling lonely (subjective state) similarly heightened the risk of earlier death, and they found “no differences” in the magnitude of effect between objective and subjective isolation. Our model reflects this parity, assigning roughly equal weight to each.

From a theoretical standpoint, this equivalence reinforces the importance of the perceived social world: it is not enough for one to have relationships; one must also feel connected. Loneliness researcher John Cacioppo and colleagues (2009) have long argued that perceived social isolation can trigger a cascade of cognitive and physiological processes that are detrimental. Lonely individuals often experience increased stress, more negative social expectations, and hyper-vigilance for social threats (e.g. interpreting ambiguous interactions as rejection). These factors can feed back into depression and anxiety, creating a vicious cycle of withdrawal and further isolation. In our simulation, this dynamic was hinted at by the especially low mental health of the group that was both isolated and lonely—once a person is in that state, objective lack of support and subjective negativity may reinforce each other.

Psychologically, the pain of exclusion can be understood through the lens of fundamental needs and evolutionary adaptiveness. Baumeister and Leary’s (1995) Belongingness Hypothesis posits that humans have an innate need to form and maintain strong interpersonal bonds. When this need is unmet, people suffer psychological and even physical ill effects. The immediate distress of being excluded, as seen in controlled experiments like the Cyberball virtual ball-toss game (Williams et al., 2000), is thought to serve as an “alarm system” (Eisenberger & Lieberman, 2004) signaling that one’s social connections are threatened. Neuroimaging evidence shows that this alarm has a biological basis: being ostracized activates the ACC, provoking a feeling akin to pain. At the same time, regulatory regions like the right ventral prefrontal cortex (RVPFC) may attempt to dampen this distress, as indicated by its inverse relationship with ACC activity during exclusion.

Not everyone reacts to exclusion in exactly the same way—some individuals (like the “Isolated, Not Lonely” group in our simulation) might be more resilient or find compensating cognitive frameworks (e.g., “I enjoy my solitude” or “I don’t need others’ approval”). Nonetheless, the broad trend is that being objectively excluded deprives individuals of social support, meaning less help in coping with stress and fewer positive interactions to boost mood, whereas being subjectively lonely deprives individuals of peace of mind, meaning more rumination and negativity even if support is available (Hawkley & Cacioppo, 2010). Over time, both pathways can converge to similar outcomes: heightened risk for depression, anxiety, and even cognitive decline or dementia in older age. It is telling that prolonged loneliness has been linked not only with mental health issues but also with physiological changes such as elevated inflammation and blood pressure, weakened immune function, and changes in gene expression related to stress response. These findings underscore that perceived social exclusion “gets under the skin” in very real ways.

From a sociological perspective, the harmful impact of social exclusion has been observed for over a century. Durkheim’s (1897) seminal analysis of suicide rates highlighted that individuals who lacked social integration were at greater risk of suicide, one of the earliest indications that social disconnection can be deadly. Modern population-based studies continue to show that communities with higher rates of loneliness and isolation suffer worse health outcomes overall (Holt-Lunstad et al., 2015). On the flip side, strong social support networks and a sense of belonging in one’s community are protective factors that buffer against stress and promote resilience. This underlines a key point: social exclusion is not just an individual psychological problem but a societal one. If large segments of the population feel disconnected or marginalized, the public health ramifications are considerable.

Social exclusion in the digital age

Our reflection would be incomplete without considering how social exclusion operates within digital and social media environments. As alluded to in the introduction, the rise of social media has introduced new paradoxes in social connection. People are technically more connected than ever—able to accumulate hundreds of “friends” or followers and to communicate instantly across distances. Yet researchers have found that heavy social media use is correlated with greater feelings of loneliness and social dissatisfaction (Primack et al., 2017). Part of this paradox stems from the nature of online social comparison and the performative pressures of social media. Users curate their content to show the best aspects of their lives, which can create an illusion that everyone else is happier, more popular, and more successful than oneself. Constant exposure to these idealized images and updates can lead to a sense of “everyone is doing better than me”, triggering feelings of exclusion (even if one is technically included in the online community).

As suggested above, this phenomenon has been encapsulated by FoMO, which directly frames the anxiety in terms of exclusion: one fears that one is “missing out” on meaningful experiences that others are enjoying. Studies on FoMO have concluded that it is fundamentally driven by unmet social needs and feelings of inadequacy in comparison to others (Gupta & Sharma, 2021). These authors describe how social media amplifies awareness of what others are doing “round the clock,” which can make individuals feel lonely and inadequate through highlighting others’ activities and popularity. The “continuous awareness” afforded by platforms like Instagram, Facebook, etc., means there is always something happening that one is not part of. For those vulnerable, this can evolve into obsessive checking and a spiral of negative emotion: seeing others’ joyful moments can lead to sadness or envy, which then leads to more compulsive use of social media to seek validation or inclusion, often resulting in further feelings of exclusion when that validation doesn’t come (or doesn’t satisfy for long).

Another aspect of social media-related exclusion is the quantification of social worth. Online, one’s value can feel numerically measured in likes, comments, shares, and follower counts. This introduces a performance aspect to social interaction: individuals may feel pressure to present a perfect image and garner positive feedback to “prove” they are included and appreciated. When their posts or profiles do not receive attention, it can feel like a form of rejection or invisibility. A teenager might feel excluded if their friends get more “likes” on photos than they do, or if they are not included in a group selfie posted from an event. In essence, social media can create a hyper-visible popularity contest that exacerbates insecurities. Over time, this might contribute to anxiety and depression. In line with this, experimental research has shown that limiting social media usage can actually decrease loneliness and depression, suggesting a causal role of these platforms in fostering isolation feelings (Hunt et al., 2018). Moreover, some longitudinal studies report a bidirectional relationship: loneliness can drive people to use social media more (seeking connection), but greater use, especially passive scrolling, ends up making them feel worse, not better (Choi et al., 2025).

It is important to note that social media is not universally harmful—indeed, it can also be a source of support and genuine connection for many. The difference often lies in how it is used and the mindset of the user. Actively engaging with close friends online (e.g., having supportive conversations) can reinforce feelings of inclusion, whereas passively consuming content or chasing approval from a large audience can erode self-worth. Our earlier findings on real vs. perceived exclusion offer a useful lens: someone might have hundreds of online contacts (low objective isolation in the digital sense) but still perceive themselves as excluded if those interactions lack depth or induce envy. In contrast, an individual with a modest online presence but a focused group of truly supportive friends (even if just a few) may feel more socially fulfilled. The quality of connections thus matters more than the quantity, both offline and online.

Policy and societal implications

Recognizing social exclusion as a significant factor in mental health suggests several avenues for societal action. At a broad level, there is growing advocacy to treat loneliness and social isolation as public health priorities (U.S. Department of Health and Human Services, Office of the Surgeon General, 2023). Governments and communities could invest in programs that foster social connection, such as community centers, group activities, or outreach to isolated individuals (for example, the elderly living alone). Healthcare providers are increasingly encouraged to screen for social disconnection as part of routine health assessments, given its impact on health comparable to smoking or obesity. On the psychological intervention front, therapies for depression and anxiety could place greater emphasis on addressing loneliness—helping clients build social skills, reconnect with others, or reframe their social perceptions and standards to feel less excluded. There is also a role for public education: raising awareness that perceived isolation is not trivial but a real threat to health can reduce stigma and encourage people to seek help or reach out to lonely peers.

Regarding social media, a light-touch implication is to promote digital literacy and healthier online habits. Users (especially younger ones) can be taught about the curated nature of social media content, so they are less likely to compare themselves to unrealistic standards. Campaigns that encourage taking breaks from social media or limiting passive use have shown promise in reducing loneliness. Some experts suggest design changes in platforms to emphasize meaningful interactions over popularity metrics—for instance, downplaying public like counts or prompting users to engage in private messaging with friends after a certain scrolling time. While we cannot expect corporations alone to solve these issues, society can create demand for platforms that prioritize well-being. Additionally, online communities can be harnessed in positive ways: support groups, interest-based clubs, and moderated forums can give people a sense of belonging and acceptance, mitigating feelings of exclusion.

Finally, it’s worth noting the importance of inclusivity in our broader social fabric. Social exclusion can also occur due to stigma or prejudice (based on race, gender identity, mental illness, material possessions, appearances, etc.), wherein individuals are made to feel they “don’t belong” in society. Such exclusion has compounding negative effects on mental health. Efforts to promote inclusive school climates, workplace diversity and belonging initiatives, and anti-discrimination policies all contribute to reducing systemic forms of social exclusion. In doing so, they likely improve community mental health. In essence, a society that consciously values connection and inclusion may buffer its members against many of the deleterious effects discussed in this paper.

Conclusion

Social exclusion, whether it takes the form of literal isolation or the internal feeling of being left out, is a powerful determinant of mental health. Through a combination of simulation and theoretical exploration, we have illustrated that both real and perceived exclusion matter—each can independently degrade well-being, and together they can exact an even greater toll. The findings resonate with a broad scientific consensus that humans thrive on social connection and suffer in its absence. In modern life, we must contend not only with traditional modes of exclusion but also with new, subtle forms of digital-age exclusion where one can be surrounded by online “friends” and yet feel utterly alone.

The convergence of evidence from psychology, neuroscience, and public health paints a sobering picture: chronic social disconnection is as detrimental to our minds and bodies as major biomedical illnesses, and it should be treated with similar urgency. Yet, there is a hopeful side to this narrative. Just as negative states of exclusion feed forward into ill health, positive efforts to increase inclusion can heal. Interventions, big and small—from community gatherings to simply reaching out to someone who might be lonely—can help fulfill the basic human need for belonging. In the end, the antidote to the pain of social exclusion is the warmth of social inclusion. Cultivating a society that prioritizes relationships, empathy, and understanding is not a lofty ideal but a practical strategy to enhance mental health on a large scale. As we move forward, acknowledging the dual importance of objective and subjective social connection will be key to building not only more connected individuals, but also more resilient and healthy communities.

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